Competition Among Public Schools: A Reply to Rothstein (2004)

Rothstein has produced two comments, Rothstein (2003) and Rothstein (2004), on Hoxby "Does Competition Among Public Schools Benefit Students and Taxpayers," American Economic Review, 2000. In this paper, I discuss every claim of any importance in the comments. I show that every claim is wrong. I also discuss a number of Rothstein's innuendos--that is, claims that are made by implication rather than with the support of explicit arguments or evidence. I show that, when held up against the evidence, each innuendo proves to be false. One of the major points of Rothstein (2003) is that lagged school districts are a valid instrumental variable for today's school districts. This is not credible. Another major claim of Rothstein (2003) is that it is better to use highly non-representative achievement data based on students' self-selecting into test-taking than to use nationally representative achievement data. This claim is wrong for multiple reasons. The most important claim of Rothstein (2004) is that the results of Hoxby (2000) are not robust to including private school students in the sample. This is incorrect. While Rothstein appears merely to be adding private school students to the data, he actually substitutes error-prone data for error-free data on all students, generating substantial attenuation bias. He attributes the change in estimates to the addition of the private school students, but I show that the change in estimates is actually due to his using erroneous data for public school students. Another important claim in Rothstein (2004) that the results in Hoxby (2000) are not robust to associating streams with the metropolitan areas through which they flow rather than the metropolitan areas where they have their source. This is false: the results are virtually unchanged when the association is shifted from source to flow. Since 93.5 percent of streams flow only in the metropolitan area where they have their source, it would be surprising if the results did change much. The comments Rothstein (2003) and Rothstein (2004) are without merit. All of the data and code used in Hoxby (2000) are available to other researchers. An easy-to-use CD provides not only extracts and estimation code, but all of the raw data and the code for constructing the dataset.

Combining genome-wide association mapping and transcriptional networks to identify novel genes controlling glucosinolates in Arabidopsis thaliana.

BackgroundGenome-wide association (GWA) is gaining popularity as a means to study the architecture of complex quantitative traits, partially due to the improvement of high-throughput low-cost genotyping and phenotyping technologies. Glucosinolate (GSL) secondary metabolites within Arabidopsis spp. can serve as a model system to understand the genomic architecture of adaptive quantitative traits. GSL are key anti-herbivory defenses that impart adaptive advantages within field trials. While little is known about how variation in the external or internal environment of an organism may influence the efficiency of GWA, GSL variation is known to be highly dependent upon the external stresses and developmental processes of the plant lending it to be an excellent model for studying conditional GWA.Methodology/principal findingsTo understand how development and environment can influence GWA, we conducted a study using 96 Arabidopsis thaliana accessions, >40 GSL phenotypes across three conditions (one developmental comparison and one environmental comparison) and ∼230,000 SNPs. Developmental stage had dramatic effects on the outcome of GWA, with each stage identifying different loci associated with GSL traits. Further, while the molecular bases of numerous quantitative trait loci (QTL) controlling GSL traits have been identified, there is currently no estimate of how many additional genes may control natural variation in these traits. We developed a novel co-expression network approach to prioritize the thousands of GWA candidates and successfully validated a large number of these genes as influencing GSL accumulation within A. thaliana using single gene isogenic lines.Conclusions/significanceTogether, these results suggest that complex traits imparting environmentally contingent adaptive advantages are likely influenced by up to thousands of loci that are sensitive to fluctuations in the environment or developmental state of the organism. Additionally, while GWA is highly conditional upon genetics, the use of additional genomic information can rapidly identify causal loci en masse