Empirical analysis with
ECONOMETRICS
Econometrics is a valuable tool for policymakers, businesses, and researchers to understand the complexities of economic data. This module simplifies econometric modeling using MS Excel, SPSS, STATA and Python.
About this module
This module explores the application of econometrics using statistical applications MS Excel, SPSS, STATA and Python. It teaches how to develop statistical models to test economic theories, estimate the impact of economic policies, and make forecasts. You will get familiarised with collecting microeconomic/ macroeconomic/ financial data, selecting appropriate statistical models, estimating the parameters of the models, and testing hypotheses.
What you’ll need
- SPSS Software package
- MS Excel
- STATA software
- Python
- 90 hours
Skills you will gain
Time series regression ARIMA Panel data regression OLS regression Assumption testing Hypothesis testing Data mining Data cleaning Correlation Logit & probit regression Linear and nonlinear regression Multiple regression GLM Multivariate regression VECM Data visualisationOUTCOME
Basics of statistics
Strengthen your understanding of quantitative data analysis.
Statistical modeling
Build regression models to test data efficiently.
Trend forecasting
Predict patterns in future economic conditions.
Policymaking
The empirical approach to making informed economic decisions.
Data testing with SPSS
ANOVA and MANOVA
- Interpreting MANOVA test with more than one dependent variable
- T-test using SPSS
- Two independent samples t-test
- How to test one way ANOVA in SPSS?
- Difference between one way and two way ANOVA
- How to apply the two way ANOVA test in SPSS?
- How to perform T-Test statistics in SPSS?
- How and when to use Paired sample T-test?
Regression with SPSS
- Linear regression analysis using SPSS
- Multivariate analysis with more than on one dependent variable
- Applying regression on secondary data using SPSS
- How to work with a moderating variable in the regression test with SPSS?
- How to work with a mediating variable in a regression analysis?
- How to interpret the results of the linear regression test in SPSS?
Getting started with STATA
Assumption tests in STATA
Time series analysis with STATA
- How to build the univariate ARIMA model for time series in STATA?
- ARIMA modeling for time series analysis in STATA
- How to predict and forecast using ARIMA in STATA?
- How to perform Johansen cointegration test in VAR with three variables?
- How to perform Granger causality test in STATA?
- VECM in STATA for two cointegrating equations
- How to test and diagnose VECM in STATA?
- How to identify ARCH effect for time series analysis in STATA?
Introduction to Python
Live tuition sessions
Our live tuition sessions are curated for statistical analysis problems requiring you to delve deeper. They include discussions on issues you feel stuck at and can’t find the answer to.
Focussed sessions
- Virtual teaching using live demonstration.
- Illustration for different levels of complexity of datasets.
- Easy to follow instructions.
- Tutoring is focused on understanding concepts rather than rote learning.
- We have customized session agendas keeping with different industry requirements.
Check out our upcoming tuition events in the calendar. Click on the event to view its agenda and book your session.