Title

## Econometrics forms an essential part of an economist’s intellectual training, as the ability to make inferences from data is an increasingly important part of economics.

This course will be taught at the intermediate level and assumes you have undertaken a basic undergraduate statistics course beforehand. It will cover the main topics that lie at the core of econometric methods, techniques and applications.

Students will be equipped with experience in the analysis and use of empirical data, the nature of uncertainty and methods of dealing with it. By considering the assumptions underlying the models, we will analyse the implications of these assumptions being violated.

### Lecturers and Teaching Assistants

### Course Syllabus

- Eequivalent of a 15 CAT module from an Undergraduate Degree.
- European system: 7.5 ECTS
- US system: approximately 3 credits.

### Course Overview

The ability to make inferences from data is an increasingly important part of economics. This course will be taught at the intermediate level and assumes you have undertaken a basic undergraduate statistics course beforehand. It will cover the main topics that lie at the core of econometric methods, techniques and applications.

Students will be equipped with experience in the analysis and use of empirical data, the nature of uncertainty and methods of dealing with it. By considering the assumptions underlying the models, we will analyse the implications of these assumptions being violated.

We will cover a variety of topics within this course and will make extensive use of econometric software packages as tools of quantitative and statistical analysis. Students will learn how to analyse empirical data, draw conclusions from it and discuss the limitations of the analysis. The following is a list of the topics that will comprise the course:

- Univariate and Bivariate Distributions
- Two variable linear regression analysis
- Multiple variable regression model
- Dummy variables in multiple variable regression model
- Misspecification
- Instrumental variables
- Maximum Likelihood and Discrete Choice Models
- Panel Data models
- Time Series - Basic Principles and Univariate models
- Time Series - Multivariate models and Cointegration

### Course Aims

This course aims to provide students with a range of important skills, which are of both academic and vocational value, as they form an essential part of the intellectual training for an economist. These skills will also be useful for a variety of other careers, as the analysis of data is central to many professions. In particular, the course aims to give students an awareness of the empirical approach to economics and the value that this to decision-making for consumers, firms and governments.

The course will be taught by individuals, who have extensive knowledge and experience of the application of quantitative and statistical analysis in a range of areas. By making use of econometric software packages, the course therefore aims to provide students with the tools they need to analyse data, correctly interpret results and understand the limitations of the data they have and the tests that are performed.

### Learning Outcomes

By the end of this module, students should be able to:

- Critically appraise work in the area of applied economics.
- Analyse and make use of empirical data in economics to solve a variety of problems.
- Make use of econometric software packages as tools of quantitative and statistical analysis to compute empirical results.
- Understand the assumptions behind the models that are used and the limitations of the results obtained.
- Understand the nature of uncertainty and the methods that can be used to deal with it.
- Develop a good intuitive and theoretical grasp of the dangers, pitfalls and problems encountered in undertaking applied modelling.

### Course Structure

For this course, there will be 4 hours of teaching per day, comprised of lectures and small group teaching. The structure will be:

- 3 hours of lectures.
- A 1 hour seminar in small groups.

Students will also be given time each day for independent study. Towards the end of the third week, students will also be provided with time for revision.

### Course Assessment

The module will be assessed via a 2-hour examination. It is not compulsory, but for anyone wishing to obtain a certificate of their study at Warwick Economics Summer School, they must sit this examination.

### Course Reading List

Below are some illustrative readings for this course.

- J. M. Wooldridge;
*“Introductory Econometrics:**A Modern Approach”*; 5th edition (2013), South-Western. - J. H. Stock and M. W. Watson;
*“Introduction to Econometrics”*; 3^{rd}edition (2014); Pearson. - D. Gujarati;
*“Econometrics by Example”*; (2011); Palgrave McMillan.

#### Michele Aquaro

### Topic 1: Static Linear Panel Data Models

- Slides(Non-examinable: slides 40, 50, 59--63, and 72).
- Data & Do-Files
- Tutorial

### Topic 2: Instrumental Variables Estimation

- Slides(Non-examinable: slides 25--31).
- Data & Do-Files
- Tutorial

### Topic 3: Binary Response Models

- Slides(Non-examinable: slides 7,12,29 and 30).
- Data & Do Files
- Tutorial

#### Jeremey Smith & Matteo Gamalerio

### Exercise Sheets

- Exercise Sheet 0
- Exercise Sheet 1
- Exercise Sheet 2
- Exercise Sheet 3
- Exercise Sheet 4
- Exercise Sheet 5

### Exercise Solutions

- Exercise Sheet 0 - Q1-0
- Exercise Sheet 0 - Q1-1
- Exercise Sheet 0 - Q2-0
- Exercise Sheet 0 - Q2-1
- Exercise Sheet 0 - Q3-0
- Exercise Sheet 0 - Q3-1
- Exercise Sheet 0 - Q3-2
- Exercise Sheet 0 - Q4-0
- Exercise Sheet 0 - Q5-0

### Handouts

- Univariate and Bivariate Distributions
- Two variable linear regression analysis
- Multiple variable regression model
- Dummy variables in multiple variable regression model
- Misspecification