Abstract:In this article we extend the Carlino and Mills and Boarnet models of local development to test for the presence and direction of rural area linkages to urban areas in Functional Economic Areas (FEAs). In a sample of southern FEAs, we detect a mix of spillover and backwash effects from urban core and fringe areas to their rural hinterlands. Rural-area population and employment both grew faster than average between 1980 and 1990 if in an FEA with a pattern of urban decentralization.
“…Chi (2010), examining the effects of highway "expansions" on population change in Wisconsin during the 1980s and 1990s, suggests that highway expansions mostly influenced population increase in suburban areas, thereby strengthening suburbanisation. On the other hand, Henry et al (1997) report that the initial stock of highways at 1980 was unrelated with population growth in rural hinterland tracts in South Carolina, Georgia and North Carolina during the 1980s. Meanwhile, McMillen and Lester (2003) contend that population density growth between 1970 and 2000 was lower within a third of a mile of highway interchanges than other locations in the Chicago metropolitan area.…”
Section: The Impact Of Road Infrastructure On Lu Changementioning
confidence: 99%
“…Other studies, however, do not find evidence of a significant relation between highways and employment. Henry et al (1997), for example, conclude that the density of highways in 1980 was not a significant factor in attracting employment growth during the 1980s, and Arauzo-Carod (2007) finds no significant relationship between TINs (road or rail) and the distribution of professional groups of population and workers across the territory.…”
Section: The Impact Of Road Infrastructure On Lu Changementioning
Improvements in geographical information systems, the wider availability of high-resolution digital data and more sophisticated econometric techniques have all contributed to increasing academic interest and activity in long-term impacts of transport infrastructure networks (TINs) on land use (LU). This paper provides a systematic review of recent empirical evidence from the USA, Europe and East Asia, classified regarding the type of transport infrastructure (road or rail), LU indicator (land cover, population or employment density, development type) and outcome (significance, relationship's direction) as well as influential exogenous factors. Proximity to the rail network is generally associated with population growth (particularly soon after the development of railway infrastructure), conversion to residential uses and the development of higher residential densities. Meanwhile, proximity to the road network is frequently associated with increases in employment densities as well as the conversion of land to a variety of urban uses including commercial and industrial development. Compared with road infrastructure, the impact of rail infrastructure is often less significant for land cover or population and employment density change. The extent of TINs' impact on LU over time can be explained by the saturation in TIN-related accessibility and LU development.
ARTICLE HISTORY
“…Chi (2010), examining the effects of highway "expansions" on population change in Wisconsin during the 1980s and 1990s, suggests that highway expansions mostly influenced population increase in suburban areas, thereby strengthening suburbanisation. On the other hand, Henry et al (1997) report that the initial stock of highways at 1980 was unrelated with population growth in rural hinterland tracts in South Carolina, Georgia and North Carolina during the 1980s. Meanwhile, McMillen and Lester (2003) contend that population density growth between 1970 and 2000 was lower within a third of a mile of highway interchanges than other locations in the Chicago metropolitan area.…”
Section: The Impact Of Road Infrastructure On Lu Changementioning
confidence: 99%
“…Other studies, however, do not find evidence of a significant relation between highways and employment. Henry et al (1997), for example, conclude that the density of highways in 1980 was not a significant factor in attracting employment growth during the 1980s, and Arauzo-Carod (2007) finds no significant relationship between TINs (road or rail) and the distribution of professional groups of population and workers across the territory.…”
Section: The Impact Of Road Infrastructure On Lu Changementioning
Improvements in geographical information systems, the wider availability of high-resolution digital data and more sophisticated econometric techniques have all contributed to increasing academic interest and activity in long-term impacts of transport infrastructure networks (TINs) on land use (LU). This paper provides a systematic review of recent empirical evidence from the USA, Europe and East Asia, classified regarding the type of transport infrastructure (road or rail), LU indicator (land cover, population or employment density, development type) and outcome (significance, relationship's direction) as well as influential exogenous factors. Proximity to the rail network is generally associated with population growth (particularly soon after the development of railway infrastructure), conversion to residential uses and the development of higher residential densities. Meanwhile, proximity to the road network is frequently associated with increases in employment densities as well as the conversion of land to a variety of urban uses including commercial and industrial development. Compared with road infrastructure, the impact of rail infrastructure is often less significant for land cover or population and employment density change. The extent of TINs' impact on LU over time can be explained by the saturation in TIN-related accessibility and LU development.
ARTICLE HISTORY
“…However, other studies using different time lags and geographic scales (e.g. , Henry et al 1997, and Vias and Mulligan 1999, provide mixed evidence, and little work has considered the interactions between jobs and population at finer spatial scales, such as the TAZs used here. This work addresses that challenge, while allowing for spatial interactions and correlations among unobserved factors influencing household and employment intensities over space.…”
ABSTRACT:Household and employment counts (by type) are key inputs to models of travel demand. For a variety of reasons, spatial dependence is very likely present in and across these counts. In order to identify the nature of these unobserved relationships, this study performs a series of Lagrange multiplier tests to confirm the co-existence of spatial lag and error processes within individual equations (6 household types and 3 employment categories). It then provides the first application of a feasible generalized spatial 3SLS estimation procedure for a seemingly unrelated regression (SUR) model of these equations.In the resulting model of Austin, Texas data, local land use conditions offer substantial predictive power of households and jobs, and transportation access plays a role, as anticipated. The work demonstrates that SUR estimation of land use intensities from parcel-level data with two types of spatial dependence is feasible and meaningful. Coupled with an upstream model of land use type, this work offers the key inputs for travel demand analyses, with transportation system performance feedback.
“…They find no substantial effect of the transit system on the growth (i.e., population and total employment), while it appears that the system "has altered the composition of employment in favor of the public sector … in those areas with high levels of commercial activity" (p. 202). Henry, Barkley, and Bao (1997), mentioned above, pay attention to rural development factors as well as the spatial linkages among urban, suburban, and rural areas. In the study, a variety of local amenity features (infrastructure, public service, housing, labor force, school quality, etc) are considered using a set of representative variables (p.486-487), in order to come up with policy recommendations for rural area development.…”
Section: Applicationsmentioning
confidence: 99%
“…Carlino and Mills 1987;Boarnet 1994b;Clark and Murphy 1996;Vias 1999) to the studies on the spatial linkages (see e.g. Henry et al 1997Henry et al , 1999Henry et al , and 2001Feser and Isserman 2005) and the investigations on development policy issues (see e.g. Bollinger and Ihlanfeldt.…”
Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. and Mills (1987) and further extended by Boarnet (1994a), have been widely adopted for empirical assessments of a broad range of development issues, including 1) whether jobs follow people or people follow jobs; 2) how urbansuburban -rural areas interact with each other; 3) what policy and other factors are essential for local and regional development; etc. This study identifies key advantages of the framework, particularly its dynamic nature, and then presents an application of the model to small area population and employment forecasting and impact analysis, beyond existing uses of the framework for empirical assessments. The present application uses data for the Chicago metropolitan area and shows that the framework can be a powerful tool for small area studies, when it is combined hierarchically with another model that describes regional macroeconomic growth trajectories. Combined with the regional growth model, it projects small area growth trajectories under several different conditions. The paper also discusses some methodological challenges in this type of application.
Terms of use:
Documents in
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.