Rizvi, Syed Kumail Abbas and Naqvi, Bushra (2009): Inflation Volatility: An Asian Perspective.
Download (1014Kb) | Preview
The primary purpose of this study is to model and analyze inflation volatility in ten selected Asian economies. We used quarterly data of inflation from 1987Q1 to 2008Q4 to model inflation volatility as time varying process through different symmetric and asymmetric GARCH specifications. We also proposed to model inflation volatility on the basis of cyclic component of inflation obtained from HP filter, instead of actual inflation when the latter does not fulfill the criterion of stationarity. Through news impact curves we tried to highlight the behavior of inflation volatility in response to lagged inflation shocks, under different GARCH specifications for selected economies. Bivariate granger causality test is also applied to analyze the direction of causality between inflation and different volatility estimates. We get few important results. At first, leverage parameter shows expected sign and is significant for almost all countries suggesting strong asymmetry in inflation volatility. The hyperbolic sign integral shape of news impact curves based on GJR-GARCH is not only consistent with the results of our previous study based on Pakistani data (Rizvi and Naqvi, 2008) but also highlight the importance of inflation stabilization programs particularly because of the subsequent evidences obtained in favor of bidirectional causality running between inflation and inflation volatility. We also found that cyclic component of inflation could be a suitable proxy of inflation for volatility estimation.
|Item Type:||MPRA Paper|
|Original Title:||Inflation Volatility: An Asian Perspective|
|English Title:||Inflation Volatility: An Asian Perspective|
|Keywords:||Inflation Volatility, Uncertainty, GJR-GARCH, EGARCH, Asymmetry, Asia, Asian|
|Subjects:||E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E31 - Price Level; Inflation; Deflation
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications
|Depositing User:||Syed Kumail Abbas Rizvi|
|Date Deposited:||23. Dec 2009 08:00|
|Last Modified:||17. Feb 2013 23:19|
Ahumada, H., Garegnani, M. L. (1999), “Hodrick-Prescott Filter in Practice”, Economica- (National-University-of-La-Plata); 45(4), pages 61-76.
Andersen, T.G., Bollerslev, T. (2006), "Volatility and Correlation Forecasting", Handbook of Economic Forecasting, Vol. 1.
Apergis, N. (2006), “Inflation, output growth, volatility and causality: evidence from panel data and G7 countries”, Economics Letters, 83 (2004) 185-191.
Ball, L. (1992), “How does inflation raise inflation uncertainty?”, Journal of Monetary Economics, 29, 371‐388.
Berument, H. et al (2001), “Modeling Inflation Uncertainty Using EGARCH: An Application to Turkey”, Bilkent University Discussion Paper.
Bilquees, F. (1988), “Inflation in Pakistan: Empirical Evidence on the Monetarist and Structuralist Hypotheses”, The Pakistan Development Review 27:2, 109–130.
Binner, J. M. et al (2009), “Does Money Matter in Inflation Forecasting?”, Federal Reserve Bank of St. Louis, Working Paper Series, 2009-030A.
Bollerslev, T. (1986), “Generalized Autoregressive Conditional Heteroscedasticity”, Journal of Econometrics, 31, 307‐27.
Bollerslev, T., and J.M. Wooldridge, (1992), “Quasi-Maximum Likelihood Estimation and Inference in Dynamic Models with Time-Varying Covariances”, Econometric Reviews, 11, 143-172.
Bokil, M. and Schimmelpfennig, A. (2005), “Three Attempts at Inflation Forecasting in Pakistan”, IMF Working Paper, WP/05/105.
Bordes, C. et al (2007), “Money and Uncertainty in the Philippines: A Friedmanite perspective”, Conference paper, Asia-Link Program.
Bordes, C. and Maveyraud, S. (2008), “The Friedman’s and Mishkin’s Hypotheses (re)considered”, Unpublished.
Brunner, A.D. and Hess, G.D. (1993), “Are Higher Levels of Inflation Less Predictable? A State-Dependent Conditional Heteroscedasticity Approach”, Journal of Business & Economic Statistics, Vol. 11, No. 2, (Apr., 1993), pp. 187-197.
Brunner, A.D. and Simon, D.P. (1996), “Excess Returns and Risk at the long End of The Treasury Market: an EGARCH-M Approach”, The Journal of Financial Research, 14, 1, 443- 457.
Caporale, T and McKiernan, B. (1997), “High and Variable Inflation: Further Evidence on the Friedman Hypothesis”, Economic Letters 54, 65-68.
Cecchetti, S. G. et al (2000), “The Unreliability of Inflation Indicators”, Current Issues in Economics and Finance, Federal Reserve Bank of New York, Vol. 6, No. 4.
Chaudhary, M. Aslam, and Naved Ahmad, (1996), “Sources and Impacts of Inflation in Pakistan,” Pakistan Economic and Social Review, Vol. 34, No. 1, pp. 21–39.
Cosimano, T. and Dennis, J. (1988), “Estimation of the Variance of US Inflation Based upon the ARCH Model”, Journal of Money, Credit, and Banking, 20(3) 409-423.
Crowford, A. and Kasumovich, M. (1996), “Does Inflation Uncertainty vary with the Level of Inflation?”, Bank of Canada, Ottawa Ontario Canada K1A 0G9.
Engle, R. (1982), “Autoregressive Conditional Heteroscedasticity with Estimates of United Kingdom Inflation”, Econometrica, 987-1007.
Fiorito, R. (2008), “Growth and Business Cycle Components”, Revised draft.
Fountas, S. et al (2000), “A GARCH model of Inflation and Inflation Uncertainty with Simultaneous Feedback”.
Fountas, S. et al (2006), “Inflation Uncertainty, Output Growth Uncertainty and Macroeconomic Performance”, Oxford Bulletin of Economics and Statistics, 68, 3 (2006) 0305-9049.
Franses, P.H. (1990), “Testing For Seasonal Unit Roots in Monthly Data”, Econometric Institute Report, No.9032A, Erasmus University, Rotterdam.
Friedman, M. (1977), “Nobel Lecture: Inflation and Unemployment”, Journal of Political Economy, Vol. 85, 451-472.
Glosten, L. R., R. Jagannathan and D. Runkle, (1993), “On the Relations between the Expected Value and the Volatility of the Normal Excess Return on Stocks”, Journal of Finance, 48, 1779-1801.
Golob, John E. (1994), “Does inflation uncertainty increase with inflation?”, Federal Reserve Bank of Kansas City - Economic Review. Third Quarter 1994.
Grier,K., Perry, M. (2000), “The effects of real and nominal uncertainty on inflation and output growth: some GARCH-M evidence”, Journal of Applied Econometric 15, 45-48.
Guay, A., St-Amant, P. (2005), “Do the Hodrick-Prescott and Baxter-King Filters Provide a Good Approximation of Business Cycles?”, Annales d’économie et de Statistique– N° 77 – 2005.
Harvey, A., and Trimbur, T. (2008), “Trend Estimation and the Hodrick-Prescott Filter”, J. Japan Statist. Soc. Vol. 38 No. 1, 41–49
Hafer, R. W. (1985), “Inflation Uncertainty and a test of the Friedman Hypothesis”, Federal Reserve Bank of St. Louis Working Paper 1985-006A.
Holland, A. S. (1984), “Does Higher Inflation Lead to More Uncertain Inflation?”, Federal Reserve Bank of St. Louis Review 66, 15-26.
Hu, M.Y., C.X. Jiang, and C. Tsoukalas, (1997), “The European Exchange Rates Before and After the Establishment of the European Monetary System”, Journal of International Financial Markets, Institutions and Money, 7, 235- 253.
Johnson, C. A. (2002), “Inflation Uncertainty In Chile: Asymmetries and the News Impact Curve”, Revista de Análisis Económico Vol. 17, Nº 1, 3-20.
Khalid, A. M. (2005), “Economic Growth, Inflation and Monetary Policy in Pakistan: Preliminary Empirical Estimates”, The Pakistan Development Review,44 : 4 Part II (Winter 2005) pp. 961–974.
Khan, M. S., and S. A. Senhadji (2001), “Threshold Effects in the Relationship between Inflation and Growth”, IMF Staff Papers 48:1.
Khan, A. H., and M. A. Qasim (1996)’ “Inflation in Pakistan Revisited”, The Pakistan Development Review 35:4, 747–759. Khan, M. S., and A. Schimmelpfennig (2006), “Inflation in Pakistan: Money or Wheat?”, IMF Working Paper, wp/06/60.
Koutmos, G., and G.G. Booth, (1995), “Asymmetric Volatility Transmission in International Stock Markets”, Journal of International Money and Finance, 14, 747-762.
Lunde, A. and Hansen, P. R. (2005) “A forecast comparison of volatility models: does anything beat a GARCH(1,1)?”, Journal of Applied Econometrics, vol. 20(7), pages 873-889.
Malik, W. Shahid and Ahmad, A. Maqsood (2007), “The Taylor Rule and the Macroeconomic performance in Pakistan”, The Pakistan Development Review, 2007:34.
Malik, W. Shahid (2006), “Money, Output and Inflation: Evidence from Pakistan”, The Pakistan Development Review 46:4.
Nas, T. F. and M.J. Perry, (2000), “Inflation, Inflation Uncertainty and Monetary Policy in Turkey”, Contemporary Economic Policy, 18, 170-180.
Nelson, D.B. (1991), “Conditional Heteroscedasticity in Asset Returns: A New Approach”, Econometrica, 59, 347-370.
Price, Simon, and Anjum Nasim, (1999), “Modeling Inflation and the Demand for Money in Pakistan: Cointegration and the Causal Structure,” Economic Modeling, Vol. 16, pp. 87– 103.
Thornton, J. (2006), “High and variable inflation: further evidence on the Fried- man hypothesis”, Southern African Journal of Economics, 74, 167-71.
Tse, Y., and G.G. Booth, (1996), “Common Volatility and Volatility Spillovers Between U.S. and Eurodollar Interest Rates: Evidence from The Features Market”, Journal of Economics and Business, 48, 299-312
Qayyum, A. (2006), “Money, Inflation and Growth in Pakistan”, The Pakistan Development Review 45 : 2 (Summer 2006) pp. 203–212.
Rizvi, S.K.A., and Naqvi, B., (2008), “Asymmetric Behavior of Inflation Uncertainty and Friedman-Ball Hypothesis: Evidence from Pakistan”, 26th Symposium on Money, Banking and Finance, Orleaons, France.
Zivot, E. (2008), “Practical Issues in the Analysis of Univariate GARCH Models”, Unpublished.
Available Versions of this Item
- Inflation Volatility: An Asian Perspective. (deposited 23. Dec 2009 08:00) [Currently Displayed]