Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-26T06:01:14.007Z Has data issue: false hasContentIssue false
  • English
  • Français

A Logit Analysis of Participation in Tennessee's Forest Stewardship Program

Published online by Cambridge University Press:  28 April 2015

Caroline D. Bell ,
Roland K. Roberts ,
Burton C. English  and
William M. Park
Caroline D. Bell
Affiliation:
Department of Agricultural Economics and Rural Sociology, The University of Tennessee, Knoxville, Tennessee
Roland K. Roberts
Affiliation:
Department of Agricultural Economics and Rural Sociology, The University of Tennessee, Knoxville, Tennessee
Burton C. English
Affiliation:
Department of Agricultural Economics and Rural Sociology, The University of Tennessee, Knoxville, Tennessee
William M. Park
Affiliation:
Department of Agricultural Economics and Rural Sociology, The University of Tennessee, Knoxville, Tennessee
Get access Rights & Permissions [Opens in a new window]

Abstract

This study determines the likely effect of cost-share incentives on participation in the Tennessee forest Stewardship Program and identifies other factors that may contribute to participation. A random utility model is used to determine the probability that a landowner will choose to participate in the program. A binary choice model is specified to represent the dichotomous decision and a logit procedure is used to fit the model. Data are obtained from mail surveys of 4,000 randomly selected landowners. Results indicate that attitudes and knowledge of forestry programs may be more influential in a landowner's decision to participate than monetary incentives.

Keywords

cost-share incentiveStewardship Incentive Programlogitnonindustrial private forestNIPFparticipationforestrytrees
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 26 , Issue 2 , December 1994 , pp. 463 - 472
Copyright
Copyright © Southern Agricultural Economics Association 1994

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ben-Akiva, Moshe and Lerman, Steven R.. Discrete Choice Analysis. Cambridge:The MIT Press, 1985.Google Scholar
Bishop, Richard C. and Heberlein, Thomas A.. “Measuring Values of Extra-Market Goods: Are Indirect Measures Biased?” Amer. J. Agr. Econ. 61(1979):926–930.CrossRefGoogle Scholar
Carson, Richard T. “Constructed Markets.” In Measuring the Demand for Environmental Quality (eds. John Braden, B. and Kolstad, Charles K.). North-Holland, Amsterdam, 1991.Google Scholar
Dicks, Michael R. and Grano, Anthony. “Conservation Policy Insights for the Future.” J Soil & Water Cons. 43(1988): 148–151.Google Scholar
Esseks, Dixon J. and Steven Kraft, E.. “Why Eligible Landowners Did Not Participate in the First Four Sign-ups of the Conservation Reserve Program.” J Soil & Water Cons. 43(1988):251–255.Google Scholar
Esseks, Dixon J. and Kraft, Steven E.. “Marketing the Conservation Reserve Program.” J. Soil & Water Cons. 44(1989):425–430.Google Scholar
Hensher, David A. and Johnson, Lester W.. Applied Discrete-Choice Modelling. John Wiley & Sons, New York, 1981.Google Scholar
Hoehn, John P. and Randall, Alan. “A Satisfactory Benefit Cost Indicator from Contingent Valuation.” J. Env. Econ. Mgmt. 14(1987):226–247.CrossRefGoogle Scholar
Jarvis, Anne Marie. “Computer Adoption Decisions – Implications for Research and Extension: The Case of Texas Rice Producers.” Amer. J. Agr. Econ. 72( 1990):1388–1394.CrossRefGoogle Scholar
Judge, George G., Griffiths, W.E., Carter Hill, R., Lütkepohl, Helmut and Lee, Tsoung-Chao. The Theory and Practice of Econometrics. Second Edition. New York:John Wiley & Sons, 1985.Google Scholar
McConnell, K.E. “Models for Referendum Data: The Structure of Discrete Choice Models for Contingent Valuation.” J. Env. Econ. Mgmt. 18(1990): 19–34.CrossRefGoogle Scholar
McFadden, D. “Conditional Logit Analysis of Qualitative Choice Behavior”, In Frontiers in Econometrics, (ed. Zarembka, P.). Academic Press, New York, 1974.Google Scholar
Neter, John, Wasserman, William, and Kutner, Michael H.. Applied Linear Regression Models. Homewood, Illinois:Richard D. Irwin, Inc., 1983.Google Scholar
Pindyck, Robert S. and Rubinfeld, Daniel L.. Econometric Models and Economic Forecasts. New York:McGraw-Hill, Inc., 1976.Google Scholar
Rosson, James F. Jr. and Dolittle, Larry. Profiles of Midsouth Nonindustrial Private Forests and Owners. U. S. Department of Agriculture, Forest Service, Southern Forest Experiment Station, Resource Bulletin SO-125, 1987.CrossRefGoogle Scholar
Sanders, William. Personal interview. Statistician, Department of Agriculture, University of Tennessee, Knoxville, 1990.Google Scholar
Skok, Richard A. and Gregersen, Hans M.. “Motivating Private Forestry, An Overview.” J. For. 73(1975):202–205.Google Scholar
U. S. Congress. Food. Agriculture. Conservation, and Trade Act of 1990. 101st Congress, 2nd session, Washington, D. C, 1990.Google Scholar
U. S. Department of Agriculture, Soil Conservation Service. Summary Report 1987 National Resources Inventory. Iowa State University Statistical Laboratory, Statistical Bulletin 790, 1987.Google Scholar
U. S. Department of Agriculture, Forest Service, Tennessee State Office. Tennessee State Stewardship Plan. Fiscal Year 1990-1994. Nashville, Tennessee, 1990.Google Scholar
U. S. Department of Commerce, Bureau of the Census. 1987 Census of Agriculture. Volume 1. Geographic Area Series. Part 51. United States. Summaiy and State Data. U.S. Government Printing Office, Washington, D.C.Google Scholar
Wells, G. R. Personal interview. Department of Forestry, Wildlife & Fisheries, University of Tennessee, Knoxville, 1990.Google Scholar