Health and economic development—evidence from the introduction of public health care

This paper investigates the causal effect of improvements in health on economic development using a long panel of European countries. Identification is based on the particular timing of the introduction of public health care systems in different countries, which is the random outcome of a political process. We document that the introduction of public health care systems had a significant immediate effect on health dynamics proxied by infant mortality and crude death rates. The findings suggest that health improvements had a positive effect on growth in income per capita and aggregate income.     

Why Reduced-Form Regression Models of Health Effects Versus Exposures Should Not Replace QRA: Livestock Production and Infant Mortality as an Example

Do pollution emissions from livestock operations increase infant mortality rate (IMR)? A recent regression analysis of changes in IMR against changes in aggregate “animal units” (a weighted sum of cattle, pig, and poultry numbers) over time, for counties throughout the United States, suggested the provocative conclusion that they do: “[A] doubling of production leads to a 7.4% increase in infant mortality.” Yet, we find that regressing IMR changes against changes in specific components of “animal units” (cattle, pigs, and broilers) at the state level reveals statistically significant negative associations between changes in livestock production (especially, cattle production) and changes in IMR. We conclude that statistical associations between livestock variables and IMR variables are very sensitive to modeling choices (e.g., selection of explanatory variables, and use of specific animal types vs. aggregate “animal units). Such associations, whether positive or negative, do not warrant causal interpretation. We suggest that standard methods of quantitative risk assessment (QRA), including emissions release (source) models, fate and transport modeling, exposure assessment, and dose-response modeling, really are important—and indeed, perhaps, essential—for drawing valid causal inferences about health effects of exposures to guide sound, well-informed public health risk management policy. Reduced-form regression models, which skip most or all of these steps, can only quantify statistical associations (which may be due to model specification, variable selection, residual confounding, or other noncausal factors). Sound risk management requires the extra work needed to identify and model valid causal relations.     

Game Theory and Risk Analysis

Risk analysts often analyze adversarial risks from terrorists or other intelligent attackers without mentioning game theory. Why? One reason is that many adversarial situations—those that can be represented as attacker‐defender games, in which the defender first chooses an allocation of defensive resources to protect potential targets, and the attacker, knowing what the defender has done, then decides which targets to attack—can be modeled and analyzed successfully without using most of the concepts and terminology of game theory. However, risk analysis and game theory are also deeply complementary. Game‐theoretic analyses of conflicts require modeling the probable consequences of each choice of strategies by the players and assessing the expected utilities of these probable consequences. Decision and risk analysis methods are well suited to accomplish these tasks. Conversely, game‐theoretic formulations of attack‐defense conflicts (and other adversarial risks) can greatly improve upon some current risk analyses that attempt to model attacker decisions as random variables or uncertain attributes of targets (“threats”) and that seek to elicit their values from the defender's own experts. Game theory models that clarify the nature of the interacting decisions made by attackers and defenders and that distinguish clearly between strategic choices (decision nodes in a game tree) and random variables (chance nodes, not controlled by either attacker or defender) can produce more sensible and effective risk management recommendations for allocating defensive resources than current risk scoring models. Thus, risk analysis and game theory are (or should be) mutually reinforcing.     

Unity is strength: staff college and the British officer corps

Utilizing Bourdieu's concept of the habitus, Keith Macdonald has recently examined the elite social origins of the British officer corps. His analysis is valid as far at it goes but it ignores the professional practices of British officers. This article examines Britain's Joint Services Command and Staff College to assess the unification of the three services around common forms of military practice. It argues that while the new staff college has been effective in disseminating new forms of professional expertise among British officers, various practices have been institutionalized which actively undermine the unity of the officer corps.     

Information systems outsourcing projects as a double moral hazard problem

In the past two decades many organizations have turned to other organizations to satisfy their information systems needs. Information systems outsourcing arrangements cover the spectrum from agreements involving the delivery of all information services to those providing specific services such as systems development, communications management, desktop computing provision and maintenance, and so on.In this paper we model information systems outsourcing arrangements as a non-cooperative game with two players: a company and an outsourcing vendor. The game between the two players has an inherent double moral hazard problem as the success of the information system outsourcing project depends on the actions of both players, which are costly for them and are not directly contractible. Both parties make their decisions taking into account the effects that these decisions have on the other player's actions. In our analysis, we compare the solution obtained without a moral hazard problem (the first-best solution) to the one obtained under a double moral hazard setting (the second-best solution). We demonstrate some results based on the assumption that increases in the productivity of the vendor lead to increases in the productivity of the company. Further we establish that outsourcing contracts should provide no separate payment for failure to the outsourcing vendor although effectively many of them do. We also provide a sharing rule for providing appropriate incentives for the vendor and examine the dynamics associated with this sharing rule. Finally, we further provide for the characterization of response functions and the ensuing Nash solution including the optimal outsourcing fee. This allows for the nuanced consideration of the degree of interaction between the effort of one party and the productivity of the effort of the other party. This particular interaction has not been explored formally in the extant research literature.     

Intellectual ability and reactions to pornography

Two studies examined the relation between intelligence and men's sexual attitudes and interpersonal behavior with a woman after viewing pornography. Undergraduate men were assessed for IQ, viewed one of several films, then were assessed on various dependent measures, including interpersonal behavior with a female confederate. Lower IQ men were more sexually suggestive to the woman after viewing a sexually violent film than after viewing an nonviolent erotic film; higher IQ men did not differ in suggestiveness as a function of sexual film condition. In Study 2, lower IQ men were also physically closer to the woman after viewing a violent sexual film than after viewing a nonviolent erotic film; higher IQ men were less variable in proximity as a function of film condition. Results are discussed in relation to research suggesting that intelligence moderates influenceability, and to sex education programs that help individuals critically evaluate antisocial content in the sexual media.     

Stability of Approximations of Average Run Length of Risk-Adjusted CUSUM Schemes Using the Markov Approach: Comparing Two Methods of Calculating Transition Probabilities

Risk-adjusted CUSUM schemes are designed to monitor the number of adverse outcomes following a medical procedure. An approximation of the average run length (ARL), which is the usual performance measure for a risk-adjusted CUSUM, may be found using its Markov property. We compare two methods of computing transition probability matrices where the risk model classifies patient populations into discrete, finite levels of risk. For the first method, a process of scaling and rounding off concentrates probability in the center of the Markov states, which are non overlapping sub-intervals of the CUSUM decision interval, and, for the second, a smoothing process spreads probability uniformly across the Markov states. Examples of risk-adjusted CUSUM schemes are used to show, if rounding is used to calculate transition probabilities, the values of ARLs estimated using the Markov property vary erratically as the number of Markov states vary and, on occasion, fail to converge for mesh sizes up to 3,000. On the other hand, if smoothing is used, the approximate ARL values remain stable as the number of Markov states vary. The smoothing technique gave good estimates of the ARL where there were less than 1,000 Markov states.     

Robust and diagnostic regression analyses

Graphical methods of diagnostic regression analysis are applied to three examples in which least squares and robust regression analyses give substantially different results. The diagnostic tools lead to the identification of data deficiencies and model inadequacies. The analyses serve as a reminder that robust regressions depend upon the linear model and upon the scale in whicli the response is analysed. The robust analysis may also be sensitive to gross errors in one or more explanatory variables