City Adoption of Environmentally Sustainable Policies in California's Central Valley

Abstract Problem: Sustainability remains "the current object of planning's fascination," as Campbell described it in 1996, but it is unclear what causes local governments to adopt environmentally sustainable policies and whether they are effective once adopted. Purpose: The goal of this article is to explain why communities adopt environmentally sustainable policies. Methods: We develop an environmental policy sustainability index for 100 incorporated cities in California's Central Valley using a combination of survey and archival data. We then use regression and cluster analyses to test which independent variables expressing three theoretical perspectives (Tiebout's public goods development model, Peterson's fiscal capacity model, and Logan and Molotch's interest group/growth machine model) are best at explaining this index. Results and conclusions: The results suggest that sustainable policies are more likely to occur in cities with better fiscal health and whose residents are of higher socioeconomic status. These findings raise important questions about the relationship between developed and developing cities that were not raised in previous studies, which focused only on major metropolitan areas in the United States. Takeaway for practice: Our results suggest that small, less-developed cities will need substantial technical, financial, and planning assistance to move toward greater sustainability. Many medium-sized, more developed cities may also need technical assistance, but are otherwise capable of becoming more environmentally sustainable. Any new policies should not discourage the largest cities from continuing to pursue their current sustainability activities, but should pass the lessons they have learned along to smaller cities to help them change to more sustainable development trajectories. Research support: This research was supported by NSF Grant 0350817. Keywords: sustainabilitygrowth machinesgrowth managementenvironmental policygreen cities Notes *p < .05 **p < .01 1. There is a large body of work on intellectual capital in business organizations, where it is generally defined as the knowledge needed to effectively combine physical and human capital into higher-value economic activities (CitationBradley, 1997). However, there is still ongoing debate in this literature about the definition and measurement of intellectual capital, which is beyond the scope of this paper. 2. The fact that there are exactly 100 cities is pure coincidence. Note that the definition we use for the Central Valley includes some cities (e.g., South Lake Tahoe) that are actually in the Sierra Nevada Mountains rather than the Central Valley. This does no harm and allows us to include cities of varying sizes as we intended. 3. The main purpose of the survey was to check the data on policies we had obtained from archival data. In the survey, we reformulated the policy definitions as questions, such as: "Does your city have policies to encourage centrally located and/or high density commercial/industrial development?" We also asked each respondent to rate the extent to which these policies achieved their stated goals (on a scale ranging from 1 = not very well to 5 = very well). Unfortunately this rating was not very informative because the respondents answered the question only for those policies in place for their city, and nearly all policies had average ratings between 3 and 4. 4. We made these decisions on the basis of respondent comments and coder experience, and they represent our best professional judgments about which were most accurate. Given that only 7 out of 50 policies required this type of evaluation, we do not feel that this compromised the integrity of the overall index. 5. We calculated proportion population growth as the difference between 2004 city population estimates and 1990 city population from the Census of Population and Housing, divided by the 1990 city population. 6. We calculated percent intergovernmental revenue per capita as intergovernmental revenue per capita divided by total revenue per capita, multiplied by 100.