Naidu (2010)

From edegan.com
Revision as of 21:50, 4 June 2011 by imported>Bo (→‎How it is tested?)
Jump to navigation Jump to search

Theory Questions

What is the author's hypothesis?

How does the author test the hypothesis?

How does the author rule out alternative hypotheses?

How might these tests be run if one had quantitative evidence?

What problems might arise in this quantitative analysis?

Empirical Questions

What's the author's hypothesis?

The null hypothesis of the empirical section is that the disenfranchisement of Southern blacks (through poll taxes and literacy tests) had no effect on

  • (a) Voter turnout,
  • (b) The Democratic party vote share,
  • (c) The teacher/child ratio for blacks,
  • (d) The teacher/child ratio for whites.
  • (e) Land values in counties with the poll taxes and literacy tests.

The author does not give a sense of his priors, but he does say that his findings (null hypotheses rejected for (a) through (c)) are "[C]onsistent with historical evidence that these disenfranchisement laws independently lowered black political participation."

In particular, the author notes that the fall in black educational inputs (ie, the teacher/student ratio) is consistent with theoretical political economy models including the one developed late in this paper.

All of this is on page 2 and 3 of the paper.

How it is tested?

The author compares adjacent county-pairs that straddle borders.

Note that the same county can be in multiple pairs, and therefore is in the sample multiple times. This creates the need for multidimensional clustering as developed by Cameron et al, 2006. Standard errors are clustered for both within-state over time correlations of county residuals, as well as within borer-segment. Discussion of these in first paragraph of Section 5 on page 22.

QUESTION ABOUT EQUATION 11 ON PG 22: Why are the two [math]D[/math] dummy variables summed?

What do the tests achieve?

The tests reject the null hypotheses (a)-(c) and (e).

How could the tests be improved?

What are the tests' strengths and weaknesses?

Can you think of any alternative empirical tests?