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This book presents a broad range of applied econometric techniques for environmental econometrics and illustrating how they can be applied in Stata.
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This book presents a broad range of applied econometric techniques for environmental econometrics and illustrating how they can be applied in Stata.
Produktdetails
- Produktdetails
- Verlag: Stata Press
- Seitenzahl: 416
- Erscheinungstermin: 10. Mai 2021
- Englisch
- Abmessung: 240mm x 184mm x 29mm
- Gewicht: 894g
- ISBN-13: 9781597183550
- ISBN-10: 1597183555
- Artikelnr.: 62232585
- Verlag: Stata Press
- Seitenzahl: 416
- Erscheinungstermin: 10. Mai 2021
- Englisch
- Abmessung: 240mm x 184mm x 29mm
- Gewicht: 894g
- ISBN-13: 9781597183550
- ISBN-10: 1597183555
- Artikelnr.: 62232585
Christopher F. Baum is a professor of economics and social work at Boston College. Baum has taught econometrics for many years, using Stata extensively in academic and nonacademic settings. He has over 40 years of experience with computer programming and has authored or coauthored several widely used Stata commands. He is the author of An Introduction to Modern Econometrics Using Stata and An Introduction to Stata Programming, Second Edition. He is an associate editor of the Stata Journal and maintains the Statistical Software Components Archive of community-contributed Stata materials. Stan Hurn is a professor of econometrics at Queensland University of Technology. He held previous positions at the University of Glasgow and at Brasenose College, Oxford. He is a fellow of the Society for Financial Econometrics. His main research interests are in the field of time-series econometrics, and he has been published widely in leading international journals. He is also the coauthor of Econometric Modelling with Time Series: Specification, Estimation and Testing and Financial Econometric Modeling.
1 Introduction 2 Linear regression models 3 Beyond ordinary least squares 4
Introducing dynamics 5 Multivariate time-series models 6 Testing for
nonstationarity 7 Modeling nonstationary variables 8 Forecasting 9
Structural time-series models 10 Nonlinear time-series models 11 Modeling
time-varying variance 12 Longitudinal data models 13 Spatial models 14
Discrete dependent variables 15 Fractional integration A Using Stata
Introducing dynamics 5 Multivariate time-series models 6 Testing for
nonstationarity 7 Modeling nonstationary variables 8 Forecasting 9
Structural time-series models 10 Nonlinear time-series models 11 Modeling
time-varying variance 12 Longitudinal data models 13 Spatial models 14
Discrete dependent variables 15 Fractional integration A Using Stata
1 Introduction 2 Linear regression models 3 Beyond ordinary least squares 4
Introducing dynamics 5 Multivariate time-series models 6 Testing for
nonstationarity 7 Modeling nonstationary variables 8 Forecasting 9
Structural time-series models 10 Nonlinear time-series models 11 Modeling
time-varying variance 12 Longitudinal data models 13 Spatial models 14
Discrete dependent variables 15 Fractional integration A Using Stata
Introducing dynamics 5 Multivariate time-series models 6 Testing for
nonstationarity 7 Modeling nonstationary variables 8 Forecasting 9
Structural time-series models 10 Nonlinear time-series models 11 Modeling
time-varying variance 12 Longitudinal data models 13 Spatial models 14
Discrete dependent variables 15 Fractional integration A Using Stata