v   2 Introduction

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• Time series analysis
• Regression analysis
• Parametric statistics
• Heteroscedasticity
• Granger causality
• Statistic
• Breusch–Godfrey test
• Wald test
• F-test
• Statistics
• Statistical tests
• Econometrics

Producing accurate standard errors is essential for both the scholarly research and official policy uses of the data because they indicate the precision of the estimates and the statistical significance of hypothesis tes

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• Sampling
• Econometrics
• Estimation theory
• Design effect
• Standard error
• Sample size determination
• Variance
• Random sample
• Heteroscedasticity-consistent standard errors
• Statistics
• Statistical inference
• Data analysis

Microeconometrics - summer term 2014 Preliminary Syllabus Dr. Dominik Menno Course description This course introduces the microeconometric methods needed for the analysis of cross-sectional and panel data and teaches the

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• Cross-sectional data
• Panel data
• Mean dependence
• Statistics
• Econometrics
• Heteroscedasticity

Theis Lange Asymptotic Theory in Financial Time Series Models with Conditional Heteroscedasticity Ph.D. Thesis

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Ghostscript wrapper for C:rstumentspsjginal-1.pdf

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• Estimation theory
• Heteroscedasticity-consistent standard errors
• Generalized method of moments
• Linear regression
• Instrumental variable
• Estimator
• Heteroscedasticity
• T-statistic
• Maximum likelihood
• Statistics
• Econometrics
• Regression analysis

Peter C. B. Phillips: Ph.D Students & Thesis Supervision Yale University: 1. *Peter C. Reiss (1982) “Price and Advertising Strategies that Segment Oligopolistic Markets: Marginal Consumers and Their Role in Competition

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• Econometric model
• Peter C. B. Phillips
• Bayesian econometrics
• Heteroscedasticity
• Econometrics
• Statistics
• Economics

THE REDUCED FORM: A SIMPLE APPROACH TO INFERENCE WITH WEAK INSTRUMENTS VICTOR CHERNOZHUKOV AND CHRISTIAN HANSEN† Abstract. In this paper, we consider simple and practical methods for performing heteroskedasticity and a

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• Regression analysis
• Parametric statistics
• Statistical inference
• Instrumental variable
• Linear regression
• Simultaneous equations model
• T-statistic
• Heteroscedasticity
• Autocorrelation
• Statistics
• Econometrics
• Estimation theory

0.1 normal: Normal Regression for Continuous Dependent Variables The Normal regression model is a close variant of the more standard least squares regression model (see Section ??). Both models specify a continuous depe

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• Statistical models
• Actuarial science
• Estimation theory
• Linear regression
• Dummy variable
• Least squares
• Errors and residuals in statistics
• Normal distribution
• Heteroscedasticity
• Statistics
• Regression analysis
• Econometrics

Syllabus APPLIED ECONOMETRICS Bonn Graduate School of Economics WSProf. Dr. Klaus F. Zimmermann

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• Estimation theory
• Single equation methods
• Limited dependent variable
• Linear regression
• Least squares
• Economic model
• Maximum likelihood
• Heteroscedasticity
• Macroeconomic model
• Statistics
• Econometrics
• Regression analysis

Microsoft Word - Sy202Spr14.doc

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• Statistical inference
• Regression analysis
• Instrumental variable
• Linear regression
• Heteroscedasticity
• Estimator
• Interval estimation
• Statistics
• Econometrics
• Estimation theory