A Markov switching approach to business cycles in India

Abstract

AbstractThis is the first empirical study that analyzes the nature of business cycles in India using quarterly GDP growth data from 1998Q1 to 2022Q4 and the Markov Switching Auto-regressive model. In order to capture the impact of exclusion and inclusion of post pandemic period data, it has developed two alternative models. Based on these models, the study provides the forecast of quarterly GDP growth and cumulative real output losses due to the pandemic. It also provides alternative scenarios and trajectories of the Indian economy towards the US$ 5 trillion milestone. It is our hope that these results will be useful to policymakers and other stakeholders to understand the business cycle issue in India and take appropriate strategies to overcome the problems associated with these cycles.Keywords: Indian economybusiness cyclesMarkov switchingturning pointsforecastsJEL CLASSIFICATION: C22C51E32E37E66 AcknowledgmentBoth authors are thankful to anonymous referees of the journal for their useful comments and suggestions.Disclosure statementNo potential conflict of interest was reported by the authors.Notes1 The switching model dates back to Quandt (Citation1958), Goldfeld and Quandt (Citation1973), Barber, Robertson, and Scott (Citation1997), and Lindgren (Citation1978).2 The economic interpretation of these three regimes is as follows: a low growth regime is characterized by a negative/low growth rate, and is therefore associated with the classic recession phases; an intermediate growth regime or a regime of moderate expansion in which the economic growth rate is below the trend growth rate without recession; and a high expansion regime where the economic growth rate is above the trend, representing a strong phase of the growth cycles.3 In India, the nation-wide lockdown was implemented on 25th March 2020 (MHA 2020). As suggested in Srivastava et al. (Citation2021), we assume that the small number of days of lockdown in March 2020 would not severely affect the GDP figure in that quarter. Hence, our sample period ends at 2020Q4 (corresponds to March 2020).4 The GDP quarterly data are available with different base year. From 1998Q1 to 2004Q4, the base is 1999-00; from 2005Q1 to 2011Q4, the base is 2004-05 and after that the base is 2011–12. Since this study uses the growth rate, the base change does not affect the analysis.5 The ADF test values are -3.963 (p = 0.002) for the data without COVID period and -3.390 (p= 0.0137) for the data including the COVID period data.6 This is in line with Dua and Sharma (Citation2016) who used MS(3)-AR(0) specification.7 To check the validity of the model, the sample size is restricted to 1983Q1 to 2016Q4 for estimating the Model 1, which is used to make the forecast from 2017Q1 to 2020Q4. While the real GDP had fluctuated between 2.94 per cent (2020Q4) and 9.66 per cent (2017Q2) during the forecast period, a comparison of the forecasts with the actual data reveals that the RMSE is just 0.72 per cent whereas the mean absolute error is 0.51 per cent. Theil’s U2 inequality coefficient is just 0.64. These results imply that the forecast accuracy is good. A similar exercise for Model 2 produces RMSE of 1.25 per cent and a Mean Absolute Error of 1.12 per cent8 RBI’s Report on Currency and Finance (2022–23) shows that India’s output loss (real) was ₹19.1 lakh crore in 2020–21, ₹17.1 lakh crore in 2021–22 and ₹16.4 lakh crore in 2022–23, i.e. a total loss of ₹52.6 lakh crore in the short run.9 If India reaches US5 trillion-dollar economy by 2024–25 as targeted, India’s per capita income will cross the minimum per capita GDP required to be an upper middle-income country (US$4466) by 2027–28. But as per our model, it will reach 5 trillion US dollar mark in 2028–29 and therefore, India will reach the upper middle income country status by 2030-31. For this purpose, we use the projected population data for India provided by UN (Citation2022).Additional informationNotes on contributorsMathew Koshy OdasserilK.R. Shanmugam is the director and professor of Madras School of Economics (India). He is specialized in Public Economics, Macroeconomic modelling and Applied Economics. He has published more than 50 research articles in various national and international journals.K. R. ShanmugamMathew Koshy Odasseril is a senior Research Scholar at Madras School of Economics. He is specialized on Macro Economic modelling and Public Economics.