1000 resultados para digitalcommons@uconn
Resumo:
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.
Resumo:
Insulin resistance is a newly recognized problem in horses that may have been around a long time. You may be wondering what it is all about and how your horse may/may not be affected. It is probably not as common a problem as it may seem. This article will discuss insulin resistance including its causes, effects, diagnosis, treatment and prevention.
Resumo:
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.
Resumo:
The Connecticut Poison Control Center (CPCC) at the University of Connecticut Health Center (UCHC) was established in 1957 under Connecticut General Statute 10a- 132. The CPCC’s main responsibility is to provide 24-hour emergency toxicology management consultations for victims of poisoning, and serve as a source for pharmacology and toxicology-related information. The center monitors the epidemiology of human poisoning and provides surveillance for environmental and occupational chemical exposures, drug abuse, and pharmaceutical interactions and adverse effects. The CPCC performs toxicological research, and provides formal toxicology instruction for allied health professionals, as well as professional and consumer poison prevention education. The CPCC is one of 63 nationwide centers certified by the American Association of Poison Control Centers (AAPCC), and the only poison center in the state of Connecticut. The AAPCC establishes standards of care for poisoning and administers the Toxic Exposure Surveillance System (TESS), a national database of poisoning statistics, to which the CPCC is a contributor.