Business Cycles and Economic Growth
Volume 18, Number 4 Article by Pradeep Banerjee December, 2006
Business Cycles and Economic Growth – An Analysis Using Leading Indicators : Edited by Pami Dua, 2004, Oxford University Press, New Delhi, pp 350, Price: Rs 650 (cloth). :
The growing complexity of the economic world has prompted a number of enquiries, generating in the process methodologies that are progressively more effective in their explanatory capabilities, and developing into relevant branches of study. One such field of study is that of business cycles. The text under review is an aggregate of papers whose concern is about ‘measuring, monitoring, and forecasting economic activity’. Pami Dua, who has edited the text, introduces the contents by pointing out that predicting the level as well as the direction of change in economic activity – ‘reading the economic tea leaves’, as she puts it – is a challenging task even for the best forecasters. Research in this area, however, does ‘vouch for the fact that the business cycle is very much alive and well’ and that ‘the ongoing efforts of the researchers (confirm) that tracking, measuring, and predicting cyclical fluctuations can greatly enhance our understanding of the economy as well as improve forecasting accuracy.’
An early researcher in the area of business cycles was Wesley Clair Mitchell, who attempted to build theoretical explanatory models based on empirical data about ‘cyclical alterations of prosperity and depressions’ over periods from different economies where such alterations were seen. In a 1938 paper, Mitchell along with Arthur F Burns presented a list of indicators that accompany cyclical activities. ‘Measuring Business Cycles’, a pioneering work in the area still cited by later day researchers, was a 1946 publication by these two researchers that defined the phenomenon and set out the methodology to be used for the analysis of business cycles. The text under review is dedicated to Geoffrey Moore, another early team member at the National Bureau of Economic Research (NBER) along with Mitchell and Burns. Moore later set up the Centre for International Business Cycle Research. In 1996 he also set up the Economic Cycle Research Institute in New York, an institute converging its work in the area of business cycles.
The sixteen chapters that make up the text fall into three sections. The first collection of essays focuses on the analytics and constructs in use to study business cycles; the second set evaluates the efficacy of leading indexes and the third focuses on applications of business cycles analysis. The final section deals with the Indian economy. The first section in entitled ‘Indicator Approach to Business, Growth, and Growth Rate Cycles’. The term ‘Indicator’ refers to Economic Indicator Analysis (EIA), a methodology developed at NBER by Moore and his associates. EIA is structured around the observations of repetitiveness, as seen in cycles of expansions occurring at about the same time in many economic activities, followed by similarly general recessions, contractions and revivals, which were pointed out by Mitchell and Burns as an attribute of market economies. The EIA approach aggregates trends of select economic indicators that would mark the various stages of a cycle. The choice of more than one indicator is to ensure better representation of the economy and to aggregate economic activities. Forecasting that an expansion would be followed by a contraction of the economy is probably an easier matter than forecasting the turning points such as business cycle peaks and business cycle troughs. This is where the indicator analysis approach, long a focus of research, has been notably productive. Indicator categories have been aggregated as leading, coincident and lagging categories. Coincident indicators are measures included in the basic notion of the business cycle, the measure of macroeconomic fluctuations included in the definition – income, output, employment, sales etc. Economic activities that precede or anticipate changes in coincident indicators are called leading indicators. These generally represent commitments made with respect to future activity or are factors that influence such commitments, and include such items as housing permits issued, new orders placed by producers, prevailing stock prices, interest rate range, and change in corporate profitability. Lagging indicators include measures of activity which customarily follow, and therefore confirm, the changes in the coincident indicators. Thus, a turning point in the lagging index, say a peak, indicates that the leading index has reached a trough and that the economy would now be entering an expansionary phase. The reason for including time series data for a number of items instead of just one, such as the GDP of the economy, is that such a method avoids dependence on one measure as a proxy for aggregate economic activity. That is the reason as to why the lagging index that tracks say the quantum of unemployment in the economy is so relevant when assessing the state of the economy. As empirical observation has shown that certain series in certain conditions turn out to have a better value over those of other series, it is advisable to rely on all such potentially useful (series) as a group1. Such findings have significantly enhanced our ability to discern trends in the economy and as also forecast probable movements.
The papers in the second section evaluate the efficacy of leading indexes such as recession prediction models as evident from their performances, and test them out in real life occurrences such as the 2001 recession in the US economy. Another essay assesses the performance of the Composite Leading Economic Indicator (CLI) index, originally developed by the US Department of Commerce and subsequently transferred in early 1996 to the Conference Board, a private economic research unit. The Conferen ce Board evaluated the components that make up the CLI and decided to add certain new series in the place of some of the earlier ones with the aim of making the CLI more in sync with the US economy. The new index has been found to be more capable of diagnosing changes in business cycles.
The third part of the text deals with applications of business cycles analysis, including a study of the Great Depression, which still continues to draw researchers. This study focuses on the manner in which economic agents arrive at decisions using information available at specific points in time. There was an element of optimism in the early period of 1930 and the stock market recorded a recovery at that time. Economic agents reached their decisions working on numbers that were available then. And yet, as Boulier et al point out in their paper ‘Measuring the Onset of the Great Depression: Then and Now’, the data was misleading and what was being reported in 1929 and early 1930 was not what was actually occurring. The economy did not record any increase in production; it was instead going into a least anticipated deflation.
The final group of papers would be of special interest to those interested in the Indian economy. As Dua points out, these papers on the Indian economy apply the economic indicator approach to construct and analyse cyclical fluctuations in economic activity. Vikas Chitre’s paper, ‘Indicators of Business Recessions and Revivals in India: 1951-1982’, is an effort to prepare a systematic list of indicators of business recessions and revivals in India. This is an important work for students of the Indian economy for not much has been researched in this area earlier. Additional papers that track business and growth rate cycles in the economy up to the 90s, and some on specific sectors of the economy, add value to the book.
This is an important book and is strongly recommended. Readers will benefit from its coverage of various themes. The text elaborates on technical details of business cycles and as also about finer aspects of this important branch of economics.
References
1. Zarnowitz, V, and C Boschan, 1975, ‘Cyclical Indicators: An Evaluation and New Leading Indexes’ in Handbook of Cyclical Indicators, Washington, Government Printing Office. Cited in Dua, P, and A Banerji, ‘Monitoring and Predicting Business and Growth Rate Cycles in the Indian Economy’ in P Dua (Ed) Business Cycles and Economic Growth, Oxford University Press, 2004.
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