Business cycle duration dependence and foreign recessions

This study revisits business cycle duration dependence in G7 countries by controlling for foreign recessions, defined as the number of other G7 countries in a recession. Estimates from regime switching logit models show that the monthly likelihood of ending an expansion roughly doubles for every extra G7 country in recession, but the end of foreign recessions do not affect the ending of recessions. They also show that recessions are duration dependent in all G7 countries, but expansions only in the United States and Germany. The economic importance of foreign recessions and duration in driving business cycle phase changes vary across countries.     

Small‐time,large‐time,and asymptotics for the Rough Heston model

We characterize the behavior of the Rough Heston model introduced by Jaisson and Rosenbaum (2016, Ann. Appl. Probab., 26, 2860–2882) in the small‐time, large‐time, and (i.e., ) limits. We show that the short‐maturity smile scales in qualitatively the same way as a general rough stochastic volatility model , and the rate function is equal to the Fenchel–Legendre transform of a simple transformation of the solution to the same Volterra integral equation (VIE) that appears in El Euch and Rosenbaum (2019, Math. Financ., 29, 3–38), but with the drift and mean reversion terms removed. The solution to this VIE satisfies a space–time scaling property which means we only need to solve this equation for the moment values of and so the rate function can be efficiently computed using an Adams scheme or a power series, and we compute a power series in the log‐moneyness variable for the asymptotic implied volatility which yields tractable expressions for the implied vol skew and convexity which is useful for calibration purposes. We later derive a formal saddle point approximation for call options in the Forde and Zhang (2017) large deviations regime which goes to higher order than previous works for rough models. Our higher‐order expansion captures the effect of both drift terms, and at leading order is of qualitatively the same form as the higher‐order expansion for a general model which appears in Friz et al. (2018, Math. Financ., 28, 962–988). The limiting asymptotic smile in the large‐maturity regime is obtained via a stability analysis of the fixed points of the VIE, and is the same as for the standard Heston model in Forde and Jacquier (2011, Finance Stoch., 15, 755–780). Finally, using Lévy's convergence theorem, we show that the log stock price tends weakly to a nonsymmetric random variable as (i.e., ) whose moment generating function (MGF) is also the solution to the Rough Heston VIE with , and we show that tends weakly to a nonsymmetric random variable as , which leads to a nonflat nonsymmetric asymptotic smile in the Edgeworth regime, where the log‐moneyness as , and we compute this asymptotic smile numerically. We also show that the third moment of the log stock price tends to a finite constant as (in contrast to the Rough Bergomi model discussed in Forde et al. (2020, Preprint) where the skew flattens or blows up) and the process converges on pathspace to a random tempered distribution which has the same law as the hyper‐rough Heston model, discussed in Jusselin and Rosenbaum (2020, Math. Finance, 30, 1309–1336) and Abi Jaber (2019, Ann. Appl. Probab., 29, 3155–3200).     

Demand for environmentally friendly vehicles: A review and new evidence

Although the need for more environmentally friendly vehicles was recognized some decades ago, this new market has not yet established itself. Consumer behavior needs to be studied to ascertain when people will decide to purchase hybrid or electric vehicles rather than conventional ones. An in-depth review of the state-of-the-art has identified existing deficiencies and these are addressed in this paper, proposing a new approach that is applied to the case of Santander in Spain. Emphasis is placed on the role of citizens in researching the local market and their requirements with respect to such vehicles; our model assumes variability in user preferences, an utmost requirement as concluded from the literature review. Results suggest that the highest demand for cleaner vehicles would be achieved in two ways: firstly, by penalizing conventional vehicles in terms of costs/km; secondly, by providing incentives directed at lowering the purchasing price of hybrid and electric vehicles. Finally, as demand becomes more elastic, the preferred strategy should initially focus on hybrid vehicles.     

Flexible customer willingness to pay for bundled smart home energy products and services

Energy markets are rapidly changing with smarter, connected, more reliable infrastructure and cleaner generation on the supply side, and more choice, greater control and enhanced flexibility for customers. This paper examines willingness to pay for bundled smart home energy products and information services, using data from a set of two discrete choice experiments that were part of a survey by the regional energy provider of upstate New York. To let the data reveal how preferences are distributed in the population, a logit-mixed logit model in willingness-to-pay space and a combination of observed and unobserved preference heterogeneity was specified and fitted. Results show that residents of Tompkins County are willing to pay more than in other counties for residential storage, and that for home energy management there is an important generational divide with millennials being much more likely to perceive the economic value in the smart energy technologies. The flexible logit-mixed logit estimates provide evidence of important heterogeneity in preferences: whereas most of the population has a positive—albeit rather low—valuation of smart energy products and services, there is a considerable percentage of customers with negative perceptions.     

Heterogeneous Demand and Supply for an Insurance‐linked Credit Product in Kenya: A Stated Choice Experiment Approach

We employ a discrete choice experiment to elicit demand and supply side preferences for insurance‐linked credit, a promising market‐based tool for managing agricultural weather risks and providing access to credit for farmers. We estimate preference heterogeneity using primary data from smallholder farmers and managers of lenders/insurers combined with household socio‐economic survey data in Kenya. We analyse the choice data using maximum simulated likelihood and Hierarchical Bayes estimation of a mixed logit model. Although there are some similarities, we find that there is conflicting demand and supply side preferences for credit terms, collateral requirements, and loan use flexibility. We also analyse willingness to buy and willingness to offer for farmers and suppliers, respectively, for the risk premium for different attributes and their levels. Identifying the preferred attributes and levels for both farmers and financial institutions can guide optimal packaging of insurance and credit providing market participation and adoption motivation for insurance‐bundled credit product.     

Western Canadian producers’ attitudes towards wheat breeding funding

In 2017, the federal government initiated national consultations for two new crop royalty systems that could be used to support additional crop breeding. In this study, we examine wheat growers’ attitudes towards breeding research and assess their inclination to contribute more to wheat variety development through checkoffs or enhanced royalties. We report a random effect probit estimation for a survey of 877 western Canadian wheat producers that took place from November 2018 to January 2019. We found at least 26% of survey respondents were willing to pay more to support additional wheat breeding. However, this support is contingent on the model for revenue collection and where additional revenue is invested. Producers generally favored increased checkoffs over enhanced royalty collection. Among the royalty options presented, the farm saved seed royalties mechanism had less support than the simpler to implement end-point royalties mechanism. We also found support is much higher if new royalty mechanisms are used to support university or government programs versus private breeding programs. This result suggests developing widespread producer support for enhanced royalty collection may require broader commitments for funding, ownership, and control of crop breeding programs.     

RISK‐MINIMIZATION FOR LIFE INSURANCE LIABILITIES WITH DEPENDENT MORTALITY RISK

In this paper, we study the pricing and hedging of typical life insurance liabilities for an insurance portfolio with dependent mortality risk by means of the well‐known risk‐minimization approach. As the insurance portfolio consists of individuals of different age cohorts in order to capture the cross‐generational dependency structure of the portfolio, we introduce affine models for the mortality intensities based on Gaussian random fields that deliver analytically tractable results. We also provide specific examples consistent with historical mortality data and correlation structures. Main novelties of this work are the explicit computations of risk‐minimizing strategies for life insurance liabilities written on an insurance portfolio composed of primary financial assets (a risky asset and a money market account) and a family of longevity bonds, and the simultaneous consideration of different age cohorts.     

Graphical Tools for Detecting Departures from Linear Mixed Model Assumptions and Some Remedial Measures

We review some results on the analysis of longitudinal data or, more generally, of repeated measures via linear mixed models starting with some exploratory statistical tools that may be employed to specify a tentative model. We follow with a summary of inferential procedures under a Gaussian set‐up and then discuss different diagnostic methods focusing on residual analysis but also addressing global and local influence. Based on the interpretation of diagnostic plots related to three types of residuals (marginal, conditional and predicted random effects) as well as on other tools, we proceed to identify remedial measures for possible violations of the proposed model assumptions, ranging from fine‐tuning of the model to the use of elliptically symmetric or skew‐elliptical linear mixed models as well as of robust estimation methods. We specify many results available in the literature in a unified notation and highlight those with greater practical appeal. In each case, we discuss the availability of model diagnostics as well as of software and give general guidelines for model selection. We conclude with analyses of three practical examples and suggest further directions for research.     

Spatial-temporal response patterns of tourist flow under entrance tourist flow control scheme

This paper explores the relationship between tourists' information demand about entrance tourist flow control schemes (ETFCS) and tourists' entrance transfer decision-making behavior, using the case study of the Summer Palace, one of the most important resort destinations in Beijing, China. After discussing tourists' decision-making behavior under ETFCS information, a revealed preference and stated preference survey (N = 1742 valid observations) were created and a joint choice model of tourist's entrance transfer and diversion entrance selection was established. Results show how various ETFCS are formulated and affect tourists' decision-making behavior under different traffic congestion. Sensitivity analysis reveals that tourists' entrance transfer decision-making behavior is related to the entry time of current crowded entrance and the time saved from the diversion entrance. Hence it is possible to formulate ETFCS in terms of tourist's spatial-temporal distribution in order to anticipate the levels of tourist intensity, especially during peak periods.     

The value of non-personally identifiable information to consumers of online services: evidence from a discrete choice experiment

We estimate the value of non-personally identifying information to consumers of online services through a discrete choice experiment based on hypothetical streaming video services. Non-personally identifying information for online services is typically information on the ways in and times at which customers use the service, and is distinct from personally identifying information such as email addresses or telephone numbers. For most of our survey respondents, we find no evidence that they were willing to pay to avoid sharing their non-personally identifying information with third parties. A smaller group of respondents never selected a service that shared information with third parties.