RT Journal Article
SR Electronic
T1 An Econometric Model to Predict Participation in Urban and Community Forestry Programs in South Carolina, U.S.
JF Arboriculture & Urban Forestry (AUF)
FD International Society of Arboriculture
SP 229
OP 235
DO 10.48044/jauf.2006.029
VO 32
IS 5
A1 Jess Fleming, J.
A1 Straka, Thomas J.
A1 Miller, Stephen E.
YR 2006
UL http://auf.isa-arbor.com/content/32/5/229.abstract
AB 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-R2 value of 0.2955 or a 29.55% probability of having a correct prediction for participation. Model 2 had a pseudo-R2 value of 0.2407. The models produced reasonable predictions of participation.