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.     

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.

     

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.     

Modeling node heterogeneity in latent space models for multidimensional networks

Multidimensional network data can have different levels of complexity, as nodes may be characterized by heterogeneous individual-specific features, which may vary across the networks. This article introduces a class of models for multidimensional network data, where different levels of heterogeneity within and between networks can be considered. The proposed framework is developed in the family of latent space models, and it aims to distinguish symmetric relations between the nodes and node-specific features. Model parameters are estimated via a Markov Chain Monte Carlo algorithm. Simulated data and an application to a real example, on fruits import/export data, are used to illustrate and comment on the performance of the proposed models.     

Markups,import competition and exporting

This paper analyses the relationship between markups and international trade at the firm level using a large sample of French manufacturing firms for the period 1995–2007. In particular, the paper investigates the effect of increasing import competition from China on firms' price–cost margins and the way in which exporting interacts with this effect. The results show robust evidence that firms in more direct competition with Chinese imports decrease their markups. However, firms that become exporters experience a smaller reduction in their price–cost margins. Consistent with these findings, the results also show that firms facing tougher competition from China are more likely to start exporting to avoid such competitive pressures.     

Earnouts: The real value of disagreement in mergers and acquisitions

Earnout agreements link part of the payment for an acquired company to its future performance. Despite their option-like features, they cannot be valued using vanilla option-pricing methods. Two peculiar sources of risk affect these contracts: Bidder default before the earnout expiration (default risk) and potential litigation associated with earnouts (litigation risk). We developed an option-pricing model that encompasses these sources of risk, showing that counterparty and litigation risk can have a remarkable impact on earnout values. Our model's relevance is further enhanced by recent accounting standards that require contingent payments to be valued at fair value.     

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.     

Reinforced urn processes for credit risk models

We propose a Bayesian nonparametric model to estimate rating migration matrices and default probabilities using the reinforced urn processes (RUP) introduced in Muliere et al. (2000). The estimated default probability becomes our prior information in a parametric model for the prediction of the number of bankruptcies, with the only assumption of exchangeability within rating classes. The Polya urn construction of the transition matrix justifies a Beta distributed de Finetti measure. Dependence among the processes is introduced through the dependence among the default probabilities, with the Bivariate Beta Distribution proposed in Olkin and Liu (2003) and its multivariate generalization.     

Exploring the firm and country determinants of the voluntary adoption of integrated reporting

Information used to manage the business and support the decision‐making of stakeholders is being subject to an evolution. In this context, traditional financial reporting is considered not sufficient anymore. This has translated into a sharp increase in the number of firms that have begun to adopt emerging reporting practices. This study aims to examine the influence that both firm‐ and country‐specific characteristics have on the voluntary uptaking of integrated reporting internationally. In order to do so, it analyses a sample of 71 international listed companies that have adopted this reporting form in 2016. The results show that firms are more likely to implement integrated reporting if they are located in countries with a higher level of corruption perception and a better risk rating and that are considered as relatively more collectivist and feminist and with a long‐term orientation. Legal system has resulted to be not significant. As for firms' characteristics, large size, profitability, market‐to‐book ratio, and the size of the board are found to be significant variables. Moreover, the results indicate that the adoption of integrated reporting is not influenced by a higher level of leverage, firm efficiency and board diversity and independence.