Journal of Economic Dynamics and Control ( IF 1.620 ) Pub Date : 2021-06-18 , DOI: 10.1016/j.jedc.2021.104177 Sacha Gelfer
This paper examines the inferences and forecasting benefits that can be made when one incorporates a large quantity of economic time series into international structural macroeconomic models. I estimate a close variation of Adolfson et al. (2007a, 2008) small open-economy dynamic stochastic general equilibrium (DSGE) model in a data-rich environment and evaluate its predictive performance of the Canadian macroeconomy. The data set I use in the paper includes Canadian, American, Asian and European macro-financial data. I compare the forecasting performance of the DSGE model estimated in a data-rich environment (DSGE-DFM) to the forecasts generated by the DSGE model estimated in its traditional fashion and forecasts generated by other reduced form forecasting models. I find that an open-economy DSGE model estimated in a data-rich environment significantly out performs its regularly estimated DSGE counterpart. Further, DSGE-DFM forecasts that incorporate real-time data are similar or better to the Bank of Canada’s Staff Economic Projections for GDP, consumption, investment, and trade statistics. In addition, the DSGE-DFM model of this paper is useful in forecasting both the real and nominal exchange rate in the short and medium-term.
中文翻译:
在数据丰富的环境中评估开放经济 DSGE 模型的预测能力
本文考察了将大量经济时间序列纳入国际结构宏观经济模型时可以做出的推论和预测收益。我估计阿道夫森等人的密切变化。(2007a, 2008) 在数据丰富的环境中建立小型开放经济动态随机一般均衡 (DSGE) 模型并评估其对加拿大宏观经济的预测性能。我在论文中使用的数据集包括加拿大、美国、亚洲和欧洲的宏观金融数据。我将在数据丰富的环境 (DSGE-DFM) 中估计的 DSGE 模型的预测性能与以传统方式估计的 DSGE 模型生成的预测以及其他简化形式预测模型生成的预测进行了比较。我发现在数据丰富的环境中估计的开放经济 DSGE 模型明显优于其定期估计的 DSGE 模型。此外,纳入实时数据的 DSGE-DFM 预测与加拿大银行对 GDP、消费、投资和贸易统计数据的员工经济预测相似或更好。此外,本文的 DSGE-DFM 模型对于预测中短期实际汇率和名义汇率都非常有用。