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on Economic Geography |
| By: | Dávid Krisztián Nagy |
| Abstract: | I study how geography shaped city formation and aggregate development in the United States prior to the Civil War. To guide my analysis, I first present a conjecture that cities' farm hinterlands fostered both city development and aggregate growth: the hinterland hypothesis. The hinterland hypothesis has rich implications on how various elements of U.S. geography -railroads, changes in U.S. political borders, increasing U.S. population, and international trade - affected city formation and U.S. growth. To quantitatively evaluate the hinterland hypothesis and its implications, I assemble a novel historical dataset on population, trading routes and agricultural productivity at a high spatial resolution, and combine it with a dynamic quantitative model of economic geography. I find evidence for the hinterland hypothesis by showing that the model can quantitatively replicate the key patterns of U.S. urbanization and city formation. Finally, I conduct a series of counterfactuals in the model to quantify the effect of geography on cities and growth, guided by the implications of the hinterland hypothesis. Results indicate that railroads were responsible for 8.2% of urban population in 1860 and for 27% of real GDP growth between 1830 and 1860. The effect of international trade was similar in magnitude, while population growth slowed down urbanization and GDP growth. The effect of political border changes was small during the period. |
| Keywords: | quantitative economic geography, economic growth and development, city formation, transport infrastructure |
| JEL: | O14 O18 O51 R12 R13 |
| Date: | 2020–02 |
| URL: | http://d.repec.org/n?u=RePEc:bge:wpaper:1172&r=all |
| By: | Davide Castellani (Henley Business School, University of Reading, UK); Giovanni Marin (Department of Economics, Society, Politics, University of Urbino, Italy; SEEDS); Sandro Montresor (Gran Sasso Science Institute, Italy); Antonello Zanfei (Department of Economics, Society, Politics, University of Urbino, Italy) |
| Abstract: | The paper builds on (eco-)innovation geography and international business studies to investigate the effects of MNEs on regional specialisation in green technologies. Combining the OECD-REGPAT and the fDi Markets datasets with respect to 1,050 European NUTS3 regions over the period 2003-2014, we find that MNEs can positively impact on regions’ specialisation in environmental technologies, when their Foreign Direct Investments (FDIs) occur in industries with a green technological footprint. The effect of green FDIs is further reinforced if they involve R&D activities. We also find that the relatedness of environmental technologies to pre-existing regional specialisations exerts a negative moderating effect on the role of green R&D FDIs in shaping patterns of specialisation. In particular, green R&D FDIs have a larger effect in regions whose prior knowledge base is highly unrelated to environmental technologies. This result is consistent with the idea that MNEs inject the host region with external knowledge, which makes the development of green-technologies less place-dependent. |
| Keywords: | green regional specialisation; MNEs; FDIs; environmental innovation |
| JEL: | O31 O33 R11 R58 |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:srt:wpaper:0620&r=all |
| By: | Jia Chen; Yongcheol Shin; Chaowen Zheng |
| Abstract: | In this paper, we develop a unifying econometric framework for the analysis of heterogeneous panel data models that can account for both spatial dependence and unobserved common factors. To tackle the challenging issues of endogeneity caused by both the spatial lagged term and the correlation between regressors and factors, we propose to approximate common factors by cross-section averages of independent variables only, and deal with the spatial endogeneity via the instrumental variables. We develop the individual estimators as well as the Mean Group and the Pooled estimators, and establish their consistency and asymptotic normality. Monte Carlo simulations confirm that the finite sample performance of our proposed estimators are quite satisfactory. We demonstrate the usefulness of our approach with an application to a gravity model of bilateral trade flows for 91 pairs of 14 European Union (EU) countries, and find that the trade flows between the UK and EU members would fall substantially following a hard Brexit. |
| Keywords: | Cross Section Dependence, Heterogeneous Spatial Panel Data Model, Factor Model, Instrumental Variable Analysis |
| JEL: | C13 C15 C23 |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:yor:yorken:20/03&r=all |
| By: | Anne Albert-Cromarias (CleRMa - Clermont Recherche Management - Clermont Auvergne - École Supérieure de Commerce (ESC) - Clermont-Ferrand - UCA - Université Clermont Auvergne); Catherine dos Santos (CleRMa - Clermont Recherche Management - Clermont Auvergne - École Supérieure de Commerce (ESC) - Clermont-Ferrand - UCA - Université Clermont Auvergne) |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-02513403&r=all |
| By: | Jonathan I. Dingel; Brent Neiman |
| Abstract: | Evaluating the economic impact of "social distancing"' measures taken to arrest the spread of COVID-19 raises a fundamental question about the modern economy: How many jobs can be performed at home? We classify the feasibility of working at home for all occupations and merge this classification with occupational employment counts for the United States. Our classification implies that 34 percent of U.S. jobs can plausibly be performed at home. |
| JEL: | D24 J22 J61 O30 R12 R32 |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:26948&r=all |
| By: | ADACHI Daisuke; FUKAI Taiyo; KAWAGUCHI Daiji; SAITO Yukiko |
| Abstract: | We construct Commuting Zones (CZs) in Japan using the commuting patterns observed in the quinquennial Population Census between 1980 and 2015. CZs are geographical units which are created by integration of municipalities. Municipalities are not good geographical units to capture labor market because many workers commute to different municipalities, while prefectures include more than one labor market. CZs are created so that they are not over-integrated and the ratio of commuting within the same unit is high. In particular, we employ a hierarchical agglomerative clustering method popularized by Tolbert and Sizer (1996), which is used for delineating the standard CZs in the US. For example, from 2366 municipalities in the year 2005, we delineate 331 CZs that are mutually exclusive and completely exhaustive. We show the effectiveness of CZs in extracting heterogeneities of economic variables in analyzing labor markets. CZs functions well for implementing a large variety of geographical analysis. |
| Date: | 2020–03 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:20021&r=all |