COURSES: 1. Short Course in Econometrics for the Practitioner (P000500) 2. Short Course in Econometric Analysis of Cointegration (P000537)

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1 Get the latest knowledge from leading global experts. Financial Science Economics Economics Short Courses Presented by the Department of Economics, University of Pretoria WITH 2015 DATES 1

2 COURSE STRUCTURE AND VENUE COURSES: Delegates attend a five-day course, presented in a computer lab on the main campus of the University of Pretoria. ASSESSMENT/ACCREDITATION/CERTIFICATION In terms of the Higher Education Act (Act 101 of 1997), the University of Pretoria is classified as a public higher education institution. The University of Pretoria is accredited by the Council on Higher Education (CHE) as a multi-purpose public training provider in the higher education and training band. Short courses and certificate programmes presented by the University of Pretoria through CE at UP are not unit standard based and not credit bearing on the National Qualifications Framework. Delegates successfully completing a course and who comply with the relevant assessment criteria, receive a certificate of successful completion from the University of Pretoria. 1. Short Course in Econometrics for the Practitioner (P000500) 2. Short Course in Econometric Analysis of Cointegration (P000537) 3. Short Course in Econometric Analysis of Panel Data (P000991) 4. Short Course in Economic Indicators: Monitoring the South African Economy (P000729) PRESENTERS Lecturers from the Department of Economics, University of Pretoria. COURSE FEE (VAT inclusive) The course fee is per delegate per course and includes comprehensive lecture notes, text books, computer lab fees, lunch and refreshments. The fee excludes travel, accommodation and subsistence allowance. REGISTRATION ENQUIRIES Mariëtte de Villiers Tel: +27 (0) Fax: +27 (0) Mariette.devilliers@ce.up.ac.za Website: ENQUIRIES REGARDING OVERALL CONTENT Reneé van Eyden (Course leader) Tel: +27 (0) E mail: renee.vaneyden@up.ac.za ECONOMICS: Short Courses 2

3 1. Short Course in Econometrics for the Practitioner (P000500) 1-5 Jun 9-13 Nov BRIEF DESCRIPTION This course is of an applied nature and focuses on hands-on experience in estimation, interpretation and evaluation of economic relationships. The aim is to reconcile economic theory with practice, thereby empowering delegates with analytical skills and a hands-on approach to decision-making processes. The course begins with a basic introduction to the concepts of regression (ordinary least squares estimation) and statistical inference. Thereafter, attention is given to the violations of the classical linear regression model that are often encountered in applied econometric work the consequences of these violations are discussed, as well as practical ways of detecting (diagnostic testing) and solving these problems. Various applications of regression analysis, such as forecasting and policy simulation are discussed and applied. The course also includes the discussion of the practical implications of employing non-stationary data in estimation, the detection of unit roots in the underlying data-generating processes and concepts of residual-based cointegration and error-correction modelling. LEARNING OUTCOMES After completion of this course, candidates should be able to; apply regression analysis, use dummy variables, deal with structural breaks, deal with violations of the basic assumptions of 00 regression analysis, be able to apply techniques of residual-based (Engle- 00 Granger) cointegration and error correction modelling in 00 the case where time-series data contain unit roots. WHO SHOULD ENROL? Experience as a researcher or analyst in any of the following fields of economic application is required: financial markets, socio-economics and health, development economics, public finance and tax policy, or international trade and finance. LEARNING ASSUMED TO BE IN PLACE Matric or Grade 12, with exposure to empirical economic analysis. Statistics at the second-year level is advised. CONTENT Principles and methodology of econometric analysis Introductory statistics Basics of regression analysis Single equation estimation Violations of the classical assumptions Regressions including dummy variables Non-stationarity and unit root testing Residual-based (Engle-Granger) cointegration Error-correction models Simulation (forecasting and policy analysis) REFERENCE MATERIAL Enders, W Applied Econometric Time Series. 3rd Edition. New York: John Wiley and Sons. Gujarati, D.N Essentials of Econometrics. 3rd Edition. McGraw-Hill. Gujarati, D.N. Porter, D.C Basic Econometrics (International Edition). 5th Edition. McGraw-Hill/Irwin. Harris, R. and Sollis, R Applied Time Series Modelling and Forecasting. John Wiley and Sons. (This text is based on an earlier title, which is out of print: Harris, R Using Cointegration Analysis in Econometric Modelling. London: Prentice Hall.) APPLICATION SOFTWARE EViews version 8 COURSE FEE (VAT Inclusive) The course fee is R per delegate 2. Short Course in Econometric Analysis of Cointegration (P000537) 8-12 Jun Nov BRIEF DESCRIPTION This course addresses appropriate modelling techniques for time-series data when unit roots are present in the data (i.e. data series are non-stationary), a problem that applied economists encounter in almost all economic timeseries applications. To ignore the fact that data may be non-stationary and to proceed to estimate a regression model containing non-stationary variables, at best ignores important information about the underlying statistical and economic processes generating the data, and at worst leads to nonsensical (or spurious) results. Therefore, to begin with, an overview of the common technical characteristics of timeseries data and the concept of stationarity is provided. The econometric techniques of cointegration and error-correction models are revised in single equations (residual-based cointegration), with emphasis on their empirical application. Thereafter, the notion of multivariate cointegration (the main focus of this course) is discussed and applied. LEARNING OUTCOMES After completion of this course candidates should be able to: understand and apply non-stationary time-series analysis; understand the concept of stationarity and unit root testing, and to apply the advanced econometric techniques of cointegration and error-correction modelling, especially in the multivariate context. 3

4 WHO SHOULD ENROL? The course is relevant for researchers and analysts in all fields of economic application: business, financial markets, socio-economics and health, development economics, public finance and tax policy, as well as international trade and finance. LEARNING ASSUMED TO BE IN PLACE This is an advanced course and requires an Honours level qualification in time-series econometrics (including a basic knowledge of the concepts of unit root testing and residualbased (Engle-Granger) cointegration, as these are merely included as revision). An understanding of matrix algebra is essential as well as experience as a researcher or analyst in any of the fields of economic application. Proficiency in EViews is also advised. CONTENT Overview of residual-based cointegration Data generating processes Stationary vs. non-stationary time series Cointegration in single equations (Engle-Granger) Error-correction models (ECM) Multivariate cointegration (focus of course) Vector autoregressive (VAR) models Impulse response functions and variance decompositions Johansen cointegration methodology Vector error-correction models (VECM) REFERENCE MATERIAL Enders, W Applied Econometric Time Series. 3rd Edition. New York: John Wiley and Sons. Harris, R. and Sollis, R Applied Time Series Modelling and Forecasting. John Wiley and Sons. (This text is based on an earlier title, which is out of print: Harris, R Using Cointegration Analysis in Econometric Modelling. London: Prentice Hall.) APPLICATION SOFTWARE EViews version 8 COURSE FEE (VAT inclusive) The course fee is R per delegate 3. Short Course in Econometric Analysis of Panel Data (P000991) Jun Nov BRIEF DESCRIPTION In this course panel data refers to the pooling over a number of time periods observations on a cross-section of countries, households, firms and so forth. Panel data allows for more informative results, more variability, more degrees of freedom and more efficiency. This course is of an applied nature and focuses on hands-on experience in estimation, interpretation and evaluation of economic relationships within a panel data context. We begin the discussion with the static linear model in a panel data setting. We start with the fixed effects (FE) model and pay attention to the least squares dummy variable (LSDV) estimator and the within transformation (within estimator). We distinguish between one-way and two-way error component models. Relevant hypothesis testing include testing for the validity of fixed effects, i.e. pooling of slope and intercept coefficients vs. only pooling the slopes. We continue the discussion by assuming a case where individual effects can be considered random factors, independently and identically distributed over cross-sections, i.e. the random effects (RE or EGLS) estimator. We also discuss making a choice between FE and RE. Relevant hypothesis testing includes testing the validity of random effects and the Hausman specification test. We also consider the problems of heteroscedasticity and autocorrelation in panel data models; testing for it and potential remedies. We then move on to topics related to endogenous regressors, dynamic linear model specification and relevant techniques (Nickel bias and correction; instrumental variables (IV) and general method of moments (GMM) estimation). We conclude with Panel time series issues and estimation (heterogeneity in both intercept and slope coefficients, random coefficients (RC) models, mean group estimator (MGE), seemingly unrelated regression (SUR) models, and panel unit root testing and cointegration). LEARNING OUTCOMES After completion of this course candidates should be able to estimate regression models for data organised in a panel and deal with violations of the basic assumptions of regression analysis. They should also be able to apply techniques of unit root testing and cointegration in the case where the panel contains unit roots. WHO SHOULD ENROL? Researchers or analysts in any of the following fields of economic application: development economics, public finance and tax policy, socio-economics and health, financial markets as well as international trade and finance. ECONOMICS: Short Courses 4

5 LEARNING ASSUMED TO BE IN PLACE Honours level qualification in time-series econometrics (including exposure to the concepts of unit root testing and cointegration). An understanding of matrix algebra and experience as a researcher or analyst in any of the fields of economic application. Proficiency in EViews is also advised. CONTENT Stationary Panel Data One-way and two-way error component models Hypothesis testing Heteroscedasticity and serial correlation Non-stationary Panel Data Unit root tests Estimation of non-stationary time series Cointegration tests Dynamic Panel Data Instrumental variable techniques Nickell Bias, DIF-GMM, SYS-GMM Panel Heterogeneity revisited and Spatial Dependence Heterogeneity in slope coefficients Seemingly Unrelated Regression (SUR) models Cross-sectional dependence REFERENCE MATERIAL Baltagi, B Panel Data Econometrics. 4th Edition. Chichester: John Wiley and Sons. Wooldridge, J.M Econometric Analysis of Cross Section and Panel Data. Cambridge: MIT Press. APPLICATION SOFTWARE EViews version 8 and STATA version 12 COURSE FEE (VAT Inclusive) The course fee is R per delegate 4. Short Course in Economic Indicators: Monitoring the South African Economy (P000729) 29 Jun - 3 Jul 30 Nov - 4 Dec BRIEF DESCRIPTION The course in Economic Indicators focuses on the available data sources and appropriate techniques to measure the macroeconomic performance of the South African Economy. The central focus of the course is on extracting meaningful information from the different types of economic indicators available in the daily press and specialist data collection institutions. The course also deals with basic economic and statistical manipulation techniques with the aim of extracting information from raw data. Emphasis is placed on the meaningful interpretation of the information in order to compile an informed opinion on the state of economic performance. Practical training is provided on ways of presenting this information to assist in the decision-making process. LEARNING OUTCOMES After completion of the course candidates should be able to extract and analyse meaningful information on the macroeconomic performance of the South African economy from the many sources of data available in the daily press and specialist data collection institutions. CONTENT Description of context and basic techniques in economic analysis Analysis of aggregate production, income and expenditure: selected national accounts information Economic growth Business cycles Inflation Balance of payments data and international indicators (exchange rates, terms of trade, etc.) Employment and unemployment data and related concepts Income distribution and various measures of welfare Financial indicators Fiscal indicators WHO SHOULD ENROL? The course is relevant for researchers, analysts and individuals who deal with issues related to the current macroeconomic performance of the South African economy. The course is also highly recommended for anyone dealing with economic policy matters. ADMISSION REQUIREMENTS Matric or grade 12 with experience in economic analysis. 5

6 REFERENCE MATERIAL Mohr, P Economic Indicators, 4th Edition. Pretoria: UNISA. COURSE FEE (VAT inclusive) The course fee is R per delegate and includes comprehensive lecture notes, text book, computer lab fees, lunch and refreshments. The fee excludes travel, accommodation and subsistence allowance. ENQUIRIES REGARDING CONTENT Dirk Scholtz (Course leader) Tel: +27 (0) dirk.scholtz@up.ac.za REGISTRATION ENQUIRIES Mariëtte de Villiers Tel: +27 (0) Fax: +27 (0) Mariette.devilliers@ce.up.ac.za Website: ENQUIRIES REGARDING CONTENT Andre Jordaan (Course leader) Tel: +27 (0) andre.jordaan@up.ac.za ECONOMICS: Short Courses 6

7 Course Portfolio of Continuing Education at University of Pretoria While we have an extensive range of courses on offer, these can be divided into the following encompassing fields of study: Agriculture Food Sciences Arts, Culture Language Business Management Entrepreneurship Education Teacher Development Environmental Natural Science Financial Science Economics General Management Responsible Leadership Human Health Human Resources Development Labour Relations Information Communication Technology Law Human Rights Marketing, Communication Customer Relations Project Risk Managament Property, Built Environment Urban Planning Public Service Administration Religious, Social Political Studies Science, Engineering Technology Supply Chain Logistics Management Tourism, Sport Recreation Veterinary Science Animal Health 7

8 Contact us: Tel: Fax: For customised courses: for quotations on in-house training. ECONOMICS: Short Courses 8