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EC203: Applied Econometrics

  • Thomas Martin

    Module Leader
30 CATS - Department of Economics

Principal Aims

This module allows students to develop an understanding of fundamental and intermediate concepts of statistical analysis, such as regression analysis. Students will also develop the capacity to apply statistical techniques to real world problems/data sets using the statistical package STATA.

Principal Learning Outcomes

Subject Knowledge and Understanding Demonstrate knowledge and understanding of:(i) Economic Principles: Knowledge and understanding of core concepts and methods in macroeconomics.(ii) An awareness of the empirical approach to economics and social science.(iii) Reviewing and extending fundamental statistical concepts, including principal component analysis.(iv) Regression analysis, its extensions and applications. Understanding of random variables, associated distributions and moments; statistical estimation, estimator sampling distributions and population inference; causality and selection bias; experimental versus non-experimental data; simple linear regression (SLR) model, assumptions, interpretation and hypothesis testing; multiple linear regression (MLR) model, assumptions, interpretation and hypothesis testing; modelling non-linear relationships; dummy variables; interaction terms; the failure of MLR assumptions; tests and implications for hypothesis testing; problems of endogeneity; instrumental variables; short panel data methods; Stata.

Syllabus

The module will typically cover the following topics:

Review of random variables, associated distributions and moments; review of statistical estimation, estimator sampling distributions and population inference; causality and selection bias; experimental versus non-experimental data; simple linear regression (SLR) model, assumptions, interpretation and hypothesis testing; multiple linear regression (MLR) model, assumptions, interpretation and hypothesis testing; modelling non-linear relationships; dummy variables; interaction terms; the failure of MLR assumptions; tests and implications for hypothesis testing; problems of endogeneity; instrumental variables; short panel data methods; Stata.

Context

Restrictions
May not be combined with modules EC226-30
Part-year Availability for Visiting Students
Available in the Autumn term only (1 x test - 12 CATS) and in the Autumn and Spring terms together (2 x tests and 1 x assignment - 24 CATS) Monash = Available in the Autumn term only (1 x test & 1 assignment – 15 CATS)

Assessment

Assessment Method
Coursework (40%) + 3 hour examination (Summer) (60%)
Coursework Details
Test 1 (13%), Test 2 (12%), Assignment (15%), 3 hour examination (Summer) (60%)
Exam Timing
Summer

Exam Rubric

Time Allowed: 3 hours plus 15 minutes reading time during which notes may be made (on the question paper) BUT NO ANSWERS MAY BE BEGUN.

Answer ALL EIGHT questions in Section A (32 marks total) and ANY FOUR questions from Section B (17 marks each). Answer Section A questions in one booklet and Section B questions in a separate booklet.

Approved pocket calculators are allowed. Statistical Tables and a Formula Sheet are provided.

Read carefully the instructions on the answer book provided and make sure that the particulars required are entered on each answer book. If you answer more questions than are required and do not indicate which answers should be ignored, we will mark the requisite number of answers in the order in which they appear in the answer book(s): answers beyond that number will not be considered.

Previous exam papers can be found in the University’s past papers archive. Please note that previous exam papers may not have operated under the same exam rubric or assessment weightings as those for the current academic year. The content of past papers may also be different.

Reading Lists