ADMECM: Econometrics

Module code: ADMECM

Module provider: School of Agriculture, Policy and Development

Credits: 20

Level: Postgraduate Masters

When you'll be taught: Semester 2

Module convenor: Professor Kelvin Balcombe, email: k.g.balcombe@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded: IN TAKING THIS MODULE YOU CANNOT TAKE ADMREM (Compulsory)

Placement information: NA

Academic year: 2024/5

Available to visiting students: Yes

Talis reading list: No

Last updated: 20 May 2024

Overview

Module aims and purpose

This module provides an introduction to different econometric models as applied to different types of data. At the end of this module students should be able to 

• translate different types of data into appropriate econometric models to make forecasts and to support decision-making 
• specify models such that they can be used to answer research questions and to be able to make model comparisons 
• conduct hypothesis testing and interpret results critically 
• to understand the assumptions behind linear models 
• to understand diagnostic tests and appropriate models to overcome violations of classical assumptions 
• handle data sets and use the software to carry out econometric analysis of different types of data using different types of models 

Module learning outcomes

By the end of the module, it is expected that students will be able to: 

1. Understand how to specify and estimate various econometric models applied to different types of data (cross-section, time series) 
2. Interpret and critically evaluate results obtained from a variety econometric models applied to different types of data and to be able to communicate these results to others. 
3. Be able to conduct diagnostic tests and implement appropriate models to overcome violations of classical assumptions. 
4. Combine data handling skills and econometric software skills to undertake applied econometric analysis and evaluate and interpret results in Gretl 

Module content

1. Introduction and Overview to Econometrics and Statistics with Illustrations +Coverage of Assessment 
2. Sample Statistics, Types of Data, Probability 
3. Expected Value, Models, Data, Correlation and Causation 
4. Hypothesis Testing:  Concepts 
5. Hypothesis Tests about Means and Proportions 
6. Ordinary Least Squares and Bivariate Regression 
7. Multiple Regression 
8. The Logit and Probit Model 
9. Why things go “wrong” 
10. Designing a Research Problem 
11. Look Back and Ahead, Coursework for part II 
12. Testing and Imposing General Linear Restrictions 
13. Why OLS for Regression? Assumptions and Properties of OLS 
14. Heteroscedasticity: Nature, Testing Consequences and Mitigation 
15. Serial correlation: Nature, Testing Consequences and Mitigation 
16. Endogeneity: Nature, Testing Consequences and Mitigation 
17. Time Series Regression, Autoregressive Models and Seasonality 
18. Model Specification 
19. Lecture: Tobit and Ordered Probit Regression 
20. Course Review and Guide to Model Building 

Structure

Teaching and learning methods

Online lectures will be available covering all of the core materials. The key concepts in the online lectures will be presented in class. All lectures will involve practical sessions where examples of statistics and econometric models will be estimated within class by students (using the software Gretl) and the results explained and discussed. 

Study hours

At least 44 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 50% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Reassessment

Additional costs