- مبلغ: ۸۶,۰۰۰ تومان
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This paper compares the quality of forecasts from DSGE models with and without financial frictions. We find that accounting for financial market imperfections does not result in a uniform improvement in the accuracy of point forecasts during non-crisis times, while the average quality of density forecast actually deteriorates. In contrast, adding frictions in the housing market proves very helpful during times of financial turmoil, outperforming both the frictionless benchmark and the alternative that incorporates financial frictions in the corporate sector. Moreover, we detect complementarities among the analyzed setups that can be exploited in the forecasting process.
In this paper we have compared the quality of point and density forecasts from a richly-specified DSGE model and its two extensions that introduce financial frictions into the corporate and household sectors. We have found that accounting for financial frictions does not result in an overall improvement in the quality of forecasts during normal times, but does offer statistically and economically significant gains in forecast efficiency during times of financial turmoil. In this respect, the model variant featuring the housing market has proved particularly successful, beating both the benchmark and the alternative that incorporates financial imperfections in the corporate sector. These findings suggest that developing models which include the housing sector should provide better guidance during turbulent times. However, our results also indicate that maintaining all three model variants may be warranted. This recommendation is supported by the relatively good performance of pooled forecasts and a substantial degree of time variation in the weights that optimize the forecast errors or predictive densities.