Corruption and Growth Under Weak Identification

The goal of this paper is to revisit the influential work of Mauro [1995] focusing on the strength of his results under weak identification. He finds a negative impact of corruption on investment and economic growth that appears to be robust to endogeneity when using two-stage least squares (2SLS). Since the inception of Mauro [1995], much literature has focused on 2SLS methods revealing the dangers of estimation and thus inference under weak identification. We reproduce the original results of Mauro [1995] with a high level of confidence and show that the instrument used in the original work is in fact 'weak' as defined by Staiger and Stock [1997]. Thus we update the analysis using a test statistic robust to weak instruments. Our results suggest that under Mauro's original model there is a high probability that the parameters of interest are locally almost unidentified in multivariate specifications. To address this problem, we also investigate other instruments commonly used in the corruption literature and obtain similar results.

Schools and Housing Markets: An Examination of School Segregation and Performance in Connecticut

This paper examines the relationship between house price levels, school performance, and the racial and ethnic composition of Connecticut school districts between 1995 and 2000. A panel of Connecticut school districts over both time and labor market areas is used to estimate a simultaneous equations model describing the determinants of these variables. Specifically, school district changes in price level, school performance, and racial and ethnic compositions depend upon each other, labor market wide changes in these variables, and the deviation of each school district from the overall metropolitan area. The specification is based on the differencing of dependent variables, as opposed to the use of level or fixed effects models and lagging level variables beyond the period over which change is considered; as a result the model is robust to persistence in the sample. Identification of the simultaneous system arises from the presence of multiple labor market areas in the sample, and the assumption that labor market changes in a variable due not directly influence the allocation of households across towns within a labor market area. We find that towns in labor markets that experience an inflow of minority households have greater increases in percent minority if those towns already ahve a substantial minoritypopulation. We find evidence that this sorting proces is reflected in housing price changes in the low priced segment of the housing market, not in the middle and upper segments.

Some Identification Issues in Nonparametric Linear Models with Endogenous Regressors

In applied work economists often seek to relate a given response variable y to some causal parameter mu* associated with it. This parameter usually represents a summarization based on some explanatory variables of the distribution of y, such as a regression function, and treating it as a conditional expectation is central to its identification and estimation. However, the interpretation of mu* as a conditional expectation breaks down if some or all of the explanatory variables are endogenous. This is not a problem when mu* is modelled as a parametric function of explanatory variables because it is well known how instrumental variables techniques can be used to identify and estimate mu*. In contrast, handling endogenous regressors in nonparametric models, where mu* is regarded as fully unknown, presents di±cult theoretical and practical challenges. In this paper we consider an endogenous nonparametric model based on a conditional moment restriction. We investigate identification related properties of this model when the unknown function mu* belongs to a linear space. We also investigate underidentification of mu* along with the identification of its linear functionals. Several examples are provided in order to develop intuition about identification and estimation for endogenous nonparametric regression and related models.

METALLOTHIONEIN RECEPTOR EXPRESSION IN LEUKOCYTES

Metallothionein (MT) represents a family of low molecular weight, cysteine-rich proteins that play a number of roles in cellular homeostasis. MT is synthesized as a consequence of a variety of cellular stressors, including exposure to toxic metals, increased temperature, tissue wounding, as well as inflammatory and tumorigenic agents. This protein has been found in both intracellular compartments and extracellular spaces, and its function may depend in part on its location. Extracellular MT is able to redistribute heavy metals between tissues, act as a powerful antioxidant, affect cell proliferation, and cause the suppression of T-dependent humoral immunity. The nature of the interaction of MT with the plasma cell membrane has yet to be characterized, despite many observations that there is a significant pool of extracellular MT, and that this extracellular MT will bind to leukocyte plasma membranes. In light of studies that MT can be detected on the surface of leukocytes from animals immunized in the presence of adjuvant, and that an MT specific receptor has been found on the surface of astrocytes, we have investigated the nature of the potential MT-specific surface receptor-binding site(s) on the plasma membrane of leukocytes. The identification of MT-receptors will allow for the characterization of the mechanism MT uses for immunomodulation, for the manipulation of MT in its immunomodulatory role, and for the identification of patients at higher risk for those potentially harmful immunomodulatory effects.

The Molecular Characterization of a Predicted Glycosyltransferase from Lycopersicon esculentum

The synthesis of the plant cell wall is very complex, and understanding how this process occurs will lead to many benefits for future research and industries dependent upon cell walls for their products. The recent discovery of the functions of AtMUR3 and AtGT18 in Arabidopsis thaliana as xyloglucan galactosyltransferases has led to the identification of many more putative glycosyltransferases in the Arabidopsis genome. Due to the structural differences between the xyloglucans of Arabidopsis and solanaceous plants, we decided to search for putative arabinosyltransferases in the Solanaceae. Solanaceous xyloglucan is substituted by one to two arabinosyl residues at the second xylose position, and sometimes contains an arabinose at the first xylose position. In contrast, Arabidopsis xyloglucan does not contain arabinose, and is substituted by galactose at the second and third xylose position. Furthermore, the second galactose residue in Arabidopsis xyloglucan is usually fucosylated, a modification not found in solanaceous plants. Searching the database of expressed sequence tags (dbEST), we identified many likely glycosyltransferases in solanaceous plants, including tomato (Lycopersicon esculentum). AtMUR3 and AtGT18 search queries resulted in the identification of three putative glycosyltransferases in L. esculentum, which were tentatively designated LeGT1, Le1GT18, and Le2GT18. Based on phylogenetic considerations, Le2GT18 was thought to be a putative arabinosyltransferase. The gene was transformed into atmur3-3 and atgt18 mutant plants, and the resulting plants will be screened for homozygous plants with the inserted gene. The homozygous T2 plants can then be screened for changes in the composition of their cell walls. Because Le2GT18 is thought to be an arabinosyltransferase, the levels of arabinose may be increased in the xyloglucan fraction of the cell wall. If so, further testing can be performed to reveal the true function of Le2GT18.