|
on Economic Geography |
|
Issue of 2021‒09‒13
seven papers chosen by Andreas Koch Institut für Angewandte Wirtschaftsforschung |
| By: | Tijl Hendrich (CPB Netherlands Bureau for Economic Policy Analysis); Jennifer Olsen (CPB Netherlands Bureau for Economic Policy Analysis); Steven Brakman (RUG); Charles van Marrewijk (UU) |
| Abstract: | The trade literature often treats countries as dimensionless points, which is a strong assumption. Agglomeration or lumpiness of production factors within countries can affect the national pattern of trade. In this paper we analyze comparative advantage patterns for 22 cities and 4 regions for (a selection of) 83 sectors within The Netherlands. Our findings are as follows. First, analysis of the lens condition indicates that the regional concentration of production factors (lumpiness) does not affect the Dutch national trade pattern. Second, despite the fact that the lens condition is verified, comparative advantage patterns across locations differ significantly from each other. Third, the differences across locations of comparative advantage patterns is explained by the interaction of local skill-abundance and sector skill-intensity, in line with the predictions of the factor abundance model. |
| JEL: | F11 F15 R12 |
| Date: | 2021–01 |
| URL: | http://d.repec.org/n?u=RePEc:cpb:discus:418&r= |
| By: | Raoul van Maarseveen |
| Abstract: | Despite the existence of a large urban-rural education gap in many countries, little attention has been paid whether cities enjoy a comparative advantage in the production of human capital. Using Dutch administrative data, this paper finds that conditional on family characteristics and cognitive ability, children who grow up in urban regions consistently attain higher levels of human capital compared to children in rural regions. The elasticity of university attendance with respect to population density is 0.07, which is robust across a wide variety of specifications. Hence, the paper highlights an alternative channel to explain the rise of the city. . |
| JEL: | I20 J24 R10 |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:cpb:discus:412&r= |
| By: | Eduardo Gutiérrez (Banco de España); Enrique Moral-Benito (Banco de España); Daniel Oto-Peralías (Department of Economics, Universidad Pablo de Olavide); Roberto Ramos (Banco de España) |
| Abstract: | We exploit the GEOSTAT 2011 population grid with a very high 1-km2 resolution to document that Spain presents the lowest density of settlements among European countries. Only a small fraction of the Spanish territory is inhabited, particularly in its southern half, which goes hand in hand with a high degree of population concentration. We uncover through standard regression analysis and spatial regression discontinuity that this anomaly cannot be accounted for by adverse geographic and climatic conditions. The second part of the paper takes a historical perspective on Spain’s settlement patterns by showing that the spatial distribution of the population has been very persistent in the last two centuries, and that the abnormally low density of settlements with respect to European neighbors was already visible in the 19th century, which indicates that this phenomenon has not emerged recently as a consequence of the transformations associated with industrialization and tertiarization. Using data on ancient sites, we find that Spain did not feature scarcity of settlements in comparison to other countries in pre-medieval times, suggesting that its current anomalous settlement pattern has not always existed and is therefore not intrinsic to its geography. |
| Keywords: | Economic Geography, Spain |
| JEL: | R10 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:pab:wpaper:21.13&r= |
| By: | Rob Euwals (CPB Netherlands Bureau for Economic Policy Analysis); Harro van Heuvelen (CPB Netherlands Bureau for Economic Policy Analysis); Gerdien Meijerink (CPB Netherlands Bureau for Economic Policy Analysis); Jan Möhlmann (CPB Netherlands Bureau for Economic Policy Analysis); Simon Rabaté (CPB Netherlands Bureau for Economic Policy Analysis) |
| Abstract: | Contrary to other studies, we find no robust effect of an increase in trade with China and Central European (CEE) countries on local employment, wages and inequality in the Netherlands. If there is an effect, it is small, with positive effects of increased exports counteracting the negative effects of increased imports. One of the reasons why we find different results for the Netherlands is the fact that the Dutch manufacturing industry was already undergoing changes well before the emergence of China and the CEE countries and became less sensitive to import competition from China or the CEE countries. In addition, the Netherlands has collective wage negotiations, which may help to explain that we do not find any effects on wages. While the effect of increased trade with China and the CEE countries on manufacturing jobs is limited, it can create uncertainty for workers. The negative effect of import competition and the positive impact of export opportunities on manufacturing jobs also point to adjustments across industries and regions. Transitioning workers to new types of work can be difficult for these workers, as they are (temporarily) unemployed and may need to move to other regions. |
| JEL: | F16 J31 R11 |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:cpb:discus:426&r= |
| By: | Jan Eeckhout; Christoph Hedtrich; Roberto Pinheiro |
| Abstract: | We show that differential IT investment across cities has been a key driver of job and wage polarization since the 1980s. Using a novel data set, we establish two stylized facts: IT investment is highest in firms in large and expensive cities, and the decline in routine cognitive occupations is most prevalent in large and expensive cities. To explain these facts, we propose a model mechanism where the substitution of routine workers by IT leads to higher IT adoption in large cities due to a higher cost of living and higher wages. We estimate the spatial equilibrium model to trace out the effects of IT on the labor market between 1990 and 2015. We find that the fall in IT prices explains 50 percent of the rising wage gap between routine and non-routine cognitive jobs. The decline in IT prices also accounts for 28 percent of the shift in employment away from routine cognitive towards non-routine cognitive jobs. Moreover, our estimates show that the impact of IT is uneven across space. Expensive locations have seen a stronger displacement of routine cognitive jobs and a larger widening of the wage gap between routine and non-routine cognitive jobs. |
| Keywords: | IT investment; Job Polarization; Spatial Sorting; Urban Wage Premium |
| JEL: | D21 J24 J31 R23 |
| Date: | 2021–09–08 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedcwq:93021&r= |
| By: | Hübler, Olaf (Leibniz University of Hannover) |
| Abstract: | This paper investigates the regional differences in the spread of COVID-19 infections in Germany. A machine learning selection procedure is used to reduce variables from a pool of potential influencing variables. The empirical analysis shows that both regional structural variables and regionally aggregated personality traits are significant for the different corona spread. The latter characteristics express differences in mentality between the federal states. The north-east of the country shows a lower degree of affectedness. Regions with a high proportion of migrants show a higher incidence than others. If personality traits are neglected, the migrants' influence is overestimated. With school education and the risk of poverty, two further important regional characteristics are identified. Federal states that have a disproportionately high share of the population with low school education tend to have fewer COVID-19 cases. With regard to poverty, no clear statement can be made. The more the population tends to be responsible towards fellow human beings, the higher is the risk of a more pronounced spread. Where there is a tendency towards altruism, which consists of helping other people, a higher level of COVID-19 infections is revealed. A significant positive correlation between infections and testing is shown by the estimates. The link between vaccinations and the number of infections is less clear. Across the three corona waves,significant changes emerge. This relates in particular to the proportion of migrants and the proportion of families at risk of poverty. The effects decrease over the course of the pandemic. |
| Keywords: | COVID-19, states, regional characteristics, personality traits, vaccinations, testing, machine learning, cluster-robust estimation, unobserved characteristics, heterogeneity, corona waves, structural break |
| JEL: | C21 C23 I12 R12 |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14669&r= |
| By: | Kulenkampff, Gabriele; Ockenfels, Martin; Plückebaum, Thomas; Zoz, Konrad; Zuloaga, Gonzalo |
| Abstract: | According to the EU policy, a future-proof broadband supply for all European households is to be achieved by 2025. There is already a wide range of fibre deployment in Europe. However, the expansion of fibre-based access networks in Europe to date has taken place mainly in large cities. In other areas, the expansion is sluggish or non-existent. As a result, a digital divide between urban and rural areas in Europe is arising. The spatial disparity in fibre roll-out is often justified by market stake holders with significant regional cost differences. In the absence of private-sector investment, government subsidy programmes are often used to improve broadband coverage. Thus, politicians have to deal with the question about the level of investment required and the spatial distribution of subsidy needs. In this paper, we will therefore investigate the question of how significant the heterogeneity in the costs of Very High Capacity (VHC) networks in Germany actually is and whether and how the costs for Very High Capacity (VHC) networks differ between urban and rural regions. In the first part of the paper, we will analyse the regional cost differences of access network areas on the basis of bottom-up calculated investment figures. In the second part of the paper, we establish statistical estimation models that explain these regional cost differences. For this purpose, we use publicly available data. As a reference value for regionally differentiated costs of Very High Capacity (VHC) access networks, we use the results of a detailed bottom-up modelling of an FTTH network carried out for the whole of Germany. The model uses georeferenced household and business location data and optimizes the access network routes along the street network in a bottom-up manner. This model allows us to determine regionally differentiated FTTH investment at the level of access areas. By matching this data with the EU-wide standardized EUROSTAT urban/rural typology classification (predominantly urban, intermediate and predominantly rural), we determine whether and to which extent significant regional cost differences can be found in Germany applying these classifications. One focus is on determining the spread of investment requirements, especially among rural areas. Based on our experience, these areas exhibit the lowest economic viability of a network roll-out and, thus, the highest need for funding. By using statistical indicators, we analyse the suitability of the EUROSTAT classification as a differentiation criterion for regional cost differences. Here, we are particularly interested in whether the areas defined as rural form a sufficiently homogeneous group, and whether they show comparable levels of required investment. Our findings confirm that the differentiation criterion used, namely EUROSTAT urban/rural typology classification, is not satisfactory in measuring regional cost differences. It cannot sufficiently account for a large share of observable differences in fibre-based access network costs. Since it is desirable to answer questions regarding the required funding for selected regions based on publicly available data, we apply regression models to identify alternative influencing factors on the basis of publicly available data, in order to better explain observable regional cost differences. Here, we find that a handful of geographical factors are capable of explaining 95% of the geographical differences in fibre investment requirements, the most relevant being the number of connection lines, the number of households per kilometre of road in built-up areas, the main road length per built-up area and the share of built-up area in relation to overall area. In the last part of the analysis, we examine whether the derived results are also meaningful in a political and regulatory context. Discussions about the necessity of promoting high-speed networks usually take place at the level of local authorities. Therefore, in a final step, we address the question whether the statistical relationships derived from the regression model at the level of access areas also apply at a higher aggregated, i.e. NUTS3, level. In summary, we show that for Germany, classifications based on subscriber density exhibit a significant spread in the investment costs of Very High Capacity (VHC) access networks, which is most pronounced in rural clusters. Statistical analyses using regression models can improve the result if geographical elements of the settlement structure are considered in the analysis. |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:itsb21:238033&r= |