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COLLEGE OF SOCIAL SCIENCE

COLLEGE OF SOCIAL SCIENCE

Table 11. Continued 1

Table 11. Continued 1 Variables Physical Characteristics Population Popchange Density Water Land Ratio Shoreline Moderating Effects White* Institutions Income*Institutions Homeownership *Institutions Control Variable EAR Constant Observation Wald test 1 with Robust Standard Errors Without Interaction .29 (.11)** -.00 (.00) -.00 (.00) .002 (.003) -.00 (.00) -.37 (.28) -4.30 (.56) 2347 127.21 (.00)*** Interaction with Mayor .30 (.11)** -.00 (.00) -.00 (.00) .002 (.003) -.00 (.00) .03 (.01)** .00 (.00) -.01 (.01) -.39 (.28) -3.86 (.66) 2347 169.12 (.00)*** Interaction with District Election .30 (.11)** -.00 (.00) -.00 (.00) .003 (.004) -.00 (.00) .00 (.00) -.00 (.00) .00 (.00) -.38 (.28) -4.07 (.59) 2347 129.68 (.00)*** Interaction with RPC 32 (.11)** -.00 (.00) -.00 (.00) .002 (.003) -.00 (.00) .00 (.01) .00 (.00)** .00 (.01) -.38 (.28) -3.80 (.71) 2347 148.08 (.00)*** However, the political turmoil (council member turnover) is statistically significant (at p=.05 level), showing its negative relationship to the pro-environmental land use policy change while holding other variables constant. This confirms the hypothesis that, when a council faces higher turnover rates, then the city does not tend to offer conservation amendments. Another important finding is that the linkage to the RPC board meeting. As the table 11 indicates, a city’s RPC connection is positively related to offering conservation amendments while holding other variables constant (significant at 77

p=.05 level). This can be interpreted that when a city has a linkage with the appropriate RPC, then the probability of offering conservation amendments will be much higher than the cities that do not have linkage with RPC (network flowing information). However, the other important informal institutional variable of ILA expenditure (network bonding communities) seems not to influence the pro-environmental land use policy change. This may comes because the data of ILA expenditure was limited to the cities in the counties that have population more than 100,000. This causes a lot of missing variables. 1,171 (32.3%) were missed out of 3636 observation years, reducing available observations. The administrative capacity variable is not also statistically significant even though the direction is positive to offering conservation amendments. This may occur because the expenditure data does not perfectly measure the actual city’s planning capacity. The comprehensive planning activity expenditure may not reflect actual planning capacity of a city 61 . Unlike many institutional variables show their hypothesized directions, most of community interest variables are not statistically significant. As table 11 reports, only homogeneity variable (percentage of white population) is positively related to cities’ offering of conservation amendments (significant at p=.05 level). This means that if a community is more homogeneous (white dominated), then the city has higher possibility to offer conservation amendments. However, even though most community interest variables are not statistically significant, the directions have positive relationships with pro-environmental land use policy change except median income variable. The physical attributes variables are mostly not significant in this model. However, population is positively related to conservation amendments while holding other variables constant, confirming scarce land increases the possibility of proenvironmental policy change. The unexpected result of these physical characteristic variables is that many variables such as density, population change, and shoreline may have negative relationship with conservation amendments even though they are not 61 For example, whenever city did works regarding comprehensive planning activities, the city spent a lot of money regardless of the size of the city. For example, cities of Bradenton Beach and Cedar Key have around 1000 population, but their expenditure on comprehensive planning activities are similar to the amount of the ones that more than 20,000 population cities. In this case, expenditure per capita does not work also. 78

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