Product differentiation,price discrimination and collusion

The existing literature which analyses the relationship between the product differentiation degree and the sustainability of a collusive agreement on price assumes that firms cannot price discriminate, and concludes that there is a negative relationship between the product differentiation degree and the critical discount factor. This paper, in contrast, assumes that firms are able to price discriminate. Within the Hotelling framework, three different collusive schemes are studied: perfect collusion on discriminatory prices; perfect collusion on a uniform price; collusion not to discriminate. We obtain that the critical discount factor of the first and the third collusive scheme does not depend on the product differentiation degree, while the critical discount factor of the second collusive scheme depends positively on the product differentiation degree. Moreover, we show that imperfect collusion is more difficult to sustain than perfect collusion.     

Virtual Design,Problem Framing,and Innovation: An Empirical Study in the Automotive Industry

This paper studies how problem framing by research and development groups, in particular the extent of problem decomposition, impacts knowledge replication processes conducted through the use of virtual simulation tools (VSTs). It presents the results of a comparative study of two research and development groups working on the design of hybrid propulsion systems. The research contributes to the literature on strategy and innovation in four ways. First, we identify three organizational and strategic factors affecting the problem framing decision. Second, we analyse the impact of problem framing on the use of VSTs and the related effect on knowledge replication processes. Third, we show the emergence of a new VST‐driven knowledge replication process, i.e. functional replication. Fourth, we explain how VST‐driven knowledge replication processes can attenuate the dangers related to the adoption of modular design strategies and address the replication vs. imitation dilemma.     

Modelling systemic price cojumps with Hawkes factor models

Instabilities in the price dynamics of a large number of financial assets are a clear sign of systemic events. By investigating portfolios of highly liquid stocks, we find that there are a large number of high-frequency cojumps. We show that the dynamics of these jumps is described neither by a multivariate Poisson nor by a multivariate Hawkes model. We introduce a Hawkes one-factor model which is able to capture simultaneously the time clustering of jumps and the high synchronization of jumps across assets.     

Credit rating industry: A helicopter tour of stylized facts and recent theories

The recent subprime crisis and the ongoing Euro zone crisis have generated an enormous interest in the credit rating industry not only among economists but also among average citizens. As a consequence, we have seen an explosion of the economic literature on the industry. The objective of this survey is to introduce readers to the key stylized facts of the credit rating industry and to the recent theoretical economic literature on this industry.     

Random Recursive Partitioning: a matching method for the estimation of the average treatment effect

In this paper we introduce the Random Recursive Partitioning (RRP) matching method. RRP generates a proximity matrix which might be useful in econometric applications like average treatment effect estimation. RRP is a Monte Carlo method that randomly generates non‐empty recursive partitions of the data and evaluates the proximity between two observations as the empirical frequency they fall in a same cell of these random partitions over all Monte Carlo replications. From the proximity matrix it is possible to derive both graphical and analytical tools to evaluate the extent of the common support between data sets. The RRP method is “honest” in that it does not match observations “at any cost”: if data sets are separated, the method clearly states it. The match obtained with RRP is invariant under monotonic transformation of the data. Average treatment effect estimators derived from the proximity matrix seem to be competitive compared to more commonly used estimators. RRP method does not require a particular structure of the data and for this reason it can be applied when distances like Mahalanobis or Euclidean are not suitable, in the presence of missing data or when the estimated propensity score is too sensitive to model specifications. Copyright © 2008 John Wiley & Sons, Ltd.     

Evolution paths on the equilibrium manifold

In a pure exchange smooth economy with fixed total resources, we define the length between two regular equilibria belonging to the equilibrium manifold as the number of intersection points of the evolution path connecting them with the set of critical equilibria. We show that there exists a minimal path according to this definition of length.     

R&D intensity of investment across Europe before and after the crisis

In this paper we investigate the comovements between the R&D intensity of private investment and GDP growth in different European Union (EU) areas over the period 1999–2014. Our empirical analysis shows that only core countries display a common countercyclical mechanism leading to an increased intensity of R&D over prolonged downturns. The lack of an effective countercyclical pattern of R&D intensity over the evolution of GDP growth in periphery countries makes this area highly vulnerable to persistent recessions, with potentially harmful consequences for long‐term growth. For recent EU members the evidence of acyclicality should be evaluated in the light of the catching‐up process still at work in this area. Our analysis suggests that any successful EU innovation policy should not disregard the potential divergence in R&D performance due to the dispersion of the countercyclical properties of the investment intensity in productivity enhancing activities in the different EU areas.     

Relocation of second degree: Moving towards a new place or returning home?

We study the “Relocations of Second Degree” (RSDs), i.e., the location decisions that modify the country of destination of a previous offshoring investment. Specifically, we distinguish between two types of RSDs, i.e., “Relocation to the Home Country (RHC)”, also known as back-reshoring, and “Relocation to a Third Country (RTC)”, i.e., the choice to move to a second host country.Specifically, we explore how the location advantages underlying the previous offshoring decision affect the probability to undertake an RHC, rather than an RTC. Location advantages reflect the favourable conditions that a foreign country offers with respect to the home one, in terms of market-seeking, asset-seeking and efficiency-seeking (i.e., cost-saving and productivity-enhancing) opportunities. Using data from the European Restructuring Monitor, we focus on the RSDs regarding manufacturing activities, implemented across European countries between 2002 and 2015. We find that, on the one hand, when a previous offshoring investment is driven by market-seeking location advantage, firms undertaking the RSD are more likely to opt for an RHC, except during the economic crisis where market-seeking European firms seem to prefer RTCs. On the other hand, RTC is a preferred choice when the location advantage is of efficiency-seeking type. In addition to offering a broader characterization of RSDs, our study provides empirical evidence of the relationship between the offshoring and relocation decisions. Managers should be aware of this connection when designing their manufacturing internationalization strategies.     

Knowledge misappropriation risks and contractual complexity in entrepreneurial ventures’ non-equity alliances

Small Business Economics - This paper explores the role of anticipated knowledge misappropriation risks in contract design in non-equity alliances involving high-tech entrepreneurial ventures. We...     

Selecting structural innovations in DSGE models

Dynamic stochastic general equilibrium (DSGE) models are typically estimated assuming the existence of certain structural shocks that drive macroeconomic fluctuations. We analyze the consequences of estimating shocks that are “nonexistent” and propose a method to select the economic shocks driving macroeconomic uncertainty. Forcing these nonexisting shocks in estimation produces a downward bias in the estimated internal persistence of the model. We show how these distortions can be reduced by using priors for standard deviations whose support includes zero. The method allows us to accurately select shocks and estimate model parameters with high precision. We revisit the empirical evidence on an industry standard medium‐scale DSGE model and find that government and price markup shocks are innovations that do not generate statistically significant dynamics.