Abstract
While poverty rates on Native American Indian reservations are triple the US average. Small business incubation programs, available elsewhere in the US, scarcely exist on the Native American Indian Reservations (NAIRs). Our unique study tests the effects of the Lakota Fund (LF), a private sector small business development initiative on the Pine Ridge Reservation in South Dakota, on the economic development of the NAIRs. Our objective is to determine whether the SBA-like programs (loans, training, and consulting) can improve economic conditions. The 1980–2006 annual county-level (Shannon Co. is ‘treatment,’and Todd Co. is ‘control’) data are a natural experiment. Results indicate that the LF inception and duration significantly raised real per capita income (RPCI)—suggesting not only the success of the LF, but support for the broader notion that privately funded small business initiatives can be used to support economic development of isolated impoverished groups within the US economy.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
The exponential intensity measure was divided by 10,000 to normalize the data and provide more accurate coefficients. Because the geometric intensity measure is, in essence, an interaction between logged loan values and the exponential intensity measure, it, too, was divided by 10,000 prior to the logarithmic transformation.
It assumes the geometric series form \( \sum_{n = i}^{k} {a_{n} \delta^{n} } \) where a n represents the average loan in year n and within which δ n interacts with the impact of the programs intensity on the loan size progressively with time. We choose e for the δ n base and allow the exponent to assume increasing integer values with year n. Assuming a geometric form can yield certain advantages, one may derive under certain assumptions, for example, a mathematical relationship between the income over time (or perhaps income autocorrelation), loan values, and the program’s intensity measure. Assume that changes in average loan values can be absorbed by growth in the economy (e.g., more money finds a home on the reservation) and that the income response to a change in loan value is governed by a certain coefficient α, that the period of response is undefined, and that some degree of time-related correlation for income exists. For the above series, then, the sum as time period n approaches infinity is given simply by \( \frac{{a_{n} }}{1 - \delta } \), where \( a_{n} \) represents an average loan injection, and the impact of that summed effect on income over an undefined time period is \( \alpha \left( {\frac{{a_{n} }}{1 - \delta }} \right) \). In this form, δ becomes the ratio or rate at which the loan value a n converges to its full effect. If one wishes to elicit the impact this ratio (or of the loan value given a certain base ratio) to income over time, one could equate income to the convergent sum and income of the previous period, ceteris paribus. This, then, takes the form \( y_{t + 1} = \alpha \left( {\frac{{a_{n} }}{1 - \delta }} \right) + y_{t} \). Moving y t to the left side of the equation grants a regressive autocorrelation equation into which one could place a desired income level and thus derive criteria applicable for examining loan values and response rates. Solving separately for the loan value and for the convergence ratio provides equations for determining loan benchmarks necessary to achieve a targeted income over time and the required impulse response of the local economy to a given loan amount to achieve a desired income level, respectively:
$$ a_{n} = \frac{\alpha }{{\left( {y_{t + 1} - y_{t} } \right)\left( {1 - \delta } \right)}} $$and
$$ \delta = 1 - \frac{{\alpha a_{n} }}{{y_{t + 1} - y_{t} }}. $$Please refer to the Data Appendix for complete description of the variables and respective sources. Also refer to footnote 3 for the specifics regarding computation of the variable PGMINT_GEO.
References
Armendariz, B., & Morduch, J. (2007). The economics of microfinance. Cambridge, MA: MIT.
Bureau of Economic Analysis, Regional Economic Accounts. (2004a). CA04—personal income and employment summary. Washington. Retrieved December, 2006, from http://www.bea.gov/regional/reis/.
Bureau of Economic Analysis, Regional Economic Accounts. (2004b). Ca1-3 per capita personal income interactive table. Washington, DC. Retrieved December, 2006, from http://www.bea.gov/regional/reis/.
Bureau of Economic Analysis, Regional Economic Accounts. (2004c). Ca25n naics. Washington, DC. Retrieved December, 2006, from http://www.bea.gov/regional/reis/.
Bureau of Economic Analysis, Regional Economic Accounts. (2004d). Ca25 sic. Washington, DC. Retrieved December, 2006, from http://www.bea.gov/regional/reis/.
Carlson, P. (1997, Febraury 23). In the year of ‘dances with wolves,’ everybody wanted to be on the Senate Indian Affairs Committee, nearly a decade later, it can hardly get a quorum. The Washington Post, W06.
Center for Policy Alternatives. (2004). 2004 policy toolkit: micro enterprise development. Washington, D.C.
Coleman, B. E. (1999). The impact of group lending in Northeast Thailand. Journal of Development Economics, 60(#1), 105–141.
First Gov. (2000). President Clinton and vice president Gore encouraging the growth of small business. Washington, DC. Retrieved June 3, 2007, from http://clinton4.nara.gov/textonly/WH/Accomplishments/Small_Business.html.
Gertler, P., Levine, D., & Moretti, E. (2008). Do microfinance programs help families insure consumption against illness? Health Economics. doi:10.1002/hec.1372).
Grameen Communications. (2002). A short history of Grameen Bank. Retrieved June 11, 2008, from http://www.grameen-info.org/bank/hist.html.
Lakota Fund. (2007). History. Pine ridge reservation, south Dakota. Retrieved June 4, 2007, from http://www.lakotafunds.org/history.htm.
Khandker, S. R. (2005). Microfinance and poverty: Evidence using panel data from Bangladesh. World Bank Economic Review, 19, 1–25.
Montgomey, H. (2005). Meeting the double-bottom line: The impact of Khushhali bank’s microfinance program in Pakistan. ADBI policy papers no. 8. http://afdi.afd.org/files/2005.09.28.cpp.Khushhali.microfinance.study.pdf .
Morduch, J. (1999). The microfinance promise. Journal of Economic Literature, 37, 1569–1614.
Pitt, M., & Khandker, S. R. (1998). The impact of group-based credit programs on poor households in Bangladesh: Does the gender of the participant matter? Journal of Political Economy, 106, 958–996.
Small Business Administration. (2004). Golden anniversary hall of fame. Washington, D.C. Retrieved February, 12, 2004, from http://www.sba.gov/50/hall.html.
Small Business Administration. (2007). Overview and history. Washington, D.C. Retrieved June 4, 2007, from http://www.sba.gov/aboutsba/history/index.html.
South Dakota Department of Education. (2001–2004). Education in south Dakota: District and statewide profiles. Pierre, SD. Retrieved December 2006, from http://doe.sd.gov/ofm/statdigest/.
South Dakota Department of Education. (2004). Statistical digest: A statistical profile of education in south Dakota. Pierre, SD. Retrieved December 2006, from http://doe.sd.gov/ofm/statdigest/05digest/Docs/05StatewideLongitudinalData.pdf.
South Dakota Department of Education and Cultural Affairs, Division of Elementary and Secondary Education. (1980–2000). South Dakota educational statistical digests. Pierre, SD: SRI reference database, Lexus nexus microfiche.
Thurik, R. (2003). Entrepreneurship and unemployment in the UK. Scottish Journal of Political Economy, 50, 264–290.
U.S. Census Bureau. (2006). Poverty 2005. Washington, D.C. Retrieved June 4, 2007, from http://www.census.gov/hhes/www/poverty/poverty05/table5.html.
Vinje, D. L. (1977). Income and labor participation on Indian reservations. Growth and Change, 8, 38–42.
Vinje, D. L. (1996). Native American economic development on selected reservations: A comparative analysis. American Journal of Economics & Sociology, 55, 427–442.
Acknowledgements
An earlier draft of this paper under the title: “Small Business Economics of the Lakota Fund on the Native American Indian Reservation” was presented at the Western Economic Association International (WEAI) annual conference, CEP Session on “Topics in Political Economy” in Waikiki, HI (July 2008), and also circulated as a IZA Discussion Paper no. 3999. We thank the WEAI session participants for their constructive suggestions, Brenda Ellis for her outstanding editorial comments, Matthew Mone for his assistance in formatting and incorporating the map of South Dakota, and anonymous referees of this journal for their constructive comments. The usual caveats apply.
Author information
Authors and Affiliations
Corresponding author
Data appendix
Data appendix
Real Per Capita Income (RPCI) is per capita personal income that has been adjusted for inflation based on the 82–84 base year Regional CPI for the South Dakota area.
-
Source: Bureau of Economic Analysis. (2004b). Regional Economic Accounts Ca1-3 Per capita personal income http://www.bea.gov/regional/reis/
Public Sector Size (PUBSECTSZ) This variable captures the size of government sector involvement in economic activity and income. It is derived by subtracting Earnings by Place of Residence (a measure of income that excludes government social insurance programs) from Earnings by Place of Work (a proxy for total earnings, including government programs) and expressing the result as a percentage of entire earnings (Earnings by place of work).
-
Source: Bureau of Economic Analysis. (2004a). Regional Economic Accounts Ca04—Personal income and employment summary http://www.bea.gov/regional/reis/
Attendance Rate (ARTE) These data provide an attendance measure of all school age children and young adults. It is calculated using ADA (Average Daily Attendance) and ADM (Average Daily Membership) data for the specific county’s school district. The above data are the ratio of ADA over ADM, expressed as a percentage to provide a picture of school attendance (and absence) in the county.
-
Sources: 1980–2000 Data–South Dakota Educational Statistical Digests, Department of Education and Cultural Affairs, Division of Elementary and Secondary Education. Various years. SRI Reference Database, Lexus Nexus Microfiche.
-
2001–2004 Data—“Education in South Dakota: District and Statewide Profiles” South Dakota Department of Education (2004). http://doe.sd.gov/ofm/statdigest/
Industry Mix (INDMIX)—The county economy’s production mix regarding its agrarian and industrial nature. It is the ratio of farm employment over non-farm employment when expressed as a percentage.
-
Source: Bureau of Economic Analysis. (2004c, 2004d). Regional Economic Accounts
-
1980–2000: CA25 SIC
-
2001–2004: CA25 N NAICS
Real Average LoanRate (RAVLOAN) Real per capita loan values adjusted for inflation based upon the 82–84 regional CPI base year for the South Dakota area. The base (unadjusted) data are the average yearly loan amount, in dollars, provided by the Lakota Fund.
-
Source: Annual data provided by Dowell Caselli-Smith, Executive Director of the Lakota Fund. Phone: 1 (605) 455-2500
Program Dummy (PGMDUM) Dummy variable for the Lakota Fund program existence (1 for years 1987–2006 for Shannon county, 0 otherwise)
Program Intensity (PGMINT) Program intensity variable (1 at program inception for year 1987; 2 for 1978; …; and 20 for 2006)
Program Intensity Squared (PGMINTSQ)Square of PGMINT
Program Intensity Exponential (PGMINT_EXP) Exponential form of the PGMINT variable
Program Intensity Geometric (PGMINT_GEO)Geometric form of the PGMINT variable. Refer to footnote 3 for the detailed computation of this variable.
Rights and permissions
About this article
Cite this article
Benson, D.A., Lies, A.K., Okunade, A.A. et al. Economic impact of a private sector micro-financing scheme in South Dakota. Small Bus Econ 36, 157–168 (2011). https://doi.org/10.1007/s11187-009-9191-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11187-009-9191-9
Keywords
- Economic development
- Lakota fund
- Micro-financing
- Native American Indian reservations
- Small business incubation