Microeconometrics Using Stata, Second Edition, Volume I: Cross-Sectional and Panel Regression Models

Autor: 
Jazyk: 
english
Vazba: 
Měkká vazba
Počet stran: 
817
Microeconometrics Using Stata, Second Edition is an invaluable reference for researchers and students interested in applied microeconometric methods.Like previous editions, this text covers all the cl ...Celý popis
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Více informací
ISBN9781597183611
AutorCameron A. Colin
VydavatelStata Pr
Jazykenglish
VazbaPaperback
Rok vydání2022
Počet stran817

Popis knihy

Microeconometrics Using Stata, Second Edition is an invaluable reference for researchers and students interested in applied microeconometric methods.

Like previous editions, this text covers all the classic microeconometric techniques ranging from linear models to instrumental-variables regression to panel-data estimation to nonlinear models such as probit, tobit, Poisson, and choice models. Each of these discussions has been updated to show the most modern implementation in Stata, and many include additional explanation of the underlying methods. In addition, the authors introduce readers to performing simulations in Stata and then use simulations to illustrate methods in other parts of the book. They even teach you how to code your own estimators in Stata.

The second edition is greatly expanded--the new material is so extensive that the text now comprises two volumes. In addition to the classics, the book now teaches recently developed econometric methods and the methods newly added to Stata. Specifically, the book includes entirely new chapters on

  • duration models
  • randomized control trials and exogenous treatment effects
  • endogenous treatment effects
  • models for endogeneity and heterogeneity, including finite mixture models, structural equation models, and nonlinear mixed-effects models
  • spatial autoregressive models
  • semiparametric regression
  • lasso for prediction and inference
  • Bayesian analysis

Anyone interested in learning classic and modern econometric methods will find this the perfect companion. And those who apply these methods to their own data will return to this reference over and over as they need to implement the various techniques described in this book.

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