Tiwari, Aviral (2010): Impact of supply of money on food prices in India: A causality analysis.
Preview |
PDF
MPRA_paper_24679.pdf Download (106kB) | Preview |
Abstract
This study attempts to investigate the direction of casualty between food prices and money supply in the static and dynamic framework. We found that narrow measure of money supply (M1) Granger causes food inflation while broad measure of money supply (M3) does not in the static framework. This implies that money supply (M1) is not neutral in determining food prices in the long run in the Indian context. From the dynamic framework of analysis we found that any one innovation in the broad measure of money supply (M3) will have positive impact on the food inflation for next three years.
Item Type: | MPRA Paper |
---|---|
Original Title: | Impact of supply of money on food prices in India: A causality analysis |
English Title: | Impact of supply of money on food prices in India: A causality analysis |
Language: | English |
Keywords: | Food Prices. Money Supply. Granger-causality |
Subjects: | Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q11 - Aggregate Supply and Demand Analysis ; Prices E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E51 - Money Supply ; Credit ; Money Multipliers C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C31 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions ; Social Interaction Models |
Item ID: | 24679 |
Depositing User: | aviral tiwari |
Date Deposited: | 22 Sep 2010 14:22 |
Last Modified: | 27 Sep 2019 08:34 |
References: | Bessler and A. David (1984). Relative prices and money: a vector autoregression on brazilian data. Amer. J. Agric. Econ 66, pp. 25-30. Devadoss, S. and William H. Meyers (1987). Relative prices and money: further results for the United States. Amer. J. Agric. Econ 69, pp. 838-42. Gonzalo, J. (1994). Five alternative methods of estimating long-run equilibrium relationships. Journal of Econometrics 60 (1/2), pp. 203–233. Harris R. (1995). Using cointegration analysis in econometric modeling. Prentice Hall, pp: 82. Hye, Q. M. A. and S. Anwar (2009). Food prices and money supply: a causality analysis for Pakistan economy. Amer. J. Agric. Econ 6 (2), pp. 227-230. Johansen, S. and K. Juselius (1990). Maximum likelihood estimation and inference on cointegration with applications to money demand. Oxford Bulletin of Economics and Statistics 52, pp. 169-210. Mackinnon, J. G. (1996). Numerical distribution functions for unit root and cointegration test. Journal of Applied Econometrics 11, pp. 601-618. Mackinnon, J. G., Alfred A. Haug, and Leo Michelis (1999). Numerical distribution functions of likelihood ratio test for cointegration. Journal of Applied Econometric 14, pp. 563-577. Phillips, P., and Pierre Perron (1988). Testing for a Unit Root in Time Series Regression. Biometrica 75, pp. 335-346. Tweeten, L.G. (1980). Macroeconomics in crisis: agriculture in an understanding economy. Amer. J. Agric. Econ 62, pp. 853-865. Urzua, C. M. (1997). Omnibus test for multivariate normality based on a class of maximum entropy distributions. Advances in Econometrics 12, pp. 341-358. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/24679 |