A STRUCTURAL RISK‐NEUTRAL MODEL FOR PRICING AND HEDGING POWER DERIVATIVES

We develop a structural risk‐neutral model for energy market modifying along several directions the approach introduced in Aïd et al. In particular, a scarcity function is introduced to allow important deviations of the spot price from the marginal fuel price, producing price spikes. We focus on pricing and hedging electricity derivatives. The hedging instruments are forward contracts on fuels and electricity. The presence of production capacities and electricity demand makes such a market incomplete. We follow a local risk minimization approach to price and hedge energy derivatives. Despite the richness of information included in the spot model, we obtain closed‐form formulae for futures prices and semiexplicit formulae for spread options and European options on electricity forward contracts. An analysis of the electricity price risk premium is provided showing the contribution of demand and capacity to the futures prices. We show that when far from delivery, electricity futures behave like a basket of futures on fuels.     

R&D Subsidies,Spillovers, and Privatization in Mixed Markets

We examine the use of subsidies to research and development (R&D) in a mixed and a private duopoly market. We show that the socially optimal R&D subsidy is increasing in the degree of spillovers, but it is lower in the private duopoly. The optimal R&D subsidy leads to an increase in total R&D and production; however, it does not lead to the equalization of per firm output and therefore to an efficient distribution of production costs. We also find that privatization of the public firm reduces R&D activity and welfare in the duopoly market. This result stands even when optimal R&D subsidies are provided.     

THE BIAS OF THE MULTIPLIER MATRIX WHEN SUPPLY AND USE TABLES ARE STOCHASTIC

The literature on stochastic input–output (I–O) analysis has paid considerable attention to the bias in the Leontief inverse. This paper extends previous studies by assuming supply and use tables (SUTs rather than I–O tables or input coefficients matrices) to be stochastic. This is a natural starting point because SUTs have become the basic data sources for I–O applications. In a Monte Carlo simulation experiment, a given SUT is randomized in two different ways and the effects are determined for eight different multiplier matrices. The analysis is carried out for Spain, Italy, the Netherlands, Germany and Finland, using their SUTs for 2006. The findings indicate that, in general, biases are statistically significant but negligibly small. This corroborates earlier findings obtained for stochastic I–O tables.     

The contribution of social tourism to sustainable tourism: a case study of seasonally adjusted programmes in Spain

Recent policy from the European Union has attempted to justify social tourism initiatives on the basis that they lead to a more sustainable tourism industry. However, the majority of latest research in the field has been focused on the benefits for participants, with the addition of some evidence on the economic impacts of such programmes on destinations, which have pointed towards sustainability outcomes including: a longer tourism season, more even spread of demand, and longer periods of employment for tourism workers. Yet there is a lack of direct evidence linking such programme to these outcomes. This paper aimed to explore this important disconnect between policy assumptions and evidence-based outcomes through an analysis of the deseasonalising effects of the Spanish social tourism programme for older people. The research found that this programme does have an effect on the seasonal nature of employment and economic activity in most regions studied, but that the huge volume of demand from international tourists in the high seasons masks the quantitative effects in the regions with the highest seasonal concentration of international tourists. Recommendations for policy and practice in sustainable tourism are made that are transferable to many countries and regions that adopt social tourism programmes.     

Farms’ technical inefficiencies in the presence of government programs*

We focus on determining the impacts of government programs on farms’ technical inefficiency levels. We use Kumbhakar's stochastic frontier model that accounts for both production risks and risk preferences. Our theoretical framework shows that decoupled government transfers are likely to increase (decrease) DARA (IARA) farmers’ production inefficiencies if variable inputs are risk decreasing. However, the impacts of decoupled payments cannot be anticipated if variable inputs are risk increasing. We use farm‐level data collected in Kansas to illustrate the model.     

Evolving splines and seasonal unit roots in weekly agricultural prices

The univariate statistical properties of agricultural price series need to be examined as a first step in the analysis of price transmission mechanisms. However, in the case of weekly price series, increasingly available, the testing procedures usually applied in this step are not suitable to deal with evolving seasonal effects. In this study, a method of testing for seasonal unit roots in weekly series of agricultural prices is described. When the deterministic seasonal component does not remain constant over time, the restricted evolving spline model (RESM) is shown to be a useful parametric formulation to capture the deterministic seasonal pattern. Therefore, the RESM model should be included as a deterministic component in auxiliary regression for unit root tests at seasonal frequencies. This proposal is applied to three weekly series of Canary Islands banana prices. From the standard seasonal unit root tests, the null hypothesis is failed to be rejected at the 5% or 10% significance level at some seasonal frequencies for each one of the series. Once critical values are obtained by simulation exercises when the RESM model is included, the hypotheses of unit root are rejected at each one of the seasonal frequencies for all of the three series.     

Spatial determinants of productivity growth on agri‐food Spanish firms: a comparison between cooperatives and investor‐owned firms

This study analyses the effect of the spatial factor, location, and interaction effects among peer companies, on the productivity growth of agri‐food companies in Spain. With this aim, we build a productivity growth index and apply a multiequational Seemingly Unrelated Regression on a sample of 344 Spanish cooperatives and investor‐owned firms for the period 2010–2012. Our findings show that agri‐food firms are influenced by spatial factors finding interesting differences between cooperatives and investor‐owned firms. With regard to the geographical location, cooperatives in the western of Spain show higher productivity growth rates, whereas investor‐owned firms in the northeast of Spain present better results. The interaction effect among closer peer companies is also a relevant factor to determine the productivity growth in agri‐food companies. This factor is more relevant for cooperatives than for investor‐owned firms.     

Three decades of productivity change in French beef production: a Färe‐Primont index decomposition

The Färe‐Primont index is used to evaluate total factor productivity (TFP) change and its components for a sample of French suckler cow farms in grassland areas in 1985–2014. The results reveal an increase in TFP of 6.6 per cent over the whole observation period, with technological progress being the major source of productivity growth. Meanwhile, efficiency decreased. Farms experienced great technological progress from 1991 to 2000. From a methodological point of view, the comparison with results obtained with Malmquist indexes shows similar trends but different magnitudes, with the Malmquist index overestimating the TFP and technological changes compared to the Färe‐Primont index. In addition, the use of a sequential approach that restricts technological change to being positive or null allows for the precise calculation of technology changes, disregarding the effects of external conditions that are captured in efficiency changes. Finally, the estimation of full dimensional efficient facets (FDEFs) that guarantees the positivity of all shadow prices used to assess the mix efficiency component of TFP change is promising.     

Interorganizational Trust and Technology Complexity: Evidence for New Technology‐Based Firms

Integrating the transaction cost economics and relational perspectives, this paper puts forward that technology complexity within new technology‐based firms negatively influences the level of interorganizational trust in key partner relationships. Using a data set of 105 key partner relationships of 59 new technology‐based firms, we find that the new technology‐based firm's level of trust in its key partners is lower when the level of technology complexity is high. Findings further show that both relationship and partner characteristics moderate the technology complexity—trust relationship. These results show that technology complexity as an appropriability mechanism becomes endogenous to collaboration, thereby extending the Teece framework.