پیش بینی نرخ تورم کانادا: یک رویکرد NKPC نیمه ساختاری
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|47510||2014||9 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Economic Modelling, Volume 43, December 2014, Pages 183–191
We examine whether alternative versions of the New Keynesian Phillips Curve equation contain useful information for forecasting the inflation process. We notably consider semi-structural specifications which combine, for closed- and open-economy versions of the model, the structural New Keynesian equation with time series features. Estimation and inference are conducted using identification-robust methods to address the concern that NKPC models are generally weakly identified. Applications using Canadian data show that all the considered versions of the NKPC have a forecasting performance that comfortably exceeds that of a random walk equation, and moreover, that some NKPC versions also significantly outperform forecasts from conventional time series models. We conclude that relying on single-equation structural models such as the NKPC is a viable option for policymakers for the purposes of both forecasting and being able to explain to the public structural factors underlying those forecasts.