The aim of this course is to provide participants with an in-depth understanding of how a good MSc dissertation should look, and how to easily use Stata to obtain any required econometrics.
Participants will receive a free temporary Stata license, as well as a recording of the training session, that will be live for 30 days.
The course is meant for any MSc student writing their MSc dissertation, who needs guidance on the best structure, and most suitable econometric methods to apply. No previous knowledge of stata is required.
- How to structure your dissertation
- Abstract and introduction in depth discussion and examples
- How to get a smart literature review –discussion of successful examples
- Build, estimate and forecast from linear regression, time series and panel models using STATA
- Understand and critically present and discus your results
Do you have course specific questions? Email our team [email protected]. If you have course content specific questions, you are welcome to reach out to the course tutor here: [email protected].
Day 1
Session 1:
- How to structure your dissertation, looking into your data visualization, testing and how to present the data set.
- What makes a good abstract?
- How to run preliminary tests in Stata and how to interpret them.
- Writing the introduction : key points you must cover
Session 2:
- What makes a good literature review? With examples.
- Fitting econometric linear regression models in Stata: how to estimate the models, run post estimation diagnostic tests, and interpret your results.
Day 2
Session 1:
- Time series models in Stata: estimation, post estimation, diagnostic tests and interpretation.
- Extending your model to include variance GARCH effect: GARCH, EGARCH, TARCH, APARCH: estimation and post diagnostic tests in Stata.
- Do we really need a GARCH? The ARCH test. The ARMA-GARCH framework.
Session 2:
- Panel data models in Stata: estimation, post estimation diagnostic tests and interpretation, fixed effect or random effect?
- The Hausmann test and how to justify your modelling choice. How to write good conclusions and convince your reader of your findings
Q&A session
Basic knowledge of linear regression is helpful but not necessary. We do not assume any knowledge of STATA.
Terms & Conditions
- Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
- Additional discounts are available for multiple registrations.
- Delegates are provided with temporary licences for the principal software package(s) used in the delivery of the course. It is essential that these temporary training licenses are installed on your computers prior to the start of the course.
- Payment of course fees required prior to the course start date.
- Registration closes 1 calendar day prior to the start of the course.
- 100% fee returned for cancellations made more than 28-calendar days prior to start of the course.
- 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
- No fee returned for cancellations made less than 14-calendar days prior to the start of the course.
The number of attendees is restricted. Please register early to guarantee your place.
Do you have course specific questions? Email our team [email protected]. If you have course content specific questions, you are welcome to reach out to the course tutor here: [email protected].