Microeconometrics Using Stata. Volume 2, Nonlinear Models and Casual Inference Methods
2nd edition
Par : , Formats :
- Nombre de pages1675
- PrésentationBroché
- FormatGrand Format
- Poids1.734 kg
- Dimensions18,5 cm × 23,6 cm × 5,2 cm
- ISBN978-1-59718-362-8
- EAN9781597183628
- Date de parution28/07/2022
- ÉditeurStata Press
Résumé
Microeconometrics Using Stata, Second Edition is aimed at both students and researchers of economics and related social sciences. The first volume is intended to be a self-contained treatment that might also be used as an applied econometrics course text. It focuses on the linear regression model and includes instrumental-variables estimation, random- and fixed-effects models, quantile regression, and analytical and bootstrap inference.
It additionally provides a brief introduction to nonlinear regression models. The second volume covers models for binary, multinomial, censored, duration, and count outcomes for both cross-sectional and panel datasets. It then covers causal methods for exogenous and endogenous treatment evaluations, spatial regression, semiparametric methods, machine learning for prediction and for causal inference, and Bayesian methods.
It additionally provides a brief introduction to nonlinear regression models. The second volume covers models for binary, multinomial, censored, duration, and count outcomes for both cross-sectional and panel datasets. It then covers causal methods for exogenous and endogenous treatment evaluations, spatial regression, semiparametric methods, machine learning for prediction and for causal inference, and Bayesian methods.
Microeconometrics Using Stata, Second Edition is aimed at both students and researchers of economics and related social sciences. The first volume is intended to be a self-contained treatment that might also be used as an applied econometrics course text. It focuses on the linear regression model and includes instrumental-variables estimation, random- and fixed-effects models, quantile regression, and analytical and bootstrap inference.
It additionally provides a brief introduction to nonlinear regression models. The second volume covers models for binary, multinomial, censored, duration, and count outcomes for both cross-sectional and panel datasets. It then covers causal methods for exogenous and endogenous treatment evaluations, spatial regression, semiparametric methods, machine learning for prediction and for causal inference, and Bayesian methods.
It additionally provides a brief introduction to nonlinear regression models. The second volume covers models for binary, multinomial, censored, duration, and count outcomes for both cross-sectional and panel datasets. It then covers causal methods for exogenous and endogenous treatment evaluations, spatial regression, semiparametric methods, machine learning for prediction and for causal inference, and Bayesian methods.
