Mark S. Henry

The Hinterland's Stake in Metropolitan Growth: Evidence from Selected Southern Regions

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.

Galston, William A., and Karen J. Baehler. Rural Development in the United States: Connecting Theory, Practice, and Possibilities. Washington DC: Island Press, 1995, xiv + 353 pp.,

Rural Development in the United States presents a comprehensive evaluation of the economic, environmental, and political implications of past rural development and a thorough consideration of the directions in which future development efforts should go. The authors have assembled the best of what is being thought and done with regard to rural development in the United States, and they place it in a broad theoretical, historical, and geographical context. Rural Development in the United States includes important information about how national and international trends affect rural communities and development strategies, and it will help guide rural economic development policy in the United States during the 1990s and beyond.

32.00 paper

In this article, comparisons are made of several spatial econometric approaches to estimation of multiequation models of small region development applied to rural community growth. Spatial extensions of the Carlino and Mills’s 1987 and Boarnet’s 1994 models are estimated to analyze the spread of population and employment into 3,500 rural communes in six French regions. Results are compared for the Henry, Barkley, and Bao’s 1997 extension of the Boarnet model, the Carlino-Mills and Boarnet models, and three spatial autoregressive models suggested by Rey and Boarnet in 1998. Tests for spread and backwash effects in the spatial autoregressive model, and the Carlino-Mills and Boarnet models, with spatial autoregressive terms added, indicate that population growth spreads to rural communities from nearby areas but that evidence on employment spread is less robust. The Henry et al. modification to Boarnet adds insight into how urban growth affects proximate rural areas by decomposing the spatial cross-regressive term into rural area, urban core, and urban fringe effects.

Spatial Econometric Models for Simultaneous Systems: Application to Rural Community Growth in France

Abstract In this paper we use an extension of the Carlino and Mills and Boarnet models to test for city size and growth influences on rural population and employment changes. In a sample of communes in six selected French regions, we find that both the size of the urban center and the growth rates of urban employment and population affect rural population and employment change. Medium size urban places have the strongest positive impacts on rural commune change.

Size and growth of urban centers in French labor market areas: consequences for rural population and employment

The purpose of this study is to determine the role of industry agglomerations on industry-level employment change in non-metro areas of the United States. Regression analysis of cross-sectional data is used to estimate the determinants of non-metro 1981–1992 employment change for ten two-digit SIC manufacturing industries. Industry agglomerations in metro and non-metro areas are identified using cluster analysis. Area characteristics included in the regression equations are diversity of the local economy, industry mix, average plant size and availability of urbanization economies. The findings indicate that industry agglomerations were associated with both larger employment gains in areas with growing industry employment and larger employment losses for areas with declining employment. Neither regional specialization in the industry nor nearby metro agglomerations were significant determinants of employment change in non-metro areas.

Industry Agglomerations and Employment Change in Non‐Metropolitan Areas

Abstract RAS is a spatial data analysis system integrated with ARC/INFO, in which we combine spatial data analytical techniques with GIS visual techniques to provide a flexible and convenient tool in regional studies. In this paper, we introduce some traditional spatial statistical analysis techniques such as the Moran I, as well as newly developed exploratory data analysis techniques such as local Moran and local Geary statistics. Criteria are suggested for the identification of spatial association by combining the local Moran and local Geary. The usefulness of these techniques in identifying and quantifying spatial associations within economic regions is illustrated using data for southern counties and census tracts.

RAS: a regional analysis system integrated with ARC/INFO

Recent trends in the southeastern states toward increased use of irrigation in agriculture may be attributed to risk aversion management by farmers in response to recent drought periods. Despite ample annual average rainfall in the Southeast during the growing season, the vicissitudes of rainfall patterns provide sufficient reason to consider irrigation for field crops as well as for vegetables and fruit (Ganguly). Increased use of irrigation additionally results in new demands for water in rural areas. It is also well documented that nonmetropolitan areas are experiencing substantial rates of positive net immigration (Wardell and Gilchrist). In the Southeast, there is a trend for new manufacturing plants to locate in rural areas where wages, taxes, and union activity are at low levels. As growth occurs in these nonmetropolitan regions, industrial, residential, and commercial activities require additional supplies of water.

A Method For Estimating the Value of Water Among Sectors of A Regional Economy

A continuing interest of regional scientists is the development of econometric models for the identification of local characteristics associated with regional growth (e.g., Carlino and Mills, 1987; Thurston and Yezer, 1994; Boarnet, 1994a). Recent advances in spatial econometrics and geographic information systems (GIS) enhance the reliability of small region growth models by incorporating the influences of spatial linkages on the local development process (e.g., Anselin, 1988b; Anselin and Florax, 1995b). Modeling the influence of spatial linkages along with local characteristics appears most beneficial in studies of small area economic change where inter-area spillovers may be extensive. For example, economic and population change in the “edge cities” of urban complexes may affect development of nearby rural areas.

Identifying Urban-Rural Linkages: Tests for Spatial Effects in the Carlino-Mills Model

tha frmcofte addition, the share of southern state personal ~~~~rural South: ~income from farming is typically less than 2 1. Agriculture is not the key to rural eco- income from farming is tyicaly less than 2 nomic development; . Agriculture i not the keytoruraleco- percent (Henry). More refined estimates of 2 Economic restructuring underway is likely the role of agriculture in rural economic activto widen the rural-urban economic gap; ity can be made and are likely to reveal a awnd the rura nstronger set of links between the food and 3. Policy intervention will be needed to re- fiber system and rural places than is evident fiber system and rural places than is evident 3. Policy intervention will be needed to re- from the broader measures of dominant ecoduce the size of the gap. Rural develop- nomic base or state income shares. ment policy will be primarily a state and Considr the ai nkaes etwn the local responsibility with very limited aid local responsibility with very limited aid farm sector and the farm system depicted in from the Federal government. State ex- Figure 1 (Tamblyn and Powell). Research is thperiment stationse needed byand shoultate and prlocal needed to estimate these basic links for rural agencies to evaluate the effectiveness of t

SOUTHERN FARMS AND RURAL COMMUNITIES: DEVELOPING DIRECTIONS FOR ECONOMIC DEVELOPMENT RESEARCH AND POLICY

Urban and regional planning and decision making have been aided over the years by variously effective, spatially-oriented technologies (Parent & Church, 1987). The postmodern version of spatial decision aids are known as geographic information systems (GIS) and typically take the form of a toolkit of data management, editing, analysis and output programs resident on computationally powerful, graphically sophisticated computer workstations. Fullfledged GISs handle both geographic entities (points, lines, areas) and their attributes in an integrated environment. GIS technology is employed in a growing variety of disciplines concerned with analysis or decision-making in the spatial domain (Aronoff, 1989; Burrough, 1986; Maguire, Goodchild, & Rhind, 1991; Ripple, 1989; Starr & Estes, 1990). Among other capabilities, GIS facilitates integration of disparate data sets, creation of new and derivative data sets, and development and analysis of spatially explicit variables. These latter may in turn be employed in models which have previously lacked such specificity (Dajani & Ortolando, 1979; Parent & Church, 1987; Wilson, 1984). The project described here employs GIS to integrate infrastructure data collected for general economic development purposes (Cowen & Shinar, 1989; Cowen & Shirley, 1991) with other general purpose data to analyze the relationship between infrastructure investments and economic expansion, as evidenced by employment growth. To do so, this project employs GIS to develop new and derivative spatial data sets to fit the hypothesized spatial process being studied, and to supply spatially referenced variables to more traditional econometric modeling