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on Economic Geography |
| By: | Tom Broekel; Rune Dahl Fitjar; Silje Haus-Reve |
| Abstract: | Contemporary research highlights the importance of relatedness, diversity, and complexity for regional economic development. However, few empirical studies simultaneously test the relevance of all these dimensions or examine how their importance varies across distinct spatial contexts. The literature also concentrates on explaining regional diversification, whereas we know less about how they affect economic and employment growth. In addition, most studies have examined industrial relatedness at the expense of the at least similarly crucial occupational dimension when studying knowledge-based regional development. The chapter discusses these issues and presents a study on how occupational diversity, complexity and relatedness shape employment growth in Norway to illustrate how an occupational perspective on regional industries can add to the understanding of evolutionary economic development. |
| Keywords: | relatedness, diversity, complexity, occupation, region, Norway |
| JEL: | R11 O31 O33 J24 |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2135&r= |
| By: | Gianandrea Lanzara; Matteo Santacesaria |
| Abstract: | We consider a spatial model where a continuous set of sellers (e.g. farmers) must choose one trading location in a discrete set (e.g. cities) in a subset of the plane. Locations differ in terms of productivity, and shipping costs depend on the underlying geography via very general distance functions. Our analysis combines tools from general equilibrium theory and computational geometry. The key insight is that, under Constant Elasticity of Substitution (CES) preferences, the equilibrium trading choices of farmers can be represented as a Voronoi tessellation with additive weights, where the weights are determined at the market equilibrium. Using this insight, we prove that an equilibrium partition of space into market areas exists and is unique for general underlying geographies, and we characterize their comparative statics in terms of the model parameters. Moreover, we develop a set of tools that are useful in empirical applications. We show that the model can be solved with a simple, and economically-interpretable, gradient-descent algorithm, and we discuss two metrics to evaluate the distance between tessellations. Finally, we provide an illustrative application to the case of Swiss cantons. |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2110.15849&r= |
| By: | Batabyal, Amitrajeet; Beladi, Hamid |
| Abstract: | There are no theoretical studies in regional science that examine which region to locate in from the standpoint of a creative class member, given that the pertinent regional authorities (RAs) are competing among themselves to attract the creative class using subsidies. This gap provides the motivation for our paper. This paper’s contribution is that it is the first to theoretically study the regional location choice of creative class members when the RAs of the locations in which they might locate are using subsidies to attract them. Specifically, a knowledge good producing creative class member must decide which of two regions (A or B) to locate his plant in. This good is produced using a Cobb-Douglas function with creative and physical capital. We analyze plant location in four cases. In the benchmark case, we show that the representative creative class member ought to locate his plant in the less expensive region B. Next, we show that a small subsidy to creative capital by region A switches the plant location decision from region B to A. Finally, when both regions grant identical subsidies to creative capital, the representative creative class member is indifferent between locating in regions A and B. So, for identical subsidies to affect the plant location decision, they are better targeted to physical and not to creative capital. |
| Keywords: | Creative Capital, Interregional Competition, Physical Capital, Subsidy |
| JEL: | R11 R58 |
| Date: | 2021–02–15 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:110446&r= |
| By: | Courtney Coile |
| Abstract: | As Americans work longer in response to a changing retirement landscape, it is important to ask whether there are groups being left out of this trend. Geography is a natural lens through which to examine this question, given regional disparities in the employment of prime-age individuals. In this study, we explore the geography of retirement using data from the U.S. Census/American Community Survey and other sources. We find large differences across U.S. commuting zones in employment rates at older ages, with a gap of about 20 percentage points between areas at the 90th and 10th percentiles of employment. Low-employment areas are systematically different, with a less educated and more diverse population, more low-wage jobs and import competition from China, poorer health outcomes and health care access, lower government spending, and more income inequality. Although these correlations are not necessarily causal, these factors collectively can explain about four-fifths of the geographic variation in employment at older ages. |
| JEL: | J22 J26 R23 |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:29433&r= |
| By: | Ernawati Pasaribu (STIS Polytechnic of Statistics, Jakarta); Puguh B. Irawan (STIS Polytechnic of Statistics, Jakarta); Tiodora H. Siagian (STIS Polytechnic of Statistics, Jakarta); Ika Yuni Wulansari (STIS Polytechnic of Statistics, Jakarta); Robert Kurniawan (STIS Polytechnic of Statistics, Jakarta) |
| Abstract: | This research study focuses on measuring the possible spillover effects of socio-economic interactions on COVID-19 pandemic vulnerability across Indonesia’s regions by utilising a spatial simultaneous model. The COVID-19 pandemic vulnerability level here is used to indicate the extent to which a region is susceptible to the spreading COVID-19 pandemic, as determined by not only the region’s COVID-19 related epidemiological factors but also by its relevant socio-demographic and economic aspects, housing, environmental health, and availability of health facilities. High COVID-19 pandemic vulnerability levels were mostly found in districts in Java Island and southern Sumatera, suggesting high population density and mobility in both regions. It was revealed that 31 districts have low COVID-19 risk levels (from epidemiological indicators-related measurements), but they have high COVID-19 vulnerability levels (from epidemiological and socioeconomic indicators-based measurements). Labour productivity was found to have a reciprocal relationship with COVID-19 vulnerability, proving that the COVID-19 pandemic has a significant impact on labour productivity and vice versa. On the other hand, regional independence affects COVID-19 vulnerability, but this does not apply the other way around. Moreover, this study has also proven that COVID-19 pandemic vulnerability levels have socio-economic spillover effects on neighbouring areas in Indonesia. |
| Keywords: | Spillover Effects; Spatial Simultaneous Model; COVID-19 Vulnerability Levels |
| JEL: | C31 R23 R53 |
| Date: | 2021–11–07 |
| URL: | http://d.repec.org/n?u=RePEc:era:wpaper:dp-2021-42&r= |
| By: | Lara Abdel Fattah; Mounir Amdaoud |
| Abstract: | This article seeks to measure the impact of the Covid-19 outbreak on local employment in metropolitan France. Based on an extensive literature on economic resilience and the first available local data on the number of job losses, we highlight, on the one hand, the differences in the resilience of employment areas in the face of the crisis and, on the other hand, the key explanatory factors behind these disparities. The first econometric results show a significant influence of the density, the level of employment in the industry, the productive structure and the entrepreneurial dynamics of the territory.However, no relationship was found between employment areas with high levels of excess mortality and those that exhibit large job losses. |
| Keywords: | Covid-19, economic resilience, employment, employment areas |
| JEL: | R11 R12 E24 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:drm:wpaper:2021-30&r= |