An Econometric Model to Predict Participation in Urban and Community Forestry Programs in South Carolina, U.S.    (View PDF)

J. Jess Fleming, Thomas J. Straka, and Stephen E. Miller

Abstract: A regression-based econometric model was generated from a statewide survey of South Carolina, U.S., residents concerning participation in urban and community forestry programs. The econometric model attempts to estimate the probability of an individual’s participation. Results are intended to increase effectiveness of program planning and organization within state forestry commissions. Model 1 was created as follows: participation = F (gender, age, education, marital status, region, area raised, area reside, household, duties, and income). Because these responses represented qualitative values, a number of dummy variables (0 or 1, for example, for yes or no) were generated to more accurately reflect the values for participation and a logit model was used. Logit regression analysis produces a value between 0 and 1 that can be interpreted as a probability. Model 2, with fewer variables, was later created to reduce possible multicollinearity problems. Model 1 had a pseudo-R 2value of 0.2955 or a 29.55% probability of having a correct prediction for participation. Model 2 had a pseudo-R 2value of 0.2407. The models produced reasonable predictions of participation.

Keywords: Econometrics; public involvement; urban and community forestry

https://doi.org/10.48044/jauf.2006.029