Co-auteur
  • GAFFARD Jean-Luc (3)
  • NESTA Lionel (2)
  • GUILLOU Sarah (2)
  • SALIES Evens (2)
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Type de Document
  • Working paper (9)
  • Article (7)
  • Communication non publiée (2)
  • Livre (1)
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This paper uses a spatial Cournot competition model to examine the effect of increasing returns to scale (IRS) in manufacturing as an agglomerating force between a fixed number of firms competing over regional markets. As one would expect, with a constant returns to scale (CRS) manufacturing sector the dispersed symmetric equilibrium will always be stable. The first important result is the confirmation that even low levels of IRS provide incentives for the manufacturing firms to deviate from this symmetric equilibrium and move towards agglomeration. An interesting aspect of the results, however, is that IRS do not automatically imply an unstable symmetric equilibrium, and the threshold required to provoke instability increases with transport costs.

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La nouvelle économie géographique présente les « rendements croissants d’agglomération » comme une variable explicative privilégiée de la concentration spatiale de l’activité économique. Dans ce cadre théorique, ces rendements croissants découleraient d’une préférence pour la variété dans la consommation. Un des enjeux empiriques de la nouvelle économie géographique reste cependant l’estimation de leur taille. Nous cherchons à évaluer la présence de tels rendements croissants d’agglomération dans la structure spatiale des salaires français, en utilisant la méthodologie d’estimation développée pour le Royaume-Uni par Fingleton (2003). Le résultat central de notre étude est la présence statistiquement significative de rendements croissants d’agglomération sur les zones d’emploi françaises, du même ordre de grandeur que ceux trouvés par Fingleton. De plus, par rapport à l’analyse originale, nous montrons que l’analyse est peu sensible à la pondération des distances entre zones d’emploi, et que la prise en compte d’une plus grande dimension temporelle permet d’améliorer la significativité des résultats.

An information-theoretic thought experiment is developed to provide a methodology for predicting endowment distributions in the absence of information on agent preferences. The allocation problem is first presented as a stylised knapsack problem. Although this knapsack allocation is intractable, the social planner can nevertheless make precise predictions concerning the endowment distribution by using its information-theoretic structure. By construction these predictions do not rest on the rationality of agents. It is also shown, however, that the knapsack problem is equivalent to a congestion game under weak assumptions, which means that the planner can nevertheless evaluate the optimality of the unobserved allocation.

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There centincreasein the breath of computational methodologies has been matched with a corresponding increase in the difficulty of comparing the relative explanatory power of models from different methodological lineages.In order to help address this problem a Markovian information criterion (MIC) is developed that is analogous to the Akaike information criterion (AIC) in its theoretical derivation and yet can be applied to any model able to generate simulated or predicted data,regardless of its methodology. Both the AIC and proposed MIC rely on the Kullback–Leibler (KL) distance between model predictions and real data as a measure of prediction accuracy. Instead of using the maximum likelihood approach like the AIC, the proposed MIC relies instead on the literal interpretation of the KL distance as the inefficiency of compressing real data using modelled probabilities, and therefore uses the output of a universal compression algorithm to obtain an estimate of the KL distance. Several Monte Carlo tests are carried out in order to (a) confirm the performance of the algorithm and (b) evaluate the ability of the MIC to identify the true data-generating process from a set of alternative models.

This paper analyses the methodology developed by Behrens and Murata (2007) to introduce variable mark-ups into models of monopolistic competition. Their risk- aversion explanation to the presence of ¯xed mark-ups in the Dixit and Stiglitz (1977) model is validated; however, we show that their constant absolute risk aversion solution ignores existing mechanisms found in the new Keynesian literature. From these we develop a model of new economic geography with a variable elasticity of substitution and variable mark-ups consistent with Behrens and Murata (2007). However, we argue that from both a theoretical and empirical perspective this new Keynesian approach is preferable to the solution of Behrens and Murata (2007).

Using a generalised version of the Venables (1996) model, this paper explores the relative locations of two vertically linked sectors with knowledge spillovers. Analytical investigation shows that the dynamic properties of the Venables model are significantly affected by the presence of spillovers. In particular, the own-cost reduction effects at low transport costs can be so strong that runaway agglomeration phenomenon appears in a manner consistent with the “black hole” concept found in the literature. However, the assumption that because information decays over space means that these black hole dynamics are endogenous to the model and disappear when transport costs are high enough. Importantly, the location predictions obtained in simulations of the model are consistent with the empirical finding that industrials sector that benefit from spillovers are typically more agglomerated than sector that do not benefit from such spillovers.

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An inconsistency is found in the demand side of the NEG models developed in Pflüger (2004) that follows from the absence of a non-negativity constraint on the consumption of agricultural goods. This seriously weakens the results of the original paper and those of ensuing contributions in Pflüger and Südekum (2008a,b). A solution to this problem is developed which imposes severe restrictions on the relative size of two of the core model parameters, the implications of which are examined.

La concentration de l’activité économique dans l’espace, et l’existence même des villes, est une des régularités empiriques les plus visibles en économie. Il n’est donc pas étonnant que cet aspect géographique de l’économie soit une notion ancienne, comme le montrent les contributions fondatrices de la science régionale de von Thünen (1833), Marshall (1890), ,Hotelling, (1929), Lösch (1940), ou Hirschman (1958). Il a fallu attendre l’article de Paul Krugman en 1991 pour que cette facette de l’économie connaisse un regain d’intérêt et pour que les mécanismes à la base de ces effets géographiques soient systématiquement étudiés. (Premier paragraphe)

in Journal of Economic Dynamics and Control Publié en 2016-12
Observatoire français des conjonctures économiques
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The present paper tests a new model comparison methodology by comparing multiple calibrations of three agent-based models of financial markets on the daily returns of 24 stock market indices and exchange rate series. The models chosen for this empirical application are the herding model of Gilli and Winker (2003), its asymmetric version by Alfarano et al. (2005) and the more recent model by Franke and Westerhoff (2011), which all share a common lineage to the herding model introduced by Kirman (1993). In addition, standard ARCH processes are included for each financial series to provide a benchmark for the explanatory power of the models. The methodology provides a consistent and statistically significant ranking of the three models. More importantly, it also reveals that the best performing model, Franke and Westerhoff, is generally not distinguishable from an ARCH-type process, suggesting their explanatory power on the data is similar

in Revue de l'OFCE - Analyse et prévisions Publié en 2012-10
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Maximum entropy predictions are made for the Kirman ant model as well as the Abrams-Strogatz model of language competition, also known as the voter model. In both cases the maximum entropy methodology provides good predictions of the limiting distribution of states, as was already the case for the Schelling model of segregation. An additional contribution, the analysis of the models reveals the key role played by relative entropy and the model in controlling the time horizon of the prediction.

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