Econometrics Course Overview:

Program Outcome:

The Econometrics course equips interns with advanced skills in using statistical methods and mathematical models to analyze and quantify economic data. Participants will learn to estimate relationships between economic variables, examine cause-and-effect connections, and make predictions using econometric models within real-time scenarios. By the end of the program, interns will have mastered diagnostic testing, model estimation, and the application of econometric techniques to real-world economic data.


Learning Objectives:

Upon completing the program, interns will be able to:

  • Perform diagnostic tests and calculate relevant statistics.
  • Manage probability models and understand their implications.
  • Estimate models for time series data and analyze temporal relationships.
  • Establish connections between economic theory and empirical analysis.
  • Handle and analyze data for linear models estimation.
  • Derive Ordinary Least Squares (OLS) parameters and interpret results.


Target Group:

This course is designed for interns aspiring to become skilled econometricians capable of applying advanced statistical techniques to economic data analysis. It is suitable for those seeking proficiency in model estimation, hypothesis testing, and economic relationship quantification.


What They Will Learn:

Participants will learn to:

  • Distinguish between econometrics, economic models, and econometric models.
  • Analyze different types of economic data: cross-sectional, time series, pooled cross-sections, and panel data.
  • Understand the nuances of causation versus correlation in econometrics.
  • Interpret and apply simple and multiple regression models.
  • Perform statistical inference in regression analysis and hypothesis testing.
  • Grasp concepts of OLS asymptotics and variable transformations.


Certifications

  • Training course certificate



Course curriculum

  • 1

    Intro to Stata, Intro to R

    • Introduction to R

  • 2

    Econometrics and Economic Data

    • Econometrics and Economic

    • Econometrics and Economic Data In Stata

    • Econometrics And Economic Data

  • 3

    Simple Regression Model

    • Simple Regression Model

    • Simple Regression Model in Stata

    • Simple Regression Model in R

  • 4

    Multiple Regression Model

    • Multiple Regression Model

    • Multiple Regression Model in Stata

    • Multiple Regression Model in R

  • 5

    Regression Inference

    • Regression Inference

    • Regression Inference in Satat

    • Regression Inference in R

  • 6

    OLS Asymptotics

    • OLS Asymptotics

    • OLS Asymptotics in Stata

    • OLS Asymptotics in R

  • 7

    Regression Variable Transformations

    • Regression Variable Transformations

    • Regression Variable Transformations in Stata

    • Regression Variable Transformations in R

  • 8

    Regression with indicator Variables

    • Regression With Indicator Variables

    • Regression With Indicator Variables in Stata

    • Regression With Indicator Variables in R

  • 9

    Heteroscedasticity

    • Heteroscedasticity

    • Heteroscedasticity in Stata

    • Heteroscedasticity in R

  • 10

    Regression Specification

    • Regression Specification

    • Regression Specification in Stata

    • Regression Specification in R

  • 11

    Time Series Models

    • Time Series Models

  • 12

    Simple Panel Data Models

    • Simple Panel Data Models

    • Simple Panel Data Models in Stata

    • Simple Panel Data Models in R

  • 13

    Panel Data Models

    • Panel Data Models

    • Panel Data Models in Stata

    • Simple Panel Data Models in R

  • 14

    Instrumental Variables

    • Instrumental Variables

    • Instrumental Variables in Stata

    • Instrumental Variables in R

  • 15

    Simultaneous Equations

    • Simultaneous Equations

    • Simultaneous Equations in Stata

    • Simultaneous Equations in R

  • 16

    Pro-bit and Logit Models

    • Probit and Logit Models

    • Probit and Logit Models in Stata

    • Probit and Logit Models in R