PFIs involving multiple public partners: a case study from the Italian healthcare sector

The financial crisis experienced by many countries since 2008 has given new importance to private finance initiatives (PFIs) for providing public services. This paper analyses the relationships between multiple public and private sector actors participating in a PFI in the healthcare sector in order to better understand the motives and behaviour of public and private sector partners. High levels of trust and the active participation of a regulatory body were found to be significant factors in terms of creating a partnership that benefits all sides.     

Bayesian selection of technology assumptions for the transformation from supply-use to input–output tables

ABSTRACT

In the construction of input–output models from supply-use tables, technology assumptions disambiguate how an industry uses inputs in the production recipe of multiple outputs. This paper uses Bayes' theorem to select technology assumptions, taking into account empirical observations. The paper presents a formulation to explore hybrids between product and industry technology assumptions in product-by-product tables. We then present Markov chain Monte-Carlo techniques to implement the Bayesian method for selecting technology assumptions. We apply the method in a case study using Eurostat supply-use tables of 2004 and 2005, exhibiting a volume of secondary products of less than 13%, and 59 products and industries per country. The results show that the choice of technology is not important, given that there is no strong evidence in favour of any of them.     

Inter‐firm R&D collaborations and green innovation value: The role of family firms' involvement and the moderating effects of proximity dimensions

The present paper investigates the relationship between the involvement of family firms in R&D collaborations aimed at developing green solutions and the value of resulting innovations. To dig into this relationship, the moderating effects of two proximity dimensions (i.e., geographical distance and technological relatedness) are also assessed. Analyses are based on a sample of 156 joint patents classified into the “Alternative energy production” field, as defined by the International Patent Classification Green Inventory and successfully filed at the United States Patent and Trademark Office in the period 1997–2010 by publicly listed companies. According to our conjectures, results reveal a positive relationship between the involvement of family firms and green innovation value. Moreover, our findings show that this relationship is hindered when partners are geographically distant or technologically proximate. Eventually, we contribute to the literature on green innovation by unveiling under which conditions inter‐firm R&D collaborations lead to more valuable innovations.     

Trauma epidemiology in Puerto Rico: in-hospital morbidity and mortality from 2002 to 2011

This study aimed to describe the distribution of injury mechanisms and to assess the impact of those mechanisms on the morbidity and mortality of trauma. All patients admitted to Puerto Rico Trauma Hospital (2002–2011) for road-traffic collisions (RTCs, 5,371), gunshot wounds (GSWs, 2,946), falls (2,319), pedestrian accidents (1,652), and stab wounds (SWs, 1,073) were selected. Gunshot victims were 1.19 (95%CI: 1.07–1.33) times as likely as road-traffic victims to have an ISS ≥25. Pedestrians were 1.76 (95%CI: 1.49–2.09) times more likely to have a GCS ≤8 than road-traffic victims were. The risk of dying was 2.64 (95%CI: 2.20–3.16) times higher for gunshot victims and 1.51 (95%CI: 1.23–1.86) times higher for pedestrians compared to patients who had had RTCs. Gunshot victims and pedestrians had the worst clinical outcomes. Accordingly, these patients should receive the most aggressive clinical management. Furthermore, it is imperative to develop public health campaigns on trauma prevention.     

An application of two-stage quantile regression to insurance ratemaking

Two-part models based on generalized linear models are widely used in insurance rate-making for predicting the expected loss. This paper explores an alternative method based on quantile regression which provides more information about the loss distribution and can be also used for insurance underwriting. Quantile regression allows estimating the aggregate claim cost quantiles of a policy given a number of covariates. To do so, a first stage is required, which involves fitting a logistic regression to estimate, for every policy, the probability of submitting at least one claim. The proposed methodology is illustrated using a portfolio of car insurance policies. This application shows that the results of the quantile regression are highly dependent on the claim probability estimates. The paper also examines an application of quantile regression to premium safety loading calculation, the so-called Quantile Premium Principle (QPP). We propose a premium calculation based on quantile regression which inherits the good properties of the quantiles. Using the same insurance portfolio data-set, we find that the QPP captures the riskiness of the policies better than the expected value premium principle.     

Stock Market Reaction to Monetary Policy: An Event Study Analysis of the Brazilian Case

This article examines the relationship between the monetary policy implemented by the Central Bank of Brazil and the stock market. We implement event study analysis and analyze the effect of the anticipated and unanticipated components of monetary policy decisions on the returns of the IBOVESPA index and 53 stocks. We find that monetary policy has a significant effect on the stock market, but is only responsible for a small proportion of market variation. The analysis at the sector level with expected returns identifies that the financial sector is the most affected by this policy, whereas with excess returns only industrial goods are significantly affected. Moreover, individual assets respond in a rather heterogeneous fashion to monetary policy; however, when we look at excess returns, we identify a reduction in the intensity and in the number of companies impacted by monetary policy. Finally, the monetary shock is explained by unanticipated variations in the unemployment rate, in the Industrial Production Index, in the General Market Price Index, and in the Broad Consumer Price Index.     

Yield curves from different bond data sets

Review of Derivatives Research - It is well known that zero coupon rates are not observable variables. Their estimation process may be cumbersome and time consuming. We explore the extent to which...     

Unraveling determinants of inferred and stated attribute nonattendance: Effects on farmers’ willingness to accept to join agri-environmental schemes

Attribute nonattendance (ANA) has received very little attention in the context of willingness to accept (WTA), although an increasing number of studies analyze the preferences of ecosystem service providers toward incentive-based schemes. We add to the understanding of ANA behavior by analyzing stated and inferred ANA in a choice experiment investigating farmers’ WTA for participating in agri-environmental schemes (AES) in southern Spain. We use mixed logit models, following Hess and Hensher for the inferred ANA approach. Evidence is found of ANA behavior for both stated and inferred approaches, with models accounting for ANA clearly outperforming those that do not account for it; however, we produce no conclusive results as to which ANA approach is best. WTA estimates are only moderately affected, which to some extent is consistent with the low level of non-attendance found for the monetary attribute. Stated and inferred approaches show very similar WTA estimates. Additionally, we investigate sources of observed heterogeneity related to ANA behavior by using a sequence of bivariate probit models for each attribute. Overall, our results hint at a positive relationship between ease of scheme adoption and nonattendance to attributes. However, further research is still needed in this field.     

Contemporaneous ADR pricing: intraday dynamics during overlapping trading hours

We contribute to the literature by identifying and accurately measuring the drivers of American depositary receipt (ADR) returns contemporaneously across various global time zones. We consider ADRs as two inherently distinct asset classes – stocks and currencies – bundled into one. Throughout, we use a relatively refined, focused, and synchronized minute-by-minute data set on ADRs and all other variables. ADRs from all countries with regular trading hours that overlap with those of the US are considered individually and in clusters. We analyze the interplay of several factors that influence ADRs pricing patterns. Further, we investigate whether such patterns vary by currency, ADR, industry, and emerging/developed market classifications. Our findings indicate that synchronized returns on underlying shares comprise 68.5–74% of the explained returns in ADRs. The remaining 31.5–26% of returns are generated by movements in currency rates. These results are robust across the several models and estimation methods employed. Our findings also show persistent small price discrepancies between ADRs and dollar-adjusted underlying shares on a minute-by-minute basis, implying possible arbitrage opportunities. However, we conclude that trading and ADR conversion costs render such opportunities unattractive.     

Intertemporal substitution in the Spanish economy: Evidence from regional data

This paper studies the intertemporal substitution in consumption and leisure for the Spanish economy by estimating the first‐order conditions of an individual optimization model with regional and aggregate data. While first‐order conditions determining intertemporal substitution in consumption show a good econometric fit, and the value we obtain for the intertemporal elasticity of substitution is similar to previously available results, the econometric fit of the intertemporal condition in leisure indicates that the behaviour of the Spanish labour supply over the cycle is more complex than can be explained by the canonical intertemporal choice model.