Economic Crises and Forecasting: a review of South Africa’s model

byP. Lehohla and D. Morudu

Policy Research and Analysis UnitOffice of the Statistician General

Statistics South Africa

Paper prepared for the

15 Conference of Commonwealth Statisticians

held on 7 – 10 February 2011

First draft: 26 January 2011This draft: 3 February 2011

Draft remains preliminary and incompleteEnquiries: Hlabim@statssa.gov.za

Table of contents

• Introduction• Approach in South Africa• A general problem: evidence from South Africa• Literature review• Some proposals: the potential role for Stats SA• Conclusions

Introduction

• Economists have useful scientific tools that enable them to anticipate regular business cycles. Indeed economists provide valuable input in shaping monetary/fiscal policies based on anticipated business cycle movements.

• What economists often fail to do is to anticipate major economic crises despite an accumulation of data series in the financial sector, balance of payments and national budgets over the years, including the international tightening of data standards.

Introduction

• Following the 2008 global crisis, a number of forums consisting of expert academia and practitioners, sponsored by international agencies such as the International Monetary Fund, World Bank and United Nations, have been developed to review the current state of economic forecasting.

• An impressive number of papers on the state of current economic forecasting have surfaced.

Introduction

• Recent research reveals efforts to improve three major approaches, viz.

(a) the composite business cycle indicators approach as developed at the National Bureau of Economic Research (NBER) in the United States

(b) econometric modeling approach following recommendations of the Cowles Commission

(c) hybrids of both the business cycle indicator approach and econometric approach, more notably illustrated through Markov switching autoregressive techniques

Introduction

• A further development consists of empirical studies that are based on the behavior of business cycles in a number of countries and how the business cycles interact, i.e. along the lines researched by the Center for International Business Cycle Research at Rutgers University.

Introduction

• South Africa currently produces, through the South African Reserve Bank, composite business cycle indicators using the NBER approach, and publishes a composite leading indicator index on a monthly basis.

• Other approaches have been suggested, but remain outside existing official economic and statistics agencies, and have not been pursued (e.g. E. Moolman (2004) on a Markov switching model for South Africa).

Introduction

• The objective of this paper is to assess weaknesses in South Africa’s business cycle forecasting efforts given current international developments in business cycle research.

Approach in South Africa

• To anticipate business cycle movements, and potentially economic crises, South Africa produces a set of composite business cycle indicators along the lines proposed by the NBER.

• A selection of time series is made from a vast number of economic time series and categorized into three distinct groups, viz. (a) leading indicator series; (b) coincident indicator series, and (c) lagging indicator series.

• The movement of each composite indicator is a weighted average of movements of a number of variables (Venter and Pretorius, 2004; Venter, 2004).

Table 1

Components of composite business cycle indicators

Composite coincident indicator Composite leading indicator

1. Gross value added at constant prices, excluding agriculture, forestry and fishing

1. Net balance on manufacturers observing an increase in the volume of orders received (half weight)

2. Value of wholesale, retail and new vehicle sales at constant prices2. Number of new passenger vehicles sold (year on year percentage change)

3. Utilization of production capacity in manufacturing3. Opinion survey of business confidence: manufacturing, construction and trade

4. Total formal non-agricultural employment4. Composite leading business cycle indicator of major trading partner countries (year on year percent)

5. Industrial production index5. Index of commodity prices (in US$) for a basket of South African export commodities

Composite lagging indicator6. Real M1 money supply (deflated with the CPI, 6 months smoothed growth rate)

1. Value of non-residential buildings completed (constant prices) 7. Index of prices of all classes of shares traded on the JSE

2. Ratio of gross fixed capital formation in machinery and equipment to final consumption expenditure on goods by households

8. Number of residential building plans passed for flats, townhouses and houses larger than 80m2

3. Ratio of inventories to sales in the manufacturing and trade sectors 9. Interest rate spread: 10 year bonds less 91 day Treasury bills

4. Nominal labor costs per unit of production in the manufacturing sector (% change over 4 quarters)

10. Gross operating surplus as a percentage of GDP

5. Cement sales in tons11. Job advertisement space in the Sunday Times newspaper (% change over twelve months)

6. Ratio of households use of installment sale credit to their disposable income

12. Net balance of manufacturers observing an increase in the average number of hours worked per factory worker (half weight)

7. Predominant prime overdraft rate of banks

Approach in South Africa

• Continued increases in e.g. the “composite leading indicator”, for periods of up to six months suggest the gross domestic product (GDP) is likely to increase in subsequent months (Venter, 2005).

• Similarly, continued decreases in the “composite leading indicator”, for about two quarters, suggest the GDP is likely to decrease in subsequent quarters.

A general problem: evidence from South Africa

• In retrospect, the composite leading indicator could have provided, as early as August 2006, an sign that the economy was headed towards a recession

• The composite leading business cycle indicator decreased almost consistently from 127,5 in July 2006 to reach 114,9 in August 2008, i.e. about 25 months in advance

A general problem: evidence from South Africa

• The release of the composite leading business cycle indicator in South Africa is hardly topical:

– it is released ex post, often after critical ex ante economic decisions have been made

– the composite leading indicator is released monthly, almost 6 to 8 weeks after the reference month

– the initial set of published data is revised for up to three months before being considered final

A general problem: evidence from South Africa

• When the composite leading business cycle indicator began declining in August 2006, initial estimates became available around October 2006 and only become final around January 2007, i.e. a 5-month lag.

• By December 2007, i.e. at the official peak of the business cycle, authorities were considering the final results of a very moderate decrease of the composite leading indicator from 125,4 in June 2007 to 125,3 in July 2007.

A general problem: evidence from South Africa

• There are even more significant delays in the determination of business cycle turning points

– South African business cycles are determined as a deviation from a long-term trend, turning points are confirmed ex post after a significant number of months (Venter, 2005).

– In terms of the SARB Quarterly Bulletin, the official business cycle peak, i.e. December 2007, was published in September 2009, almost two years after the fact.

A general problem: evidence from South Africa

• The significance of the composite leading business cycle indicator in policy formulation is not readily apparent

– while the composite leading indicator suggested a pending downward economic phase through its movement from August 2006 to July 2007, monetary authorities continued to raise the repo rate in 9 subsequent Monetary Policy Committee meetings from 7,5% in 2006:06 to 12% in 2008:06.

A general problem: evidence from South Africa

Figure 1: Composite business cycle indicators

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A general problem: evidence from South Africa

• In brief– the composite leading business cycle indicator lacks a

mechanism to signal pending economic crises, it does not distinguish between regular recessions and crises

– The composite leading business cycle is released with lags that are rather too long for policy makers to maximize the indicator’s potential usefulness.

– These problems are not uniquely South African, but are typical challenges to the component business cycle indicator approach.

Literature review

• Predicting economic crises remains a major challenge in economics– Research suggests the existence of

“significant information rigidities” which make it difficult for forecasters to promptly incorporate useful domestic and international “news”

[D. Harding, et al. (2010), K. Carstensen, et al. (2010), P. Loungani, et al. (2010), D. Bragoli (2010), K. Drechsel, et al. (2010)]

Literature review

• Recent literature reveals efforts to improve three major approaches, viz.

(a) the composite business cycle indicators approach

(b) econometric modeling approach

(c) hybrids of both the business cycle indicator approach and econometric approach

Literature review

• On business cycle indicators, a number of studies propose refined techniques for selecting leading, coincident and lagging composite indicators

• The selection of more refined indicators, including “qualitative” indicators, is meant to provide more responsive composite indicators with more useful business cycle or economic crisis signaling qualities.

[G. Cubadda, et al. (2010), F. Youssef, et al. (2010), G. de Bondt, et al. (2010)]

Literature review

• A number of studies propose methods to quicken the production and release of business cycle indicators, including tentative signals that distinguish between prospective recessions and crises [Z. Guohua (2010), H. Lee, et al. (2010)]

– E.g. the Business Cycle Signal System in China, or the Business Cycle Clock in Korea, have in-built critical values that help inform markets immediately whether the economy is “overheated, likely to overheat, normal, likely to cool down or cool”.

Literature review

• Further proposals to facilitate prompt supply of data for business cycle composite indicators include “nowcasting”[M. Pedersen (2010), E. Andreou, et al. (2009), K. Lee, et al. (2010), M. Wildi (2009), M. Camacho, et al. (2010)]

– Pedersen (2010) suggests the development of “monthly indicators of economic activity” to approximate monthly GDP as practices in a number of Latin American countries

– Andreau, et al. (2009) suggest the use of daily financial data to estimate current real economic activity or “live GDP”

Literature review

• A second set of proposals consists of calls for the development of more rigorous econometric models in business cycle forecasting

[M. Franchi, et al. (2010), P. Exterkate, et al. (2010), S. Grassi, et al. (2010), T. Clark (2010), P. Foschi, et al. (2010), M. Lupinski (2010), O. Biau, et al. (2010), L Bisio, et al. (2010), M. Chauvet, et al. (2010), L. Lemoine, et al.

(2010)]

Literature review

• Chauvet, et al. (2010), construct a set of leading business cycle indicators using a time-varying autoregressive probit model.

• Grassi, et al. (2010) and Clark (2010) propose the use of Bayesian Vector Autoregressive models using individual economic variables rather than composite business cycle indicators.

• Lupinski (2010) suggest use of a dynamic factor model using data with mixed frequencies and ragged edges. Lemoine, et al. (2010) suggest use of stochastic volatility in the mean (SV-M) models to anticipate business cycles.

Literature review

• Other econometric proposals include:– Exterkate, et al. (2010) who propose the use of kernel

ridge regressions, “used extensively in machine leaning communities”, to estimate non-linear and high-dimensional business cycle series relations using kernels.

– Biau, et al. (2010) propose a new business cycle technique that is based on the “random forest”, currently in use in medical and biological research.

Literature review

• A third set of proposals consists of an admixture between the composite indicator approach and the econometric approach.– The proposals are concerned with the linear features

of the business cycle composite indicator weights, and suggest introducing non linear properties in the prediction of business cycles / crises

[E. Learner, et al. (2002), S. Altug, et al. (2010), S. Senyuz, et al. (2010)]

Literature review

• Arguably, dynamics differ between recessions and expansions, e.g. recessions have larger shocks than expansions, and expansions have much wider durations than recessions.

• To accommodate the non-linearity of business cycles, studies suggest use of Markov switching autoregressive models.

• An added feature of the proposal is that the approach is more transparent than the NBER approach (i.e. there is no need for private Business Cycle Dating Committee meetings), and results are easily reproducible.

Literature review

• Further research consists of empirical studies that seek to capture the behavior of business cycles in a number of countries and how the business cycles interact, i.e. along the lines researched by the Center for International Business Cycle Research at Rutgers University[S. Altug, et al. (2010), R. Male (2010), M. Antonakakis, et al. (2010), J. Allegret, et al. (2010), U. Bergman, et al. (2010), J. Fidrmuc, et al. (2009), J. Goggin, et al. (2010)]

Literature review

• The latter set of studies provides a promising basis for developing a framework for anticipating local, regional or global economic crises.

• The studies also indirectly highlight challenges with data from diverse countries, diverse stages of statistical development among countries on business cycle analysis and structures.

Literature review

• The literature is also abundantly explicit on the challenges of market innovations that undermine proper monitoring of the economy

– the development of new financial instruments [mortgage backed securities (MBS), collateralized debt obligations (CDO), credit default swaps (CDS)] in “shadow banking” and “off balance sheet mechanisms”, eluded normal economics and banking surveys and regulations [C. Towe (2009), H. Remsperger (2008), W. Bier (2009)]

– That is, it remains imperative that statistical agencies monitor developments in the economy and continually identify possible improvements in the collection of data on new and modified market instruments.

Some proposals: potential role of Stats SA

• Statistic South Africa provides most of the series used for the development of the composite business cycle indicators– One possible area for the increased

involvement of Stats SA is through undertaking required opinion surveys.

• Most of the opinion surveys in South Africa are conducted outside Stats SA, e.g. private sector.

Some proposals: potential role of Stats SA

• Phenomena like “shadow banking” and “off balance sheet” mechanisms, if these were prevalent in South Africa, would have completely eluded inclusion in business cycle indicators and hence proper monitoring.

– It remains imperative that Stats SA constantly monitor innovative developments in the economy and constantly identify possible improvements in the collection of data on modified and new market instruments.

Some proposals: potential role of Stats SA

• The South African business cycle approach seems to fare well in anticipating business cycles, but does not provide adequate signals to anticipate economic crises.

• The approach is also unable to provide direction on time, with delays of about 5 months to two years

Some proposals: potential role of Stats SA

• This study suggests (along proposals already made by statistics agencies of China, Korea, the Netherlands and others) the development of economic activity indicators that can be produced instantly with the release of any relevant new data, and provide an instant barometer of the current and prospective state of the economy

• The release of more monthly indicator time series, rather than quarterly series, would complement the approach

• Also, proposals such as “nowcasting”, meant to provide economic foresight have to be natured and fully explored

Some proposals: potential role of Stats SA

• Another area that needs constant attention, at least among statistical agencies, is the continued development of statistics across countries.

– Not all countries have clear business cycle indicator programs, many indicators are not seasonally adjusted, not deflated, not continuous, and do not have comparable frequencies.

– There is need for an organized effort to develop business cycle indicators internationally.

Conclusions

• The study outlined South Africa’s main business cycle forecasting approach, viz. the composite business cycle approach, and identifies the major shortcomings of the approach as:

(a) indicators are developed retrospectively with doubtful prospective inputs

(b) indicators do not provide useful signals to distinguish between prospective economic downturns and crises

(c) market innovations as depicted in “shadow banking” and “off balance sheet mechanisms” would not have been captured through current composite business cycle indicators

Conclusions

• The paper explores recent literature on business cycle forecasting and presents tentative proposals to

(a) quicken the production of composite indicators

(b) devise mechanisms that prospectively signal between a simple economic downturn and a crisis

(c) guard against market innovations that make monitoring difficult

(d) improved upkeep and processing of data internationally.

Conclusions

• The area of what approach to adopt, especially among the three major approaches, remains unclear.– The NBER approach is quite entrenched, historically

and in terms of usage across countries. The approach however posits significant challenges in terms of transparency and reproducibility of results

– Other proposed approaches that are more transparent with easily reproducible results, may develop to overtake the dominant NBER approach, especially if the current NBER data/infrastructure remains useful.

Thank you!