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on Economic Geography |
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Issue of 2018‒09‒10
seven papers chosen by Andreas Koch Institut für Angewandte Wirtschaftsforschung |
| By: | David S. Jacks; Dennis Novy |
| Abstract: | We examine the evolution of market potential and its role in driving economic growth over the long twentieth century. Theoretically, we exploit a structural gravity model to derive a closed-form solution for a widely-used measure of market potential. We are thus able to express market potential as a function of directly observable and easily estimated variables. Empirically, we collect a large dataset on aggregate and bilateral trade flows as well as output for 51 countries. We find that market potential exhibits an upward trend across all regions of the world from the early 1930s and that this trend significantly deviates from the evolution of world GDP. Finally, using exogenous variation in trade-related distances to world markets, we demonstrate a significant causal role of market potential in driving global income growth over this period. |
| Keywords: | economic geography, market potential, structural gravity, trade costs |
| JEL: | F10 N70 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7164&r=geo |
| By: | Rodríguez-Pose, Andrés; Wilkie, Callum |
| Abstract: | This article traces the ascent of China from knowledge economy laggard to world leader over the last two decades, using a comparative perspective. Chinese trends in R&D and patenting are compared to those of the countries of the ‘triad’ (the European Union, Japan and the US), as well as to those of other large emerging economies (Brazil, India, Mexico and South Africa). The analysis demonstrates how both in innovation inputs and outputs China reflects an innovation reality closer to that of the most developed areas of the world than to that of other emerging countries. However, the rapid ascent of Chinese innovation has generated a distinct set of territorial dynamics, with innovation much more geographically concentrated than elsewhere in the world and more reliant on agglomeration forces than on more traditional ‘innovative’ drivers. Such a distinct geography of innovation may have until now facilitated the innovation surge in China, but poses serious future risks in terms of the sustainability of the system. |
| Keywords: | innovation; knowledge economy; R&D; patenting; regions; China |
| JEL: | N0 |
| Date: | 2016–11–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:84294&r=geo |
| By: | OTAZAWA Toshimori; OHIRA Yuki; Jos VAN OMMEREN |
| Abstract: | This study contributes to the literature on the relationship between geographical and relation-based distances of economic agents. We aim to estimate the causal effect of a firm's position in the inter-firm transaction network on its spatial location within a city. Using micro data of inter-firm financial transactions for non-retail firms in the metropolitan areas of Japan, we demonstrate that the more central firms in transaction networks tend to have smaller inter-firm distances and therefore locate at more accessible places within the city. We also find that the results are robust to alternative specifications both of network centrality measures and spatial accessibility measures. It is also declared that the effect for single establishment firms are much stronger than that for multi-establishment firms. Furthermore, the result shows that this effect is noticeable for young firms in knowledge-intensive industries. The evidence suggests the potential importance of the inter-firm transaction pattern as a determinant of urban spatial configuration. |
| Date: | 2018–08 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:18054&r=geo |
| By: | Shibaev, Sergei S. |
| Abstract: | This paper develops a statistical model for measuring spatial interactions when estimating macroeconomic regimes and regime shifts. The model is applied to study the contagion and propagation of recessions in small regional economies in the United States from 1990 to 2015. The empirical analysis identifies two geographical concentrations (or clusters) where small regional economies were affected by recessions in similar ways. These clusters are interpreted as groups of regions that are potentially at-risk to collective economic distress, which is useful for national and regional policy makers. The first identified cluster is characterized by regional economies with important roles in the financial sector, while the second cluster is characterized by the oil and gas extraction sector. The empirical findings uncover an important propagation dynamic that would be overlooked if one were to apply the model without the spatial extension developed in this paper. Specifically, the evidence shows significant spatial spillovers between small regional economies, meaning that shocks to regions are expected to be higher, when shocks to neighboring regions are high on average. The magnitude of this effect is amplified for the period spanning and following the Great Recession. |
| Keywords: | Financial Economics, Public Economics |
| Date: | 2016–11 |
| URL: | http://d.repec.org/n?u=RePEc:ags:quedwp:274695&r=geo |
| By: | MORI Tomoya |
| Abstract: | This paper reviews the extant formal models that explain the spatial pattern together with the size distribution of cities, and discusses the remaining research questions to be answered in this literature. To obtain meaningful results about the spatial patterns of cities, a model needs to depart from the most popular; a two-region and the systems-of-cities frameworks in urban and regional economics in which there is no variation in interregional distance. This is one of the major reasons that only few formal models have been proposed in this literature. To draw implications as much as possible from the extant theories, this review involves extensive discussions on the behavior of the many-region extension of the extant models. The mechanisms that link the spatial pattern of cities and the diversity in city sizes are also discussed separately in detail. |
| Date: | 2018–08 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:18053&r=geo |
| By: | Li, Liyao (School of Economics, Singapore Management University); Yang, Zhenlin (School of Economics, Singapore Management University) |
| Abstract: | In this paper, M-estimation and inference methods are developed for spatial dynamic panel data models with correlated random effects, based on short panels. The unobserved individual-specific effects are assumed to be correlated with the observed time-varying regressors linearly or in a linearizable way, giving the so-called correlated random effects model, which allows the estimation of effects of time-invariant regressors. The unbiased estimating functions are obtained by adjusting the conditional quasi-scores given the initial observations, leading to M-estimators that are consistent, asymptotically normal, and free from the initial conditions except the process starting time. By decomposing the estimating functions into sums of terms uncorrelated given idiosyncratic errors, a hybrid method is developed for consistently estimating the variance-covariance matrix of the M-estimators, which again depends only on the process starting time. Monte Carlo results demonstrate that the proposed methods perform well in finite sample. |
| Keywords: | Adjusted quasi score; Dynamic panels; Correlated random effects; Initial-conditions; Martingale difference; Spatial effects; Short panels |
| JEL: | C10 C13 C15 C21 C23 |
| Date: | 2018–08–23 |
| URL: | http://d.repec.org/n?u=RePEc:ris:smuesw:2018_015&r=geo |
| By: | Bortz, Pablo.; Moncaut, Nicolás.; Robert, Verónica.; Sarabia, Marianela.; Vázquez, Darío. |
| Abstract: | En Argentina existen algunos casos de clústeres tecnológicos incipientes, en los que las interacciones entre actores públicos y privados están dando lugar a la emergencia de nuevas actividades intensivas en conocimiento. En el presente trabajo utilizamos el marco multidimensional de habilidades colectivas con el objetivo de analizar dos experiencias locales en las que ha surgido un conjunto de empresas en sectores de alta tecnología: nano y biotecnología en Santa Fe y software en Tandil. Si bien diversos indicadores permiten caracterizar a estas experiencias como exitosas en términos de transferencia tecnológica, creación de empresas, generación de empleo y exportaciones, el análisis de su trayectoria también muestra ciertas restricciones, como la baja resiliencia y lenta expansión, en Santa Fe, y modalidades de inserción en las cadenas globales de valor en segmentos de bajo valor, en Tandil. De un modo similar se identifican dificultades para la proyección de las experiencias locales en el territorio nacional. Los casos analizados permiten dar cuenta de la importancia de las diferencias contextuales y de los elementos territoriales en la construcción de las habilidades colectivas y reivindican la importancia del aprendizaje interactivo para el desarrollo de clústeres tecnológicos. |
| Abstract: | In Argentina, there are some cases of incipient technological clusters, in which the interactions between public and private actors result in the emergence of new knowledge-intensive activities. This study uses a multi- dimensional framework of collective capabilities with the aim of analysing local experiences, in which a number of enterprises emerged in sectors of high technology such as the nano and biotechnology in Santa Fe and software in Tandil. Even though various indicators allow to consider these experiences as successful in terms of technology transfer, creation of enterprises, jobs and exports, the analysis of their development paths show also some limitations such as low resilience and slow expansion, in Santa Fe, and the insertion into low value segments of Global Value Chains in Tandil. Moreover, difficulties were identified in up-scaling local experiences to the national territory. The cases analysed reveal the importance of the contextual differences and the territorial elements in the construction of collective capabilities, and stress the importance of interactive apprenticeship for the development of technological clusters. |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:ilo:ilowps:994998293402676&r=geo |