Forecasting Chinese inflation and output: A Bayesian vector autoregressive approach

Huang, Y-F. (2012): Forecasting Chinese inflation and output: A Bayesian vector autoregressive approach.

Abstract

This study compares several Bayesian vector autoregressive (VAR) models for forecasting price inflation and output growth in China. The results indicate that models with shrinkage and model selection priors, that restrict some VAR coefficients to be close to zero, perform better than models with Normal prior.

• Item Type: MPRA Paper
• Language: English
• Keywords: BVAR; factor model; shrinkage priors
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General

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