Abstract
It is popular to summarize the relationship between an outcome variable y and a vector (x, z) through a linear mean regression where the mean of y is modelled as a linear function of both x and z. A more robust specification is called for in some situations where the imposed linear relationship between (the mean of) y and z is suspect. A partially linear specification allows for a regression function that maintains linearity in x but allows the effect of z to be nonlinear. This partially linear model has been widely studied in the statistics and the semiparametric econometrics literature.
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Bibliography
Ahn, H., and J. Powell. 1993. Semiparametric estimation of censored selection models. Journal of Econometrics 58: 3–29.
Engle, R., C. Granger, C. Rice, and J. Weiss. 1986. Semiparametric estimates of the relation between weather and electricity sales. Journal of the American Statistical Association 81: 310–320.
Hardle, W. 1991. Applied nonparametric regression. New York: Cambridge University Press.
Hardle, W., H. Liang, and J. Gao. 2001. Partially linear models (contributions to statistics). Heidelberg: Physica-Verlag.
Heckman, J. 1974. Shadow wages, market wages and labor supply. Econometrica 42: 679–693.
Robinson, P. 1988. Root-n-consistent semiparametric regression. Econometrica 56: 931–954.
Schmalensee, R., and T. Stoker. 1999. Household gasoline demand in the United States. Econometrica 67: 645–662.
Speckman, P. 1988. Kernel Smoothing in partial linear models. Journal of the Royal Statistical Society, B 50: 413–436.
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Tamer, E. (2018). Partial Linear Model. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_2228
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DOI: https://doi.org/10.1057/978-1-349-95189-5_2228
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