Flexible learning
Online postgraduate courses
Software for Econometrics and Big Data
Please note to take this course you must first have completed Foundations of Econometrics
The aim of this course is to provide students with programming skills that can be used to perform data management operations and several types of statistical and econometric analysis in an efficient and reproducible way. Students will be taught the fundamentals of programming in Stata. The module will prepare students for PhD research or work as an econometrician consultant in public and private organisations.
This module can be taken as part of a PG Certificate, PG Diploma or Full Masters Program.
- 10 Credits
- 100 hours of study
- 15 contact hours
- 85 hours for private study
Faculty
Structure
Structure
Software for Econometrics and Big Data is an elective 10 credit course and therefore students are expected to input approximately 100 hours of study into the course.
The total number of contact hours is 15 hours. This leaves 85 hours for private study.
Lectures
This module consists of 2- hour lectures per day for 5 days, plus a 1 - hour tutorial per day.
There will be optional clinics on the last day of the course.
The dates of each lecture are confirmed closer to the start of each term. If you have any questions about dates, please contact edu@timberlake.co.uk.
Stata
Module Programme
Programming: Some Fundamental Concepts
- Do and ado files in Stata
- Data types: Working with dates and time, time series operators, factor variables
- Debugging – the capture command
- Protecting your data with preserve and restore
Guidelines for writing programs in Stata
- Basic guidelines for writing do-files
- Enhancing speed and efficiency
- How to seek help for Stata programming
Programming Stata Do-Files I
- Transformation of string and numeric variables
- Recoding discrete and continuous variables
- Recoding missing variables
- Generate and egen functions
- Local and global macros
- Extended macro functions and list functions
Programming Stata Do-Files II
- Scalars and matrices
- Temporary variables and tempnames
- Looping commands: forvalues and foreach
- By, statsby, rolling and other prefix commands
- Transforming data with reshape
- Combining datasets with append and merge
Programming Concepts and Tools in Action I
- Tabulating and computing statistics across a set of variables and groups
- Computing durations and aggregating transactions data
- Summarising group characteristics over observations
Programming Concepts and Tools in Action II
- Adding aggregate characteristics to micro observations
- Reusing results: return and ereturn commands
- Accessing estimation results and margins
Automation - Do-File Programming I
- Storing results in matrices
- Stata’s post and postfile commands
Automation - Do-File Programming II
- Automating estimation output – the user-written commands estout and tabout,saveresults
- Automating graphical output
ADO-File Programming I
- Structure of an ado-file● Syntax and return statements
- Using program options
- Including a subset of observations
- Generalizing commands to handle multiple variables
- Rendering commands byable
ADO-File Programming II
- Writing an e-class program
- Programs for egen, ml, nl
- Programs for gmm
- Guidelines for ado-file programming style
Fundamentals of Mata programming
- Mata Fundamentals
- A simple Mata function
- Components of a Mata function
- Calling Mata functions
- Mata’s st_interface functions
Prerequisites
English Language Requirements
Both Programmes are open to applicants anywhere in the world. We may ask applicants to provide a recognised English language qualification, dependent upon their nationality and where they have studied/worked previously.
The requirement is an IELTS (Academic) Test with an overall score of at least 6.5, and a minimum of 6.0 in each element of the test. We will also consider other English language qualifications. If their score is below our requirements, they may be eligible for one of Lancaster University's pre-sessional English language programmes.
Academic Requirements
Applicants to the Postgraduate Certificate of Achievement, Postgraduate Certificate, Postgraduate Diploma or full MSc in either programme require either an upper second-class degree in economics, econometrics or related subjects.
Learning Outcomes
- Understand the principles of Stata programming
- Write Stata do-files for automating the workflow
- Write ADO-files to extend Stata by creating new commands
- Understand the basics of Mata Programming Language
- Use automatic model selection to build econometric models
- Use saturation estimation
- Present, interpret and analyse the results of automatic model selection
- Utilise effectively PcGive and the R gets package packages
Frequently Asked Questions
All sessions are conducted live and online at a scheduled time, but are also recorded. Students may attend live and watch the recordings back to recap the material or watch the recordings only if unable to attend live. We always advise students to attend live where possible as this will allow them the best opportunity to engage with the content and ask the lecturer's questions.
All modules are examined through online coursework submissions, you will have the support of your module lecturer/tutor in this poccess.
No, all necessary software is provided to students.
All courses are recorded and available on the LUMS internet platform throughout the current academic year. They can therefore be viewed 24 hours a day.
Timberlake Consultants and Lancaster University Management School (LUMS) Economics department have a longstanding partnership; combining 40+ years of industry expertise with over 50 years of academic excellence. We are delighted to build on this with our micro-credential postgraduate courses.
Flexible learning
Online postgraduate courses
Specialist courses
Best-in-field experts
Tailored learning
Career-oriented education
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Flexible learning
Online postgraduate courses
Specialist courses
Best-in-field experts
Tailored learning
Career-oriented education