Ronald C. Rutherford’s research while affiliated with University of South Florida and other places

We examine matched rent-price ratios and rent transaction prices for single-family houses in Miami-Dade County between January 2009 and April 2014. The primary dataset consists of properties that are purchased and then rented within 240 days of the purchase. Each of the buyers in the sample are considered investors since each property included has a rental event indicating they are not owner occupied. We examine the relationship between housing and market characteristics and the impact active investors have on single-family rents and rent-price ratios. Entities that purchase the largest number of units pay more for properties, obtain marginally higher rent and obtain lower rent-to-price ratios.

This paper is working on one IPO panel data to estimate the predicting power of some covariates on future status of IPO firms after going public. These new firms could be delisted due to two major reasons, either acquisition or liquidation. Specifically, our study aims to examine how the possibility of each type of delisting could be determined. There are two main findings in this paper. First, we find that the inclusion of the aftermarket performance in a competing-risk model helps distinguish the impact of those covariates on the two types of delistings. For example, profitability increases the chance of being delisted due to mergers but decreases the chance of being delisted due to bad performance. Second, our evidence indicates that time-varying covariates may impact the delistings in different ways. For instance, profitability appears to affect the voluntary delistings only until last year before delisting. In sum, our paper contributes to the prior literature by shedding light on how voluntary/forced post-IPO delistings are determined.

In this paper, we propose a new factor in predicting stock returns, after taking agency problems into account. Although intensive studies have focused on asset growth and profitability as factors in predicting future returns, very limited attention has been given to their interaction. We construct a measure that combines both asset growth and scaled gross profit in a single measure (defined as AGGP, hereafter), by excluding the change in capital expenditures from gross profit. We demonstrate that our measure of profitability controls for the agency problem from managerial decisions in investment. Our results are also robust to the scaling issues raised by recent studies. Further, consistent with prior literature, our measure produces superior results in the full universe of CRSP stocks, but inferior results when applied to a subset of the 500 largest nonfinancial firms. This is consistent with the fact that those largest firms are less affected by the agency problem, leading to the failure of our new measure in predicting future returns among this subsample. In sum, our new measure sheds new lights on how to price agency issues, by providing a “cleaner” profitability measure free of agency costs and also lending supportive evidence to the mispricing explanation of the asset-growth effect.

A co-listing strategy exists when two or more listing agents jointly represent the owner of a property who desires to sell it. This strategy is not new in the real estate brokerage industry, but its popularity has increased during recent years with the formation of teams of agents who repeatedly work together using the co-listing strategy. To date, the literature has not analyzed this business strategy. This study investigates the probability of selling, selling price, and time on market effects related to the use of the co-listing strategy. The results of this study indicate that co-listing is associated with a higher probability of sale, an increased selling price, and a marginal longer or shorter marketing time, depending on the situation. Comparing market outcomes for agents who form teams and repeatedly employ the co-listing strategy against market outcomes for agents who are involved in only one co-listing indicates that both types of co-listing produce higher prices and are more likely to result in a sale, but the effects for repeated co-listings are larger in magnitude. Additionally, repeated co-listing slightly reduces marketing time, but single co-listing slightly increases marketing time. The marketing time effects in both repeated and single co-listings, however, are too small to be economically important. In general, this study suggests that sellers are better served by the co-listing strategy compared to no co-listing, especially when the co-listing agents repeatedly work together in teams.

Recent research on limited service brokerage finds positive broker intermediation effects evidenced by price increases ranging from 2% to 6%. Time-on-market effects of limited service contracts range from an increase of 20% to a reduction of 14%. One article indicates the results suggesting positive broker intermediation effects are contrary to expectations. After controlling for builder-owned properties and the type of listing contract, we find no evidence of positive broker intermediation associated with limited service listings. Houses listed using an exclusive-right-to-sell and limited service contract experience negative price effects with no impact on time-on-market. A repeat sales sample provides additional evidence supporting either a negative or zero intermediation effect for limited service listings.

We examine a recent trend in the market where investors purchase residential properties. We find that investors purchase at a discount of 9.5% compared to individuals purchasing in the same time period and geographic area. More specifically, we find that small investors purchase at a discount of 8.0%, medium investors purchase at a discount of 11.1%, large investors purchase at a discount of 13.6%, and institutional investors purchase at a discount of 7.7%. We also find that the presence of investor buyers in a market helps improve house values. A 10% increase in the percentage of houses purchased by investors in a census block leads to a 0.20% increase in house prices.

In this study, we find the subsequent price for a property initially sold as a real estate owned (REO) property occurs at market prices. The subsequent price to the REO purchaser is related to indicators that the property has been remodeled, renovated, or updated. This suggests that the difference between the price received by servicers/lenders that foreclose and sell a REO property, and the price received by subsequent property owners that sell is in large part due to timely improvements made postforeclosure. Lenders are not selling REO properties at irrational prices, but rather at prices that reflect the condition of the properties.

The existence of the real estate brokerage industry is generally attributed to high transaction costs in real estate markets. Brokers are typically expected to market sellers' properties, assist in contract negotiations, and coordinate the post-contract tasks necessary to close transactions. Presumably, brokers can perform these duties at lower cost than sellers. In addition to cost efficiencies, brokers may also impact market outcomes. Numerous researchers have investigated whether or not the use of brokers as well as various broker actions, broker characteristics, and broker/seller legal relationships affect market outcomes in the form of price and/or, time-on-the-market effects. We extend this line of research by considering price, time-on-market, and probability of sale effects in relation to four specific broker strategies: public open houses, broker open houses, MLS virtual tours, and MLS photographs. The results indicate positive relationships between these strategies and house prices and mixed relationships between these strategies and probability of sale and time-on-market.

Purpose – The purpose of this paper is to examine how long a real estate investment trust (REIT) initial public offer (IPO) survives until a merger occurs, and to determine the impact of different firm characteristics that exist at the time of the IPO on that survival in the aftermarket period. Design/methodology/approach – The authors apply an accelerated failure time (AFT) duration model to determine how long the IPO will survive until merger occurs. Findings – The results indicate that the time from the IPO to an eventual merger increases with size, the age of the REIT at IPO, and the percentage of institutional ownership. In contrast, the authors find that the time until merger decreases with increased market performance prior to the time of the offering and with the number of additional IPOs occurring at the time of the IPO. Practical implications – There is a growing body of research that suggests that IPOs might be motivated by subsequent mergers. An understanding of those characteristics that effect the time until a merger occurs these relationships will enable market participants and capital providers to make better decisions about proceeding with, or evaluating, a REIT IPO. Originality/value – There is a significant body of research on IPOs in general; however, the findings of this research vary depending upon the industry being examined. Further, there are a limited number of papers on IPO aftermarket survival. This is the only paper on REIT IPO aftermarket survival.

The Competing-risk Analysis of post-IPO Delistings This paper is working on one IPO panel data to estimate the predicting power of some covariates on future status of IPO firms after going public. Specifically, our study aims to study how the possibility of the delisting due to different reasons, including merges, moves between exchanges, and bad performance (liquidation/Bankruptcy), is affected by those covariates. The results show that the inclusion of the aftermarket performance in a competing risk model helps to distinguish the impact of those covariates on the delistings caused by three events. There are three main results from our analysis. First, it is found that most of covariates have significant effects on two types of delistings, mergers-and failure-originated. On the other side, only firm size and capital structure are related to the delisting when the IPO firm switches to another exchange. Second, we find that some covariates have significant effects on two delistings, acquisition/merger-or liquidation/bankruptcy-originated, in the same direction, including technology dummy, IPO activity, firm age, asset growth, R&D expenses, and leverage. Third, three covariates, including venture capital dummy, profitability, and firm size, have opposite effect on different events triggering the delisting, mergers and bad performance. The increase of these covariates could increase the risk of acquisition/merge delisting whereas reduce the risk of failure delisting.