Complete and incomplete econometric models

• Main Author: Geweke, John
• Format: eBook Book
• Language: English
• Published: Princeton Princeton University Press 2010; Princeton Univ. Press
• Edition: 1
• Series: The Econometric and Tinbergen Institutes Lectures
• Subjects: Accuracy and precision; Ancillary statistic; Approximation; Autocorrelation; Autoregressive conditional heteroskedasticity; Autoregressive model; Bayes factor; Bayes-Statistik; Bayesian; Bayesian econometrics; Bayesian inference; Bayesian probability; Bayesian statistics; Behavioral economics; Business; BUSINESS & ECONOMICS; BUSINESS & ECONOMICS / Econometrics; BUSINESS & ECONOMICS / Forecasting; BUSINESS & ECONOMICS / Finance / General; Central limit theorem; Closed-form expression; Combination; Complexity; Conjecture; Copula (probability theory); Decision problem; Decision-making; Dynamic stochastic general equilibrium; Econometric model; Econometric models; Econometric Theory; Econometrics; Economics; Empirical distribution function; Estimation; Excess Kurtosis; Existential quantification; Finance; General equilibrium theory; Generalized method of moments; Importance sampling; Independent and identically distributed random variables; Inference; Joint probability distribution; Kurtosis; Latent variable; Likelihood function; Likelihood-ratio test; Linear prediction; Loss function; Makroökonometrie; Marginal distribution; Marginal likelihood; Markov chain; Mathematical methods; Mean squared error; Modellierung; Monte Carlo algorithm; Null hypothesis; Observable; P-value; Parameter; Parametric model; Posterior predictive distribution; Posterior probability; Prediction; Predictive analytics; Preference (economics); Prior probability; Probability; Quantity; Random variable; Risk aversion; Scoring rule; Simulation; Skewness; Standard deviation; Standard error; Statistic; Statistical hypothesis testing; Stochastic volatility; Theorie; Time series; Uncertainty; Utility; Variance; Ökonometrisches Modell; Decision-making; Kurtosis; Standard error; Autoregressive model; Predictive analytics; Bayesian econometrics; Complexity; Loss function; Utility; Scoring rule; Combination; Accuracy and precision; Random variable; Likelihood function; Posterior predictive distribution; Approximation; Decision problem; Dynamic stochastic general equilibrium; Estimation; Bayesian; Prediction; Conjecture; Bayesian probability; Inference; Generalized method of moments; Existential quantification; Joint probability distribution; Uncertainty; Independent and identically distributed random variables; Monte Carlo algorithm; Parametric model; Variance; Copula (probability theory); Latent variable; Markov chain; Autoregressive conditional heteroskedasticity; Null hypothesis; Linear prediction; Statistic; Bayesian statistics; Econometric Theory; Skewness; Marginal distribution; Ancillary statistic; Stochastic volatility; Standard deviation; Likelihood-ratio test; Bayesian inference; Closed-form expression; P-value; Importance sampling; Preference (economics); General equilibrium theory; Econometric model; Probability; Quantity; Empirical distribution function; Bayes factor; Prior probability; Behavioral economics; Observable; Marginal likelihood; Risk aversion; Excess Kurtosis; Central limit theorem; Posterior probability; Parameter; Statistical hypothesis testing; Autocorrelation; Mean squared error
• ISBN: 0691140022; 9780691140025; 1400835240; 9781400835249
• DOI: 10.1515/9781400835249

Econometric models are widely used in the creation and evaluation of economic policy in the public and private sectors. But these models are useful only if they adequately account for the phenomena in question, and they can be quite misleading if they do not. In response, econometricians have developed tests and other checks for model adequacy. All of these methods, however, take as given the specification of the model to be tested. In this book, John Geweke addresses the critical earlier stage of model development, the point at which potential models are inherently incomplete.