Bayesian selection of technology assumptions for the transformation from supply-use to input–output tables

ABSTRACT

In the construction of input–output models from supply-use tables, technology assumptions disambiguate how an industry uses inputs in the production recipe of multiple outputs. This paper uses Bayes' theorem to select technology assumptions, taking into account empirical observations. The paper presents a formulation to explore hybrids between product and industry technology assumptions in product-by-product tables. We then present Markov chain Monte-Carlo techniques to implement the Bayesian method for selecting technology assumptions. We apply the method in a case study using Eurostat supply-use tables of 2004 and 2005, exhibiting a volume of secondary products of less than 13%, and 59 products and industries per country. The results show that the choice of technology is not important, given that there is no strong evidence in favour of any of them.     

Analyzing online reviews in hospitality: data-driven opportunities for predicting the sharing of negative emotional content

Hospitality is one of the sectors that are nowadays most heavily characterized by consumers’ tendency to share online reviews on dedicated digital platforms. While most past work has focused on understanding the effect of online reviews and ratings on consumers’ evaluation and purchase decisions, this research tackles the issue of what drives the sharing of certain types of online content. Specifically, we investigate the sharing of user-generated content characterized by negative emotional valence, and study the effect of two factors on the extent to which user-generated content contains negative emotions. One such factor is reviewer's expertise, while the other is hotel quality. Our analysis of 1200 TripAdvisor reviews on Italian hotels located in three major Italian cities confirm our hypothesis that expert reviewers might share reviews containing less intense negative emotional content compared to less expert reviewers especially when the hotel is of high quality. To support our hypothesis, we build on the research on psychological antecedents of word-of-mouth behaviour suggesting that expert consumers are particularly reluctant to share negative word-of-mouth to avoid projecting a negative image of themselves in social contexts, thus possibly damaging their reputation.     

金属增材制造专用材料发展现状

金属增材制造是一项全新的变革性制造技术,未来发展前景广阔。其下游应用领域尚未完全打开,存在一定的市场风险;我国金属增材制造用中低端材料产能过剩,但以钛、铝材为主的高端材料供给不足,仍然依靠进口,其制备技术基本被国外垄断。基于此,建议国内企业加强研发合作,利用行业内先进的技术资源,加速推进高端金属材料研发进程,同时能有效降低投资风险。     

Inter‐firm R&D collaborations and green innovation value: The role of family firms' involvement and the moderating effects of proximity dimensions

The present paper investigates the relationship between the involvement of family firms in R&D collaborations aimed at developing green solutions and the value of resulting innovations. To dig into this relationship, the moderating effects of two proximity dimensions (i.e., geographical distance and technological relatedness) are also assessed. Analyses are based on a sample of 156 joint patents classified into the “Alternative energy production” field, as defined by the International Patent Classification Green Inventory and successfully filed at the United States Patent and Trademark Office in the period 1997–2010 by publicly listed companies. According to our conjectures, results reveal a positive relationship between the involvement of family firms and green innovation value. Moreover, our findings show that this relationship is hindered when partners are geographically distant or technologically proximate. Eventually, we contribute to the literature on green innovation by unveiling under which conditions inter‐firm R&D collaborations lead to more valuable innovations.     

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.     

Stock Market Reaction to Monetary Policy: An Event Study Analysis of the Brazilian Case

This article examines the relationship between the monetary policy implemented by the Central Bank of Brazil and the stock market. We implement event study analysis and analyze the effect of the anticipated and unanticipated components of monetary policy decisions on the returns of the IBOVESPA index and 53 stocks. We find that monetary policy has a significant effect on the stock market, but is only responsible for a small proportion of market variation. The analysis at the sector level with expected returns identifies that the financial sector is the most affected by this policy, whereas with excess returns only industrial goods are significantly affected. Moreover, individual assets respond in a rather heterogeneous fashion to monetary policy; however, when we look at excess returns, we identify a reduction in the intensity and in the number of companies impacted by monetary policy. Finally, the monetary shock is explained by unanticipated variations in the unemployment rate, in the Industrial Production Index, in the General Market Price Index, and in the Broad Consumer Price Index.     

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...     

Contemporaneous ADR pricing: intraday dynamics during overlapping trading hours

We contribute to the literature by identifying and accurately measuring the drivers of American depositary receipt (ADR) returns contemporaneously across various global time zones. We consider ADRs as two inherently distinct asset classes – stocks and currencies – bundled into one. Throughout, we use a relatively refined, focused, and synchronized minute-by-minute data set on ADRs and all other variables. ADRs from all countries with regular trading hours that overlap with those of the US are considered individually and in clusters. We analyze the interplay of several factors that influence ADRs pricing patterns. Further, we investigate whether such patterns vary by currency, ADR, industry, and emerging/developed market classifications. Our findings indicate that synchronized returns on underlying shares comprise 68.5–74% of the explained returns in ADRs. The remaining 31.5–26% of returns are generated by movements in currency rates. These results are robust across the several models and estimation methods employed. Our findings also show persistent small price discrepancies between ADRs and dollar-adjusted underlying shares on a minute-by-minute basis, implying possible arbitrage opportunities. However, we conclude that trading and ADR conversion costs render such opportunities unattractive.     

Intertemporal substitution in the Spanish economy: Evidence from regional data

This paper studies the intertemporal substitution in consumption and leisure for the Spanish economy by estimating the first‐order conditions of an individual optimization model with regional and aggregate data. While first‐order conditions determining intertemporal substitution in consumption show a good econometric fit, and the value we obtain for the intertemporal elasticity of substitution is similar to previously available results, the econometric fit of the intertemporal condition in leisure indicates that the behaviour of the Spanish labour supply over the cycle is more complex than can be explained by the canonical intertemporal choice model.     

The role of venture capitalist to enhance the growth of Spanish and Italian university spin-offs

The establishment of spin-offs to commercialise university knowledge/technology is a potential mechanism to promote economic and innovative development. Nevertheless, University Spin-Offs (USOs) are usually resource-constrained, especially in obtaining funding, limiting their growth. Venture Capital (VC) investors play an important role in the financing and the improvement of their managerial skills, which are critical for firm growth. This paper aims to explore both the effect of VC partners on the USOs’ growth and the cross-national differences in the role played by them. To study both issues, we empirically analysed 516 Spanish and 904 Italian USOs created by 50 Spanish and 57 Italian universities, respectively, and observed them between 2005 and 2013. The results showed different effects in the Spanish and Italian cases. While in Spain the presence of VC partners positively affects the USOs’ growth, in Italy there is not a significant effect. This evidence calls for systematic policies by public administrations and universities to foster USO growth.