Econometrics Topics Overview of the book The nature

Econometrics, Topics: Overview of the book The nature of regression anaysis • The concept of linear regression • Correlation vs Regression • Statistical vs Deterministic relationships • Terminology and notation 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 1

Econometrics, Topics: Overview of the book Two-variable regression analysis: some basic ideas • Population regression function (PRF) • Sample regression function (SRF) • Linearity in variables • Linearity in parameters 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 2

Econometrics, Topics: Overview of the book Two-variable regression model: The problem of estimation • OLS-estimation. • Point estimates of parameters. • Coefficient of determination, R 2. 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 3

Econometrics, Topics: Overview of the book The normality assumption (CNLRM) • Normality assumption of the residuals. • Properties of OLS-estimators under normality assumption. • Distributions related to the normal: i. e. t, chi-squared, F. • Maximun Likelihood (ML) estimation. 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 4

Econometrics, Topics: Overview of the book Two variable regression: Interval estimation and hypothesis testing • Interval estimation of parameters (confidence intervals). • Hypothesis testing of parameters (t-test, F-test). • Mean predicion. • Individual predicion. • Normality tests. 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 5

Econometrics, Topics: Overview of the book Extensions of the two-variable linear regression model • Regression through the origin • Functional forms • Elasticity • Log-log models • Log-lin models • Lin-log models 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 6

Econometrics, Topics: Overview of the book Multiple regression analysis: The problem of estimation • Three variable model estimation (two regressors) • Partial regression coefficients • R 2 and adjusted R 2 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 7

Econometrics, Topics: Overview of the book Multiple regression analysis: The problem of inference • t-test in multiple regression framework • F-test, (of model, of subset of parameters) • Restricted least squares • Test for structural stability, (structural breaks) • Testing linear restrictions (F-test) 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 8

Econometrics, Topics: Overview of the book Dummy variable regression models • The nature of dummy variables • Regression using dummy variables • Interaction-effects using dummy variables • Seasonal analysis • Piecewise linear regression, (testing for structural breaks) 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 9

Econometrics, Topics: Overview of the book Multicolliniarity • What is multicolliniarity • The consequenses of multicolliniarity • How to detect multicolliniarity • Remedial measures 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 10

Econometrics, Topics: Overview of the book Heteroscedasticity • What is heteroscedasticity? • The consequenses of heteroscedasticity • Estimation in prescens of hetersoscedasticity • GLS, WLS • Detection of heteroscedasticity • Remedial measures 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 11

Econometrics, Topics: Overview of the book Autocorrelation (Time Series Course…) • What is Autocorrelation • The consequenses autocorrelation • Estimation allowing for autocorrelation • Detection of autocorrelation • Remedial measures 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 12

Econometrics, Topics: Overview of the book Econometric modeling • Model selection criteria • Consequences of model mis-specification • Errors of measurement 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 13

Econometrics, Topics: Overview of the book Nonlinear regression models Linear and non-linear models (in both parameters and variables) 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 14

Econometrics, Topics: Overview of the book Qualitative Response Regression models (Special focus in B 4 Applied statistical methods) • Linear probability model • Logit model • Probit model 2020 -09 -10 B 2 - Ch 01 - 012 - Topics chapters overview 15