This article investigates racial differences in the spending patterns of tourists. The article develops a deterministic model to explain expenditures by tourists who stay overnight at a destination. The model is then applied to survey data of tourist expenditures collected from overnight visitors to Virginia Beach during the summer of 1997. The study finds that ceteris paribus overnight visitors spend about the same regardless of their race, while the most important determinant of tourist spending is visitor income. The findings hold whether total party expenditures, party expenditures per day, or expenditures per person per day are examined.

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This paper attempts to identify and adjust for several shortcomings of previous port impact studies in the estimation of primary port economic impact. These shortcomings are found to create the potential for both positive and negative bias. Also presented in this paper is a technique for circumventing several practical problems in the estimation of secondary economic impact. These adjustments are applied to estimate the economic impact of the Port of Hampton Roads, Virginia.ORT ECONOMIC IMPACT STUDIES have become increasingly P important in measuring the static impact of both international and inland ports. Many state and local budgeting agencies find such studies useful in the determination of capital and operating budgets for publicly-owned port facilities.The purpose of this paper is to identify and adjust for several shortcomings of previous port impact studies in accounting for primary sector port economic activity. Further, we suggest a novel technique for utilizing inputoutput tables in estimating the secondary impact of port economic activity. The vehicle used to present these adjustments is our study of the shortterm impact of the Port of Hampton Roads on economic activity in the Commonwealth of Virginia in 1984.The first section of this paper will deal with problems in defining primary port economic impact. The next section introduces a methodology for estimating secondary port economic effects. The third section presents our findings in Hampton Roads. The final section contains conclusions.

Airbnb is an Internet-based firm that connects potential short-term renters with hosts who own or control rental properties. Its rapidly expanding activities are tracked by Airdna, an independent firm that generates seemingly conventional performance metrics describing Airbnb. These metrics include occupancy rates, average daily rates, and revenue per available room. However, Airdna does not adhere to long-established STR definitions for these variables. Using data from Virginia Beach, Virginia, we demonstrate that Airdna’s performance metrics exhibit notable upward biases vis-á-vis STR’s metrics. Potential rental hosts, hoteliers, tax collectors, and investors are at risk if they act on the assumption that Airdna’s metrics are comparable with widely understood measures used by STR and tourism experts.

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