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DaSSWeb - Transformed Regression-based Long-Horizon Predictability Tests

June 7th | 14:30

DaSSWeb, Data Science and Statistics Webinar
Transformed Regression-based Long-Horizon Predictability Tests

Paulo Rodrigues

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We propose new tests for long-horizon predictability based on IVX estimation of a transformed regression which explicitly accounts for the over-lapping nature of the dependent variable in the long-horizon regression arising from temporal aggregation. To improve efficiency, we moreover incorporate the residual augmentation approach recently used in the context of short-horizon predictability testing by Demetrescu and Rodrigues (2022). Our proposed tests improve on extant tests in the literature in a number of ways. First, they allow practitioners to remain ambivalent over the strength of the persistence of the predictors. Second, they are valid under much weaker conditions on the innovations than extant long-horizon predictability tests; in particular, we allow for general forms of conditional and unconditional heteroskedasticity in the innovations, neither of which are tied to a parametric model. Third, unlike the popular Bonferroni-based methods in the literature, our proposed tests can handle multiple predictors, and can be easily implemented as either one or two-sided hypotheses tests. Monte Carlo analysis suggests that our preferred tests offer improved  finite sample properties compared to the leading tests in the literature. We report results from an empirical application investigating the use of real exchange rates for predicting nominal exchange rates and inflation.


Paulo M. M. Rodrigues (PhD, University of Manchester; Agregação, Universidade do Algarve). He is a senior research economist at the Bank of Portugal and Professor at Nova School of Business and Economics. He is also an external fellow of the Essex Centre for Financial Econometrics and of the Clive Granger Centre for Time Series Analysis at the University of Nottingham. He was a Jean Monnet Fellow at the European University Institute in Florence and visiting Scholar at the Institute for Advanced Studies in Vienna, Austria, the University of British Columbia, Vancouver, Canada and the University of Navarra, Spain.  Research interests include time-series econometrics, financial econometrics and empirical macroeconomics.  He has published a number of peer-reviewed articles in several internationally renowned scientific journals, including Journal of Econometrics, Econometric Theory, Econometrics Reviews, Journal of Financial Econometrics and Oxford Bulletin of Economics and Statistics, Review of Economics and Statistics

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