Pollution in strategic multilateral exchange: Taxing emissions or trading on permit markets?

We introduce polluting emissions in a sequential noncooperative oligopoly model of bilateral exchange. In one sector, a leader and a follower use polluting technologies which create negative externalities on the payoffs of strategic traders who belong to the other sector. By modeling emissions as a negative externality, we show that the leader pollutes more (less) than the follower when strategies are substitutes (complements). Then, we consider the implementation of public policies to control the levels of emissions, namely, two taxation mechanisms and a permit market. We study the effects of these public policies. Moreover, we determine the conditions under which these public policies can implement a Pareto-improving allocation.     

Incomplete information,idiosyncratic volatility and stock returns

When investors have incomplete information, expected returns, as measured by an econometrician, deviate from those predicted by standard asset pricing models by including a term that is the product of the stock’s idiosyncratic volatility and the investors’ aggregated forecast errors. If investors are biased this term generates a relation between idiosyncratic volatility and expected stocks returns. Relying on forecast revisions from IBES, we construct a new variable that proxies for this term and show that it explains a significant part of the empirical relation between idiosyncratic volatility and stock returns.     

Globalisation,industrial diversification and productivity growth in large European R&D companies

This paper aims to assess the impact of both geographic and industrial diversification of economic activities on the productivity performance of large European R&D Multinational Enterprises (MNEs). Based on the worldwide subsidiaries of these firms, we measure the performance of the firms according to their level of industrial diversification and globalisation that we proxy with the presence and importance of subsidiaries in the EU, North America and Asia–Pacific regions. The sample consists of large R&D firms that represent about 80 % of total European R&D. In general, the results indicate a positive impact from globalisation on firms’ R&D productivity, especially in the US, while a negative impact for industrial diversification is found.     

Networks,weak signals and technological innovations among SMEs in the land-based transportation equipment sector

On apprend plus par la conversation des Doctes,

que par la lecture de leurs livres

Les épistres de Seneque

Translation by François de Malherbe,

Paris, Anthoine de Sommaville, 1639, p. 21

Small and medium-sized enterprises, because of their limited resources, use a variety of sources and are linked to different networks to obtain the information they need to develop their strategy and then to gradually organize their environment. Among other things, networks keep them up-to-date with changes in the economy and allow them to take advantage of opportunities to innovate, thus remaining ahead of their competitors. The networks – personal or business – with which these firms interact the most are usually geographically or sociologically close by, embedded in the environment, and are known as strong tie networks. They generally supply signals in a familiar language, based on habit as well a good reciprocal knowledge, which are easy to understand. In addition to this, however, the most dynamic firms also have contacts with weak tie networks, which are further removed from the usual behaviours of entrepreneurs and provide weak signals that, while difficult to grasp and decode, nevertheless offer new, pre-competitive information that can support major innovations. Very little empirical research has been done so far to test the probability of this theory. This paper reports on the results of a survey involving 147 SMEs, all in the land-based transportation equipment sector. It confirms the importance of weak tie networks as opposed to other types of networks, recognizing their complementary contribution to technological innovation. The organization's absorptive capacity is also found to be a significant intermediary factor in taking advantage of weak tie networks.     

Random walks,liquidity molasses and critical response in financial markets

Stock prices are observed to be random walks in time despite a strong, long-term memory in the signs of trades (buys or sells). Lillo and Farmer have recently suggested that these correlations are compensated by opposite long-ranged fluctuations in liquidity, with an otherwise permanent market impact, challenging the scenario proposed in Quantitative Finance, 2004, 4, 176, where the impact is instead transient, with a power-law decay in time. The exponent of this decay is precisely tuned to a critical value, ensuring simultaneously that prices are diffusive on long time scales and that the impact function is nearly lag independent. We provide new analysis of empirical data that confirm and make more precise our previous claims. We show that the power-law decay of the bare impact function comes both from an excess flow of limit order opposite to the market order flow, and to a systematic anti-correlation of the bid–ask motion between trades, two effects that create a ‘liquidity molasses’ which dampens market volatility.     

Taxation of a Polluting Non-renewable Resource in the Heterogeneous World

This paper extends the literature on the taxation of polluting exhaustible resources by taking international heterogeneities and national tax-setting into account. We propose a two-country Romer model of endogenous growth in which the South is endowed with the stock of an essential polluting non-renewable resource and world economic growth is driven by a northern research sector. We consider the stock of pollution as affecting global welfare. First, we characterize the optimal environmental taxation policies. Second, we examine the impacts of national taxes. Their time profile determines the extraction path, the dynamics of pollution accumulation and that of world output. Their respective levels entail inter-country interactions by altering the efficiency of the world resource allocation, the tax revenues and the resource rents. We study isolatedly the distortional and distributional effects of local taxes. Then, we completely assess the overall impact of a unilateral tax increase. Finally, we find that, even if heterogeneous countries coordinate their taxation policies to correct the global environmental problem, their divergent strategic interests cause another global, non-environmental distortion in the allocation of the resource.     

Sarmanov Family of Bivariate Distributions for Multivariate Loss Reserving Analysis

The correlation among multiple lines of business plays a critical role in aggregating claims and thus determining loss reserves for an insurance portfolio. We show that the Sarmanov family of bivariate distributions is a convenient choice to capture the dependencies introduced by various sources, including the common calendar year, accident year, and development period effects. The density of the bivariate Sarmanov distributions with different marginals can be expressed as a linear combination of products of independent marginal densities. This pseudo-conjugate property greatly reduces the complexity of posterior computations. In a case study, we analyze an insurance portfolio of personal and commercial auto lines from a major U.S. property-casualty insurer.     

Forecasting electricity spot prices using time-series models with a double temporal segmentation

The French wholesale market is set to expand in the next few years under European pressure and national decisions. In this article, we assess the forecasting ability of several classes of time-series models for electricity wholesale spot prices at a day-ahead horizon in France. Electricity spot prices display a strong seasonal pattern, particularly in France, given the high share of electric heating in housing during winter time. To deal with this pattern, we implement a double temporal segmentation of the data. For each trading period and season, we use a large number of specifications based on market fundamentals: linear regressions, Markov-switching (MS) models and threshold models with a smooth transition. An extensive evaluation on French data shows that modelling each season independently leads to better results. Among nonlinear models, MS models designed to capture the sudden and fast-reverting spikes in the price dynamics yield more accurate forecasts. Finally, pooling forecasts give more reliable results.     

On the realized volatility of the ECX CO2 emissions 2008 futures contract: distribution, dynamics and forecasting

This article documents the conditional and unconditional distributions of the realized volatility for the 2008 futures contract in the European climate exchange (ECX), which is valid under the EU emissions trading scheme (EU ETS). Realized volatility measures from naive, kernel-based and subsampling estimators are used to obtain inferences about the distributional and dynamic properties of the ECX emissions futures volatility. The distribution of the daily realized volatility in logarithmic form is shown to be close to normal. The mixture-of-normals hypothesis is strongly rejected, as the returns standardized using daily measures of volatility clearly departs from normality. A simplified HAR-RV model (Corsi in J Financ Econ 7:174–196, 2009) with only a weekly component, which reproduces long memory properties of the series, is then used to model the volatility dynamics. Finally, the predictive accuracy of the HAR-RV model is tested against GARCH specifications using one-step-ahead forecasts, which confirms the HAR-RV superior ability.