Fertility Determinants and Economic Uncertainty: An Assessment Using European Panel Data

This study examined the determinants of fertility, using panel data for 27 European countries. We employed panel co-integration to estimate fertility as function of demographic and economic variables. We showed that low fertility in most industrialized countries in Europe is due to low infant mortality rates, high female employment, low nuptiality rate, and high opportunity cost of having children. Using two measures of economic uncertainty, which are associated with labor market decisions—a production (an output) volatility measure and the unemployment rate—we examined to what extent economic insecurities affect fertility decisions. The empirical results showed that both measures of economic uncertainty have a significant negative impact on fertility implying that labor market insecurities might be a significant factor affecting fertility decisions.     

Model Uncertainty and Model Averaging in the Estimation of Infectious Doses for Microbial Pathogens

Food‐borne infection is caused by intake of foods or beverages contaminated with microbial pathogens. Dose‐response modeling is used to estimate exposure levels of pathogens associated with specific risks of infection or illness. When a single dose‐response model is used and confidence limits on infectious doses are calculated, only data uncertainty is captured. We propose a method to estimate the lower confidence limit on an infectious dose by including model uncertainty and separating it from data uncertainty. The infectious dose is estimated by a weighted average of effective dose estimates from a set of dose‐response models via a Kullback information criterion. The confidence interval for the infectious dose is constructed by the delta method, where data uncertainty is addressed by a bootstrap method. To evaluate the actual coverage probabilities of the lower confidence limit, a Monte Carlo simulation study is conducted under sublinear, linear, and superlinear dose‐response shapes that can be commonly found in real data sets. Our model‐averaging method achieves coverage close to nominal in almost all cases, thus providing a useful and efficient tool for accurate calculation of lower confidence limits on infectious doses.     

A Systems Approach to the Policy‐Level Risk Assessment of Exotic Animal Diseases: Network Model and Application to Classical Swine Fever

Exotic animal diseases (EADs) are characterized by their capacity to spread global distances, causing impacts on animal health and welfare with significant economic consequences. We offer a critique of current import risk analysis approaches employed in the EAD field, focusing on their capacity to assess complex systems at a policy level. To address the shortcomings identified, we propose a novel method providing a systematic analysis of the likelihood of a disease incursion, developed by reference to the multibarrier system employed for the United Kingdom. We apply the network model to a policy‐level risk assessment of classical swine fever (CSF), a notifiable animal disease caused by the CSF virus. In doing so, we document and discuss a sequence of analyses that describe system vulnerabilities and reveal the critical control points (CCPs) for intervention, reducing the likelihood of U.K. pig herds being exposed to the CSF virus.     

The relative influence of country conditions, industry structure, and business strategy on multinational corporation subsidiary performance

Two competing theories of firm performance have been proposed in the business strategy literature, the industry structure view and the resource-based view of the firm. Empirical studies have estimated the relative contribution of industry structure, corporate, and business unit effects to business unit performance. These studies, however, have been restricted to using only single-country data. Missing from this debate is an international dimension that includes the relative importance of country conditions as a determinant of firm performance. The objective of this article is to fill this void by adding country characteristics to the analysis. Using cross-country data of four large multinationals in a single industry, we estimate the relative importance of country characteristics in addition to industry structure, corporate characteristics, and subsidiary strategy as determinants of subsidiary performance by using multiple regression analysis. This analysis also will contribute to the discussion on environmental determinism versus strategic choice. Country and industry characteristics are mainly outside the control of management, whereas corporate characteristics and subsidiary strategy are under management's control. Results show that country characteristics are by far the most important determinant of subsidiary performance, followed by industry structure, subsidiary strategy, and corporate characteristics. Thus, country conditions are a very important determinant of firm performance that so far has been overlooked in previous studies. These results indicate that subsidiary performance is determined mainly by conditions outside the control of subsidiary management. In terms of competing theories, these results support the environmental determinism view more than the strategic choice view and the resource-based view of the firm more than the industry structure view. These results also have important implications for multinational corporations' selection of countries for entry and investment and for performance evaluation of subsidiary management.     

An Empirical Approach for Deriving Information on Total Duration of Exposure from Information on Historical Exposure

Exposure duration is an important component in determining long-term dose rates associated with exposure to environmental contaminants. Surveys of exposed populations collect information on individuals' past behaviors, including the durations of a behavior up to the time of the survey. This paper presents an empirical approach for determining the distribution of total durations that is consistent with the distribution past durations obtained from surveys. This approach is appropriate where the rates of beginning and ending a behavior are relatively constant over time. The approach allows the incorporation of information on the distribution of age in a population into the determination of the distribution of durations. The paper also explores the impact of longevity bias on survey data. A case study of the application of this approach to two angler populations is also provided. The results of the case study have characteristics similar to the results reported by Israeli and Nelson ( Risk Anal. 12, 65-72 (1992)) from their analytical model of residential duration. Specifically, the average period of time for the total duration in the entire population is shorter than the average period of time reported for historical duration in the surveyed individuals.     

The BLUE's covariance matrix revisited: A review

In this paper we comment on and review some unexpected but interesting features of the BLUE (best linear unbiased estimator) of the expectation vector in the general linear model and in particular, the BLUE's covariance matrix. Most of these features appear in the literature but are rather scattered or hidden.     

Experimental designs when there are one or more factor constraints

In response surface methodology, designs of orders one or two are often needed such that some or all the factor levels satisfy one or more linear constraints. A method is discussed for obtaining such designs by projection of a standard design onto the constraint hyperplane. It is shown that a projected design obtained from a rotatable design is also rotatable, and for a rotatable design that is also orthogonal (in particular any orthogonal first-order design) a least squares analysis carried out on the generating design supplies a least squares solution for the constrained design subject to the constraints. Some useful properties of the generating design, such as orthogonal blocking and fractionation are retained in the projected design. Some second-order mixture designs generated by two-level factorials are discussed.     

A New Proof of Murthy's Estimator which Applies to Sequential Sampling

Murthy's estimator has been used for constructing an unbiased estimator of a population total or mean from a sample of fixed size when there is unequal probability sampling without replacement. Traditionally, the estimator is derived by constructing an unordered version of Raj's ordered unbiased estimator. This paper presents an elementary proof of Murthy's estimator which applies the Rao–Blackwell theorem to a very simple estimator. This proof includes any sequential sampling scheme, thus extending the usefulness of Murthy's estimator. We demonstrate this extension by deriving unbiased estimators for inverse sampling.     

Choice Bracketing

When making many choices, a person can broadly bracket them by assessing the consequences of all of them taken together, or narrowly bracket them by making each choice in isolation. We integrate research conducted in a wide range of decision contexts which shows that choice bracketing is an important determinant of behavior. Because broad bracketing allows people to take into account all the consequences of their actions, it generally leads to choices that yield higher utility. The evidence that we review, however, shows that people often fail to bracket broadly when it would be feasible for them to do so. In addition to documenting the diverse effects of bracketing, we also discuss factors that determine whether people bracket narrowly or broadly. We conclude with a discussion of normative aspects of bracketing and argue that there are some situations in which narrower bracketing results in superior decision making.