Health system spending, and the consequent impact on health are increasingly a focus of governments around the world. Given the strain on resources and systems, increasingly scarce resources require targeting more effectively. Measuring efficiency and productivity are increasingly the focus of government gepartments, both nationally and locally. Thus, assessing how efficiency is measured and how valid and robust results are is critical to those involved in policy and service delivery. This chapter presents revised guidelines as to how users should set up such studies to be as useful as possible and how end users can assess how useful they actually are to them in their specific setting. Conclusions are drawn as to how these can be used in a fast-changing world, and potential consequences of not following guidance are discussed.

Conditional frontier models, including full and partial, robust frontiers, have evolved into an indispensable tool for exploring the impact of exogenous factors on the performance of the decision-making units in a fully nonparametric setup. Nonparametric conditional frontier models enable the handling of heterogeneity in a formal way, allowing explanation of the differences in the efficiency levels achieved by units operating under different external or environmental conditions. A thorough analysis of both full and robust time dependent conditional efficiency measures and of their corresponding estimators allows unravelling the compounded impact that exogenous factors may have on the production process. The nonparametric framework does not make assumptions on error distributions and production function forms and avoids misspecification problems when the data-generation process is unknown, as is common in applied studies. This chapter proposes a comprehensive review and journey through the conditional nonparametric frontier models developed so far in the efficiency literature. The authors show how this nonparametric dynamic framework is important for evaluating efficiency in the healthcare sector. They provide numerical illustrations on datasets from the Italian healthcare system, including summaries of practical implementation details.

This chapter provides a brief overview of the stochastic frontier analysis (SFA) in the context of analyzing healthcare, with a focus on hospitals, where it has received widespread attention. The authors consider many of the popular extensions and generalizations of the classic SFA model in both cross-sectional and panel data. They also briefly discuss semiparametric and nonparametric generalizations, spatial frontiers, Bayesian SFA, and the endogeneity in SFA. They illustrate some of these methods for real data on public hospitals in Queensland, Australia, as well as provide practical guidance and references for their computational implementations via R.

Various hospitals in the US and around the world suffer from the well-known problem of emergency department (ED) overcrowding, which prevents them from serving patients effectively and efficiently. An important contributor to this problem, which became even more dire after the COVID-19 pandemic, is prolonged boarding of patients who are admitted to inpatient units through the ED. Patients admitted through the ED constitute about 50% of all nonobstetrical hospital admissions in the US, and they may be boarded in the ED for long hours with the hope of finding an available bed in their primary inpatient unit. This chapter sheds light on effective ways of reducing ED boarding times by considering the trade-off between keeping patients in the ED and assigning them to a secondary inpatient unit. Using simulation analyses calibrated with hospital data, they find that implementing this policy could significantly help hospitals to improve their patient safety by reducing boarding times while controlling the overflow of patients to secondary units. Using data analyses and various simulation experiments, they also help hospital administrators by generating insights into hospital conditions under which achievable improvements are significant.

This chapter provides basic production theoretical underpinnings used in modeling and measuring performance in the healthcare realm, which covers a host of institutions, practitioners, regulators, insurers, and patients, among others. This is a difficult task given the complexity of the healthcare sector. In general, the authors seek some meaningful benchmarks to use in assessing performance that are rich enough to model these complex entities. They begin with introducing technology or sets, which include as elements the many inputs used to treat patients in clinics or hospitals, which are in turn employed to improve patient outcomes (outputs), which may be multidimensional as well. They introduce key axioms that are imposed on these sets. However, although key in determining the benchmark or best practice possibilities, these sets are not practical for determining the performance of individual entities relative to the benchmark. More practical are functional representations of these multidimensional sets that are easy to estimate, which include distance functions and their dual value functions. These functions inherit properties from their respective technology sets, which in turn require certain specifications of their functional form if they are to be estimated parametrically.

This chapter discusses the implications of considering the health system as part of the national social infrastructure, using the example of the demand surge experienced during the COVID-19 pandemic for the UK’s rationed, largely free at the point of need National Health Service (NHS). It explores the impact of the past prioritization of the cost efficiency of the service rather than long-term need. An infrastructure perspective incorporating resilience and peak-demand considerations sheds new light on the performance of the health service and underlines the role of healthcare systems in human capital investment and economy-wide productivity.

This chapter discusses the extent to which standard economic efficiency analysis can be applied to the economics of reducing ill health caused by environmental factors. This type of analysis is relevant when production functions can be applied to public health environmental situations such as those involving the public supply of safe water and sanitation. On the other hand, different analytical approaches are required to assess more holistically the social economic efficiency of public policies to control most environmentally related diseases. Concrete theoretical evidence about the analytical significance of the presence of externalities is backed up with examples. These cases include cadmium poisoning, drinking water contaminations, issues involved in the control of COVID-19, and the willingness of individuals to vaccinate against infectious diseases. In addition, particular attention is paid to problems involved in determining the social economic efficiency of the amount and use of methods of controlling environmentally related diseases when their effectiveness declines with use.

This chapter marks the starting point of our investigation of actual policy solutions to tackle armed conflict. When a doctor has reached her diagnosis, she must then decide on the right medication to administer. Similarly, while economists started by studying the drivers of political violence, in recent years increasing efforts have been made to understand how to cut the Gordian knot of conflict. As argued in this chapter, a first-order factor is the institutional environment, and in particular the need to give a voice to all citizens and groups in society. Democracy is desirable, but without proper safeguards it can have a dark side and result in blood being spilt. Furthermore, the type of democracy and the provisions of sharing power between groups matter. Closer inspection of local-level power-sharing in Northern Ireland, the building of modern Switzerland after its civil war in 1847, the difficulties for current democratization in Iraq and the franchise extension during the British Age of Reform drive this discussion forward.

The starting point of this chapter is the observation that would-be dictators are abundant around the globe, but some succeed in setting up and sustaining a rebel army while others do not. As argued in this chapter, a key ingredient for rebel success and conflict longevity is funding. One source of financing is the stolen spoils of nature. Think, for example, of blood diamonds. Beyond this particular example, we also discuss in this chapter systematic evidence on how access to mineral rents triggers an escalation of fighting activities of armed groups. In addition to resource rents, it is foreign funding that results in prolonged conflict, and may lead to proxy wars between fighting factions supported by rival foreign powers. The destructive potential of these sources of funding is examined by drawing on examples and empirical evidence from Angola, the Democratic Republic of Congo and India.

This chapter discusses the impact of particular policies at the global level. It turns out that coordination and common standards can make a big difference. First, it is shown that the global traceability of minerals can cut rebel funding significantly. Next, the role of monitoring multinationals is highlighted. Notably, recent studies have pinpointed the importance of corporate social responsibility of mining firms, revealing that the best-run mineral extractors may have a beneficial impact on the local population, while poorly run firms yield disastrous outcomes. Further, given that wars tend to trigger a series of vicious cycles, there is a powerful case for facilitating refugee admission. It is discussed how a well-coordinated refugee policy can reduce violence perpetuation over future generations. Next, we investigate what role international trade can play for fostering peace and what harmful effects arms trade can entail. It is shown how arms-producing countries can – without bearing large economic costs – reduce the ability of bad regimes to attack their civilians. Finally, the importance of a rule-based international order and a well-managed green transition is highlighted.