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1 © Prof. Illing Winter 2014/15 Part 1

Monetary Theory

Prof. Dr. Gerhard Illing

M. Sc. Course

Winter Term 2014/2015

Slides Part 1

Introduction Central banks and the role of money


Monetary Theory – Part 1 Introduction Lecture: Prof. Dr. Gerhard Illing

Mo and Wed 10-12 a.m. A 125 Main Building Start: 6.10.2014

Tutorial (2 groups): Matthias Schlegl Fr 8-10 or 10 - 12 p.m. Room A 125 Main Building Start: 10.10.2014

Reading:

Gerhard Illing, Script Theory of Monetary Policy

Walsh, Monetary Theory and Policy, MIT Press

Research Papers (additional course material provided during term)

Exam: 04.02.2015, 10:00 - 12:00, Theresienstr. 39 (B), B 138


Monetary Theory – Part 1 Introduction Aim of the Course:

Understand theory of central bank policy Relate to central bank practise Interaction between fiscal and monetary policy Mechanism design for „optimal“ policy Challenges from liquidity trap and financial crisis

Understand the role of money in macro models Traditional macro models, New Keynesian models; Modeling financial stability concerns

Discuss selected current research topics

Emphasis on rigorously formulated theoretical models, empirical relevance and on economic intuition


Monetary Theory an Policy - Issues Recent Financial Crisis: Rethinking of Monetary Policy Design

Zero Lower Bound; Issue of Financial Stability Central Bank as Lender of Last Resort

Unconventional monetary policy measures: Quantitative Easing (Balance Sheet expansion ~ Financing gov. debt?) Qualitative Easing (Purchase of risky assets; securitisation ~ Socialising private risks or insurance against bad outcome?) Forward guidance: Commitment to keep policy rate at exceptionally low levels for an extended period ~ Impact on long term interest rates?

Raise inflation target? (Bank of Japan Jan. 2013 from 1% to 2 %)

Controversy: Hyperinflation or Deflation? Risk of High Inflation: John Cochrane, Jürgen Stark, Joachim Starbatty; Risk of Deflation: Ben Bernanke, Janet Yellen, Paul Krugman


Inflation and Public Debt

0

100

200

300

400

500

600

700

1921 1931 1941 1951 1961 1971 1981 1991 2001

Zimbabwe: Debt to GDP 1921-2010

-5000

0

5000

10000

15000

20000

25000

30000

1921 1931 1941 1951 1961 1971 1981 1991 2001

Zimbabwe Inflation 1921-2010

020406080

100120140160180

1976 1981 1986 1991 1996 2001 2006 2011

Argentina, Debt to GDP, 1976 - 2012

-5000

500100015002000250030003500

1939 1949 1959 1969 1979 1989 1999 2009

Argentina Inflation 1939-2010


Inflation and Public Debt


Central Bank Balance Sheet Expansion

0

50

100

150

200

250

300

350

400

450

500

2007 2008 2009 2010 2011 2012 2013 2014

ECB Fed BoE SNB BoJ


Euro area

80

100

120

140

160

180

200

220

240

2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012 2013 2013

Euro area, all index 2007=100

Monetary Base M3 credit to non financial firms CPI Germany


Deflation: the good, the bad and the ugly?

0.7

0.75

0.8

0.85

0.9

0.95

1

1.05

1.1

1.15

1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940

Real GDP per capita GDP Deflator

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

1865 1870 1875 1880 1885 1890 1895 1900

Real GDP per capita GDP Deflator

David Andalfatto Who's Afraid of Deflation? Claudio Borio and Andrew J Filardo, Back to the future? Assessing the deflation record, BIS Working Papers, No 152, 2004

U.S. after end of the civil war U.S. Great Depression

http://andolfatto.blogspot.de/2014/09/whos-afraid-of-deflation.html




Central banks and the role of money Standard paradigm for modern policy analysis:

Friedman: Inflation is always and everywhere a monetary phenomenon DSGE models (Woodford 2003; Gali 2008) abstract from the role of money (money as endogenous variable) ~ Cashless economy; interest rate targeting; instability of money demand Critique of ECB‘s two pillar strategy

Key issues: Determination of inflation and price level; Interaction between fiscal and monetary policy; transmission mechanism

Currently: Heated controversy about adequate model/ policy Vehement attacks on policy makers; (Hyper-)inflation vs. deflation debate

Key: Need to model the role of frictions and financial intermediation to gain proper understanding of the role of money, credit and liquidity Importance of shadow banking, leverage, collateral, fire sales, repo market

Instructive to learn from history of different monetary models


1.1 Money supply and demand What is money? Why do we hold money? Money demand; Money supply?

Macro Model: Equilibrium condition for money market:

Money demand = Money supply (Quantity Theory [Identity])

rYikYiMPM ⋅== )(),(

in terms of growth rates:

yYY

PP

kk

kk

MM

++=

++=•

••••

πµ

;


Monetary aggregates: Meaning of M0 M1 M2 M3 ...?

ECB Definition: M0: Base money: Currency (banknotes and coins) in circulation

+ reserves of credit institutions held with central bank

M1: currency in circulation (cash in non-banking sector) + overnight deposits held at credit institutions

M2: M1 + deposits with agreed maturity of up to 2 years + deposits redeemable at notice of up to 3 months.

M3: M2 + repo agreements, money market fund shares and units as well as debt securities with a maturity of up to two years

1.1 Money supply and demand


M0 Base money, directly controlled by central bank (monetary base, central bank money, high powered money)

M1 narrow definition for potential transactions (emphasizes money as medium of exchange)

M2 broader than M1, includes also temporary or permanent role in portfolio allocation (money as store of value)

M3 includes money market funds ~ shadow banking (money as store of value)

Permanent portfolio re-allocation between M1, M2, M3 and other assets → instability of money demand Re-allocation depends on (a) interest rate; (b) risk tolerance (c)… → attempts to estimate adjusted money demand


H

H: High powered money; Base money, Central bank money



M3 9.522,3

M2 8.394,8 M1 4.698,5 Currency

in circulation

Overnight Deposits

Deposits with an agreed

maturity of up to 2 years

Deposits redeemable

at notice of up 3 months

Repos Money market fund shares/units

Debt securities with a maturity of up to 2 years

793,6 3.904,9 1.781,3 1.914,9 433,9 570,2 123,4

Monetary aggregates in the Euro Area December 2010

(Table 1.4, P. 12f ECB Monthly Bulleton March 2012) Base Money H (M0) in the Euro Area 2010: 1073,1 bn. €

(Table 1.4, P. 9) GDP (PY) 9160,9 Mrd. € → H/PY = 11,7%


1.1 Money supply and demand Money demand as a function of transaction activity PY and interest rate i

k=M/PY: Inverse of velocity of circulation of money

Compare Germany – USA (M1)


1.1 Money supply and demand Money demand as a function of transaction activity PY and interest rate i

k=M/PY: Inverse of velocity of circulation of money

1979/81 High volatility of interest rate Paul Volcker period of strict monetary targeting



0%

2%

4%

6%

8%

10%

12%

14%

1973 1978 1983 1988 1993 1998 2003 2008

Zins

satz

0,000,050,100,150,200,250,300,350,400,450,50

Kas

senh

altu

ngsk

oeff

izie

nt

k=M/PY

Germany: Interest rates and money (M1)/GDP

Money Demand: decreasing in interest rate i

Interest rate

k=M/PY


Money demand and opportunity cost of holding money Attempt to find stable relation between adjusted money and true opp. costs

ECB MB March 2003, Fig. 4

1) Opportunity cost of M3 (right-hand scale) Calculated as difference between 3month money market rate and own interest on M3 components.

2) Real M3-growth minus real GDP growth (left-hand scale) Calculated as difference between M3 growth, adjusted with GDP-deflator and real GDP growth



1.2 Baumol/ Tobin Model Theoretical Models of Money Demand: First generation Minimise transaction costs [shoe leather costs] (Baumol / Tobin)

Optimal number t of transactions?

Trade off between two effects of money holding:

1) Opportunity cost of holding money: foregone interest income (i-iM) M

2) Transaction Cost: K= αP t + βPY: Each reallocation of the portfolio incurs real costs:

a) Fixed cost αP (shoe leather costs) per transaction t

b) Proportional transaction costs βP Nominal cost rising in price level P

Minimise total cost: YPMYPPMMiiYPtPMMiiK βαβα ++−=++−=

2)()(

tYPM

2⋅=


1.2 Baumol/ Tobin Model From Baumol / Tobin Approach we get as money demand function:

• Real Money Demand homogenous of degree 0 in Price level (Real money balances)

• Negative elasticity of interest; elasticity of income smaller than 1 (1/2) • Satiation (i→ iM) : Money demand goes to infinity Modifications: • Financial innovation may change money demand • Money is part of portfolio wealth → money demand rises with wealth W

[money as store of value; safe asset] • Additional elements: black market activity, demand as international currency reserve

Empirical Analysis:

Long run: Fairly stable relation between inflation and money growth

Short run: strong increase in volatility of money demand → money growth no reliable indicator for inflationary potential

YYMiiMii

YYYikPM

2/1

)(2

2/1

)(2),(

−=

−== αα


1.2 Portfolio–Theory of Money Optimisation under risk: Trade off between

costs of holiding money (foregone interest) and liquidity/Safety (Savings in transaction costs; precautionary saving)

Uncertainty: → precautionary saving; speculative assets

a) Theory of speculation (Keynes): (subjectively sure) expectations about interest rate moves→ Holding cash avoids risk of capital losses

b) Portfolio theory (Tobin): Optimal diversification of risk averse agents

No dichotomy between money demand and demand for other assets

Key lesson for money demand: Each portfolio has some share of cash holding (as risk free investment). Cash holding is negatively related to interest rate; increasing with financial wealth and rising volatility (Vix-index)


1.2 Portfolio–Theory of Money μ/ σ approach: Risk averse agents mix between efficient risky market

portfolio M and risk less cash G

σ

μ M

P

G

Why is cash a risk-less asset? Goverment bonds: Interest rate risk No nominal risk, but real risk: Inflation erodes real value of money

Outside money: Legal tender for all debt Cannot be rejected as final payment Private money: Market price risk (deposit insurance)


1.3 Endogenous Money Monetary Policy via Interest rates vs. money supply

How does a central bank control price level and/or money supply?

Condition for strategy of targeting money supply: reliable relation between money growth and rate of inflation

Money supply as reliable indicator (intermediate target) for price level strongly depends on stability of money demand

With unstable money demand (high volatility), strict targeting of money supply creates high volatility of output.

Instability of money demand because of high substitutabilty of different asset classes

Interest rate targeting superior with high volatility of money demand

Targeting money supply superior with high volatility of real sector

Instructive: Keynesian IS-LM model William Poole (1970)


1.3 Endogenous Money

Md 2

Md´1

•

Ms

i1 A

A´ i2

M/P

i

Money market equilibrium: Md /P= Y L(i) Determination of Price level P and interest rate i for given M?

M/P

A“


Md (PY)

1.3 Endogenous Money August 2007: Strong Increase in demand for central bank reserves

Ms

M

4% A

M

i

New equilibrium A´ M’

Md´ (PY´ > PY)

Increase in demand for liquidity to

Md´

Marginal Lending Facility B

Quick tender: ECB provides additional 94.8 bn. € At the rate 4%

A´

+94.8 bn. €


1.3 Endogenous Money

i

y y

y2

Interest rates vs. money supply targeting Unstabile money demand: Strict monetary targeting is destabilising

y1


1.3 Endogenous Money: Euro area Attempts to find stable money demand: Portfolio shifts affect demand for money!

High volatility of asset prices → flight to safety High Substitutabilty of assets causes instability of money demand

M3 adjusted: tries to account for impact of volatility on money demand Endogenous Money: At least in the short run: Central banks accomodate changes in demand for liquid assets → Money growth driven by money demand But: central banks try to control demand for liquid assets via changes in the interest rate Rational: Price stability Financial stability concerns?

kky•

−−= µπ


1.3 Endogenous Money Before 2007: M3 growth far above ECB reference value (4.5%)

Source: Monthly Report Deutsche Bundesbank February 2007

Causality: Does money drive credit or credit drive money?

Is Mike right?


1.3 Endogenous Money: Euro area

Source: Hyun Jeong Kim, Hyun Song Shin and Jaeho Yun Monetary Aggregates and the Central Bank's Financial Stability Mandate


1.3 Endogenous Money: Euro area

Source: Kim, Shin and Yun


1.4 Instability of Money Multiplier Endogenous Money: Banks create inside money (deposits, money market funds .. )

Modern central banks set interest rates. Are they able to control money supply?

Central bank controls outside money (base money H).

Broader money M determined also by credit institutions and private agents (demand for cash from households)

Relation between M and H depends on actions of all three groups

1) Households: Demand for cash and deposits Money M1: C (cash) + D: (deposits)

2) Credit institutions: Accept deposits; give loans; need to refinance via central bank

3) Central bank: controls high powered money H (base money) H = C+ R

R: Reserves of credit institutions


1.4 Instability of Money Multiplier Central bank

controls base money H = C+ R via it‘s own balance sheet (as long as control over assets) (exchange rate peg: Currency reserves are endogenous)

D depends on the loans granted by credit institutions

Can central bank influence deposits D (M1, M2,…) via R?

If R = r D: Control of R affects D indirectly and thus M

Assets Liabilities Currency reserves

Gold

Assets bought via Open Market

Operations with banks

Other assets

Cash C

Reserves R

of credit institutions

r: desired reserves of credit institutions depend on opportunity costs r r i( , )

buying additional

assets

Extension of Base money ↑

(balance sheet)


1.4 Instability of Money Multiplier Example of money multipler process: Simplification:

1) Non-banks want to hold cash and deposits in fixed proportions: C = k D

2) Commercial banks plan to hold a fixed share r of reserves R=r D

3) Central bank controls base money H

Money multiplier depends on

a) Desired reserve holding by banks

b) Desired cash holding by private sector

H=C+R base money cash holding C=k D

M=C+D money (M1) reserve holding: R=r D

H=(k+r) D ; M=(1+k) D → M= (1+k)/(k+r) H


1.4 Instability of Money Multiplier: USA Friedman /Schwartz, A monetary history of the United States, 1867-1960, NBER 1963


1.4 Instability of Money Multiplier: USA Friedman /Schwartz, A monetary history of the United States, 1867-1960, NBER 1963


2.4 Instability of Money Multiplier: USA

0,0000,0010,0010,0020,0020,0030,0030,004

1984 1989 1994 1999 2004 2009 2014

M1 Money Multiplier, Ratio, Monthly, Seasonally Adjusted

M1 Money Multiplier, Ratio, Monthly, Seasonally Adjusted

0,000

0,500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

1984 1989 1994 1999 2004 2009 2014

St. Louis Adjusted Monetary Base, Bln $ M1 Money Stock, Bln $


Fed Balance Sheet Assets


Fed Balance Sheet Liabilities

„overheating printing press“?


ECB Monetary Policy

Minimum bid rate

Rate for marginal lending facility

Main Refinancing Rate


ECB Balance Sheet


Money Multiplier M2: Euro Area


ECB FINANCIAL INTEGRATION IN EUROPE April 2013 link

http://www.google.de/url?sa=t&rct=j&q=&esrc=s&frm=1&source=web&cd=1&cad=rja&uact=8&ved=0CCEQFjAA&url=http://www.ecb.europa.eu/pub/pdf/other/financialintegrationineurope201304en.pdf&ei=JcoZVOibE7KI7AanoID4Cw&usg=AFQjCNEkpeGvUYEZ9Ffrhu6B1IVG1Mq9Pg&bvm=bv.75097201,d.bGQ


Euro area lending rate dispersion


Euro Area Yield Dispersion


1.1 Money, liquidity and credit What is money? Why do we hold money?

Confusion: Different notions of money: Outside vs. inside money: M0 ↔ M1 M2 M3 Base money M0 (central bank money) vs. M1 M2 M3 Private money provided by private banks/ Shadow banks

Traditional view: Stable relation between M0, money in the banking system Mi (i≥1) and credit activity ~reliable indicator for inflationary potential

Financial Innovation → high substitutability →instability in money demand relation; Portfolio rebalancing between different asset classes Cyclical fluctuations (flight to safe assets during crisis) Break down of stability of „money demand“ (unreliable money growth targeting)

Need to include shadow banking in analysis; otherwise risk to draw misleading conclusions (as in Chari/Christiano/Kehoe 2008)

See: Adrian/Shin (2010); Gorton/Metrick 2010 (Run on shadow banking sector)

Liquid assets: Market vs. funding liquidity; Safe assets (securitisation); value of collateral, Haircuts, Repo market Procyclical liquidity of assets → incentives for high leverage → fragility


1.5 Money, liquidity and credit Assets Liabilities

Cash, Treasuries Asset Backed Securities

Loans

Deposits Repo-Finance

Equity

Market liquidity: Ability to raise cash via

selling asset

Funding-Liquidity: Ability to raise cash via

borrowing with assets as collateral Drying out of liquidity:

Assets can be sold only at discounts (Fire Sale Prices)

Drying out of liquidity: Short term debt cannot be rolled over

Rising haircuts for collateral Rising margin calls

Procyclical liquidity of assets → liquidity spirals during crisis → domino effects; contagion; credit crunch Liquidity hoarding: Shrinking of money multiplier Mi/M0 See: Shleifer/Vishny; Brunnermeier/Pederson; Gorton; Geanakoplos


Banks value loans at market price:

Banks

Market value L of Mortgages

Equity (net wealth)

Deposits

Market value rises

Net wealth rises

With rising market value L: Increase in net wealth; reduced leverage

Bank managers raise new deposits aiming to adjust their leverage

Increase in Loans

Increase in Deposits

Increase in loans→ Real Estate Price P rises

Increase in market value of loans: Feedback mechanismus

1.5 Money, liquidity and credit


1.5 Money, liquidity and credit: shadow banking Flight to safety: Run on „shadow banking sector“

High Leverage → Increase in Haircut /Spikes in Margin Calls → Shrinking credit (deleveraging) → Contraction (Externalities)

Example: Money market funds as “lifeblood of wholesale funding markets” 2008 low-risk, low-return funds supply critical liquidity with assets under management of $4,200bn – Implicit commitment not to „break the buck“

After Lehman’s default: $400 billion run out of the money market 29.9.2008 Treasury Announces Guaranty Program for Money Market Funds

John Geanakoplos, Solving the Present Crisis and Managing the Leverage Cycle, FRBNY Economic Policy Review / August 2010


1.5 Money, liquidity and credit: shadow banking

00

500

1,000

1,500

2,000

2,500

3,000

1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009 20

TCDNS MMMFTCMAHDFS

Total Checkable Deposits, Billions $

Money Market Mutual Funds; Credit Market Instruments; Asset, Level, Billions $

FRED Federal Reserve Economic Data


1.5 Money, liquidity and credit: shadow banking Flight to safety: Run on „shadow banking sector“

High Leverage → Increase in Haircut /Spikes in Margin Calls → Shrinking credit (deleveraging) → Contraction (Externalities)

Example: Money market funds as “lifeblood of wholesale funding markets” 2008 low-risk, low-return funds supply critical liquidity with assets under management of $4,200bn – Implicit commitment not to „break the buck“

After Lehman’s default: $400 billion run out of the money market 29.9.2008 Treasury Announces Guaranty Program for Money Market Funds

Key: Debt finance vs. equity finance (narrow banking)

Commitment to redeem liabilities at a fixed rate (debt: gold standard; safe assets) vs. fluctuating value of shares → prone to crisis; incentive device

Commitment of modern central banks: „Price stability“ (low inflation) Crucial: Trust ~ money is intrinsically worthless; accepted as a promise to be able to exchange it into future goods → multiple equilibria (credibility)



Chari Christiano Kehoe Myths about the Financial Crisis of 2008

Credit Lines: Banks had made contingent commitments to provide liquidity to shadow banks



Adrian/ Shin, Liquidity and Leverage














Central bank as financial intermediary after breakdown of shadow banking

Ultimate Borrowers

Households

Non financial firms

Government

x Ultimate Claim Holders

Households

(Pension funds,

Insurance)

Financial Intermediaries

Commercial banks Shadow banks

Central Bank

equity

debt

Excess reserves blocked

Outside money

Inside money (net zero supply)


Adrian, Tobias/Hyun Song Shin (2009). "Money, Liquidity, and Monetary Policy." American Economic Review, 99(2): 600-605. *

Geanakoplos, John (2010) Solving the Present Crisis and Managing the Leverage Cycle, FRBNY Economic Policy Review / August 2010

Gorton, Gary B. (2012) Some Reflections on the Recent Financial Crisis NBER Working Paper No. 18397 September 2012

Kim, Hyun Jeong/ Hyun Song Shin, Jaeho Yun (2013) Monetary Aggregates and the Central Bank’s Financial Stability Mandate, International Journal of Central Banking

Additional Reading


Monetary Theory

Prof. Dr. Gerhard Illing

M. Sc. Course

Winter Term 2014/2015

Slides Part 2

Stylized Facts about Money: Long Run; Short Run, VAR, Taylor Rules, Yield Curve


How does money /monetary policy affect the economy?

Key concept: Phillips-curve: Trade off between unemployment and inflation: High real growth rates only at the expense of high inflation?

Distinguish between long run and short run effects:

In the long run, money is neutral, even „superneutral“ – it does not affect the real growth rate in the economy

Milton Friedman: High money growth causes inflation → need to control money growth

In the short run, money may have real effects (due to sticky prices) →

Monetary policy may be used to stabilise shocks: Interest rate policy to smooth/dampen shocks

2.1 Short Run vs. Long Run Perspective


)( ettN

At ayy ππ −+=

u

π π

uN

Phillips-Curve and Aggregate Supply

Phillips-curve

Aggregate Supply

y

)( te

tNt duu ππ −−=yN

2.1 Short Run vs. Long Run Perspective


2.1 Empirical analysis of monetary policy Monetary Policy in the short run

1. Keynesian View: Trade off between inflation and unemployment (short run Phillips-curve)

2. Classical View: Friedman and Schwartz (1963) Empirical analysis of US history Real effects of monetary shocks,

but no real effects of fiscal shocks But: „long and variable lags“ for the real effects!

Thus, policy should not aim to stimulate real activity 3. Modern View: Use modern econometric techniques (VAR)

Impulse response analysis Key paper for US: Christiano, Eichenbaum, Evans (1996) Europe: Smets/Wouters (EER 2003) Theoretical base: DSGE models

4. Rules vs. Discretion (Taylor rule): Money vs. interest rates rules


2.1 Empirical analysis of monetary policy How does monetary policy affect the economy?

VAR: Use econometric methods to analyse the impact of monetary shocks on different variables

Distinguish between short run on long run effects

Hypothesis: in the short run, monetary policy has an impact on the real economy; in the long run, it affects only the price level

Problems with econometric analysis:

a) Identify monetary instruments: What is the relevant policy instrument? (monetary – vs interest rate targeting?)

b) How do we capture lags?

c) Monetary policy is systematic: endogenous changes of instruments (Feedback mechanism) - Identification of shocks dubious

d) Model restrictions are crucial for most of the results: Robustness?


2.2 Stylized Facts about Money: Long Run

What drives inflation? Let us look first at the data:

Evolution of the price level in Britain 1265-2009


2.2 Stylized Facts about Money: Long Run What drives inflation? Let us look first at the data:


Why did prices rise so much during the last century? Change from gold standard to fiat money How can we measure (changes in) the price level? Statistical issue: Find representative basket of commodities

CPI: consumer price index; Core CPI; PCE deflator for Personal Consumption Expenditures, GDP Deflator Last decades: Worldwide decline in inflation rates Recently, deflationary episodes

What drives fluctuation in the rate of inflation? What is the optimal rate of inflation? Should central banks target the price level or inflation? Should central banks target nominal GDP (in level or changes)?

Heated debates

2.2 Stylized Facts about Money


2.2 Stylized Facts about Money: Long Run Recent trends: Worldwide decline in inflation rates

CPI Inflation US, Japan and Germany

-3

0

3

6

9

12

15

18

21

24

1960 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011

Per

cent

USA Japan Germany


2.2 Stylized Facts about Money: Long Run Long run analysis: Find out empirical correlation for a long time horizon

Correlation between money growth and Inflation?

- Correlation between inflation and real GDP growth?

McCandlees and Weber (1995) Look at data for monetary aggregates and output (GDP) growth

from 1960-1990 for 110 countries Calculate (geometric) average over 30-years for

GDP growth, inflation, growth of monetary aggregates M0, M1, M2 Look for „long-run, cross-country correlations“


In the long run, we find a significant correlation between money growth and inflation Correlation coefficient

between 0,92 and 0,96 But be careful!

Correlation does not tell us about causality

Does money growth cause inflation or the other way round?


Money and Inflation



Money and real growth


Barro: in the long run, no correlation between inflation and growth: → Superneutrality of money

But: countries with high inflation (hyperinflation) exhibit low growth (Causality??)

2.2 Stylized Facts about Money: Long Run Money and real growth


Barro: High rates of inflation correlated with high volatility of the rate of inflation

2.2 Stylized Facts about Money : Long Run Inflation und inflation volatility


2.2 Stylized Facts about Money: Long Run Long Run Analysis – Summary McCandlees and Weber (1995); Barro (1996):

In the Long Run, high money growth correlated with proportionally high rate of inflation

Superneutrality of money: In the long run, there is no real effect (No Trade off a la Phillips-Curve)

But: Possibly non-linear relationship between inflation and output growth: • For countries with stable economies with low rate of inflation:

Positive relation between inflation and growth • For countries with excessively high rates of inflation: low growth!

Negative relation between inflation and growth • So the Long run Phillips-curve may be non-linear

Issues: What is the optimal monetary policy? What is the optimal rate of inflation? First, we need to look also at short run effects! In short run, there can be a trade off between price stability and stabilisation

policy (Phillips-curve)


Phillips-Curve: Short Run Trade Off

between Inflation and unemployment Friedman/ Phelps: Important role of

expectations: Phillips-Curve is

shifting: No trade off in the long run

But also shifts in Natural Rate of unemployment!

2.2 Stylized Facts about Money: Short Run Phillips-Curve Germany 1960-1969


How do we measure short run effects of monetary policy?

Challenge: Identification of pure policy effects Policy instrument: Money growth vs. interest rate? Endogenous, systematic response vs. pure policy shock? Identify monetary policy shocks: Classical empirical analysis: Friedman and Schwartz (1963): look at

data in US history Monetary Shocks have real effects, but they work with „long and

variable lags“ Modern empirical analysis uses

advanced econometric methods: Vector Autoregression (VAR) (Christopher Sims) Leading example for US: Christiano, Eichenbaum, Evans (1996)

2.3 Stylized Facts about Money: VAR models


2.3 Stylized Facts about Money: VAR models AR Models: How to understand cyclical fluctuations?

Deviations from trend (price level path; GDP path)

Cyclical components are positively autocorrelated (i.e. positively correlated with their own lagged values) and they exhibit random-looking fluctuations.

A simple model that captures these features is the AR(1) model

(Auto-Regressive of order 1):

Suppose the AR(1) series starts at zero (yt-1 = 0; no deviation from trend).

Then there is a unit shock: t = 1 From then on, all shocks are zero afterwards.

In period t, we will have yt = 1.

What happens next? In period t + 1, we have yt+1 = ρ .

In period t + n, we have yt+n = ρn.

ttt yy ερ += −1


1. 3 Stylized Facts about Money: VAR models The shock fades away gradually. How fast depends on the size of ρ.

So the volatility of the series is partly due to (1) the size of shocks and also due to (2) the strength ρ of the propagation mechanism.

The time path yt after this hypothetical shock is called Impulse Response Function.

Can think of this as the path followed from t onwards when shocks are (εt + 1, εt+1 , εt+2, .....) instead of (εt, εt+1 , εt+2, .....) i.e. the incremental effect in all future periods of a unit shock today.

Graphs of Impulse Response Functions are commonly used to illustrate dynamic properties of macro data.

Lag structure determines dynamics: AR(1) model → gradual erosion

AR(2, 3) models: more complex responses (oscillating or hump-shaped) How many lags should we allow? Battery of lag selection tests to decide upon the appropriate lag length.


2.3 Stylized Facts about Money: VAR models AR models are a useful tool for understanding the dynamics of

individual variables But they ignore the interrelationships between variables.

Vector Autoregressions (VARs) model the dynamics of n different variables, allowing each variable to depend on lagged values of all of the variables.

Can examine impulse responses of all n variables to all n shocks.

VAR invented by Christopher Sims (1980). Now used as a central tool in applied macroeconomics.


Impulse Response Functions from Vector Autoregression (VARs)

• Intuition: Interaction between different time series (such as policy variable and inflation) in the presence of feedback-effects

• Simplest example: two variables and one lag:

yttttt zyzbby εγγ +++−= −− 1121111210

zttttt zyzbbz εγγ +++−= −− 1221212120




Transformation of the system allows analysis of the impact of innovations (shocks) of one variable

After some transformations, we get:

are estimated parameters of the model

How do different variables react to shocks/ change in policy?

+

=

−

−∞

=∑

izt

iyt

it

t

iiii

zy

zy

εε

φφφφ

0 2221

1211

)()()()(

)(ijkφ

Challenge: Identify relevant variables Key economic variables (technology, labour supply, oil price; preferences) Policy instruments (money supply, interest rate?)



Effect of a 1% increase in the Federal Funds Rate across time

Grey area: confidence interval: „true“ value with 60 % probability within the interval

Effects on retail sales:

Significant Fall after an nach increase in interest rates

Strongest effect after 5 Quartils (0,9% fall)

Example: Christiano, Eichenbaum, Evans


Output (GDP): In the short run, an increase in

the federal funds rate leads to a decrease in output, but slower than retail sales (initially: building up of inventories) Strongest Impact (-0,7%) only after

8 Quartais

Key Lesson: Monetary Policy works with „long and variable lags (1-2 years)

2.3 Stylized Facts about Money: VAR models Christiano, Eichenbaum, Evans


Unemployment rate Fall in output causes layoffs and

increase in unemployment Slow increase (like output) largest effect after 8 Quartils

(+ 0,1%) Then the impact goes down strongly

Suggests Phillips-curve-Trade off In the short run!

2.3 Stylized Facts about Money: VAR models Christiano, Eichenbaum, Evans


Rate of inflation Puzzle: Inflation initially slightly

increasing

Then: Price level falls slowly

Key Lesson: Much longer lags for nominal variables! Reason: Sticky prices and wages Again: Long and variable Lags




VAR models can examine effects of shocks. But what are the shocks? Lots of possibilities:

1 Policy changes which are not due to the systematic component of policy captured by the VAR equation. (Great trembling)

2 Changes in preferences, such as attitudes to consumption versus saving or work versus leisure. (Great vacation)

3 Technology shocks: Random changes in the efficiency with which firms produce goods and services. (Great forgetting)

4 Shocks to frictions: Changes in the efficiency with which various markets operate, such as the labour market, goods markets, or financial markets.

VARs can describe how things work, but cannot explain why. Need to know how people behave and respond in the economy → Need for economic theory: DSGE models aim to have the dynamic structure of VARs (shocks and propagation mechanisms, IRFs) but are derived from economic theory


2.4 Stylized Facts about Money: Taylor Rule

Can we derive an optimal rule? Criterion: Minimise welfare losses

Adequate rules under uncertainty? Informational requirements? Is there sufficient information about monetary transmission mechanisms?

Milton Friedman: Discretionary policy can lead to distortions →Call for strict monetary targeting (target money growth rate)

Kydland/Prescott, Barro/Gordon: Game theoretic analysis of problem of dynamic inconsistency (inflationary bias) Theoretical model for value of commitment Cukierman et. al: Empirical analysis between central bank independence and policy performance (inflation rate) John Taylor: Interest rate rule as binding commitment

Other rules: Inflation targeting; Nominal GDP targeting, Central bank contracts

Old debate: Rules vs. Discretion



Cukierman Index d – rate of depreciation in the real value of money comp – compliance to law (legal time in office) LVAW – aggregate measure of legal independence

Correlation between central bank independence and stability performance

Source: Cukierman (1992), p. 421

Vittorio Grilli, Donato Masciandaro und Guido Tabellini „Political and Monetary Institutions and Public Financial Policies in the Industrial Countries“, Economic Policy, 6(2), 1991, S. 341–392.



Forward looking Taylor rule: Base policy on forecasts as information variable

Expected rate of inflation; expected output gap, given current available information Ω

*)(*)( 21 ttttt yyi −+−+= γππγα

Taylor-Rule John Taylor: Central banks should target real short term interest rate. Correct deviations of inflation and real growth (unemployment) from target Taylor‘s-Rule (1993): weight on inflation 2.5; weight on output gap 0.5

More general:

*)(21*)(5.1** yyri ttt −+−++= πππ

*)))((*)))(( 1211 yyEEi tttttt −Ω+−Ω+= −− γππγα

Information variable: current rate of inflation and output gap

Note: for *;*;* πααπππ −==→=== ttttte

t riyy

Interest rate smoothing: t

Titt t

iii ηρρ +−+= − *)1(1



( ) ( )* * * *0,5 0,5 0,5 1,5 0,5t t t t t ti r y r yπ π π π π= + + − + = − + +

2,58 0,51 0,37(6,35) (2,48) (6,19)

t t ti yπ= + ⋅ + ⋅

0

2

4

6

8

10

12

14

1991

:01

1991

:07

1992

:01

1992

:07

1993

:01

1993

:07

1994

:01

1994

:07

1995

:01

1995

:07

1996

:01

1996

:07

1997

:01

1997

:07

1998

:01

1998

:07

1999

:01

1999

:07

2000

:01

2000

:07

2001

:01

2001

:07

2002

:01

2002

:07

2003

:01

Taylor Rule

Actual interest rate

ECBBundesbank

Original Taylor (1993):

ECB estimate (Sauer/Sturm):



John Taylor



Orphanides/Wieland 2008



Economic Projections and Rules of Thumb for Monetary Policy Federal Reserve Bank of St. Louis Review, July/August 2008, 90(4), pp. 307-24.


Economic Projections and Rules of Thumb for Monetary Policy Federal Reserve Bank of St. Louis Review, July/August 2008, 90(4), pp. 307-24.




Orphanides/Wieland 2008

Ben Bernanke, Monetary policy and the housing bubble, AEA 2010

http://www.federalreserve.gov/newsevents/speech/bernanke20100103a.htm


Stylized Facts about Money: Taylor Rule

Historic FOMC transcripts 2005 Different versions of the rule Fed policymakers regularly look at a range of policy rules use forecast parameters and place a greater weight on the output gap than inflation.



Effective Federal Funds Rate (FFR) und Taylor Rule implied Federal Funds Rate (Rule);

Source: Rudebusch und St. Louis Fed

-8,00

-6,00

-4,00

-2,00

0,00

2,004,00

6,00

8,00

10,00

12,00

1988 1991 1994 1997 2000 2003 2006 2009

FFR Rule

Glenn D. Rudebusch, The Fed’s Monetary Policy Response to the Current Crisis, 2009


Effective Shadow Federal Funds Rate link

http://www.frbatlanta.org/cqer/researchcq/shadow_rate.cfm



Janet L. Yellen

New York

April 11, 2012

The Economic Outlook and Monetary Policy


2.4 Stylized Facts about Money: Taylor Rule Alex Nikolsko-Rzhevskyy /David H. Papell Taylor’s Rule versus Taylor Rules








What index to target?

http://www.clevelandfed.org/research/trends/2014/0514/01infpri-3.gif


2.4 Controversy about Taylor rule in financial crisis

Additional reading: (aiming to understand the importance of weights in the Taylor Rule, the role of the target inflation rate and the impact of the Zero Lower Bound)

Athanasios Orphanides / Volker Wieland, Economic Projections and Rules of Thumb for Monetary Policy Federal Reserve Bank of St. Louis Review, July/August 2008, 90(4), pp. 307-24 link

Glenn D. Rudebusch, The Fed's Monetary Policy Response to the Current Crisis, May 22, 2009, link

Ben Bernanke, Monetary policy and the housing bubble, AEA 2010 link

Alex Nikolsko-Rzhevskyy /David H. Papell Taylor’s Rule versus Taylor Rules, University of Houston, September 2012 link

Janet L. Yellen, The Economic Outlook and Monetary Policy, New York April 11, 2012 link

http://www.frbsf.org/publications/economics/letter/2009/el2009-17.html


http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1826363

http://www.federalreserve.gov/newsevents/speech/yellen20120411a.htm


2.5 Short term and long term interest rates Ben S. Bernanke Long-Term Interest Rates, Speech March 1, 2013 Link Why are long-term interest rates so low in the United States and in other major

industrial countries? At first blush, the answer seems obvious: Central banks in those countries are

pursuing accommodative monetary policies to boost growth and reduce slack in their economies. However, while central banks certainly play a key role in determining the behavior of long-term interest rates, theirs is only a proximate influence. A more complete explanation of the current low level of rates must take account of the broader economic environment in which central banks are currently operating and of the constraints that that environment places on their policy choices.



2.5 Short term and long term interest rates


2.5 The Yield Curve Long term nominal bond yield can be broken down into three

components: (i) expected average inflation (inflation premium); (ii) expected average real short rate; (iii) term premium.

With risk neutrality, only the first two components should be relevant: Expectations theory of the term structure: the real yield is the average of the real future short rates,

Nominal yield is the real yield plus average anticipated inflation (Irving Fisher)

The "term premium" is then just a residual. But on average, the nominal yield curve is upward-sloping: Duration Risk

Stephen Williamson, Ben Bernanke and the Term Structure of Interest Rates Tuesday, March 19, 2013


Implied forward rates

ECB MONTHLY BULLETIN SEPTEMBER 2014 https://www.ecb.europa.eu/stats/money/yc/html/index.en.html

https://www.ecb.europa.eu/stats/money/yc/html/index.en.html

https://www.ecb.europa.eu/stats/money/yc/html/index.en.html


2.5 Expectation Channel: The Yield Curve Expectations about future interest rate path has strong impact on Yield Curve. Yield Curve: provides information about expectations of financial markets

i

t

invers

normal


2.5 Expectation Channel: The Yield Curve Different views about relation between yield for homogeneous bonds with

different maturity (link betweeen short and long term yields):

a) Expectations theory of the term structure (classical view): Interest rate arbitrage → yield for long term bonds is equal to dem geometric mean of expected short term rates holds under risk neutrality! Presence of arbitrage → bonds with different maturity as perfect Substitutes (no risk premium)

b) Liquidity theory: Risk premium for bonds with longer maturity


2.5 Expectation Channel: The Yield Curve Expectations theory of the term structure (classical view)

il yield for long term bond (maturity T)

ik yield for short term bond (maturity 1)

Arbitrage Condition:

Example: T=2: il = ½ [i1 + E(i2)]

Implication:

If no changes in interest rates expected: constant yield curve : il = ik

If interest rates are expected to rise: increasing yield curve (il > ik)

If interest rates are expected to fall: falling yield curve(il <ik)

( ) ( )( )( )...( )1 1 1 1 11 2 3+ = + + + +il i i i iT T


2.5 Expectation Channel: The Yield Curve b) Liquidity theory:

Longer maturity: less liquidity Liquidity premium as compensation for maturity risk Both borrower and lender are risk averse But they evaluate risks differently

Two types of risk for long term bond

1) Capital risk: Risk: maturity too long Lender: Needs funds before maturity, but bond price has fallen Borrower: Pay back funds before maturity, but bond price higher

2) Wealth risk: Risk: maturity too short Lender: Reinvesting costly with interest rates falling Borrower: Refunding costly with interest rates rising

Keynes/Hicks: Lender fear capital risk, Borrower fear wealth risk But on average, upward-sloping yield curve

( ) ( )( )1 1 1 22

1 2+ = + + +il i i l

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