پایداری تورم در ایران: رویکرد انباشته کسری
محورهای موضوعی : اقتصاد کار و جمعیتحسین امیری 1 , علی اصغر سالم 2 , مرجانه بشخور 3
1 - استادیار اقتصاد دانشگاه خوارزمی
2 - استادیار اقتصاد دانشگاه علامه طباطبایی
3 - کارشناس ارشد اقتصاد
کلید واژه: طبقهبندی JEL:C22, E31 . واژگان کلیدی: پایداری تورم, رویکرد انباشته کسری, روشهای کلاسیک, تخمین بیزین, پارامتر حافظه,
چکیده مقاله :
هدف این مقاله تحلیل پایداری تورم در ایران با استفاده از یک رویکرد عمومی می باشد. برای این منظور نرخ تورم در ایران در دوره زمانی 1395- 1316 و بر اساس رویکرد انباشته کسری (FI) مدلسازی و در مرحله بعد پارامتر حافظه تورم با استفاده از روش های کلاسیک (روش شبه پارامتریک GPH، حداقل مربعات غیرخطی، حداکثر درست نمایی دقیق و تخمین زن حداقل فاصله) و بیزین برآورده شده است. نتایج حاصل از برآورد به هر دو روش نشان می دهد که نرخ تورم در ایران پایدار می باشد. پایداری نرخ تورم دلالت ها و کاربردهای مهمی در سیاستگذاری به خصوص سیاست گذاری پولی دارد؛ به طوری که در اثر وارد شدن شوک ها و تکانه های اقتصادی بر تورم، اثرات آن تا مدت زمان طولانی ماندگار خواهد بود. بنابراین لازم است تا سیاستگذاران منابع عمده منحرفکننده نرخ تورم از جمله وابستگی به درآمدهای نفتی، عدم توجه به نقش و کارکرد صندوق ذخیره ارزی، کسری بودجههای مداوم دولت، به رسمیت شناخته نشدن استقلال بانک مرکزی و نیز وجود مشکلات ساختاری را شناسایی و در سیاستگذاریهای اقتصادی رویکردهای مناسبی در این زمینه اتخاذ کنند.
The aim of this paper is to analyzing the persistency of inflation in Iran by using a general approach, with the goal of providing a plausible and acceptable explanation. For this, the inflation rate of Iran in period 1937-2016 and on the base of fractionally integrated (FI) approach was modeled and in the later phase inflation memory parameter has been estimated by using classic methods (the Geweke and Porter-Hudak semi parametric method nonlinear least squares, exact maximum likelihood, and a minimum distance estimator) and Bayesian methods. The results of the estimation in both methods show that the inflation rate in Iran is stable. Stability of inflation rates has important implications for policy-making, especially monetary policy, so that due to the impact of economic shocks on inflation, its effects will be last for a long time. Therefore, it is necessary to policy makers identify the major sources of distorting inflation, including dependence on oil resources, no attention to the role and function of the reserve fund, the government budget deficit, central bank dependence and the existence of structural problems and consider appropriate approaches in this field.
منابع
- جعفری صمیمی، احمد، بالونژاد نوری، روزبه (1392). کاربرد روشهای نیمه پارامتریک و موجکها در بررسی وجود پایداری نرخ تورم در ایران. فصلنامه مدلسازی اقتصادی، 7 (23): 30-15.
- Agiakloglou, C., Newbold, P. and Wohar, M. (1992). Bias in an estimator of the fractional difference parameter. Journal of Time Series Analysis, 14 (3): 235–46.
- Agostinelli, C. and Bisaglia, L. (2010). ARFIMA Processes and Outliers: a Weighted Likelihood Approach. Journal of Applied Statistics, 37: 1569-1584.
- Andersen, T.G., and Bollerslev, T. (1997). Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns. Journal of Finance, 52 (3): 975–1005.
- Andersen, T.G., Bollerslev, T., Diebold, F.X. and Labys, P. (1999). The Distribution of Exchange Rate Volatility. NBER Working Paper No. 6961.
- Andrews, Donald W.K. (1991). Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation. Econometrica, 59 (3): 817–58.
- Bai, J., and Perron, P. (1998). Estimating and Testing Linear Models with Multiple Structural Changes. Econometrica, 66 (1): 47–78.
- ———. (2003a). Computation and Analysis of Multiple Structural Change Models. Journal of Applied Econometrics, 18 (1): 1–22.
- ———. (2003b). Critical Values for Multiple Structural Change Tests. The Econometrics Journal, 6 (1): 72–78.
- Batini, N. (2002). Euro Area Inflation Persistence. Working Paper No. 201, European Central Bank.
- Beran, J. (1994). Statistics for Long-Memory Processes. New York: Chapman & Hall.
- Breidt, F.J., Crato, N., and Lima, P.D. (1998). The Detection and Estimation of Long Memory in Stochastic Volatility. Journal of Econometrics, 83 (1–2): 325–48.
- Calvo, G.A. (1983). Staggered Prices in a Utility-Maximizing Framework. Journal of Monetary Economics 12 (3): 383–98.
- Christiano, L.J., Eichenbaum, M., and Evans, C. (2001). Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy. Working Paper No. 2001-08, Federal Reserve Bank of Chicago.
- Chauvet, M. and Kim, I. (2010). Micro Foundations of Inflation Persistence in the New Keynesian Phillips Curve. MPRA Paper 2310, University Library of Munich, Germany.
- Coenen, G., and Wieland, V. (2005). A Small Estimated Euro Area Model with Rational Expectations and Nominal Rigidities. European Economic Review, 49 (5): 1081–1104.
- Cogley, T., and Sargent, T.J. (2001). Evolving Post-World War II U.S. Inflation Dynamics. In NBER Macroeconomics Annual, ed. Ben S. Bernanke and Kenneth S. Rogoff.
- Cuestas, J.C., Harrison, B. (2010). Inflation persistence and nonlinearities in Central and Eastern European countries. Econom Lett, 106: 81–83.
- Dickey, D.A., and Fuller, W.A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49 (4): 1057–72.
- Diebold, F.X., and Rudebusch, G.D. (1989). Long Memory and Persistence in Aggregate Output. Journal of Monetary Economics, 24 (2): 189–209.
- Diebold, F.X., and Senhadji, A.S. (1996). The Uncertain Unit Root in Real GNP: Comment. American Economic Review, 86 (5): 1291–98.
- Ding, Z., Granger, C.W.J., and Engle, R.F. (1993). A Long Memory Property of Stock Market Returns and a New Model. Journal of Empirical Finance, 1 (1): 83–106.
- Dolado J.J., Gonzalo, J., and Mayoral, L. (2002). A Fractional Dickey-Fuller Test for Unit Roots. Econometrica, 70 (5): 1963–2006.
- Doornik, J.A., and Ooms, M. (2001). A Package for Estimating, Forecasting and Simulating ARFIMA Models: ARFIMA Package 1.01 for Ox. Mimeo, University of Rotterdam.
- Driscoll, J., and Steiner Holden, S. (2004). Fairness and Inflation Persistence. Journal of the European Economic Association, 2 (2): 240–51.
- Fuhrer, J.C. (1997). The (UN) Importance of Forward-Looking Behavior in Price Setting. Journal of Money, Credit, and Banking, 29 (3): 338–50.
- Fuhrer, J., and Moore, G. (1995). Inflation Persistence. Quarterly Journal of Economics, 110 (1): 127–59.
- Gali, J., and Gertler, M. (1999). Inflation Dynamics: A Structural Econometric Analysis. Journal of Monetary Economics, 44 (2): 195–222.
- Gali, J., Gertler, M., and L´opez-Salido, J.D. (2001). European Inflation Dynamics. European Economic Review, 45 (7): 1237–70.
- Geweke, J., and Porter-Hudak, S. (1983). The Estimation and Application of Long Memory Time Series Models. Journal of Time Series Analysis, 4:221–38.
- Granger, C.W.J, and Joyeux, R. (1980). An Introduction to Long Memory Series. Journal of Time Series Analysis, 1:15–30.
- Hall, R.E. (1999). Comment on Rethinking the Role of NAIRU in Monetary Policy: Implications of Model Formulation and Uncertainty, by Arturo Estrella and Frederic S. Mishkin. In Monetary Policy Rules, ed. John B. Taylor. Chicago: University of Chicago Press.
- Hassler, U., Meller, B. (2014). Detecting multiple breaks in long memory: the case of US inflation. Empir Econ, 46: 653–680.
- Haubrich, J.G., and Andrew W.L. (2001). The Sources and Nature of Long-Term Memory in Aggregate Output. Economic Review (Q II):15–30, Federal Reserve Bank of Cleveland.
- Hosking, J. R.M. (1981). Fractional Differencing. Biometrika, 68 (1): 165–76.
- Kim, C.J, Nelson, C.R., and Piger. J. (2004). The Less-Volatile U.S. Economy: A Bayesian Investigation of Timing, Breadth, and Potential Explanations. Journal of Business and Economic Statistics, 22 (1): 80–93.
- Koop, G., Ley, E., Osiewalski, J., and Steel, M.F.J. (1997). Bayesian Analysis of Long Memory and Persistence using ARFIMA Models. Journal of Econometrics, 76 (1–2):149–69.
- Kwiatkowski, D.; Phillips, P.; Schmidt, P.; and Shin, Y.; (1992). Testing the Null Hypothesis of Stationary against the Alternatives of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root? Journal of Econometrics, 54: 159-178
- Levin, A., and Piger. J.M. (2003). Is Inflation Persistence Intrinsic in Industrial Economies? Working Paper No. 023E, Federal Reserve Bank of St. Louis.
- Mandelbrot, B., and Wallis, J.R. (1969). Robustness of the Rescaled Range R/S in the Measurement of Noncyclic Long-Run Statistical Dependence. Water Resources Research, 5:967–88.
- Mayoral, L. (2004a). A New Minimum Distance Estimator for ARFIMA Processes. Mimeo.
- Newey, W.K., and West, K.D. (1994). Automatic Lag Selection in Covariance Matrix Estimation. Review of Economics Studies, 61:631–53.
- Ng, S., and Perron, P. (2001). Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power. Econometrica, 69 (6): 1519–54.
- O’Reilly, G., and Whelan, K. (2004). Has Euro-Area Inflation Persistence Changed over Time? Working Paper No. 335, European Central Bank.
- Perron, P. (1989). The Great Crash, the Oil Price Shock and the Unit Root Hypothesis. Econometrica, 58: 1361–1401.
- Phillips, P.C.B., and Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75 (2): 335–46.
- Pivetta, F., and Reis, R. (2004). The Persistence of Inflation in the United States. Mimeo, Harvard University.
- Roberts, J.M. (2001). How Well Does the New Keynesian Sticky-Price Model Fit the Data? Finance and Economics Discussion Series Paper No. 2001-13, Board of Governors of the Federal Reserve System.
- Rotemberg, J. (1987). The New Keynesian Micro foundations. Macroeconomics Annual, 2:69–104.
- Sargent, T.J. (1999). The Conquest of American Inflation. Princeton, NJ: Princeton University Press.
- Sowell, F. (1992a). Maximum Likelihood Estimation of Stationary Univariate Fractionally Integrated Time Series. Journal of Econometrics, 53 (1–3): 165–88.
- ———. (1992b). Modeling Long-Run Behavior with the Fractional ARIMA Model. Journal of Monetary Economics, 29 (2): 277–302.
- Stock, J. (2001). Comment on Evolving Post World War II U.S. Inflation Dynamics. Mimeo, Harvard University.
- Taylor, J.B. (1979). Staggered Wage Setting in a Macro Model. American Economic Review, 69: 108–13.
- ———. (1980). Aggregate Dynamics and Staggered Contracts. Journal of Political Economy, 88 (1): 1–23.
- ———. (1998). Monetary Policy Guidelines for Unemployment and Inflation Stability. In Inflation, Unemployment and Monetary Policy, ed. Robert M. Solow and John B. Taylor. Cambridge, MA: MIT Press.
- ———. (2000). Low Inflation, Pass-Through and the Pricing Power of Firms. European Economic Review, 44 (7): 1389–1408.
- Tillmann, P. (2012). Has inflation persistence changed under EMU? German Economic Review, 13(1): 86–102.
- Zaffaroni, P. (2004). Contemporaneous Aggregation of Linear Dynamic Models in Large Economies. Journal of Econometrics, 120 (1): 75–102.
_||_