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Log Income vs. Linear Income: An Application of the Encompassing Principle

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  • Luigi Ermini
  • David F. Hendry

Abstract

An open question in empirical economics is whether models should be estimated by using the actual, or linear, values of economic variables or their logarithms. This paper applies the principle of encompassing to suggest specification and mis‐specification tests of log vs. linear individual equations fitted to I(1) data, and illustrates the analysis for US quarterly disposable income. The finite‐sample properties of the encompassing tests are examined in a Monte Carlo experiment customized to the parameter values found in the empirical analysis.
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  • Luigi Ermini & David F. Hendry, 1991. "Log Income vs. Linear Income: An Application of the Encompassing Principle," Working Papers 199111, University of Hawaii at Manoa, Department of Economics.
    • Handle: RePEc:hai:wpaper:199111
    Note: To request a hard copy of this paper, please email the department at econ@hawaii.edu.
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    3. Cheng-Feng Cheng, 2012. "Evaluate the Effectiveness of Manager Compensation," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 11(1), pages 25-44, June.
    4. Katarina Juselius & Niels Framroze Møller & Finn Tarp, 2014. "The Long-Run Impact of Foreign Aid in 36 African Countries: Insights from Multivariate Time Series Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 153-184, April.
    5. Jonas Harnau, 2018. "Log-Normal or Over-Dispersed Poisson?," Risks, MDPI, vol. 6(3), pages 1-37, July.
    6. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5.
    7. Masayoshi Hayashi, 2013. "On the Decomposition of Regional Stabilization and Redistribution," CIRJE F-Series CIRJE-F-910, CIRJE, Faculty of Economics, University of Tokyo.
    8. Ricardo Ramírez-Aldana & Lizbeth Naranjo, 2021. "Random intercept and linear mixed models including heteroscedasticity in a logarithmic scale: Correction terms and prediction in the original scale," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-21, April.
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