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Students in interested in development economics may be familiar with the work of Daron Acemoglu.

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Problem 2 [30 points] Students in interested in development economics may be familiar with the work of Daron Acemoglu.  A seminal work in the field that this question will be drawing from is,

 

Acemoglu, D, Johnson, S, Robinson, J, The Colonial Origins of Comparative Development: An Empirical Investigation, The American Economic Review, Vol 91, No. 5, Dec. 2001, pp. 1369-1401.

 

In this paper the authors seek to further the understanding of why countries farther from the equator seem to enjoy higher economic growth.  They attribute the difference to a pattern of European colonization which was different in different climates.  Areas in which Europeans had more resistance to the local diseases were colonized such that governmental institutions came to resemble those in Europe.  In areas where Europeans had less resistance to the local diseases were colonized such that governmental institutions were created to extract wealth from colony and its local inhabitants.  

 

The authors have assessments of current government institutions in many countries, and of the government institutions that existed in the past, and on GDP.  They would like to show that government institutions are a large factor in determining economic well-being.  They also want to show that due to the extraordinarily high persistence of culture, current institutions seem to have their roots in the distant past, particularly in the experience of European colonization.  Economists sometimes use the word “strong” to indicate democratic-type institutions and the word “weak” to indicate institutions that do not offer much protection from rights violations and expropriation.

 

But the authors worry about endogeneity.  As an example, the colonists’ wealth could feed back into their choice of government institutions.  If that is true, then it is some other aspect of colonization other than disease resistance that may have caused the path-dependent outcome of institutions.  Or it may have been the religion or some other aspect of the culture of particular European groups that caused different paths for institutions.    

 

Instrumental variables and two-stage least squares provides a mechanism to examine only the input of European disease resistance during the colonization period on the formulation of governmental institutions.  In the first stage, the governmental institutions index is regressed upon the European mortality rate during colonization, and control variables.  The predicted governmental institutions strength can then be interpreted as the portion of institutional strength that can be attributed to the European disease resistance.  The outcome of these regressions is quite interesting on its own, and the authors always report both stages of their two-stage process.  

 

GDP is then regressed on the predicted institutional strength, and control variables, to show that past European disease resistance is a major factor in explaining the current arrangement of GDP around the world, and the linkage between the past experience and the current situation is governmental institutions.  

 

Prof. Acemoglu provides the data, and the Stata do files, for this paper on his website.  

https://economics.mit.edu/faculty/acemoglu/data/ajr2001

That provides a very convenient starting point for the investigation in this question.  Despite a quick mention of clustered standard errors within climate groups in footnote 18, the authors run and report their results without using robust standard errors.  In this question you will replicate some of the results using robust standard errors, and re-assess the statistical significance and the conclusions.  The paper is an interesting and accessible read about both instrumental variables and economic development.

 

As this question is formulated around reproducing the work of others, and the code, at least in Stata, is readily available, the question is meant as a connection to, and experience with, real-life economic research using instrumental variables.  As you reproduce the results (but using robust standard errors), you are encouraged to absorb as much about the investigation approach and write-up methodology of the authors as you can. 

 

For this question, supply your written answers, and your copied and pasted R or Stata output, for each sub-part in turn.  Additionally, as the sub-part of the question, submit, via a copy and paste, your R script file or Stata do file.  When supplying this code, start at the very beginning of your code, including bringing in packages (for R), setting the working directory (if necessary) and reading in the data.  

 

The TSLS results in table 5 of the paper, page 1389, are reprinted below, with the second stage in panel A and the first stage in panel B.

 

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