Daniel T. Winkler

The Earnings of Real Estate Salespersons and Others in the Financial Services Industry

This study explores the determinants of earnings of salespersons in financial services using nationwide data from the 1990 U.S. Census. The study reveals that security and insurance salespersons earn substantially more than do persons in real estate sales. The returns to K through 12 schooling are highest in the insurance and securities areas, while the returns to college are highest in security sales. For males, the returns to graduate education are negative in real estate and insurance. For females in these same areas, returns are large and positive in insurance and negative in real estate. In all areas of financial services, earnings are higher in larger, more wealthy, homogenous cities.

Price Spreads and Residential Housing Market Liquidity

Most studies of housing market liquidity have measured liquidity in terms of time on the market (TOM), and have sought to explain TOM in terms of property characteristics and measures of market conditions. This paper departs from past studies of housing market liquidity by examining the spread between the listing and contract prices.We develop theory to explain the price spreads in the residential housing market. The model includes the list price of the home, the cost of the search, the standard deviation of offer prices, and TOM. Empirical tests using 3,597 sales for 25 months show a robust relationship of housing market spreads and these variables. Listing price and cost of search have the predicted positive coefficients, and the standard deviation of price offers is found to be negatively related to the price spread.

An Analysis of Shopping Center Investment

During the 1980s, the oversupply of retail space has lowered rents, raised vacancies, and damaged the integrity of financial institutions as developers and other borrowers have been forced into default. This paper explores the propensity of developers to create shopping center space. The research draws on the macroeconomic investment literature to formulate a model of shopping center investment. We estimate our model using shopping center and sales data from all fifty states of the United States and the District of Columbia. Our results provide evidence about how investment in new shopping space responds to changes in retail sales, capital costs, and taxes.

Cost Implications of No-Fault Automobile Insurance.

No fault advocates commonly predict automobile insurance cost savings for consumers in states adopting no-faults statutes in place of a tort system. For states implementing no-fault, the cost results have been mixed. This study compares the loss costs of no-fault from 1974 through 1985. Not surprisingly, the findings suggest that the bodily injury liability loss costs were lower on average in no-fault states than in tort states after controlling for the influence of wages, population density, and the presence of comparative negligence. However, total bodily injury related costs were not significantly lower on average in no-fault states, and they were significantly higher in states with compulsory add-on laws and to a lesser extent in states with high tort thresholds. Whether the lack of estimated cost savings on average in no-fault states in attributable to selection bias or not, the causes of this result are important issues for further research.

Labor Supply, Flexible Hours and Real Estate Agents

Real estate agents have flexibility in choosing hours and employers. These responses are tested with a five-equation recursive model. Agents choose between full- and part-time work. The conditional wage measures productivity adjusted for self-selection to each status. Hours worked in each status depend on the fitted after-tax wage and household income, yielding flexible supply elasticities. Using a 2005 survey of 8,450 U.S. real estate agents, a year of experience raises the full-time hourly wage by 2.5%. Conditional hours worked decline by 0.6%, implying an earnings return of 1.9% per year of experience. The labor supply elasticity for full-time agents is 0.21; it is almost zero for part timers.

Experience from Early Tort Reforms: Comparative Negligence Since 1974.

Insurance consumers in states that have adopted comparative negligence pay more for automobile liability insurance than do consumers in states that retain contributory negligence. Through the use of a transformed generalized least squares regression model, allowance is made for: no-fault, population density, state-specific price-level, and automobile safety/fatality differences. States with pure comparative have much higher costs than do states with modified comparative negligence; states with modified comparative have higher costs than those with contributory negligence. The influence of alternative liability rules on the cost of insurance is of public concern. In recent years many states have changed from contributory negligence to either pure or modified comparative negligence. This article examines the cost of automobile insurance under three liability rules. The authors conclude that states with either type of comparative negligence have higher automobile insurance costs.

Technology and Realtor Income

The ever-expanding use of the Internet and various other information technologies may directly impact the income levels of the real estate brokerage community. With a database of more than 6,000 usable observations from the 1999 National Association of Realtors® member profile, we examine the impact of technology usage on the incomes of Realtors®. In a two-step procedure, we first develop factor loadings, using factor analysis, for multifaceted technology usage by Realtors®. Then we perform a regression analysis of Realtors® income incorporating a variety of independent variables representing licensee (brokers and salespersons) demographics and brokerage firm characteristics as well as the factor score for technology usage. Our results show that the use of the Internet and other information technologies is positively related to the earnings of Realtors®. In a second regression analysis, we use our technology factor score to determine which of a variety of individual Realtor® demographic and brokerage firm characteristics are more related to technology usage than other characteristics. We find that technology usage increases with schooling, number of firms for which the agent has worked, marriage, franchise affiliation, firm size, ownership interest, and hours worked. By contrast, technology usage falls with age, and usage is lower for females and nonwhites. The results of this paper expand our knowledge concerning familiarity with and use of real estate technology and related income.

The Value of Smoking Prohibitions in Vacation Rental Properties

We examine the value of smoking prohibitions by developing a model of the rent differential between smoking and nonsmoking properties. We empirically test for the rent differential using a data set of vacation rental properties from the Outer Banks of North Carolina. Given peak season rents, hedonic variables such as oceanfront location, and number of bedrooms and bathrooms price according to expectations. Distance from vehicular congestion also leads to greater rent, reflecting vacationer desires for beauty as well as peace and quiet. Most significantly, our results reveal that vacationers are willing to pay substantial additional rent for properties that prohibit smoking. Understanding the demand for smoking prohibitions is important to academics, professionals, and others associated with owning, operating, and financing real estate.

A Note on Licensing and the Market for Real Estate Agents

This study develops and estimates a model of real estate agent demand and supply. The estimates of the model show that the licensing examination pass rate and the educational requirements set by state licensing boards affect the numbers and incomes of real estate agents. The study further shows that the demand for agents is related to economic activity in the housing market and that the supply of agents is very elastic with respect to agent earnings.

Forecasting Shopping Center Supply

Forecasting the supply of shopping centers is potentially important to developers, owners, property managers, lenders, appraisers, and other real estate professionals associated with the owning, operation, and financing of shopping centers. During the last decade, an oversupply of retail space has lowered rents, raised vacancies, and damaged the financial integrity of retail property owners and lender financial institutions. This chapter reviews two models — the Koyck distributed lag model and the investment model — that help to predict the creation of shopping center space. The models provide evidence about how the supply of new shopping space responds to changes in retail sales, in the cost of capital, and in local tax rates. Both models indicate that prolonged cycles exist in the construction of shopping space that could lead to the oversupply of retail space.