IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Amount and Spatial Distribution of Public Open Space to Maximize the Net Benefits from Urban Recreation

  • Kovacs, Kent F.

The spatial arrangement of public open spaces in communities has an important influence on the recreational net benefits from those public open spaces. A prime example of a public open space in communities where spatial arrangement is important is parks. From the perspective of maximizing the net benefits of recreation, there is a tradeoff between placing all the land for parks in a single park and making several parks to reduce the travel costs of households to the parks. If several parks are made, then the amount of land in each park is reduced, and the recreational net benefit of a trip to any of the parks is less. Since recreation is an important source of value from parks, an examination of an optimal spatial arrangement of parks for recreation in a community is of interest to community planners. The community is assumed to be a slice of a larger urban area or a small town since the housing structure and socioeconomic characteristics of the community is assumed homogeneous. The demand for recreation trips to parks is shifted by the socioeconomic characteristics of the population and the size of the parks. The size of the parks is the division of the number of parks into the total amount of land in parks. The price of a trip to a park is the cost of a round trip to the park. The consumer surplus of a trip to a park is the net benefit the person receives from the park. The amount of land for parks and number of parks to maximize the net benefits from recreation is determined from the model of the demand for trips to a park. Comparative static results suggest that the optimal amount of land, number of parks, and the size of the parks depend on the socioeconomic characteristics of the city. Cities with higher populations, more income, and more education should have more land in parks, more parks, and the parks should be smaller. Lower travel costs and prices of land should result in more land in parks and more parks, but there should be no influence on the park size. Data are collected from seventy cities on the amount of land, size, and number of parks. The distances between the parks, distances of the parks from downtown, and other variables relevant to the spatial distribution of parks are also obtained. Data on the socioeconomic characteristics of the population, travel costs, and the price of land are collected for the cities. The same data is collected for each of the one hundred and sixty nine zip codes associated with the seventy cities. These zip codes are spatially smaller and may better represent homogeneous communities. Three equations are estimated to learn the influence of the socioeconomic and travel cost features of a city on the spatial distribution of parks. The three equations are the estimation of the amount of land, the number and the size of parks. The results of the estimation for the amount of land in parks equation match the theoretical predictions, and the fit of the relationship is good. Population, population density, and land price have a significant influence on the amount of land in parks. A larger population makes a city create more land in parks while population density and the price of land makes a city reduce the amount of land. The results of the estimation for the number and size of parks are less clear. The results match the comparative static predictions loosely, and the fit of the equations is not good. These findings may reflect incorrect assumptions on the preferences of people for park size in the theoretical model, or the data that the preferences are supposed to represent are clouded with noise from government regulations, costly removal of parks, and other features of the complexity of urban spatial structure. Although recreation is significant component of the value households derive from parks, there has been little attention paid to determining the spatial arrangement of parks to maximize the net benefits. The theoretical results suggest that the amount of land and the spatial distribution of parks should be sensitive to the socioeconomic characteristics of a community. However, only the predicted signs of the socioeconomic characteristic on the amount of land in parks hold up empirically. The spatial distribution of land is more sensitive to institutional factors that probably make it necessary to have more data on parks to fully identify the relationship between the socioeconomic characteristics and the number and size of parks.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://purl.umn.edu/19206
Download Restriction: no

Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2005 Annual meeting, July 24-27, Providence, RI with number 19206.

as
in new window

Length:
Date of creation: 2005
Date of revision:
Handle: RePEc:ags:aaea05:19206
Contact details of provider: Postal: 555 East Wells Street, Suite 1100, Milwaukee, Wisconsin 53202
Phone: (414) 918-3190
Fax: (414) 276-3349
Web page: http://www.aaea.orgEmail:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Halstead, John M. & Whitcomb, Joanna L. & Hamilton, Lawrence C., 1999. "Economic Insights Into The Siting Problem: An Application Of The Expected Utility Model," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 28(1), April.
  2. Diana Weinhold & Eustaquio J. Reis, 2001. "Model Evaluation and Causality Testing in Short Panels: The Case of Infrastructure Provision and Population Growth in the Brazilian Amazon," Journal of Regional Science, Wiley Blackwell, vol. 41(4), pages 639-657.
  3. Jared Hewko & Karen E Smoyer-Tomic & M John Hodgson, 2002. "Measuring neighbourhood spatial accessibility to urban amenities: does aggregation error matter?," Environment and Planning A, Pion Ltd, London, vol. 34(7), pages 1185-1206, July.
  4. Achim Kemmerling & Andreas Stephan, 2001. "The Contribution of Local Public Infrastructure to Private Productivity and Its Political-Economy: Evidence from a Panel of Large German Cities," CIG Working Papers FS IV 01-14, Wissenschaftszentrum Berlin (WZB), Research Unit: Competition and Innovation (CIG).
  5. James M. Poterba, 1997. "Demographic structure and the political economy of public education," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 16(1), pages 48-66.
  6. Edward L. Glaeser & Jose A. Scheinkman & Andrei Shleifer, 1995. "Economic Growth in a Cross-Section of Cities," NBER Working Papers 5013, National Bureau of Economic Research, Inc.
  7. Haughwout, Andrew F., 2002. "Public infrastructure investments, productivity and welfare in fixed geographic areas," Journal of Public Economics, Elsevier, vol. 83(3), pages 405-428, March.
  8. Nathalie Gaussier, 2001. "The Spatial Foundations of Obnoxious Goods Location: The Garbage Dumps Case," Regional Studies, Taylor & Francis Journals, vol. 35(7), pages 625-636.
  9. Claudia Goldin & Lawrence F. Katz, 1998. "Human Capital and Social Capital: The Rise of Secondary Schooling in America, 1910 to 1940," NBER Working Papers 6439, National Bureau of Economic Research, Inc.
  10. Martin, Ron, 1999. "The New 'Geographical Turn' in Economics: Some Critical Reflections," Cambridge Journal of Economics, Oxford University Press, vol. 23(1), pages 65-91, January.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:ags:aaea05:19206. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.