Skip to main content
Log in

Estimation of Minimum Market Threshold for Retail Commercial Sectors

  • Published:
International Advances in Economic Research Aims and scope Submit manuscript

Abstract

Understanding the ability of a local market to support a particular type of establishment is a prerequisite to designing effective development strategies. While several factors contribute to the vitality of the local retail market, the most fundamental factor is the relative size of the market in terms of potential customers. A commonly applied technique to assess the ability of a community to support various business activities is the estimation of demand threshold using simple count data models. However, due to the presence of excessive zeros in the dependent variable, this study uses Hurdle Poisson and Zero Inflated Poisson (ZIP) count data models and estimates demand threshold for twelve retail commercial sectors for 2,201 counties in the U.S. The results show that the demographic characteristics of the county population and its remoteness are significant factors determining the number of establishments in a county. The results from this study may be used by local economic development practitioners and entrepreneurs to retain, promote, and attract retail commercial businesses in the local communities.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Notes

  1. The simple Poisson and Negative Binomial variations of these models are also tried. While Poisson models results are inferior to ZIP model but the NB models failed to converge for several retail sectors. Hence, it is decided not to report the results.

  2. As suggested by a reviewer an interaction term (income *metro) was included in both models and for most of the regressions the coefficient had a strong and negative impact on the dependent variable. However, its inclusion made the ‘metro’ variable weak and positive which is contrary to conventional hypothesis. Hence, the results are not reported.

References

  • Berry, B. J., & Garrison, W. (1958a). A note on central place theory and the range of a good. Economic Geography, 34, 304–311.

    Article  Google Scholar 

  • Berry, B. J., & Garrison, W. (1958b). Recent developments in central place theory. Proceedings of The Regional Science Association, 4, 107–121.

    Article  Google Scholar 

  • Berry, B. J., & Parr, J. B. (1988). Market centers and retail location: Theory and applications. Englewood Cliffs: Prentice Hall.

    Google Scholar 

  • Daniels, T. L. (1989). Small town economic development: growth or survival? Journal of PlanningLiterature, 4, 413–429.

    Google Scholar 

  • Darling, D. L., & Tubene, S. L. (1996). Determining the population threshold of minor trade center: a benchmark study of non-metropolitan cities in Kansas. Review of Agricultural Economics, 18, 95–101.

    Google Scholar 

  • Davis, A., & Harris, T. R. (2004). An application of double hurdle firm location model: An example with state of Montana. Working Paper, Department of Resource Economics, University of Nevada, Reno, NV.

  • Deller, S. C., & Harris, T. R. (1993). Estimation of minimum market thresholds using stochastic frontier estimators. Regional Science Perspectives, 23(1), 3–17.

    Google Scholar 

  • Foust, B. & Pickett, E. (1974). Threshold estimates: A tool for small business planning in Wisconsin, Unpublished manuscript, Department of Geography, University of Wisconsin, Eau Claire.

  • Harris, T. R., & Shonkwiler, J. S. (1997). Interdependence of retail businesses. Growth and Change, 24, 523–533.

    Google Scholar 

  • Harris, T. R., Chakraborty, K., Xiao, L., & Narayanan, R. (1996). Application of count data procedure to estimate thresholds for rural commercial sectors. The Review of Regional Studies, 26, 75–88.

    Google Scholar 

  • Harris, T. R., Yen, S., & Deller, S. C. (2000). Estimation of minimum demand threshold: An application of count data procedure with the existence of excess zero observation. Paper Presented at the AAEA annual meeting, Tampa, FL, July 30-Aug.

  • Harris. T. R., Shonkwiler, J. S., & Lin, Y. (2001). Application of discrete normal distribution for dynamic rural sector analysis: Preliminary results. Selected Paper presented at the AAEA annual meeting in Chicago, IL, Aug 5–8.

  • Kemp, A. (1997). Characterization of a discrete normal distribution. Journal of Statistical Planning and Inference, 63, 223–229.

    Article  Google Scholar 

  • King, L. J. (1984). Central place theory. London: SAGE Publications.

    Google Scholar 

  • Leatherman, J. C., Howard, D. J., & Kantens, T. L. (2002). Improved prospects for rural development: an industrial targeting for the great plains. Review of Agricultural Economics, 24(1), 59–77.

    Article  Google Scholar 

  • Liu, W., & Cela, J. (2008). Count data models in SAS. Paper 371, SAS Global Forum.

  • Mulligan, G. F. (1987). Consumer travel behavior: extensions of a multipurpose shopping model. Geographical Analysis, 19, 364–375.

    Article  Google Scholar 

  • Mushinski, D., & Weiler, S. (2002). A note on the geographic interdependencies of retail market area. Journal of Regional Science, 42(1), 75–86.

    Article  Google Scholar 

  • Parr, J., & Denike, K. (1970). Theoretical problems in central place analysis. Economic Geography, 47, 568–586.

    Article  Google Scholar 

  • Salyards, D. M., & Leitner, K. R. (1981). Market threshold estimates: a tool for business consulting in Minnesota. American Journal of Small Business, 6(2), 26–32.

    Google Scholar 

  • Schuker, A. V. & Leistritz, F. L. (1991). Threshold population levels for rural retail businesses in North Dakota. Unpublished paper, Department for Agricultural Economics, North Dakota State University, Fargo.

  • Shaffer, R. (1989). Community economics: Economic structure and change in smaller communities. Ames: Iowa State University Press.

    Google Scholar 

  • Shaffer, R., Deller, S., & Marcouiller, D. (2004). Community economic development: Linking theory and practice. Cambridge: Blackwell.

    Google Scholar 

  • Shonkwiler, J. S., & Harris, T. R. (1996). Rural retail business thresholds and interdependencies. Journal of Regional Science, 36(4), 617–630.

    Article  Google Scholar 

  • Stone, K. E. & McConnon, Jr. J. C. (1980). Retail sales migration in the Midwestern United States. Paper presented at the AAEA meetings, University of Illinois, Urbana.

  • Stone, K. E. & McConnon, Jr. J. C. (1984). Trade area analysis extension program: A catalyst for community development. In Proceedings of realizing your potential as an agricultural economist in extension, Ithaca, NY.

  • Thilmany, D., McKenny, N., Mushinski, D., & Weiler, S. (2005). Beggar-thy-neighbor economic development: a note on the effect of geographic interdependencies in rural retail markets. The Annuls of Regional Science, 35, 593–605.

    Article  Google Scholar 

  • American Fact Finder (2002). U.S. Bureau of Census at: http://factfinder2.census.gov/main.html.

  • Census of Population (2000). U.S. Bureau of Census at: http://www.census.gov/.

  • Economic Census (2002). Census of Retail Trade at: http://www.census.gov/econ/census02/data/us/US000_44.HTM.

  • USDA-URCC-2003. U.S. Department of Agriculture at: http://www.ers.usda.gov/data/RuralUrbanContinuumCodes/.

  • Wensley, M. R. D., & Stabler, J. C. (1998). Demand—threshold estimation for business activities in rural saskatchewan. Journal of Regional Science, 18(1), 155–177.

    Article  Google Scholar 

  • Yesilova, A., Kaydan, M. B., & Kaya, Y. (2010). Modeling insect-egg data with excess zeros using zero-inflated regression models. Hacettepe Journal of Mathematics and Statistics, 39(2), 273–283.

    Google Scholar 

  • Zorn, C. J. W. (1998). An analytical and empirical examination of zero-inflated and hurdle Poisson specifications. Sociological Methods and Research, 26(3), 368–400.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kalyan Chakraborty.

Additional information

Earlier version of this paper was presented at the 71st International Atlantic Economic Conference, Athens Greece. March 16–19, 2011

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chakraborty, K. Estimation of Minimum Market Threshold for Retail Commercial Sectors. Int Adv Econ Res 18, 271–286 (2012). https://doi.org/10.1007/s11294-012-9354-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11294-012-9354-3

Keywords

JEL

Navigation