Monetary Policy and Private Investment in India: The MIDAS Experience

  • Debasis RoojEmail author
  • Reshmi Sengupta


Recent evidence shows that Indian economy is experiencing a slowdown in private investment. Even after a significant decline in interest rates over the last two years, credit growth, particularly industrial credit growth, and private investment have remained sluggish. We examine the link between monetary policy and private investment in India by applying mixed-frequency vector autoregressive (MIDAS-VAR) method to monthly yield on 91-day T-bill, a proxy for monetary policy tool on quarterly bank loans, private investment, and gross domestic product. Mixed-frequency regression analysis includes variables of different frequencies into the analysis without the need for aggregating the higher-frequency variables into lower-frequency ones. Converting higher-frequency variables into lower-frequency variables often referred to as temporal aggregation is known to have an adverse impact on statistical inferences. MIDAS performs better in recovering the causal relationships between variables released at different frequencies when compared to the conventional common low-frequency approach by allowing having heterogeneous impacts on a low-frequency variable within each low-frequency time period. The mixed-frequency analysis reveals an interesting mix of results linking the monetary policy to the private investment in India. A comparative analysis with single-frequency (quarterly) analysis underestimates the influence of monetary policy. The mixed-frequency approach, therefore, yields richer economic insights into India’s sluggish investment than the classical single-frequency approach.


Monetary policy Mixed-frequency data analysis Private investment Indian economy 


  1. Anand, R., & Tulin, V. (2014). Disentangling India’s Investment Slowdown. Working Paper 14/47, International Monetary Fund, Washington, DC.Google Scholar
  2. Anderson, B. D. O., Deistler, M., Felsenstein, E., Funovits, B., Koelbl, L., & Zamani, M. (2016). Multivariate AR systems and mixed frequency data: G-identifiability and estimation. Econometric Theory, 32, 793–826.CrossRefGoogle Scholar
  3. Andreou, E., Ghysels, E., & Kourtellos, A. (2010). Regression models with mixed sampling frequencies. Journal of Econometrics, 158, 246–261.CrossRefGoogle Scholar
  4. Barkbu, B., Berkmen, S. P., Lukyantsau, P., Saksonovs, S., & Schoelermann, H. (2015). Investment in the Euro Area: Why Has It Been Weak? International Monetary Fund Working Paper No. 15/32.CrossRefGoogle Scholar
  5. Bussière, M., Ferrara, L., & Milovich, J. (2015). Explaining the Recent Slump in Investment: The Role of Expected Demand and Uncertainty. Banque de France Working Paper No. 571.Google Scholar
  6. Das, S., & Tulin, V. (2017). Financial Frictions, Underinvestment, and Investment Composition: Evidence from Indian Corporates (No. 17/134). International Monetary Fund.CrossRefGoogle Scholar
  7. Ghysels, E. (2016). Macroeconomics and the reality of mixed frequency data. Journal of Econometrics, 193, 294–314.CrossRefGoogle Scholar
  8. Ghysels, E., Hill, J. B., & Motegi, K. (2016). Testing for Granger causality with mixed frequency data. Journal of Econometrics, 192, 207–230.CrossRefGoogle Scholar
  9. Ghysels, E., Santa-Clara, P., & Valkanov, R. (2004). The MIDAS Touch: Mixed Data Sampling Regression Models, Working Paper, UCLA and UNC.Google Scholar
  10. International Monetary Fund (IMF). (2015, April). Private Investment: What’s the Holdup? World Economic Outlook (pp. 111–143).Google Scholar
  11. Lewis, C., Pain, N., Strásky, J., & Menkyna, F. (2014). Investment Gaps after the Crisis. OECD Economics Department Working Paper No. 1168.Google Scholar
  12. Leboeuf, M., & Fay, R. (2016). What Is Behind the Weakness in Global Investment? Bank of Canada Staff Discussion Paper No. 2016-5.Google Scholar
  13. McCracken, M. W., Owyang, M., & Sekhposyan, T. (2015). Real-Time Forecasting with a Large, Mixed Frequency, Bayesian VAR, No. 2015-030, FRB St Louis Paper.Google Scholar
  14. Motegi, K., & Sadahiro, A. (2018). Sluggish private investment in Japan’s Lost Decade: Mixed frequency vector autoregression approach. The North American Journal of Economics and Finance, 43, 118–128.CrossRefGoogle Scholar
  15. Motonishi, T., & Yoshikawa, H. (1999). Causes of the long stagnation of Japan during the 1990s: Financial or real? Journal of the Japanese and International Economies, 13, 181–200.CrossRefGoogle Scholar
  16. Saarenheimo, T. (1995). Credit crunch caused investment slump? An empirical analysis using Finnish data.Google Scholar
  17. Sadahiro, A. (2005). Sengo Nihon no Makuro Keizai Bunseki. Tokyo: Toyo Keizai Inc.Google Scholar
  18. Schembri, L. (2017, March 21). Getting Down to Business: Investment and the Economic Outlook. Remarks to the Greater Vancouver Board of Trade, Vancouver.Google Scholar
  19. Silvestrini, A., & Veredas, D. (2008). Temporal aggregation of univariate and multivariate time series models: A survey. Journal of Economic Surveys, 22, 458–497.CrossRefGoogle Scholar

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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.FLAME UniversityPuneIndia

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