preprints.org > business, economics and management > econometrics and statistics > doi: 10.20944/preprints202407.0302.v1 (registering DOI)

Preprint Article Version 1 This version is not peer-reviewed

Version 1 : Received: 2 July 2024 / Approved: 3 July 2024 / Online: 3 July 2024 (09:45:08 CEST)

In economics, especially econometrics, fixed-effects are widely recognized as powerful tools for heterogeneity analysis of longitudinal data sets. However, the existing research pays more attention to such as the variable selection, parameter estimation and dimension reduction on linear relationships with too many assumptions while nonlinear relationships are ubiquitous. In this paper, an extension fixed-effects model is proposed on the curve_fit nonlinear least squares. First, with the help of expert knowledge, the series regressions between independent variables including time and dependent variable is estimated on each series data, and the parameters are estimated by curve_fit. Similarly, the coeffection between independent variables including time and dependent variable is also initially estimated on the whole panel data. Second, the distance between regressions is defined, and then the coeffect function between the series regressions is obtained on the initial co-effect with curve_fit. Third, the time-effects and individual fixed-effects for each series data in the panel data are estimated on the differences of series regressions and co-effect function. Additionally, the effectiveness of the proposed method is varified on the synthetic data.

panel data analysis; fixed-effects; time-effects; curve_fit; nonlinear squares; function distance

Business, Economics and Management, Econometrics and Statistics

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