Information Theoretic Estimation of Econometric Functions

Millie Yi Mao () and Aman Ullah
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Millie Yi Mao: Azusa Pacific University

No 201923, Working Papers from University of California at Riverside, Department of Economics

Abstract: This chapter introduces an information theoretic approach to specify econometric functions as an alternative to avoid parametric assumptions. We investigate the performances of the information theoretic method in estimating the regression (conditional mean) and response (derivative) functions. We have demonstrated that they are easy to implement, and are advantageous over parametric models and nonparametric kernel techniques.

Keywords: Information theory; Maximum entropy distributions; Econometric functions; Conditional mean (search for similar items in EconPapers)
Pages: 24 Pages
Date: 2019-11
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (1)

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https://economics.ucr.edu/repec/ucr/wpaper/201923.pdf First version, 2019 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:ucr:wpaper:201923

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