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Econometrics

Econometrics. By Vijay Kasi and Sebastian Pickerodt Presented in CIS 9280, Oct 10, 2002. What is Econometrics?. “ Econometrics is based upon the development of statistical methods for estimating economic relationships, testing economic theories, and evaluating government and business policy ”

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Econometrics

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  1. Econometrics By Vijay Kasi and Sebastian Pickerodt Presented in CIS 9280, Oct 10, 2002

  2. What is Econometrics? • “Econometrics is based upon the development of statistical methods for estimating economic relationships, testing economic theories, and evaluating government and business policy” • Most often, observational data has to be used instead of experimental data. • Therefore, there is a need for special methods to obtain “ceteris paribus*” results. * lat.: “other things being equal”

  3. Econometrics as a discipline Economic Theory Testing Theory Theory Economical Statistics Econometrics Forecasting Data Mathematical Statistics Methods Policy Advice

  4. Phases of Econometric Research • Statement of theory or hypothesis • Specification of the mathematical model of the theory • Specification of the econometric model of the 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

  5. Statement of Theory • “…men are disposed as a rule and on average to increase their consumption as their income increases, but as much as the increase in their income.”, J.M. Keynes Y X

  6. ^ ^ ^ ^ ^ ^ Y 2 X Mathematical and Econometric model • mathematical:Y=1+2X • econometric:Ŷ=1+2X+u u 1

  7. Types of Data • Cross-Sectional Data • A (random) sample of several entities at a given point of time. • Time Series Data • One or several variables measured at subsequent points in time. • Pooled Cross Sections • Data from different Cross-Sectional samples from various points in time combined. • Longitudinal Data • Data from the same Cross-Sectional sample taken at subsequent points in time.

  8. Sources of Data • Business statistics • Bureau of Economic Analysis (BEA) • Economic Bulletin Board (EBB) • National income and production statistics • Federal Reserve Bank • International Monetary Fund IMF • Organization of Economic Cooperation and Development (OECD) • United Nations (UN) • Individual business or organizational data • …

  9. Estimation of Parameters of Econometric Model • Simple Regression • Multiple Regression • Based on Ordinary Least Squares (OLS) Demo

  10. Hypothesis Testing • Undertake hypothesis test, construct confidence intervals and asses the overall fit of the model to the data used to estimate it. • Methods used include • R² • ² • t Test • F Test

  11. Assumptions made in Classical Regression Model • Linearity in the parameters • Fixed values for regressors (X’s) in repeated sampling • Zero mean value of û for given X’s • Constant variance of û for given X’s (Homoscedasticity) • No autocorrelation in disturbances. • û and X’s are independent or at least uncorrelated • Number of observations is greater than number of regressors • Sufficient variability in the values taken by the X’s. • Correct specification of the regression model. • No exact linear relationship (i.e., no multicollinearity) in the X’s. • Normal distribution of û. • Advanced econometrics deals with situations in which these assumptions are not justified.

  12. Forecasting and Policy • Estimate: 1=-231.8, 2=0.7194 • Ŷ= -231.8+0.7194X • To forecast: insert anticipated value for X. • For policy purposes: solve model for X and insert a desired value for Y. • X=(Y+231.8)/0.7194

  13. Example of Econometrics in IS • Snir and Hitt (2001) examine the effect of bidding cost in online reverse auction markets for IT services. • Data: transaction history of one relevant marketplace. • Hypothesis 2: Projects with a higher value receive more bids. [Provided that bidding is costly.] • nb,i = β0+ β1ln(va,i)+ β2ln(Mi) + β3ln(Ti) + β4ln(Pi) + εi P: Project length: used as measure for project value n: Number of bids v: Average bid M: Market maturity T: Auction length • Hypothesis 2 was supported by β4being positive and significant.

  14. Pros and Cons • Pros • Set of methods to interpret non-experimental or observational data • The data is taken “as-is” , thus free of any observer bias. Thus method could have good external validity • Cons • The underlying assumptions are a threat to internal validity

  15. References • Hitt, E. M., Snir, L. M. (2001). “The Emerging Knowledge Economy: Exchange in Internet Spot Markets for IT Expertise.” Management Science. • Gandhi, D. N. (1995). Basic Econometrics, McGraw Hill. • Kmenta, J. (1997). Elements of Econometrics, University of Michigan Press. • Wooldridge, J. M. (1999). Introductory Econometrics: A Modern Approach, South-Western Pub.

  16. Questions

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