All fifty states in the United States offer preferential forest property tax programs (PFPTPs) that defer, reduce, or eliminate property taxes on enrolled private forest lands, to foster ecosystem services. Among individual programs, there is wide variability in enrollment levels, as well as program structure and administration. Past research has explored patterns of enrollment in individual states, but to our knowledge has never been conducted at the national level. We used binary logistic regression with multiple imputation for missing data to explore the landowner, land, and program characteristics that correlate with likelihood of enrollment in a PFPTP. We found that most landowner objectives and concerns, including those that would appear to be linked to program enrollment, such as concern about the level of taxes, were generally not correlated with likelihood of enrollment. Owning more forest area was correlated with higher likelihood of enrollment. The link of enrollment to population density suggested that enrollment is higher in moderate densities, with higher and lower densities having lower enrollment, possibly due to conflicting incentives for enrollment as land values increase. Program characteristics were negatively correlated with likelihood of enrollment, especially those that restrict uses or management. The owner's desire for wooded land to stay wooded and higher levels of penalty for program withdrawal were positively correlated with likelihood of enrollment and average rates of tax reductions were not significantly correlated, suggesting that landowners may see programs as a method of conserving and protecting their forestland in the future more than as simply a way to save money.
- Binomial logistic regression
- Ecosystem services
- Family forest landowner
- National Woodland Owner Survey (NWOS)
- Property tax