Modelling with Discretized Variables

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Tác giả: Felix Chan, Laszlo Matyas, Agoston Reguly

Ngôn ngữ: eng

Ký hiệu phân loại: 001.43 Historical, descriptive, experimental methods

Thông tin xuất bản: 2024

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 202094

Comment: 35 pages, 4 tables, 2 figuresThis paper deals with econometric models in which the dependent variable, some explanatory variables, or both are observed as censored interval data. This discretization often happens due to confidentiality of sensitive variables like income. Models using these variables cannot point identify regression parameters as the conditional moments are unknown, which led the literature to use interval estimates. Here, we propose a discretization method through which the regression parameters can be point identified while preserving data confidentiality. We demonstrate the asymptotic properties of the OLS estimator for the parameters in multivariate linear regressions for cross-sectional data. The theoretical findings are supported by Monte Carlo experiments and illustrated with an application to the Australian gender wage gap.
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