Methods for Environmental and Economic Accounting for the Exploitation of Wild Fish Stocks and their Applications to the Case of Icelandic Fisheries

The paper discusses methods for estimating the value of commercially exploited fish stocks and the cost of exploiting them. Methods which are recommended in the System of National Accounting (SNA) satellite system and the System for Integrated Environmental and Economic Accounting (SEEA) and relevant for this task are discussed. The paper questions the relevance of some of these methods. It argues for the integration of economic accounting for wild fish stocks with estimation of efficient management of them. Using biological and economic data makes it possible to produce consistent estimates of the value of fish stocks and the cost of exploiting them. These estimates are useful for national accounting and for guiding management of fisheries. This method allows estimation of the cost of inefficiency of fisheries management besides estimation of the cost of depletion. The different methods are illustrated using data on commercial fisheries in Iceland and the fish stocks that they exploit. It is shown that even if all methods are based on market valuation and use only objective data they lead to very different outcomes.     

Input cost, capacity utilization and substitution in the short run

This article studies the behavior of input cost shares in an environment where labor is costly to adjust, materials can be adjusted at no cost and capital is fixed. A model relating cost shares with relative prices and adjustment costs is proposed, allowing joint estimation of the elasticity of substitution and the adjustment cost function, which is an unknown function of the capacity utilization. Based on a panel of more than 700 manufacturing firms, we find evidence of strong input share variations according to the degree of capacity utilization. The estimated shapes of adjustment costs curves of labor are in agreement with our theoretical model, and we obtain sensible elasticities of substitution estimates. Based on such estimates, we find evidence of a negative (positive) bias in downturns (recoveries) in conventional productivity growth measures.     

Estimating an hedonic translog cost function for the home health care industry

Medicare home health care plays an important role in providing cost effective care for the chronically ill and elderly. Long seen as a cost effective substitute for nursing home care, home care has become even more important with expenditures increasing by 31.4% from 1990 to 1996. The purpose of this paper is to provide a short run cost analysis of a sample of home health care providers to gain insight into the efficient provision of home health care services. This paper is a significant improvement over previous studies in that it uses a nationwide database to more accurately represent the multiproduct nature of the industry and uses an hedonic translog cost estimation with desirable economic properties.     

USING OVERLAPPING AND INCOMPLETE TIME SERIES FOR THE ESTIMATION OF COST OF LIVING INDICES

We address the estimation of cost of living indices from time series which are incomplete, in a way that exploits all available information, while also giving an indication of the uncertainty associated with the estimation. The method used allows for multiple sources of prices for a single item, extending over the same or partially overlapping time ranges. We describe summarily the methodology and demonstrate its use in the estimation of a cost of living index for Biscaye (North of Spain), for the period 1862–1940.     

资产全寿命周期管理方法简要评述

近几年来的大量研究成果表明,资产全寿命周期管理方法已经成为资产管理领域关注的焦点。通过文献梳理发现,该方法主要用于机器设备资产寿命周期内的全面管理。基于此,立足于资产全寿命周期的主要研究内容,即设备的可靠性、可维修性与经济性进行探讨,对机器设备资产的寿命周期成本与维修策略进行研究,对已有的比较有代表性的国内外资产全寿命周期管理的研究成果进行简要的评述。首先,对机器设备资产寿命周期内的费用估算和分析方法进行了总结和回顾,主要就设备资产寿命周期的费用划分、费用估算方法进行了总结和阐述,为以后寿命周期费用的估算方法的选择和改进提出了改进意见。其次,针对机器设备资产全寿命周期内的维修计划和维修策略进行了总结和陈述,分析了维修计划制定的原则和方法,并针对已有的维修策略特点进行对比分析。在总结已有研究成果的基础上,结合电网企业的实际应用,对未来研究的发展趋势进行展望。     

On estimating firm-level production functions using proxy variables to control for unobservables

In the common case where polynomial approximations are used for unknown functions, I show how proxy variable approaches to controlling for unobserved productivity, proposed by Olley and Pakes [Olley, S. and Pakes, A., 1996. The dynamics of productivity in the telecommunications equipment industry. Econometrica 64, 1263–1298.] and Levinsohn and Petrin (Levinsohn, J. and Petrin, A., 2003. Estimating production functions using inputs to control for unobservables. Review of Economic Studies 70, 317–341.], can be implemented by specifying different instruments for different equations and applying generalized method of moments. Studying the parameters within a two-equation system clarifies some key identification issues, and joint estimation of the parameters leads to simple inference and more efficient estimators.     

Technical and Allocative Efficiency among Socialist Enterprises: The Case of the Garment Industry in China

Using survey data, this paper compares technical and allocative efficiency among state, urban collective, township-village, and joint venture enterprises in the garment industry in China. Township-village enterprises are further classified into independent enterprises and cooperative ventures with state and urban collective enterprises. According to the estimation results of the production and labor share functions, state and urban collective enterprises are much less efficient, both technically and allocatively, than cooperative township-village enterprise and joint ventures. These findings suggest that this new type of socialist enterprise and joint ventures will eventually dominate in the garment industry. J. Comp. Econom. December 1994, 19(3), pp. 410-433. Tokyo Metropolitan University, Hachiohji City, Tokyo 192-03, Japan; Tokyo Gakugei University, Koganei City, Tokyo 184, Japan; and International Food Policy Research Institute, Washington, DC 20036.     

Catching Growth Determinants with the Adaptive Lasso

Abstract. This paper uses the adaptive Lasso estimator to determine variables important for economic growth. The adaptive Lasso estimator is a computationally very efficient procedure that simultaneously performs model selection and parameter estimation. The computational cost of this method is negligibly small compared with standard approaches in the growth regressions literature. We apply this method for a regional dataset for the European Union covering the 255 NUTS2 regions in the 27 member states over the period 1995–2005. The results suggest that initial GDP per capita (with an implied convergence speed of about 1.5% per annum), human capital (proxied by the shares of highly and medium educated in the working age population), structural labor market characteristics (the initial unemployment rate and the initial activity rate of the low educated) as well as being a capital region are important for economic growth.     

A simple and efficient estimation method for a non-linear demand system

A least-squares-type estimation method appears to be about as efficient as maximum likelihood with a known contemporaneous covariance matrix.     

Estimation of Biological and Economic Parameters of a Bioeconomic Fisheries Model Using Dynamical Data Assimilation

A new approach of model parameter estimation is used with simulated measurements to recover both biological and economic input parameters of a natural resource model. The data assimilation technique is the variational adjoint method (VAM) for parameter estimation. It efficiently combines time series of artificial data with a simple bioeconomic fisheries model to optimally estimate the model parameters. Using identical twin experiments, it is shown that the parameters of the model can be retrieved. The procedure provides an efficient way of calculating poorly known model parameters by fitting model results to simulated data. In separate experiments with exact and noisy data, we have demonstrated that the VAM can be an efficient method of analyzing bioeconomic data.     

Risk preference and productivity measurement under output price uncertainty

This paper deals with joint estimation of production and risk preference functions in the presence of output price uncertainty. We use quadratic production and utility functions under the assumption that producers maximize expected utility of anticipated profit. A panel data on Norwegian salmon farms is used for this purpose. Empirical results show that all salmon farmers are risk averse. Relative risk premium (the implicit cost of private risk bearing) is found to be about 15% of mean profit. We also find rapid technological change taking place (3.75% per year) in the salmon farming industry. First version received: February 2000/Final version received: February 2001     

Bank Ownership and Efficiency in the Aftermath of Financial Crises: Evidence from Indonesia

This paper examines the relationship between types of ownership of banks and their efficiency in the aftermath of a financial crisis using Greene's “true” panel data stochastic frontier model, which takes into account unobserved heterogeneity among banks. The Indonesian banking sector is analyzed using financial data of 144 banks operating in Indonesia over the period of 2000Q4–2005Q2. In the aftermath of the 1997 Asian financial crisis, the cost efficiency of all banks improves over time on average. However, there is some evidence that, as these banks improve their efficiency, state‐owned banks are the least efficient banks while joint‐venture and foreign‐owned banks are the most efficient.     

Hospital efficiency under global budgeting: evidence from Taiwan

Global budgeting sets a predetermined cap to restrain health expenditure, but the fixed budget for medical providers could result in less efficient services. This paper measures hospital efficiency under global budgeting using simultaneous stochastic frontier analysis, stressing that physicians and dentists within a hospital were under separate budgets in Taiwan. Empirical results show that hospital efficiency was not improved after global budgeting, and physicians were found to be less efficient than dentists. The physicians and dentists within the same hospital were also found to be less integrated after global budgeting. Empirical results show that a joint analysis improves the estimation efficiency from separate analysis and suggest that the aggregate inefficiency came mostly from physicians in hospitals that were small, public, non-teaching, located in small markets and had a low market share. Except for public hospitals, physicians and dentists in the above hospitals were also found to be less integrated.     

On Setting Prices and Testing Cross-Subsidy with Accounting Data

Regulators are often faced with the challenge of both setting efficient prices and avoiding cross subsidy. Successful implementation of these goals requires estimates of both marginal costs and incremental costs. We present a methodology for estimating both marginal and incremental costs for postal products. The proposed algorithms combine micro-unit accounting data and econometric estimation of the cost structure. We apply the methodology to the U.S. Postal Service and produce estimates of marginal and incremental costs for eighteen postal products and incremental costs for another four groups of products.     

On the median regression for SURE models with applications to 3-generation immigrants data in Sweden

In this paper we generalize the median regression method to be applicable to system of regression equations, in particular SURE models. Giving the existence of proper system wise medians of the residuals from different equations, we apply the weighted median regression with the weights obtained from the covariance matrix of the equations obtained from ordinary SURE method. The benefit of this model in our case is that the SURE estimators utilise the information present in the cross regression (or equations) error correlation and hence more efficient than other estimation methods like the OLS method. The Seemingly Unrelated Median Regression Equations (SUMRE) models produce results that are more robust than the usual SURE or single equations OLS estimation when the distributions of the dependent variables are not normally distributed or the data are associated with outliers. Moreover, the results are also more efficient than is the cases of single equations median regressions when the residuals from the different equations are correlated. A theorem is derived and indicates that even if there is no statistically significant correlation between the equations, using SUMRE model instead of SURE models will not damage the estimation of parameters.     

Scale and efficiency measurement using a semiparametric stochastic frontier model: evidence from the U.S. commercial banks

In this paper, we use the local maximum likelihood (LML) method proposed by Kumbhakar et al. (J Econom, 2007) to estimate stochastic cost frontier models for a sample of 3,691 U.S. commercial banks. This method relaxes several deficiencies in the econometric estimation of frontier functions. In particular, we relax the assumption that all banks share the same production technology and provide bank-specific measures of returns to scale and cost inefficiency. The LML method is applied to estimate the cost frontiers in which a truncated normal distribution is used to model technical inefficiency. This formulation allows the cost frontier, inefficiency effects and heteroskedasticity in both noise and inefficiency components to be quite flexible.      

Moment Estimation of the Probit Model with an Endogenous Continuous Regressor

We propose a generalized method of moments (GMM) estimator with optimal instruments for a probit model that includes a continuous endogenous regressor. This GMM estimator incorporates the probit error and the heteroscedasticity of the error term in the first‐stage equation in order to construct the optimal instruments. The estimator estimates the structural equation and the first‐stage equation jointly and, based on this joint moment condition, is efficient within the class of GMM estimators. To estimate the heteroscedasticity of the error term of the first‐stage equation, we use the k‐nearest neighbour (k‐nn) non‐parametric estimation procedure. Our Monte Carlo simulation shows that in the presence of heteroscedasticity and endogeneity, our GMM estimator outperforms the two‐stage conditional maximum likelihood estimator. Our results suggest that in the presence of heteroscedasticity in the first‐stage equation, the proposed GMM estimator with optimal instruments is a useful option for researchers.     

基于MFCA的废弃物回收优先排序方法及应用研究

随着资源环境问题的日益凸显,废弃物回收再利用引起了广泛关注。基于物质流成本会计（MFCA）及物质流转平衡原理,建立了将隐性成本嵌入生产工序流程的废弃物回收优先排序方法。为了验证该方法的实用性及科学性,以A钢铁企业为例进行了案例研究。结果表明：根据各工序环节的隐性成本测算结果可以确立废弃物回收优先次序,该方法能有效促进A钢铁企业环保效益与经济效益协同提升。     

变电站投资费用模型及敏感因素分析

本文结合变电站各阶段费用的特点,应用全寿命周期费用分析方法对变电站的建设进行决策分析。将变电站的全寿命周期费用分为一次投资费用、运行费用和中断供电损失费用,建立了变电站全寿命周期费用估算模型,基于运行年限、年利率和通货膨胀率对变电站的全寿命周期费用进行修正以及敏感因素分析。以220kV变电站为例,对其综合自动化系统和常规保护系统进行全寿命周期费用的分析和比较,从而验证了所建全寿命周期费用模型对变电站建设进行决策分析的实用性和可行性。     

RJV FORMATION AND STRATEGIC ENTRY ACCOMMODATION*

This article examines the relationship between cost reduction and public goods effect of research joint ventures (RJVs) and strategic entry deterrence. R&D is process innovation à la Kamien, Muller and Zang (1992 ) and R&D cost sharing between the incumbent and the entrant in a RJV can be asymmetric per Long and Soubeyran (2002 ). It is found that conforming with the conventional wisdom, the incumbents prefer to form RJV to deter entry when the entrant is very inefficient. However, if the entrant is moderately inefficient, it is a better choice for the incumbent to accommodate entry by forming a RJV with it. In contrast, if the entrant is very efficient, then the equilibrium RJV structure depends on the magnitude of spillover effect: it is better to deter entry in the case of high spillover effect.