708 resultados para AGGLOMERATION EXTERNALITIES


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This paper estimates the impact of industrial agglomeration on firm-level productivity in Chinese manufacturing sectors. To account for spatial autocorrelation across regions, we formulate a hierarchical spatial model at the firm level and develop a Bayesian estimation algorithm. A Bayesian instrumental-variables approach is used to address endogeneity bias of agglomeration. Robust to these potential biases, we find that agglomeration of the same industry (i.e. localization) has a productivity-boosting effect, but agglomeration of urban population (i.e. urbanization) has no such effects. Additionally, the localization effects increase with educational levels of employees and the share of intermediate inputs in gross output. These results may suggest that agglomeration externalities occur through knowledge spillovers and input sharing among firms producing similar manufactures.

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The presence of a large informal sector in developing economies poses the question of whether informal activity produces agglomeration externalities. This paper uses data on all the nonfarm establishments and enterprises in Cambodia to estimate the impact of informal agglomeration on the regional economic performance of formal and informal firms. We develop a Bayesian approach for a spatial autoregressive model with an endogenous explanatory variable to address endogeneity and spatial dependence. We find a significantly positive effect of informal agglomeration, where informal firms gain more strongly than formal firms. Calculating the spatial marginal effects of increased agglomeration, we demonstrate that more accessible regions are more likely than less accessible regions to benefit strongly from informal agglomeration.

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This paper analyzes the geography of regional competitiveness in manufacturing in Brazil. The authors estimate stochastic frontiers to calculate regional efficiency of representative firms in 137 regions in the period 2000-2006, in four sectors defined by technological intensity. The efficiency results are analyzed using Markov Spatial Transition Matrices to provide insights into the transition of regions between efficiency levels, considering their local spatial context. The results indicate that geography plays an important role in manufacturing competitiveness. In particular, regions with more competitive neighbors are more likely to improve their relative efficiency (pull effect) over time, and regions with less competitive neighbors are more likely to lose relative efficiency (drag effect). The authors find that the pull effect is stronger than the drag effect.

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We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data that allows us to address simultaneously some important methodological issues, such as spatial clustering, nonlinearities, and overdispersion. This model is applied to the study of location determinants of inward greenfield investments that occurred during 2003–2007 in 249 European regions. After presenting the data set and showing the presence of overdispersion and spatial clustering, we review the theoretical framework that motivates the choice of the location determinants included in the empirical model, and we highlight some reasons why the relationship between some of the covariates and the dependent variable might be nonlinear. The subsequent section first describes the solutions proposed by previous literature to tackle spatial clustering, nonlinearities, and overdispersion, and then presents the Geo-NB-GAM. The empirical analysis shows the good performance of Geo-NB-GAM. Notably, the inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity that induces spatial clustering. Allowing for nonlinearities reveals, in keeping with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some threshold value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs never overcome positive agglomeration externalities.

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In the last two decades, authors have begun to expand classical stochastic frontier (SF) models in order to include also some spatial components. Indeed, firms tend to concentrate in clusters, taking advantage of positive agglomeration externalities due to cooperation, shared ideas and emulation, resulting in increased productivity levels. Until now scholars have introduced spatial dependence into SF models following two different paths: evaluating global and local spatial spillover effects related to the frontier or considering spatial cross-sectional correlation in the inefficiency and/or in the error term. In this thesis, we extend the current literature on spatial SF models introducing two novel specifications for panel data. First, besides considering productivity and input spillovers, we introduce the possibility to evaluate the specific spatial effects arising from each inefficiency determinant through their spatial lags aiming to capture also knowledge spillovers. Second, we develop a very comprehensive spatial SF model that includes both frontier and error-based spillovers in order to consider four different sources of spatial dependence (i.e. productivity and input spillovers related to the frontier function and behavioural and environmental correlation associated with the two error terms). Finally, we test the finite sample properties of the two proposed spatial SF models through simulations, and we provide two empirical applications to the Italian accommodation and agricultural sectors. From a practical perspective, policymakers, based on results from these models, can rely on precise, detailed and distinct insights on the spillover effects affecting the productive performance of neighbouring spatial units obtaining interesting and relevant suggestions for policy decisions.

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This paper contributes to the empirical literature on the effects of agglomeration and road accessibility on productivity of firms by looking at the case of Spain. We approach productivity indirectly by using individual wages allocated at the NUTS III level. We use a repeated cross-section of individual micro-data for the years 1995, 2002 and 2006. The availability of interprovincial travel time data for each of the three years allows controlling for transport improvements over the period by using a market potential variable. Additionally, agglomeration is approached by employment density and we control for localization economies, human capital externalities and a large set of individual and workplace characteristics. Estimating by instrumental variables, our results show a positive and significant effect of market accessibility on wages and non linear effect for employment density.

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Recent empirical work emphasizes the importance of the extensive margin of trade (new exporters, new export activities) for long run export growth. In this context, understanding the determinants of duration of new exporters is key for underpinning the dynamics of exports growth. As new exporters tend to show low survival rates, identifying the determinants of export duration is highly relevant for academic and policy purposes. In this paper, we explore whether information externalities arising from different levels of spatial interaction allow new exporters to increase the duration of their trade activities. For this, we use transaction level data on Colombian exports between 2004 and 2011. Results show that export networks, understood as the agglomeration of exporting firms at different spatial levels, reduce the risk of dropping out from exporting and that this effect is stronger the more similar are export activities carried out by firms

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The intensity of regional specialization in specific activities, and conversely, the level of industrial concentration in specific locations, has been used as a complementary evidence for the existence and significance of externalities. Additionally, economists have mainly focused the debate on disentangling the sources of specialization and concentration processes according to three vectors: natural advantages, internal, and external scale economies. The arbitrariness of partitions plays a key role in capturing these effects, while the selection of the partition would have to reflect the actual characteristics of the economy. Thus, the identification of spatial boundaries to measure specialization becomes critical, since most likely the model will be adapted to different scales of distance, and be influenced by different types of externalities or economies of agglomeration, which are based on the mechanisms of interaction with particular requirements of spatial proximity. This work is based on the analysis of the spatial aspect of economic specialization supported by the manufacturing industry case. The main objective is to propose, for discrete and continuous space: i) a measure of global specialization; ii) a local disaggregation of the global measure; and iii) a spatial clustering method for the identification of specialized agglomerations.

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The following are notes that have been distributed by me over the last few years to students in Environmental Economics at The University of Queensland. They give particular attention to whether externalities are Pareto or Kaldor-Hicks relevant from a policy point of view. Externalities are Kaldor-Hicks or Pareto irrelevant if no change is possible for which gainers could compensate losers. Both absolute and marginal externalities may be Kaldor-Hicks relevant. Infra-marginal negative externalities are often, but not always, Kaldor-Hicks irrelevant. There are at least two cases where such externalities can be relevant. First, the absolute impact of the negative externality may be so great that the source of the externality should be eliminated. Secondly, if the externality arises from production, its nature may depend on the type of production technique adopted. Although for the technique adopted, an infra-marginal negative externality occurs. That is Paretian irrelevant given that choice of this technique is the only available possibility, alternative techniques may actually be available in practice. Some of these may generate even smaller total external effects and be socially preferable. Both cases are outlined and illustrated in these notes. The analysis reveals the dangers of relying on marginalism for deciding on environmental policy. Total (external) effects are often of great social and economic importance and appropriate social choices cannot be made on the basis of marginalism alone.

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To determine self-consistently the time evolution of particle size and their number density in situ multi-angle polarization-sensitive laser light scattering was used. Cross-polarization intensities (incident and scattered light intensities with opposite polarization) measured at 135 degrees and ex situ transmission electronic microscopy analysis demonstrate the existence of nonspherical agglomerates during the early phase of agglomeration. Later in the particle time development both techniques reveal spherical particles again. The presence of strong cross-polarization intensities is accompanied by low-frequency instabilities detected on the scattered light intensities and plasma emission. It is found that the particle radius and particle number density during the agglomeration phase can be well described by the Brownian free molecule coagulation model. Application of this neutral particle coagulation model is justified by calculation of the particle charge whereby it is shown that particles of a few tens of nanometer can be considered as neutral under our experimental conditions. The measured particle dispersion can be well described by a Brownian free molecule coagulation model including a log-normal particle size distribution. (C) 1996 American Institute of Physics.

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Ramos, D., Arezes, P. M., & Afonso, P. (2015). A systematic approach for externalities in occupational safety through the use of the delphi methodology. Paper presented at the Occupational Safety and Hygiene III - Selected Extended and Revised Contributions from the International Symposium on Safety and Hygiene.

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A one-step melt-mixing method is proposed to study dispersion and re-agglomeration phenomena of the as-received and functionalized graphite nanoplates in polypropylene melts. Graphite nanoplates were chemically modified via 1,3-dipolar cycloaddition of an azomethine ylide and then grafted with polypropylene-graft-maleic anhydride. The effect of surface functionalization on the dispersion kinetics, nanoparticle re-agglomeration and interface bonding with the polymer is investigated. Nanocomposites with 2 or 10 wt% of as-received and functionalized graphite nanoplates were prepared in a small-scale prototype mixer coupled to a capillary rheometer. Samples were collected along the flow axis and characterized by optical microscopy, scanning electron microscopy and electrical conductivity measurements. The as-received graphite nanoplates tend to re-agglomerate upon stress relaxation of the polymer melt. The covalent attachment of a polymer to the nanoparticle surface enhances the stability of dispersion, delaying the re-agglomeration. Surface modification also improves interfacial interactions and the resulting composites presented improved electrical conductivity.

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The kinetics of GnP dispersion in polypropylene melt was studied using a prototype small scale modular extensional mixer. Its modular nature enabled the sequential application of a mixing step, melt relaxation, and a second mixing step. The latter could reproduce the flow conditions on the first mixing step, or generate milder flow conditions. The effect of these sequences of flow constraints upon GnP dispersion along the mixer length was studied for composites with 2 and 10 wt.% GnP. The samples collected along the first mixing zone showed a gradual decrease of number and size of GnP agglomerates, at a rate that was independent of the flow conditions imposed to the melt, but dependent on composition. The relaxation zone induced GnP re-agglomeration, and the application of a second mixing step caused variable dispersion results that were largely dependent on the hydrodynamic stresses generated.

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We implement a family of efficient proposals to share benefits generated in environments with externalities. These proposals extend the Shapley value to games with externalities and are parametrized through the method by which the externalities are averaged. We construct two slightly different mechanisms: one for environments with negative externalities and the other for positive externalities. We show that the subgame perfect equilibrium outcomes of these mechanisms coincide with the sharing proposals.