On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility

In this paper we use Malliavin calculus techniques to obtain an expression for the short-time behavior of the at-the-money implied volatility skew for a generalization of the Bates model, where the volatility does not need to be a diffusion or a Markov process, as the examples in Sect. 7 show. This expression depends on the derivative of the volatility in the sense of Malliavin calculus. E. Alòs’ research is supported by grants MEC FEDER MTM 2006 06427 and SEJ2006-13537. J.A. León’s research is partially supported by the CONACyT grant 45684-F. J. Vives’ research is supported by grant MEC FEDER MTM 2006 06427.     

New business formation and employment growth: some evidence for the Spanish manufacturing industry

This paper explores the effects of new business formation on employment growth in Spanish manufacturing industries. New firms are believed to make an important contribution to economic growth but the extent of this contribution is unclear. We consider time lags of new firm formation as explanatory variables of employment change and identify how long the effect of new firm entries on employment lasts. Our main results show that the effects of new business formation are positive in the short term, negative in the medium term and positive in the long term, thus confirming the existence of indirect supply-side effects found in similar studies for other countries.

A reduced lattice model for option pricing under regime-switching

We present a binomial approach for pricing contingent claims when the parameters governing the underlying asset process follow a regime-switching model. In each regime, the asset dynamics is discretized by a Cox–Ross–Rubinstein lattice derived by a simple transformation of the parameters characterizing the highest volatility tree, which allows a simultaneous representation of the asset value in all the regimes. Derivative prices are computed by forming expectations of their payoffs over the lattice branches. Quadratic interpolation is invoked in case of regime changes, and the switching among regimes is captured through a transition probability matrix. An econometric analysis is provided to pick reasonable volatility values for option pricing, for which we show some comparisons with the existing models to assess the goodness of the proposed approach.     

INCOME DISTRIBUTIONS IN INPUT-OUTPUT MODELS

The analysis of income distribution (ID) has traditionally been of prime importance for economists and policy-makers. However, the standard input–output (I–O) model is not particularly well equipped for studying current issues such as the consequences of decreasing access to primary inputs or the effects of specific redistributive policies. This paper addresses this gap in the existing literature. We propose that IDs can excellently be studied by restructuring the I–O relations. A new coefficients matrix is defined, the so-called augmented input coefficients matrix. This matrix is the sum of the intermediate input coefficients matrix and newly constructed matrices of sector-specific input coefficients that represent the existing distribution of income. We show that shifts in the distribution can be modelled by attributing weights to these matrices and vary these according to system-specific rules. Numerical illustrations based on the existing literature are given throughout the paper.     

Fair Valuation of Equity-Linked Policies under Insurer Default Risk

Abstract

We consider the problem of computing the fair value of equity-linked policies with an interestrate guarantee when the insurer is subject to credit risk. The framework is developed based on modern financial theory using the no-arbitrage principle. In this context, an equity-linked policy is considered as a vulnerable contingent claim that expires before maturity if the firm asset value reaches a prespecified default threshold depending on the firm’s liabilities. We derive a closedform formula in a continuous-time environment to compute the fair value of the contract. We also develop a discrete-time model that allows us to address fair evaluation when the policy embeds a surrender option.     

Preferenza sociale non transitiva e teorema di Arrow

Questo lavoro estende il teorema di impossiblità di Arrow al caso di preferenza sociale stretta non transitiva. In particolare, si dimostra che se una Funzione di Decisione Sociale (FDS) soddisfa le condizioni di dominio universale, indipendenza dalle alternative irrilevanti, transitività della relazione di indifferenza sociale, il principio di Pareto forte e la regola di indifferenza paretiana, allora la FDS deve essere dittatoriale. Vengono inoltre illustrate le implicazioni di tale risultato per il caso in cui la FDS soddisfa la condizione di dualità.

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Summary This paper extend's Arrow's impossiblity theorem to the case where strict social preference may be intransitive. The main result of the paper is that if a Social Decision Function satisfies Unrestricted Domain, Independence of Irrelevant Alternatives, Transitivity of Social Indifference, the Strong Pareto Principle, and the Pareto Indifference Rule, then there exists a dictator. An application of this result is a new impossibility theorem concerning SDF obeying the condition of Duality. As a by-product of this analysis, the relationships between Neutrality and Duality are somewhat clarified.

     

Modeling node heterogeneity in latent space models for multidimensional networks

Multidimensional network data can have different levels of complexity, as nodes may be characterized by heterogeneous individual-specific features, which may vary across the networks. This article introduces a class of models for multidimensional network data, where different levels of heterogeneity within and between networks can be considered. The proposed framework is developed in the family of latent space models, and it aims to distinguish symmetric relations between the nodes and node-specific features. Model parameters are estimated via a Markov Chain Monte Carlo algorithm. Simulated data and an application to a real example, on fruits import/export data, are used to illustrate and comment on the performance of the proposed models.     

Projecting total costs and health consequences of increasing mt-sDNA utilization for colorectal cancer screening from the payer and integrated delivery network perspectives

Abstract

Aims: To evaluate total costs and health consequences of a colorectal cancer (CRC) screening program with colonoscopy, fecal immunochemical tests (FIT), and expanded use of multitarget stool DNA (mt-sDNA) from the perspectives of Integrated Delivery Networks (IDNs) and payers in the United States.

Materials and methods: We developed a budget impact and cost-consequence model that simulates CRC screening for eligible 50- to 75-year-old adults. A status quo scenario and an increased mt-sDNA scenario were modeled. The status quo includes the current screening mix of colonoscopy (83%), FIT (11%), and mt-sDNA (6%) modalities. The increased mt-sDNA scenario increases mt-sDNA utilization to 28% over 10 years. Costs for both the IDN and the payer perspectives incorporated diagnostic and surveillance colonoscopies, adverse events (AEs), and CRC treatment. The IDN perspective included screening program costs, composed of direct nonmedical (e.g. patient navigation) and indirect (e.g. administration) costs. It was assumed that IDNs do not incur the costs for stool-based screening tests or bowel preparation for colonoscopies.

Results: In a population of one million covered lives, the 10-year incremental cost savings incurred by increasing mt-sDNA utilization was $16.2 M for the IDN and $3.3 M for the payer. The incremental savings per-person-per-month were $0.14 and $0.03 for the IDN and payer, respectively. For both perspectives, increased diagnostic colonoscopy costs were offset by reductions in screening colonoscopies, surveillance colonoscopies, and AEs. Extending screening eligibility to 45- to 75-year-olds slightly decreased the overall cost savings.

Limitations: The natural history of CRC was not simulated; however, many of the utilized parameters were extracted from highly vetted natural history models or published literature. Direct nonmedical and indirect costs for CRC screening programs are applied on a per-person-per modality basis, whereas in reality some of these costs may be fixed.

Conclusions: Increased mt-sDNA utilization leads to fewer colonoscopies, less AEs, and lower overall costs for both IDNs and payers, reducing overall screening program costs and increasing the number of cancers detected while maintaining screening adherence rates over 10 years.