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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

1. Core Inflation Dynamics and Impact of Demand and Supply Shocks: Evidence from India

verfasst von : Priyanka Sahu, Naresh Kumar Sharma

Erschienen in: Current Issues in the Economy and Finance of India

Verlag: Springer International Publishing

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Abstract

This paper attempts to investigate the impact of demand and supply side factors on core inflation in India. First, we empirically calculate core inflation through conventional exclusion based measure (excluding food, excluding energy and excluding both food and energy) as well as statistical measure (asymmetric trimmed mean approach). Next, we empirically try to observe the association of core inflation with macroeconomic variables through autoregressive-distributed lag model (ARDL) and bound test approach. Empirical findings based on ARDL bound test approach confirms the existence of short run and long run association of core inflation with macroeconomic variables. Overall, the response of core inflation to demand-side factors is high in case of real variables as compared to monetary variables and its response to skewness-based supply-side factor is high as compared to food and fuel inflation.

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Nächstes Kapitel Demand for Money in India: An ARDL Approach
Fußnoten
1
Weight for each component of CPI is collected from Ministry of Statistics and Programme Implementation
 
2
Estimated Trimmed mean (48.5_20) core inflation is used as a proxy for core inflation in the econometric modelling.
 
3
Skewness based inflation or supply shock is calculated by differencing core inflation (calculated through asymmetric trim mean approach) from headline inflation.
 
4
ARDL bound test is convenient to use with a combination of stationary and non-stationary data (at level).
 
Literatur
Alkhareif, R. M., & Barnett, W. A. (2015). Core inflation indicators for Saudi Arabia. Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, 62(3), 257–266.
Baxter, M., & King, R. G. (1999). Measuring business cycles: Approximate band-pass filters for economic time series. Review of economics and statistics, 81(4), 575–593.
Bernanke, B. S. (2007). Inflation Expectations and Inflation Forecasting. Monetary Economics Workshop of the National Bureau of Economic Research Summer Institute, Cambridge, Mass.
Bhattacharya, R., & Patnaik, I. (2014). Monetary policy analysis in an inflation targeting framework in emerging economies: The case of India. Working Papers 14/131, National Institute of Public Finance and Policy.
Blinder, A ., & Reis, R. (2005). Understanding the Greenspan standard in Federal Reserve Bank of Kansas City, The Greenspan era: lessons for the future.proceedings of the 2005 Jackson Hole Symposium, pp 11–96.
Bodenstein, M., Erceg, C. J., & Guerrieri, L. (2008). Optimal monetary policy with distinct core and headline inflation rates. Journal of Monetary Economics, 55, 18–33.
Bryan, M. F., & Cecchetti, S. G. (1994). Measuring core inflation. In Monetary policy (pp. 195–219). Chicago: The University of Chicago Press.
Cecchetti, S. G. (1996). Measuring short-run inflation for central bankers. Working paper 5786. National Bureau of Economic Research.
Clark, T. (2001). Comparing measures of core inflation. Federal Reserve Bank of Kansas City Economic Review, 86(2), 5–31.
Cogley, T. (2002). A simple adaptive measure of core inflation. Journal of Money, Credit, and Banking, 34(1), 94–113.CrossRef
Darbha, G., & Patel, U.R. (2012). Dynamics of inflation “herding”: Decoding India’s Inflationary Process: Brookings Report.
Dolmas, J. (2005). Trimmed mean PCE inflation. Working Papers 0506, Federal Reserve Bank of Dallas.
Eckstein, O. (1981). Core Inflation. Englewood Cliffs, N.J.: Prentice-Hall.
Edward, K., & Saeed, Z. (2017). Nowcasting US Headline and Core Inflation. Journal of Money, Credit and Banking, 49(5), 931–968.
Gamber, E. N., Smith, J. K., & Eftimoiu, R. (2015). The dynamic relationship between core and headline inflation. Journal of Economics and Business, 81, 38–53.CrossRef
Gordon, R. J. (1977). The Theory of Domestic Inflation. The American Economic Review, 67(1): 128–134.
Gordon, R. J. (1982). Price Inertia and Policy Ineffectiveness in the United States, 1890–1980. Journal of Political Economy, 90(6): 1087–1117.
Hallman, J. J., & Anderson, R. G. (1993). Has the long-run velocity of M2 shifted? Evidence from the P* model. Economic Review, 29(1), 14.
Hallman, J. J., Porter, R. D., & Small, D. H. (1991). Is the price level tied to the M2 monetary aggregate in the long run? The American Economic Review, 841–858.
Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551–1580.
Johansen, S. (1995). A stastistical analysis of cointegration for I (2) variables. Econometric Theory, 11(1), 25–59.
Kar, S. (2009). Statistical tools as measures of core inflation for India. Indian Economic Review, 225–245.
Kiley, M. T. (2008). Estimating the common trend rate of inflation for consumer prices and consumer prices excluding food and energy prices. Divisions of Research & Statistics and Monetary Affairs, Federal Reserve Board.
Moses, C. K. (2013). The P-star model of inflation and its performance for the Kenyan economy. International Journal of Economics and Finance, 5(9), 82.
Laflèche, T., & Armour, J. (2006). Evaluating measures of core inflation. BoC Review, 19, 29.
Marques, C. R., Neves, P. D., & Sarmento, L. M. (2003). Evaluating core inflation indicators. Economic Modelling, 20(4), 765–775.CrossRef
Mishkin, F. S. (2007). Headline versus core inflation in the conduct of monetary policy. In: Business Cycles, International Transmission and Macroeconomic Policies Conference, HEC Montreal, Montreal, Canada.
Mohanty, D., Rath, D. P., & Ramaiah, M. (2000). Measures of core inflation for India. Economic and Political Weekly, 35(5), 273–282.
Naresh, S., & Motilal, B. (2015). Measuring core inflation in India: An asymmetric trimmed mean approach. Cogent Economics & Finance, 3(1), 1014252, 1–15.
Pesaran, M.H., Shin, Y. (1999). An autoregressive distributed lag modelling approach to cointegration analysis. In: Strom, S. (Ed.), Econometrics and Economic Theory in 20th Century: The Ragnar Frisch Centennial Symposium. Cambridge University Press, Cambridge Chapter 11.
Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of applied Econometrics, 16(3), 289–326.CrossRef
Quah, D., & Vahey, S. P. (1995). Measuring core inflation. The Economic Journal, 105(432), 1130–1144.CrossRef
Raj, J., & Misra, S. (2011). Measures of core inflation in India–an empirical evaluation. Reserve Bank of India Department of Economic and Policy Research Working Paper 16.
Ramachandran, M., & Kumar, R. (2017). Inflation and shocks. Development research Group, Reserve Bank of India.
Rich, R. W., & Steindel, C. (2005). A review of core inflation and an evaluation of its measures. Federal Reserve Bank of New York Staff Reports, no. 236
Rina, B. (2013). Inflation dynamics and monetary policy transmission in Vietnam and emerging Asia. Journal of Asian Economics, 34, 16–26.
Metadaten
Titel
Core Inflation Dynamics and Impact of Demand and Supply Shocks: Evidence from India
verfasst von
Priyanka Sahu
Naresh Kumar Sharma
Copyright-Jahr
2018
Buch
Current Issues in the Economy and Finance of India

Print ISBN: 978-3-319-99554-0

Electronic ISBN: 978-3-319-99555-7

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-99555-7_1