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## Syllabus

### Updated A.Y. 2022-2023

Introduction to a course

What will we learn on this course

Chapter 1            ECONOMIC QUESTIONS AND DATA

Economic questions we examine

Causal effects and idealized experiments

Data: Sources and types

Chapter 2            REVIEW OF PROBABILITY

Random variables and probability distributions

Expected values, meand and variance

Two random variables

Normal, Chi-squared, t-distribution, F-distribution

XXXXXXX              INTRODUCTION TO GRETL

Chapter 3            REVIEW OF STATISTICS

(skipped)

Chapter 4            LINEAR REGRESSION WITH ONE REGRESSORS

The linear regression model

Estimating the coefficients of the linear regression model

Measures of fit

The least squares assumptions

Sampling distributions of OLS estimators

Chapter 5            REGRESSION WITH A SINGLE REGRESSOR: HYPOTHESIS TESTING AND CONFIDENCE INTERVALS

Testing hypotheses about one of the regression coefficients

Confidence intervals for a regression coefficients

Regression when X is a binary variable

Heteroscedasticity and homoskedasticity

The theoretical foundations of ordinary least squares

Using the t-statistic in the regression when the sample size is small

Chapter 6            LINEAR REGRESSION WITH MULTIPLE REGRESSORS

Omitted variable bias

The multiple regression model

The OLS estimator in multiple regression

Measures of fit in multiple regression

The least squares assumptions in multiple regression

The distribution of the OLS estimators in multiple regression

Multicollinearity

Chapter 7            HYPOTHESIS TESTS AND CONFIDENCE INTERVALS IN MULTIPLE REGRESSION

Hypothesis tests and confidence intervals for a single coefficient

Tests of joint hypotheses

Testing single restrictions involving multiple coefficients

Confidence sets for multiple coefficients

Analysis of the test score data set

PROJECT              Discussion about topics and organization of groups

Chapter 8            NONLINEAR REGRESSION FUNCTIONS

A general strategy for modeling nonlinear regression functions

Nonlinear functions of a single independent variable

Interactions between independent variables

Nonlinear effects on test scores of the student-teacher ratio

EXERCISES

Chapter 9            ASSESSING STUDIES  BASED ON MULTIPLE REGRESSION

Internal and external validity

Threats to internal validity of multiple regression analysis

Internal and external valitidy when the regression is used for forecasting

Example: Test scores and class size

Chapter 14          Time Series Analysis - ARIMA models

VAR models