The course aims to provide students with important skills which are of both academic and vocational value, being an essential part of the intellectual training of an economist and social scientist and also useful for a career.
Principal Learning Outcomes
By the end of the module students shouldbe able to 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. Demonstrate capacity of: (i) Analytical thinking, reasoning and application. (ii) Critical, creative and strategic thinking. (iii) Abstraction and Problem solving. (v) Applying critical analysis to the topics of the module, formulating concepts and hypotheses, and showing how they are tested in relevant literature. Demonstrate proficiency in study and research skills such as: (i) data skills: Use of library and internet as information sources. Knowledge of how to locate relevant data, extract appropriate data, analyse and present material. (ii) mathematical/statistical skills: use/application of mathematics and diagrams in economic analysis; understanding of statistical analysis of data. Use of spreadsheet and the statistics package STATA. (iii) communicating their knowledge and understanding to others, verbally and in writing. (iv) reviewing the relevant literature and evidence.
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.
- Core Module
- L1L8 - Year 2
- Optional Core Module
- LM1D (LLD2) - Year 2, R9L1 - Year 2, R3L4 - Year 2, R4L1 - Year 2, R2L4 - Year 2, R1L4 - Year 2, V7MR - Year 2
- Optional Module
- V7ML - Year 2, V7ML - Year 3, LA99 - Year 2, V7MM - Year 4, V7MP - Year 2, V7MP - Year 3, V7MQ - Year 4
- Pre or Co-requisites
- EC120 for Economics students, including joint degrees (excluding GL11). IB122 for WBS students. EC106 or EC107 for all other students.
- May not be taken by GL11 students. May not be combined with EC226. Only available to LA99 students with a minimum mark of 65 in QS104.
- 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 Method
- Coursework (40%) + 3 hour exam (60%)
- Coursework Details
- Two 50 min tests (1 x 12% + 1 x 13%) + 1 Assignment (15%)
- Exam Timing
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.