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A GUIDE TO RETAIL IMPACT STUDIES In some cases, the area to be considered in the impact analysis is already specified by the permitting regulations. For example, Maine's Informed Growth Act specifies that the "comprehensive economic impact area" to be considered "includes the municipality [where the store would be located] and its abutting municipalities." The statutorily defined "impact area" and the "market area" will overlap, but may or may not be identical. In cases where the area to be analyzed is defined by statute, that impact area should be used for the analysis instead of the market area. Please note, however, that under the Maine statute, the impact area "includes" the municipality and abutting municipalities, but does not prohibit the addition of other areas so as to evaluate the entire market area. The terms "market area" and "impact area" are used interchangeably below. Comparing Demand with Actual Retail Sales in the Market Area by Line of Goods Having determined the lines of goods to be sold by the proposed large format retailer and the geographic extent of the impact area or market area, the analyst then quantifies the volume of retail sales in the impact area (referred to as the "supply") and compares those figures with the amount of retail activity expected based on local population and demographic characteristics. This analysis is often referred to as a "retail gap" or "leakage" study. It is a well-established tool of economic analysis and is widely and frequently prepared for communities of all sizes. The purpose of this analysis in this context is to gain an understanding of where new retailers will likely reduce leakage and where they will likely redirect retail sales from existing stores in the impact area. Actual or estimated local sales figures should be established for each line of goods to be studied. Proprietary datasets of sales are available for purchase from various data providers. In large communities, these datasets are generally reliable because public data for larger markets is less often subject to suppression. Suppression is the withholding of public data in order to protect the privacy of businesses or individuals included in the dataset. The smaller the community, the more likely one is to encounter widespread suppression. For example, if a community has only one car dealership, public data will generally not reveal car sales in that jurisdiction. Private sector data providers correct for suppression by applying various methodologies to fill in gaps in the data. In our experience, these datasets are quite accurate, though sales for specific lines of goods in smaller markets may be easily adjusted by the analyst based on real world observations. Actual sales in the impact area are then compared to expected sales in the area. Expected analysts do not calculate demand in-house, relying instead on proprietary data providers. These data providers, moreover, allow potential demand to be estimated within highly customized geographic boundaries. Although these statistical packages, offered by firms such as Claritas, have a cost associated with them, the fees are generally small and will not affect the cost of such studies in any meaningful way. 11