Abstract
As urban growth and competition for natural resources heighten, the attention to preserving such resources, including land, is also growing. As one example, the appearance and passage of conservation referenda represents a high-profile, grassroots political effort across the USA. In this study, factors influencing the appearance and passage of ballot initiatives in Colorado are compared to previous literature, identifying potential regional variation in such drivers. Results suggest that, while some place-based characteristics like total population and educational attainment have a consistent effect, the role of income and households with children does not. It appears support for conservation is much more broadly distributed across the population in the West and that residents view conservation as an ongoing activity, not a singular event. Likewise, there is some evidence that Western voters view agriculture and conservation as mutually exclusive. Although fundamental results do not change, accounting for spatial effects alters the magnitude and significance of factors affecting both appearance and passage of conservation referenda.
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Notes
More referenda have been held in New Jersey than any other US state. In part this is due to New Jersey’s Green Acres Planning Incentive Initiative, a statewide program incentivizing open space preservation (see page 4).
The Front Range is also known as the Front Range Urban Corridor. In 2000, it included all counties labeled in blue in Fig. 1 except Broomfield, which did not become a county until 2002. At the time of the 2000 Census, the 16 counties constituting the Front Range, as it is known, were home to approximately 3.6 of the 4.3 million Colorado residents (~ 83.85%). The United States Office of Budget and Management divides Colorado’s Front Range into seven Core-Based Statistical Areas (CBSA’s) which include the following major cities: Fort Collins, Greeley, Boulder, Denver, Colorado Springs, Cañon City, and Pueblo.
As indicated by the following county-ski resort pairings: Routt-Steamboat Springs, Eagle-Vail, Summit-Breckenridge, Pitkin-Aspen, Gunnison-Crested Butte, San Miguel-Telluride.
Nearly all counties holding referenda outside the central Rockies and lower Arkansas watershed are along the Front Range.
Ideally, we would also control for the money allocated through referendum. Whereas the TPL database contains full information on the characteristics discussed below, it does not contain all cost estimates. Although a concern, previous research (Nelson et al. 2007) found that outcomes were not affected by the cost of the referendum.
It is also worth noting that the stated purpose of many referenda addressing water conservation was ’watershed preservation.’ This sort of vague wording may make outcomes less obvious to voters, especially when compared with more straightforward projects such as ‘trail restoration’ which have clear and tangible impacts.
Most Colorado agriculture relies on water fed through systems of diversion canals and the state’s farmers own in excess of $6 billion dollars in water rights (Graff et al. 2013).
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Appendix: Robustness checks
Appendix: Robustness checks
The model was run under a battery of different specifications in order to determine the stability of its results. Eight different primary specifications were chosen, and the preferred models are presented above. Both spatial and a non-spatial versions of the Heckman two-step process were estimated. Neither indicated selection bias. These were followed by the exact same estimation, but without the use of the IMR (i.e., estimated independently). Following this, the spatial variable was introduced only into the appearance model and both models were again estimated independently. In the last three specifications, a binary variable was introduced that controlled for all jurisdictions which passed three or more referenda during the time period analyzed. This was estimated once using the Heckman two-step process with the spatial variable included, once estimating both appearance and passage independently with the spatial variable included, and once estimating both independently without the spatial variable included.
Under each specification, the model was estimated once as it is presented above. It was also estimated with the existing prior support variable dropped from the appearance model. It was then estimated a final time with the repeat passage and prior passage variables dropped from the passage model. These variations were estimated to see whether latent, higher, or lower support levels in a given jurisdiction affected the likelihood of appearance or passage. The results presented above are stable under nearly every specification in significance level, magnitude, and sign.
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Chriestenson, C., Thilmany, D. Do factors contributing to appearance and success of conservation referenda in the West differ from those found in other regions of the United States?. Ann Reg Sci 65, 83–104 (2020). https://doi.org/10.1007/s00168-020-00975-7
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DOI: https://doi.org/10.1007/s00168-020-00975-7