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Direct and indirect effects. In the rest of this chapter, we refer to direct and indirect economic impacts of highway projects. Direct effects impact businesses immediately within the project area, while indirect effects are experienced by businesses outside of the project area. For example, if a store is adjacent to a widened highway, a direct effect of the project could be increased business due to greater vehicle traffic past the store location. If that increased business represents a shift of business from a competitor a few miles away, the loss in business at the competing store would be an indirect effect. During and after construction. The distributive impacts of highway projects can be divided into two phases--the construction disruption and the postconstruction period. During construction, access to businesses in the vicinity of the project can be disrupted. Sometimes businesses fear that they will lose customers because of poor access, loss of parking spaces, noise, or other disamenities associated with nearby road or highway construction. The disruption to business activity can be temporary, if the lost customers return after construction is complete, or permanent, if customers form loyalties with substitute stores or suppliers during the construction period. Importantly, there is some disagreement about how much businesses are harmed during a road construction project. Often, transportation agencies take measures to minimize or mitigate the effects of the loss of access, parking, or noise. Also, the negative effects on nearby firms will be influenced by the loyalty of their customers and the nature of their competition. Hence different firms in a construction zone could be affected differently by the project. After construction, a completed road or highway project can change the pattern of accessibility and thus influence the competitiveness of different businesses. One might imagine that the spatial influence of a road project after construction will be roughly the reverse of the impact during construction. The businesses near the road improvement will benefit from improved access, and might be able to lure customers from more distant competitors. Yet while this example helps illustrate the different distributive impacts of the construction and post- construction time periods, there are many reasons why the impacts during and after construction will not be mirror images. Environmental justice analysis should consider the spatial pattern of the positive and negative impacts of highway projects before and after construction, and how those patterns affect minority and low-income communities. METHODS Table 9-1 summarizes the methods we present in this chapter. Method 1. Map and GIS assessment The simplest method for assessing the environmental justice impacts of highways related to economic development is to map businesses around the project. This could be as straightforward as walking or driving the corridor (i.e., a so-called "windshield survey") to assess which businesses might be affected by a construction project. More involved analyses can be carried out by looking at business locations that are depicted on a map. Typically, such a map would be developed using geographic information systems (GIS). A similar technique could be used for 219

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the after-construction period to identify which firms might benefit from improved access and which might be negatively affected by the loss of business to those firms. Table 9-1. Summary of methods for analyzing economic development Assessment Appropriate Use Data Expertise Method level uses when needs required 1. Map and GIS Screening Project/corridor Effects are expected to Low Geographic assessment be low and more information resource-intensive system techniques are not (GIS) available 2. Surveys or Screening/ Project/corridor/ Project or policy is Medium Group focus groups detailed system controversial and high interaction level of interaction with and affected individuals is facilitation required 3. Gravity Detailed Project Changes are expected High Accessibility models in accessibility in many modeling directions and over a wide area When to use. This technique is among the least resource intensive and simplest to apply. It is appropriate either where more resource-intensive techniques are not available to an agency or for projects with relatively small impacts for which more rigorous (and hence expensive) analyses would not be commensurate with the scope of the project. Analysis. For each business identified in the project, you can assess whether the impact of construction will result in a loss of customers using rules of thumb (e.g., reasonable walking or driving distances) or expert judgment (see the description of focus groups in Method 2). This direct effect cannot be cleanly separated from indirect effects because to some extent the loss of customers will depend on available substitute business locations in the same market area. Hence, for each business in the construction zone, you may also want to use data in a GIS format to assess possible competing businesses. This could be a simple listing of such firms, or one could assess the relative characteristics of the competing businesses and the businesses in the construction zone to assess the likelihood of shifts in a customer base. Data needs, assumptions, and limitations. The key element of this method is to document firms that are likely to be affected either during or after construction because of their proximity to the project. These firms will experience the direct effects of the project. For indirect effects, one could catalogue firms in surrounding market areas. The area of interest might be established based on rules of thumb, as noted earlier, or on more detailed assessments of market areas and the locations for nearby competitors of particular firms near the project. 220

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Results and their presentation. One example of this technique would be to walk or drive the project corridor and catalogue each business by location, type of business, and assessment of the expected impact during and after construction. A hypothetical example of the survey results is shown in Table 9-2. Table 9-2. Example of local access assessment Expected impact during Expected impact after Location Business construction project completion 22 Main Gas station One entrance lane obstructed No change in access 26 Main Grocery Loss of 20 parking spaces New right turn lane into parking lot 30 Main Hair salon Entrance lane narrowed Five new parking spaces 34 Main Drugstore Increase in traffic in opposing lane New dedicated left turn lane into at parking lot entrance parking lot The same type of analysis could be used to understand impacts after construction. For each business in an area of improved accessibility, you can assess whether that business will likely draw business away from competitors. This can again be based on rules of thumb or expert judgment. Assessment. This method is the simplest and least resource intensive of those described. As such, it is appropriate in several circumstances. Agencies with limited capabilities can conduct a GIS-based analysis quite easily. This method is also suited to small projects and particularly to those where the agency expects few or no environmental justice issues. Agencies can use this technique as a screening method to verify hunches that projects will have limited environmental justice implications or to illuminate possible issues that will require further analysis. The disadvantage of a GIS-based assessment is that the results can be subjective if, for example, agencies do not carefully articulate the criteria that led to particular conclusions regarding choosing competing businesses or project impact areas. Agencies should take care to apply systematic criteria when making such judgments so that the outcome of the assessment can be clearly linked to the assumptions and methods used. Method 2. Surveys or focus groups Understanding attitudes and reactions of parties affected by transportation projects is important in assessing environmental justice. Surveys or focus groups are a useful tool to acquire information about the characteristics of the affected parties, as well as their expectations regarding the project. These can include expected business losses due to construction disruption, expected benefits due to improved accessibility after the project is complete, and perceived changes in competitiveness due to the altered pattern of accessibility. The quality and appropriateness of surveys and focus groups can vary in different contexts. Occasionally, analysts have been suspicious of these methods, fearing that they allow users to overstate negative impacts. Yet agencies have sometimes under-appreciated the value of surveys or focus 221

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groups both as a means of outreach and as an analytical tool. In some instances, the perceptions of persons and businesses affected by a project might be more accurate than analytical methods, and surveys and focus groups are an excellent way to get information that otherwise might not be available. When to use. Survey or focus groups are especially useful (1) when input from affected parties is vital for understanding the distributive character of economic impacts, (2) when impacts are confined to small geographic areas and analytical techniques based on data for larger geographic regions will not capture the spatial character of the impacts, (3) when data on impacts are not readily available from other means, and (4) when agencies will benefit from direct interaction with the public, as in the case of controversial projects where perceptions are important or when an agency wishes to facilitate communication with parties affected by the project. Analysis. Surveys can be used to capture the general attitudes of a wide range of parties. The results can be analyzed to match groups that benefit from, or are disadvantaged by, transportation projects to geographic locations. Survey sample sizes should be large enough that summaries by geographic areas, income, or race will have sufficient within-category sample sizes. That will often require over-sampling within specific geographic areas, income groups, or minority or ethnic groups. Data needs, assumptions, and limitations. Surveys can be designed to elicit two kinds of information. The first includes general characteristics of the parties in question, such as type of business, number of employees, logistical and other inventory arrangements, and mode of travel of a firm's suppliers, clientele, and employees. The second includes the expectations of the affected parties regarding losses and gains during and after construction of the project. Firms can be asked to estimate how much business will be lost due to construction disruptions, such as closed lanes, noise, and lack of parking space. The gains are mainly in the form of expected increases in business volume once the project is completed. After completion the project may also adversely affect some firms because of shifts in economic activity to locations better served by the new transportation infrastructure. Hence, some firms might be asked to estimate these negative impacts. Surveys are typically conducted either by mail or phone. Various books give detailed advice on how to conduct a survey using either method. One popular reference book is Mail and Internet Surveys: The Tailored Design Method (Dillman 1999). These books offer suggestions on matters such as phrasing questions in a neutral manner, techniques to increase response rates, and follow- up methods for subjects who do not initially respond to the survey. This literature is useful whether an agency develops its own survey or contracts with an outside firm to create it. There are many firms that provide survey research services. Some have a national client base, while others specialize in particular regions or metropolitan areas. Internet-based surveys have recently been used in some settings and are also described in Dillman (1999). A common risk in Internet-based surveys, however, is that the sample of respondents will not be representative of an underlying population of interest. This can occur both because persons or firms with Internet access do not represent a random sample of all persons or firms and because those parties who are particularly interested in a topic are the most 222

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likely to respond to a survey. While response bias is a potential issue in any survey, it is often regarded as more problematic in settings, like some crude Internet-based surveys, where nonrespondents are not contacted to prompt a response. For environmental justice studies, the fact that low-income populations might not have good Internet access could limit the scope for Internet-based surveys. For this reason, we cannot recommend them. Note that, when assessing the economic impacts of transportation projects, the survey population is likely to be firms. This raises additional complications beyond those in household surveys. Before the survey is sent, the appropriate officer within the firm must be identified. This should be an individual who has the needed data readily available. For surveys about economic impacts, this individual will likely be someone high in the management structure of the firm. Thus a pre- survey contact to explain the importance of the study is important. Response rates will increase if firms clearly understand how the survey study will benefit them. Even with the best efforts, response rates for surveys of firms are often lower than response rates for surveys of households. For firms, response rates of 20 to 30 percent are not unusual. See, for example, the discussion in Boarnet (1998b) or Kalafatis and Tsogas (1994). Focus groups provide opportunities for open-ended responses and discussions that are typically not possible in surveys. The groups are usually small--often not more than six or eight persons. They are thus typically used when the need for detailed information outweighs the need for statistical analysis. Focus groups are desirable when agencies are in the exploratory phase; often the information gathered can be used in later research. For example, it is common to use focus groups in the preliminary phase when designing a survey. Results and their presentation. The central purpose of surveys and focus groups is to acquire a clear understanding of the general attitudes, concerns, and preferences of minority populations and low-income populations regarding a proposed transportation project. Results of these methods of interacting with protected populations can be used to help assess whether the project would have a generally positive or negative effect on the economic well-being of these populations. The results also can be used to identify changes in the project or measures that could be taken to mitigate undesirable effects. Often, the analysis of survey data involves summarizing responses for the population. For environmental justice analyses, survey responses will typically be summarized by geographic area, income, or race. This requires that data be collected on locations of survey respondents (firms or households) and on income or race for individuals or for firm owners, employees, and clientele. Assessment. Surveys and focus groups provide detailed information due to the first-hand knowledge of the persons surveyed or interviewed. Hence, these techniques can improve the understanding of the distributive impacts of transportation projects, and the results can be used to design mitigative measures. One must be careful when using survey data, however. Survey respondents who oppose a project, for example, may exaggerate its negative impacts. In addition, the gains and losses predicted by respondents will be based on their perceptions, which may be inaccurate. Care should thus be taken when interpreting the results. Surveys are most reliable 223

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when respondents are better able to judge impacts than any other group and when they have little incentive to exaggerate or misstate impacts. Method 3. Gravity models In addition to being used as a trip distribution model in the traditional four-step transportation planning process, gravity models are also widely used for market analysis. These models can be used to determine such things as the spatial extent of retail market areas, optimal store or public facility sizes, and optimal store or facility locations. The ability of gravity models to give estimates of the size of market areas is of particular interest when assessing the economic impacts of highway projects. Gravity models can be used to understand how changes in accessibility will change market areas, and hence sales, at particular store locations or in particular geographic areas. They can give both qualitative assessments of locations that will likely experience changes in business activity after a transportation improvement and quantitative estimates of those changes. Good references on gravity models for this sort of application include Hayes and Fotheringham (1984), Bendavid-Val (1991), and Filipovitch (1996). Gravity models have two basic elements, scale and distance, which are the determinants of the interaction between any pair of geographical areas. For example, densely populated cities (large scale) tend to generate and attract more trips than sparsely populated cities. Moreover, trips are more likely to occur between cities that are located closer together (short distance) than between distant cities. Gravity models can be adapted to assess environmental justice impacts of highways by analyzing how changes in accessibility (distance impacts) affect the relative attractiveness of communities or neighborhoods. When to use. Gravity models are most appropriate for a highway project that creates significant changes of accessibility in many directions and over a wide area. They can help answer questions about how a proposed transportation project would affect the ability of businesses operated by or serving minority populations to be competitive. Agencies with an operational transportation planning model can make some adjustments to the model to analyze environmental justice impacts. Also, gravity models can be used as a stand-alone tool. Some technical skills are required, however, and so this method may not be suitable for agencies with limited resources. Analysis. With traffic analysis zones (TAZs), census tracts, or census block groups as the units of observation, gravity models can predict how a highway project will affect the attractiveness of an area through changes in its relative accessibility. Consider the hypothetical example in Table 9-3. In the table, origin TAZs are shown in each column, and destination TAZs in the rows. For example, initially, average time for trips that start and end in TAZ A is 5 minutes. Average time for trips that start in TAZ A and end in TAZ B is 15 minutes. The impact of the project is depicted in Figures 9-1 and 9-2. Before a new highway is built, traffic from TAZ A to C must go through B. The construction of the highway causes disruption in TAZs A and C, thereby increasing travel time both within the TAZs and between them. However, after the highway is opened, travel time between A and C (bypassing B) is reduced by more than half. Because less traffic needs to go through TAZ B, the travel time between A and B 224

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also decreases. However, the travel time between A and C becomes less than between A and B. The question is then, how does the new highway affect the relative attractiveness of each zone? The production-constrained gravity model can be written as: Oi w a b j dij Tij = w a b d j ij j where Tij = the shopping spending of zone i residents in zone j Oi = total shopping spending of zone i residents wj = the number of retail stores (or total retail square footage) in zone j dij = the distance between zone i and j The total amount of retail sales in zone j, Rj is given by R j = Tij i Table 9-3. Travel times between TAZs Initial travel times (minutes) Origin TAZ Destination TAZ A B C A 5 15 25 B 15 5 10 C 25 10 5 Travel times during the construction (minutes) Origin TAZ Destination TAZ A B C A 10 15 30 B 15 5 10 C 30 10 10 Travel times after the opening of the highway (minutes) Origin TAZ Destination TAZ A B C A 5 12 10 B 12 5 8 C 10 8 5 The parameter a is expected to be positive, as the larger the number of stores in a zone, the more attractive it will be to shoppers. In contrast, b is expected to be negative because the more distant 225

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the zone, the less likely shoppers will travel to shop there. The above model can be estimated with survey data on shopping travel patterns. In past studies, the ranges of a and b were found to be between 0.5 and 2.0, and -0.5 and -2.0, respectively. Although how the values of the parameters are determined is beyond the scope of this guidebook, some insights into their relative values may be provided here. For example, the values of the parameters may reflect characteristics of trip makers and road networks. Inaccessible locations, such as those within congested areas, may be associated with larger dij because even short distances can provide disincentives for making a trip. Also, destination characteristics and trip purpose can be reflected by the parameter wj. For instance, grocery stores attract trips with higher frequency than furniture stores. In this case, zones with stores that attract trips with lower frequency may be associated with a smaller wj. A C 15 10 B Figure 9-1. Initial network travel times between TAZs A 10 C 12 8 B Figure 9-2. Network travel times between TAZs after the opening of the highway 226

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The forecasted link travel times during and after construction can be input into the gravity model. The results will be a new pattern of trip distribution between zones. If we assume that each zone generates the same amount of traffic, the travel time between zones will determine the amount of traffic between them. The initial distribution will therefore be such that TAZ B will be the most attractive because it is most accessible to both A and C. During the construction, the distribution pattern will not change much because even though travel times in TAZs A and C increase, the relative travel times do not change overall. However, after the highway is opened, travel times from both TAZs A and B to C will decrease, thereby improving the overall attractiveness of TAZ C. TAZ B, on the other hand, will become less attractive relative to C. With this pattern of changes in trip distribution, we can assume that businesses in TAZ C will benefit from the highway opening, but those in TAZ B will likely suffer. According to these results, we can create a map that reflects the distribution of benefits as shown in Figure 9-3. A Neutral C Positive Negative B Figure 9-3. Distribution of economic impacts after construction This map can then be overlaid on a map that represents ethnic and income groups to analyze the environmental justice impacts of the new highway. It is also possible to quantify the gain and loss at different locations in monetary terms. A gravity model can be used to allocate retail- shopping spending to various neighborhoods based on existing residential locations and accessibility changes due to the new highway project. For example, if the population and average income in the three TAZs above are known, they can be used to estimate retail-shopping spending by residents of each TAZ using the gravity model described below. To quantify the impact of a highway project on retail sales, you can compute the retail sales in each TAZ based on current network travel times. This is used as a basis for comparison. The new network travel times can then be used to predict retail sales after the project is completed. The change in retail sales reflects gains and losses in each TAZ. This information can be used to construct a map of distributive impacts. The overlaying technique, as discussed earlier, can then be used for further analysis to determine how distribution impacts may differentially affect protected populations. Data needs, assumptions, and limitations. The key information for this method is how a highway project affects accessibility. This information will be used to determine changes in link 227