The short‐time behavior of VIX‐implied volatilities in a multifactor stochastic volatility framework

We consider a modeling setup where the volatility index (VIX) dynamics are explicitly computable as a smooth transformation of a purely diffusive, multidimensional Markov process. The framework is general enough to embed many popular stochastic volatility models. We develop closed‐form expansions and sharp error bounds for VIX futures, options, and implied volatilities. In particular, we derive exact asymptotic results for VIX‐implied volatilities, and their sensitivities, in the joint limit of short time‐to‐maturity and small log‐moneyness. The expansions obtained are explicit based on elementary functions and they neatly uncover how the VIX skew depends on the specific choice of the volatility and the vol‐of‐vol processes. Our results are based on perturbation techniques applied to the infinitesimal generator of the underlying process. This methodology has previously been adopted to derive approximations of equity (SPX) options. However, the generalizations needed to cover the case of VIX options are by no means straightforward as the dynamics of the underlying VIX futures are not explicitly known. To illustrate the accuracy of our technique, we provide numerical implementations for a selection of model specifications.     

Does apprenticeship improve job opportunities? A regression discontinuity approach

In Italy the main difference between apprentices and other types of temporary workers is that apprentices must receive firm-provided training. The firm incentive in hiring apprentices consists in paying lower wages and labour taxes. Using an Italian administrative dataset containing information on the jobs started between January 2009 and June 2012, we estimate the effect of apprenticeship on the hazard function to a permanent job. Identification is based on a regression discontinuity design. We find that, for 29-year-old workers, apprenticeships are “long entrance halls” towards permanent contracts, especially within the firm where the apprenticeship is performed.

     

Market Power and Patent Strategies: Evidence from Renaissance Venice

This paper exploits the introduction of the first regularized patent system, which appeared in the Venetian Republic in 1474, to examine the factors shaping inventors’ propensity to use a new form of intellectual property. We combine detailed information on craft guilds and patents in Renaissance Venice and show a negative association between patenting activity and guild statutory norms that strongly restricted entry and price competition. Our analysis shows that the heterogeneity in patenting activity documented by the industrial organization literature is not a special feature of modern technologies, but is rather a persistent phenomenon affected by market power.     

A Self‐Tuning Model for Smart Manufacturing SMEs: Effects on Digital Innovation

With the changing way people live, communicate, and work, enterprises are striving to shift their existing business model into a “self‐tuning” one. Enterprises are becoming more agile, adaptive, and ambidextrous in order to boost innovation in the current digital transformation era. Nowadays, “digital innovation” is closely associated with Industry 4.0 enablers and smart enterprises. Prior research has shown that while multinational enterprises—across many sectors—have already embraced the aforementioned advancements, their adoption by small and‐medium‐sized enterprises (SMEs) has so far taken place mainly in the manufacturing sector. Thus, based on a sample of 280 self‐tuned smart manufacturing SMEs and having utilized the structural equation modeling (SEM), this study was aimed to investigate how digital innovation is influenced by the three pillars of self‐tuning models—agility, adaptation, and ambidexterity. Our paper has focussed on the digital systems in which SMEs, spurred by networking and open innovation solutions, operate and innovate in response to external triggers, displaying a balance between exploration and exploitation, and a strong agile capacity.     

THE IMPACT OF THE EU EMISSIONS TRADING SYSTEM ON COMPETITIVENESS AND CARBON LEAKAGE: THE ECONOMETRIC EVIDENCE

This paper carefully surveys the econometric literature that tests for competitiveness effects and related carbon leakage caused by the EU Emissions Trading System (EU ETS). The results of this literature tell us that to date there is no evidence of the EU ETS having had widespread negative or positive effects on the competitiveness of regulated firms, nor is there evidence of significant carbon leakage. However, the paper also identifies three important caveats to this general conclusion. Firstly, the evidence we have still largely refers to the first two trading periods, namely Phases I (2005–2007) and II (2008–2012). Secondly, some heterogeneity of estimated effects is observed, but patterns, notably sectoral patterns, hardly emerge. Thirdly, very little explored is whether the EU ETS has had long-term effects on the economy via investment leakage or firm dynamics. Further empirical studies investigating these long-term effects are particularly desirable.     

Feeding management of dairy cattle affect grassland dynamics in an alpine pasture

The effect of different supplementary feeding rates for grazing cattle on high-altitude pastures dynamics was evaluated. A field experiment was carried out during three years in a subalpine pasture area of the Eastern Alps. The investigated pasture area was 40?ha, located between 1820 and 2230?m?a.s.l. Two paddocks were chosen in the experiment and two herds of 12 cattle each were kept in the two enclosures for 5 weeks. For the first herd (HS), the supplementary feeding rate was 4.8?kg?OM?head^?1 per day, while for the second herd (LS), the rate was 1.6?kg?OM?head^?1 per day. The amount of herbage consumed by each cattle was determined using the n-alkane technique. To monitor the pasture vegetation dynamics, eight metal exclusion cages were placed in each paddock to determine herbage growth, utilization rates, vegetation composition and animal grazing selectivity. Grazing behaviour of dairy cattle, in terms of herbage intake and species selection was affected by the different feeding rates. Cattle grazing Paddock HS consumed 1.9?kg?OM?day^?1 of herbage less than Paddock LS. In the LS paddock, cattle grazed higher phytomass rates. When the animals were fed by higher concentrate rates, a more selective grazing seemed to significantly increase the pasture necromass component. The lower grazing selectivity favoured the development of species as Nardus stricta and Deschampsia caespitosa, which are well known for their low palatability. Distinct vegetation dynamic patterns were observed, with a reduction of hair grass and an increase of legumes in the Paddock LS.     

Objective methods for graphical structural learning

Graphical models are used for expressing conditional independence relationships among variables by the means of graphs, whose structure is typically unknown and must be inferred by the data at hand. We propose a theoretically sound Objective Bayes procedure for graphical model selection. Our method is based on the Expected-Posterior Prior and on the Power-Expected-Posterior Prior. We use as input of the proposed methodology a default improper prior and suggest computationally efficient approximations of Bayes factors and posterior odds. In a variety of simulated scenarios with varying number of nodes and sample sizes, we show that our method is highly competitive with, or better than, current benchmarks. We also discuss an application to protein-signaling data, which wieldy confirms existing results in the scientific literature.     

Cognitive flexibility and adaptive decision‐making: Evidence from a laboratory study of expert decision makers

Research Summary : How can strategic decision makers overcome inertia when dealing with change? In this article we argue that cognitive flexibility (i.e., the ability to match the type of cognitive processing with the type of problem at hand) enables decision makers to achieve significantly higher decision‐making performance. We show that superior decision‐making performance is associated with using semiautomatic Type 1 cognitive processes when faced with well‐structured problems, and more deliberative Type 2 processes when faced with ill‐structured problems. Our findings shed light on the individual‐level mechanism behind organizational adaptation and complement recent work on strategic inertia. In addition, our findings extend management studies that have stressed the relevance of cognitive flexibility for responding to the demands of increasingly open, flexible, and rapidly changing organizations. Managerial Summary : Humans are creatures of habits. We tend to prefer known courses of action over new ones. In many cases, habits are good. However, when things change in unpredictable ways, the past may not be good guidance for the future. We argue that “cognitive flexibility”—the ability of understanding when to rely on habits vs. when to explore new courses of action—enables managers to switch from a “fast” decision mode, based on habits, to a “slow,” more deliberate decision mode that facilitates the exploration of new courses of action. Managers high in cognitive flexibility reflect on the situation at hand, recognize and value diversity in viewpoints, and integrate such diversity in their own decision processes. By valuing diversity, they are more likely to overcome inertia.