1. Extra Lecture: Instrumental Variables Olaf J. De Groot NOTE: The content of this lecture is not part of the exam. It is meant to make you UNDERSTAND the concepts of Instrumental Variables… Do NOT study the content, just use it to make sure you understand the concepts

2. Outline Quick discussion of OLS Estimation Examples of in- and outputs from OLS Instrumental Variables Estimation: – Why – How – Problems Examples: – Tabellini – Other Examples

3. OLS Estimations 1 ABXYCDABXYCD

4. CapitalLabour Conflict GDP Export demand GDP0

5. OLS Estimations 2 Next step is to operationalize the expected linkage into a testable regression: Y=β 0 + β 1 *K+ β 2 *L+ β 3 *K+ β 4 *GDP0+ β 5 *NX + β 6 *conf+ε Or, to put it more generally: Y= β 0 + β*X+ β 6 *conf+ε Goal of the estimation is to fit the β’s in such a way so that the residual is minimized.

6. OLS: Typical input CountryGDP(%)K(%)L(%)NX($)GDP0($p)Conf(bin) A410110010,0000 B3725013,0000 C290-508,0001 D563-103,0000 E-5-2012,0001 F0203019,0000 G28209,0000 H6153506,0000 I7113407,0000 J362-4010,0000 K140-2015,0000 L0409,0001

7. OLS: Typical Output variableEstimated BetaStandard errorsP-value constant0.8250.1250.001 K0.0120.0060.052 L1.2010.4850.023 Ln(GDP0)1.5240.3570.008 NX0.1020.0970.857 conflict2.1031.0020.046 Adjusted R-Squared0.523 Export Demand and Capital growth are not significant. That is, it is impossible the reject the null hypothesis that there is no effect. GDP0, on the other hand, it is certain with more than 99% that there is an effect.

8. Instrumental Variables: Why Sometimes the linkages you want to research are not as clear-cut. Ex.1: XY (endogeneity) Ex.2:X?Y (measurement) Ex.3:Omitted variables Solution: IV estimation: Z XY

9. Instrumental Variables: How There are two ways in which you can employ IV-estimation: – Easy way, by replacing X with Z, but requires strict conditions from the data: 1)Instrument has to be truely exogenous 2)Z has to correlate with X very strongly Not often feasible – Harder way, by using a 2-stage Least Squares (2SLS estimation), which we are going to discuss today.

10. Instrumental Variables: 2SLS Obviously, 2SLS uses 2 stages. In first stage, the influence resulting from Y->X is excluded and a new X is calculated (X-hat) whose value merely includes the value as a result of a change in Z During the second stage, X-hat is regressed on Y.

11. Instrumental Variables: graphical 1 ZAXYBZAXYB

12. Instrumental Variables: graphical 2 Stage 1 ZA XY B X= λ 0 +λ 1 *A+λ 2 *B+λ 3 *Z+μ, then estimate X-hat

13. Instrumental Variables: graphical 3 Stage 2 ZA XY B Y= β 0 + β 1 *A+ β 2 *B+ β 3 *X-hat+ ε

14. Instrumental Variables: Problems Biggest problem is finding a good IV. Good IVs meet the following criteria: – Strong causal effect from Z on X. – No relation between Z and Y in either direction – Preferably no strong effects of Z on A or B Researcher using IV spends most time explaining why that particular IV is appropriate.

15. Instrumental Variables: Easy Example You want to know influence of operating cost on distance driven (by car). Problem of endogeneity, so use fuel price as instrument 1)regress: (oper.costs)=λ+θ(fuel price)+μ 2)Calculate (oper.costs)=λ+θ(fuel price) 3)Regress (distance)=α+β(oper.costs)+ε

16. Instrumental Variables: Example Tabellini’s paper on the effect of culture on economic growth is one example. Question: Does Culture influence economic development – Culture is measured with World Values Survey – Culture: trust, respect, confidence, etc – Economic development also influences culture (in low-growth environment, maybe less confident)

17. Tabellini: graphical 1 Historical determinantsUrbanization rate CultureGDP growth Education

18. Background idea: Tabellini Historical DeterminantsCultureCurrent Current Development

19. Other IV examples 1 Somebody wants to research the influence of economic growth on Probability of civil war. But, GDPPr(conflict) So, want to use IV, but which one? Looking at Africa, they realise that African agricultural economies are dependent on Rainfall. There is no relationship between rainfall and conflict, so this is a proper IV. Miguel et al., 2004, JPE

20. Other IV examples 2 Somebody wants to research the influence of information technology on corruption in USA. But, ITcorruption So, want to use IV, but which one? Idea: lightning voter information IT usage costs corruption IT usage WP, Andersen et al, 2008

21. Other IV examples 3 Somebody wants to know what the influence of education on later wage is. But: educationability wage So, are you measuring return to educ or ability? Several authors have used wars as IV that influences education level, independent of ability. E.g. Large EU wage database and use dummy for people born in Germany during 1930s: born(G,1930s)Educwage

22. Other IV examples 4 Somebody wants to study the wage penalty for mothers pay at return to labour market. You have: working women sample, wages, dummy for women with 6-12 month old baby, controls. BUT, motherhood may be endogenous. You look at gender of previous children. Pr(second child) increases if first was girl. So:(firstborn=girl)secondborn wage

23. Other IV examples 5 Somebody wants to study the influence of Aid on Economic Growth. But there is reverse causality, so an exogenous effect on aid is to be found as IV One idea is to look at natural disasters, which are always good exogenous variables. Natural disaster also has direct effect, so use disaster in OTHER nations as IV disaster in –Xaid for –Xaid for X growth in X

24. Conclusion Instrumental Variables are good way to deal with endogeneity. When reading IV-paper, think: – Is the IV truely exogenous to the final result? – Is the correlation between the IV and X good enough. Be very creative in finding ways to use IVs in your estimations.