Nonparametric tests of collectively rational consumption behavior: An integer programming procedure

We present an IP-based nonparametric (revealed preference) testing procedure for rational consumption behavior in terms of a general collective model, which includes consumption externalities and public consumption. An empirical application to data drawn from the Russia Longitudinal Monitoring Survey (RLMS) demonstrates the practical usefulness of the procedure. Finally, we present extensions of the testing procedure to evaluate the goodness-of-fit (accounting for optimization error as well as measurement error) of the collective model subject to testing.     

Testable implications of general equilibrium models: An integer programming approach

Focusing on the testable revealed preference restrictions on the equilibrium manifold, we show that the rationalizability problem is NP-complete. Subsequently, we present a mixed integer programming (MIP) approach to characterize the testable implications of general equilibrium models. Attractively, this MIP approach naturally applies to settings with any number of observations and any number of agents. This is in contrast with existing approaches in the literature. We also demonstrate the versatility of our MIP approach in terms of dealing with alternative types of assignable information. Finally, we illustrate our methodology on a data set drawn from the US economy. In this application, an important focus is on the discriminatory power of the rationalizability tests under study.     

The empirical content of Cournot competition

We consider the testable implications of the Cournot model of market competition. Our approach is nonparametric in the sense that we abstain from imposing any functional specification on market demand and firm cost functions. We derive necessary and sufficient conditions for (reduced form) equilibrium market price and quantity functions to be consistent with the Cournot model. In addition, we present identification results for the corresponding inverse market demand function and the firm cost functions. Finally, we use our approach to derive testable restrictions for the models of perfect competition, collusion and conjectural variations. This identifies the conditions under which these different models are empirically distinguishable from the Cournot model. We also investigate empirical issues (measurement error and omitted variables) related to bringing our testable restrictions to data.     

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.     

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.     

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.     

Adapting extreme value statistics to financial time series: dealing with bias and serial dependence

We handle two major issues in applying extreme value analysis to financial time series, bias and serial dependence, jointly. This is achieved by studying bias correction methods when observations exhibit weak serial dependence, in the sense that they come from \(\beta\)-mixing series. For estimating the extreme value index, we propose an asymptotically unbiased estimator and prove its asymptotic normality under the \(\beta\)-mixing condition. The bias correction procedure and the dependence structure have a joint impact on the asymptotic variance of the estimator. Then we construct an asymptotically unbiased estimator of high quantiles. We apply the new method to estimate the value-at-risk of the daily return on the Dow Jones Industrial Average index.     

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.