A national inventory and analysis of US transfer of development rights programs

Abstract

Transfer of development rights (TDR) programs shift development intensity between land parcels. Jurisdictions, most commonly local municipal or county governments, employ TDR to protect resources such as farmland or historical properties and to encourage infill and redevelopment where deemed appropriate. However, while championed by economists and others seeking to reduce conflicts between land development and preservation, TDR program adoption has varied widely across the US. What demographic, economic, or environmental factors are associated with TDR program establishment? This paper describes a census of 375 TDR programs in the United States, documenting primary program attributes and adoption year and categorizing their functions and typology. Using logistic regression, we analyze program spatial patterns and factors predicting program implementation. We find that areas that are coastal, more liberal, have higher home values, in home-rule states, and in states with state-wide growth management programs, are all significantly more likely to implement TDR programs.

Keywords:

• transfer of development rights
• density transfer
• market-based incentives
• land use policy
• urban density
• flexible zoning

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplemental data

All data and code for the article can be accessed online through the UNC Dataverse, https://doi.org/10.15139/S3/8C1KYA

Notes

1 Interestingly, our model found only a very weak relationship between TDR adoption and higher-value agricultural production, another potential indicator of community values around natural resources.

Additional information

Funding

This paper is based upon work graciously supported by the USDA Office of Environmental Markets (OEM; Agricultural Market and Economic Research Grant No. 58-0111-18-012), through the US National Science Foundation under Coastal SEES Grant No. 1427188 and Geography and Spatial Sciences Grant No. 1660450.