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

Natural Resource Curse and Poverty in Appalachian America

  • Mark D. Partridge
  • Michael R. Betz
  • Linda Lobao

The Appalachian mountain region has long been characterized by deep poverty which led to the formation of the Appalachian Regional Commission (ARC) in 1965. The ARC region covers West Virginia and parts of 12 other states, running from New York to Mississippi (Ziliak 2012). The ARC region had an average county poverty rate of over 40 percent in 1960, about double the national average (Deaton and Niman 2012; Ziliak 2012). While the poverty gap between the ARC region and the rest of the nation closed significantly by 1990, it remained nearly twice as large in Central Appalachia. There are many reasons for higher poverty in Appalachia in general and Central Appalachia in particular. Possible causes include a low-paying industry structure, below average education, low household mobility, and remoteness from to cities (Weber et al. 2005; Partridge and Rickman 2005; Lobao 2004). A key distinction between Central Appalachia and the rest of the ARC region is its historic dependence on coal mining. There is long literature arguing that the area’s dependence on coal mining has contributed to its deep poverty through weaker local governance, entrepreneurship, and educational attainment, as well as degrading the environment, poor health outcomes, and limitations on other economic opportunities (Deaton and Niman 2012; James and Aadland 2011). These factors are broadly associated with the natural resources curse in the international development literature. More recently, the process of mountain top mining (MTM) has expanded coal mining’s environmental footprint in the region, possibly increasing health risks and further reducing the chances for long-term amenity-led growth that can alleviate poverty (Deller 2010; Woods and Gordon 2011). This study reinvestigates the causes of county poverty rates in Appalachia with a special focus on coal mining’s role. Using data over the 1990-2010 period we assess whether coal mining continues to have a positive association with poverty rates,

(This abstract was borrowed from another version of this item.)

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://hdl.handle.net/10.1093/ajae/aas086
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Agricultural and Applied Economics Association in its journal American Journal of Agricultural Economics.

Volume (Year): 95 (2013)
Issue (Month): 2 ()
Pages: 449-456

as
in new window

Handle: RePEc:oup:ajagec:v:95:y:2013:i:2:p:449-456
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.org/
Email:


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. Mark D. Partridge & Dan S. Rickman, 2008. "Distance From Urban Agglomeration Economies And Rural Poverty," Journal of Regional Science, Wiley Blackwell, vol. 48(2), pages 285-310.
  2. Dorfman, Jeffrey H. & Patridge, Mark D. & Galloway, Hamilton, 2008. "Are High-Tech Employment and Natural Amenities Linked?: Answers from a Smoothed Bayesian Spatial Model," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6459, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  3. Mark D. Partridge & Dan S. Rickman, 2005. "High-Poverty Nonmetropolitan Counties in America: Can Economic Development Help?," International Regional Science Review, , vol. 28(4), pages 415-440, October.
  4. Dan Black & Terra McKinnish & Seth Sanders, 2005. "The Economic Impact Of The Coal Boom And Bust," Economic Journal, Royal Economic Society, vol. 115(503), pages 449-476, 04.
  5. James, Alex & Aadland, David, 2011. "The curse of natural resources: An empirical investigation of U.S. counties," Resource and Energy Economics, Elsevier, vol. 33(2), pages 440-453, May.
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:oup:ajagec:v:95:y:2013:i:2:p:449-456. 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: (Oxford University Press)

or (Christopher F. Baum)

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.