Innovating for Good in Opportunistic Contexts: The Case for Firms’ Environmental Divergence

Journal of Business Ethics - Opportunistic behaviors are considered ethically and strategically troublesome since they disrupt otherwise mutually beneficial relationships. Previous literature has...     

Claims Reserving with a Stochastic Vector Projection

In the last three decades, a variety of stochastic reserving models have been proposed in the general insurance literature mainly using (or reproducing) the well-known Chain-Ladder claims-reserving estimates. In practice, when the data do not satisfy the Chain-Ladder assumptions, high prediction errors might occur. Thus, in this article, a combined methodology is proposed based on the stochastic vector projection method and uses the regression through the origin approach of Murphy, but with heteroscedastic errors instead, and different from those that used by Mack. Furthermore, the Mack distribution-free model appears to have higher prediction errors when compared with the proposed one, particularly, for data sets with increasing (regular) trends. Finally, three empirical examples with irregular and regular data sets illustrate the theoretical findings, and the concepts of best estimate and risk margin are reported.     

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.     

Household Determinants of the Adoption of Improved Cassava Varieties using DNA Fingerprinting to Identify Varieties in Farmer Fields: A Case Study in Colombia

We examine factors affecting the adoption of improved cassava varieties of 217 households in the Cauca Department in southwest Colombia. Using DNA fingerprinting through Single Nucleotide Polymorphisms (SNPs), we identified different cultivars in farmers fields. We also used this information to remove possible bias in the adoption model that could have resulted from a misclassification of improved varieties (IVs). As a result, we found that farmers substantially overestimate their use of IVs and there are important differences in the determinants of adoption between farmer self‐identification and DNA fingerprinting. This finding implies that the incorporation of DNA fingerprinting in IV adoption studies is important to ensure the accuracy of future agricultural economic research and the relevance of subsequent policy recommendations.     

Educational supply policies: distortions and labor market performance

Journal of Economics - Is it always worth implementing an open enrollment policy? And implementing policies that pursue equity in school supply? What is the impact of these two policies on the...     

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.     

高校知识溢出与企业创新绩效

本文利用全样本数据探讨了作为创新和知识溢出微观主体的高校对企业创新绩效的影响。本文通过ArcGIS测算了2007-2015年上市公司所在地周边全部高校数量，并以企业研发投入金额、发明专利衡量企业创新水平，利用Anselin et al（2000）的KPF方程，采用双聚类OLS检验高校知识溢出对企业创新行为的影响效应与机制。研究发现：第一，高校知识溢出对企业研发创新投入和有效创新产出均具有显著促进作用；第二，知识溢出效应具有显著的地理邻近性特征，而行政边界关联影响较弱；第三，高校知识溢出通过提高企业研发投入，提升员工和管理层人力资本，进而影响企业创新绩效。进一步研究表明，空间异质性、高校异质性、企业异质性、中心城市集聚效应、高铁开通等因素导致高校知识溢出效应存在差异。     

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...     

The contribution of granular and fundamental comparative advantage to European Union countries' export specialisation

This paper analyses the contribution of fundamental comparative advantage (a country-specific component) and granular comparative advantage (a firm-specific component) to European Union countries' export specialisation. We find that, on average, granular comparative advantage may explain export specialisation in 29% of industries, which account for 47% of total exports. We also show that 60% of the variation in export specialisation across countries and industries may be explained by granular comparative advantage. These results highlight that some outstanding firms may play a very important role in explaining European Union countries' export specialisation.     

Three decades of research on corporate governance and R&D investments: a systematic review and research agenda

This paper reviews and systematizes the empirical research on the nexus between corporate governance (CG) and investments in research and development (R&D) published in leading business, management, economics and finance journals over the past 30 years. We find that CG is key in shaping R&D investments. Moreover, the effects of both firm- and country-level CG are important for both internal and external R&D investments. Drawing on our review, we welcome future studies to examine the effect of the interplay between various CG mechanisms and different types of R&D investments, and possibly identify mediating variables besides the moderating ones. Moreover, we highlight the need for future interdisciplinary studies, as well as investigations of private companies and across developing countries. Whenever causal interpretations are attempted, both sample selection and endogeneity problems should be addressed, along with testing the CG-R&D investment nexus for nonlinear dynamics. The implications of the study for both theory and practice are also discussed.