module specification

This module has two components.  The first component will focus on mathematical tools used in contemporary economics, business economics and financial economics analysis. It will deal with both, the use of mathematics in the conceptualisation of economic theory as well as its use as a means to solve specific problems.  The second component will focus on the mathematical and statistical methods employed in the construction of econometric models and the application of these models for empirical analysis and policy evaluation

EC5003  Introduction to Econometrics; EC5006 Microeconomics

The module aims to:
1. develop students’ skills and understanding of a selection of mathematical and econometric techniques and theories which are commonly used by economists;
2. develop students’ abilities to provide economic interpretations to formal arguments;
3. develop students’ understanding of mathematical reasoning in economics;
4. knowledge of procedures employed to construct econometric models for policy analysis and forecasting.

The module also aims to develop students' skills, in particular: literacy; academic study skills; subject research; data analysis; applied analysis; quantitative analysis; critical thinking; and problem solving.

Mathematical Economics
Constraint Optimisation: The problem and its economic interpretations, equality constraints, the Lagrange approach, a note on inequality constraints, maximum value function, envelope functions. Duality Expenditure minimisation:  duality:  Expenditure functions and the compensated demand curves; properties of expenditures, functions and the Shepherd’s Lemma, indirect utility and Roy’s identity.   Other important identities, Slutsky’s equation, the importance of duality.
Linear Programming : Linear production technologies; Samuelson’s Surrogate Production Function, linear optimisation and solution algorithms; Duality and Complementary Slackness; demand for characteristics
Information and the Market: price of information; asymmetric information and the existence of equilibrium; the problem of signalling. Introductory Note on Game Theory and Bargaining
Dynamic Analysis; First order differences equations.   Cobweb models with first order dynamics.   Macro models with first order dynamics.  The Harrod-Domar model.
Second order difference equation.   Cobweb models with second order dynamics.   Macro models with second order dynamics. Unemployment/inflation model. Monetary policy in the Fisher Black model.
Dynamic optimisation.

Econometrics
Preliminary data analysis: trends, non-stationarity, testing procedures
Model specification: autoregressive distributed lag models, structural and vector autoregressive models, error correction representation, exogeneity and Granger causality, testing procedures
Estimation and Inference:  maximum likelihood method, LR, LM, Wald
Qualitative Choice, Limited/Truncated variable models: logit, probit, tobit models
Panel Data Analysis 

There will be a 3 hour session each week which will comprise a lecture (2 hours) and a seminar or IT workshop (1 hour) session.  In the lectures   new material, identifying the issues and the line of argument will be delivered.  In the seminar, students will engage in problem solving techniques and/or computer workshops.  

On successful completion of the module students will be able to:
1. understand the basic tools of static and dynamic optimisation;
2. understand some of the mathematical reasoning, which is used in contemporary economic theory;
3. solve problems with the use of mathematical reasoning;
4. understand the principles underlying the fundamental statistical models employed in empirical analysis of economic processes;
5. undertake algebraic operations and differential calculus, as relevant to derive formulae for the topics covered;
6. select  the statistical model most appropriate for the problem at hand and to interpret empirical results correctly.
  
 

There are three components of assessment: a class test in mathematical economics, an econometric report and a three hour unseen examination on both mathematical economics and econometrics. In each assessment, students are required to demonstrate a command of the basic principles underlying the subject matter and the application of the technical skills to analyse real-life issues.      

Mathematical Economics
Attfield, Demery and Duck, (1985) Rational Expectations in Macroeconomics, Blackwell
Baumol, W.(1970), Economic Dynamics, Macmillan, 3rd ed.
Binmore, K., (1991)  Fun and Games, Lexington.
Dixit, A and Skeath S. (1999) Games of Strategy, W.W Norton & Company.
Fisher Black,  (1990) Business Cycles and Equilibrium, Blackwell.
Gandolfo, (1980)  Mathematical Methods of Economic Dynamics, North Holland, 2nd ed
Gibbons, R., (1992)  A Primer in Game Theory, Harvester Wheatsheaf.
Hammond, P and Sydsaeter, K (2002) Essential Mathematics for Economic Analysis Prentice Hall.
Jehle, G A and Reny, P J (2000) Advanced Microeconomic Theory, Second edition, Adison Wesley.
Pemberton, M. and Rau, N. (2011) Mathematics for Economists: An Introductory Textbook, Manchester University Press, 3rd ed

Econometrics
Brooks, C. , (2008), Introductory Econometrics for Finance, Cambridge University Press
Gujarati, D.N. and Porter, (2010), Basic Econometrics, McGraw-Hill
Stock,  J.H. and M.W. Watson, (2012), Introduction to Econometrics, Pearson
Wooldridge, J.M., (2012),  Introduction to Econometrics: A Modern Approach; South-Western CENGAGE Learning