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The design of new hospital inpatient rooms is moving towards private (single occupancy) rooms. These rooms are generally preferred by patients and they may improve patient care, but they are more expensive to build and to staff than semi-private rooms. The question of their societal worth is important because hospitals are expensive, long-term investments and, once built, are prohibitively expensive to change. This paper presents a benefit-cost analysis of private rooms versus semi-private rooms in a proposed new hospital. We estimate that the net social benefit of a bed in a private room is about $70,000 more than a bed in a semi-private room.
This article reviews the rationale for and various approaches used by economists to incorporate distributional consequences of projects or policies into benefit-cost analyses. Approaches reviewed include distributional weights and metrics based on the Lorenz curve. Analysis of distributional issues in partial equilibrium and general equilibrium settings are briefly reviewed. We present an empirical demonstration of how the contingent valuation method (CVM) and hedonic property methods (HPM) can be used to quantify how non-market environmental benefits are distributed by income and ethnicity. Using CVM, the distribution of non-market benefits can be cross-tabbed with respondent demographics, so that a variety of “distributions” of benefits by relevant demographic groups can be calculated. Using the HPM, the analyst can statistically test to see if the implicit price gradient varies with differences in income and ethnicity. In our empirical example, we find that ethnicity and income interaction terms on the implicit price gradient are statistically significant suggesting differential effects of National Forest fire suppression policies on Hispanics and low income households.
State-owned enterprises (SOEs) retain a strong presence in many economies around the world. How do governments manage these firms given their dual economic and political nature? Many states use authority over executive appointments as a key means of governing SOEs. We analyze the nature of this “personnel power” by assessing patterns in SOE leaders’ political mobility in China, the country with the largest state-owned sector. Using logit and multinomial models on an original dataset of central SOE leaders’ attributes and company information from 2003 to 2017, we measure the effects of economic performance and political connectedness on leaders’ likelihood of staying in power. We find that leaders of well-performing firms and those with patronage ties to elites in charge of their evaluation are more likely to stay in office. These findings suggest that states can leverage personnel power in pursuit of economic and political stability when SOE management is highly politically integrated.
The federal Safe Drinking Water Act (SDWA), as amended in 1996, enables benefit-cost analysis (BCA) to be used in setting federal drinking water standards, known as MCLs. While BCAs are typically conceived of as a tool to inform efficiency considerations by helping to identify MCL options that maximize net social benefits, in this paper we also illustrate how important equity and affordability considerations can be brought to light by suitably applying BCAs to drinking water regulations, especially in the context of communities served by relatively small water systems. We examine the applicability and relevance of health-health analysis (HHA), and provide an empirical evaluation of the risk tradeoffs that may be associated with the MCL established for arsenic. We find that the cost-associated risks may offset a nontrivial portion of the cancer risk reduction benefits attributed to the MCL (e.g., the additional adverse health impacts from the costs may be roughly half as large as the number of cancer cases avoided). This reveals the relevance of using the HHA approach for examining net benefits of MCLs in small drinking water utilities, and raises issues related to whether and how these cost-associated health risks should be considered in BCAs for drinking water standards.
The income elasticity of the value per statistical life (VSL) is an important parameter for policy analysis. Mortality risk reductions often dominate the quantified benefits of environmental and other policies, and estimates of their value are frequently transferred across countries with significantly different income levels. U.S. regulatory agencies typically assume that a 1.0 percent change in real income over time will lead to a 0.4 to 0.6 percent change in the VSL. While elasticities within this range are supported by substantial research, they appear nonsensical if applied to populations with significantly smaller incomes. When transferring values between high and lower income countries, analysts often instead assume an elasticity of 1.0, but the resulting VSL estimates appear large in comparison to income. Elasticities greater than 1.0 are supported by research on the relationship between long-term economic growth and the VSL, by cross-country comparisons, and by new research that estimates the VSL by income quantile. Caution is needed when applying these higher elasticities, however, because the resulting VSLs appear smaller than expected future earnings or consumption in some cases, contrary to theory. In addition to indicating the need for more research, this comparison suggests that, in the interim, VSL estimates should be bounded below by estimates of future income or consumption.
A standard framework for business ethics views the inquiry as an application of major ethical theories to specific issues in business. As these theories are largely presented as being principled, the exercise therefore becomes one of applying general principles to business situations. Many adopting this standard approach have thus resisted the implementation of the most prominent development in ethical theory in recent history: that of particularism. In this article, I argue that particularist thinking has much to offer to business ethics and that standard resistance to particularist business ethics is based largely on misunderstandings. I do so by illustrating how the harbinger of particularism, W. D. Ross, countenances the practical wisdom of particularist ethics while being 1) invulnerable to standard objections to particularist business ethics and 2) compatible with the generalism of the standard approach. The Rossian business ethic is therefore one that the standard approach should be eager to include.
This paper deals with public investment in High-Speed Rail (HSR) infrastructure and tries to understand the economic rationale for allocating public money to the construction of new HSR lines. The examination of data on costs and demand shows that the case for investing in HSR requires several conditions to be met: an ex ante high volume of traffic in the corridor where the new lines are built, significant time savings, high average willingness of potential users to pay, the release of capacity in the conventional rail network and airports. On the contrary, net environmental benefits seem to be insignificant in influencing the social desirability of HSR investment. This paper discusses, within a cost-benefit analysis framework, under which conditions the expected benefits could justify the investment in HSR projects.
In the competition between American states for economic development, about half of American states offer lower levels of labor rights in the form of “right-to-work” (RTW) laws. RTW states often tout their advantages in competing for foreign investment, but do foreign companies really want weaker labor regulation? Many foreign firms locate production in the United States not to lower labor costs but for other reasons, such as proximity to consumers or to employ highly skilled workers, implying that differences across labor regulations within rich countries may be declining in importance. In this article, we investigate the relationship between RTW laws and greenfield foreign direct investments. In particular, we explore recent RTW changes across two states, Indiana and Michigan, controlling for national trends in foreign investment. Adopting RTW increases foreign investment in manufacturing in both states, but Michigan's RTW law is associated with gains in service-sector projects even while Indiana's is not. While RTW may attract more manufacturing, it is not enough to generate broad-based gains across the economy.
Although corporate social responsibility (CSR) has gone “mainstream,” the relationship between CSR and corporate political activities (CPA) has received little scholarly attention. This is problematic because firms potentially have a more sizable impact through their lobbying activities for socially and environmentally beneficial (or unbeneficial) public policies than through their own operations. This paper investigates if, and how, UN Global Compact signatory firms differ in their policy preferences on key EU proposals compared to other interest groups. To capture state-of-the-art data on firms’ policy preferences, I draw from the INTEREURO database, which includes firms’ lobbying positions on forty-three directives and twenty-seven regulations covering 112 public policy issues in the European Union. Statistical results show that Global Compact signatory firms significantly lobby for stricter regulation than non-signatory firms and industry associations, however, their positions are still lower than nonbusiness groups. These results are similar across various public policy issues and suggest that the regulatory preferences of firms’ participating in soft law CSR initiatives are more aligned with stakeholders' interests. This paper contributes to public policy literature exploring the relationship between hard and soft law as well as literature studying the political representation of divergent interest.
I can't breathe … a haunting phrase moaned at the intersection of past and present, serving as an audible supplement to the visual evidence to yet another collision of race and policing. This phrase reflects the current state of police-community relations in the United States. But, what lies on the other side of now? This Element examines this salient question in the context of excessive use of force and through the lenses of race, policing and public governance. We draw upon extant research and scholarship on representative bureaucracy, public engagement in the co-creation of public polices and the co-production of public services, and the emerging findings from studies in network science, coupled with insights from elite interviews, to offer implications for future research, the profession of policing, the public policymaking process, public management, and post-secondary institutions.
What distinguishes observed-score methods from other types of method described in this book is that they typically use raw scores1 to match examinees from the reference and focal groups. As a result, there is no need to fit a latent variable model such as an IRT model (the disadvantages of using latent variable models are that they often require large sample sizes to obtain accurate parameter estimates, and they require acceptable model fit to obtain valid DIF statistics [Bolt, 2002]). Another advantage of using observed-score methods is that many of the procedures provide an effect size measure in addition to a hypothesis test. Many of the effect sizes, in fact, have well-established benchmarks that test developers and researchers can use to classify an item as exhibiting negligible, moderate, and large DIF. Because of these advantages, observed-score methods are a popular approach for testing DIF.
IRT is a powerful scaling technique that provides a collection of latent variable models that describe performance at the item level relative to an examinee’s latent variable. IRT models have several attractive features that make them appealing for test developers and researchers to use to construct educational and psychological tests (Lord, 1980). The models can be applied to educational achievement tests such as TIMSS, as well as to psychological latent variables such as depression or anxiety measures. IRT is the driving force for the development and widespread use of computerized adaptive testing. The purpose of this chapter is to introduce IRT and its fundamental principles and applications so that the reader who is unfamiliar with IRT will have sufficient knowledge to apply the IRT DIF methods described in Chapter 4.
The concept underlying measurement invariance is often introduced using a metaphoric example via physical measurements such as length or weight (Millsap, 2011). Suppose I developed an instrument to estimate the perimeter of any object. My instrument is invariant if it produces the same estimate of the object’s perimeter, regardless of the object’s shape. For example, if my instrument provides the same estimate of the perimeter for a circle and a rectangle that have the same true perimeter, then it is invariant. However, if for a circle and a rectangle of the same true perimeter my measure systematically overestimates the perimeters of rectangles, then my measure is not invariant across objects. The object’s shape should be an irrelevant factor in that my instrument is expected to provide an accurate estimate of the perimeter, regardless of the object’s shape. However, when we have a lack of measurement invariance, the estimated perimeter provided by my instrument is influenced not only by the true perimeter but also by the object’s shape. When we lack measurement invariance, irrelevant factors systematically influence the estimates our instruments are designed to produce.
Methods for testing DIF in IRT are model based, in that they require fitting a latent variable model in both groups. IRT provides a convenient and powerful framework for evaluating whether an item is functioning differentially by comparing each group’s parameter estimates or IRF. In fact, DIF can be defined explicitly from the IRT models as the difference in the probability of responding to a category (e.g., correct response for a dichotomous item) for examinees with the same ability from different populations (Lord, 1980). This definition is consistent with comparing the IRFs or item parameter values between groups. In other words, if the parameter values or IRFs are identical in both populations, then the probabilities of responding to a category are the same and therefore the item is DIF-free. However, if the IRFs differ in the populations, then the item is functioning differentially (Lord, 1980).