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Introduction to Econometrics: A Comprehensive Guide

This course, led by Pablo Agnese at FH Düsseldorf, provides an in-depth exploration of econometrics, focusing on regression analysis, binary dependent variables, and time series analysis. Key concepts such as hypothesis testing, estimation, and data types are covered, enabling students to develop quantitative analysis skills. The course includes practical training with Eviews software, supplemented by literature from esteemed authors like Gujarati and Wooldridge. Grading is based on a test (80%) and weekly exercises (20%). Enhance your understanding of econometric methods and their applications.

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Introduction to Econometrics: A Comprehensive Guide

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  1. Introduction to Econometrics pablo.agnese@fh-duesseldorf.de www.pabloagnese.com (23.32 00.43) FH Düsseldorf 2011-2012 Pablo Agnese

  2. Outline • Unit 1: Introduction • Unit 2: Regression analysis • Unit 3: Regression analysis : Further details • Unit 4: Binary dependent variable • Unit 5: Time series

  3. Goals • Basic concepts in quantitative analysis • Some technical stuff  • More technical stuff   • We will learn how to use Eviews   

  4. Literature • Gujarati, D., Basic econometrics, 5th ed. 2008 • Gujarati, D., Essentials of econometrics, 4th ed. 2009 • Gujarati, D., Econometrics by example, 2011 • Stundenmund, A.H., Using econometrics: A practical guide, 5th ed. 2005. • Wooldridge, J., Introduction to econometrics: A modern approach, 4th ed. 2008

  5. Grading Test (80%) Weekly exercises (20%) Monitoring: email exchange and/or tutorials Eviews

  6. Unit 1: Introduction • Unit 2: Regression analysis • Unit 3: Regression analysis : Further details • Unit 4: Binary dependent variable • Unit 5: Time series

  7. 1.Introduction 1.1 What is econometrics? • Calculus • Probability • Statistics • Game theory Scientific method (econometrics): • Hypotheses or theory • Mathematical model • Econometric model • Data • Estimation • Hypothesis testing • Structural analysis, forecasting, simulations

  8. 1.Introduction 1.2 Definitions • Population • Sample • Random variable • Distribution function / relative frequency • Parameter • Estimator 1.3 Data • Cross section • Time series • Panel data

  9. 1.Introduction 1.4 Variables • Quantitative: discrete or continuous • Qualitative: ordinal or cardinal 1.5 Some widely used measures: • Of centralization: mean (expected value), median, mode… • Of position: quartiles, deciles, percentiles… • Dispersion: rank, variance, standard deviation, CV… • Skewness • Kurtosis

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