The Extent of Voluntary Information in the Annual Report and the Share Price Volatility： Application of DEA and SFA on the French Market

In the current paper, the authors investigate empirically the relationship between the share price volatility and the amount of voluntary information disclosed in the corporate annual report. The authors use the data envelopment analysis （DEA） and the stochastic frontier analysis （SFA） models on a sample of 50 listed French firms belonging to the Soci6t6s des Bourses Fran^aises （SBF250） index from 2004 to 2008. The authors focus on the extent of voluntary disclosure in the annual reports that have been measure by using a composite disclosure index. Then, the authors study the relevance of disclosure policies through the ability of the voluntary disclosure level to effectively reduce the share price volatility. The findings of DEA and SFA provide, in average, highly efficient scores of the sample, reveal the several dispositions taken by the French Exchange Market authorities and the initiative of French firms to improve the market stability. In addition, the findings highlight, in average, stability of the firms＇ efficiency scores over the studied period. The authors explain these findings by the stability of corporate disclosure policy as suggested in previous literature （e.g., Botosan, 1997）. However, there are some differences between the findings of SFA and DEA models.

Is Larger Scale Better? Evidence from Rice Farming in Jianghan Plain

Small-scale household agricultural production has been in conflict with China＇s agricultural modernization.In the context of vigorously promoting rural land circulation and moderate scale management nationwide,research on the relationship between farm size and scale efficiency has become increasingly important.In this paper,we use the ＂DEA-OLS＂ two stage method to analyze data from 368 surveys of rice farming households in the Jianghan Plain.The scale efficiency of rice farming was calculated,and the relationship between farm size and scale efficiency investigated.The results indicate that（1） the rice farm size is generally small in Jianghan Plain,with an average of 0.77 ha.The average scale efficiency is 0.88,and it is the main factor limiting an increase in comprehensive technical efficiency.Moreover,88.32% of households are in the stage of increasing returns to scale.（2） There is a stable inverted ＂U＂ type relationship between rice farm size and scale efficiency.Considering characteristics of the householder,the household and land quality,the maximum scale efficiency corresponds to a household with 5 ha of rice farm.（3） Among householder characteristics,age has a significant negative influence on scale efficiency,and scale efficiency is lower for a household whose householder is engaged in non-farm work than for one whose householder is devoted to farming.As for land quality,there was a significant positive effect of irrigation on scale efficiency.Among family characteristics,the application of a machine during the seeding process increased scale efficiency by 3.07%.Therefore,we suggest that local government should actively promote rural land circulation,implement a staged-scale management subsidy,and other forms of support for the purchase of agricultural machinery and technical popularization.Increased investment in irrigation improvements and mechanical facilities and encouragement of farmers to enlarge their farm size could improve scale efficiency and farming profit and lead to the development of moderate scale management.

A nonparametric distance function approach with endogenous direction for estimating marginal abatement costs of CO_(2) emissions

The directional distance function(DDF)framework has been widely used to estimate the marginal abatement cost(MAC)of CO_(2)emissions to support decision-making in environmental sustainability and climate change issues.In the use of DDF,an important task is mapping evaluated entities towards a realistic production technology frontier.This study develops a new nonparametric approach for estimating the MAC of CO_(2)emissions.The approach incorporates the optimal endogenous direction into an enhanced environmental production technology and has three advantages.First,it avoids the arbitrariness in mapping directions.Second,it captures the heterogeneity in optimization paths across different decision-making units(DMUs).Third,it generates more reliable benchmarks for estimating MAC by constructing an environmental technology frontier that is consistent with the material balance principle.We apply the approach to study China's thermal power industry and find clear heterogeneity in MACs and optimization paths at the province level.The results on the optimal endogenous directions show that the DMUs prefer to increase both desirable output and CO_(2)emissions when CO_(2)emissions are unregulated.Comparisons with other approaches reveal that arbitrarily mapping exogenous directions and technology representations are likely to generate distorted and unrealistic MACs.