Politics, institutions and entrepreneurship: city decisions leading to inventoried GHG emissions

Figures & data

Table 1.  Anticipated relationships with governmental versus community carbon inventory.

	Policy adoption for GHG inventory in government	Policy adoption for GHG inventory in the community
City manager	Positive	Negative
Civic entrepreneur	None	Positive
Elected entrepreneur	Positive	Positive
Bureaucratic entrepreneur	Positive	None

Table 2.  City government adoptions of GHG inventory policy.

	Frequency (%)
No GHG inventory policy	275 (50.93)
GHG inventory for governmental operations	141 (26.11)
GHG inventory for community businesses and residences	41 (7.59)
GHG inventory for both government and community	83 (15.37)
Total	540 (100)

Data from: The 2010 survey conducted by Richard C Feiock [104].

Table 3.  Descriptive statistics for variables used to explain GHG inventory policies.

	Mean (parameter estimate)	Standard deviation (parameter estimate)	Minimum value	Maximum value
Council–manager government	0.62	0.48	0	1
Civic entrepreneur	0.46	0.51	0	1
Elected entrepreneur	0.50	0.50	0	1
Bureaucratic entrepreneur	0.64	0.48	0	1
Population	104,325.2	391,788.1	3856	8,008,278
Proportion age 16 and under	0.22	0.04	0.05	0.33
Proportion non-hispanic white	0.70	0.21	0.04	0.98
Per capita personal income	22,479.55	8,367.82	9,462	77,092
Problem severity	2.50	0.82	1	4
Homeowner association support	3.63	0.81	1	5
Business association support	4.10	0.79	0	5

Data from: The International City Management Association, 2009 Municipal Yearbook, The US Census of 2000 Census of Population and Housing.

Table 4.  Probit regression results: GHG inventory in government and community.

	Any GHG inventory (parameter estimate)	Government GHG inventory (parameter estimate)	Community GHG inventory (parameter estimate)
Council–manager	-.11 (.18)	.06 (.17)	-.32 (.18)^‡
Civic entrepreneur	.20 (.19)	.28 (.18)	.38 (.20)^‡
Elected entrepreneur	.51 (.19)^‡	.22 (.19)	.58 (.23)^§
Bureaucratic entrepreneur	.70 (.19)^§	.99 (.20)^§	-.04 (.23)
Problem severity^†	.19 (.12)	.20 (.12)^‡	.11 (.12)
Population (log)	.44 (.12)^§	.31 (.10)^§	.30 (.11)^§
Age	-4.14 (2.12)^‡	-2.52 (2.01)	-6.11 (2.19)^‡
Non-hispanic white	-.42 (.46)	-.58 (.45)	.00 (.52)
Per capital personal income	.00 (.00)^‡	.00 (.00)^‡	.11 (.00)
Homeownership association	.17 (.11)	.06 (.10)	.15 (.11)
Business association	.12 (.11)	.14 (.11)	-.01 (.12)
Observations	450	450	450
Log likelihood	-166.90	-173.97	-151.74

Note: standard errors in parentheses.

^†Survey measure of perceptions of energy/climate change problem severity.

^‡p< .05

^§P < .01

Francis NJ, Feiock RC. A Guide for Local Government Executives on Energy Efficiency and Sustainability. www.businessofgovernment.org/report/guide-local-government-executives-energy-efficiency-and-sustainability

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