International Finance Discussion Papers (IFDP)
March 1990
Evaluating the Predictive Performance of Trade-Account Models
Jaime Marquez and Neil R. Ericsson
Abstract:
This paper evaluates the distributional properties of forecasts from six econometric models of the U.S. trade account. Using stochastic (Monte Carlo) simulation, we derive confidence intervals and forecast-based test statistics which account for uncertainty from future disturbances and from coefficient estimation. Empirically, the confidence intervals of the trade-account forecasts are very wide, and are generally (but not necessarily) increasing with the forecast horizon. Even with such a large degree of uncertainty, some models exhibit "predictive failure" when tested. To evaluate forecasts across models, we generalize Chong and Hendry's (1986) forecast-encompassing test statistic to allow for model nonlinearity and to account for uncertainty arising from estimation. All models are rejected by this test, i.e., the data are highly informative. Although both the calculated forecast uncertainty and the test failures temper the role of these models in formulating policy, the failures imply the potential for improved model specification with narrower confidence bands.
A robust, competitive manufactured goods sector is also key. A growing manufactured goods sector increase the flexibility of the economy to respond to external and internal shocks and is associated with higher per capita income growth. World trade in manufactures is growing faster and at relatively better and less votatile terms of trade than trade in commodities. Criteria such as labor productivity in agriculture and manufacturing, population growth rates, and changes in the share of production and exports of manufactured goods provide evidence of which countries of the new generation can take advantage of the manufacturing dynamic.
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