Typically, the explanatory variables included in a regression model, in conjunction with the omitted relevant regressors implied by the usual error term, have both direct and indirect effects on the dependent variable. Attempts to obtain their separate estimates have been plagued with simultaneity issues. To circumvent these problems, this paper defines their sum as “total effects”, develops a time-varying coefficients methodology for their estimation without simultaneity bias, and applies these techniques to estimate the total effects of commercial bank credit per-capita on real GDP per-capita in Mauritius. An innovation is the introduction of extraneous variables that act as “coefficient drivers” chosen on the basis of best predictive performance, as measured by the smallest value of Theil’s U-statistic we were able to locate in the estimation.
CITATION STYLE
Swamy, P. A. V. B., Chang, I. L., von zur Muehlen, P., & Achameesing, A. (2022). The Role of Coefficient Drivers of Time-Varying Coefficients in Estimating the Total Effects of a Regressor on the Dependent Variable of an Equation. Journal of Risk and Financial Management, 15(8). https://doi.org/10.3390/jrfm15080331
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