When counterfeits raise the appeal of luxury brands

Counterfeiting is a widespread practice throughout the world. The conventional wisdom is that it affects branded goods negatively. In this paper, however, we suggest that counterfeiting may actually benefit certain luxury brands. By means of two studies, we show how the market presence of luxury counterfeit items can increase consumers’ willingness to pay for original brands. In Study 1, we show that the presence of luxury counterfeits can increase consumers’ willingness to pay for well-known original brands, but not for lesser-known ones. Brand awareness plays a moderating role in the positive relationship between counterfeiting and willingness to pay (WTP). In Study 2, we address the psychological mechanisms that explain this increased willingness to pay. The results show that consumers’ (a) pleasure at being envied, (b) pleasure in distinguishing themselves, and (c) perception of the quality of the original goods fully mediate the relation between the presence of counterfeit in the market and consumers’ WTP for originals. We subsequently discuss the theoretical and managerial implications of the two study results.     

Nationalism,cognitive ability,and interpersonal relations

Interpersonal relations are shaped by the judgements associated with the social categories that individuals perceive in their social contacts. I develop a model of how those judgments form based on a theory of symbolic values. The model depicts the interaction between two values, one associated with an inherited ethnic trait (“nationality”) and one with an endogenous achievement trait (“income”). Individuals with lower cognitive ability are predicted to invest more value on nationalism and to have hostile relations with immigrants. Multiple equilibria are possible, and better schooling may eliminate equilibria with xenophobia. Econometric findings based on data from three large surveys corroborate the predictions derived from the theoretical model.     

Quantifying knowledge exchange in R&D networks: a data-driven model

We propose a model that reflects two important processes in R&D activities of firms, the formation of R&D alliances and the exchange of knowledge as a result of these collaborations. In a data-driven approach, we analyze two large-scale data sets, extracting unique information about 7500 R&D alliances and 5200 patent portfolios of firms. These data are used to calibrate the model parameters for network formation and knowledge exchange. We obtain probabilities for incumbent and newcomer firms to link to other incumbents or newcomers able to reproduce the topology of the empirical R&D network. The position of firms in a knowledge space is obtained from their patents using two different classification schemes, IPC in eight dimensions and ISI-OST-INPI in 35 dimensions. Our dynamics of knowledge exchange assumes that collaborating firms approach each other in knowledge space at a rate μ for an alliance duration τ. Both parameters are obtained in two different ways, by comparing knowledge distances from simulations and empirics and by analyzing the collaboration efficiency \(\mathcal {\hat {C}}_{n}\). This is a new measure that takes in account the effort of firms to maintain concurrent alliances, and is evaluated via extensive computer simulations. We find that R&D alliances have a duration of around two years and that the subsequent knowledge exchange occurs at a very low rate. Hence, a firm’s position in the knowledge space is rather a determinant than a consequence of its R&D alliances. From our data-driven approach we also find model configurations that can be both realistic and optimized with respect to the collaboration efficiency \(\mathcal {\hat {C}}_{n}\). Effective policies, as suggested by our model, would incentivize shorter R&D alliances and higher knowledge exchange rates.     

Algorithmic Pricing What Implications for Competition Policy?

Review of Industrial Organization - Pricing decisions are increasingly in the “hands” of artificial algorithms. Scholars and competition authorities have voiced concerns that those...     

Equity-settled share-based payments and their (strategic) use under asymmetric information

Share-based payments are of widespread use in today's economy. Consulting firms are increasingly accepting equity compensation for their services (particularly from startups) and many governments provide fiscal incentives to support this choice. Likewise, profit-sharing licensing is an on-trend business practice by innovative firms and patent holders when transferring their technology to interested adopters. This paper unveils strategic considerations according to which an agent/seller designs its optimal policy in regard to the equity share to request in exchange for its service, technology, or trademark. The model assumes a fringe of interested users/customers differentiated by both the support they need from the seller and the value of the underlying relationship; and also holding an informational disadvantage on their own type. Given the seller's cost configuration, equilibrium outcomes entail entering a profit-sharing relationship either with the high-type customers only or with all customers. Yet, in this case, equity-based payment claims are —for rent extraction purposes— common (i.e., not differentiated) across types.     

Long COVID? Prospects for economic scarring from the pandemic

This paper examines the potential persistent effects (scarring) of the COVID-19 pandemic on the economy and the channels through which they may occur. Our findings from a broad set of historical recessions confirm that recessions are associated with persistent output losses and that the greatest scarring has occurred following financial crises. The amount of scarring following pandemic and epidemic recessions in the sample is in between that of typical recessions and financial crises. Results on the channels show that the productivity channel is important, as all types of recessions have been followed by persistent losses to total factor productivity.     

Bias-optimal vol-of-vol estimation: the role of window overlapping

Decisions in Economics and Finance - The simplest and most natural vol-of-vol estimator, the pre-estimated spot variance-based realized variance, is typically plagued by a large finite-sample bias....     

Introduction to the special issue on the 24th annual Workshop on Economic science with Heterogeneous Interacting Agents,London, 2019 (WEHIA 2019)

Journal of Economic Interaction and Coordination -