A "politically robust" experimental design for public policy evaluation, with application to the Mexican universal health insurance program.

We develop an approach to conducting large-scale randomized public policy experiments intended to be more robust to the political interventions that have ruined some or all parts of many similar previous efforts. Our proposed design is insulated from selection bias in some circumstances even if we lose observations; our inferences can still be unbiased even if politics disrupts any two of the three steps in our analytical procedures; and other empirical checks are available to validate the overall design. We illustrate with a design and empirical validation of an evaluation of the Mexican Seguro Popular de Salud (Universal Health Insurance)program we are conducting. Seguro Popular, which is intended to grow to provide medical care, drugs, preventative services, and financial health protection to the 50 million Mexicans without health insurance, is one of the largest health reforms of any country in the last two decades. The evaluation is also large scale, constituting one of the largest policy experiments to date and what may be the largest randomized health policy experiment ever.     

Tests of institutional versus non-institutional models of local public expenditure determination

Are institutional or non-institutional factors more important determinants of local public expenditure decisions? Employing data that allows us to directly identify the entire distribution of voter expenditure demands, we estimate models of deviations of actual expenditures from the expenditure demand of defensible benchmarks — namely, the median voter's expenditure demand and the mean of voters' expenditure demands. Three competing paradigms are employed to specify these models; namely, a non-institutional model, the reform government movement's explanation of how institutions affect local government decisions and a transactions-cost model of this same phenomenon. Predictions from these three competing models differ in many respects. Comparisons of results from estimating models of expenditure deviations are found to be generally more consistent with the non-institutional model than with either of the two institutional models. These results suggest that a competitive local public service market helps limit the ability of governments to tax and spend in excess of the demands of the median or mean voter.     

Activating voters in congressional elections

This paper shows that one of the consequences of electoral campaigns is activation. Much research in the last decade has shown that campaign spending is related to electoral outcomes, but nearly all of this research has been conducted on district-level data, so we do not know how campaigns influence individual voters. This research returns to the theoretical framework offered inThe People's Choice and shows that at least part of the effect of campaigns is due to the increased likelihood of people voting when campaigns are more intense.     

A Fast, Easy, and Efficient Estimator for Multiparty Electoral Data

Katz and King have previously developed a model for predictingor explaining aggregate electoral results in multiparty democracies.Their model is, in principle, analogous to what least-squaresregression provides American political researchers in that two-partysystem. Katz and King applied their model to three-party electionsin England and revealed a variety of new features of incumbencyadvantage and sources of party support. Although the mathematicsof their statistical model covers any number of political parties,it is computationally demanding, and hence slow and numericallyimprecise, with more than three parties. In this paper we producean approximate method that works in practice with many partieswithout making too many theoretical compromises. Our approachis to treat the problem as one of missing data. This allowsus to use a modification of the fast EMis algorithm of King,Honaker, Joseph, and Scheve and to provide easy-to-use software,while retaining the attractive features of the Katz and Kingmodel, such as the t distribution and explicit models for uncontestedseats.     

Development and validation of the AmpFlSTR MiniFiler PCR Amplification Kit: a MiniSTR multiplex for the analysis of degraded and/or PCR inhibited DNA

DNA typing of degraded DNA samples can be a challenging task when using the current commercially available multiplex short tandem repeat (STR) analysis kits. However, the ability to type degraded DNA specimens improves by redesigning current STR marker amplicons such that smaller sized polymerase chain reaction (PCR) products are generated. In an effort to increase the amount of information derived from these types of DNA samples, the AmpFlSTR MiniFiler PCR Amplification Kit has been developed. The kit contains reagents for the amplification of eight miniSTRs which are the largest sized loci in the AmpFlSTR Identifiler PCR Amplification Kit (D7S820, D13S317, D16S539, D21S11, D2S1338, D18S51, CSF1PO, and FGA). Five of these STR loci (D16S539, D21S11, D2S1338, D18S51, and FGA) also are some of the largest loci in the AmpFlSTR SGM Plus kit. This informative nine-locus multiplex, which includes the gender-identification locus Amelogenin, has been validated according to the FBI/National Standards and SWGDAM guidelines. Our results demonstrate significant performance improvements in models of DNA degradation, PCR inhibition, and nonprobative samples when compared to the AmpFlSTR Identifiler and SGM Plus kits. These data support that the MiniFiler kit will increase the likelihood of obtaining additional STR information from forensic samples in situations in which standard STR chemistries fail to produce complete profiles.