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This chapter introduces heterogeneity in the 2TSF model, in different ways. We develop a model where moments of a distribution depend on covariates and are estimated by maximum likelihood. We also exploit the “scaling property” to obtain a model without distributional assumptions that can be estimated by nonlinear least squares. The empirical application of the chapter compares the various approaches.

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Incorporating Heterogeneity in the 2TSF Model

  • 章节

  • 发表日期：

    2025年

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  • Alecos Papadopoulos,
  • Christopher F. Parmeter

摘要

This chapter introduces heterogeneity in the 2TSF model, in different ways. We develop a model where moments of a distribution depend on covariates and are estimated by maximum likelihood. We also exploit the “scaling property” to obtain a model without distributional assumptions that can be estimated by nonlinear least squares. The empirical application of the chapter compares the various approaches.