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.     

A Stochastic Model with Penalized Coefficients for Spatial Price Comparisons: An Application to Regional Price Indexes in Italy

This paper focuses on a new strand of research that uses stochastic approach for making spatial price comparisons. We propose a novel method to account for the presence of spatial dependencies in consumer prices and consequently in price indexes by imposing penalization conditions on the estimation of traditional CPD models leading to the spatially-penalized country-product-dummy (SP-CPD) model. The paper proposes an appropriate estimation strategy, which enables us to simultaneously estimate all the parameters in the model, including the smoothing parameter of the penalization term instead of determining it externally. In order to estimate spatial price indexes for areas lacking in price data, we suggest applying the kriging methodology to the price indexes obtained from the SP-CPD model. This new approach is applied to official Italian CPI data for constructing regional spatial price indexes for 2014. The results show that price levels are higher in the Northern-Central regions than in the South.     

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.     

Growth machines and social movements in mature tourist destinations Costa del Sol-Málaga

Abstract

The purpose of this study is to analyse the new processes of tourism growth and its conflicts from the perspective of social movements. First, the urban growth machine analysis model is applied by the systematisation of six projects. Second, the resistance movements against those projects and whether this resistance could be the start of local tourism degrowth policies are examined. The methodology is qualitative, based on documentary analysis, participatory observation, discussion groups and interviews. The case study is the destination of Costa del Sol-Málaga. The results enable the development of the urban growth machine model in tourist destinations. Meanwhile, social movements demystify the argument based on neoclassical economic progress. The social movements condemn the effects of large-scale top-down projects, and implement alternative bottom-up proposals. Although the social movements do not reject tourism, they call for greater control over its impact, denounce unlimited growth, overtourism and the loss of urban quality of life. These movements advocate a lifestyle linked to the everyday space, which they believe is threatened by excessive urban-tourism growth. They are a symptom of the need to devise a proposal using the principles of degrowth.     

Interest rates,inflation, and the Fisher effect in China

The paper estimates the relationship between the nominal Treasuries rate and inflation in China. The dynamic econometric analysis yields a preferred, automatically reduced, empirical model revealing a Fisher effect. But the results are sensitive to using different sub-samples encompassed in the decade-and-a-half period following the disassociation of Treasuries from the People’s Bank of China administered interest rates at the end of the 1990s.     

Performance Measures in Dose-Finding Experiments

In the first phase of pharmaceutical development, and assuming that the probability of positive response increases with dose, the main statistical goal is to estimate a percentile of the dose–response function for a given target value $\mathrm{\Gamma }$. We compare the Maximum Likelihood and centred isotonic regression estimators of the target dose and we discuss several performance criteria to assess inferential precision, the amount of toxicity exposure and the trade-off between them for a set of some exemplary adaptive designs. We compare these designs using graphical tools. Several scenarios are considered using simulation, including the use of several start-up rules, the change of slope of the dose-toxicity function at the target dose and also different theoretical models, as logistic, normal or skew-normal distribution functions.     

Valuing American-style options under the CEV model: an integral representation based method

Review of Derivatives Research - This article derives a new integral representation of the early exercise boundary for valuing American-style options under the constant elasticity of variance (CEV)...     

A spatial approach to the FDI-growth nexus in Spain: Dealing with the headquarters effect

This paper examines the effects of inward FDI on economic growth across the Spanish regions over the period 1996–2013, paying particular attention to the ‘headquarters effect’, namely that FDI is not always registered where it is effectively made but in the region in which the firm’s headquarters is located. By estimating a panel Spatial Durbin Model to allow for the detection of spatial spillovers, two main findings are reported. First, FDI does foster economic growth. Second, only when the headquarters effect is properly addressed do spatial spillovers arise. Hence, this effect is masking the impact of regional FDI spillovers on growth, which affects the reliability of the results and, consequently, FDI policies choice. Importantly, the results are: a) robust to the way of computing the headquarters effect; b) independent of the spatial weight matrix specification; and c) confirmed when splitting FDI into different industrial and service branches.     

Volatility of volatility is (also) rough

Using high-frequency data for major volatility indexes, we compute the volatility of volatility and show that its logarithm follows a fractional Brownian motion with Hurst parameter smaller than 1/2 thereby extending to the volatility asset class the recent findings obtained for the equity index markets. The results confirm that the volatility of volatility is a rough process and it possesses the long memory property. We also show that the correlation between the volatility and the volatility of volatility is positive, consistent with observations in the volatility option market. Lastly, a robustness check using volatility futures confirms the findings.