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on Economic Geography |
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Issue of 2024‒02‒26
five papers chosen by Andreas Koch, Institut für Angewandte Wirtschaftsforschung |
| By: | Redding, Stephen J. |
| Abstract: | Economic activity is highly unevenly distributed within cities, as reflected in the concentration of economic functions in specific locations, such as finance in the Square Mile in London. The extent to which this concentration reflects natural advantages versus agglomeration forces is central to a range of public policy issues, including the impact of local taxation and transport infrastructure improvements. This paper reviews recent quantitative urban models, which incorporate both differences in natural advantages and agglomeration forces and can be taken directly to observed data on cities. We show that these models can be used to estimate the strength of agglomeration forces and evaluate the impact of transportation infrastructure improvements on welfare and the spatial distribution of economic activity. |
| Keywords: | cities; commuting; transportation; urban economics |
| JEL: | R00 |
| Date: | 2023–01–25 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:121373&r=geo |
| By: | Hwanoong Lee; Changsu Ko; Wookun Kim |
| Abstract: | We exploit a series of public-sector entity relocations in South Korea as an exogenous source of variation in public sector employment to estimate the local employment multiplier. We find that the introduction of one public sector employment position increases private sector employment by one unit, primarily driven by the service sector. Consistent with existing literature, we document that the effect of public employment on private employment is highly localized. In addition to changes in private employment, we also discover that the relocations led to a positive net influx of residents into the treated neighborhoods; this effect is also localized. Lastly, by estimating the local employment multiplier for each relocation site, we document the heterogeneity of the local employment multiplier and provide suggestive evidence that this het-erogeneity is shaped by the local economic environment's capacity to accommodate additional general equilibrium responses. |
| Keywords: | employment multiplier, public employment, spatial spillover, migration, heterogeneity |
| JEL: | H31 J45 J61 R11 R23 R58 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10870&r=geo |
| By: | Kathryn Baragwanath Vogel; Gordon H. Hanson; Amit Khandelwal; Chen Liu; Hogeun Park |
| Abstract: | This paper integrates daytime and nighttime satellite imagery into a spatial general-equilibrium model to evaluate the returns to investments in new motorways. Our approach has particular value in developing-country settings in which granular data on economic activity are scarce. To demonstrate our method, we use multi-spectral imagery—publicly available across the globe—to evaluate India’s varied road construction projects in the early 2000s. Estimating the model requires only remotely-sensed data, while evaluating welfare impacts requires one year of population data, which are increasingly available through public sources. We find that India’s road investments from this period improved aggregate welfare, particularly for the largest and smallest urban markets. The analysis further reveals that most welfare gains accrued within Indian districts, demonstrating the potential benefits of using of high spatial resolution of satellite images. |
| JEL: | O1 R1 |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32047&r=geo |
| By: | Ben Gilbert (Department of Economics and Business, Colorado School of Mines); Hannah Gagarin (Department of Economics and Business, Colorado School of Mines); Ben Hoen (Lawrence Berkeley National Laboratory) |
| Abstract: | The goals of this paper are twofold: we first aim to quantify the impact of US wind development on local communities in terms of earnings and employment for workers and establishments. Second, we examine and then illustrate how the use of data aggregated to arbitrary spatial units (i.e., counties) can lead to biased economic impact estimates. We accomplish these goals using disaggregated, geocoded data on the universe of workers and establishments from 23 states who participated in their state’s unemployment insurance program. We compare estimates of regional economic spillovers from aggregating this data in two ways. First, we aggregate to increasing 20-mile rings around the location of wind projects (and matched control locations) and estimate impacts in a difference-in-differences framework. Second, we aggregate to the county level and then use county centroids to further aggregate county-level data to increasing 20-mile rings before re-estimating the same specifications. We find that the average wind project causes employment at establishments within 20 miles to increase by between 3.5 to 4.5 percent, whereas we find no discernible average effect on employment at greater distances, or for earnings at any distance. We find that the employment effect persists for as many as four years after the project arrives. Using worker data, we find employment and earnings effects of similar aggregate magnitude, but spread across further distances from the wind project. This is consistent with wind development spurring economic activity at nearby establishments, which improves employment prospects for workers who may commute to those establishments. Results using county-aggregated data are much smaller and mostly statistically insignificant. This has implications not just for policymakers, but for researchers who aim to continue to understand how burgeoning energy sectors such as wind impact local areas. |
| Keywords: | wind power, employment, income, geographic spillovers |
| JEL: | J2 J3 Q4 R12 |
| Date: | 2023–01 |
| URL: | http://d.repec.org/n?u=RePEc:mns:wpaper:wp202301&r=geo |
| By: | Luca Barbaglia; Lorenzo Frattarolo; Niko Hauzenberger; Dominik Hirschbuehl; Florian Huber; Luca Onorante; Michael Pfarrhofer; Luca Tiozzo Pezzoli |
| Abstract: | Timely information about the state of regional economies can be essential for planning, implementing and evaluating locally targeted economic policies. However, European regional accounts for output are published at an annual frequency and with a two-year delay. To obtain robust and more timely measures in a computationally efficient manner, we propose a mixed-frequency dynamic factor model that accounts for national information to produce high-frequency estimates of the regional gross value added (GVA). We show that our model produces reliable nowcasts of GVA in 162 regions across 12 European countries. |
| Date: | 2024–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2401.10054&r=geo |