Lecture 1 Basic Econometrics Rifai Afin SE MSc

Lecture 1 Basic Econometrics Rifai Afin SE, MSc

Let me introduce myself • Name: Rifai Afin SE, MSc • Education: - Undergraduate: Airlangga University - Post Graduate: University of Essex, UK

Experience (continued) • Teaching undergraduate level since 2004 • National consultant for both international such as The World Bank, ILO, ADB, USAID, AUSAID, and national organization such as Bank Indonesia, Ministry of Finance, Ministry National Development Planning, and local government since 2005

Publication (continued) • International seminar: Indonesian Regional Science Association IRSA • National Seminar: Academic Seminar at Economics Post graduate program, University of Indonesia, and Symposium of Indonesian Economist Association. • Journals: ISEI, BEMP, UWP, and JRE

Aims of the Course • Students completing this course will be able to: – Use the classical linear regression model to examine relationships between variables. – Test hypotheses about the relationships between variables. – Understand the problems that arise when the assumptions of the classical model are violated and overcome them – Estimate different types of econometric models.

Course Structure • Module 1: Classical Estimation – Introduction to the methodology of econometric research. – Revision of the simple linear regression model. – The Multiple Regression Model – Hypothesis Testing

Course Structure • Module 2: Violations of the Classical Error Assumptions – Heteroscedasticity – Autocorrelation – Topics from Stochastic Regressors, Random Walks, Qualitative Dependant Variables, Panel Data

Administrative Information • Lecturer in Charge – Rifai Afin SE, MSc – Room: Department of Economics, 2 nd Floor Faculty of Economics Building, telephone: 081938650018 – Office Hours: Tuesday 10. 00 -11. 00. – E-mail: rifaiafin 22@gmail. com or rifai@redi. or. id

Administrative Information • You need to: – Enrol for tutorials using at least 12 times – In the 8 nd week of term you should attend at least two of the computer lab sessions. – In these sessions you will be introduced to the computer package Eviews and Stata

Administrative Information • Computer Lab Work: · Most weeks there will be computer work to be completed Computer Lab Access • Applied econometric lab is the centre of econometric training and the schedule of training will be informed later • Computer assistance will be provided in this lab • Note: You will have computer work to complete for your first tutorial.

Administrative Information • Books to Buy: – Basic econometrics by Gujarati (4 th edition). • Assessment: – Midterm exam: 40% – Final exam : 60%

Econometric Methodology • Objective – Overview of the process of empirical research • What is econometrics? – Economic measurement? – Quantitative analysis of actual economic phenomena? – Empirical determination of “Economic Laws”? • Two main schools of econometric thought – Classical and Bayesian

Econometric Methodology – Statement of theory or hypothesis – Specification of mathematical model of theory – Specification of econometric model of theory – Obtaining the data – Estimation of the parameters of the econometric model – Hypothesis testing – Forecasting or prediction – Using the model for control or policy purposes

Econometric Methodology • Example: – Keynesian theory of consumption • Statement of theory or hypothesis – Marginal propensity to consume (MPC – 0<MPC<1 • Specification of the mathematical model – Y=Consumption Expenditure; X=Income

Econometric Methodology Y =MPC 1 X

Econometric Methodology • Specification of the econometric model – mathematical model represents an exact or deterministic relationship between Y and X • Economic relationships are inexact • u is the disturbance or random error term – u is a random (stochastic) variable • Linear regression model

Econometric Methodology • Obtaining data – WWW – CDROM – Library

Econometric Methodology

Econometric Methodology • Estimation of the model – regression analysis – OLS estimates (details next lecture) – On average, a US$1 increase in real income led to an increase of about US 72 c in consumption expenditure

Econometric Methodology • Hypothesis testing – theory: 0<MPC<1 – Is 0. 72 statistically less than 1? • Forecasting or prediction – Suppose GDP is expected to be $6000 billion, what will consumption expenditure be?

Econometric Methodology • Can also work out the Income Multiplier (M) – M=1/(1 -0. 72)=3. 57 • Using the model for control or policy purposes – Govt believe expenditure of US$4000 will lead to unchanged unemployment

Econometric Methodology • Using the model for control or policy purposes – Govt believe expenditure of US$4000 will lead to unchanged unemployment – What level of income leads to the target consumption expenditure? – Control variable X; target variable Y

Summary and Conclusions • Three stages of research – Specification of model • relevant variables, mathematical form, signs and magnitudes of parameters, error terms – Estimation • Data requirements (time series, cross section, panel), level of aggregation(households, regional, national), estimation techniques (OLS, etc)

Summary and Conclusion – Model evaluation • a priori beliefs (signs and magnitudes etc), significance of coefficients, degree of fit within sample, forecasting ability beyond sample, nature of residuals