and Its Components:
An Exploratory Analysis
break. Alternatively, one may derive clues by visually examining the data and statisti- cally test the break point indicated by the graph. The second approach looks for evi- dence from the data by a sequential testing procedure without any a priori assumption based on theory or visual query. In other words, the second approach is about deriv- ing the break point endogenously rather than testing for a break point given exogenously.
There has been some discussion
about when India’s growth began to slow down – did the deceleration occur before or after the onset of the global crisis? This article subjects quarterly GDP estimates to a statistical analysis to identify the break point in growth. It also illustrates the possibilities of examining break points in a trend in an interactive manner.
1 The Context
n recent months, several scholars have made the observation that growth of the gross domestic product (GDP) in India had started decelerating even before the crisis hit the world economy towards the end of the year 2008. See, for example, Rakshit (2009), Bhanumurthy and Kumawat (2009) and Srinivasan (2009). In other words, the process of growth acceleration until 2006-07 had already run out of steam before the crisis came to precipitate the fall in the growth rate further. Although there are signs of a recovery of the economy since the first quarter of the current financial year, the concern that the benefits of earlier reforms have played themselves out lead- ing to a deceleration still remains valid. Because, in that case, the optimism about a recovery to the earlier growth path over time may not be warranted and we may need a closer look at the sources of that growth. This brief note presents an exploratory analysis of the Indian quarterly GDP series at factor cost (1999-2000 prices), and a few of its aggregate components, for the period 1996-97 to 2008-09.1 Essentially, it is a
search for statistical evidence of a structural break during the recent period in India. It is also a search for a way to examine such changes in the time-series data which is transparent and tangible in its approach without falling into the traps inherent in
The Chow (1960) Test is most commonly used for exogenous break point in different variations. Over the past two decades or so, there has been a substantial growth of lit- erature on the methodology of determining structural breaks endogenously (See Bai (1997), Bai and Perron (2003), Altissimo and Corradi (2003), among many others.) However, the supremacy of any single ap- proach is yet to emerge to establish itself as the “best practice” in the post Chow-test era. As a result, for a practitioner, there is the dilemma of choosing between pre-specified break point(s) which can vary from one re- searcher to another, and the endogenously determined break point(s) which can vary from one test to another. In such a situa- tion, a middle road seems to be a practical approach. In the exploration presented here, a simple-minded mix of smoothing approaches is used to describe the trend. Visual judgment is complemented by statistical tests in the process of creating the descriptions. However, the statistical tests used here should probably be consid- ered only as indicative exercises as the un- derlying assumptions of these tests are not strictly valid, in general. For brevity of presentation, only the essential results are included in this note. Detailed results can be downloaded by the
Chandan Mukherjee (chandan.mukherjee@ gmail.com) is at the National Institute of Public F inance and Policy, New Delhi.
such data (time-patterns in a random walk,2 for example, can lead to a misleading im- pression of a trend). Broadly speaking, there are two approaches to the statisti- cal...