Currency forecasting based on an error components-seemingly unrelated nonlinear regression model

Abstract

This paper proposes to forecast foreign exchange rates by means of an error components-seemingly unrelated nonlinear regression (EC-SUNR) model and, simultaneously, explore the interrelationships among currencies from newly industrializing economies with those of highly industrialized countries. Based on the empirical results, we find that the EC-SUNR model improves on the performance of forecasting foreign exchange rates in comparison with an intrinsically nonlinear dynamic speed of adjustment model that has been shown to outperform several other important models in the forecasting literature. We also find evidence showing that the foreign exchange markets of the newly industrializing countries are influenced by those of the highly industrialized countries and vice versa, and that such interrelationships affect the accuracy of currency forecasting. Copyright © 2005 John Wiley & Sons, Ltd.

Chief executive officer compensation, firm performance, and strategic coopetition: A seemingly unrelated regression approach

“…= AGE (CEO's age), X10 = OWN (value of shares owned by the CEO excluding stock options), and ε it is the random error for the ith regression equation. SUR is a model and a tool of pooling cross-sectional and time-series or panel data (Kmenta, 1997;Zellner, 1962 The error components (EC, Nerlove, 1971) and the EC-SUR (Avery, 1977;Lin, 2005)…”

“…The error components (EC, Nerlove, ) and the EC‐SUR (Avery, ; Lin, ) model have been proposed to pool panel data. But these models are not suitable for us to analyze the coopetition phenomena.…”