Forecasting Korean inflation
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초록
This paper studies the performance of various forecasting models for Korean inflation rates. The models studied in this paper are the AR(p) model, the dynamic predictive regression model with such exogenous variables as the unemployment rate and the term spread, the inflation target model, the random walk model, and the dynamic predictive regression model using estimated factors along with the unemployment rate and the term spread. The sampling period studied in this paper is 2000M11--2011M06. Among the studied models, the dynamic predictive regression model using estimated factors along with the unemployment rate and the term spread tends to perform best when the factors are extracted from I(1) series and the variables for the factor extraction are selected by the criterion of the correlation of each variable with the inflation rate
Abstract
This paper studies the performance of various forecasting models for Korean inflation rates. The models studied in this paper are the AR(p) model, the dynamic predictive regression model with such exogenous variables as the unemployment rate and the term spread, the inflation target model, the random walk model, and the dynamic predictive regression model using estimated factors along with the unemployment rate and the term spread. The sampling period studied in this paper is 2000M11--2011M06. Among the studied models, the dynamic predictive regression model using estimated factors along with the unemployment rate and the term spread tends to perform best when the factors are extracted from I(1) series and the variables for the factor extraction are selected by the criterion of the correlation of each variable with the inflation rate
참고문헌 (28)
- Ang A, "Do macro varifables, asset markets, or surveys forecast inflation better", Journal of Monetary Economics, 54, pp.1163~1212 (2007)
- Atkeson A, "Are phillips curves useful for forecasting inflation", Federal Reserve Bank of Minneapolis Quarterly Review, 25(1), pp.2~11 (2001)
- Bai J., "Estimating cross-section common stochastic trends in nonstationary panel data", Journal of Econometrics, 122, pp.137~183 (2004)
- Boivin J, "Are more data always better for factor analysis", Journal of Econometrics, 132, pp.169~194 (2006)
- Breiman L., "Bagging predictors", Machine Learning, 24, pp.123~140 (1996)
- Factor models, "Breitung J", Sogang university, ~ (2011)
- Canova F., "G-7 inflation forecasts: Random walk, Phillips curve or what else", Macroeconomic Dynamics, 11, pp.1~30 (2007)
- Choi I., "Efficient estimation of factor models", Econometric Theory, 28, pp.274~308 (2012)
- Efficient estimation of nonstationary factor models, "Choi I", Sogang University, ~ (2011)
- Connor G, "Performance measurement with the arbitrage pricing theory: A new framework for analysis", Journal of Financial Economics, 15, pp.373~394 (1986)
- Diebold, FX, "Comparing predictive accuracy", Journal of Business and Economic Statistics, 13, pp.134~144 (1995)
- Diron M, "Are inflation targets good inflation forecasts", Economic Perspectives, pp.33~45 (2008)
- Do Phillips curves conditionally help to forecast inflation, "Dotsey M", Federal Reserve Bank of Philadelphia, ~ (2011)
- Eickmeier S, "How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach", Journal of Forecasting, 27, pp.237~265 (2008)
- Estrella A, "The predictive power of the term structure of interest rates in Europe and the United States: Implications for the European central bank", European Economic Review, 41, pp.1375~1401 (1997)
- Fisher J, "When can we forecast inflation", Federal Bank of Chicago Economic Perspectives, 26(1), pp.30~42 (2002)
- Forni M, "Do financial variables help forecasting inflation and real activity in the euro area", Journal of Monetary Economics, 50, pp.1243~1255 (2003)
- Inoue A, "How useful is bagging in forecasting economic time series? A case study of U.S. consumer price inflation", Journal of the American Statistical Association, 103, pp.511~522 (2008)
- Kozicki S, "Predicting real growth and inflation with the yield spread", Federal Bank of Kansas City Economic Review, 82, pp.39~57 (1997)
- Mishkin FS, "What does the term structure tell us about future inflation", Journal of Monetary Economics, 25, pp.77~95 (1990)
- Stock JH, "Forecasting inflation", Journal of Monetary Economics, 44, pp.293~335 (1999)
- Stock JH, "Macroeconomic forecasting using diffusion indexes", Journal of Business & Economic Statistics, 20, pp.147~162 (2002)
- Stock JH, "Forecasting output and inflation: The role of asset prices", Journal of Economic Literature, 41, pp.788~829 (2003)
- Stock JH, "Chapter 10: Forecasting with many predictors, In Handbook of Economic Forecasting", pp.515~554 (2006), Elsevier
- Phillips curve inflation forecasts. No 14322, "Stock JH", National Bureau of Economic Research, ~ (2008)
- Timmermann A, "Chapter 4: forecast Combinations, In Handbook of Economic Forecasting Elsevier", pp.135~196 (2006)
- Forecasting using supervised factor models, "Tu Y", University of California, ~ (2011)
- Wright JH, "Forecasting US inflation by Bayesian model averaging", Journal of Forecasting, 28, pp.131~144 (2009)