The kernel estimation method is a nonparametric procedure for analysing economic models. It is a data-based procedure which avoids the a priori parametric specification of the economic model, and it has become popular because of its wide applicability and well-developed theory. A substantial literature has developed where the local polynomial kernel estimator has been proposed to analyse various economic models, which include regression models, single-index models, dynamic time series models and panel data models. The frontier of this subject is expected to develop further in both theory and applications, especially with advances in computer technology.
Bootstrap Convergence Cross-section econometrics Curse of dimensionality Kernel estimators in econometrics Linear models Local modelling Nonlinear models Nonlinear time-series analysis Nonparametric regression Time-series econometrics
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Fan, J., and I. Gijbels. 1996. Local polynomial modeling and its applications. London: Chapman and Hall.Google Scholar