Asymptotic properties of a correlation coefficient type statistic connected with the general linear model

It is proved that under certain conditions the conditional distribution of the sample multiple correlation coefficient given the ‘other’ observations in a multivariate normal distribution is asymptotically normal. Moreover a second-order approximation for the first moment is given.     

Learning from input–output mixes in DEA: a proportional measure for slack‐based efficient projections

Several Data Envelopment Analysis (DEA) models use a radial distance measure that is based on the Debreu–Farrell notion of (in)efficiency. While this measure has an attractive interpretation, its use may be problematic if slacks or zeros are present in the data. The additive DEA model can perfectly deal with these problems, but the meaning of its associated scores is less intuitive than the one attached to the radial measures. We introduce an alternative efficiency measure, based on the results of the additive model, that can be decomposed in a Debreu–Farrell component and a factor that captures differences in input–output mixes with respect to those of the best practice reference observation. On an aggregate level, this second component can be considered as an indicator of the dispersion between radial efficiency measurement and results based on the Pareto–Koopmans efficiency notion. On the individual level, the measure allows us to regard relative inefficiency as resulting from (i) a divergence of implicit cost price vectors, and (ii) a cost level that is too high, even after adjustment for the implicit cost prices. Copyright © 1999 John Wiley & Sons, Ltd.     

What Is the Economic Meaning of FDH? A Reply to Thrall

Journal of Productivity Analysis -     

Exploitation,international taxation,and global justice

Abstract

I investigate the central principle that underlies the OECDs tax base erosion and profit shifting initiative. The principle claims that (corporate) profits should be taxed where economic activities deriving the profits are performed and where value is created. First, I argue that its plausibility depends on establishing that states have an entitlement to the productive factors in their territory, and therefore to a share of the value created by employing those factors. Second, I maintain that this cannot presently be established. If states fail to discharge duties requiring wealth redistribution, they do not have an unqualified right to the productive factors in their territory. Even if they are not subject to such duties, states can only legitimately claim a share in the fair value of the goods created. I show that given widespread exploitation in global value chains, the market prices of (intermediary) goods do not reflect their fair value.     

The economic meaning of Data Envelopment Analysis: A ‘behavioral’ perspective

We reconsider the motivation of Data Envelopment Analysis (DEA), the non-parametric technique that is widely employed for analyzing productive efficiency in academia, the private sector and the public sector. We first argue that the conventional engineering motivation of DEA can be problematic since it often builds on unverifiable production axioms. We then provide a dual viewpoint and highlight the ‘behavioral’ interpretation of DEA models. We start from a specification of the production objectives while imposing minimal structure on the production possibilities, and construct tools to meaningfully quantify deviations of observed producer behavior from optimizing behavior. This brings to light the economic meaning of DEA, provides guidelines for selecting the appropriate model in practical research settings, and prepares the ground for instituting new DEA models. We also provide an empirical application that demonstrates the practical relevance of our arguments. We hope that our insights will contribute to the further dissemination of DEA, and stimulate public sector applications of DEA that build on its behavioral interpretation.     

The relationship between in-store marketing and observed sales for organic versus fair trade products

To stimulate sales of sustainable products, such as organic and fair trade products, retailers need to know whether their in-store instruments effectively enhance market shares. This study uses sales data and a multilevel modeling approach to explain the market shares of sustainable products according to shelf layout factors, price level, price promotions, and consumer demographics. It argues that the effect of these variables differs between organic versus fair trade products, as buying motives might differ, organic buyers tend to be more loyal, and price is a more informative signal of quality for organic products. Results show that the number of facings has a positive relationship with the market share of fair trade brands, but not with the market share of organic brands. The same holds for the price difference with the leading brand, which is important for fair trade brands but not for organic brands. In contrast, an arrangement of the product category by brand is associated with higher market share for organic brands but not for fair trade brands. Additionally, placement at eye level and clustering of items benefits both types of sustainable brands, whereas they appear to be not very sensitive to price promotions. Finally, higher sales of sustainable products are found in areas where the customer base is older and has a higher education level.     

One market, one number? A composite indicator assessment of EU internal market dynamics

We consider the lack of consensus about an appropriate theoretical framework linking sub-indicators as a defining characteristic of composite indicators. This intrinsic feature implies uncertainties about the appropriate normalization and aggregation of the raw data. The two are related: index theory offers some valuable guidelines about their connection. Yet these do not fully solve the basic problem of expert disagreement. We embed such (residual) disagreement in the aggregation method itself. Specifically, we apply an impartial benefit-of-the-doubt weighting procedure, where weight restrictions incorporate the available information on experts’ opinions. We apply this procedure to the dynamic performance assessment of EU Internal Market effects, thereby highlighting its capacity to disaggregate member states’ observed performance shifts into changes relative to benchmarks and performance changes of the benchmarks (i.e. catching up versus genuine progress). Our results indicate that the latter factor is more important in explaining the observed progress.     

A multi-level and multi-actor approach to risk governance: a conceptual framework to support policy development for Ambrosia weed control

Invasive species such as Ambrosia (an annual weed) pose a biosecurity risk whose management depends on the knowledge, attitudes and practices of many stakeholders. It can therefore be considered a complex policy and risk governance problem. Complex policy problems are characterised by high uncertainty, multiple dimensions, interactions across different spatial and policy levels, and the involvement of a multitude of actors and organisations. This paper provides a conceptual framework for analysing the multi-level and multi-actor dimensions of Ambrosia management. Potential and existing public, private and public–private management strategies are identified to address the interests and needs of different actor groups across different levels. We conclude that policies that promote a mix of public and private Ambrosia management strategies may respond better to the needs and interests of different actor groups across different levels than a one-size-fits-all approach. However, multiple policy strategies need to be aligned in order to lead to synergies and spreading coherent messages to the public. Collaboration may enhance the likelihood of biosecurity management and risk governance of Ambrosia being adequately implemented and enforced.     

Towards a Further Understanding of the Antecedents of Retailer New Product Adoption

In addition to the traditionally investigated profit-drivers of retail adoption, such as gross margin, trade support, consumer marketing support, and product uniqueness, the authors investigate to what extent relatively under-investigated variables, such as relationship variables and category variables, are potential antecedents of retailers’ new product adoption decisions. Based on a sample of 392 new product adoption decisions by buyers of a Dutch food retailer, the authors provide evidence that both relationship and category variables do matter in new product adoption decisions by retailers. They show a significant negative effect of relationship dependence, and a significant positive effect of relationship length on a retailer's new product adoption probability. Furthermore, the authors show that higher levels of expected category growth due to the new product introduction are associated with higher levels of retailer adoption probability. Finally, in contrast with all previous retail adoption studies, this study shows a significant, positive relation between the relative gross margin of the new product and the retailer adoption probability.