Module code: ECOM043

Module Overview

This module introduces students to  microeconometric techniques relevant for the estimation of a range of models including those with either qualitative or limited dependent variables, models for survival analysis,panel data models  programme evaluation and decomposition techniques, and regression discontinuity design. A strong emphasis is placed on the empirical applications of these techniques and their intuition.

Module provider


Module Leader

WITT Robert (Economics)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

Module cap (Maximum number of students): N/A

Overall student workload

Workshop Hours: 2

Independent Learning Hours: 84

Lecture Hours: 22

Laboratory Hours: 9

Captured Content: 33

Module Availability

Semester 2

Prerequisites / Co-requisites


Module content

Indicative content includes:

OLS and Quantile Regression, Maximum Likelihood Principle, LP and Logit, Probit Models, Truncated and Censored Regression Models, Duration Models, Panel Data Models, Programme Evaluation and Decomposition Techniques and Regression Discontinuity Design.

Assessment pattern

Assessment type Unit of assessment Weighting
Online Scheduled Summative Class Test CLASS TEST 25
Examination Online FINAL EXAMINATION 75

Alternative Assessment


Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate the students’ understanding of the statistical concepts associated with the methods studied, and ability to use STATA to solve simple problems can be assessed

Thus, the summative assessment for this module consists of:

  • A multiple-choice test. The multiple choice test allows students to demonstrate the breadth of their understanding of the early topics, and its timing also allows them to receive relatively early feedback on how they have started the module;

  • A final exam. The questions require a mixture of maths, stats, diagrams and written responses.

The long questions are designed to test depth of knowledge on a particular topic and their writing skills. The questions are drawn from (but do not cover) the whole module, and this explains the degree of choice offered on these.

Formative assessment and feedback

Students receive verbal feedback on questions asked during lectures and in the 9 computer-lab sessions plus workshop. (Exercise sheets are circulated in advance and then questions discussed in class using Stata; data sets, do files and full solutions are also provided together with PowerPoint slides).  After the MCQ test, written solutions and feedback are provided.  Feedback on the MCQ consists of individualised written comments and the opportunity for each student to have a short meeting to talk through this.  At the start of the module, the previous year’s test and exam are made available (on SurreyLearn).  There is one revision session before the final exam, plus a continuous Discussion Forum on SurreyLearn and two online one-hour open forums for students to come along and talk openly about the module.


Module aims

  • access and understand an applied economics literature that uses these techniques
  • undertake competent empirical research using such techniques and
  • develop a familiarity with the STATA econometric package in undertaking such empirical analysis. 

Learning outcomes

Attributes Developed
001 Be able to use STATA and interpret STATA output KC
002 To critically evaluate and understand econometric techniques relevant for the estimation of a range of microeconometric models KC
003 To be able to interpret and analyse patterns or trends in data and to think through economic problems analytically PT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

Make the students understand the ideas behind the methods analysed

Allow the students to apply these methods to simple situations

Reading using lecturer's guidance

Preparing exercises for discussion in computer-lab sessions  

Responding to questions in lectures and in computing classes and workshops

The learning and teaching methods include:

  • Lectures that are recorded and disseminated as captured content

  • STATA computer-lab sessions

  • A workshop

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list
Upon accessing the reading list, please search for the module using the module code: ECOM043

Other information

In line with the University's curriculum framework, the School of Economics is committed to developing graduates with strengths in Employability, Digital Capabilities, Global and Cultural Capabilities, Sustainability and Resourcefulness and Resilience. This module is designed to allow students to develop knowledge, skills, and capabilities in the following areas:


Numerous aspects of the labour market are affected by (and can influence) many different types of inequalities across gender, ethnic groups and the poor. By estimating wage, employment and crime equations and discussing their results, module introduces students to examples of these effects.

Resourcefulness and Resilience

The majority of the readings for the module are from text books and journal articles; addition, students have the opportunity to study and analyse data in their weekly computer lab sessions. Studying the former and completing the latter fosters resourcefulness. Resilience can be enhanced by reacting to feedback from the exercise sheets and through a degree of discussion during the lectures, tutorials and workshops.


The module promotes the use of econometric skills and interpretation of data, as well as writing skills. These are valuable in the workplace.

Digital Capabilities

By the end of the module, students are expected to have a high degree of proficiency in Stata and to produce written solutions to a high presentational standard.

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Economics MSc 2 Compulsory A weighted aggregate mark of 50% is required to pass the module
Economics (International Economics) MSc 2 Optional A weighted aggregate mark of 50% is required to pass the module
Economics (Macroeconomics and Financial Markets) MSc 2 Optional A weighted aggregate mark of 50% is required to pass the module
Economics (Policy Evaluation and Data Analysis) MSc 2 Compulsory A weighted aggregate mark of 50% is required to pass the module
Economics and Finance MSc 2 Optional A weighted aggregate mark of 50% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.