Almost Consistent Estimation of Panel Probit Models with “Small” Fixed Effects

We propose four different GMM estimators that allow almost consistent estimation of the structural parameters of panel probit models with fixed effects for the case of small Tand large N. The moments used are derived for each period from a first order approximation of the mean of the dependent variable conditional on explanatory variables and on the fixed effect. The estimators differ w.r.t. the choice of instruments and whether they use trimming to reduce the bias or not. In a Monte Carlo study, we compare these estimators with pooled probit and conditional logit estimators for different data generating processes. The results show that the proposed estimators outperform these competitors in several situations.     

B股与H股及红筹股之间的溢出效应与信息流动

运用向量GARCH-M模型检验了B股与H股及红筹股之间的溢出效应与信息流动.实证结果表明:红筹股对沪深市B股、H股对沪市B股的收益和波动溢出效应均显著存在,而反向的溢出效应均不显著,表明信息是从红筹股向沪深市B股、从H股向沪市B股单向流动的;深市B股与H股之间相互的收益溢出效应均存在,而波动溢出效应均不存在,信息在H股和深市B股之间的流动情况不明显;在信息流动过程中,红筹股始终处于信息领先地位.     

Evaluating a private foundation's health program

Public policy decisions in health are increasingly difficult and expensive. Although there will never be enough information available, private foundations can help to bridge the most important gaps in knowledge. Larger foundations may also wish to respond to those who doubt the value of foundation activities. This article reviews the experiences over the past eight years of The Robert Wood Johnson Foundation in employing evaluation and related social research procedures in the planning and implementation of a major philanthropic effort to improve the health and medical care of Americans. Discussed are the still evolving Foundation evaluation framework, the unanticipated problems in undertaking specific evaluations, and the substantive findings of some of the studies.     

Using In Vitro High‐Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high‐throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline‐based meta‐regression can be used to integrate data across multiple assay replicates to generate a concentration–response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk‐specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta‐regression, may allow risk assessors to identify points of departure and risk‐specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.     

Majority size and conformity behavior in charitable giving: Field evidence from a donation-based crowdfunding platform in Japan

A charitable donor typically imitates the majority contribution of other donors. This study examines the relationships between majority size and this so-called donor’s conformity behavior, by empirically investigating the impacts of multiple earlier donations on the donation of a subsequent donor to JapanGiving, a donation-based crowdfunding platform in Japan. This analysis is possible because the platform’s webpage displays the previous donation amounts in chronological order, thus allowing us to examine the modal amount of more recent donations. By using data on 9989 actual donations, our dynamic panel analysis suggests that when the number of most recent continuous modal donations increases, the likelihood that a subsequent donor matches the modal amount increases. This result supports the notion that a donor’s conformity behavior is more likely to occur when a greater proportion of other donors give a similar amount. Furthermore, the effects of continuous modal donations are strongly observed for low monetary ranges. We interpret that initiating further cooperation among a large number of less cooperative other donors would become harder, or individuals would obtain an excuse for less cooperation due to the others’ behaviors. Finally, we discuss how our findings connect economic studies of charity and social psychology studies of conformity and could help improve the effectiveness of fundraising by charities.     

Deriving Behavior Model Parameters from Survey Data: Self‐Protective Behavior Adoption During the 2009–2010 Influenza A(H1N1) Pandemic

In this paper, we demonstrate how public opinion surveys can be designed to collect information pertinent to computational behavior modeling, and we present the results of a public opinion and behavior survey conducted during the 2009–2010 H1N1 influenza pandemic. The results are used to parameterize the Health Belief Model of individual health‐protective decision making. Survey subjects were asked questions about their perceptions of the then‐circulating influenza and attitudes towards two personal protective behaviors: vaccination and avoidance of crowds. We empirically address two important issues in applying the Health Belief Model of behavior to computational infectious disease simulation: (1) the factors dynamically influencing the states of the Health Belief Model variables and (2) the appropriateness of the Health Belief Model in describing self‐protective behavior in the context of pandemic influenza.     

Lawrence R. Klein 1920–2013: Notes on the early years

Klein can well be said to have created the field of macroeconometric modeling almost singlehandedly. His international influence started at an early stage. The article offers scattered archive observations on Klein's early years from undergraduate study to the University of Pennsylvania in 1958. Klein was in 1944 recruited by the Cowles Commission in Chicago to construct the first macroeconomic model in the USA, drawing on the experiences of the interwar modeling work of Jan Tinbergen and the new path-breaking econometric methods developed by Trygve Haavelmo. The first Klein model was taken into use at the end of 1945 to shed light on the prospects for the US economy in the transition from war to peace. After two-three years in Chicago Chicago, Klein traveled for a year in Europe and initiated macroeconometric modeling work in Canada, at the University of Michigan, and at Oxford University. This was only the beginning of the lifelong influence exerted on modelers around the globe. The article pays attention to Klein's relation to Paul Samuelson, Jacob Marschak, Trygve Haavelmo, Ragnar Frisch, and others.     

Towards expenditure rules and fiscal sanity in the euro area

The study demonstrates the key role of expenditure policies in explaining fiscal developments during EMU in the euro area, its three largest members and four “macro-imbalances” countries. It compares actual primary expenditure trends with those that would have prevailed if countries had followed neutral policies based on expenditure rules since the start of EMU. Moreover, the implications for debt trends are calculated. Results show that all sample countries except Germany applied expansionary expenditure policies already before the crisis. Consequently, expenditure and debt paths were much higher compared to a counterfactual neutral expenditure stance. Rule-based expenditure policies could have led to much safer fiscal positions much more in line with the EU's Stability and Growth Pact. An empirical analysis of the determinants of countries’ expenditure stance confirms the need for stronger fiscal rules and institutions in the euro area.     

MANAGED COMPETITION IN HEALTH INSURANCE

Rising healthcare costs have sparked debate about the best way to provide high‐quality affordable health insurance. We discuss the potential for regulated insurance markets to outperform single‐payer public insurance. We use as an example the private Medicare plans that now provide insurance to almost a third of seniors in the United States. The evidence suggests that private plans can limit costs and potentially appeal to enrollees, and that well‐designed risk adjustment can mitigate market failures due to adverse selection. However, fostering competition between insurers, especially in smaller markets, is difficult. We discuss how future research might illuminate the relative advantages of public and private health insurance.