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.     

The extension of social security coverage in developing countries

We study the dynamic general equilibrium effects of introducing a social pension program to elderly informal sector workers in developing countries who lack formal risk sharing mechanisms against income and longevity risks. To this end, we formulate a stochastic dynamic general equilibrium model that incorporates defining features of developing countries: a large informal sector, private transfers as an informal safety net, and a non-universal social security system. We find that the extension of retirement benefits to informal sector workers results in efficiency losses due to adverse effects on capital accumulation and the allocation of resources across formal and informal sectors. Despite these losses recipients of social pensions experience welfare gains as the positive insurance effects attributed to the extension of a social insurance system dominate. The welfare gains crucially depend on the skill distribution, private intra-family transfers and the specific tax used to finance the expansion.     

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.     

Product survival analysis for the App Store

We empirically analyze both free and paid products on the top 100 Free and Grossing charts in the Korea App Store using Weibull parametric survival analysis on the product level. The findings are as follows: First, influences of ranking, customer ratings, and contents size on product survival are different for free and paid products. Customer ratings and contents size critically affect product survival when the price is zero. Second, the early entrant advantage exists in App Store, which results from a ranking system in the App Store and consumer learning. However, the effect of early entrant advantage differs between the Free and Grossing charts; the benefit of early entrant advantage is greater on the Free chart than that on the Grossing chart. Finally, we provide a competitive profit model that is related to free products.     

Product Market Competition and Lobbying Coordination in the U.S. Mobile Telecommunications Industry

This paper empirically investigates market behavior and firms?? lobbying in a unified structural setup. In a sequential game, where firms lobby for regulation before they compete in the product market, we derive a testable measure of lobbying coordination. Applying the setting to the early U.S. cellular services industry, we find that lobbying expenditures, as measured by campaign contributions, and market conduct were consistent with a one-shot Nash equilibrium and that price caps were binding on average. Furthermore, campaign contributions from cellular firms effectively lowered the burden of the price caps and reduced production costs.     

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.     

Expatriate utilization,subsidiary knowledge creation and performance: The moderating role of subsidiary strategic context

Little research examines the mechanisms for the relationship between expatriate utilization and subsidiary performance. Building on the knowledge-based view of the firm, we propose a multi-stage mediation model to explain how expatriate staffing promotes subsidiary financial performance. Our results underscore that expatriate utilization has an indirect, mediated effect on subsidiary financial performance through its links with subsidiaries’ knowledge creation and product performance. Adopting a moderated mediation approach, we also find that the indirect relationship between expatriate utilization and subsidiary product performance via subsidiary knowledge creation is strengthened by the context of transnational strategy as a moderating contingency.     

The effects of consumer empowerment on risk perception and satisfaction with food consumption

This study intends to measure consumer empowerment related to food consumption and determine its effect on food risk perception and satisfaction with food consumption. Data were derived from an analysis of the “2017 Research on Food Consumption Behaviour” by the Korea Rural Economic Institute. Consumer empowerment, risk perception and satisfaction with food consumption were measured using a 5‐point Likert scale. The differences in consumer empowerment according to gender, age, educational level and monthly income were statistically significant. The factors that affected risk perception were information use, healthy eating, consumer rights, consumer responsibility and monthly income. The higher the scores for information use, healthy eating and consumer responsibility, the higher the score for satisfaction with food consumption.