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This course provides an introduction to statistical analysis of economic data, also known as “Econometrics.” It gives you a good understanding of the properties of econometric models and techniques which consists of a blend of economic theory, mathematical modelling, statistical analysis, and computational methods.

Course Objectives

The objective of this course is to provide you with an introduction to basic econometric concepts and data analysis techniques, such as descriptive statistics, correlation and regression, probability, chance variability, and sampling. You will also have a sound understanding of hypothesis testing, the basic regression theory and techniques used in empirical work which include simple and multiple regression models, dummy variables etc. You would be able to examine the role of econometrics in analyzing issues of social concern and the limitations of econometrics and their applications on society.

You will be trained on how to explore a dataset, write codes to analyze relationships and to test hypotheses about economic phenomenon to prepare you for a job as an economist where data analysis is required.


This course requires use of Stata® — an econometrics package very popular among economists. Working with data and implementing econometric software (i.e., Stata) is integrated into every aspect of the course.

The software will be installed for you at the beginning of the class. You will also be given datasets in problem sets and be asked to perform certain econometric routines.

Course Learning Outcomes
Successful completion of the course enables you to understand how econometric methods are used to estimate causal relationships from observational data.

Course Outline

Module 1: Exploring STATA Interface

  • Tour of the Stata interface
  • Preview: Example datasets included with Stata
  • PDF documentation in Stata
  • Quick help in Stata®
  • Download and install user-written commands in Stata®

Module 2: Importing of data

  • Copy/paste data from Excel® into Stata®
  • Import Excel® data into Stata®
  • Import CSV data into Stata®

Module 3: Graph

  • Bar graphs
  • Box plots
  • Basic scatterplots
  • Histograms
  • Pie charts

Module 4: Data Management

  • Creating a new variables
  • Grouping variables
  • Creating label variables
  • Label the values of categorical variables
  • Changing the display format of a variable
  • How to round a continuous variable
  • Converting a string variable to a numeric variable
  • Adding notes to a variable
  • Identifying and replace unusual data values
  • Converting categorical string variables to labeled numeric variables
  • Creating a new variable that is calculated from other variables
  • Creating a categorical variable from a continuous variable
  • Identifying and remove duplicate observations
  • Optimizing the storage of variables
  • Reshape data from long format to wide format
  • Reshape data from wide format to long format
  • Appending files into a single dataset
  • Merging files into a single dataset

Module 5: Understand Measurement of Variable and Hypothesis Testing

  • Measurement of variable
  • Probabilities & Hypothesis Testing

Module 6: Comparing Means and Correlation

  • One -Sample T Test
  • T-test for Two Paired Samples
  • T-test for Two Independent samples
  • Analysis of Variance (ANOVA)
  • Pearson’s correlation coefficient
  • Spearman’s rank correlation coefficient
  • Partial correlation coefficient

Module 7: Regression

  • Simple linear regression
  • Multiple Regression
  • Logistic regression: Binary predictors
  • Logistic regression: Continuous predictors
  • Logistic regression in Stata®, part 3: Factor variables

Module 8: Time Series

  • Time series: Formatting and managing dates
  • Time series: Line graphs and tin()
  • Time series: Time-series operators
  • Time series: Correlograms and partial correlograms
  • Time series: Introduction to ARMA/ARIMA models
  • Time series: Moving-average smoothers

Module 9:   Panel data models

  • Fixed and random effects models

Module 10: Export Results and data