Pollution Abatement Subsidies and the Eco-Industry

This paper considers the combination of pollution taxes and abatement subsidies when some polluting firms procure their abatement goods and services from an oligopolistic eco-industry. The regulator must here cope with two simultaneous price distortions: one that comes from pollution and the other which is caused by the eco-industry’s market power. In this context, we show that taxing emissions while subsidizing polluters’ abatement efforts cannot lead to first-best, but the opposite occurs provided it is the eco-industry’s output which is subsidized. When public transfers also create distortions, welfare can be higher if the regulator uses only an emission tax, but subsidizing abatement suppliers while taxing emissions remains optimal when the eco-industry is concentrated.     

Job and worker flows in high adjustment cost settings

This paper analyses the relationship between the size of adjustment costs and the intensity of labor market flows. I argue that high adjustment costs inhibit adjustment to temporary shocks, leaving adjustment to long-lived shocks unchanged. Worker turnover is also reduced because of the negative impact that adjustment costs have on churning.Received: January 2002, Accepted: November 2002, JEL Classification: J23, J63I am grateful to the FCT for funding this research (research grant Praxis/PCSH/C/CEG/13/96), and to Pedro Portugal, Daniel Hamermesh and two anonymous referees for helpful comments on earlier versions of this paper. I thank the Department of Statistics at the Ministry of Labor for providing the data. CETE is supported by the FCT.     

STOCK MARKET CRASH AND EXPECTATIONS OF AMERICAN HOUSEHOLDS

This paper utilizes data on subjective probabilities to study the impact of the stock market crash of 2008 on households' expectations about the returns on the stock market index. We use data from the Health and Retirement Study that was fielded in February 2008 through February 2009. The effect of the crash is identified from the date of the interview, which is shown to be exogenous to previous stock market expectations. We estimate the effect of the crash on the population average of expected returns, the population average of the uncertainty about returns (subjective standard deviation), and the cross-sectional heterogeneity in expected returns (disagreement). We show estimates from simple reduced-form regressions on probability answers as well as from a more structural model that focuses on the parameters of interest and separates survey noise from relevant heterogeneity. We find a temporary increase in the population average of expectations and uncertainty right after the crash. The effect on cross-sectional heterogeneity is more significant and longer lasting, which implies substantial long-term increase in disagreement. The increase in disagreement is larger among the stockholders, the more informed, and those with higher cognitive capacity, and disagreement co-moves with trading volume and volatility in the market.     

An algorithm for resource allocation with constraints in an input-output framework

In a large corporation or at the national level, planning involves a large number of inter-related activities competing for the same resources. In spite of its rather restrictive assumptions, Leontief's Input-Output model is still one of the best tool for the study of physical and financial flows between activities or economic sectors. A simple algorithm to find its solution when the available resources are limited is presented in this paper. The properties of that algorithm that was incorporated in an inter-industrial model built in Venezuela are proven and are followed by examples of application.

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Riassunto In grandi imprese o in sistemi economici nazionali la pianificazione riguarda un numero elevato di attività interrelate che fanno uso delle stesse risorse. Nonostante le ipotesi di base piuttosto restrittive, il modelloinput-output di Leontief è ancora uno degli strumenti più efficaci per lo studio dei flussi fisici e finanziari tra attività o settori economici.In questo lavoro viene presentato un semplice algoritmo per individuare la soluzione d'un problema di pianificazione quando sono limitati gli ammontari delle risorse. Sono dimonstrate alcune proprietà di questo algoritmo, che fu impiegato su un modello di relazioni interindustriali costruito in Venezuela e sono fornite alcune applicazioni esemplificatrici.

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Versione definitiva pervenuta il 14-2-1983     

A metafrontier directional distance function approach to assessing eco-efficiency

This paper uses directional distance functions to extend the non-parametric metafrontier approach to efficiency measurement proposed by O’Donnell et al. (Empir Econ 34:231–255, 2008) to the assessment of technological differences in eco-efficiency between groups of producers. Furthermore, eco-efficiency is assessed at the level of specific environmental pressure management. This methodology is applied to a sample of Spanish olive producers that belong to both traditional mountain and traditional plain growing systems. We find great potential for both olive growing systems to reduce environmental pressures. In terms of pressures on natural resources, the most eco-efficient technology is the traditional plain system, while the traditional mountain system is the most eco-efficient when considering pressures on biodiversity. These results might help policymakers design strategies to improve the performance of olive growing and meet the demands of society regarding the economic and ecological functions of this farming activity.     

Modelling spatial regimes in farms technologies

We exploit the information derived from geographical coordinates to endogenously identify spatial regimes in technologies that are the result of a variety of complex, dynamic interactions among site-specific environmental variables and farmer decision making about technology, which are often not observed at the farm level. Controlling for unobserved heterogeneity is a fundamental challenge in empirical research, as failing to do so can produce model misspecification and preclude causal inference. In this article, we adopt a two-step procedure to deal with unobserved spatial heterogeneity, while accounting for spatial dependence in a cross-sectional setting. The first step of the procedure takes explicitly unobserved spatial heterogeneity into account to endogenously identify subsets of farms that follow a similar local production econometric model, i.e. spatial production regimes. The second step consists in the specification of a spatial autoregressive model with autoregressive disturbances and spatial regimes. The method is applied to two regional samples of olive growing farms in Italy. The main finding is that the identification of spatial regimes can help drawing a more detailed picture of the production environment and provide more accurate information to guide extension services and policy makers.     

Open interest,volume, and volatility: evidence from Taiwan futures markets

This paper examines the relationships amongst volatility, total trading volume (TVOL) and total open interest (TOI) for three Taiwan stock index futures markets as well as the role of the latter two variables in the dynamics of GARCH modeling and forecasting. From both ex-post and ex-ante perspectives, we study this issue by using the VAR model and augmented GARCH-type models, respectively. For the GARCH-type models, we employ both symmetric and asymmetric models augmented with lagged logs in TOI and/or TVOL. We find that whether addition of these two variables helps the basic GARCH models predict future volatility depends upon the sample period examined for all three sets of futures. Nonetheless, the best three models for out-of-sample volatility forecasting in the MSE sense are generally the augmented models for all sub-intervals and all three futures contracts.