Modeling Usage of Medical Care Services: The Medical Expenditure Panel Survey Data, 1996-2000

We explore the determinants of usage of six different types of health careservices, using the Medical Expenditure Panel Survey data, years 1996-2000.We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models.We find that the complexity of the model that is required to fit the datawell depends upon the way in which the data is pooled across sexes andover time, and upon the characteristics of the usage measure.Pooling across time and sexes is almost always favored, but when more heterogeneous data is pooled it is often the case that a more complex statisticalmodel is required.medical care; count data; maximum likelihood

The black-white test score gap widens with age?

Abstract We re-examine the theoretical concept of a production function for cognitive achievement, and argue that an indirect production function that depends upon the variables that constrain parents' choices is both more tractable from an econometric point of view, and more interesting from an economic point of view than is a direct production function that depends upon a detailed list of direct inputs such as number of books in the household. We estimate flexible econometric models of indirect production functions for two achievement measures from the Woodcock-Johnson Revised battery, using data from two waves of the Child Development Supplement to the PSID. Elasticities of achievement measures with respect to family income and parents' educational levels are positive and significant. Gaps between scores of black and white children narrow or remain constant as children grow older, a result that differs from previous findings in the literature. The elasticities of achievement scores with respect to family income are substantially higher for children of black families, and there are some notable difference in elasticities with respect to parents' educational levels across blacks and whites.education; cognitive achievement; test score gaps

Modeling Usage of Medical Care Services: The Medical Expenditure Panel Survey Data, 1996-2000

We explore the determinants of usage of six different types of health careservices, using the Medical Expenditure Panel Survey data, years 1996-2000.We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models.We find that the complexity of the model that is required to fit the datawell depends upon the way in which the data is pooled across sexes andover time, and upon the characteristics of the usage measure.Pooling across time and sexes is almost always favored, but when more heterogeneous data is pooled it is often the case that a more complex statisticalmodel is required.This research was supported by grants SEC 2003-05112 and SGR 2001-016

Likelihood-Based Approaches to Modeling Demand for Medical Care

We review recent likelihood-based approaches to modeling demand for medical care. A semi-nonparametric model along the lines of Cameron and Johansson's Poisson polynomial model, but using a negative binomial baseline model, is introduced. We apply these models, as well a semiparametric Poisson, hurdle semiparametric Poisson, and finite mixtures of negative binomial models to six measures of health care usage taken from the Medical Expenditure Panel survey. We conclude that most of the models lead to statistically similar results, both in terms of information criteria and conditional and unconditional prediction. This suggests that applied researchers may not need to be overly concerned with the choice of which of these models they use to analyze data on health care demand.Health care demand, count data, maximum likelihood

On the production of cognitive achievement and gaps in test scores

We investigate the accumulation of cognitive achievement using an indirect production function, estimated using a flexible, dynamic econometric model and a new, rich data set. Gaps between black and white children remain constant, narrow, or disappear entirely as children grow older, depending upon the achievement measure and the family structure. Income elasticities are substantially higher for children of black families, and there are some notable differences in elasticities with respect to parents' educational levels. Within racial groups, the effects of fathers' and mothers' educational levels are different. Between children of stable two-parent families and children of mother-only families, a gap exists that is at least as important as the racial gap

The black-white test score gap widens with age?

We re-examine the theoretical concept of a production function for cognitive achievement, and argue that an indirect production function that depends upon the variables that constrain parents' choices is both moretractable from an econometric point of view, and more interesting from an economic point of view than is a direct production function that depends upon a detailed list of direct inputs such as number of books in the household. We estimate flexible econometric models of indirect production functions for two achievement measures from the Woodcock-Johnson Revised battery, using data from two waves of the Child Development Supplement to the PSID. Elasticities of achievement measures with respect to family income and parents' educational levels are positive and significant. Gaps between scores of black and white children narrow or remain constant as children grow older, a result that differs from previous findings in the literature. The elasticities of achievement scores with respect to family income are substantially higher for children of black families, and there are some notable difference in elasticities with respect to parents' educational levels across blacks and whites

Modeling usage of medical care services : the medical expenditure panel survey data, 1996-2000

We explore the determinants of usage of six different types of health care services, using the Medical Expenditure Panel Survey data, years 1996-2000. We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models. We find that the complexity of the model that is required to fit the data well depends upon the way in which the data is pooled across sexes and over time, and upon the characteristics of the usage measure. Pooling across time and sexes is almost always favored, but when more heterogeneous data is pooled it is often the case that a more complex statistical model is required

Modelling usage of medical care services: the medical expenditure panel survey data, 1996-2000

We explore the determinants of usage of six different types of health care services, using the Medical Expenditure Panel Survey (MEPS) data, years 1996-2000. We apply a number of models for univariate count data, including semiparametric, semi-nonparametric and finite mixture models. We find that the complexity of the model that is required to fit the data well depends upon the way in which the data is pooled across sexes and over time, and upon the characteristics of the usage measure. Pooling across time and sexes is almost always favoured, but when more heterogeneous data is pooled it is often the case that a more complex statistical model is required.

Ampollas de facil ruptura : contaminación por partículas en relación a su apertura

Tesi de Llicenciatura per a la obtenció del Grau de Farmàcia. Facultat de Farmàcia. Universitat de Barcelona. Director: Suñé i Negre, Josep M. (Josep Maria). 1988

Likelihood-Based Approaches to Modeling Demand for Medical Care

We review recent likelihood-based approaches to modeling demand for medical care. A semi-nonparametric model along the lines of Cameron and Johansson's Poisson polynomial model, but using a negative binomial baseline model, is introduced. We apply these models, as well a semiparametric Poisson, hurdle semiparametric Poisson, and finite mixtures of negative binomial models to six measures of health care usage taken from the Medical Expenditure Panel survey. We conclude that most of the models lead to statistically similar results, both in terms of information criteria and conditional and unconditional prediction. This suggests that applied researchers may not need to be overly concerned with the choice of which of these models they use to analyze data on health care demand