X hits on this document

237 views

0 shares

0 downloads

0 comments

45 / 94

Tax incentives/tax abatements

167

51.9

Loans or grants

135

41.9

Interest rate subsidies on loans

238

73.9

Land write-downs for industrial/commercial development

232

72.0

Industrial development bonds

225

69.9

Regulatory relief

249

77.3

Technical assistance

139

43.2

NOTE: The number of responding cities was 322.

Basolo, Huang / CITIES AND ECONOMIC DEVELOPMENT

TABLE 1

Types of Economic Development Inducements Used by Cities, Fiscal Years 1992-1995

Inducement

n

%

sample. Interest rate subsidies, industrial development bonds, and tax incentives/abatements also were popular economic development tools. Cities used 4.3 of these inducements (see Table 2), on average, and only one city in the sample reported using none of them.

The survey data revealed that 295 (91.4%) of the cities expended at least some funds on eco- nomic development. The mean of these expenditures is $1,858,038, as shown in Table 2.2 The dis- tribution of the expenditures, however, was substantially and positively skewed. Expenditures seem to be a good approach to measuring the extent of resources devoted to economic develop- ment. Prior to specifying our models, however, we ran a correlation between the count of induce- ments and expenditures to assess the validity of using a tools approach as a measurement of economic development support. The analysis produced a zero-order correlation coefficient of –.38 (p = .000). In other words, there is a moderate and negative relationship between the number of inducements and the expenditures in our sample of cities. This result suggests that the count of tools is indeed a questionable measure of economic development support as suggested by Wolman (1996). We used total economic development expenditures as the dependent variable in our models (see Table 3). In doing so, we recognize our support measure fails to capture off-budget tax abate- ments and other forms of economic development support, such as technical assistance and regula- tory relief. However, we believe that expenditures do reflect a major dimension of support for economic development by cities.

Public choice theory predicts that intercity competition will be a major factor in the support of local economic development. In some studies, competition is measured as the average number of economic tools used by localities within a specified area, such as the region or state (Fleischmann et al., 1992; Green & Fleischmann, 1991). This measure can be criticized for at least two reasons. First, the average number of tools ties the competition measure to a summary statistic that may reflect a highly skewed distribution. Second, the measure is not generalizable to other local policy areas. In other words, if the city limits story is appropriate, competition must be operationalized to apply to all policy types.

This research directly links the operationalization of intercity competition to public choice the- ory as developed by Tiebout (1956). We count the number of competitors, or jurisdictions, within each sample city’s metropolitan statistical area (see Table 4 for a description of all independent variables). A similar approach was used by Schneider (1989) and Basolo (2000).3

Support for economic development should be tied to the objectives of the policies. The objec- tives of economic development in practice tend to be twofold. First, cities often compete for direct fiscal benefits such as the taxes generated by certain businesses. Cities with relatively worse fiscal conditions may be more likely to spend economic development funds to attract or retain these types of businesses (Pagano & Bowman, 1995). This research uses the revenues-to-expenditures ratio in cities as a measure of fiscal conditions (Basolo, 2000; Goetz, 1990). Second, economic develop- ment seeks to serve population needs such as jobs and livable wages. Population needs have been measured a variety of ways, including the unemployment rate (Reese, 1991), poverty rate, and median household income (Rubin & Rubin, 1987). We compute the z scores for these three vari- ables and create an additive, composite index to measure population needs. The intercorrelations

333

Document info
Document views237
Page views237
Page last viewedSun Dec 04 17:45:27 UTC 2016
Pages94
Paragraphs1542
Words59114

Comments