What Can Be Learned from Spatial Economics?

Abstract

Spatial economics aims to explain why there are peaks and troughs in the spatial distribution of wealth and people, from the international and regional to the urban and local. The main task is to identify the microeconomic underpinnings of centripetal forces, which lead to the concentration of economic activities, and centrifugal forces, which bring about the dispersion of economic activities at the regional and urban levels. Transportation matters at both scales, but in a different way. The emphasis is on the interregional flows of goods and passenger trips at the regional level and on individual commuting at the urban level. ( JEL F12, L13, R12, R23, R30, R40)

Housing Constraints and Spatial Misallocation

“…Also, using data from the National Longitudinal Survey of Youth, we find that workers in high wage cities tend to have higher Armed Forces Qualification Test scores, but the correlation disappears when we control for education, race, and ethnicity. 18 18 Recent evidence based on longitudinal data that follow workers moving from low wage cities to high wage cities also suggests that unobservable differences in skill are limited once education is controlled for. Baum-Snow and Pavan (2012) finds that sorting on unobserved ability within education group contributes little to observed TFP.-Since local employment is a function of local TFP and the local wage, we can invert this relationship to express local TFP as a function of employment and wages.…”

On the drivers of UK direct investment in the Spanish regions: A spatial Durbin approach

“…There is a clear reason justifying a regional approach: the fact that this type of linkages is stronger the higher the level of data disaggregation, namely the smaller the unit of analysis. This is why many papers establish a clear link between spatial econometrics and regional economics; indeed, one of the most recent ones, published by Proost and Thisse (2019) refers to regional economics as one of the constituent subfields of spatial economics…”

A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province

“…With respect to locational variables, we included a variable representing whether a county is a coastal county and two distance variables measuring the geographical proximity of a county to Xiamen (the state-level special economic zone in Fujian province and the most affluent city in terms of per capita GDP) and to its affiliated prefecture-level city. As economic activities were unevenly distributed across places, those places with locational advantages such as being adjacent to the province's growth center would attract more development opportunities, i.e., the spatial spillover effects well-recognized in the economic geography literature [19,36,37]. These factors could affect the levels of urban development as well as pollution emissions and would compromise the estimated relationships between urban expansion and pollutant emissions if excluded from the modelling analysis.…”