Basic Econometrics

Basic Econometrics

Rifai Afin SE, MSc

Lecture 1

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

• Lecturer in Charge– Rifai Afin SE, MSc

– Room: Department of Economics, 2nd Floor Faculty of Economics Building, telephone: 081938650018

– Office Hours: Tuesday 10.00-11.00.

– E-mail: [email protected] or [email protected]

Administrative Information

Administrative Information

• You need to:– Enrol for tutorials using at least 12 times– In the 8nd 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

• 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 (4th edition).

• Assessment:– Midterm exam: 40%– Final exam : 60%

Administrative Information

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

– 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

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=Income10; XY

Econometric MethodologyY

X

1

=MPC

• 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

uXY

• Obtaining data– WWW– CDROM– Library

Econometric Methodology

Econometric Methodology

Data on Y (personal consumption expenditure) and X (Gross DomesticProduct), 1980-1991 in 1987 Billions of $US

Year Y X1980 2447.1 3776.31981 2476.9 3843.11982 2503.7 3760.31983 2619.4 3906.61984 2746.1 4148.51985 2865.8 4279.81986 2969.1 4404.51987 3052.2 4539.91988 3162.4 4718.61989 3223.3 4838.01990 3260.4 4877.51991 3240.8 4821.0

Source: Gujarati, p 6. Reproduced from Economic Report of the President, 1993, TableB-2, p. 350.

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 US72c in consumption expenditure

XY 7194.08.231ˆ

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?

6.4084ˆ

)6000(7194.08.231ˆ

Y

Y

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

MPCM

1

1

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 Y5882

7194.08.2314000

X

X

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