# Econometric Theory I

Module title Econometric Theory I BEEM139 2023/4 15 Dr Sebastian Kripfganz (Convenor)
 Duration: Term Duration: Weeks 1 2 3 11
 Number students taking module (anticipated) 12

## Module description

Econometrics is the branch of economics devoted to the development and application of statistical methods to the study and clarification of the economic phenomena. This module provides an advanced introduction to econometric theory, understood as a collection of mathematical and statistical concepts and principles which motivates much of the empirical analysis conducted by economists.

## Module aims - intentions of the module

This module aims at providing the students with an introduction to the theory of econometrics covering important topics in econometric estimation and inference. The module will provide students with the necessary knowledge for understanding recent developments in econometrics.

The module will help students carry out future applied econometric analysis by allowing them to understand the underlying econometric theory, which is important in order to make reasonable judgments about the methods to implement.

## Intended Learning Outcomes (ILOs)

### ILO: Module-specific skills

On successfully completing the module you will be able to...

• 1. explain theoretical aspects of important topics in econometrics

### ILO: Discipline-specific skills

On successfully completing the module you will be able to...

• 2. apply important general principles and tools used in econometrics
• 3. demonstrate a specialised knowledge of theoretical aspects of econometrics to enable you to carry out applied research or direct you towards an academic career

### ILO: Personal and key skills

On successfully completing the module you will be able to...

• 4. demonstrate a logical attitude towards the solution of problems
• 5. demonstrate confidence in identifying, tackling and solving research problems

## Syllabus plan

The following non-exclusive list gives an indication about possible topics covered by this module:

1. The linear regression model

-Ordinary least squares estimation

-Unbiasedness and efficiency

2. Model specification and hypothesis testing

-The partitioned regression model

-Omitted variables and irrelevant regressors

-Testing linear restrictions

3. Asymptotic theory

-Modes of convergence

-Consistency and asymptotic normality

4. Instrumental variables

-Endogenous regressors

-Two-stage least squares estimation

-Generalised method of moments

## Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad
32118

## Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled Learning and Teaching22Lectures
Scheduled Learning and Teaching10Tutorials
Independent Study118Independent study

## Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Bi-weekly exercises1-6 questions1-5Oral/written

## Summative assessment (% of credit)

CourseworkWritten examsPractical exams
30700

## Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Problem Set 1152-4 problems1-5Oral/Written
Problem Set 2152-4 problems1-5Oral/Written
Final Exam702 hours1-5Oral/Written
0
0
0

## Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Problem Set 1Problem Set 1 (15%)1-5August
Problem Set 2 Problem Set 2 (15%)1-5August
Final exam Final exam (70%)1-5August

## Indicative learning resources - Basic reading

Davidson, J. (2018). An introduction to econometric theory. Wiley.

Greene, W. H. (2012). Econometric analysis. Pearson.

Hansen, B. (2022). Probability and statistics for Economists. Princeton University Press.

Hansen, B. (2022). Econometrics. Princeton University Press.

Hayashi, F. (2000). Econometrics. Princeton University Press.

Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. MIT Press.

Wooldridge, J. M. (2020). Introductory econometrics: a modern approach. Cengage Learning.

### Key words search

Estimation, inference, regression, asymptotic theory

Credit value 15 7.5 Only available to MRes Economics PhD pathway students None 7 No 04/04/2016 13/02/2023