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Forecasting inflation, industrial output and exchange rates : a template study for India
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posted on 2005-01-01, 00:00 authored by D Thomakos, Prasad BhattacharyaPrasad BhattacharyaThis paper reports results from a forecasting study for inflation, industrial output and exchange rates for India. We cannot reject the null hypothesis for linearity for all series used except for the growth rate of the foreign exchange series and our analysis is based on linear models, ARIMA and bivariate transfer functions and restricted VAR. Forecasting performance is evaluated using the models’ root mean-squared error differences and Theil’s inequality coefficients from recursive origin static, fixed origin dynamic and rolling origin dynamic forecasts. For models based on weekly data, based on RMSEs, we find that the bivariate models improve upon the forecasts of the ARIMA model while for models based on monthly data the ARIMA model has almost always better performance. In choosing between the two bivariate models on the basis of RMSEs, our overall results tend to support the use of a restricted VAR, as this model had the best forecasting performance more frequently than the transfer function model.
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Journal
Indian economic reviewVolume
40Issue
2Pagination
145 - 165Publisher
University of DelhiLocation
Dehli, IndiaISSN
0019-4670Language
engPublication classification
C1.1 Refereed article in a scholarly journalUsage metrics
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