Healthcare-Related Financial Burden Among Families in the U.S.: The Role of Childhood Activity Limitations and Income

This study examined the impact of childhood activity limitations on family financial burden in the U.S. We used ten complete panels (1996–2006) of the Medical Expenditure Panel Survey (MEPS) to evaluate the burden of out-of-pocket healthcare expenditures for 17,857 families with children aged 0–17 years. Multivariate generalized linear models were used to examine the relationship between childhood activity limitation status and both absolute and relative financial burden. Families of children with limitations had higher absolute out-of-pocket healthcare expenditures than families of children without limitations ($594.36 higher; p < 0.05), and were 54% more likely to experience relative burden (p < 0.05). Substantial socioeconomic disparities in financial burden were observed. Policies are needed to enable these families to access appropriate and affordable healthcare services.     

Parameter estimation in a highly non-linear model using simultaneous perturbation stochastic approximation

Often it is necessary to estimate the parameters of a model or unknown system. Various techniques exist to accomplish this task, including Kalman and Wiener filtering, least-mean-square (LMS) algorithms, and the Levenberg-Marquardt(L-M) algorithm. These techniques require an analytic form of the gradient of the function of the parameters to be estimated. A key feature of the simultaneous perturbation stochastic approximation (SPSA) method is that it is a gradient-free optimization technique (Spall; 1992,1998a,b, 1999). In the current problem, the function of parameters to be identified is highly non-linear and of sufficient difficulty that obtaining an analytic form of the gradient is impractical. Therefore, in this paper the

performance of the SPSA algorithm will be examined in terms of parameter selection, data requirements, and convergence performance on this non-linear problem. Results will be reported on both a first-order "standard" implementation of SPSA and on a second-order version of SPSA that tends to enhance convergence.     

Economic development and fertility change in Mexico, 1950–1970

This paper is an attempt to isolate the determinants of fertility in Mexico. Of the variables included, two are significant in accounting for differences in the level of completed fertility in the 32 "states" in 1970. They are the share of the labor force in agriculture, which is directly related to fertility, and the percentage of the population speaking an indigenous language, which shows an inverse relationship.The most important factors acting to reduce total fertility rates over time are increases in life expectancy and declines in the share of the labor force in agriculture. However, based on the estimated linear relationship, these two variables by themselves are not adequate to achieve a rapid decline in fertility in the future.     

Action learning and control theory

The essay is a kind of ‘product mix’ of two separate concepts, manifestly quite different but found ultimately to blend into a common message. The author found management literature over the past two decades somewhat difficult to assimilate, due perhaps to an engineering training where problems are always simplified into tangible models and laws. Control theory (or cybernetics), however, seemed to offer a way out of the difficulty, especially as psychologists were using control theory to take them beyond the range of the ‘conditioned reflex’, and the author was encouraged to try out cybernetic ideas in terms of human problems in management and industry. The development of ‘action learning’ as a pragmatic yet sophisticated technique has provided a challenge for the cybernetic model. It is thought that many readers, particularly those with an engineering or scientific background, might find this exposition in social cybernetics helpful in getting a comprehensive grasp of action learning.     

Generalized Method of Moments With Many Weak Moment Conditions

Using many moment conditions can improve efficiency but makes the usual generalized method of moments (GMM) inferences inaccurate. Two‐step GMM is biased. Generalized empirical likelihood (GEL) has smaller bias, but the usual standard errors are too small in instrumental variable settings. In this paper we give a new variance estimator for GEL that addresses this problem. It is consistent under the usual asymptotics and, under many weak moment asymptotics, is larger than usual and is consistent. We also show that the Kleibergen (2005) Lagrange multiplier and conditional likelihood ratio statistics are valid under many weak moments. In addition, we introduce a jackknife GMM estimator, but find that GEL is asymptotically more efficient under many weak moments. In Monte Carlo examples we find that t‐statistics based on the new variance estimator have nearly correct size in a wide range of cases.     

A new approach to assessing ethical conduct in scientific work

The intent of the current article is to describe the development of a new approach to the study of ethical conduct in scientific research settings. The approach presented in this article has two main components. The first component entails the development of a taxonomy of ethical events as they occur across a broad range of scientific disciplines. The second involves the identification of proximate criteria that will allow systematic and objective evaluation of ethical behaviors through low-fidelity performance simulations. Two proposed measures based on the new approach are intended to identify and measure variations in the scientific environment that might predispose certain individuals to make unethical decisions.     

Individual Heterogeneity and Average Welfare

Individual heterogeneity is an important source of variation in demand. Allowing for general heterogeneity is needed for correct welfare comparisons. We consider general heterogeneous demand where preferences and linear budget sets are statistically independent. Only the marginal distribution of demand for each price and income is identified from cross‐section data where only one price and income is observed for each individual. Thus, objects that depend on varying price and/or income for an individual are not generally identified, including average exact consumer surplus. We use bounds on income effects to derive relatively simple bounds on the average surplus, including for discrete/continuous choice. We also sketch an approach to bounding surplus that does not use income effect bounds. We apply the results to gasoline demand. We find tight bounds for average surplus in this application, but wider bounds for average deadweight loss.     

Cross-National Variation in Violent Crime Rates: Race, r-K Theory, and Income

Rushton's theory of r-K race differences was examined in relation to the rate of murder, rape, and serious assault per 100,000 population and Gross Domestic Product per Person for 74 countries from the 1993–1996 International Crime Statistics published by INTERPOL and the 1999 CIA World Fact Book. Each country was assigned to one of the three macro-races East Asian, European, and African. The results corroborated earlier findings that violent crime is lowest in East Asian countries, intermediate in European countries, and highest in African and in Black Caribbean countries. The median number of violent crimes per 100,000 population were: 7 East Asian countries—34; 45 European countries—42; and 22 African and Black Caribbean countries—149, respectively. The median Gross Domestic Product per Person was highest in East Asian countries ($12,600), intermediate in European countries ($7,400), and lowest in African and Black Caribbean countries ($1,900). Across the three population groups there was an ecological correlation of –.96 between crime and wealth (wealthier countries had less crime). Finer-grained analyses, however, found that while wealth was negatively related to crime across European or East Asian countries, it was positively related to crime for the African and Black Caribbean countries (i.e., the wealthier an African or Black Caribbean country, the greater its rate of violent crime). Future research needs to examine genetic factors in addition to cultural factors as well as their interactions.     

Average and Quantile Effects in Nonseparable Panel Models

Nonseparable panel models are important in a variety of economic settings, including discrete choice. This paper gives identification and estimation results for nonseparable models under time‐homogeneity conditions that are like “time is randomly assigned” or “time is an instrument.” Partial‐identification results for average and quantile effects are given for discrete regressors, under static or dynamic conditions, in fully nonparametric and in semiparametric models, with time effects. It is shown that the usual, linear, fixed‐effects estimator is not a consistent estimator of the identified average effect, and a consistent estimator is given. A simple estimator of identified quantile treatment effects is given, providing a solution to the important problem of estimating quantile treatment effects from panel data. Bounds for overall effects in static and dynamic models are given. The dynamic bounds provide a partial‐identification solution to the important problem of estimating the effect of state dependence in the presence of unobserved heterogeneity. The impact of T, the number of time periods, is shown by deriving shrinkage rates for the identified set as T grows. We also consider semiparametric, discrete‐choice models and find that semiparametric panel bounds can be much tighter than nonparametric bounds. Computationally convenient methods for semiparametric models are presented. We propose a novel inference method that applies in panel data and other settings and show that it produces uniformly valid confidence regions in large samples. We give empirical illustrations.