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On Setting flat Rental Rates: A Regression-Based Approach
Joseph L. Pagliari, Jr* James R. Webb**
Abstract. This study presents a regression-based analysis of flatcar rents for a crosssection of properties located in an knock against city submarket. It go abouts to provide a solution for owners and managers of apartments to the thorny job of setting a propertys rental number. The nestle used in this analysis differs from previous studies in at least three important respects: (1) vacancy is handle as part of the dependent variable, (2) the property-speci?c rental rate generated by the regression analysis is compared to the propertys literal legal rent, and (3) each property in the submarket is ranked by the difference between its actual effective rent and its characteristic-adjusted effective rent. This is then followed by several observations concerning the advantages and disadvantages of such an analysis in a practical setting.
Introduction
The question of setting the appropriate cost for any good or service is a extreme aspect of business management, so too for apartment owners and operators. equivalent other businesses, apartment markets are constantly in ?ux.
The units demanded shift with tenants wants, needs and their ability to afford them, while competing properties continuously attempt to differentiate their product based on quality and/or price. In short, the pricing/product landscape is constantly changing. For the apartment sector (like the hotel sector), this volatility is particularly important, given the large circumstances of leases expiring each year. In this study, regression analysis is used to account the appropriate rental rate for a cross-section of apartment properties. Regression packages1 are now available in just about electronic spread sheets. Therefore, owner/operators in the multifamily sector, as with to the highest degree business managers, can substantially improve their decisionmaking...If you want to quarter a full essay, order it on our website: Ordercustompaper.com
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