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Economic Impacts of Preservation in New Jersey and Texas

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preservation organizations in two states-New Jersey and Texas-commissioned the authors to conduct comprehensive investigations of the contributions of historic preservation in their respective states. The New Jersey Historic Trust conducted the New Jersey study and the Texas Historical Commission (THC) oversaw the Texas study. Funding for the two studies was provided by the National Center for Preservation Technology and Training, THC, Texas Certified Local Governments (CLGs), and other sources. The two state investigations (hereinafter referred to as the "NJ-TX studies") build from prior studies and extend the state of the art in several ways. More so than in prior investigations, the NJ-TX studies develop preservation-specific data. Examples include profile information on heritage travelers (as opposed to general tourists) and data on their spending patterns, and data on the labor and material requirements related specifically to historic rehabilitation (as opposed to general rehabilitation). The NJ-TX studies are comprehensive analyses. There are many facets to historic preservation, and a study of its economic impacts should incorporate as many of these as possible. The NJ-TX investigations attempt to do this by analyzing the respective economic contribution of: (1) historic rehabilitation; (2) heritage tourism; (3) Main Street investment; (4) operation of historic sites and organizations; and (5) property value and property tax contributions of historic properties. Finally, the NJ-TX studies consider both the direct effects of preservation-related activities and the indirect and induced economic impacts. In brief, the total or multiplier effect, sometimes referred to as the ripple effect, has three elements:

  1. A direct effect (the initial action causing the ripple effects) is the change in purchases due to a change in economic activity.
  2. An indirect effect is the change in the purchases of suppliers to the economic activity directly experiencing change.
  3. An induced effect is the change in consumer spending that is generated by changes in labor income within the region as a result of the direct and indirect effects.
To illustrate, the direct effects encompass the goods and services immediately involved in the economic activity analyzed, for example historic rehabilitation. This could include, for historic rehabilitation, carpenters hired and steel purchased. Indirect effects encompass the value of goods and services needed to support the provision of the direct effects (e.g., materials purchased by the steel plant). Induced effects include the goods and services needed by the households who provide the direct and indirect labor required to rehabilitate a historic structure (e.g., food purchases by the carpenters` or steelworkers` households). Indirect and induced effects are estimated using an input-output model. To estimate the total or multiplier effects of historic preservation, the NJ-TX studies applied an input-output model developed by the Regional Science Research Corporation (RSRC). (For an explanation of input-output models, see previous article.) The RSRC model offers some advantages in detailing the total economic effects of an activity, such as historic rehabilitation. For example, the RSRC enables estimates of governmental revenue (i.e., tax) and regional wealth impacts. The analysis in both studies presents the direct effects of the components of historic preservation (e.g., historic rehabilitation and heritage tourism) and then applies the RSRC model to derive the multiplier effects. Economic effects are specified with respect to the following: Jobs: Effects on employment, both part time and full time, by place of work are estimated using the typical job characteristics of each detailed industry. (Manufacturing jobs, for example, tend to be full time; in retail trade and real estate, part-time jobs dominate.) Thus, the job figures are expressed as job-years; that is, several individuals might fill one job-year on a given project. Income: Income figures include earned or labor income-specifically, wages, salaries, and proprietor income. Income does not include nonwage compensation (i.e., benefits, pensions, or insurance), transfer payments, or dividends, interest, or rents. Wealth: Wealth is estimated as value added-the subnational-level equivalent of gross domestic product (GDP); at the state level, it is called gross state product (GSP). Value added is widely accepted by economists as the best measure of economic well-being. Taxes: Tax revenues generated by the activity are detailed for the federal, state, and local levels of government. New Jersey and Texas Studies on the Economic Contribution of Historic Preservation The direct and total effects of historic preservation in New Jersey and Texas are summarized in exhibits 1 and 2 respectively. In examining the results, the tremendous difference in the population size of the two states must be considered (e.g., in 1997, Texas had a population of 19.4 million, compared with New Jersey`s 8.1 million residents). Understandably, therefore, the direct and total impacts of historic preservation are larger in absolute terms in Texas than in New Jersey. The following sections highlight the important findings from the NJ-TX studies and briefly describe critical data collection and analytic steps. The New Jersey study relied on 1994 data (then the most cur-rent available) while the Texas study, conducted later, had a 1996 to 1997 baseline. Historic Rehabilitation New Jersey invested approximately $123 million in historic rehabilitation in 1994; Texas invested approximately $173 million in 1997. These figures were comparable: the $123 million represented 6 percent of New Jersey`s $2.0 billion total rehabilitation expenditure, and the $173 million accounted for 4 percent of Texas`s $4.2 billion total rehabilitation expenditures. The $123 million and $173 million estimates were based on sampling and other sources. In New Jersey, for example, the sample included a range of community types: urban, mature suburb, developing suburb, and rural. We determined the historic rehabilitation incidence (i.e., the share of total rehabilitation that was effected on properties designated as historic on national, state, and/or local registers) for each community type. Next, we extrapolated to obtain statewide results. A similar procedure was applied in Texas. The historic rehabilitation incidence was developed for nine Certified Local Governments (CLGs) participating in the study, and using these data, as well as building permit and census information for the remaining Texas communities, a state-wide estimate of historic rehabilitation was made. The New Jersey and Texas statewide historic rehabilitation investments ($123 million and $173 million respectively) were entered into the RSRC model using four general property types. Before typing these data, however, we first "deconstructed" the labor and material components of historic rehabilitation (as opposed to general rehabilitation). This analysis was based on an examination of the details of almost 60 historic rehabilitation projects encompassing nearly $100 million of construction work in different types of historic buildings (single- family, multifamily, and nonresidential). The analysis also considered the type and extent of construction activity performed (e.g., the extent of systems upgrading work, and interior or exterior repairs). From these detailed case studies, the research specified the precise "bundle" of construction activities that constitute historic rehabilitation. The RSRC model translated each state`s historic rehabilitation investments by property type. These, in turn, were summed into the total economic impacts (statewide and national) noted in exhibits 1 and 2. For example, statewide impacts in New Jersey included the generation of more than 2,300 jobs, $81 million in income, and $116 million in GSP. The national economic impacts from Texas`s historic rehabilitation included almost 8,150 new jobs, $251 million in income, and $346 million in GDP. Heritage Tourism The incidence and profiles of heritage travelers were segregated from annual travel surveys conducted by both states. Of the 366 million person-days of travel in Texas, 40.7 million, or 11.1 percent, were heritage-related. The heritage traveler share of person-days of travel in New Jersey was 5.4 percent. In both states, heritage travelers spend relatively more than average travelers do (e.g., in Texas, heritage travelers spend $114 daily compared with $88 spent daily by other travelers). Statewide, total annual heritage tourism spending was estimated at $432 million in New Jersey and $1.434 billion in Texas. Texas is clearly a better- known heritage tourism destination despite New Jersey`s higher density of historic properties. Further, Texas`s larger size helps it to retain more of the jobs related to this retail-based activity. Using the information from each state`s annual travel survey, we were able to determine heritage travelers` spending for lodging, food, entertainment, and other purposes. These results were entered into the RSRC Model. The tremendous economic contribution of heritage travel is detailed in exhibits 1 and 2. Nationally, Texas heritage tourism generated almost 59,000 jobs, $1.536 billion in income, $2.377 billion in GDP, and $0.722 billion in taxes. For New Jersey, the national figures were 15,530 new jobs, $383 million in income, $559 million in GDP, and $216 million in taxes. Main Street Programs & Historic Sites & Organizations More than 1,200 communities across the nation have used the Main Street approach to invigorate their downtown areas. Texas has the largest number of Main Street sites (approximately 80) of any state in the nation. On a periodic basis, communities participating in the Texas Main Street Program (as is true in other states) compile standardized data, such as the number of business starts, data on new construction, and data on rehabilitation. If we subtract rehabilitation outlays (since we want to avoid double counting), the net Texas Main Street investment was $97 million. The total national economic impacts, including both direct and multiplier effects, from the $97 million Texas Main Street investment was determined by the RSRC model to encompass approximately 4,100 new jobs, $113 million in income, $171 mil-lion in GDP, and $53 million in taxes. The instate Texas gains were approximately 50 to 60 percent of these figures. We also determined the spending of historic sites and organizations. This information was obtained from both in-state surveys and surveys conducted by Rutgers. Thus, in New Jersey, a Rutgers survey determined that the state`s historic sites and organizations spend $36 million annually. To avoid double counting, we had to ascertain the economic impacts added by historic sites and organizations over and above the economic contributions of the historic preservation components already tallied (e.g., historic rehabilitation at the sites and the revenues received from heritage travelers). Subtracting the rehabilitation costs and visitor revenues resulted in an estimated annual net spending by New Jersey historic sites and organizations of $25 million. This direct spending was then translated into total economic impacts through the RSRC input-output model. The New Jersey results are shown in exhibit 1. The same process was used to determine annual net spending by historic museums in Texas, the results of which are shown in exhibit 2. Property Values A side-by-side comparison was made of the property values of historic properties (i.e., designated properties) and comparable non-historic properties in nine Texas CLGs. A hedonic analysis was performed to control for various housing quantity attributes. Historic designation was associated with high-er property values in all of the CLGs, with that difference found to be statistically significant in seven of the nine communities. In the cities where historic designation had a statistically significant effect on property values, average property value increases ranged between 5 percent and 20 percent of the total property value. In dollar terms (dollar-value change per housing unit), historic designation was associated with average increases in housing values ranging between approximately $3,000 and $19,000. Application of Studies on the Economic Impacts of Historic Preservation Studies such as those conducted in New Jersey and Texas can be used to demonstrate the tremendous economic pump-priming effect of historic preservation. The total annual national economic impacts of New Jersey`s preservation activities amounted to almost 22,000 new jobs, $572 million in income, $929 million in GDP, and $415 million in taxes. The in-state New Jersey impacts included approximately 10,100 new jobs, $263 million in income, $543 million in GSP, and $298 million in taxes. For Texas, the total annual national economic impacts included approximately 73,200 new jobs, $1.956 billion in income, $2.967 billion in GDP, and $904 million in taxes. The in-state Texas impacts included approximately 40,700 new jobs, $890 million in income, $1.471 billion in GSP, and $445 million in taxes. Although not detailed in this article, the above economic impacts are spread throughout the economy, from agriculture to manufacturing. Our research showed that preservation was often a superior economic catalyst compared with other investments. For example, in New Jersey, $1 million in non-residential historic rehabilitation was found to generate 38.3 jobs nationally and 19.3 jobs in-state. In comparison, $1 million in new nonresidential construction was found to generate fewer jobs: 36.1 jobs nationally and 16.7 jobs in-state. Our analysis can be used to rebut unwarranted but nonetheless common attacks on preservation. While opponents find it difficult to disagree that preservation is a "good thing," they often allege that preserving the past will "cost jobs" or will "lower property values." Our research shows that such allegations are simply wrong-headed. Economic results, like those above, can be used to justify incentives for historic preservation. Texas allows all taxing entities to offer property tax relief for the preservation of historically significant properties. The economic benefits of such preservation (documented in the Texas study), including enhanced tax revenues, reduce the tax cost of the property tax incentives. Similarly, Rutgers used the results of the New Jersey investigation to show that the public cost of capital grants for historic rehabilitation that were distributed by the New Jersey Historic Trust was easily offset by state tax revenues resulting from those investments. For too many years, preservation has been defended solely on aesthetic grounds. NJ-TX-type studies show that preservation also provides significant economic benefits. Rutgers is currently analyzing the economic impacts of preservation in Missouri and hopes to apply the analysis in other locations. David Listokin and Michael L. Lahr are professors at the Center for Urban Policy Research at Rutgers University, New Brunswick, New Jersey. REFERENCES Leithe, Joni L., Thomas Muller, John E. Petersen, and Susan Robinson. 1991. The Economic Benefits of Preserving Community Character: A Methodology. Chicago: Government Finance Research Center of the Government Finance Officers Association. Listokin, David, Barbara Listokin, and Michael L. Lahr. 1998. The Contributions of Historic Preservation to Housing and Economic Development. Housing Policy Debate 9: 431-478. Listokin, David, and Michael L. Lahr. 1997. Economic Impacts of Historic Preservation in New Jersey. Research oversight by the New Jersey Historic Trust; funding from the National Center for Preservation Technology and Training. Listokin, David, Michael L. Lahr, and Robin Leichenko. 1999. Economic Impacts of Historic Preservation in Texas. Research oversight and funding by the Texas Historical Commission, Preservation Dallas, and Texas Certified Local Governments. Rypkema, Donovan D. 1994. The Economics of Historic Preservation: A Community Leader`s Guide. Washington, DC: National Trust for Historic Preservation.

Publication Date: Spring 2000

Author(s):David Listoken & Michel L. Lahr
Volume:14
Issue:3

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