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Public–Private Partnerships (PPPs) are used worldwide to reduce the infrastructure gap. Public entities encourage private sector involvement through PPPs, but the degree of such commitment is affected by several factors, related to the specific PPP project and to the institutional and economic environment in the host country. The purpose of this chapter is to perform an empirical analysis of the determinants of the degree of private sector participation in PPPs in developing and emerging countries. This chapter explores fractional response models to explain the degree of private participation in PPPs using data from 2000 to 2014, obtained from the World Bank’s PPI database. The results suggest that the type of project is a key determinant of the degree of private sector involvement. Favourable fiscal conditions and the existence of explicit support from the government (direct or indirect) increase the degree of private involvement. Multilateral support reduces private participation, emphasizing a substitution effect. In the same way, private sector involvement appears as a substitute to overcome failures in countries with poor financial systems. The results are particularly important for public authorities. This chapter identifies key factors that can foster private sector involvement in PPPs. Although the expansion of PPPs is a well-accepted reality, empirical studies that explore factors that affect the degree of private sector involvement are still lacking. This chapter particularly addresses this topic.

Purpose – To examine the effects of health insurance types on the use of prescribed medication that treat patients with hypertension, diabetes, and asthma. The study distinguishes between individuals with private health maintenance organization (HMO) plans and private non-HMO plans. The study also distinguishes between people with health insurance and drug coverage and people with health insurance and no drug coverage.

Methods – Joint discrete factor models are estimated to control for endogeneity of each type of coverage.

Findings – The main findings suggest that the effect of health insurance varies across patients with different conditions. The strongest and most significant effect is evident among patients with hypertension while the weakest and least significant is among patients with asthma. These findings suggest that patients with asymptomatic conditions are more likely to exhibit moral hazard than patients with conditions that impose immediate impairment. Additional results suggest that, relative to the uninsured and people with health insurance but no drug coverage, patients with drug coverage are more likely to initiate drug therapy and to consume more medications.

Originality – The results of the study indicate that moral hazard of drug utilization is condition specific. The variation in “silence” of conditions’ symptoms could be a key reason for difference in insurance effects among patients with hypertension, diabetes, and asthma.

Purpose – This study constitutes a first attempt to experimentally test the performance of a 100% auction versus a 100% free allocation of CO2 permits under the rules and parameters that mimic the EU ETS (imperfect competition, uncertainty in emissions' control, and allowing banking), with environmental targets more restrictive than the current ones but foreseeable for the near future.

Methodology/approach – Two experimental treatments were run to achieve our goal. Both included the rules and the parameters that parallel the EU ETS structure, the only difference being the rule for the primary allocation of permits.

Findings – Our experimental results indicate that the EU ETS has the potential to reduce CO2 emissions, achieving targets considerably more restrictive than the current ones at high efficiency levels, both with auctioned and free emission permits.

Practical implications – Concerns about undue scarcity, and corresponding high prices, in secondary markets generated by a primary auction market are not warranted under the proposed dynamic auction format. This adds arguments favoring auctioning over grandfathering as the rule for the initial allocation of emission permits in the EU ETS.

Originality/value of chapter – This study implements a theoretically appropriate auction format for the primary allocation of emission permits (the Ausubel (2004) auction) and incorporates a first attempt to include in the analysis measures of the risk preferences of subjects participating in emission permits experiments. These characteristics are for the first time implemented under a complex experimental design (including uncertainty of emission abatement, and banking), trying to parallel the EU ETS trading environment.

It is not easy to get a long perspective on the distribution of wealth in Sweden because there is no single data source that gives a consistent view for a long period of time. The early estimates of the distribution of wealth were based on the concept of tax-assessed wealth which is the basis of the wealth tax. This definition has the disadvantage of not including assets that were not taxed, and no or very unreliable data were given for the majority of the tax payers who were below the taxation threshold. Furthermore, this variable was defined for individuals and for jointly taxed individuals, but no economically meaningful household concept was available. Register data have since then improved, in particular after the late 1990s when data became available directly from banks, brokers, and insurance companies without the filtering of the tax payers. The problem with the household definition remains, but in SESIM we have made corrections to get a useful definition (see Chapter 3). A relatively large survey (HEK) run by Statistics Sweden which combines survey information about the household with register data on assets estimates the median household wealth to 156000 SEK in 1999 and 197000 SEK in 2003.² The latter estimate is in the 1999 price level.³ These estimates apply to all households independent of age. As will be shown below, the level of wealth depends very much on age.

In 1969, the psychiatrist Elisabeth Kübler-Ross wrote On Death and Dying. In this influential essay, she presented her now-famous 5-stage model of approaching death, which can be modelled into a downward trajectory (1. shock and denial, 2. anger, 3. bargaining, 4. depression) followed by a symmetrical psychological rise (5. acceptance).

In 1888–1894, in response to Hans von Bülow's death, Gustav Mahler composed his Symphony No. 2 (subtitled ‘Resurrection’), in which the idea of death is omnipresent: it opens with a funeral march based on a symphonic poem called Totenfeier (‘Remembrance Ceremony’) containing a Dies Irae motive and closes with a very long finale inspired by Klopstock's Die Auferstehung (The Resurrection). The structure of the finale itself is quite similar to the symmetrical mechanism described by Kübler-Ross, which can be summarised in the symphony by this verse sung by the choir: ‘Sterben werd’ ich, um zu leben!’ (‘I shall die, to live!’). With this ‘death and transfiguration’ movement, the orchestra and the choir embodying the psychological process of a dying subject covers every single step of the model: from a ‘cry of despair’ in the first bar (1. shock) to a horn call without response (2. denial), to the depiction of a rivalry between the Dies Irae motive (‘death’) and what will be the Resurrection theme (3. bargaining), to a grieving section (4. depression) and to a long rising towards an optimistic climax at the end (5. acceptance).

Even though the death acceptance process was far from being formalised in Mahler's days, this symphony shows that more than 75 years before Kübler-Ross, the composer, who had many opportunities to grieve since his youth (facing his brothers' and sisters' deaths), intuitively converted these experiences into an in-depth knowledge of the psychological processes of dying. In other words, after having dealt with the loss of loved ones, Mahler turns out to know how to deal with his own.

Purpose – To estimate the impact of diabetic drug adherence on hospitalizations, emergency room (ER) visits, and hospital costs.

Methods – It is often difficult to measure the impact of drug adherence on hospitalizations since both adherence and hospitalizations may be correlated with unobservable patient severity. We control for such unobservables using propensity score methods and instrumental variables for adherence such as drug coinsurance levels and direct-to-consumer advertising.

Findings – We find a significant bias due to unobservable severity in that patients with more severe health are more apt to comply with medications. Thus, the relationship between adherence and hospitalization will be underestimated if one does not control for unobservable severity. Overall, we find that increasing diabetic drug adherence from 50% to 100% reduces the hospitalization rate by 23.3% from 15% to 11.5%. ER visits reduce by 46.2% from 17.3% to 9.3%. Although such an increase in adherence increases diabetic drug spending by $776 a year per diabetic, the cost savings for averted hospitalizations and ER visits are $886 per diabetic, a cost offset of $1.14 per $1.00 spent on diabetic drugs.

Originality – Most of the drug cost-offset literature focuses only on the impact of cost-sharing and drug spending on cost-offsets, making it impossible to back-out the empirical impact of actual drug adherence on cost-offsets. In this chapter, we estimate the direct impact of adherence on hospitalizations and costs.

Objective. To quantify the association between obesity and somatic hospital costs and number of overall somatic hospital contacts – number of inpatient admissions, number of outpatient visits, and number of emergency department visits – based on anthropometric measurements of waist circumference (WC) and information from The National Patient Registry and The Danish Case-Mix System (DRG).

Participants. The study population consisted of two sub-samples from the Inter99 study at Research Centre for Prevention and Health in 1999–2001. One sub-sample used WC as an indicator for obesity (n=5,151), whereas the other used BMI as an indicator for obesity (n=4,048). Using WC, obesity was defined as WC > 102cm for men and > 88cm for women. Normal weight was defined as circumference < 94cm for men and < 80cm for women. Using BMI, obesity was defined as BMI > 30kg/m2, whereas individuals with BMI=18.5–24.9kg/m2 were defined as normal weight. Individuals with BMI < 18.5kg/m2 were excluded from both sub-samples.

Design. We undertook a 3-year retrospective study of the relationship between obesity and use of hospital resources. Data on hospital contacts and costs were obtained from The National Patient Registry and DRG. Analyses were performed using two-part models and Poisson regression. Outcome variables were costs and hospital contacts.

Results. This study has demonstrated that obese individuals have a greater use of hospital services and greater hospital costs compared with normal weight individuals. When using WC as an indicator for obesity, mean hospital costs were 33.8% greater among obese women and 45.3% greater among obese men in a 3-year period but the differences were not significant. When using BMI to measure obesity, obese men had significantly greater costs (57.5%) than normal weight men.

Furthermore, obese men and women (indicated byWC) had an increased number of hospital contacts compared with normal weight individuals (rate ratio 1.32, 95% CI 1.21–1.43 for men and 1.20, 95% CI 1.11–1.28 for women) including inpatient admissions, outpatient visits, and emergency department visits. The same trends were seen when obesity was indicated by BMI.