Vouchers for Basic Education in Developing Economies: An Accountability Perspective

Advocates argue that voucher programs can correct the incentiveproblems of education systems in developing economies. An accountabilityperspective, based on a principal-agent framework, was developedto clarify the arguments for and against education vouchers.An assessment of findings on voucher programs in industrialcountries and a review of voucher or quasi-voucher experiencesin Bangladesh, Chile, Colombia, Côte d'Ivoire, and theCzech Republic support the usefulness of the analytic framework.The assessment concludes that the policy relevance of voucherprograms for developing economies remains uncertain. Major voucherinitiatives have been attempted only in countries with a well-developedinstitutional infrastructure. Some studies find favorable benefitsfor at least some population groups, but others find limitedeffects and evidence of increasing social stratification inschools. Whether vouchers lead to better outcomes or greaterstratification appears related to specific contexts, institutionalvariables, and program designs.      

Considering Aquacultural Externality in Coastal Land Allocation Decisions in India

Commercial aquaculture in India has come under attack for having caused negative agricultural and environmental impacts. This paper formulates an interactive model of non-renewable and renewable resources to characterize land allocations between aquaculture and agriculture in ecologically and economically sustainable fashion. Through an empirical application, various economic and policy circumstances that affect the optimal land allocation mix are evaluated. The aquaculture industry must address two economic effects: off-site negative effects on renewable food and other coastal resources, and on-site self-pollution of shrimp ponds. Current regulatory and land-use policies are inadequate to address these effects.     

Industrial Climate Neutrality in the EU: Outline of an Integrated Industrial Green Deal

Intereconomics - Industry, and in particular the energy-intensive extraction and production of basic materials such as chemicals, cement, steel, non-ferrous metals, ceramics, and so on, is...     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.     

Social contracts,markets and efficiency: Groundwater irrigation in North India

This paper uses primary data to analyze the institutions and informal markets that govern groundwater allocation in a sugarcane-cultivating village in North India. We find that, in contrast to earlier literature, the observed water trades result in efficient water allocation across farms. We interpret this and other stylized facts in terms of a social contract using a simple bargaining model with limited inter-player transfers. Poor functioning of the power sector leads to reduced pumping and a water supply constraint. Simulations show that power supply reform can significantly increase farm yields, and be financed out of increased farm profits.     

An Empirical Analysis of the Extreme Cherry Picking Behavior of Consumers in the Frequently Purchased Goods Market

Extreme cherry pickers are customers who seek price deals and excessively avail themselves of deep discount offers, which generates negative profits for retailers. This study uses market transaction and primary consumer survey data to provide insights into the determinants, prevalence, and profit impacts of such behavior in the frequently purchased goods market. We find that the extreme cherry picking segment is small (about 2% of all shoppers), but its relative value varies across stores, and consumers manifest this behavior only in secondary stores. An inverse U-shaped relationship marks consumers’ opportunity costs for cross-store price search and likelihood of extreme cherry picking behavior. Finally, we also find that a loss leader promotional strategy adds to retailers’ bottom lines, despite the pure loss generated by extreme cherry pickers.     

Robust Hierarchical Bayes Small Area Estimation for the Nested Error Linear Regression Model

Standard model‐based small area estimates perform poorly in presence of outliers. Sinha & Rao ( 2009 ) developed robust frequentist predictors of small area means. In this article, we present a robust Bayesian method to handle outliers in unit‐level data by extending the nested error regression model. We consider a finite mixture of normal distributions for the unit‐level error to model outliers and produce noninformative Bayes predictors of small area means. Our modelling approach generalises that of Datta & Ghosh ( 1991 ) under the normality assumption. Application of our method to a data set which is suspected to contain an outlier confirms this suspicion, correctly identifies the suspected outlier and produces robust predictors and posterior standard deviations of the small area means. Evaluation of several procedures including the M‐quantile method of Chambers & Tzavidis ( 2006 ) via simulations shows that our proposed method is as good as other procedures in terms of bias, variability and coverage probability of confidence and credible intervals when there are no outliers. In the presence of outliers, while our method and Sinha–Rao method perform similarly, they improve over the other methods. This superior performance of our procedure shows its dual (Bayes and frequentist) dominance, which should make it attractive to all practitioners, Bayesians and frequentists, of small area estimation.     

Recent Progress on Endogeneity in Choice Modeling

We describe recent progress in several areas related to endogeneity, including: choice set formation and attention to attributes; interactions among decision-makers; respondents' strategic behavior in answering stated preference choices; models of multiple discrete/continuous choice; distributions of willingness-to-pay; and methods for handling traditionally endogenous explanatory variables.     

Communication and Promotion Decisions in Retailing: A Review and Directions for Future Research

Communication and promotion decisions are a fundamental part of retailer customer experience management strategy. In this review paper, we address two key questions from a retailer's perspective: (1) what have we learned from prior research about promotion, advertising, and other forms of communication and (2) what major issues should future research in this area address. In addressing these questions, we propose and follow a framework that captures the interrelationships among manufacturer and retailer communication and promotion decisions and retailer performance. We examine these questions under four major topics: determination and allocation of promotion budget, trade promotions, consumer promotions and communication and promotion through the new media. Our review offers several useful insights and identifies many fruitful topics and questions for future research.     

The Impact of Online and Offline Information Sources on Automobile Choice Behavior

The Internet has significantly impacted the information search behavior of consumers. Many consumers regularly consult Internet sources for information on product categories, brands, manufacturers, and retailers, particularly when making a purchase decision about major durable goods. Automobiles are one example of such goods. The Internet has become a major source for information on automobile brands, attributes, and dealers. While much research has been done on the impact of the Internet on automobile information search behavior and search costs, there is limited work on the relationship between Internet use and the ultimate automobile choice. This type of relationship may have interesting managerial implications for both manufacturers of automobiles and firms that provide information on automobiles. This paper attempts to address this gap. It examines whether Internet use is associated with different choice patterns for automobiles. Using discrete choice analysis on automobile choice data, we explore whether there will be differences in the salience of specific information types for online versus offline consumers. We find that Internet users rely more on ratings while non-Internet users rely more on recommendations when making automobile choices. Our findings have several useful managerial implications for information provision, both online and offline.