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on Economic Geography |
| By: | Flavio L. Pinheiro; Pierre-Alexandre Balland; Ron Boschma; Dominik Hartmann |
| Abstract: | As regions evolve, their economies become more complex, and they tend to diversify into related activities. Although there is a bright side to this diversification process in terms of economic development, there may also be a dark side to it, as it possibly contributes to regional inequalities. The paper uses data on industries and patents to analyze the diversification patterns of 283 regions in 32 European countries over the past 15 years. We find that only the most economically advanced regions have the opportunity to diversify into highly complex activities. These regions tend to focus on related high-complex activities, while lagging regions focus on related low-complex activities, creating a spatial inequality feedback loop. This pattern creates a wicked problem for innovation policy: the strategy needed to improve the innovativeness of the European knowledge system might disproportionately benefit regions that are already developed and foster disparities. |
| Keywords: | dark side of innovation, geography of innovation, regional diversification, complexity, regional inequality, Smart Specialisation Policy |
| JEL: | O25 O33 R11 O31 |
| Date: | 2022–01 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2202&r= |
| By: | Dieter F. Kogler; Ronald B. Davies; Changjun Lee; Keungoui Kim |
| Abstract: | This paper aims to uncover the mechanism of how the network properties of regional knowledge spaces contribute to technological change from the perspective of regional knowledge entry-relatedness and regional knowledge entry-potential. Entry-relatedness, which has been previously employed to investigate the technology evolution of regional economies, is advanced by introducing a knowledge gravity model. The entry-potential of a newly acquired regional specialisation has been largely ignored in the relevant literature; surprisingly given the high relevance that is attributed to the recombination potential of new capabilities. In other words, just adding new knowledge domains to a system is not sufficient alone, it really depends on how these fit into the existing system and thus can generate wider economic benefits. Based on an empirical analysis of EU Metro and non-Metro regions from 1981 to 2015, we find that entry-relatedness has a significant negative association with novel inventive activities, while entry-potential has a significant positive association with the development of novel products and processes of economic value. This highlights that regions’ capacity to venture into high-potential areas of technological specialization in the knowledge space outperforms purely relatedness driven diversification that is frequently promoted in the relevant literature. |
| Keywords: | Regional knowledge space; Entry-relatedness; Entry-potential; Technological change; Economic growth; Patent analysis |
| JEL: | O33 O31 R11 |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:ucn:oapubs:10197/12731&r= |
| By: | Piyush Panigrahi |
| Abstract: | Larger Indian firms selling inputs to other firms tend to have more customers, tend to be used more intensively by their customers, and tend to have larger customers. Motivated by these regularities, I propose a novel empirical model of trade featuring endogenous formation of input-output linkages between spatially distant firms. The empirical model consists of (a) a theoretical framework that accommodates first order features of firm-to-firm network data, (b) a maximum likelihood framework for structural estimation that is uninhibited by the scale of data, and (c) a procedure for counterfactual analysis that speaks to the effects of micro- and macroshocks to the spatial network economy. In the model, firms with low production costs end up larger because they find more customers, are used more intensively by their customers and in turn their customers lower production costs and end up larger themselves. The model is estimated using novel micro-data on firm-to-firm sales between Indian firms. The estimated model implies that a 10% decline in inter-state border frictions in India leads to welfare gains ranging between 1% and 8% across districts. Moreover, over half of the variation in changes in firms’ sales to other firms can be explained by endogenous changes in the network structure. |
| Keywords: | production networks, international trade, economic geography |
| JEL: | F11 F12 D24 C67 C68 L11 O11 O12 R12 R15 D85 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_9466&r= |
| By: | Arman Khachiyan; Anthony Thomas; Huye Zhou; Gordon H. Hanson; Alex Cloninger; Tajana Rosing; Amit Khandelwal |
| Abstract: | We apply deep learning to daytime satellite imagery to predict changes in income and population at high spatial resolution in US data. For grid cells with lateral dimensions of 1.2km and 2.4km (where the average US county has dimension of 55.6km), our model predictions achieve R2 values of 0.85 to 0.91 in levels, which far exceed the accuracy of existing models, and 0.32 to 0.46 in decadal changes, which have no counterpart in the literature and are 3-4 times larger than for commonly used nighttime lights. Our network has wide application for analyzing localized shocks. |
| JEL: | R0 |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:29569&r= |