Econometric Modeling (eBook)

A Likelihood Approach

David F. Hendry, Bent Nielsen (Autoren)

eBook Download: PDF

2012
384 Seiten
Princeton University Press (Verlag)
978-1-4008-4565-1 (ISBN)

Infos

Econometric Modeling provides a new and stimulating introduction to econometrics, focusing on modeling. The key issue confronting empirical economics is to establish sustainable relationships that are both supported by data and interpretable from economic theory. The unified likelihood-based approach of this book gives students the required statistical foundations of estimation and inference, and leads to a thorough understanding of econometric techniques. David Hendry and Bent Nielsen introduce modeling for a range of situations, including binary data sets, multiple regression, and cointegrated systems. In each setting, a statistical model is constructed to explain the observed variation in the data, with estimation and inference based on the likelihood function. Substantive issues are always addressed, showing how both statistical and economic assumptions can be tested and empirical results interpreted. Important empirical problems such as structural breaks, forecasting, and model selection are covered, and Monte Carlo simulation is explained and applied. Econometric Modeling is a self-contained introduction for advanced undergraduate or graduate students. Throughout, data illustrate and motivate the approach, and are available for computer-based teaching. Technical issues from probability theory and statistical theory are introduced only as needed. Nevertheless, the approach is rigorous, emphasizing the coherent formulation, estimation, and evaluation of econometric models relevant for empirical research.

Autor

David F. Hendry is Professor of Economics at the University of Oxford and a Fellow of Nuffield College. Bent Nielsen is Reader in Econometrics at the University of Oxford and a Fellow of Nuffield College

Produkt-Details

• Erscheint lt. Verlag: 21.6.2012
• Zusatzinfo: 50 line illus.
• Verlagsort: Princeton
• Sprache: englisch
• Themenwelt: Wirtschaft ► Volkswirtschaftslehre ► Ökonometrie
• Schlagworte: Accuracy and precision • Asymptotic Distribution • autocorrelation • Autoregressive conditional heteroskedasticity • Autoregressive model • Bayesian • Bayesian Statistics • Bernoulli distribution • Bias of an estimator • Calculation • central limit theorem • Chow Test • Cointegration • conditional expectation • Conditional probability distribution • Confidence interval • Confidence region • Correlation and dependence • Correlogram • Count Data • Cross-Sectional Data • Cross-sectional regression • Distribution Function • Dummy variable (statistics) • Econometric model • Empirical distribution function • Equation • Error Term • estimation • Estimator • Exogeny • Exploratory data analysis • Fair coin • F-distribution • Forecast Error • Forecasting • F-Test • Granger Causality • Heteroscedasticity • inference • instrumental variable • Joint probability distribution • law of large numbers • Least absolute deviations • Least Squares • Likelihood Function • Likelihood-ratio test • linear regression • Logistic Regression • Lucas critique • Marginal distribution • Markov process • Mathematical Optimization • maximum likelihood estimation • Model Selection • Monte Carlo Method • Moving-average model • Multiple Correlation • Multivariate normal distribution • Nonparametric regression • Normal distribution • Normality test • One-Tailed Test • opportunity cost • orthogonalization • Parameter • Partial correlation • poisson regression • Probability • Probit Model • p-value • Quantile • Quantity • Quasi-Likelihood • Random Variable • Regression Analysis • Residual sum of squares • round-off error • Seemingly unrelated regressions • Selection bias • Simple Linear Regression • Skewness • standard deviation • standard error • stationary process • Statistic • Student's t-test • Sufficient statistic • summary statistics • test statistic • Time Series • t-statistic • Type I and type II errors • unit root • Unit root test • Utility • Variable (mathematics) • Variance • vector autoregression • White test
• ISBN-10: 1-4008-4565-3 / 1400845653
• ISBN-13: 978-1-4008-4565-1 / 9781400845651