Forecasting Chilean Inflation with the Hybrid New Keynesian Phillips Curve: Globalisation, Combination, and Accuracy

Medel, Carlos A. (2017): Forecasting Chilean Inflation with the Hybrid New Keynesian Phillips Curve: Globalisation, Combination, and Accuracy.

Abstract

This article analyses the multihorizon predictive power of the Hybrid New Keynesian Phillips Curve (HNKPC) covering the period from 2000.1 to 2014.12, for the Chilean economy. A distinctive feature of this article is the use of a Global Vector Autoregression (GVAR) specification of the HNKPC to enforce an open economy version. Another feature is the use of direct measures of inflation expectations--Consensus Forecasts--differing from a fully-founded rational expectations model. The HNKPC point forecasts are evaluated using the Mean Squared Forecast Error (MSFE) statistic and statistically compared with several benchmarks, including combined forecasts. The results indicate that there is evidence to do not reject the hypothesis of the HNKPC for the Chilean economy, and it is also robust to alternative specifications. In predictive terms, the results show that in a sample previous to the global financial crisis, the evidence is mixed between atheoretical benchmarks and the HNKPC by itself or participating in a combined prediction. However, when the evaluation sample is extended to include a more volatile inflation period, the results suggest that the HNKPC (and combined with the random walk) delivers the most accurate forecasts at horizons comprised within a year. In the long-run the HNKPC deliver accurate results, but not enough to outperform the candidate statistical models.

• Item Type: MPRA Paper
• Language: English
• Keywords: New Keynesian Phillips Curve; inflation forecasts; out-of-sample comparisons; survey data; Global VAR; structured time-series models; forecast combinations
• Subjects: C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C26 - Instrumental Variables (IV) Estimation; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E31 - Price Level ; Inflation ; Deflation; E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications

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