1Econ 403: Topics in Development Economics and PolicyAssignment 1Due: January 25th, 2016, 2:10pm (beginning of class)Location: Lecture room[Note: Please hand in your own solutions]I. Robustness of the Cross-Country Income – Poverty RelationshipThe objective of this question is to assess whether modifications to the regression modelin Besley & Burgess (2003) affect the conclusions regarding the sufficiency of promotingnational income per capita growth to achieve the MDG poverty goal.• In order to carry this exercise, you will use the Stata dataset titled“povertygoals7_bis.dta”, made available by the authors. it is available on thecourse’s Blackboard webpage.• This dataset is composed of repeated observations for a sample of countries. Wewill employ the sample of countries used for the analysis by the authors, thosethat include extreme poverty measures (which use a poverty of approximately$1.09 per person/day).Instructions(a) Estimate the bivariate regression:ln Pit = ? + ?ln µit + eitwhereln Pit = the natural logarithm of the poverty headcount ratio (headcoun)ln µit = the natural logarithm of the GNP per capita, PPP (gnppc)Hints: Construct variables in natural logs using ‘generate’ command.For the regression analysis, use ‘regress’ command, with option ‘if povline < 50’.Also, include the option ‘cluster(ccode)’ to allow the error terms to be correlatedfor all observations for each country.The command should have the following structure:regress lny lnx if povline < 50, cluster(ccode)[2 points](b) Estimate the multivariate regression allowing for country fixed effects (whichcontrol for unobserved characteristics that are fixed at the country level).ln Pit = Si ?i1(ccode = i) + ?ln µit + eitwhere1(ccode = i) are indicator variables for each one of all countries i2Hints: The country fixed effects specification can be estimated in Stata using the‘areg’ command, with the option ‘absorb(ccode)’The command should have the following structure:areg lny lnx if povline < 50, absorb(ccode) cluster(ccode)[2 points](c) Estimate the two following multivariate regressions that gradually add thefollowing controls:(1) year fixed effects:ln Pit = Si ?i1(ccode = i) + ?ln µit + Stdt1(year = t) + eitwhere 1(year = t) are indicator variables for each one of the years (denoted t)in the dataset.(2) the natural logarithm of population sizeln Pit = Si ?i1(ccode = i) + ?ln µit + Stdt1(year = t) + ß ln POPit + eitwhereln POPit = the natural logarithm of the country population (pop)Hint: The year fixed effects should be added manually to the country fixed effectsspecification, by creating year dummy variables. The other options mentionedabove should remain the same.)[3 points](d) Test for the statistical significance of each estimate of the ? (simple/partial)correlation in each model. Interpret the magnitudes of the coefficients in eachmodel, and relate these, in the context of the discussion of omitted variables (orunobserved heterogeneity) bias. [5 points](e) Calculate the predicted annual growth rate of national income per capita necessaryto halve world poverty by 2015 (from 1990). Interpret the results. Whatconclusions can we reach regarding the main analysis conducted by the authors?[5 points](f) Repeat steps (a) – (e) using as dependent variable the natural logarithm of thepoverty gap. What conclusions can we reach in this case? [3 points]

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