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on Economic Geography |
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Issue of 2023‒10‒09
four papers chosen by Andreas Koch, Institut für Angewandte Wirtschaftsforschung |
| By: | Moritz Goldbeck (ifo Institute & LMU Munich) |
| Abstract: | Digital work settings potentially facilitate remote collaboration and thereby decrease geographic frictions in knowledge work. Here, I analyze spatial collaboration patterns of some 191 thousand software developers in the United States on the largest code repository platform GitHub. Despite advanced digitization in this occupation, developers are geographically highly concentrated, with 79.8% of users clustering in only ten economic areas, and colocated developers collaborate about nine times as much as non-colocated developers. However, the colocation effect is much smaller than in less digital social or inventor networks, and apart from colocation geographic distance is of little relevance to collaboration. This suggests distance is indeed less important for collaboration in a digital work setting while other strong drivers of geographic concentration remain. Heterogeneity analyses provide insights on which types of collaboration tend to colocate: the colocation effect is smaller within larger organizations, for high-quality projects, among experienced developers, and for sporadic interactions. Overall, this results in a smaller colocation effect in larger economic areas. |
| Keywords: | geography; digitalization; networks; knowledge economy; colocation; |
| JEL: | L84 O18 O30 R32 |
| Date: | 2023–09–05 |
| URL: | http://d.repec.org/n?u=RePEc:rco:dpaper:422&r=geo |
| By: | Clément Imbert; Joan Monras; Marlon Seror; Yanos Zylberberg |
| Abstract: | This paper argues that migrants’ decision to bring their dependent family members shapes their consumption behavior, their choice of destination, and their sensitivity to migration barriers. We document that in China: (i) rural migrants disproportionately move to expensive cities; (ii) in these cities they live without their family and in poorer housing conditions; and (iii) they remit more, especially when living without their family. We then develop a quantitative general equilibrium spatial model in which migrant households choose whether, how (with or without their family), and where to migrate. We estimate the model using plausibly exogenous variation in wages, housing prices, and exposure to family migration costs. We use the model to estimate migration costs and relate them to migration policy. We find that hukou policies protect workers in large, expensive, and high income cities at the expense of rural households, who use remittances to overcome some of these costs. |
| Keywords: | migration; remittances; economic geography; spatial equilibrium |
| JEL: | R12 J61 O15 |
| Date: | 2023–08–30 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedfwp:96924&r=geo |
| By: | Steven Poelhekke (Vrije Universiteit Amsterdam); Benjamin Wache (CPB Netherlands) |
| Abstract: | Does venture capital (VC) investment yield economic growth? A large literature studies the effect of VC investments on firm-level activity, but its effects on economic growth are less well understood. We identify the effect of VC investment flows on destination county employment, wages, and establishment creation, using a novel instrument that captures the ‘social connectedness’ of counties to major sources of VC investment. Using detailed data on VC flows from investors to companies, we find a large positive impact of VC investment, suggesting that strong social connections to large venture capital hubs are an important contributor to regional economic growth. |
| Keywords: | Growth, venture capital, social connectedness |
| JEL: | R11 G24 G41 |
| Date: | 2023–08–30 |
| URL: | http://d.repec.org/n?u=RePEc:tin:wpaper:20230050&r=geo |
| By: | Badi H. Baltagi (Center for Policy Research, Maxwell School, Syracuse University, 426 Eggers Hall, Syracuse, NY 13244) |
| Abstract: | The spatial Mundlak model first considered by Debarsy (2012) is an alternative to fixed effects and random effects estimation for spatial panel data models. Mundlak modelled the correlated random individual effects as a linear combination of the averaged regressors over time plus a random time-invariant error. This paper shows that if spatial correlation is present whether spatial lag or spatial error or both, the standard Mundlak result in panel data does not hold and random effects does not reduce to its fixed effects counterpart. However, using maximum likelihood one can still estimate these spatial Mundlak models and test the correlated random effects specification of Mundlak using Likelihood ratio tests as demonstrated by Debarsy for the Mundlak spatial Durbin model. |
| Keywords: | Mundlak Regression, Panel Data, Fixed and Random Effects, Spatial error model, Spatial Durbin model |
| JEL: | C33 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:max:cprwps:258&r=geo |