+ All Categories
Home > Documents > pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of...

pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of...

Date post: 31-Mar-2018
Category:
Upload: vudang
View: 214 times
Download: 2 times
Share this document with a friend
132
SOME APPROACHES TO THE DEVELOPMENT OF A FRAMEWORK OF INDICATORS TO MONITOR FINANCIAL STABILITY IN DEVELOPING COUNTIRES ON THE EXAMPLE OF RUSSIAN FEDERATION MASTER THESIS M.Sc. in Finance and International Business Author: Anna Sereda Exam #: 277646 Academic Advisor: Philipp J.H. Schröder
Transcript
Page 1: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

SOME APPROACHES TO THE DEVELOPMENT OF A FRAMEWORK OF INDICATORS TO MONITOR FINANCIAL STABILITY IN

DEVELOPING COUNTIRES

ON THE EXAMPLE OF RUSSIAN FEDERATION

MASTER THESIS

M.Sc. in Finance and International Business

Author: Anna Sereda

Exam #: 277646

Academic Advisor: Philipp J.H. Schröder

September, 2009

Page 2: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

Contents: Page:

Introduction (3)

1. Scientific background of the problem, description of the financial stability (5)

1.1. Banking crises (8)

1.1.1. Theoretical models of banking crisis (8)

1.1.2. Empirical analysis of banking crisis (10)

1.2. Currency crises (15)

1.2.1. Theoretical models of banking crisis (15)

1.2.2. Empirical analysis of banking crisis (25)

2. Main approaches to the development of a framework of indicators monitoring financial

stability (27)

2.1. Qualitative analysis (27)

2.2. Econometric evaluation (35)

2.3. Nonparametric analysis (42)

3. Development of a framework of indicators monitoring financial stability (47)

3.1. Signaling approach (49)

3.2. Analysis of operational capacity of the potential signaling indicators based on the

example of Russian Federation in 1994-2009 (57)

3.3. Composition of financial stability indexes (60)

4. Monitoring the financial stability in Russia 2009 (II quarter) (65)

4.1. Russian Federation (I quarter 2008 – II quarter 2009) (67)

Conclusions (69)

Literature (71)

Appendix 1-8

2

Page 3: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

Introduction

Not even the highly developed countries are fully secured from the risks and threats of the

financial system instability. Transitional and developing economies are especially open and

vulnerable to these risks, because while their markets are open, the mechanisms which buffer the

negative impact of the fundamental factors of financial instability are not yet formed. During the

past three decades, the world faced many bouts of financial instability within individual

countries, which sometimes spread world-wide. Recent examples include the sharp price

movements in U.S. equity markets in 1987 (“black Monday”) and 1997; bond market turbulence

in the G-10 countries in 1994 and in the United States in 1996; currency crises in Mexico (1994–

95), Asia (1997), Russia (1998); the collapse of the hedge fund Long-Term Capital Management

in 1998; the currency swings of the 1990s; volatility of global equity markets in 2000 and 2001,

and present full scale world economic crisis are no exceptions to this rule.

Defining episodes of financial instability is a complicated task. In particular, it is logical

to consider bankruptcy of a few financial institutions as a financial instability. During certain

economic conditions it could be just a part of the regular market process, when unprofitable and

ineffective entities leave the competition. At the same time, bankruptcy of one financial

institution can become a trigger to the financial crisis. Thus, in my work financial instability is

defined as problems in the financial system of the country which cause significant negative

influence on the economic activity.

Previous scientific research has shown that periods of financial instability prior to

financial crises may have common features. The significant losses that economies face as a result

of the financial crises led to the creation of empirical models that allow recognition of symptoms

prior to the critical point to give policymakers time to neutralize the negative consequences.

Monitoring of the present condition of the financial system based on a series of indicators

analyzed on a regular basis is also important. This fact was realized after significant direct

(recapitalization of the banking system) and indirect (recession) costs of the financial crises

occurred in different regions around the globe in 1990-s.

Sources of financial instability vary. Among them is a mismanagement of assets, scarcity

3

Page 4: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

of capital in financial institutions, bank runs, etc. When financial instability increases even

insignificant misbalances in economy may lead to the development of the financial crisis

with very negative consequences for the economy.

In my research I made an attempt to examine possible qualitative, quantitative and non-

parametric characteristics of the present condition of the financial system of Russian Federation.

Analysis of indicators cannot be a strictly formalized procedure because the threshold levels

signaling about decrease/increase of the probability of financial instability are relatively

provisional and depend on the certain economic conditions. It is always necessary to analyze the

present economic situation and in the relation to that correct conclusions drawn on the basis of the

formal analysis.

The first part of the research defines the relations between particular variables of the

financial stability and examines the scientific expertise. Two of the most common types of crises

are examined in detail – banking and currency crises. Banking crisis is usually related with an

inability of some banks to carry out their liabilities or with the active government interference

focused on the prevention of the occurring problems. Currency crisis is the situation when

speculative attack on the national currency leads to the sharp devaluation which government tries

to prevent by engaging gold and foreign currency reserves or by a significant raise of the interest

rates.

Notably in the modern history the Russia faced different types of financial crises and

experienced to its fullest their negative consequences. Thus, financial instability by definition is

dangerous and undesirable for sustaining gradual and successful economic development, and

development of the methodology to identify these crises in their early in its early identification is

an important and relevant subject.

On the basis of conclusions drawn from the first part of work an attempt was made to

establish a framework of indicators to monitor financial stability and separate methodological

matters related to it are examined in the second part of the research. Finally, the working

capacity of the offered framework is tested on the example of the developing market of the

Russian Federation.

While the application of the offered methodology does not necessarily allow forecasting

with absolute certainty an approaching financial crisis, a framework of signaling indicators with

a certain degree of reliability allows identifying negative tendencies in the economy in advance

4

Page 5: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

and gives an opportunity to neutralize them. Moreover, I will show that methodology of defining

threshold levels means maximization of the prognostic power of the indicators.

CHAPTER 1

Scientific background of the problem, description of the financial stability and its main

components.

Through the past decades many researchers have attempted to determine a set of indicators

to examine of current tendencies in the development of the financial system. Early surveys

stressed the analysis of the fundamental economic indicators, while modern surveys identify the

investor’s expectation as having the most the important role in forecasting of financial crises.

Classic interpretation of the financial instability was given by Irving Fisher (Fisher,

1933). He asserts that financial instability is strongly correlated with the macroeconomic

cycles; in particular, with the dynamics of total debt in economy. Problems, related to the over

accumulation of the total debt in the real sector, lead to a situation where it is necessary to

discharge debt in order to restore the equilibrium to the economy. This discharge of debt results

in a decrease of deposits and a divestiture of assets at a low price. This in turn leads towards a

recession with a drop in the rate of price increases and output, as well as an increase in

unemployment and the number of bankruptcies. Thus, according to Fisher, the main cause of the

financial instability is the negative dynamics of the fundamental indexes.

In their work, Diamond and Dybvig (Diamond, Dybvig, 1983) relate causes of the

financial instability with factors which influence behavior of the banks depositors. They

propose the possibility when the economy transitions from the state of the ‘good’ equilibrium to

the ‘bad’ it can be accompanied by a bank panic. Diamond and Dybvig believe that economic

agents making bank deposits during this period provide some stability of the financial system

and in case of some negative events the probability of bank panic increases. They identify that

the investor’s confidence is an important factor of the financial system stability.

Mishkin (Mishkin, 1996) examines the role and influence of the asymmetrical

information on the development of the financial system . He asserts that information

asymmetry between creditors and borrowers leads to the creation of the adverse selection. In

other words, borrowers often possess more information about the characteristics of investment

projects in which they intend to invest. Creditors, with incomplete information, are forced to

5

Page 6: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

hedge against risks of uncertainty by lending money under average rate of interest between risk

and zero risk investments. As a result, borrowers needing money for financing high-yield projects

with low risk degree are forced to pay higher interest than they would pay in case of informational

transparency. At the same time, borrowers who finance high risk projects have an opportunity to

obtain loans with lower interest rate. All that leads to displacement of ‘good’ investment projects

with ‘bad’ and therefore to the drop in quality of portfolios of financial intermediaries.

From the point of view of both creditors and borrowers, Guttentag and Herring

(Guttentag, Herring, 1984) discuss the possibility of occurrence of difference in the expected

return on the project in case of uncertainty on the future return on the investments. For example,

if the expected return on the project for the creditor is lower than return on the alternative project,

the borrower’s loan may be rejected. Guttentag and Herring state that the growth of the financial

instability increases the number of rejections on the loans as well and in its turn this leads to the

instability in the real sector, invoking a new cycle of financial crisis. Deposit insurance is

noted as a possible solution of the problem. However, Keeley (Keeley, 1990) says that deposit

insurance may be related to the problem of moral hazard, and as result financial intermediaries

will face higher risks than in case of not using deposit insurance. The case is that they can

receive money at a risk-free rate (on insured deposits rate) and invest them in high risk projects.

It also can increase sensitivity and vulnerability of the financial system to possible shocks.

Some studies show that asymmetrical information on the financial markets might be the

source of contagion effect. In the conditions of mutual interdependence between financial

markets of different countries, the negative external shocks might be passed to the wealthy

economies from the others. Kodres and Pritsker (Kodres, Pritsker, 1998) specifically develop a

theoretical model which includes factors affecting the contagion effect, where contagion depends

on the level of information asymmetry. They also demonstrate that even if the mechanisms of

risk hedging exist, the contagion still might happen without influence of negative microeconomic

shocks. That is possible when investors decide to lower risks and offshore financial means out of

the country. In fact, a similar situation took place in Asian countries before the crisis in 1997.

According to Davis (Davis, 1996) institutional investors often face the agent-principal

problem and it might be one of the facilitators of the financial instability. The case asserts that

the goal of fund managers might not be client’s profit maximization. As a result, the asset price

fluctuations on the market may significantly increase, thereby increasing the probability of

6

Page 7: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

financial instability. To solve this problem the authors suggest monitoring closely top

management activities and apply various evaluation systems to monitor quality of management

performance. In this case, managers will tend to behave like other players on the market and

avoid non-reliance. Following after, other investors will allow top managers to maintain their

reputation on the good level because the risk of achieving results lower than average will

significantly decrease.

Many researches published during the period of Mexican crisis in 1994 and Asian crisis

in 1997 examined the fragility of financial institutions in relation to exogenous shocks. Authors

pay attention to such factors of financial instability as depreciation of the national currency,

decline of the rate of economic growth, deterioration of the balance of payments, high inflation

rates, deterioration in the terms of trade, speculative attacks on the stock market, and production

loss in the export sectors. Additionally, such quality factors of instability like insufficient

supervision over the banking system, inadequate fiscal and monetary policy, imperfect

legislation, accounting standards and others are being analyzed.

There is a significant amount of research, the main purpose of which was the detailed

analysis of contagion effect (Baig and Goldfajn, 1999; Fratzscher, 1998). Factors initiating the

contagion included a high correlation between exchange market and stock market, close inter-

country banking and external trade relations, low level of gold and foreign currency reserves, as

well as overall weakness of the financial system. Besides that, Kaminsky and Reinhart

(Kaminsky, Reinhart, 2000) shows that additional risk factor for occurrence of contagion is

the existence of common creditor with the country already experiencing financial crisis.

Considering that financial and exchange crises often accompany each other , factors

that are used to forecast the exchange crises, might be used as well as the financial crisis

indicators. Thus, correlation between financial and exchange crises was found in the research of

Dornbush, Goldfajn and Valdes (Dornbusch, Goldfajn, Valdes, 1995), Kaminsky and Reinhart

(Kaminsky, Reinhart, 1999), also Kaminsky, Lizondo and Reinhart (Kaminsky, Lizondo,

Reinhart, 1998). Findings show that exchange crisis leads to the financial crisis if the influence of

devaluation on the quality of bank assets is so significant that it decreases significantly net bank

asset value.

Thus, I reviewed scientific researches on the influence of the macroeconomic indicators

on the stability of the financial system. However, aggregated microeconomic indicators play no

7

Page 8: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

lesser role in the development of a framework of indicators monitoring financial stability. Their

usage in empirical researches is only limited with data accessibility. Thus, in the classic work of

Altman (Altman, 1968) qualitative indicators, such as asset quality, profitability and liquidity are

examined. However, in this case analysis was applied to the individual companies. Later, other

research was conducted which used aggregated microeconomic indicators for the monitoring of

financial stability. Specifically in the works of Frankel, Rose and Honohan (Frankel, Rose,

1996; Honohan, 1997) the importance of such indicators as short-term liabilities in foreign

currencies is noted. Gonzales-Hermosillo, Pazarbasioglu, and Billings (Gonzalez-Hermosillo,

Pazarbasioglu, Billings, 1997) produce testimony to their statement that essential role in

forecasting financial crisis play such factors as non operating loans and capital adequacy.

In the framework of indicators monitoring financial instability are often included such

factors as interbank rate, relation of deposits volume to money quantity, stock market index and

others. Notably, Kaminsky, Lizondo and Reinhart came to conclusion that aggregated

microeconomic indicators are better to use for forecast of currency crises than banking ones.

Thus, I reviewed the main scientific studies that examine factors used by researchers as

indicators of financial instability. Now I will examine in detail the banking crises, because

historically they were the type of financial crisis most often to occur.

1.1. Banking crisis

Theoretical models of banking crises

Specific character of the activities of commercial banks does not allow a full explanation

of their behavior on the basis of standard microeconomic models. Developed theoretical models

and industry analysis of the banking sphere show that while conducting behavioral research of

commercial banks, the problems of asymmetrical information become increasingly important.

These include the relations between “bank – borrower”, “bank – depositor” and credit rationing.

The absence of explicit effects of scale in banking service offers and the specifics of price

competition between commercial banks, creates a limit in the possible application of standard

8

Page 9: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

models in industry analysis. Concurrently, the number of unique market and commercial risks

inherent only to the banking sphere are not discussed in the theory of the firm. Thus, in relation

to the problem of sustainability in a banking firm, the possibility of bankruptcy is one of the

most important aspects of the activity analysis of the commercial banks 1.

The concept of exposure (vulnerability) of the national banking system was first

introduced in 1977 by Minsky (Minsky, 1977). Traditionally, banking crises are divided into two

main types: bank runs, which spread to a few separate banks including the largest national bank

institutions; and bank panics, when crisis developments spread not only to the entire banking

system but also into the system of national accounts and balances2. The model of Diamond-

Dybving (Diamond, Dybvig, 1983) is considered to be a fundamental model of the banking crisis,

which develops in consequence of liquidity problems of a separate commercial bank.

This model describes behavior of the commercial bank and its depositors in the

conditions of uncertainty. It is assumed that the bank is attracting deposits which are able to be

withdrawn on demand only and depositors can withdraw their money at any time. Thus, there is

a risk of the possibility that the situation will arise when all depositors would like to withdraw

their money at the same moment of time3. The model allows us to draw three main conclusions:

1. Banks with attracted demand deposits may stabilize their position on the competitive

market by sharing risk of deposits withdrawal by depositors, who have different

intertemporal preferences.

2. Even though an increase in the amount of demand deposits in liabilities helps to coinsure

risks of premature deposits withdrawal, it might also lead to undesirable equilibrium,

when all depositors surrender to panic and desire to withdraw their deposits.

3. “Bank runs” have serious economic consequences because even “healthy” banks might

experience problems after premature deposits withdrawal forcing a stop-down of

investment projects.

As a possible solution to the problem of premature deposit withdrawal the authors

suggest a system of state insurance of the bank deposits, which will ensure the “good”

1 Detailed review of microeconomic models describing behavior of the banking organization, also models of industrial organizations in the banking sectors was presented in (Freixas, Rochet, 1997).2 It is necessary to note that bank panic is often a consequence of the bank runs, if the government actions on bailing out and support of problematic banks were not sufficient enough.3 In fact, to experience problems with liquidity, it is not necessary that all depositors address the bank simultaneously. Because bank assets have different time structure and liquidity, it is enough if the amount of claims that are higher of the liquid assets of the bank.

9

Page 10: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

equilibrium; besides its positive effect, such a system has its negative sides as well: state

insurance might lead to the increase of the financing of the highly risky projects, and therefore

will increase the possibility of the bank crisis.

Further developments of models of “bank panic” and “bank run” are based on the

different modifications of the Diamond-Dybving model: Chari and Jagannathan (Chari,

Jagannathan, 1988) present a situation when “bank panic” starts as result of

misinterpretation of the real situation by a large number of the depositors; Temzelides

(Temzelides, 1997) shows that “good” equilibrium can be obtained in the case of even few

banks, though the possibility of bank panic increases in proportion of increase of the average size

of the bank. Chen (Chen, 1999) studied the influence of the contagion effect on the

development of the banking crisis and transformation of “bank run” on the separate banks into

overall “banking panic”.

Additional focus was placed on the studies of the bank crises from a macro level.

Mishkin, Edwards and Vegh (Mishkin, 1996; Edwards, Vegh, 1997) view problems of separate

banks in the context of the development of the financial crisis. Mishkin specifically pays

attention to the problem of asymmetrical information, its role in the development of crisis

throughout the banking system, and on financial and real sectors of the economy. Edwards and

Vegh show that shock changes of macroeconomic conditions in situations of a predetermined

exchange rate of the national currency might cause the crisis in the banking sphere. This in

turn empowers crisis developments in other sectors of economy.

For the analysis of the crisis developments in Japan in 1990’s, Hayashi and Prescott

(Hayashi, Prescott, 2002) use the model of the real business cycle and came to the conclusion

that limitations on credit accommodations did not result in a decrease of investment activity.

With the help of the model of overlapping generations, Barseghyan (Barseghyan, 2004)

studied the government’s role of curing banks during financial crisis and came to the conclusion:

if the government is too slow with curing and rehabilitation procedures, then banks start the

Ponzi game. In other words, take new loans to refinance old ones, which in case of financial

crisis will only worsen the situation.

Empirical analysis of banking crises

10

Page 11: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

There is a significant amount of scientific research containing empirical analysis of the

crises of national banking systems and bankruptcies of separate banks. Most of them were

prepared by large international financial organizations (World Bank, International Monetary

Fund) which traditionally develop advisory notice and practical measures focused on negotiation

of crisis developments in the banking sphere.

During the past decades, many of developing and emerging economies faced such

banking crises including, Mexico, Argentina, Thailand, Korea, and Russia. These events were

incredibly destructive not only to the banking sector but to the entire national economy as a

whole. It highlighted the necessity of timely forecasting of the crisis developments so that

necessary measures to prevent them would take place and be effective.

There are also a significant number of scientific researches into the economic literature

that studies the mechanisms launching the crisis. Most of the research focused on the monitoring

of financial stability is possible to divide in two main groups, depending on the approach used.

Group one uses “signaling approach” which consists of an observation of indicators

during the “calm” period, the period before the crisis and during the crisis. Then on the base

such analysis a conclusion is drawn about the usefulness and applicability of the certain

indicators for the monitoring financial stability. Significant changes in the dynamics of the

particular indicator before the crisis speak about its applicability for the effective monitoring.

Group two researchers use the evaluation of econometric models, where as the

endogenous variable used binary variable that is equal to 1 during the crisis or before it. In such

models regressors are different variables used as indicators of financial instability .

Eichengreen and Rose (Eichengreen, Rose,1998) outlined five main reasons of the crisis

in the banking system. They are: internal macroeconomic policy; external macroeconomic

conditions; exchange rate fluctuations; financial structure of the country; and problems of control

and regulation. They also examined nine groups of variables:

Variables responsible for the world interaction: volume of international gold and foreign

exchange reserves (in % from imports volume of the country in a month in monetary

terms), foreign debt (in % GDP), current account balance of the current account

transactions (in % GDP) and real exchange rate;

Key macroeconomic indicators responsible for the fiscal and monetary policy and economic

dynamics: budgetary deficit/surplus (in % GDP), growth rate of the domestic credit and

11

Page 12: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

growth rate of GDP per capita in real terms;

External variables: growth rate of GDP in real terms in the countries of OECD and world

exchange rate (that is weighted average interest rate of the USA, Germany, Japan,

France, Great Britain, and Switzerland interest rates; weights were taken proportionally

to the share in the foreign debt of the examined country, for each of the noted countries).

Results and outcomes of their research:

a) World interest rate starts to rise approximately 2 years before the crisis and

reaches its highest point either a year before the crisis or in the year of crisis. GDP

growth ratio in real terms drops during the years preceding the crisis, though not

as much as interest rates.

b) Other external variables do not have an significant influence.

c) Such indicators as credit boom and growth of budget deficit cannot be

considered as signaling indicators of banking crisis because their occurrence

does not justify about high possibility of crisis any time soon.

Demirguc-Kunt and Detragiache (Demirguc-Kunt, Detragiache, 1998) also analyzed

variables which could serve as signaling indicators. Given observations were based on the

sample of 31 cases of banking crises from 1980 to 1994 with the usage of logit models. The

authors show that a low growth ratio of the economy, high inflation and high real interest rates

are factors that evidence about rise of possible problems in the banking sector. At the same time,

high growth ration on credits and unfavorable shocks of trade conditions effects low on the

possibility of crisis on banking market. With that the rate of change of the exchange rate and

volume of budget deficit probably do not have significant influence on the possibility of crisis-

producing situation in the banking sectorа. There is an interesting finding concerning the

existence of the deposit insurance system. With introduction of the deposit insurance system in

the country, banks involved in the system start to take higher risks which lead to the elevation of

risks in the banking system overall and logically leads to the increase of possibility of crisis.

A slightly different approach to identify signaling indicators is used by Hardy and

Pazarbasiogly (Hardy, Pazarbasioglu, 1998). A main variable characterizing the start of banking

crisis, they used a fictitious variable which takes on three values: 2 – during the period of

difficulties in the banking sector, 1 – during preceding period, and 0 – in all other cases.

Authors use the following arguments for defining preceding period before crisis into a separate

12

Page 13: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

category: first, with such separation it becomes possible to determine predictive capability of

signaling indicators without information that is only becomes available during the crisis

period; secondly, behavior of many economic variables might significantly differ during the

crisis and period before it.

In the sample for the analysis 50 countries were included, 38 of them experienced 43

banking crises varying in severity. In the sample were not included countries which experienced

hyperinflation during the examined period and former socialistic countries with transitional

economies.

Possible indicators of banking crisis were divided in three main groups: variables of the

real sector; variables of banking sector, and shocks that influence the situation in the banking

sector.

Besides the noted variables, also taken into account was whether a country belonged to

a particular region and the existence of multiple economic crises in the country.

Empirical test gave following results:

a) Banking crises start simultaneously with the significant decrease of GDP growth ratio

in real terms, sharp rise of consumption alarms about possible crisis in the short run.

b) Sharp drop of banking deposits in the real terms and significant increase of loans

issued to the private sector signals about crisis in short run. Considerable increase of

aggregated foreign liabilities of the country (in % GDP) may also be a signaling

indicator though its predictive value is lower than in mentioned higher indicators.

c) First to point on the possibility of crisis is sharp falls of inflation with its following

growth. Real interest rates usually rise in the period preceding the crisis and keep

growing during the crisis. Growth of real effective exchange rates, a sharp drop of

growth ratio on import in real terms also testifies about upcoming banking crisis.

d) In the countries already experienced in crisis the possibility of its repetition is higher

than in the countries which have never experienced banking crisis.

Caprio and Klingebiel (Caprio, Klingebiel, 1996b) came to the conclusion that a poorly

developed financial market does not protect a country from the external shocks.

Kaminsky (Kaminsky, Reinhart, 1998) study predictive validity of different signaling

indicators. According to their findings the best signaling indicators for forecasting crisis in

banking sphere are from:

13

Page 14: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

variables characterizing fiscal and monetary policy: relation of M2 to the monetary base and

relation of domestic credit to GDP;

variables of current account: export and real exchange course;

variables characterizing capital markets: difference between real exchange rates (foreign

and domestic), world interest rate, debt to the banks and deposits dynamics;

variables characterizing the real sector of economy – dynamics of industrial production,

internal interest rate in real terms and changes in share indexes.

Bell and Pain (Bell, Pain, 2000) conducted a brief survey of some previous research on

the matter. Based on these, they draw a conclusion that a banking crisis is usually preceded by

following events: expansion of interest rates in real terms, low growth ratio of output, rapid

growth of domestic credit and drop of volume of external trade and real exchange rate.

Continuing their previous work (Demirguc-Kunt, Detragiache, 1998), Demirguc-Kunt

and Detragiache conducted an analysis of indicators of banking crises by using newer time-series

data and more countries in the series, in comparison with the previous work. They identified the

following results: low rate of growth of GDP, high inflation and high real interest rates result in

the high probability of the coming banking crisis. Among variables of banking sector, two of

them increase the probability of banking crisis: increase of ration of monetary base to gold and

foreign currency reserves and volume of loans to the private sector. Besides that, authors

showed that low level of GDP per capita and existence of deposit insurance system increases

the possibility of banking crisis in the country.

Besides that, Demirguc-Kunt and Detragiache systemize possible causes of problems in

banking sector: 1) degree of separate bank expose and systematic banking crises; 2) financial

liberalization and crises; 3) international shocks, regimes of exchange rates and crises; 4)

structure of bank owners and crises; 5) role of institutions, 6) political system and crises.

In their work Peresetsky, Karminsky and Golovan (Peresetsky, Karminsky, Golovan,

2004) actually show that with the help of the signaling indicators it is possible to predict

problems in the banking system of the country.

Thus, I reviewed main scientific surveys devoted to the signaling indicator analysis

forecasting banking crisis. Putting them together, we can define following key figures, which

signal about increase of possibility of banking crisis in the best way:

Economic growth ratio: GDP growth ratio of in real terms, dynamics of industrial

14

Page 15: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

production.

Balance of payments: eeal effective exchange rate, real exchange rate, import and export.

Interest rates: real exchange rate, difference between world and domestic interest rates

in real terms

Monetary indicators: inflation, GDP deflator, monetary multiplier.

National income account: consumption.

Banking sector: bank deposits in real terms (in relation to GDP); loans to the private

sector in real terms, aggregated foreign liabilities in relation to GDP.

1.2. Currency crisis

Theoretical approaches

There are three generations of models of currency crises in the economic literature. In the

first generation models, all variables are determined and the depletion of gold and foreign

exchange reserves is considered to be the main cause of currency crises. In the second generation

models, uncertainty plays the most important role; in other words, economic policy is not

predetermined but instead depends on the current state of the economy and economic conditions.

Finally, the third generation models pay close attention to the contagion effect.

Discussion on the matter of balance of payment crisis exploded after Paul Krugman’s

work (Krugman, 1979). Analogical models become models of the first generation. In his work,

Krugman expresses his hypothesis that the main cause of currency crises is the economic policy,

specifically the inconsistence between effective intervention of fixed exchange rate and

stimulating (fiscal or monetary policy) internal economic policy (monetary expansion).

Krugman describes the situation in which domestic credit growth along with a fixed exchange

rate leads to a reduction of international reserves and, as result, to the boost of speculative

activities with the currency. These activities momentarily exhausted reserves and forced the

government to abandon the policy of fixed rate. Thus, the period before crisis might

accompany a gradual decrease of foreign reserves, budget deficit (fiscal expansion) and a sharp

15

Page 16: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

increase in the number of loans to the governmental and private sector (monetary expansion).

A core model of currency crisis of the first generation is the model of a medium country

where conditions of purchasing power parity and interest rate parity are fulfilled. It is assumed in

the model that economic agents are perfectly anticipated and that domestic assets are available

on the world market and are perfect substitutes to the external assets. While the amount of

international reserves exceeds some minimally accepted value, the central bank controls part of

international reserves to support the fixed exchange rate. When the support of fixed exchange

rate is abandoned due to the speculative attack and reserves drop below minimally accepted

value, the transition to a floating exchange rate takes place. Foreign currencies inside of the

country are not adopted, and all goods are traded on the world market. Thus, the model consists

of five equations:

Demand equation on money supply:

mD−p=a0+a1 y−a2 i , (1)

where, mD – is the logarithm of monetary base, p – is the logarithm of price index inside of the

country; y – real gross national product; i – return on assets in national currency (demand on real

cash balances is due to transactional component and costs of carrying cash).

Equation of purchasing power parity:

p = p* + s, (2)

where, p* - is the logarithm of external prices index; s – is the logarithm of exchange rate. In the

conditions when all goods are traded and fixed exchange rate is supported, internal prices fully

depend on external prices.

Equation of interest rate parity:

i=i¿+E s (3)

where, i* - is external interest rate; Es – expected rate of change of the logarithm of foreign

exchange rate (expected value of derivative of the logarithm of foreign exchange rate in time).

Yield of domestic assets takes in account expected rate of change of the exchange rate of the

national currency. In the conditions of perfect information with the effective intervention of

fixed exchange rate, the expected rate of change of the exchange rare equals zero and domestic

interest rate equals to external interest rate.

Equation of money supply:

16

Page 17: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

M S = RS + D, (4)

where, MS – monetary base; R – national central bank’s reserves in foreign currency; S –

nominal exchange rate (s=log(S)); D – domestic credit (respective balance sheet accounts of the

central bank).

Balance one the money market:

M D = M S, (5)

where, M D = exp mD.

If one assumes that domestic credit rises with the constant rate µ, then the reserves of the

national central bank will decrease. Let us suppose that after the speculative attack, the central

bank exhausted its own international reserves and on the floating exchange rate wins over the

exchange market. This value of the exchange rate is called the shadow or equilibrium exchange

rate for the fixed exchange rate at a current time.

The model shows that shadow exchange rate increases along with the growth of

domestic credit, and that allows the calculation of the moment of devaluation. In the conditions

of perfect information, there cannot be a plummeting of exchange rates (the condition of

arbitrage absence), and that means that speculative attack with the following devaluation will

take place exactly in the moment of time when the shadow exchange rate is equal to the set

value, allowing us to calculate the moment of devaluation.

The model shows that if in the case of future policy for the central bank and government

is certain, devaluation will have three stages: gradual decline of the reserves, rough attack and

post-crisis period during which the exchange rate will not be fixed on the same level. If agents

foresee that attack on reserves might lead to devaluation and abolishment of the fixed exchange

rate, they will act to lower the level of reserves to the minimal level, thus denying for the central

bank an opportunity to protect overvalued currency.

In the real situation, policies of the government and central bank could not be known

for sure, and that is why the assumption about perfect information is not correct . For the

analysis of the currency crisis under uncertainty, stochastic variables are added in the model

described above. There are two ways of inserting such variables in the model: 1) it is unknown in

advance level of the international reserves; if reserves drop lower than this level, then the central

bank gives up the support of the fixed exchange rate and devaluation of the national currency

happens; 2) is the uncertainty in the dynamics of the domestic credit.

17

Page 18: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

Uncertainty of the reserve’s volume which the central bank will use for the national

currency protections is introduced in Krugman’s article (Krugman, 1979). The main result of the

model is a finding that speculative behavior is relatively sensitive to the specification of the

process, which sets minimally allowed variables for the central bank volume of international

reserves. If this level is random, then devaluation starts as the result of continuing during

certain amount of time speculative attacks. If the volume of minimal allowed reserves is fixed

and unknown to the currency profiteers, then like in the classic model, devaluations starts as the

result of the sudden speculative attack (Willman, 1989).

Uncertainty in the dynamics of the domestic credit was first introduced in the article of

Flood and Garber (Flood, Garber, 1984), in the stochastic model in discrete time. If to add

stochastic shock (on which the shadow exchange rate depends) to the constant rate of increase of

the domestic credit, then the shadow exchange rate will be a stochastic variable, that means it is

possible to evaluate the possibility of devaluation as the possibility of the shadow exchange rate

will exceed value set by the central bank in the next period:

π t+1=Pr (~s t+1> s ) (6)

where, πt+1 – possibility of devaluation in the next time period; ~s t+1 – shadow exchange rate in

the next period; s – set by the central bank value of the exchange course. While making a

decision on the speculative attack, economic agents look up to expected value of the exchange

rate which reflects expected profit as the result of the attack:

Est +1=(1−π t+1 ) s+π t +1~s t+1 (7)

where, Est +1 – expected profit of the profiteer in the next period; πt+1 – possibility of devaluation

during the next period; ~s t+1 – shadow exchange rate in the next period; s – set up by the

central bank value of the exchange rate. Extensions of the crisis models for the slow price

adjustments and the case when domestic and external assets are not perfect substitutes, are

presented by in some research (for example, Flood, Hodrick, 1986; Willman, 1988). The easiest

method of adding of slow price adjustments into the model is the substitution of the equation

of price parity on dynamic equation for process in the form offered by Dornbusch

(Dornbusch, 1976; Dornbusch, 1987):

pt=λ⋅[δ (st− pt )−ψ⋅( it−pt )− y ] , (8)

18

Page 19: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

where, ƛ – is the speed of price adjustments in relation to the excessive demand; st – is the

logarithm of the exchange rate; pt – logarithm of the price index; it – logarithm of the interest

rate; y – aggregated demand, which negatively depends on the real interest rate and real

exchange rate.

Further, solving system for the floating exchange rate, we find path of the shadow

exchange rate, which allows us to calculate similarly the moment of devaluation. The model

shows that the faster the prices change, the faster the currency crisis starts (δT / δλ<0 ) . If the

price change is momentary, then they remain constant during the period of the support of the

fixed exchange rate and change by jump during the devaluation. If the prices adjust slowly and

an expectation of devaluation takes place, then internal prices will change gradually from the

moment of expectations occur and to the moment of devaluation will achieve its new value. The

slower prices change, the more time is needed to achieve a new value and accordingly the

expected time before devaluation is larger.

The other method of weakening the purchasing power parity is the separation of the

goods on traded and non-traded, which is offered by Goldberg (Goldberg, 1988; Goldberg,

1994). Traded goods satisfy the parity prices equation, and with the fixed exchange rate good’s

prices change along with the external prices. Prices on the non-traded goods which do not enter

the world market include systematic and random deviations from the parity:

Pt /S t=Pt¿+ ρt+Ωt , (9)

here, Pt – domestic index on non-traded goods; St – nominal exchange rate; Pt¿

– external

prices index; ρt – systematic price deviations from the purchasing power parity; Ωt – random

shocks. Accordingly, aggregated price index is a weighted sum of price indexes on traded and

non-traded goods.

Besides that, the model separates random fluctuations of the domestic credit on two

components – unexpected income and unforeseen expenses, random changes of limitations on

accessibility of foreign lending.

Just like in the basic stochastic model (Flood, Garber, 1984), the main result of this

model is the calculation of the shadow exchange rate path and devaluation probability.

Blanco and Garber (Blanco, Garber, 1986) modify the currency crisis model of the first

19

Page 20: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

generation for the description for the currency crises in Mexico, with accounting the fact that

devaluation didn’t lead to the transition to the floating exchange rate; instead the new exchange

rate was fixed on a new level. In the model, the main factor leading to the crisis is the fiscal and

monetary policy that leads to the excessive build-up of the domestic credit.

Fundamental variables of the model cause misbalance of demand on real cash balances,

and it is a stochastic factor which determines random development of the events which

influences the exchange market and described by the equations (1)–(5):

~h t=

~s t−α⋅(E~s t +1−~s t ) , (10)

where, st – is the logarithm of the nominal exchange rate.

If one assumes, excessive demand is a stochastic process (authors suggest that ht –

autoregressive process of the first order), then the shadow exchange rate which is determined

through ht will also be a stochastic variable. That is why in this model is it possible to talk

about possibility of devaluation and expected exchange rate.

Assuming that during the devaluation the set value of the exchange rate varies

proportionally with the excess of the shadow exchange rate over the fixed exchange rate before

devaluation (the coefficient of proportionality is constant for each devaluation). This permits the

calculation of the minimum permissible volume of the central bank’s reserves.

In the work of Cumby and van Wijnbergen (Cumby, van Wijnbergen, 1989), an

analogical model is used for the analysis of the stabilization program in Argentina in 1978–1981.

The specialty of the situation in Argentina was in its stabilization program, which was based on

the tables of the daily values of the exchange rate which were announced in advance. From the

point of view of the model, the announced values can be seen as a fixed exchange rate. If for its

support it required heavily expanding domestic credit, then that might increase the pressure on

the foxed exchange rate, even with the account of its daily fluctuations. The suggested model is

an analogy to the Blanco and Garber’s model with the only difference being that in their research

the authors do not aggregate variables which influence demand on the real cash balances and

exchange market into one variable ht.

Calculation results on the offered model showed that sharp increases of the domestic

credit in the second quarter of 1980 led to downfall of creditability to the capacity of the central

bank to retain announced exchange rate. With that just prior to devaluation in June, 1981 abrupt

20

Page 21: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

jump of the devaluation probability of 80% in the next period took place.

For the analytical purposes of the EU exchange rate system during 90’s, a wide range of

models were used, which would examine dynamics of the exchange rate within some interval of

values, exit out of which prevented through money market intervention. The fundamental result

of this research is the conclusion that with the sufficient amount of reserves the exchange rate

might be held within the set limits, with that the path near the target range depends mainly from

the interventions of the central bank, not from the behavior of the fundamental variables

(Krugman, 1991).

Sterilization of currency interventions is one of the tolerable approaches used by the

central bank for its monetary policy so that drastic reduction of the monetary base during the

speculative attack would not happen. That means additional enlargement of the domestic credit

on the amount equals to the size of intervention in the national currency. Thus, under the

condition of sterilization of currency interventions, shadow exchange rate turns out to be always

higher than the fixed one (Flood, Marion, 1998). That means that in the conditions of full

certainty in the model the implementation of sterilization of currency interventions is

incompatible with the support of fixed exchange rate.

In real life, we have countries with fixed exchange rates, and simultaneously with the

speculative attack, sterilization of the currency intervention takes place, moreover, such regimes

can sustain for quite a long time. For the account of this event, Flood, Garber and Kramer

(Flood, Garber, Kramer, 1996) express the hypothesis that domestic and foreign assets are not

perfect substitutes, and domestic interest rate includes risk premium for investing into the

domestic assets, which depends on the share of national assets in the investor’s portfolio inside

of the country and abroad. This assumption allows a weakening of the model for the case when

domestic and foreign securities are not perfect substitutes (there are barriers, risk premium for

the investments inside of the country takes place and it means compensation liability related with

the partial substitution of domestic and external securities).

Inclusion of another variable which reflects the risk premium into the equation of interest

rate parity brings nonlinearity into the model through the behavior of economic agents (private

sector), which might lead to the existence of multiple equilibriums. That means that in the classic

model besides the crisis, which happens as result of inconsistent fiscal and monetary policy,

there is a possibility of situation when crisis happens because of self-fulfilling expectations

21

Page 22: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

2

(“bad” equilibrium) and possible sudden change from the one equilibrium to another one, which

is more favorable for speculative attack. Research shows that a similar approach entertains the

possibility of existence of the regime with the fixed exchange rate and sterilization of currency

intervention, but this is possible only when reserves are relatively large.

There is one more method of introduction of nonlinearity to the model – assumption

about different regimes of the government actions, when after devaluation the fixed exchange

course is supported (Obstfeld, 1996). Suppose that in result of devaluation government changes

build-up rate of the domestic credit for μ1>μ (build-up rate of the domestic credit before

devaluation). In that case it is possible to calculate two paths of the shadow exchange rate,

accordingly matched µ and µ1. Obviously, higher build-up rate of the domestic credit leads to

the higher pressure on the exchange rate and advances the moment of devaluation, because it

corresponds with the higher value of the shadow exchange rate.

If the value of the domestic credit is not too large, then when fixed exchange rates are

supported, it is in equilibrium. If domestic credit exceeds some limit, then in the situation of

perfect information, the equilibrium is the speculative attack and devaluation. At the same time,

with the certain values of the domestic credit, the possibility of devaluation depends on level of

coordination of the profiteers (size of the international reserves of the central bank is positive).

If profiteers are disaggregated, then equilibrium will be a preservation of the fixed exchange

rate regime; if they unite, then after the speculative attack devaluation will start. In other words,

in such situation multiple equilibriums are possible; moreover, transition from one equilibrium to

another might happen independently from actions of government and central bank. This

approach is based on the main idea of the currency crisis models of the second generation – there

are different variants are possible of the government’s policy depending on the economy

conditions, profiteers behavior and overall situation on the currency market .

In his article Obstfeld (Obstfeld, 1994) examines the choice between devaluation and its

consequences (influence on unemployment, real output, etc.) as the optimality criterion of

implemented. Let following function of the social costs minimized:

L= θδ 2

2+(δ−Eδ−u−k )2

2→min,

(11)

where, δ – devaluation rate; u – random fluctuations with the zero expected value and

22

Page 23: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

predetermined dispersion; k – measure of devaluation influence (for example, macro

indicators rate of change).

With the certain correlation between these parameters, it might happen that devaluation

will have to be implemented even when having an opportunity to protect fixed exchange rate with

the help of currency interventions. With that comparison of theoretical values of the parameters,

which are relevant for devaluation, with the actual implementations of the currency crises in

different countries allows us to evaluate costs related to the transition from the one equilibrium

to another.

In general, versus from the models of the first generation, where exhaustion of the

international reserves is the main cause of the currency crisis, models of the second generation

are based on the hypothesis that government might abandon the fixed exchange rate regime for

the sake of negative influence of such regime on other main economic variables.

Multiple goals complicate the choice between the support of the fixed exchange rate and

alternative government policies (for example, decline in unemployment, banking system support,

etc.). Target functions for the government might be set as positively dependent from the support

of the fixed exchange rate, and negatively dependent - from deviation of output from the target

level. Under certain conditions costs of the support of the fixed exchange rate might exceed the

benefits. For example, external shock in a shape of increase of world interest rate with the fixed

exchange rate will cause increase of domestic interest rates and drop in output and employment,

leading to the increase of government costs. As soon as world interest rate exceed the certain

level, it is no longer profitable to sustain the fixed exchange rate regime for the government. In a

similar way the other factors influencing the target function of the government might serve as the

potential indicators of the oncoming crisis.

Models of currency crises of the second generation also show that because of the multiple

equilibrium on the exchange markets, which is related to the nominal character of the

macroeconomic policy, crises might be self-fulfilling with the crises development occurring

without noticeable changes in the fundamental variables. Key assumption in these models is the

fact that macroeconomic policy is not predetermined but transforms depending on the changes

in the economy and economic agents form their expectations taking in account this correlation .

In its turn, expectation and actions of economic agents influence economic variables, thus

affecting overall economic policy. Such cyclicality leads to the potential multiple equilibrium

23

Page 24: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

and economy might transfer from the one equilibrium to another without feasible changes in

the fundamental variables. Thus, initially the economy might stay in equilibrium compatible

with the fixed exchange rate regime, but sudden deterioration of expectations might lead to the

change in policy, and as result, to the abandonment of the fixed exchange rate regime,

confirming by this expectations of the economic agents.

In the view of the above conclusions, the list of possible signaling indicators might be

complemented with the following variables: output deviation from the defined trend or desired

level; high unemployment rate; growth of world and domestic interest rates; volume of the

national debt; problems in the banking sector; and political variables.

There is a certain difficulty in the models of the second generation in the explanation of

the financial crisis only on the base on adverse moves of the fundamental variables. Crisis might

develop without substantial modification of the fundamental variables. As result, crisis

forecasting becomes extremely difficult.

In the works devoted to the models of third generation, attention is paid to the “contagion

effect”, i.e. effect of crisis transfer. In their work Gerlach and Smets (Gerlach, Smets, 1994)

present a model in which devaluation in one country leads to devaluation in the countries –

trade partners because of the desire of the last to avoid loss of competitiveness.

According to Tomczynska (Tomczynska, 2000) it is possible to determine three factors

which make a separate county vulnerable in case of financial instability in the world . First,

contagion effect with the external financial crises happens when there are system-based relations

between a country and an economy experiencing difficulties. These system-based relations might

be non-observable and, as the rule, based on the similar economic and institutional

characteristics. Second factor that increases the risk of the crisis transfer is the macroeconomic

relations (Eichengreen, Rose, Wyplosz, 1996). To characterize, the last factor is possible through

the definition of a few channels of contagion that affects transfer:

1) world shocks lead to rise of the pressure simultaneously on the currencies of different

countries;

2) significant devaluation of the currency in one country suppresses export of trading

partners as the consequence of loss of the price competitiveness;

3) existence of financial relations leads to the situation when crisis events in one encourage

investors to balance their portfolios through the risk management.

24

Page 25: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

There is a third factor which might play the key role in the definition of the adverse effect

of the international financial problems. It is reflected in such called “effects of full contagion”.

Full contagion happens when majority of international investors act similar independently from

the condition of fundamental variables. When crisis happens in some developing country, they

can divest assets simultaneously from the developing markets to developed ones (this occurred

during the crises in 1997 in the developing countries).

Empirical analysis of currency crises

Large numbers of the financial crises in the developing countries in during 90’s kindled

significant interest in the models of early signaling and led to heated discussion on the subject in

the economic literature.

Thus, extensive review was made by Kaminsky, Lizondo, and Reinhart (Kaminsky,

Lizondo, Reinhart, 1998). The authors examined 28 works devoted to the empirical research of

the currency crises for last 20 years. In spite of the fact that research data significantly differ

from methodological point of view and from the list of the examined crises, the authors drew

some common conclusions. First of all, crises can have many causes, part of which is described

by the dynamics of the separate economic variable. As result, for the explanation of all crises a

large amount of variables might be needed. At the same time dynamics of some variables seem

to have good forecasting characteristics for the prediction of the majority of crises . In

particular, real exchange rate and international reserves were examined in many of the

researches and turn out to be meaningful in most of the cases.

After publication of the Kaminsky, Lizondo, Reinhart research, all works on the subject

of forecasting financial crises started to be divided in four groups depending on the

methodology used in the research. First group usually includes early works that only includes

the qualitative discussion of causes and events preceding currency crises.

The second group of works studies distinctive principles in the dynamics of

macroeconomic variables for the period before and after currency crises.

Non-parametric approach is used in the third group of works and it is based on the system

“signal extraction”. Based on this approach, a conclusion is made about the applicability of

different variables as the signals about approaching crisis.

The fourth group of the articles estimates the possibility of the financial crisis based on the

25

Page 26: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

explicit theoretical model. In these articles the indicator of the currency crisis is modeled as a

fictitious variable, taking values 0 or 1. Nevertheless, other than in the previous approach,

independent variables do not take a form of fictitious variables, with that regression of all

variables is analyzed simultaneously, while signaling approach studies interrelation of dependent

variable and independent variable are studied separately for each of the variables (Frankel and

Rose, 1996).

Frankel and Rose used the stochastic model for the crisis probability evaluation on the

annual data from the sample of 105 developing countries from the period of 1971–1992.

Devaluation of the national currency on more than 25% in a year was used for the definition of

the crisis in a country.

The authors used a few specifications of the model and came to the conclusion that

possibility of the crisis increases when output rate of growth drops down, increases rate of

growth of the domestic credit, international interest rates rise, foreign direct investments

decrease as a part of aggregated debt, international reserves decrease and national currency

strengthens. At the same time results for the output rate of growth, real exchange rate and

reserves were not sustainable in different specifications.

Berg and Pattillo overestimated the results of Frankel and Rose’s research. Using as an

approaching crisis signal a fictitious variable equal 1, and if possibility of the crisis exceeded

25%, only 17 out of 69 crises were predicted correctly while 33 out of 711 normal periods were

faulty predicted. According to the authors one of the reasons of such results was high diversity of

the sample countries. However, examining more homogeneous and small sample of the countries

for the period of 1970–1996, 38 out of 60 crises and 342 out of 383 normal periods were

forecasted correctly.

The authors also used stochastic model for the currency crisis probability evaluation.

They use data and the definition of the crisis which is described in the research by Kaminsky,

Lizondo, and Reinhart. In their regression model, the value of dependent variable equals to 1 not

only during the crises but during the periods of 23 months preceding the crisis . Following

variables showed highest predictive value:

real exchange rate deviation from the determined trend;

current account position of the balance of payments;

rate of growth of international reserves;

26

Page 27: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

export growth ratio;

relation of the money supply (M2) to reserves.

Using as an approaching crisis signal a fictitious variable equals 1, and if possibility of the

crisis exceeded 25%, model predicted correctly 48% of the crises inside of the sample and 84%

of normal periods. Out of sample analysis results turn out to be even better: 80% of crises and

79% of normal periods were forecasted correctly.

CHAPTER 2

Main approaches to the development of a framework of indicators to monitor financial

stability.

All research can be divided in three groups depending on the methodology used to

determine the most effective signaling indicators of the financial crisis.

Quality analysis. This approach includes a comparison of graphs of the dynamics of the

fundamental economic variables during the period of crisis and at a normal time. To some extent,

calculation of some statistic indicators is available; these indicators characterize dynamics of the

time series of signaling indicators.

Econometric models. Such an approach implies to the regression models, which allows

evaluation of the interrelation of variables with the financial crisis probability. Most often logit-

or probit-analysis is used, where regression model shows dependence of the financial crisis

probability from the number of economic indicators. Estimated model is used for forecasting

purposes to predict probability of the financial crisis in the future.

Non-parametric evaluation. Different numerical characteristics are established to define

economic vulnerability tendencies in advance. There are two main directions: 1) determination of

the threshold level for the indicators; 2) establishment of consolidated indexes of financial

stability.

In literature review, I will present main scientific papers related to each of the noted

groups, though often authors combined several approaches in their researches.

27

Page 28: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

2.1. Quality analysis

In their work, Eichengreen, Rose and Wyplosz (Eichengreen, Rose, Wyplosz, 1995) make

an attempt to determine variables which can serve as early warning signs of impending crises .

The authors tried to find an answer to the question of whether dynamics of some economic

variables can predict exchange rate crises, they also tried to analyze if the behavior exhibits

different indicators during the period prior to the crisis and after the crisis.

For the purposes of study of currency crisis the list was made of official announcements

about devaluation and revaluation, transition from the fixed exchange rate to the floating

exchange rate, when thresholds of exchange rate band were broadened, and other significant

changes in the fiscal policies around the world during the period of 1959−1993. Such cases are

called “events” of the exchange market because it is clear that not all of these episodes were full

scale currency crises. Data of twenty different countries was used on a quarterly basis

Authors presented behavior of the variables during different crises and “events” on the

exchange market in the form of diagrams, hoping to find some common trends and patterns in

their behavior. Each graph illustrated behavior of some variable two years before and after the

“event” or a crisis. They studied dynamics of the following variables: changes in gold and

foreign currency reserves; exchange rate; short-term interest rate; refinancing rate of the Central

Bank; changes in export and import; relation of current account balance of balance of payments

to GDP; relation of budget deficit to GDP; domestic credit; money supply; unemployment;

inflation; GDP in real terms; yield of government stocks and bonds; and stock index.

Authors show that a few quarters before devaluation decrease of the gold and foreign

currency reserves is observed, export decrease and import increase, and therefore, increase of the

current account deficit. After devaluation reserves and exports recover relatively fast. At the

same time for the import and current account balance more time is needed. Moreover, a

significant increase of the real effective exchange rate before devaluation was discovered.

In countries before devaluation large budget deficit, growth of domestic credit and money

supply were registered. Higher rates of inflations and short-term interest rates were observed,

notably interest rates did not decrease after devaluation. On the labor market before and after

devaluation high unemployment rates were observed.

Authors also noted that before revaluation macroeconomic variables show opposite

28

Page 29: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

tendencies, their behaviors do not differ much from their normal state.

Frankel and Rose (Frankel and Rose, 1996) also used graph analysis to determine

potential signaling indicators of the currency crisis. For their analysis they used data from 105

countries for the period of 1971-1992. In their work currency crisis is defined as nominal

devaluation of the exchange rate on more than 25% with the increase of the devaluation speed on

more than 10%. It is noted that even though changes of foreign reserves and interest rates

should be taken in account for the identification of a crisis, it is not done in their work because

necessary data is not available from many of developing countries.

In the work variables are divided in following groups:

Domestic variables: growth ratio of the domestic credit; relation of surplus/deficit of the

budget to GDP; GDP growth ratio in real terms.

Foreign variables: relation of foreign debt to GDP; relation of gold and foreign currency

reserves to volume of import, on a monthly basis; relation of current account balance to

GDP; real exchange rate.

Variables characterizing foreign debt (in relation to total sum of foreign debt): share of

foreign borrowing attracted by commercial banks; share of easy loans; share of foreign

debt with the floating interest rate; share of foreign debt of the government sector; share

of short-term foreign debt; share of the debt to international financial organizations; and

the relation of inflow of foreign direct investments to foreign debt.

External variables: short-term world interest rate (average weighted interest rate in

industrial countries); GDP growth ratio in real terms in the countries of OECD.

Authors show that foreign interest rates rise before the crisis. At the same time account

balance of the current operations of the balance of payments and state budget deficit sustain their

long-term average values before the crisis.

Eichengreen and Rose (Eichengreen, Rose, 1998) studied banking crises in the

developing countries. They used macroeconomic and financial indexes for the period of

1975−1992. Indicators were divided in five main groups: indicators of the domestic

macroeconomic policy, indicators of the external economic conditions, exchange rate regime,

indicators of the domestic financial structure, problems of supervision and management.

For identification of the banking crisis authors used the results of Caprio and Klingebeil

(Caprio, Klingebiel, 1996). Banking crisis is defined as a situation when problems that banks

29

Page 30: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

are experiencing lead to the significant decrease of the capital in the banking system . Caprio

and Klingbiel analyzed crisis developments in 69 countries relying on official figures and expert

judgments and made an attempt to determined how serious the problems are and how they

influence the banking sectorр.

Eichengreen and Rose examine dynamics of the nine key variables prior to 39 crisis

events: The authors show that prior to a banking crisis foreign interest rates rise and industrial

output slows down. Though, dynamics of the “foreign” and domestic variables do not allow

using them as signaling indicator of the financial instability.

In the research of the International Monetary Fund (International Monetary Fund, 1998),

in the identification of the currency crisis, the index is composed equal to weighted average

values of the rate of increase of the exchange rate and gold and foreign currency reserves . They

define a banking crisis as a situation of forced large-scale shut down and mergers of banks or

acquisition of financial institutions by the government; also as massive withdrawal of deposits by

the population. Research examines crises in 50 countries during the period of 1975-1997 and

showed that developing countries experienced larger amount of crises during the noted period. It

turned out that banking and currency crises are often follow one after another. Following

variables were used as signaling indicators: surplus of balance of trade; real effective exchange rate;

gold and foreign currency reserves; export; GDP in real terms; index of stock market; inflation; dynamics

of the money supply in nominal and real terms; relation of the money supply to gold and foreign currency

reserves; relation of the money indexes M2 to M1.

The following variables were used for forecast of the banking crisis: GDP in real terms;

real fixed capital formation/capital investments; surplus/deficit of budget; inflation; nominal

exchange rate; real effective exchange rate; domestic credit; оrelation the money indexes M2 to

M1.in real terms; index of stock market; the relation of account balance of the current operations

to GDP; and the capital inflow/outflow.

Examination of the indicators allowed determination of the increase of inflation and

exchange rate, and also a decrease of the export volumes before the crisis. Moreover, for the

period prior to the crisis is typically the increase of the rate of growth of the money supply and

enlarging of the domestic credit.

Before the banking crisis, the overall situation in the economy is characterized by high

inflation, significant deficit of the current operations account, rapid growth of the domestic

30

Page 31: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

credit, related to some degree to the foreign capital inflow and in some cases with previous

liberalization of the financial system of the country.

Due to the fact that before the crisis values of not all variables differed statistically

significant from the normal level and due to the availability of the statistical data, as best

signaling indicators of the financial crisis were selected real exchange rate, domestic credit, and

relation of the money supply to gold and foreign currency reserves.

Glick and Moreno (Glick, Moreno, 1999) study crises in the countries of the East Asia

and Latin America during the period of 1972–1997. They describe crisis as a situation when

deviation of the exchange rate from the mid-value exceeds two standard deviations calculated on

the entire period selected. Periods of hyperinflations are examined separately.

Dynamics of the following variables is examined in the article:

Indicators of the currency market: nominal and real money supply M2; monetary

multiplier; relation of money supply M2 to gold and foreign currency reserves; and

domestic credit in real terms.

Indicators of competitiveness and trade: regression of the real effective exchange rate

from trend (i.e. remains of the regression equation of the real effective exchange rate on

trend, export, import and relation of net exports to aggregated export); export dynamics;

and the trade balance surplus.

Graph analysis shows that increases of the money supply in real terms and domestic

credit in real terms slow down before the crisis, and it speaks about the decline in economic

activity. Such results contradict other similar research, in which sharp increases of the money

supply signals about approaching crisis. Monetary multiplier increases before the crisis and it

becomes obvious approximately one month before the crisis. Authors also found a tendency of

declining gold and foreign currency reserves before the crisis.

Increase of money supply in nominal terms and growth of the domestic credit in

comparison to the “calm” period were higher in Latin America and lower in Asia, which is

explained with high inflation in the first region.

Prior to crisis in both regions real export and trade balance surplus were also lower and

real exchange rate was higher than during “calm” periods. Obviously, such dynamics showed

high degree of the exposure to external shocks.

Aziz, Caramazza, and Salgado (Aziz, Caramazza, Salgado, 2000) study the relations

31

Page 32: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

between macroeconomic and financial variables. One example is between some of the industrial

and developing economies. They studied crises which were revealed in depreciation of the

national currency and sharp decrease of the volume of the gold and foreign currency reserves.

Analysis included comparison of the dynamics of different macroeconomic and financial

variables during the crisis and “calm” period.

The article studied currency crises during the period of 1975−1997. Authors define

currency crisis as significant devaluation of the national currency. A series of indicators whose

behavior significantly differ during the critical events were idetified on the basis of the

conclusions from the theoretical models of currency crises and results from earlier researches on

the same subject.

For each of the variables whose period of observation (from 1975 to 1997) was divided

between “calm” periods and so called “critical windows”. “Critical windows” are a number of

periods prior to and after the critical date. Authors used windows in 49 months for the monthly

data (24 months prior to the crisis and 24 months after it) and window in 5 years for the annual

data (2,5 years prior to the crisis and 2,5 after it).

After average values were calculated (on the critical events) for all variables for each

moment of time within the “critical window”. Average values were calculated of the variables

during the “calm periods”. To define whether variable’s behavior differs significantly during the

crisis period from the dynamics of the “calm period”, authors performed standard t-test on the

statistical significance of the deviation in average values of the variable during critical and

“calm” periods. Entire selection of crises was divided in following (possibly crossing) subgroups:

1. crises in industrial countries;

2. crises in the countries with developing economy;

3. crises of devaluation of the national currency (i.e. crises when 75% of increase of

speculative pressure index is defined by the exchange rate);

4. crises of significant loss of the gold and foreign currency reserves (i.e. crises when 75%

of increase of speculative pressure index is defined by loss of the gold and foreign

currency reserves);

5. “rough” crises, when speculative pressure index value exceeds three standard deviations from

the average value;

6. “soft” crises, when index value is in the interval from 1,5 to 2 standard deviations from the

32

Page 33: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

average value;

7. crises cause by the problems in banking sector;

8. crises with fast following recovery of the economy, when GDP returns to its normal

trend within two years;

9. crises with the slow following recovery of the economy, when GDP returns to its normal

trend within three years or later.

For all types of crises real exchange rate in average was higher during the “calm” period

in comparison with the crisis period. Two years before the crisis its average value was 0,4

standard deviation higher than during the crisis. In most of the cases after crisis real exchange

rate declined fast.

Sometimes, currency crises were preceded by a slowdown in the growth rate of export,

even though, it wasn’t significant and was not observed in all types of crises. In particular, it

wasn’t statistically significant for the crises in industrial countries and crises of significant loss

of the gold and foreign currency reserves.

Terms of trade (relation of export prices to import prices) usually worsens during the

period prior to the crisis, yet statistically significant if it was only few months before the crisis.

Besides, majority of the types of crises had deficit of the balance of payments before the crisis.

For most of the types of crises inflation significantly exceeded its value of the “calm”

period before the crises, though analysis of “rough” crises and crises related with problems in

banking sphere didn’t reveal such tendency.

For the study purposes on the monetary market indexes M1 and M2 were used. Analysis

showed increase of the nominal value of the indexes a year – year and a half before the crisis.

Nominal growth of the domestic credit was also noted but it wasn’t expressed strongly. At the

same time growth acceleration of the domestic credit in real terms was not significant. In real

terms indexes M1 and M2 raise approximately 24−12 month before the crisis and after that

(precisely before the crisis) demonstrated decline.

In most of the cases, a slowdown of the growth ratio of output was not found, though

with significant currency devaluation and crises followed by slow recovery a statistically

significant decrease of the rate of growth of output was still noticed . Finally, an increase of

the world interest rates was registered approximately a half a year before the crisis.

In their research Carramazza, Ricci and Salgado (Carramazza, Ricci, Salgado, 2000)

33

Page 34: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

used a similar approach in defining critical period. Four different groups of variables are

examined in the article:

1) General shocks include an increase of the world interest rate, slowdown of the world

economic growth, decrease of prices on export goods, sharp change of the exchange rates

of the currencies of the main world economies.

2) External economic relations. If a country experiences financial crisis accompanied with

strong currency depreciation, other countries may also get hurt because of the export

decline in this country and increase of the price competition from the goods imported

from such country. Thus, necessity of examination of not only the countries which suffer

from the crisis but also those who can get hurt as well is outlined.

3) Capital outflow also may be a cause of the crisis or intensify it. Thus, financial instability

in the country may stimulate investors to change the structure of the investment portfolio

for the risk cushioning, in other words, cut investments in the assets in this country.

Obviously, significant capital outflow may increase financial exposure of the country.

4) Changes in the investors’ expectations can also play a key role in the spread around of

the crisis. Crisis in one country may serve as a signal that in other countries

macroeconomic indicators can get worse. With that investors desire to obtain profits

through the attacks on the currencies of those countries whose situation is similar with

the one experienced the crisis.

In most of the developing economies, opposed to developed countries, increase of the

real exchange rate within three years period before the crisis was significant. Balance of

payments deficit a year before the crisis in most cases turned out to be significantly higher than

the average one during the “calm” period.

Authors also showed that factors which can reflect a country’s exposure to the crises

include slowdown of the GDP rate of growth and high unemployment level. Decrease of output

before the crisis was noticeable mainly in the developed countries. Variables of the monetary

market and budget deficit didn’t enter in the number of variables which allow predicting

developments of the critical events.

Besides, the relation of the monetary index M2 to gold and foreign currency reserves was

recognized as a working signaling indicator of the financial crisis. Thus, in Mexico this indicator

significantly exceeded its own normal average value during the “calm” period.

34

Page 35: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

2.2. Econometric valuation

Eichengreen, Rose and Wyplosz (Eichengreen, Rose, Wyplosz, 1995) used quarterly data

from 20 countries of OECD from the period of 1959–1993 to determine the best signaling

indicators of the financial crisis. The authors showed particular interest in political variables. In

their work they showed that control over the capital flows can give the government an

opportunity to repulse a speculative attack on the nation’s currency.

With further help of logit-analysis, the authors defined macroeconomic variables which

could be used to predict financial crisis. It turned out that speculative attacks as well as transition

to the fixed exchange rate statistically significant increase probability of the financial crisis.

Moreover, in their research, the role of inflation and monetary factors was confirmed as good

signaling indicators of the financial crisis. Authors also showed an increase of the negative

balance of the current account of balance payments increased the probability of devaluation.

For the analysis Frankel and Rose (Frankel and Rose, 1996) used data from

approximately 100 countries from 1971 t o 1992. They define devaluation as nominal

depreciation of the exchange rate on no less than 25% with the increase of depreciation speed in

10%. Further they develop multidimensional probit-model. Most of the variables responsible for

the structure of the foreign debt turned out to be insignificant.

Research of Sachs, Tornell, and Velasco (Sachs, Tornell, Velasco, 1996) was dedicated

to the Mexican crisis in 1995. For identification of the cases of “credit booms” authors used

relations of bank claims to the private sector to GDP (B/GDP). If fractional variations of this

variable (LB) were high, then it was considered that “credit boom” took place in the country.

Besides, authors calculated for all country relations of the monetary index M2 to gold and foreign

currency reserves (M2/R) which was interpreted as an indicator of sufficiency of reserves, and

index of revaluation of the real exchange rate (RER) equal to the change of average value of the

real effective exchange rate index in 1990-1994 in comparison to 1986-1989.

35

Page 36: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

All observations are then divided in periods during which countries had strong

fundamental variables, and periods during which countries had weak fundamental variables.

Authors thought that countries which had strong fundamental variables are the index value of

revaluation of the real exchange rate (RER) at the present moment situated in the upper quartile,

and value of the “credit boom” index (LB) is in the lower quartile. For taking into account the

“quality” of fundamental variables of the country during evaluation of the regression model,

authors introduce fictitious variable equal 1 if the country during the present period has

weak fundamental variables and 0 in the opposite situation. Besides, during the evaluation

process they use variable which characterizes gold and foreign currency reserves and equal to 1

for those countries whose indicator’s M2/R value at the present moment is situated in the lower

quartile, and 0 in the opposite situation. After that econometric model was evaluated (12):

IND=β1+β2 RER+β3 LB+β4 DLR RER+β5 DLR LB+β6 DFW DLR RER+β7 DFW DLR LB+ε . (12)

Evaluation results of the equation (14) show that speculative pressure on the exchange

rate of the national currency increases with decline of the gold and foreign currency reserves and

increase of the bank claims to the private sector. Proof of the hypothesis that excessive capital

inflow increases crisis possibility was not found.

In their study Corsetti, Pesenti and Roubini (Corsetti, Pesenti, Roubini, 1998) examined

Asian crisis. Excessive foreign debt of the Asian companies and deficit of the balance of

payments are named as the main causes of the crisis. Authors pay special attention to the

problem of the moral hazard: Following signaling indicators were used in the article:

1) Index which reflects crisis probability presents itself weighted average value of monthly

increases of the exchange rate and gold and foreign currency reserves.

2) “Health” variables of the financial system is the relation of non-operating loans to the

total assets of the banks. Other indicators equal to the growth ratio of the relation of bank

credits to GDP. The third variable takes in account loans issued by the commercial banks

to non-banking sector.

3) Index of overs-and-shorts of the current account positions. If growth ratios of the real

exchange rate on the end of 1996 in comparison with the average valued of 1988–1990

exceeds 10%, then index equals to current account (% to GDP); in the opposite case it

36

Page 37: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

equals 0.

4) Fundamental variables are the relation of indexes M1, M2 and maintenance expenditures on

foreign debt to gold and foreign currency reserves.

Further, authors designed a probit-model that reflects dependence of the crisis

probability from the noted variables. Evaluation of the model shows that crisis probability is

strongly influenced by the fundamental variables and imbalance of the balance of payments.

Demirguc-Kunt and Detragiache (Demirguc-Kunt, Detragiache, 1998b) study banking

crises both in developed and developing countries during 1980–1994. For the econometric

evaluation of the banking crisis probability authors use the multidimensional logit-model.

In the article, banking crisis is defined as a situation when one of the following cases

takes place (depending on the available statistical data): share of non-operating assets in total

assets is over 10%; costs on reconstruction of the banking system is at least 2% of GDP; and the

problems of the banking sector lead to full scale nationalization of banks.

Evaluations of the model show that slowdown of the GDP growth rates and a worsening

of the terms of trade increase the possibility of the banking crisis. Rise of the interest rate, relation

of money supply M2 to the gold and foreign currency reserves and speeding up of inflation also

have statistically significant positive correlation with the crisis probability.

Empirical evidence was found of the hypothesis that countries where banking sector

lends more credits to the private sector will face a higher probability of a banking crises.

Hardy and Pazarbaioglu (Hardy, Pazarbaioglu, 1998) also devoted their research to the

determination of the role of macroeconomic factors in the process of forecasting financial crisis

probability. They study the role of macroeconomic factors in creation of prerequisites for the

occurrence of the crisis in the banking system. For their analysis authors use data on banking

crises in Asian countries and Latin America of 1980 – 90’s on the basis of which they build a

logit-model. Authors determine three groups of explanatory variables:

Variables of the real sector: growth ratio of real GDP; growth ratio of private

consumption; and the growth rate of private fixed investments.

Variables of the banking sector: debt on private deposits in relation to GDP; relation of

issued bank loans to GDP; and the relation of banking sector foreign debt to GDP.

Shocks that influence banking sector: inflation; deposit interest rate in real terms; real

exchange rate; growth ration of import in real terms; and the terms of trade.

37

Page 38: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

Possibility of problems in banking sector strongly depends on GDP growth ratio;

consumer boom might cause crisis; speed up of inflation with its following drop is one of the

most important variables in forecasting banking crisis; bank deposits in real terms decrease both

during the period before the crisis and during the crisis itself; amount of loans to the private

sector sharply increase before the crisis and decrease during the crisis itself; increase of the

exchange rate and interest rate increase possibility of crisis; and the inclusion of the variables,

which take in account regional differences, in the model increases its prognostic value.

Kruger, Osakwe and Page (Kruger, Osakwe, Page, 1998) analyze factors which

influence occurrence of currency crises in Asia, Latin American and Africa during 1977–

1993. Probit-regression is used for econometric evaluation. For identification of crisis authors used

index equal weighted average value of increases of nominal exchange rate and gold and foreign

currency reserves. If value exceeded a standard deviation of 1.5, then crisis takes place. In the

model, the variable which is responsible for the contagion effect is ( R(Crisis j ,t )). It takes value

1 if some other country experienced crisis during the same period, and that country is from the

same geographical region as the examined one.

Authors used following exogenous variables: relation of foreign debt to GDP; relation of

money supply M2 to gold and foreign currency reserves; relation of current account position of

the balance of payments to GDP; real exchange rate; relation of budget deficit to GDP; domestic

credit; GDP growth ratio per capita; inflation; and world interest rate.

The article shows that the slowdown of the GDP growth ratio, unsecured by gold and

foreign currency reserves, the increase of money supply and appreciation of the national

currency facilitate crisis events. Variables related to foreign debt turned out to be insignificant.

And finally, the contagion effect was evidenced empirically.

The subject of study of Milesi-Ferretti and Razin (Milesi-Ferretti, Razin, 1998) is a sharp

increase of the current account of the balance of payments and depreciation of the national

currency in the countries with average and low income during 1973–1994. Authors considered

as crisis events following situations during which following conditions were fulfilled

simultaneously:

a) decrease of relation of current account deficit to GDP in approx. 3% (average value three

years before the crisis in relation to average value three years after the crisis);

b) minimal value of current account deficit after devaluation is no higher of its maximum

38

Page 39: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

value during the period of three years before devaluation;

c) after devaluation current account deficit decreases on approx. 1/3.

Analysis was conducted with help of following variables:

Variables of real sector: GDP growth ratio; growth ratio of consumption; growth ratio of

investments; budget deficit/surplus; and GDP per capita.

External variables: current account of the balance of payments; real effective exchange

rate of nation currency; relation of gold and foreign currency reserves to import; level of

trade freedom (relation of the sum of export and import to GDP); and international

transfers (% GDP).

Foreign debt: relation of foreign debt to GDP; maintenance of foreign debt in relation to

GDP; share of soft foreign debt in total foreign debt; share of short-term foreign debt in

total foreign debt; share of state foreign debt in total foreign debt; and the relation of

attracted foreign direct investments to foreign debt.

Financial variables: relation of money supply M2 to GDP; growth ratio of domestic

credit;and the relation of bank loans issued to private sector to GDP.

Exogenous variables: USA interest rate; GDP growth ration in countries of OECD; and

the terms of trade.

Fictitious variables: regional variables; variables that take in account exchange rate

regime; and the variable that takes in account participation in the IMF programs.

For evaluation purposes probit-analysis was used, in other words crisis probability was

evaluated in dependence from the values of mentioned earlier indicators with the time lag in one

month. Model evaluation showed positive correlation of the crisis probability with high GDP per

capita, high current account deficit of the balance of payments, low growth ratio of investments,

poor terms of trade, high US interest rate, and stable and fast economic rates of growth in the

OECD countries. Moreover, significant relation of gold and foreign currency reserves to import

and large share of soft foreign debt in total foreign debt negatively correlated with the crisis

probability.

In their work, the authors also examined currency crises for identification and use the

following four definitions:

a) currency depreciation in relation to the US dollar on no less than 25% a year, with that

noted value has to be at least 10% higher of its value of previous year;

39

Page 40: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

b) currency depreciation in relation to the US dollar on no less than 25% a year, with that

noted valued has to be 2 times higher its value of previous year; currency depreciation

for the previous year shouldn’t exceed 40%;

c) currency depreciation in relation to the US dollar on no less than 15%, with that noted

value has to be at least 10% higher of its value of previous year; currency depreciation

for the previous year shouldn’t exceed 10%;

d) in addition to the previous condition, it is needed that a year before the crisis the

exchange rate was fixed.

To the list of variables used by authors for the analysis of crises of balance of payments

was added relating currency reserves to import or money index M2 so they could examine

currency crises as well.

Evaluation of the probit-model showed that increases of the current account of the

balance of payments, decline of gold and foreign currency reserves, over-evaluated exchange

rate and poor trade conditions increase devaluation probability. Slow GDP growth abroad and

high world interest rates also increase probability of the currency crisis, though high international

transfers decrease its probability.

The aim of research conducted by Deutsche Bundesbank (Deutsche Bundesbank, 1999)

was to gain an understanding of the Asian crisis of 1997. Determination of the crisis events in

the research was made with help of index that took in account changes of the exchange rate and

gold and foreign currency reserves. Interest rate was not taken in account because authors found

its high correlation with the exchange rate. They defined as a crisis a situation when index value

exceeded 1.5 standard deviations.

The binominal model was established using variables to determine the probability of the

financial crisis in relation to real exchange rate, export, relation of current account of the balance

of payments to GDP, gold and foreign currency reserves, domestic credit, difference in inflation

in the country examined and the USA, and world interest rates. All coefficients of the model

turned out to be significant and had an expected sign. Results confirm that higher interest rate

and slow economic growth in industrial countries increase crisis probability.

Glick and Moreno (Glick, Moreno, 1999) examined crises in Asia and Latin America

during 1972–1997. They defined a crisis a situation when deviation of the exchange rate from the

average level exceeds two standard deviations. For the statistical analysis probit-regression is

40

Page 41: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

used. They showed that crisis probability increases with the decline of gold and foreign currency

reserves and increase of relation of money supply M2 to gold and foreign currency reserves.

Decrease of the domestic credit also increases devaluation probability.

Tornell (Tornell, 1999) examined Asian and Mexican crises in a similar way. He

studied countries with the developing economies only, and suggested that investors will exercise

speculative attacks on the currencies of those countries where devaluation probability is high, i.e.

countries with highly over-evaluated currencies and small gold and foreign currency reserves.

“Credit boom” in Tornell’s work is identified with help of the variable LB equal to

increase the volume of loans issued by banks to the private sector and government corporations

during previous four years in real terms. Variable RER presents itself a change of real effective

exchange rate during previous four years. Besides, in econometric analysis fictitious variable DHR

is used. It equals 1 if relation of money supply M2 to gold and foreign currency reserves prior to

crisis was less than 1.8, and 0 in the opposite situation. Finally, author divides observation on the

periods when country had strong fundamental variable (LB<0%, RER<5%) and all other cases.

In the first case value of the fictitious variable was equal 1, and 0 in the opposite situation. After

that equation (13) was evaluated:

IND=β1+β2 RER+β3 LB+β4 DLR RER+β5 DLR LB+β6 DFW DLR RER+β7 DFW DLR LB+ε . (13)

Evaluation results show that in countries with low gold and foreign currency reserves and

weak fundamental variables, devaluation and “credit boom” increase significantly crisis

probability, and on countries with strong fundamental variables exchange rate and “credit boom”

do not influence crisis probability. The article also shows that countries from the same region as

the source of crisis, suffer from it more.

In the research of Carramazza, Ricci and Salgado (Carramazza, Ricci, Salgado, 2000)

the applicability of financial variables for forecasting of crisis events is examined, attention is

also paid to the role of the institutional factors. Countries influenced by Mexican and Russian

crises are examined only.

Speculative pressure index is calculated during the first part of crises identification. On the

second step authors evaluate probit-model of regression on panel data from 1990 t o 1998.

Further, authors introduce the concept of “common creditor”, i.e. country which lend the largest

41

Page 42: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

amount – source of crisis. Variable BISB shows importance of the common creditor for the

country, it equals to the share of credits issued to the country by common creditor from total

amount of credits issued through the Bank for International Settlements (BIS). Variable BISA

shows the importance of common creditor for the country (it is a share of borrowings received

from the common creditor in all borrowings of the country). Then, uniting these variables it is

possible to establish new index BISAB equal to the product of BISA and BISB .

As exogenous variables, the authors used two groups of variables. The first group

included variables whose influence on the crisis occurrence can be explained theoretically: real

exchange rate, current account of the balance of payments in relation to GDP, export share in

GDP, budget deficit (% GDP), relation of M2 to GDP; GDP growth ration in real terms,

contagion index.

Contagion index includes two components. The first component allows taking into

account income effect and equals to weighted average change of industrial output of the main

trade partners of the country during the year after the crisis. Price effect recognizes change in

competitiveness and is calculated as growth rate of real exchange rate of the country during six

months after the crisis.

The second group of variables describes capital outflow and weakness of the market:

share of short-term foreign debt in relation to the total debt, variable BISAB ,volatility of the

stock market index, correlation of stock market index of the country and country the source of

crisis ,relation of M2 to gold and foreign currency reserves, relation of short-term foreign debt of

the country to gold and foreign currency reserves.

Model evaluation allowed researchers to find significant positive correlation with the

probability of the crisis of the real exchange rate growth, a growing current account deficit of the

balance of payments, a slowdown of output in real terms, the growth of the share of short-term

foreign debt in relation to the total foreign debt, and also the presence of the common creditor

(BISAB), increase of the relation of short-term foreign debt of the country to gold and foreign

currency reserves and relation of M2 to GDP.

42

Page 43: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

2.3. Non-parametric evaluation

The first work in which a non-parametric evaluation approach was used to forecast

financial instability was the research of Kaminsky, Lizondo and Reinhart (Kaminsky, Lizondo,

Reinhart, 1998). They performed empirical analysis of the currency crises in 1990’s and offered

their own system of early alarm signals to determine approaching critical events.

The authors defined as a crisis a situation in which a speculative attack on a currency

leads to its fast devaluation, decrease of gold and foreign currency reserves or combination of

two of these factors. Identification of these crises was made with help of the speculative pressure

index equal to a weighted average change in currency exchange rate and gold and foreign

currency reserves in a month.

In their research authors study following indicators: gold and foreign currency reserves; imports;

exports; terms of trade; real exchange rate; and the spread between world and domestic interest rates;

excessive money supply in real terms; monetary multiplier; relation of domestic credit to GDP; real

interest rate on deposits; relation of the credit interest rate to deposit interest rate; deposits of the

commercial banks; GDP in real terms; and the stock market index.

As signal horizon, or the period within which dynamics of indicators may forecast crisis,

24 months was used. For each of the indicators in each country, a threshold is defined separately.

If the indicator’s value exceeds the threshold, then it means it signals. Threshold levels were

selected so that on the one hand indicators would not give many false signals, and on the other

hand would not miss the critical events.

Each indicator may signal (first row Table 1) or may not signal (second row). If

indicators signal, if afterwards a crisis follows within the 24 month time horizon, then the

signal is “good” (cell A). If indicators signal and a crisis does not happen within 24 months, then

the signal is considered as noise or “bad“ signals (cell B). If the indicator does not signal and a

crisis happens, then the signal considered “missed” (cell C). If the indicator does not signal and a

crisis does not happen within 24 months, then signal is also considered as a “good” one (cell D).

Ideal indicators will be characterized with non-zero values only in cells A and D.

Table 1

Distribution of indicator’s signals (Kaminsky, Lizondo, Reinhart, 1998)

43

Page 44: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

Event Crisis within 24 months No crisis within 24 months

Signal A B

No signal C D

The number of months is placed in the cells of Table N during which each event took

place. During the selection process of indicators, the share of “good” signals A/(A+C), “bad”

signals B/(B+D), and “relation of noise to signals” [B/(B+D)]/[A/(A+C)] were taken in account.

Besides, for the “good” indicator conditional probability that crisis will happen A/(A+B) has to

be higher than unconditional (A+C)/(A+B+C+D).

In their work, the authors showed that the signaling approach might be effective at

forecasting critical events and indicators in which prognostic values were found: exchange rate,

domestic credit, money supply, gold and foreign currency reserves and export.

Later Kaminsky developed a non-parametric approach to forecasting financial crises. In

her work (Kaminsky, 1999) she studied currency and banking crises of the 1990’s. In that work

the time interval is divided between “calm” and crisis periods. First, it is being tested if the

numbers of signals during the crisis are higher than number of signals during the “calm” period,

then indicators behavior is examined in relation to the approaching moment of crisis. After that,

signals are divided on “soft” and “rough” (depending on how much they exceeded threshold

levels) and examined separately.

It is noted in the research that if indicators suggest a crisis immediately before one

occurs, then most likely it shows the happening of the event instead of forecasting it. That is why

the author studied the time structure of the signals. It turns out that increases of the total number

of signals before the crisis is not that significant and average number of signals during the past

six months and previous months do not differ much. Thus, “good” indicators are equally good at

their job as right before the crisis and some time prior to it.

Kamisnky’s research was one of the first where the attempts of composition of

consolidated indexes. In the article for n of available indicators of financial stability a few

variants of such indexes were reviewed:

sum of all signals: I t

1=∑i=1

n

S ti

, where Sti=1 , if at the moment of time t indicator gave a

signal i;

44

Page 45: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

I t

2=∑i=1

n

(SM ti+2 SEt

i ), where SM t

i=1 , if at the moment t indicator i gave “soft” signal

and SEti=1 , if at the moment t indicator i gave “rough” signal4;

I t

3=∑i=1

n

S t− si

, where St−si =1 , if indicator i gave signal during the time line from (t-s) to t;

I t

4=∑i=1

n

S ti /wi

, where w i is a relation of “noise” to signals of indicator i.

Further for each indicator and each t=1…T is possible to determine conditional

probability Pt of the event Ct, t+h, crisis will happen during the time period of [t; t+h] at the

condition that there was a signal:

Ptk=P(C t , t+h|I≤It< I=

= periods when I≤I t< I and crisis happens within h month / periods when I≤I t< I

Further Rt =1 is being set for t=1…T if crisis actually happens during the time period of [t;

t+h] and Rt =0 in the opposite case. Assessment of accuracy of forecasting of all four indexes

showed that the best forecast is made by index I4. Besides author discovered that the cumulative

index allows for better forecasting crises than separate indicators.

In their work Kaminsky and Reinhart (Kaminsky, Reinhart, 1999) continue to examine

banking and currency crises in industrial and developing countries, which happened during the

period of 1970-1995. Specifically they pay attention to the situations when currency and banking

crises happen simultaneously, i.e. so called “crises-twins” take place. Identification of the

currency crises is made with help of the index equal to weighted average value of the

fluctuations of the exchange rate and gold and foreign currency reserves. By the beginning of the

banking crisis, it was considered a case of massive withdrawal of deposits, or merger or

acquisition of one or more financial institutes by the government.

For the analysis of the currency rises the signal window was chosen starting with 24

months before the crisis and finishing with its start; for banking crises signal window included

12 months prior to crisis and 12 months after.

In that article authors test the same indicators as were used in the previous studies.

4 “Rough” threshold values increased in comparison with the “soft” values on some exogenous set value.

45

Page 46: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

Threshold levels are also selected in such a way that relation of the noises to the “good” signals

was minimal. Conducted analysis shows that variables characterizing capital movements are

good to predict currency crises. Variables of the real sector are more useful for forecasting

banking crises.

Edison (Edison, 2000) also makes an attempt to establish a system of early alarming

signals which could be useful in forecasting financial crisis. His judgments mostly comes

works by authors Kaminsky, Lizondo and Reinhart (Kaminsky, Lizondo, Reinhart, 1998),

which were broadened in few directions. Edison examines following indicators:

Indicators of current account positions: real exchange rate, import, export.

Indicators of capital transactions account: gold and foreign currency reserves, relation of

the money supply to gold and foreign currency reserves; spread between domestic and

world interest rate.

Indicators of real sector: GDP in real terms, stock market index.

Financial indicators: monetary multiplier, relation of domestic credit to GDP, real

interest rate on deposits, relation of credit interest rate to deposit interest rate, excessive

money supply, deposits of the commercial banks.

Edison analyses financial crises from 1970−1998. He established the same threshold

levels as Kaminsky and her colleagues. With that, he showed analysis of the dynamics of the real

exchange rate, export and relation of money supply to GDP are better to forecast financial crisis.

An alternative approach on the definition of threshold levels (1.5 standard deviations

from the average value) was offered which allows the determination of a few well working

indicators. But as a whole, results were significantly worse than at defining threshold levels on

the base of the “noise” minimization to the “good” signals.

Besides, Edison used consolidated indexes used by Kaminsky (Kaminsky, 1999). His

analysis showed that in many countries these indexes actually increase before the crisis. He

concluded that it is impractical to fully rely on such approach because of the large dispersion

of indexes and problems of their interpretation.

Hawkins and Klau (Hawkins and Klau, 2000) also make an attempt to establish

consolidated advancing indexes of financial stability. For forecast of approaching financial

instability authors suggest to use three consolidated indexes: speculative pressure index, index of

eternal exposure, and index of the exposure of the banking system. Methodology of the index

46

Page 47: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

calculation is presented in detail in Appendix 1.

The authors analyzed indexes dynamics of those countries which suffered from the

Russian crisis, crises in Asia and Latin America and showed that examined indexes allow

making statistically valid forecast of financial instability.

Thus, in this chapter, I reviewed the main approaches of examination of indicators

which allow a signaling before approaching financial crises.

CHAPTER 3

Development of the framework of signaling indicators

Literature review from the first two chapters helped to determine main analysis

approaches of the financial stability indicators and define their threshold levels which would

mean financial instability in the short-run. These approaches include: qualitative analysis,

econometric analysis and non-parametrical methods of analysis which include establishment of

consolidated indicators

Qualitative analysis is conjugated with substantial subjectivity in interpretation of the

dynamics of the signaling indicators. That is why to my opinion it is necessary to develop some

quantitative characteristics which would facilitate the monitoring of the financial stability to

more objective one. Literature review on the subject allows the argument that there are two main

ways of creating of such characteristics – econometric modeling and non-parametric evaluation.

Econometric modeling is based on the scoring models of binary selection with different

indicators of financial instability used as exogenous variables. In this paper I discard econometric

analysis due to the following reasons.

First, in comparison with non-parametric evaluation methodology of econometric analysis

is significantly more complicated and requires implementation of the large number of theoretical

prerequisites in respect of the origins of the data used. At the same time methodology developed

in this paper is relatively simple and its results are easy to interpret.

Second, literature review of the applicability of econometric models in terms of

probability evaluation of the financial instability show that in spite of the examination of the same

episodes of the crisis events, results of different authors differ significantly in relation to the

choice of the best signaling indicators and selection of the threshold levels. Choice of a particular

47

Page 48: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

econometric model and interpretation of its results for monitoring of financial stability purposes

will be no more objective than simple qualitative analysis of indicators. None of the scientific

works reviewed demonstrate an advantage of econometric evaluation in comparison to non-

parametric methods.

Third, by virtue of non-linearity of the models of binary selection it seems to be more

complicated to evaluate the input of each of the regressors in the increase of probability of the

financial instability in the case of actual value of indicator is significantly deviated from the

average value.

Finally, for obtaining statistically significant results it is necessary to examine bigger

number of the crisis events. In case of Russian Federation, there were only four episodes on

which the statistical data is available. These are: crisis of interbank credit market in August,

1995, the crisis of the stock market in October, 1997, full scale financial crisis in August, 1998

and creditability crisis to the banking system in May, 2004. It is obvious that four crisis episodes

are not enough for the evaluation of the model of binary selection. Model evaluation on panel

data, i.e. with the use of data from the other crisis events in other countries, on my opinion is not

acceptable because it will significantly decrease the strength of a test whereby the crisis

probability is evaluated. In spite of the common features, crises in different countries have many

specific features due to the differences in national economies. That is why the dynamics of the

indicators of financial stability before the crises differ in each different country.

Therefore, econometric methods of the model’s evaluation are related to the specifications

of the task. They are determined by the following factors:

Crises in different countries are not homogeneous enough which prevents consolidation

of previous experiences;

Each case has its own unique characteristics; some features that can point on the

vulnerability of economy, cannot be measured mathematically;

Necessary data is not available;

With time crises determinants can significantly modify and change.

Thus, I will adhere to non-parametric methods. Obviously, these methods have their own

limitations. In particular, it is harder to use standard statistical test through implementation of

these methods. Most of the scientific research devoted to forecasting financial instability uses

the so called “signaling approach”, which was first introduced in the research of Kaminsky,

48

Page 49: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

Lizondo and Reinhart (Kaminsky, Lizondo and Reinhart, 1998). That is why in my work I will

make an attempt to adapt “signaling” approach for establishing the framework of indicators of

financial instability on the Russian Federation market.

Besides the search of indicators dynamics of which is the best way to reflect approaching

financial instability, it is important to develop some consolidated indicator of financial stability,

which would accumulate all information gathered from the separate signaling indicators. In my

empirical part of my work I will analyze the dynamics of different consolidated indexes of

financial stability and will choose those which are the most practical for the analysis of the

Russian financial market.

3.1. Signaling approach

The analysis of theoretical and empirical aspects of the interrelation of different macro-

and microeconomic variables and the probability of the financial system crisis allows for the

identification of a series of variables which can be used as the signaling indicators:

Rate of economic growth: GDP growth ratio, dynamics of industrial output

Balance of payments: current account balance, gold and foreign currency reserves,

foreign debt, terms of trade (export prices), export and import, real effective exchange

rate, capital outflow.

Interest rates: real exchange rate, difference between world and domestic interest rates

in real terms, relation of credit rate to deposit rate.

Monetary indicators: customer price index, dynamics of the domestic credit in real terms,

monetary multiplier, relation of monetary supply to gold and foreign currency reserves,

growth ratio of deposits in real terms, excessive money supply in real terms, speculative

pressure index

It should be noted that in practice not all indicators can be used for the analysis of the

financial system stability because statistical data on some variables may not be available. Each

approach to the analysis of indicators should be subjective, i.e. with the use of expert estimation

and information about market conditions which cannot be presented in terms of quantity

variable. That is why a distribution of indicators for different sectors of the financial market is

relatively conditional and most of attention should be paid to the overall economic condition in

49

Page 50: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

the country.

Literature overview shows that financial crises are usually preceded by negative trends of

the main macroeconomic indicators. Therefore, a system of signaling indicators should include

variables that allow estimating the overall situation in the country. When available statistical data

on the separate sectors of the financial market is limited by a small number of indicators, the

variables obtained have especially significant meaning. Let’s take a closer look at these

indicators.

Economic growth. Rate of economic growth is the key index of economic dynamics ,

which permits judgment of how successfully the economy will expand. GDP growth ratio in

real terms and dynamics of industrial production are suggested to use as main signaling

indicators.

It is assumed that a slowdown of economic growth reduces the ability of national

borrowers to pay off their debts and therefore increases credit exposure. Recessions often precede

major financial crises.

Balance of payments indexes. Main indexes of balance of payments provide details

which enables a timelier manner of information about an increasing probability of currency crisis.

This also allows the following up of information leading to approaching external shocks.

In particular, an increase of ratio of current account balance to GDP usually leads to

significant export revenues inflow in the country which gets absorbed by the financial system. At

the same time, substantial deficit on current account may provide a signal about increasing

probability of a currency crisis and reduction on liquidity of the financial system. In turn, an

increase of exchange risks is able to cause short-term investment outflow and worsen financial

instability. Moreover, a downswing of gold and foreign currency reserves or increase of

foreign debt is also considered as an obvious sign of financial instability.

Scientific evidence justifies that substantial deterioration in terms of trade leads to

difficulties in the financial sectors in many countries. Small economies with heavy dependence

from the export of raw materials and resources are the most vulnerable to shifts in world market

conditions. Real effective exchange rate is closely related to the terms of trade; its increase leads

to deterioration of competitiveness of domestic producers and might lead to a slowing down of

the rate of economic growth or recession.

Moreover, substantial acceleration of capital outflow may signal approaching

50

Page 51: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

instability, which causes pressure amplification on the exchange rate of the national currency .

Finally, export and import dynamics are used as stability indexes of the balance of

payments. Usually currency crises were preceded by a reduction of exports and increase of

imports.

Interest rates are the fundamental characteristics of the financial market. Understanding

their dynamics provides monitoring towards the stability of the financial system and notifying at

a reasonable time about emerging problems.

Real interest rate is the most important index of the group. An increase in the real interest

rate results in an increase of instability of the financial system and encourages growth of

coefficient of non-working debt. At the same time, a sustainably negative real interest rate speaks

about existing disproportions in the financial system. One reason might be an attempt of the

government to fixate nominal interest rate. It makes sense to analyze the volatility of the interest

rate along with its level. An increase of volatility of the interest rate speaks about increase of

interest rate risk; and therefore, about increase of instability of the financial system.

Besides national interest rate, international interest rates also play an important role for

the financial system. Increase of the world interest rate increases vulnerability of the national

financial system. This is because capital outflow from the developing markets to developed

countries takes place, worsening the creditworthiness of borrowers on the developing markets (at

foreign currency loans). That is why in the number of signaling indicators of financial crisis

included spread between domestic and foreign interest rate.

Finally, the relation of credit rate to deposit rate is being analyzed. Before currency crises

start enlargement of spread between credit rates and deposits was observed in many of the cases.

It is because domestic credit growth precede currency crisis . In this situation the share of “bad”

credits grows and banks raise credit rates trying to compensate possible losses from outstanding

loans. Deposit rates also rise but in a lower proportion.

Monetary indicators. Analysis of monetary indicator dynamics might be extremely useful

in forecasting crisis in the financial system. Thus, acceleration of rate of growth of consumer

prices before a crisis is possible. Besides, rapid growth hinder estimation of the credit risk and

enhances uncertainty. Sharp drops of inflation can also lead to the decrease of nominal yield and

cash flows, which can erode stability of the financial institutes.

Financial crisis are often preceded by the expansion of the domestic credit, including an

51

Page 52: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

increase of the share of “bad” loans. That is why relation of domestic credit to GDP is included

in the list of possible signaling indicators. Excessive money supply in real terms (considerable

extent of which speaks about increased possibility of the financial crisis) is defined as a deviation

of weighted money demand from observed money supply (expressed as a share of the money

quantity in GDP).

One of the most important indicators in this group is the relation of deposits to the money

supply. Decline of this relation index might signal a loss of creditability to the banking system

and as such lead to occurrence of liquidity crisis. At the same time, a decline of the indicator may

signal that financial institutions other than banks are more effective.

The relation of credits to deposits can illustrate the ability of the banking system to obtain

the means necessary for the demand satisfaction on loans. High value of the index might justify

problems in the banking system and low level of liquidity.

Finally, the monetary multiplier also is able to signal instability of the financial system.

Considerable growth of a multiplier might be the sign of weakening of selection procedure of

fund receivers by the commercial banks. At the same time, in many of developing economies,

including Russia, this index is still on a relatively low level in comparison with the developed

countries, that is why its dynamics should be interpreted carefully.

Speculative pressure index was included in the list of signaling indicators for the

monitoring purposes of the situation on the exchange market. This index is an aggregated index

and allows evaluating stability of the exchange rate of the national currency in a short-run5.

Such index presents a weighted-average of the three variables:

1) Increase rate of the exchange rate of the national currency per month, E ;

2) Increase rate of gold and foreign currency reserves (reversed in sign), R ;

3) Level of the interest rate (for Russia it is a weighted-average interest rate on the ruble

credits to corporate entities in the lending institutions), i.

Two last variables reflect fiscal and monetary policy of the governmental bodies on the

exchange market in case of the speculative attack on the exchange rate of the national currency.

It is assumed that at the fixed exchange rate speculative attack on the exchange rate will

appear as a decrease of the gold and foreign currency reserves. At the same time at any given

regime of the exchange rate, for the protection of national currency the central bank may raise

5 This index was first introduced in the article of (Eichengreen, Rose, Wyplosz, 1995)

52

Page 53: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

interest rates. It is taken in account through including in the formula to calculate third variable.

Thus, speculative pressure index is calculated in a following way:

I=w1 E+w2 (−R )+w3 i

3 (14)

Weightsw1 , w2 , w3 , are picked up so that dispersion of all three values were equals, in

other words, D(w1 E)=D(w2 R )=D (w3 i ). Therefore, taking w1=1 , w2=√ D( E )

D( R),w3=√ D ( E )

D( i) .

Statistical methods of time series analysis are used for the composition of this indicator.

Researchers who offer formulas for the calculation of this index considered two threshold

levels, exceeding any of each was assessed as a thread of the currency crisis: mean value of

index through the entire period and value equal to three standard deviations.

In most of the cases I use growth ratios of the variables or examined their relation to GDP

to ensure the comparability of data. In some cases variables described in levels were used

because in such form they show the most prognostic power. Table 4 (Appendix 2) presents the

description of the transformation of the signaling indicators, report frequency and source of

information.

Further of the analysis of the signaling approach I will observe some methodological

matters related to it.

Monitoring instruments. Main advantage of the “signaling approach” is that assessment

of the predictive value of each of indicators is proceeded individually, which allows to range the

variables. Moreover, this methodology can be used for the development of the present economic

policy, because the variable that signals might be defined precisely. Risk probability in this

methodology is represented as a binary function of the indicators value, which takes 0 value

when indicator variable is less than threshold level and it takes value 1 in opposite case. Thus,

this model does not recognize cases when variable exceeded threshold insignificantly and when

it is significantly more than a threshold level.

Thus, the offered system of indicators is mostly based on the “signaling approach”. At

the same time, statistical and econometric methods are used to compose certain indicators. In

particular, according to Kaminsky, Lizondo, Reinhart (Kaminsky, Lizondo, Reinhart, 1998)

methodology, excessive real money supply (significant value of which signals about high

53

Page 54: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

possibility of the financial crisis) is defined as a deviation of weighted money demand from

observed money supply (expressed as a share of the money quantity in GDP), i.e. as the remains

of the regression equation of the following form:

M t

GDPt=a0+a1Y t+a2 Δpt+a3 t+εt ,

(15)

where, Mt - money supply M2; GDPt – nominal GDP; Yt – GDP in real terms; Δpt - consumer

price index; t – time. In this equation

M t

GDPt reflects observed money supply, while expression

from the rights reflects money demand. Thus, remains ε t are interpreted as the variable of

excessive money supply, i.e. difference between money supply and demand.

Monitoring frequency. Signaling approach describes signal as an exit of one of

indicators threshold levels. If indicator signals during the certain period of time before crisis, so

called “signal window”, then such signal is considered “good”. If indicator signals and critical

events do not happen during the certain period of time, then this signal is considered “bad”.

The most preferable monitoring frequency is set up exogenously and signal window in 3

months before the crisis. A large signal window is not practical because situations in the

financial market are highly volatile and change quickly. In other words, I believe that negative

tendencies which can potentially lead to the financial instability are possible to determine 1-2

quarters before their occurrence. Besides, if these negative tendencies arise earlier, then closer to

the potential date of financial instability they will only get stronger and at the same time noted

period of time is relatively enough to neutralize negative influences. Thus, quarter monitoring

allows timelier notification of negative tendencies in the financial system of the country and

permits the taking of preventive measures to ensure financial stability.

Moreover, quarters are the optimal window because data for most of variables is not

published more frequently than this. Thus, I will analyze indicators of the financial stability on a

quarterly basis, though for the maximum revelation of their dynamics I will use monthly statistic

data if available.

What concerns time series necessary for the accumulation of the critical changes of each

of the signaling indicators, I assume that such period is two-three quarters. Such conclusion is

54

Page 55: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

drawn from the scientific evidence. Unfortunately, like in many other cases while creating

system of indicators it is not possible to evaluate this period quantitatively because of the

absence of the necessary statistic data.

Threshold values. Signaling approach assumes the necessity of the test of the zero

hypothesis that economy is at its normal stage of development against alternative hypothesis that

within 3-6 months it will experience financial instability. Just like with testing any statistical

hypothesis it is necessary to select some critical value which divides indicators distribution on

two zones6. If indicator’s value hits critical zone, exceeds threshold level, then it is considered

and noted indicator signals.

The question of defining the level of indicators typical for the normal functioning of the

financial system is very difficult. It also concerns threshold values exceed of which will allow to

talk about high probability of the financial crisis in a short-run. The situation is possible when

the same dynamics of the indicators will signal equally about increasing probability of the

financial crisis and normal development of the financial system at the same time. Analysis each

of indicators and explanation of its dynamics separately seem to be the most sensible approach in

this case. Then obtained information will be put together drawing an overall situation in the

economy and finally the conclusion about high/low probability of the financial crisis is made.

I will analyze indicator’s dynamics and conclude that variable’s behavior shows high

probability of the crisis in a short-run if there will be an observation of high increase/decrease of

the variable’s value (in dependence from the theoretical hypothetic behavior of the indicator

before the crisis).

Threshold levels are defined in such way so that on the one hand they maximize the

amount of “good” signals, and on the other hand, minimize “noise” signals, i.e. when an

indicator signals and nothing happens within “signal window”. In that case if it is not possible to

set up a threshold level for an indicator that would ensure acceptable level of “good” signals with

the set level of “noise”, such indicator will be excluded from examination.

For the optimal choice of threshold level for each of the indicators it is necessary to set

up some criteria. Relation of share of “bad” signals to the “good” signals will be criteria of that

kind. To explain this criterion all values of indicator will be divided in four groups presented in

the table below. Obviously, in case of ideal indicator its values will fit cells A and D only.6 I will test single-sided hypothesis, i.e. I assume that either increase or decrease of the variable’s value can justify increasing probability of the financial instability.

55

Page 56: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

Table 2

Distribution of the indicator’s values during the signaling process

There is a crisis in 3 months No crisis in 3 months

Signal A B

No signal C D

Unconditional probability of the financial instability for each of indicators is set as

relation of observations after which financial instability followed within 3 months to all

observations:

P(C )= A+CA+B+C+ D

,

(16)

If indicator sends big amount of “good” signals, has good working capability, then it can

be expected that probability of financial instability at the condition of the signal P(C | S )

(conditional probability) will be higher that unconditional P(C). With that

P(C|S )= AA+B

,

(17)

In other words, it makes sense to use indicator for forecasting financial instability if

following correlation is fulfilled:

P(C|S )> P(C ) (18)

This condition is necessary for the selection of the optimal threshold level. Moreover,

the relation of “bad” signals to “good” ones is minimized in the following way:

N / S= B /( B+D)A /( A+C )

(19)

Thus, possible threshold levels for each indicator are described and a threshold was

selected at which variable values (18) was minimal and condition (17) was fulfilled. Notably, in

some cases relation of “bad” signals to “good” ones is equal 0 because share of “bad” signals

56

Page 57: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

equals 0 too, however if the indicator is not sensitive enough, i.e. does not signal before many of

critical events. That is why at the selection of indicators and threshold levels it is necessary to

pay attention on the share of crises (PC) which indicator predicts. In other words, to identify if a

given indicator signals within the given period of time before the crisis at least once.

In the next two sections I will analyze the performance capacity of the offered system of

signaling indicators on the example of the financial system of Russian Federation, establish

indexes of financial stability, and after will conduct an analysis of the financial stability in

former Soviet republics and transitional economies around the globe.

3.2. Analysis of operational capacity of the potential signaling indicators based on the

example of Russian Federation in 1994-2009

Methodology of signaling approach described earlier allowed receiving of the results

presented in Table A1 (Appendix 1). It was possible to calculate quantitative characteristics for

all indicators, except foreign state debt and dynamics of industrial output which do not have

enough of the statistical information. Threshold values were defined on the basis of the data

analysis from the period of 1994–2009 (with account of their availability on some variables).

In Table A1 variables are ordered according to their prognostic power, which is in excess

of conditional probability of financial instability over unconditional. In other words, the better

the indicator, the higher the probability of financial instability under conditions of a given signal,

and therefore, excess of this probability over unconditional probability because unconditional

probability does not depend from the choice of threshold value. Differences in unconditional

probability are determined only by the fact that different indicators have different amount of

data.

Received results allow a conclusion that use of all indicators except net capital outflow

allows the forecasting of financial instability with probability surpassing unconditional.

However, in my opinion it makes sense to set some limit of such excess so it will not be beyond

the scope of statistical error. Such a limit could be the difference between conditional and

unconditional probabilities of financial instability in size of 5%. In that case good indicators will

be first 13 from Table A1.

57

Page 58: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

In spite of a relatively high working capability of offered framework of indicators,

examination of received statistical characteristics of signaling indicators still can result in a

question of their effectiveness as most indicators predict no more than a half of crisis

episodes; and increase of conditional probability of financial instability in comparison with

unconditional for some indicators does not exceed 5–10%. Of course it is necessary to

understand limitations of the offered framework. In particular, this methodology gives only

certain information about occurring tendencies on the financial market, but does not show that

financial crisis will happen for sure. Analysis of the signaling indicators allows a monitoring of

long-term tendencies in the economy. Separate negative tendencies can be compensated by

advantageous factors in the short-run. At the same time the market slump accumulated negative

events in the economy can cause financial instability in the end.

Table 3 and Appendix 2 present the condition of the framework of signaling indicators of

financial instability prior to crises events in Russian Federation. These tables are based only on

working indicators, the first 13 from the Table A1.

Table 3

Condition of the framework of signaling indicators before the crisis episodes in Russian

Federation

Crisis Number of indicators

with statistical data

available prior to

crisis

Number of indicators

which signaled during

3 months period prior

to crisis

Share of indicators

which signaled in total

amount of indicators,

%

Crisis of interbank credit

market in 1995

12 5 42

Crisis of the stock market

in 1997

13 6 46

Currency crisis in 1998 13 9 69

Creditability crisis to the

banking system in 2004

13 5 38

From Table 7 it is clear that biggest amount of indicators signaled about an approaching

financial crisis in 1998. It is an expected result because the noted crisis event had the largest

58

Page 59: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

scale of all events examined. Around 40% of indicators signaled prior to the rest of the episodes.

It is possible to see from the conducted analysis in the previous chapters that one of the

most difficult milestones of the construction of the system of signaling indicators is a selection of

the proper variables for the forecasting of crises in each given case. Table A2 of Appendix

shows a number of publications in which indicator was found statistically significant in its

empirical evaluation

In my work I will perform similar test of the operational capability of indicators but for

larger number of indicators, specific to the recent creditability crisis to the banking system in

2004, currency crisis in 1998, crisis of the stock market in 1997 and crisis of interbank credit

market in 1995. The test outcomes are presented in the table A3 of Appendix.

Thus, after conducting analysis of the operational capability of the potential signaling

indicators of the financial crisis in the Russian Federation and their behavior before the crisis

events which were observed in the past, the data leads to the conclusion which suggested

indicators allows a determining in advance of symptoms of financial instability. Unfortunately,

there is insufficient statistical data for testing operational capability of many indicators

(especially as it concerns variables, specific for the separate sectors of the financial market of

the Russian Federation). Scientific expertise shows that they also play an important role in

forecasting financial instability and therefore must be included in the offered system of

indicators. Moreover, to forecast the type of the crisis is very difficult, that is why it is needed to

analyze a whole population of offered indicators.

As it was mentioned previously, during crisis events indicators do not equally work well,

in other words in separate cases we can observe negative tendencies in the dynamics of

indicators, which might not be followed with the crisis events afterwards, so called “false

alarm”. Moreover, the situation is possible when indicators remain stable in spite of an existing

obvious crisis event, or so called “ignored event”, but it is not a sign of their bad quality .

Because of the diverse behavior of indicators through different types of crises it seem to be not

possible to set up some absolute threshold level after exceeding which crisis occurrence become

inevitable. In proportion to accumulation of necessary statistical data the next step of the

development of the system of signaling indicators must be a development of more formal

procedure of indicators selection and evaluation of their quality.

In regards to an offered system of indicators, before the liquidity crisis in the banking

59

Page 60: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

system of Russian Federation in 2004, the relation of operational indicators to non-operational

was 7:9, which is a relatively good result because it suggested variables are aimed to signal about

the problems in all sectors of the financial system of the Russian Federation and many of them

simply do not fit to forecast critical events specifically in the banking sector. At the same time,

after crisis in 2004 the offered system did not give false signals about the crisis events.

3.3. Composition of the indexes of financial stability

In the previous chapters 13 signaling indicators of financial stability were selected which

allowed forecasting of the best critical eposides which took place in the Russian Federation.

However, in the practical application of these indicators, problems are identified in their

aggregating of their signals for composition of the consolidated indexes of financial stability . In

this section a few variants of calculation of these indexes will be offered and I will try to select

the best one on the base of defined criteria.

Let’s define X vector which consists of the values of 13 selected indicators. Previously it

was mentioned that indicator Xjsignals during the period t (dummy variable St

jtakes value 1) if

it crosses defined (in the previous section) threshold value Xj:

S tj=1=S t

j ,|X tj|> X j|

(20)

In the expression absolute values X are used because values of some indicators decrease

prior to crisis and some increase. In case of no signal:

S tj=0=S t

j ,|X tj|< X j|

(21)

Thus, we can examine a few consolidated indexes of financial stability which are based

on the indexes offered in the articles of Kaminsky (Kaminsky, 1999) and Hawkins and Klau

(Hawkins and Klau, 2000) Appendix . First index is the sum of all signals at the moment t:

60

Page 61: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

I t1=∑

j=1

13

S tj

(22)

It is clear that this consolidated index does not take in account many factors. For example,

financial instability probability may increase but it does not mean that all indicators will signal

simultaneously. That is why following a graduate accumulation of the problems in economy the

following index will be used:

I t2=∑

j=1

13

S t−s ,tj

(23)

where, St−s , t equals 1 if j indicator signals at least once within S months before the moment t.

Parameter S is set exogenously based on our assumption that crisis symptoms are supposed to

reveal a minimum of 3 months before its start; so it is assumed that S equals 3.

Both of the described indexes are not used to the fullest information received during

setting threshold values of the signaling indicators, because they do not take into account the

forecast precision of each of indicators. The logical approach of accountability of such

information is an indicators’ weighting with help of values equal excess of conditional

probability of the financial instability over the unconditional in case of the signal:

I t3=∑

j=1

13

S tj( P j(C|S )−P j(C ))

(24)

Notably, Goldstein, Kaminsky and Reinhart (Goldstein, Kaminsky, Reinhart, 2000) use

as weights values opposite to relations of “bad” signals over “good” one for reach of the

indicators. However some of these values equal 0 that is why I use alternative weights. In my

opinion, the better analysis of the dynamics of indicator allows predicting financial instability in

comparison to unconditional probability of the financial crisis (for example, we can say that

evidence shows that crisis happens in average once in 3 years), then higher weight it should

have.

After calculating the value of each of the three indexes during the certain period of time,

61

Page 62: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

we can calculate their threshold values the same way as it was done for the signaling

indicators. However, such threshold values are able to receive binary information only. In other

words, if the index hits its threshold value it means that with high probability financial instability

will occur within the following 3 months. It is possible to evaluate the probability of financial

instability P(C|I≤I t< I )at different index values:

P(C|I≤I t < I )= AA+B

(25)

where, I – lower interval limit, for which probability of financial instability is calculated; I –

upper interval limit; A – equals to number of cases when index value was in the interval [I ; I )

and within next 3 months crisis occurred; B equals to number of cases index value was in the

same interval [I ; I ) but crisis events didn’t occur.

Table 3 presents results of empirical distribution of the probabilities of financial

instability in dependence from values of each index. Probability of financial instability decreases

fast and non-linear after indexes achieve relatively high values. In other words, if small amount

of indicators signal, then probability of financial instability is low, although it sharply increases

after accumulation of alarm signals.

Table 3

Probabilities of the financial instability in dependence from the consolidated index values

I1 I2 I3

Index value Probabilities,% Index value Probabilities,% Index value Probabilities,%

0 0,00 0-2 0,00 <0,05 0,00

1 2,17 3-4 2,78 0,06-0,5 1,22

2 2,94 5-8 12,50 0,5-0,7 25,00

3 12,50 ≥9 66,67 0,7-1,53 40,00

4 20,00 1,53-1,6 50,00

5 40,00 ≥1,6 100,00

≥6 57,14

After evaluation of the probabilities of financial instability depending on values of

62

Page 63: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

consolidated indexes the problem of the selection of indicators with the best prognostic power

arises. For evaluation of prognostic power each of the indexes it is logical to evaluate deviation

of empirical probabilities of the financial instability Pt from actual probabilities (that is values of

dummy variable Rt which takes value 1 during three months before the crisis and 0 in all other

cases). Hence, for each of the indexes it is possible to calculate:

Qk= 1T ∑

t=1

T

( Ptk− Rt )

2

(26)

where, k = 1;2;3 is an index for which the prognostic power is calculated, and T equals to the

number of observations.

Table 11 presents values of index Q for all three indexes and the best signaling indicator

(current account balance of the balance of payments) and variable equal to unconditional

probability of financial instability on during the entire examined period of time.

Table 4

Prognostic power of consolidated indexes of financial stability

Index Prognostic power (Q)

Unconditional probability 0,134

Current account balance of the balance of payments 0,130

I1 0,093

I2 0,105

I3 0,074

It is clear that the highest prognostic power has index I3 which takes in account

“operational capability” of each of indicator. Also, all consolidated indexes forecast financial

instability more precisely than the best of signaling indicators. However, this indicator is more

63

Page 64: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

effective as a leading indicator of financial stability than being used for forecasting of

unconditional probability of financial instability.

Thus, conducted analysis allows establishing a framework of signaling indicators of

financial instability which alarms in advance about developing problems on the Russian

financial market. On the basis of previous chapters it is possible to draw the following

conclusions.

First, establishment of a framework of signaling indicators of financial instability is

conceptually possible. In other words, there are some series of the economic variables statistical

analysis allows to forecast occurrences of financial instability in case of the signals given by this

variables with the probability exceeding unconditional probability of the financial instability.

The application of different methodologies of the selection of working signaling indicators give

similar results and it confirms their effectiveness.

Second, in spite of the relatively high working capability of the offered framework, most

of the indicators predict no more than half of the crisis episodes, increase of conditional

probability of financial instability in comparison with unconditional for some indicators does not

exceed 5-10%. That is why limitations of the offered methodology should be accounted and

alternative estimation methods of the financial sector should be used, too.

Third, my research showed that development of the framework of indicators of

financial instability for the particular country and not for the group of the countries allows

increases significantly the working capability of the indicators , which is especially important at

using offered methodology for decision-making by economic agents . Analysis of the

financial market of one country only accounts for its specific features and adopts accordingly

to threshold levels for the signaling indicators. Most working capabilities in the case of Russia

have shown the following indicators: current account balance for the balance of payments, real

interest rate, relation of money supply to gold and foreign currency reserves, real effective

exchange rate of ruble, and excessive money supply in real terms. Their use allows achieving an

increase of probability of financial instability in case of their signals in comparison with

unconditional probability on more than 40%.

Finally, analysis allowed establishment of a consolidated index of financial stability I3

with help of which it is possible to obtain quantitative estimation of the occurrence of financial

instability. Probability of financial instability increases non-linearly in proportion to increase of

64

Page 65: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

the number of signals given by indicators: if a small amount of indicators signal then a crisis

probability remains on the low level, though with the accumulation of the signals probability of

instability on the financial market sharply increases.

In the last chapter an example of the application of the developed framework of

indicators for monitoring financial stability in Russian Federation 1999-2009 will be given.

CHAPTER 4

Monitoring of the financial stability in Russia 2009 (II quarter)

In this chapter I will approximate a system of signaling indicators of financial instability

on the financial markets of the developing countries andl examine the financial market of the

Russian Federation. The main obstacle to conducting the analysis is absence of the relevant

statistical data.

Empirical models observed in the literature review offer a number of economic and

financial indicators for the sensitivity analysis of the analyzing country in relation to the crises

of financial system. Even though theory does not provide an unambiguous answer on what is an

65

Page 66: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

early warning system, the performed research determines those variables which are supposed to

signal an approaching crisis.

Offered analysis allows following up after long-term tendencies in the economy. Thus,

separate negative tendencies in a short-run may be compensated with favorable factors (for

example, in Russia that is a significant budget surplus caused by record oil prices). At the same

time a worsening of the market environment accumulated negative tendencies in economy might

cause financial instability.

Main macro indicators of monitoring, which reflect overall situation in the financial sector

of the country are classified in the following order:

Rate of economic growth: GDP growth ratio, dynamics of industrial output.

Balance of payments: current account balance, gold and foreign currency reserves,

foreign debt, terms of trade (export prices), export and import, real effective exchange

rate, capital outflow.

Interest rates: real exchange rate, difference between domestic and foreign interest rates,

relation of credit rate to deposit rateм.

Monetary indicators: customer price index, dynamics of the domestic credit in real terms,

monetary multiplier, growth ratio of deposits in real terms, relation of money supply to

gold and foreign currency reserves, excessive money supply in real terms.

Speculative pressure index

If not pointed differently, in my work I will confine composition methodology to that

offered in the article of Kamisky, Lizondo and Reinhart (Kaminsky, Lizondo, Reinhart, 1998),

also I will follow closely the Manual of International Monetary Fund ( Compilation Guide on

Financial Soundness Indicators, 2006). Although during the process of selection of the relevant

indicators for the analysis, I took in account results of other similar researches.

In most of the cases I used growth ratios of variables or analyze them in relation to GDP,

which allows ensuring data comparability and also solve the problem of non-stationary time

series. At the same time in a number of cases analysis uses variables expressed in levels because

in that particular way they have most prognostic ability. Table A5 of Appendix 5 shows the

description of changes of indicators, it also includes information about sources of information

and their periodicity.

Dynamics for most of indicators is examined starting from 1999, when a majority of

66

Page 67: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

negative consequences of the financial crisis in 1998 were already overcome. At the same time,

in a number of cases, mostly because of the absence of relevant statistical data, indicators may

be analyzed in a different time range.

For the monitoring of financial stability in Russian Federation the methodology of

quantitative and qualitative analysis of the signaling indicators is used, within which threshold

levels of the indicators were established, and consolidated index of the financial stability was

calculated (which allows estimation of the probability of the financial instability during next

quarter).

For a majority of variables there is no particular threshold level exceeding which will

allow speaking clearly about increase/decrease of the financial crisis probability. Analysis of

signaling indicators is strongly based on the expert evaluations of the current situation . That

is why making a final decision whether indicator signals about increase/decrease of the crisis

probability, is made through taking into consideration a particular current situation in the

economy of the country. Moreover, there are no particular values of indicators which would be

possible to call “normal” for the stable development of the financial system, because depending

on the particular state of economic situation the same value of indicator may either give reasons

to concern or be indicative of normal development.

The consequence of analysis is following: first, the table summarizing monitoring results

on all variables is made. It is followed by the brief description of overall economic situation in

the country, and enclosure includes graphs of all indicators of the monitoring. Tables include

values of respective variables in the time line of few last quarters, allowing comparing changes.

Though they are used only for reference because besides absolute values of variables, while

dividing into groups of “good” and “bad” indicators I took in account seasonality of their

changes, previous dynamics, levels obtained and etc. Though, at the first sight they still allow to

draw some conclusions about current situation in economy of the country.

Russian Federation

Results of the application of the quantity methodology are presented in the table below

which shows: the values of signaling indicators during the period of 2008-2009, threshold levels

and information of the signal. In Appendix 6 and 7 the dynamics of indicators is presented and

grap hically demonstrated when indicators exceeded their threshold levels.

67

Page 68: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

In the first quarter of 2009 the financial system of the Russian Federation was faced

significant difficulties caused by capital outflow from the country, decline of the exchange rate

of ruble and a decrease in economic activity. Just like in the fourth quarter of 2008 in January, 5

out of 13 indicators signaled: GDP growth ratio in real terms, capital outflow, gold and foreign

currency reserves, export and speculative pressure index.

In the beginning of 2009 it was clear that Russia would experience a full scale economic

crisis influenced not only by the financial sector of the economy but the real one too.

Government used funds accumulated over the years to soften the economic downturn. In spite of

some stabilization during spring, monitoring results show a high probability of new problems in

the financial system of Russian Federation within the next half a year. In all likelihood, these

problems might be caused by a further deterioration of world economy and domestic problems

related for example to growth of overdue payments of debts to the Russian banks.

Due to an improvement of foreign economic environment in the second quarter of 2009,

the financial system of the Russian Federation was in better condition than in the beginning of

the year. In comparison to the first quarter, in April-June only 3 out 13 indicators gave signals:

GDP growth ratio in real terms, export and domestic credit in real terms. In my opinion these

indicators demonstrate main threats which Russian economy may face in the short-run. In spite

of some pickup in the financial sector, the situation in the real sector is very complicated, and in

its turn, it will cause further growth of overdue payments on the loans issued to non-financial

sector by banks. Even in the case of recovery of the economy in the medium-term period

outrunning growth of import in comparison with exports most likely will cause a further decrease

of the current account position of the balance of payments, which will increase downward

pressure on the exchange rate of ruble. Moreover, in the conditions of recession increase of

budget expenditures in the end of the year will bring to the stage the problem of inflations.

Thus, in spite of some stabilization in the Russian economy a worsening of the situation

in fall and winter 2009-2010 is very possible. Documented conditions of the framework of

indicators conform to the probability of the increase of scale of financial instability within the

next couple of quarters on the level of no more than 40%. This result means with high

probability of new problems in the financial sector of the Russian Federation within next half a

year.

68

Page 69: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

Conclusion

In my research, the scientific evidences devoted to examination of the causes of financial

crises were examined. Principles of development of the processes individual for the Russian

financial market prior the episodes of financial instability were analyzed. Research was based on

the analysis of the framework of signaling indicators dynamics which allows a determination of

negative tendencies in the financial sector before the crisis.

Presented research includes complex analysis of the problems related to the establishment

of the framework of signaling indicators and draws the following conclusions:

1. Conducted research created a list of working indicators which make sense to test

on the conditions of the Russian financial market. This list includes the following

variables: real exchange rate, GDP growth ratio, dynamics of the domestic credit, money

69

Page 70: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

supply, changes in the consumer prices, terms and trade among others. Examination of

the scientific expertise within the defined field of research demonstrated limitations in the

applicability of the offered methodology of forecasting financial instability. While

established methodology permitted the determination of negative tendencies in the

economy, they are not an absolutely accurate means of identification of the financial

crisis. For a better picture of the situation in the financial sector of the country it is

necessary to use expert evaluation and other methods of the analysis of the financial

stability. At the same time offered methodology does not lose in quality or ability of

forecasting to alternative approaches of the monitoring of financial stability.

2. Conducted analysis of the dynamics of signaling indicators defines a series of

economic variables. The statistical analysis of these variables provides an opportunity to

forecast occurrences of financial instability in the case of alarming signals with

probability exceeding unconditional probability of the financial instability. Engagement

of qualitative and non-parametric approaches of the indicators selection gave a similar

result and all three methods complemented each other.

3. Establishment of the framework of signaling indicators of financial instability for

a particular country instead of a group of countries, allows a significantly increase its

effectiveness, which is especially important for decision making by economic agents.

Analysis of the financial market of one country requires accounting for specific features

of the economy and adapting accordingly the threshold levels of the signaling indicators.

In the case of Russia, the most effective signaling indicators were current account balance

for the balance of payments, real interest rate, relation of money supply to gold and

foreign currency reserves, real effective exchange rate of the ruble and excessive money

supply in real terms. Their use allows with increasing probability of financial instability

in the case of the alarming signal in comparison with unconditional probability of

financial instability on the level of no more than 40%.

4. The consolidated index of financial stability, through which it was possible to

obtain quantitative evaluation, was also established. With that, it turned out that the

probability of the occurrence of financial instability increased non-linearly in proportion

to the increasing number of the signals sent by signaling indicators.

5. Offered methodology permits only a portion of information about developing

70

Page 71: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

tendencies in the financial sector to be received but does not point out whether financial

crisis will happen or not. The offered analysis can be used to monitor medium-term

tendencies in the economy. Thus, negative tendencies in the short-run can be

compensated by favorable factors. At the same time, through a worsening of the

functional conditions, accumulated negative trends can cause financial instability.

Literature

1. Abiad A. Early Warning Systems: A Survey and a Regime-Switching Approach // IMF

Working Paper No.03/32. 2003.

2. Agenor P.-R., Bhandari J.S., Flood R.P. Speculative Attacks and Models of Balance-of-

Payments Crises. NBER Working Papers 3919, 1991.

3 Akerlof G., Romer P. Looting: The economic underworld of bankruptcy for profit // Brookings

Papers on Economic Activity. 1993.

4. Alexander W., Davis J., Ebrill L., Lindgren C.-J. Systemic Bank Restructuring and

Macroeconomic Policy. Washington, D.C.: IMF, 1997.

5. Altman E. Financial Ratios, Discriminant Analysis and the Prediction of the Corporate

Bankruptcy // Journal of Finance. 1968. Vol. 23 (September).

71

Page 72: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

6. Arteta C., Eichengreen B. Banking Crises in Emerging Markets: Presumptions and Evidence //

Financial Policies in Emerging Markets (ed. by M. Blejer, M. Skreb). 2002.

7. Aziz J., F. Caramazza and R. Saldago. Currency crises: in search of common elements // IMF

working paper 00/67. March 2000.

8. Baig T., Goldfajn I. Financial Market Contagion in the Asian Crisis // IMF Staff Paper. 1999.

Vol. 46 (June).

9. Barseghyan L. Non-Performing Loans, Prospective Bailouts, and Japan’s Slowdown. The

Center for Japan-U.S. Business and Economic Studies Working Paper #317. Stern School of

Business, New York University. April 2004.

10. Bell J., Pain D. Leading indicator models of banking crises – a critical review // Financial

Stability Review. December 2000.

11. Berg A., Borenszstein E., G-M/ Milesi-Ferretti and C. Patillo. Anticipating balance of

payments crises – the role of early warning systems. IMF occasional paper No. 186. January

2000.

12. Berg A., Patillo C. Predicting Currency Crisis: The Indicators Approach and an Alternative //

Journal of International Money and Finance. 1999. Vol. 18.

13. Berg A., Patillo C. Are Currency Crises Predictable? A Test International Monetary Fund

Working Paper 98/154. November 1998.

14. Blanco H., Garber P. Recurrent Devaluation and Speculative Attacks on the Mexican Peso //

Journal of Political Economy, University of Chicago Press. Vol. 94(1). February 1986.

15. Brown C.O., Dinç S. The Politics of Bank Failures: Evidence from Emerging Markets. 2004.

16. Caballero R. and Krishnamurthy A. International and domestic collateral constraints in a

model of emerging market crises // Journal of Monetary Economics No. 48. 2001.

17. Caprio G., Honohan P. Restoring Banking Stability: Beyond Supervised Capital Requirement

// Journal of Economic Perspectives. 1999. Vol. 13. 4.

18. Caprio J., Klingebiel D. Bank insolvencies. Cross-country experience. World Bank Policy

Research Working paper. 1620. 1996a.

19. Caprio J., Klingebiel D. Bank insolvency: Bad luck, bad policy, or bad banking? Annual

World Bank Conference on Development Economics. 1996b.

20. Caprio J., Hunter W., Kaufmann G., Leipziger D. Preventing Bank Crisis. Lessons from

Recent Global Bank Failures. Washington, D.C.: The World Bank, 1998.

72

Page 73: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

21. Caprio J. Safe and sound banking in developing countries: We’re not in Kansas more.

Prepared for the Brooking Conference ‘FDICIA: Bank Reform Five Years Later and Five Years

Ahead’ on December 19. 1996, 1997.

22. Caprio G., Martinez-Peria M.S. Avoiding Disaster: Policies to Reduce the Risk of Banking

Crises. Discussion Paper. 2000.

23. Caprio G., Summers L. Finance and Its Reform: Beyond Laissez- Faire’, Policy Research

Working Paper No. 1171. 1993.

24. Carramazza F., L. Ricci and R. Salgado. Trade and financial contagion in currency crises //

IMF working paper 00/55. March 2000.

25. Chari V., Jagannathan R. Banking panics, information, and rational expectations

equilibrium // Journal of Finance. 1988. 43.

26. Chen Y. Banking panics: The role of the first-come, first-served rule and information

externalities // Journal of Political Economy. 1999. 107.

27. Compilation Guide on Financial Soundness Indicators. IMF. July 2004.

28. Corsetti G., P. Pesenti and N. Roubini. Paper tigers? A model of the Asian crisis // NBER

Working Paper No. 6783. November 1998.

29. Cumby R.E., Wijnbergen S. van. Financial Policy and Speculative Runs with a Crawling

Peg: Argentina 1979–1981 // Journal of International Economics. Vol. 27. No.1/2. August 1989.

30. Davis E.P. Institutional Investors, Unstable Financial Markets and Monetary Policy // Risk

Management in Volatile Financial Markets (ed. By F. Bruni, D.E. Fair, R. O`Brien), 1996.

31. Demirguc-Kunt A., Detragiache E. Financial liberalization and financial fragility. Prepared

for the 1998 World Bank Annual Conference on Development Economics. 1998a.

32. Demirguc-Kunt A., Detragiache E. The determinants of banking crises in developing and

developed countries. IMF Staff Papers. 1998b. 45.

33. Demirguc-Kunt A., Detragiache E. Cross-Country Empirical Studies of Systemic Bank

Distress: A Survey. IMF Working Paper. May 2005.

34. Deutsche Bundesbank. The role of economic fundamentals in the emergence of currency

crises in emerging markets. Deutsche Bundesbank Monthly Report. April 1999.

35. Diamond D.W., Dybvig P.H. Bank Runs, Deposit Insurance, and Liquidity // Journal of

Political Economy. 1983. Vol. 91 (June).

73

Page 74: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

36. Dornbusch R., Goldfajn I., Valdes R.O. Currency Crises and Collapses. Brookings Papers on

Economic Activity: Macroeconomics 2. Brookings Institution. 1995.

37. Dornbusch R. Expectations and Exchange Rate Dynamics // Journal of Political Economy.

1976. 84. December.

38. Dornbusch R. Collapsing Exchange Rate Regimes // Journal of Development Economics.

1987. Vol. 27. October.

39. Drees B., Pazarbasioglu C. The Nordic banking crisis. Pitfalls in financial liberalization?

IMF Occasional paper. 161. 1998.

40. Edwards S., Vegh C. Banks and macroeconomic disturbances under predetermined exchange

rate // Journal of Monetary Economics. 1997. 40.

41. Eichengreen B., Rose A. Staying afloat when the wind shifts: External factors and emerging-

market banking crises. NBER Working paper. 6370. 1998.

42. Eichengreen B., Rose A., Wyplosz C. Exchange market mayhem. The antecedents and

sftermath of speculative attacks // Economic Policy. 1995. October 1995.

43. Eichengreen B., Rose A., Wyplosz Ch. Contagious Currency Crises. NBER Working Paper

No. 5681. July 1996.

44. Enoch C., Green J. Banking System and Monetary Policy. Issues and Experience in the

Global Economy. Washington, D.C.: IMF, 1997.

45. Esquivel G. and F. Larrain. Explaining currency crisis. Harvard Institute for International

Development. June 1998.

46. Evans O., A. Leone, M. Gillard and R. Hilbers. Macroprudential indicators of financial

system soundness. IMF occasional paper No. 192, April 2000.

47. Fisher I. The Debt-Deflation Theory of Great Depression // Econometrica. 1933. Vol. 1

(October).

48. Flood R., Marion N. Perspectives of the Recent Currency Crisis Literature. NBER Working

Paper No. 6380 (Cambridge, Massachusetts, MIT Press). 1998.

49. Flood R., Garber P. Collapsing Exchange-Rate Regimes: Some Linear Examples // Journal of

International Economics. 1984. Vol. 17.

50. Flood R., Garber P. Linkages between Speculative Attack and Target Zone Models of

Exchange Rates // Quarterly Journal of Economics. 1991. Vol. 106.

74

Page 75: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

51. Flood R.P., Marion N. Speculative Attacks: Fundamentals and Self- Fulfilling Prophecies.

NBER Working Paper 5789. 1996.

52. Flood R.P., Robert J. Hodrick. Real Aspects of Exchange Rate Regime Choice with

Collapsing Fixed Rates // Journal of International Economics. 1986. Vol. 21. November.

53. Flood R., Garber P., Kramer. Collapsing Exchange Rate Regimes: Another Linear

Example // Journal of International Economics. 1996. 41. No ¾. November.

54. Flood R., Marion N. A Model of the Joint Distribution of Banking and Exchange Rate Crises

// IMF Working Paper No. 01/213. 2001.

55. Flood R.P., Marion N. Perspectives on the Recent Currency Crisis Literature // International

Journal of Finance and Economics. 1999. Vol. 4. No. 1.

56. Frankel J.A., Rose A.K. Currency Crashes in Emerging Markets: An Empirical Treatment //

Journal of International Economics. 1996. Vol. 41 (November).

57. Frankel J.A., Rose A.K. Currency Crashes in Emerging Markets: Empirical Indicators.

NBER Working Paper No. 5437 (Cambridge, Massachusetts, MIT Press). 1996.

58. Fratzscher M. Why Are Currency Crises Contagious? A Comparison of the Latin American

Crisis of 1994-1995 and the Asian Crisis of 1997-1998 // Weltwirtschaftliches Archiv. 1998.

Vol. 134. 4.

59. Fratzscher M. What Causes Currency Crises: Sunspots, Contagion or Fundamentals?

European University Institute Department of Economics. EIU Working Papers 99/39. 1999.

60. Fratzscher M. On Currency Crises and Contagion // International Journal of Finance and

Economics. 2003. Vol. 8. No. 2.

61. Freixas X., Rochet J.-C. Microeconomics of Banking. Cambridge. MIT Press, 1997.

62. Gerlach S., Smets F. Contagious Speculative Attacks. CEPR Discussion Papers 1055.

C.E.P.R. Discussion Papers, 1994.

63. Glick R. and R. Moreno. Money and Credit, Competitiveness, and Currency Crises in Asia

and Latin America. Centre for Pacific Basin Monetary & Economic Studies working paper

PB99–01,

64. Goldberg L.S. Collapsing Exchange Rate Regimes: Shocks and Biases. NBER Working

Paper 2702. Cambridge, Massachusetts: National Bureau of Economic Research, 1998.

65. Goldberg L.S. Predicting Exchange Rate Crises: Mexico Revisited // Journal of international

Economics. 1994. 36.

75

Page 76: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

66. Goldstein M., Kaminsky G.L., Reinhart C.M. Assessing Financial Vulnerability: An Early

Warning System for Emerging Markets. Institute for International Economics, 2000.

67. Goldstein M., Turner P. Banking crises in emerging economies: Origins and policy options.

BIS Economic Papers. 1996. 46.

68. Gonzalez-Hermosillo B., Pazarbasioglu C., Billings R. Determinants of banking system

fragility: A case study of Mexico. IMF Staff Papers. 1997. 44.

69. Guttentag J., Herring R. Credit Rationing and Financial Disorder // Journal of Finance. 1984.

Vol. 39 (December). Federal Reserve Bank of San Francisco. 1999.

70. Hardy D., Pazarbasioglu C. Leading indicators of banking crises: Was Asia different? IMF

Working paper. 98/91. 1998.

71. Hausmann R., Rojas-Suarez L. Banking Crises in Latin America. Washington, D.C.: IADB,

1996.

72. Hawkins J., Klau M. Measuring Potential Vulnerabilities in Emerging Market Economies.

BIS Working Paper 91. October 2000.

73. Hawkins J., Klau M. Early Warning Indicators for Emerging Economies. Paper prepared for

Irving Fisher Committee conference. 20–22 August 2002. Basel.

74. Hayashi F., Prescott E.C. The 1990s in Japan: A Lost Decade // Review of Economic

Dynamics, Academic Press for the Society for Economic Dynamics. Vol. 5(1). January 2002.

75. Heffernan S. An econometric model of bank failure // Economic and Financial Modelling.

Summer 1995.

76. Heffernan S. Modern Banking in Theory and Practice. John Wiley & Sons, 1996.

77. Herrera S. and C. Garcia. User`s Guide to an Early Warning System for Macroeconomic

Vulnerability in Latin American Countries. World Bank Working Paper 2233. November 1999.

78. Honohan P. Banking System Failures in Developing and Transition Countries: Diagnosis and

Prediction. BIS Working Paper . 39. 1997.

79. Hutchison M., McDill K. Are all banking crises alike? The Japanese experience in

international comparison. NBER Working paper. 7253. 1999.

80. International Monetary Fund. Chapter IV: Financial crises: characteristics and indicators of

vulnerability. World Economic Outlook. May 1998.

81. International Monetary Fund. International Capital Markets. September 1999.

76

Page 77: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

82. International Monetary Fund. Early warning system models: the next steps forward // Global

Financial Stability Report. Chapter IV. March 2002.

83. Kamin S. and O. Babson. The contributions of domestic and external factors to Latin

American devaluation crisis: an early warning systems approach. US Federal Reserve System

International Finance Discussion Paper No. 645. September 1999.

84. Kaminsky G. Currency and banking crises: the early warnings of distress // IMF working

paper 99/178. December 1999.

85. Kaminsky G., Reinhart C. On Crises, Contagion, and Confusion // Journal of International

Economics. 2000. Vol. 51. Issue 1.

86. Kaminsky G., Reinhart C. The Twin Crises: The Causes of Banking and Balance-of-

Payments Problems // American Economic Review. 1999. Vol. 89 (June).

87. Kaminsky G., Lizondo S., Reinhart C. Leading Indicators of Currency Crises // IMF Staff

Papers. 1998. Vol. 45 (March).

88. Kaminsky G., Reinhart C. Financial Crises in Asia and Latin America: Then and Now //

AEA Papers and Proceedings. 1998. 98.

89. Kane E. J. The S&L Insurance Mess: How Did it Happen? Urban Institute Press. 1989.

90. Keeley M.C. Deposit Insurance, Risk and Market Power in Banking // American Economic

Review. 1990. Vol. 80 (December).

91. Kodres L., Pritsker M. A Rational Expectations Model of Financial Contagion. Finance and

Economics Discussion Series . 1998–48. 1998.

92. Kruger M., P. Osakwe and J. Page. Fundamentals, contagion and currency crises: an

empirical Analysis. Bank of Canada working paper No. 98–10, July 1998.

93. Krugman P. A Model of Balance-of-Payments Crises // Journal of Money, Credit and

Banking. 1979. Vol. 11 (August).

94. Krugman P. Target Zones and Exchange Rate Dynamics // Quarterly Journal of Economics.

1991. Vol. 106. August.

95. Krugman P., Rotemberg J. Target Zones with Limited Reserves. NBER Working Paper

3418. Cambridge, Massachusetts: National Bureau of Economic Research, 1990.

96. Krugman P. Balance Sheets, the Transfer Problem, and Financial Crises // International Tax

and Public Finance 6. 1999.

77

Page 78: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

97. Lindgren C.-J., Garcia G., Saal M. Bank Soundness and Macroeconomic Policy.

Washington, D.C.: IMF, 1996.

98. Mehrez G., Kaufmann D. Transparency, Liberalization, and Financial Crises. 1999.

Milesi–Ferretti G. and A. Razin. Current Account Reversals and Currency Crises: Empirical

Regularities. IMF working paper No. 98/99. June 1998.

99. Minsky H. Theory of Systemic Fragility // In Altman E., Sametz A. Financial Crises:

Institutions and Markets in Fragile Environment. NY: Wiley, 1977.

100. Mishkin F.S. Understanding Financial Crises: A Developing Country Perspective. NBER

Working Paper 5600. 1996.

101. Muller C., R. Perrelli and M. Rocha. The role of corporate, legal and macroeconomic

balance sheet indicators in crisis detection and prevention // IMF working paper No. 02/59.

March 2002.

102. Obstfeld M. (1984). Balance-of-Payments Crises and Devaluation // Journal of Money,

Credit and Banking. Vol. 16. May.

103. Obstfeld M. The Logic of Currency Crises. NBER Working Paper 4640. Cambridge,

Massachusetts: National Bureau of Economic Research, 1994.

104. Obstfeld M. Models of Currency Crises with Self-Fulfilling Features. NBER Working

Paper 5285. Cambridge, Massachusetts: National Bureau of Economic Research, 1996.

105. Peresetsky .., Karminsky A., Golovan S. Probability of default models of Russian banks.

BOFIT Discussion Papers No 21. 2004.

106. Persaud A. Event risk indicator handbook. JP Morgan. London. January 1998.

107. Radelet S. and J. Sachs. The East Asian Financial Crisis: Diagnosis, Remedies, Prospects.

Brookings Papers on Economic Activity. 1998.

108. Rossi M. Financial Fragility and Economic Performance in Developing Economies: Do

Capital Controls, Prudential Regulation and Supervision Matter? // IMF working paper No.

99/66. May 1999.

109. Sachs J., Tornell A., Velasco A. Financial Crises in Emerging Markets: The Lessons from

1995. NBER Working Paper 5576. Cambridge, Massachusetts: National Bureau of Economic

Research, 1996.

110. Salant St., Henderson D. Market Anticipation of Government Policy and the Price of

Gold // Journal of Political Economy. 1978. 86.

78

Page 79: pure.au.dkpure.au.dk/portal/files/8354/Thesis.docx  · Web viewThis model describes behavior of the commercial bank and its depositors in the ... Because bank assets have different

111. Sargent T., Wallace N. Some unpleasant monetarist arithmetic // Federal Reserve Bank of

Minneapolis Quarterly Review. 1985. 9.

112. Sundararajan V., Balino T. Banking Crises: Cases and Issues. Washington, D.C.: IMF,

1991.

113. Sy A. Rating the Ratings Crises // IMF Working Paper No. 03/122. 2003.

114. Temzelides T. Evolution, coordination, and banking panics // Journal of Monetary

Economics. 1997. 40.

115. Tomczynska M. Early Indicators of Currency Crises. Review of some literature. Studies and

Analysis – Center for Social and Economic Research # 208 – Warsaw, 2000.

116. Tornell A. Common fundamentals in the Tequila and Asian crises // NBER Working Paper

No. 7139. 1999.

79


Recommended