Business Cycle Chronology For Indian Economy: A Turning Point Analysis.

AuthorKaur, Sumanpreet


It is pertinent to observe and account for the business cycles in every economy in order to ensure smooth functioning of all the sectors by taming the fluctuations in time with the help of before hand signals. Moreover, the macroeconomic policies rely heavily on the phase of the business cycle. The monetary and fiscal policies are also subject to revision from time to time for stabilizing the business cycle fluctuations in the market economy and for reducing the extent of business cycle volatility. Therefore, for policy makers, the identification of expansion and contraction phases is of utmost significance so that stabilization policies can be framed accordingly and macroeconomic stabilization can be achieved. This calls for the dating of business cycles for an economy so that the identified chronology can be utilized by the policy makers for designing the appropriate polices and roadmap for smoothening out the fluctuations occurring in the economy from time to time.

The pioneering research work towards the study of repetitive forces triggering business cycles was undertaken by the National Bureau of Economic Research (NBER) in 1920 and its dating committee has been dating the business cycles for the U.S. economy. Business cycle analysis is of paramount importance for the Indian economy, keeping in view its changing characteristics, with increasing openness and market orientation and the concentration of more and more economic activities in the organized sector. However, in the pre-liberalized era, business cycle phenomenon was not so prevalent in the Indian economy since it was predominantly agricultural in nature and investment demand was also highly stable as it was majorly in the hands of the government sector. But in the following years, the Indian economy has undergone major changes (Patnaik & Sharma, 2002; Shah, 2008) which incorporated structural transitioning of the economy, making it vulnerable to cyclical uncertainties.

Business cycles can be seen as fluctuations in the aggregate economic activity and therefore, can be dated with the help of a reference series or an aggregate measure of economic activity. Often a single series has been used as the measure of aggregate economic activity for research purpose in business cycle analysis. While dealing with a single series, the most common rule of thumb is to date recessions if GDP experiences at least two successive quarters of decline. However, the two-quarters of decline is bound to happen in most recessions but it is neither necessary nor a sufficient condition for a recession to happen (Layton & Banerji, 2003). The exceptions to this rule of thumb can be found in empirical findings of many nations. The mere GDP declines are not always accompanied by the pronounced, pervasive and persistent declines in output, income, employment and trade (Banerji &Dua, 2011). So, this "two-quarter decline" rule of thumb is not applicable everywhere and if applied may give misleading results. Further, a composite index of coincident indicators from all the major sectors of an economy may also be compiled in order to date and measure business cycles. Nonetheless, in case of a single series to be adopted for business cycle analysis, GDP holds good proposition and it is the universally accepted measure for aggregate economic activity. However, in all economies, GDP is not recorded for higher frequencies and same is the case with the Indian economy. For Indian economy, annual estimates of GDP have been compiled and the quarterly estimates were made available from 1996. The monthly chronology of business cycles necessitated the need to analyze alternative monthly estimates of economic activity so as to precisely look for turning points in particular months. Therefore, another reference variable has to be chosen to carry out business cycle analysis which is maintained on a monthly frequency. Out of all the coincident variables available, IIP is the most celebrated one when it comes to be used as a proxy for GDP. Accordingly, the present paper attempts to date monthly business cycles for the Indian economy by taking IIP as the proxy for aggregate economic activity.

Review of Empirical Attempts

Some of the important studies are reviewed and reported below in order to get deeper insights into the comprehension of business cycles dating methods and procedures. Gangopadhyay and Wadhwa (1997) analyzed monthly IIP series for the period 1975 to 1995 and obtained the chronology of Indian business cycles. Dua and Banerji (2000) dated the classical and the growth rate cycles by constructing a coincident index for the Indian economy, following the traditional NBER procedure for the time period 1964 to 1997. The study identified six recessions and five expansions for the Indian economy. In a subsequent paper, Dua and Banerji (2001) constructed a composite leading index covering monetary, construction and the corporate sectors to anticipate business cycle and growth rate cycle upturns and downturns. Chitre (2001) analyzed 94monthly indicators to study the business cycles in India for the period 1951 to 1982. The reference series was constructed based on eleven economic indicators.

Patnaik and Sharma (2002) examined the presence of business cycles in the Indian economy and revealed that GDP growth has declined in 1957-58, 1965-66, 1979-1980 and 1991-92. Mohanty et al. (2003) attempted the cyclical analysis of monthly index of the industrial production in India and indicated that there have been 13 growth cycles in the Indian economy with varying durations during 1970-1971 to 2001-2000 and a composite leading index (CLI) was constructed and forecasted the turning points of the reference series with a lead period of about 6 months. A study by OECD (2006) for the period 1978 to 2004, identified seven growth cycles with an average duration of 38 months, using data on monthly IIP. OECD further developed a Composite Index of Leading Indicators (CILI) for India from the set of 30 indicators which registered a median lead of four months for all turning points. Nandi (2010) studied the role of global financial crisis in the Indian context by dating the growth cycles for Indian economy with IIP as the reference series from 1995 to 2010 by applying a dating algorithm developed by Bry and Boschan (1971), hereafter referred as BB procedure. The study revealed that the cycle has started its downturn from as early as August 2007, indicating a domestic industrial downturn before the global financial crisis. Further, the leading indicator index signaled a quick recovery from its trough in September 2007.

Banerjee and Dua (2011) defined business and growth rate cycles and described the importance of key coincident indicators and reference chronologies, subsequent to reflections on the definition of a recession. They further evaluated the robustness of the indicator approach for predicting business and growth rate cycles. Dua and Banerji (2012) described business and growth rate cycles with special reference to the Indian economy. The study employed the classical NBER approach to determine the timing of recessions and expansions as well as the chronology of growth rate cycles for the Indian economy. It described the performance of the leading index designed to anticipate business cycle and growth rate cycle upturns and downturns. Ghate et al. (2013) presented a comprehensive set of stylized facts for business...

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