Abstract
In this paper, we consider the forecasting power, both in- and out-of-sample, of 11 financial variables with respect to the growth rate of Indian industrial production over the monthly out-ofsample period of 2005:4–2011:4, using an in-sample of 1994:1–2005:3. The financial variables used are: M0, M1, M2, M3, lending rate, 3-month Treasury bill rate, term spread, real effective exchange rate, real stock prices, dividend yield and non-food credit growth. We observe that that, at times, in-sample and out-of-sample predictive ability of the financial variables tend to coincide. We find relatively strong evidence of out-of-sample predictability for at least one of the horizons for M0, M1, M2, M3, the lending rate and real share price growth rate. The term-spread and dividend yield are added to the list when weaker versions of the out-of-sample test statistics are considered as well. Given that we consider a large number of financial variables, when we checked the significant results by accounting for data mining across the 11 financial variables, majority of these results ceases to be significant, with only M0, M1 and M2 retaining some of its predictive ability.
Highlights
There exists a large international literature dealing with the role of financial variables in forecasting real output growth1
As can be seen, the little evidence, at times conflicting, that exists regarding the role of financial variables in forecasting Indian output growth is mainly in-sample
The monthly data used in this study, covering the period of 1994:1–2011:4, are obtained from the Handbook of Statistics on the Indian economy provided by the Reserve Bank of India (RBI),Global Financial Database (GFD) and International Monetary Fund’s (IMF) International Financial Statistics (IFS)
Summary
There exists a large international literature dealing with the role of financial variables in forecasting real output growth. One needs to analyse whether adding financial variables over and above the information already contained in the lagged output growth improves predictability of the latter over an outof-sample, besides within-sample Against this backdrop, we consider the forecasting power of 11 financial variables with respect to the growth rate of Indian industrial production over the monthly outof-sample period of 2005:4–2011:4, using an in-sample of 1994:1–2005:3. We use the Harvey et al (1998) and Clark and McCracken (2001) statistics to test the null hypothesis that the out-of-sample forecasts of industrial production growth from a benchmark autoregressive (AR) model encompass the forecasts from the ARDL model that includes a given financial variable.
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