The authors consider two alternative methods of forecasting real per capita GDP at various horizons: 1) univariate time series models estimated country by country; and 2) cross-country growth regressions. They evaluate the out-of-sample forecasting performance of both approaches for a large sample of industrial and developing countries. They find only modest differences between the two approaches. In almost all cases, differences in median (across countries) forecast performance are small relative to the large discrepancies between forecasts and actual outcomes. Interestingly, the performance of both models is similar to that of forecasts generated by the World Bank's Unified Survey. The results do not provide a compelling case for one approach over another, but they do indicate that there are potential gains from combining time series and growth-regression-based forecasting approaches.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)