Vertical externality and strategic delegation

This paper examines the effects of vertical externality generated by the upstream monopoly on the incentives that owners of competing downstream firms give their managers. It is shown that the introduction of the upstream monopoly may have significant effects on the incentive schemes for the downstream firms' managers. In particular, it is shown that in equilibrium, each owner obtains the simple Nash equilibrium outcome regardless of the mode of competition (quantity or price) in the downstream market. Copyright © 2002 John Wiley & Sons, Ltd.     

The Cross-industry Spillover of Technological Capability: Korea’s DRAM and TFT–LCD Industries

Studies of Korea’s Thin Film Transistor–Liquid Crystal Display (TFT–LCD) industry have emphasized the government policy, industrial organization, and the firm’s strategy as key success factors. However, the fact that knowledge spillover, which tends to occur between highly technologically related industries, can lead to a reduction in innovation effort has been overlooked. We examined the technological relationships between Dynamic Random Access Memory (DRAM) and TFT–LCD industries and investigated their spillover into the areas of technology, human resources and organization, and network. The results show spillover in capital control, technology, production and quality management, organizational systems, and key personnel. This implies that spillover effect in high technology firms may diversify their products due to existing technological capabilities.     

CONDITIONAL HETEROSCEDASTICITY IN THE MARKET MODEL AND EFFICIENT ESTIMATES OF BETAS

Previous studies have investigated only unconditional heteroscedasticity in the market model. This paper tests for both conditional and unconditional heteroscedasticities as well as normality. Using the monthly stock rate of return data secured from the Center for Research in Security Prices (CRSP) tape for 1976 through 1983, this paper shows that conditional heteroscedasticity is more widespread than unconditional heteroscedasticity, suggesting the necessity of model refinements that take conditional heteroscedasticity into account. This paper provides an alternative estimation of betas of individual securities and portfolios based on the autoregressive conditional heteroscedastic (ARCH) model introduced by Engle. The efficiency of the market model coefficients is markedly improved across all firms in the sample through the ARCH technique.     

Estimating the autocorrelated error model with trended data

A Monte Carlo study of the small sample properties of various estimators of the linear regression model with first-order autocorrelated errors. When independent variables are trended, estimators using Ttransformed observations (Prais-Winsten) are much more efficient than those using T–1 (Cochrane–Orcutt). The best of the feasible estimators isiterated Prais-Winsten using a sum-of-squared-error minimizing estimate of the autocorrelation coefficient ?. None of the feasible estimators performs well in hypothesis testing; all seriously underestimate standard errors, making estimated coefficients appear to be much more significant than they actually are.     

Comparison of SML and GMM estimators for the random coefficient logit model using aggregate data

A simulated maximum likelihood (SML) estimator for the random coefficient logit model using aggregate data is found to be more efficient than the widely used generalized method of moments estimator (GMM) of Berry et?al. (Econometrica 63:841?C890, 1995). In particular, the SML estimator is better than the GMM estimator in recovery of heterogeneity parameters which are often of central interest in marketing research. With the GMM estimator, the analyst must determine what moment conditions to use for parameter identification, especially the heterogeneity parameters. With the SML estimator, the moment conditions are automatically determined as the gradients of the log-likelihood function, and these are the most efficient ones if the model is correctly specified. Another limitation of the GMM estimator is that the product market shares must be strictly positive while the SML estimator can handle zero market share observations. Properties of the SML and GMM estimators are demonstrated in simulated data and in data from the US photographic film market.     

Environmental evaluation of agri-environment schemes using participatory approaches: Experiences of testing the Agri-Environmental Footprint Index

The Agri-Environment Footprint Index (AFI) has been developed as a generic methodology to assess changes in the overall environmental impacts from agriculture at the farm level and to assist in the evaluation of European agri-environmental schemes (AES). The methodology is based on multi-criteria analysis (MCA) and involves stakeholder participation to provide a locally customised evaluation based on weighted environmental indicators. The methodology was subjected to a feasibility assessment in a series of case studies across the EU. The AFI approach was able to measure significant differences in environmental status between farms that participated in an AES and non-participants. Wider environmental concerns, beyond the scheme objectives, were also considered in some case studies and the benefits for identification of unintentional (and often beneficial) impacts of AESs are presented. The participatory approach to AES evaluation proved efficient in different environments and administrative contexts. The approach proved to be appropriate for environmental evaluation of complex agri-environment systems and can complement any evaluation conducted under the Common Monitoring and Evaluation Framework. The applicability of the AFI in routine monitoring of AES impacts and in providing feedback to improve policy design is discussed.     

Integrated assessment of public investment in land-use change to protect environmental assets in Australia

A framework for comprehensive integrated assessment of environmental projects is developed and applied in partnership with a regional environmental body. The framework combines theory with practice, bringing a pragmatic and efficient approach to the rigorous assessment of projects for a large number of environmental assets in the north central region of the state of Victoria, Australia. The approach is codified as the Investment Framework for Environmental Resources (INFFER). The analysis assisted the environmental body to make strong business cases for a number of environmental projects, resulting in funding for those projects. Key features of the study include extensive participation of decision makers and stakeholders, integration of a comprehensive set of information about projects, explicit assessment of uncertainties and information gaps, and analysis of the most appropriate policy mechanism for each project. The process of applying the framework involved four steps: identification of around 300 important environmental assets in the region, filtering the list of assets to remove those that are less likely to provide opportunities for cost-effective public investment, development and detailed assessment of projects for a subset of assets, and negotiation of funding for projects. Implications for land-use policy include that environmental projects vary widely in their cost-effectiveness, requiring careful targeting of funds if environmental benefits are to be maximised. Many existing environmental programs use simplistic analyses to support decision making, resulting in missed opportunities for substantially greater environmental benefits. Promoting adoption of improved analytical methods is very challenging, requiring changes in mind-set and culture in environmental organisations. Widespread adoption is unlikely unless funders create incentives by rewarding those project proponents who undertake rigorous and comprehensive project assessments that focus on achievement of environmental outcomes.     

The joint replenishment and delivery scheduling of the one-warehouse, n-retailer system

We deal with the joint replenishment and delivery scheduling of the one-warehouse, n-retailer system in this paper. We suggest a more flexible policy for the joint replenishment and delivery scheduling of a warehouse compared with the existing researches. We introduce the mathematical model and two efficient algorithms for the joint replenishment and delivery scheduling of the warehouse. Subsequently, we develop the hybrid genetic algorithm (GA) and compare it with two efficient heuristic algorithms for extensive computational experiments. Further, we show the advantages of our GA in dealing easily with resource restrictions.     

Lopsided inclusion: The impact of multi-employer bargaining and class-based unionism on non-regular employment in South Korea

This study examines the impact of multi-employer bargaining on non-regular workers across different unions and types of non-regular employment. Using national representative survey data from South Korea, I find that multi-employer bargaining increases the likelihood that a workplace union would address a pay increase for non-regular workers when the union was affiliated with a confederation espousing class-based as opposed to business-unionism. However, such a relationship was weaker for temporary agency workers and subcontractors than for direct-hire fixed-term workers. This mechanism is further illustrated through a second round of data collection and analysis, namely in-depth interviews. I identify two factors that characterize the class-based confederation: (1) centralized pressure from the union and (2) activists and their identity work. Altogether, these results further an understanding of how the identities of national union confederations can influence local representatives’ approach to representing non-regular workers and how those influences are manifested through workplace-level collective bargaining.