- 82 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
About this book
Researchers have often been troubled with relevant data available from both temporal observations at regular intervals (time series) and from observations at single points of time (cross section). Pooled Times Series Analysis combines time series and cross- sectional data to provide the researcher with an efficient method of analysis and improved estimates of the population being studied.
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Yes, you can access Pooled Time Series Analysis by Lois W. Sayrs in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Contents
- Series Editor's Introduction
- Chapter 1 - Introduction
- Chapter 2 - Theoretical Derivation of the Pooled Time Series Model
- Pooling in Application
- The Pooled Linear Regression Model
- Four Models of Pooling
- Preliminary Diagnostics and Residual Analysis
- Chapter 3 - The Constant Coefficients Model
- Estimating the Constant Coefficients Model
- Correcting for Autoregression
- Heteroscedasticity
- Limitations of the Constant Coefficient Model
- Chapter 4 - The LSDV Model
- Heteroscedasticity and Unit Effects
- Estimating the LSDV Model
- Chapter 5 - The Random Coefficient Model
- Estimating the Random Coefficient Model: GLS
- An ARMA Variation of the GLS Model
- A Seemingly Unrelated Regression Version of the GLS Model
- The Swamy Random Coefficient Model
- The Hsaio Random Coefficient Model
- The Switching Model
- The ARCH Model
- Conclusions on the Random Coefficient Model
- Chapter 6 - The Structural Equation Model
- Two-Stage Estimation
- Maximum Likelihood Estimation
- LOGIT and PROBIT Specifications
- Conclusions on Maximum Likelihood
- Chapter 7 - Robustness: How Good Are These Estimates?
- Robust Estimators
- Heteroscedasticity and Robustness
- Chapter 8 - Conclusions on Pooled Time Series
- Notes
- References
- About the Author