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Article

The Role of Coefficient Drivers of Time-Varying Coefficients in Estimating the Total Effects of a Regressor on the Dependent Variable of an Equation

by
Paravastu Ananta Venkata Bhattanatha Swamy
1,
I-Lok Chang
2,
Peter von zur Muehlen
1,* and
Amit Achameesing
3
1
Federal Reserve Board, 20th & Constitution Avenue, Washington, DC 20551, USA
2
Department of Mathematics and Statistics, American University, 4400 Massachusetts Avenue, Washington, DC 20016, USA
3
Business School, University of Stellenbosch, Carl Cronje Dr, Bellville, Cape Town 7530, South Africa
*
Author to whom correspondence should be addressed.
J. Risk Financ. Manag. 2022, 15(8), 331; https://doi.org/10.3390/jrfm15080331
Submission received: 10 June 2022 / Revised: 5 July 2022 / Accepted: 6 July 2022 / Published: 27 July 2022
(This article belongs to the Special Issue Predictive Modeling for Economic and Financial Data)
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Abstract

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.
Keywords: total effects; bank credit; economic growth; direct effects; indirect effects; threshold regression; real GDP; coefficient drivers; Theil’s U statistic total effects; bank credit; economic growth; direct effects; indirect effects; threshold regression; real GDP; coefficient drivers; Theil’s U statistic

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MDPI and ACS Style

Swamy, P.A.V.B.; Chang, I.-L.; von zur Muehlen, P.; Achameesing, A. The Role of Coefficient Drivers of Time-Varying Coefficients in Estimating the Total Effects of a Regressor on the Dependent Variable of an Equation. J. Risk Financ. Manag. 2022, 15, 331. https://doi.org/10.3390/jrfm15080331

AMA Style

Swamy PAVB, Chang I-L, von zur Muehlen P, Achameesing A. 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. 2022; 15(8):331. https://doi.org/10.3390/jrfm15080331

Chicago/Turabian Style

Swamy, Paravastu Ananta Venkata Bhattanatha, I-Lok Chang, Peter von zur Muehlen, and Amit Achameesing. 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, no. 8: 331. https://doi.org/10.3390/jrfm15080331

APA 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), 331. https://doi.org/10.3390/jrfm15080331

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