The ACR Model: A Multivariate Dynamic Mixture Autoregression*

This paper proposes and analyses the autoregressive conditional root (ACR) time‐series model. This multivariate dynamic mixture autoregression allows for non‐stationary epochs. It proves to be an appealing alternative to existing nonlinear models, e.g. the threshold autoregressive or Markov switching class of models, which are commonly used to describe nonlinear dynamics as implied by arbitrage in presence of transaction costs. Simple conditions on the parameters of the ACR process and its innovations are shown to imply geometric ergodicity, stationarity and existence of moments. Furthermore, consistency and asymptotic normality of the maximum likelihood estimators are established. An application to real exchange rate data illustrates the analysis.     

Propositions for testing the involvement construct in recreational and tourism contexts

Abstract

The involvement construct has been extensively studied in the consumer behavior literature. Recent conceptual and measurement breakthroughs have made examination of the construct appealing in the contexts of recreational and tourist behavior. This article suggests 15 propositions that evolve from a review of involvement‐related literature. The propositions are grouped under the following headings: measurement issues; the relationship between involvement and time; the relationship of involvement with search and purchase behavior; the relationship between involvement and promotional stimuli; and accessing the involvement variable. The propositions are intended to stimulate and guide empirical research related to involvement in recreation and tourism contexts.     

The Jarrow/Turnbull default risk model—Evidence from the German market

Abstract

This article estimates default intensities within the continuous-time Jarrow and Turnbull model for German bank and corporate bond prices. It is shown that a joint implicit estimation of the default intensity and the recovery rate is numerically unstable. In addition to cross-sectional estimations, separate estimations (for each bond individually) are performed. Results strongly support separate estimation over the building of any cross-sections. In contrast to preceeding literature, the optimum volume of data required to provide reasonable estimates of the default intensity is also investigated. It is shown that calibration based on daily data as a rule does not minimize the ex ante mean squared pricing errors. Finally, it is shown that the constant default intensity assumption is not sound with the underlying data and the determinants of the default intensity are investigated. Regressions show that the lagged default intensity estimate, the level of the default-free term structure and liquidity proxies affect the estimated default intensity via joint parameters.     

A Case Study of Long QT Regulation: A Regulatory Tennis Game Across the Atlantic

This paper has been written in a context of vivid transatlantic discussions about regulation and precaution. The study is looking at a specific and topical issue of drug safety regulation, the so‐called QT interval. The QT interval is commonly described as a reflection of how long it takes to “recharge” heart cells after they have been stimulated to beat, and it has been argued that both natural and drug induced lengthening of this interval may lead to a increased risk of death. The paper is based on interviews with all the major regulatory bodies responsible for the regulation of QT prolongation. The research focused on a number of key questions, starting with the “story” behind present QT regulation. It describes the debates that emerged in the 1992s about the significance of QT variations, and the existing level of uncertainty, on whether long QT is something we should worry about or not. Looking at the QT regulation story, no doubt the regulator answered this question by “yes”. However, there are still some divergences about the magnitude of the risk between experts and non experts, between Europeans and Americans, between ‘insiders’ and ‘outsiders’, which the paper explores in its complexity. Finally, the paper is introducing a conceptual model to analyse these developments, the so‐called “regulatory tennis game” that shaped the present regulation. It is also stressing some of the intrinsic problems of the “expert driven bi‐partite model” for making evidence based decisions about risk.     

Culture As A Moderator Of The Relationship Between Service Quality And The Tourist'S Satisfaction With Different Distribution Channels

The present research analyzes the influence of culture on the relationship between each of the dimensions of service quality and tourists' satisfaction with the distribution channel, differentiating between travel agencies and the Internet. More specifically, the research seeks to understand the influence of the cultural dimensions of uncertainty avoidance and individualism/collectivism on the relationship between each of the dimensions of service quality and satisfaction, depending on the medium through which the service is purchased. The sample was made up of 600 tourists. Of these, 300 tourists (150 Spanish and 150 English) had purchased hotel accommodation for their last holiday via a travel agency, and the other 300 (150 Spanish and 150 English) had purchased hotel accommodation for their last holiday via the Internet. The findings indicate that there are variations in the relationships between each of the dimensions of service quality and satisfaction, and that these variations are shaped by the cultural dimensions of uncertainty avoidance and individualism/collectivism.     

Climate Policy Under Fat-Tailed Risk: An Application of Dice

Uncertainty plays a significant role in evaluating climate policy, and fat-tailed uncertainty may dominate policy advice. Should we make our utmost effort to prevent the arbitrarily large impacts of climate change under deep uncertainty? In order to answer to this question, we propose a new way of investigating the impact of (fat-tailed) uncertainty on optimal climate policy: the curvature of the optimal carbon tax against the uncertainty. We find that the optimal carbon tax increases as the uncertainty about climate sensitivity increases, but it does not accelerate as implied by Weitzman’s Dismal Theorem. We find the same result in a wide variety of sensitivity analyses. These results emphasize the importance of balancing the costs of climate change against its benefits, also under deep uncertainty.     

Oscar Karl Mouritz Schjøll

Abstract

De viktigste ytre data i Schjølls liv var følgende: Cand. real. 1872, lærer i den høiere skole 1872-79, aktuar og kontorchef i Livsforsikringsselskapet Idun 1879-95, direktør for Riksforsikringsanstalten (nu Rikstrygdeverket) 1895–1904, direktør for Den norske Enkekasse og Pensjonskassell for Statens Tjenestemenn 1904–1920, direktør for Statens Pensjonskasse 1917–1920, medlem av Tilsynskomiteen for private forsøfgelses- og understøttelsesselskaper 1900–1931. Han var en av stifterne av Den Norske Aktuarforening og korresponderende medlem av » Vereinigung schweizerischer Versicherungs mathematiker »     

Semiparametric estimation of conditional mean functions with missing data

A new semiparametric estimator for estimating conditional expectation functions from incomplete data is proposed, which integrates parametric regression with nonparametric matching estimators. Besides its applicability to missing data situations due to non-response or attrition, the estimator can also be used for analyzing treatment effect heterogeneity and statistical treatment rules, where data on potential outcomes is missing by definition. By combining moments from a parametric specification with nonparametric estimates of mean outcomes in the non-responding population within a GMM framework, the estimator seeks to balance a good fit in the responding population with low bias in the non-responding population. The estimator is applied to analyzing treatment effect heterogeneity among Swedish rehabilitation programmes.

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What do we know about real exchange rate nonlinearities?

Nonlinear modeling of adjustments to purchasing power parity has recently gained much attention. However, a huge body of the empirical literature applies ESTAR models and neglects the existence of other competing nonlinear models. Among these, the Markov Switching AR model has a strong substantiation in international finance. Our contribution to the literature is fivefold: First, ESTAR and MSAR models from a unit root perspective are compared. To this end, a new unit root test against MSAR is proposed as the second contribution. Thirdly, the case of misspecified alternatives in a Monte Carlo setup with real world parameter constellations is studied. The ESTAR unit root test is not indicative, while the MSAR unit test is robust. Fourthly, the case of correctly specified alternatives is considered and low power of the ESTAR but not for the MSAR unit root test is observed. Fifthly, an empirical application to real exchange rates suggests that they may indeed be explained by Markov Switching dynamics rather than ESTAR.