residential real estate realities after the financial ... · in the years since the great recession...

J. Reid Cummings 1

Residential Real Estate Realities after the Financial Crisis: Examining the Effectiveness of Seller-Paid

Incentives to Buyers and Agents

J. Reid Cummings, DBA University of South Alabama

Abstract

The focus of this study is on the effectiveness of various combinations of seller-paid incentives offered to buyers and/or agents in connection with residential sales transactions. Specifically, I examine the impacts of combinations of incentives offered to buyers and selling agents on sales prices and marketing duration in a metropolitan area experiencing a declining real estate market during the post-financial crisis period. Consistent with previous research, I find incentives offered to buyers are effective. Additionally, in certain circumstances, incentives offered to agents are also effective.

Section 1. Introduction In the years since the Great Recession (Wilkerson, 2009) began, due to the bursting of the housing bubble and the subsequent financial crisis relating to the mortgage market meltdown (Bianco, 2008), the real estate industry has been devastated on many fronts (DeLisle, 2007, 2008). The implosion of the mortgage markets began in July 2007 when two Bear Stearns mortgage-backed securities hedge funds, holding nearly $10 billion in assets disintegrated into nothing (Foster, 2008). Panic quickly spread to financial institutions that were unable to hide their sub-prime mortgage exposure; outright fear soon replaced panic, and the ensuing national credit crisis rapidly evolved into the collapse of the housing and construction markets (Coleman, La-Cour-Little and Vandell, 2008). Millions of American homeowners faced a new, unfamiliar reality: the values of their homes were no longer rising. Instead, they were falling, and in literally hundreds of thousands of cases, dramatically so (Baker, 2008). Seemingly overnight, many Americans realized they could no longer stick a sign in their front yard and wait on their front porch for the pre-crisis quick formation of long lines of eager buyers. The new, post-crisis residential real estate realities forced many sellers, especially motivated ones, to consider more aggressive approaches if they wanted to successfully sell their homes.

2 The Southern Business and Economic Journal

Because of the combination of significant losses in equity value and increased debt service payments after the crisis, homeowners had to understand, accept, and react to the lightning fast shift from the exploding seller’s market that existed before the crisis to the imploding buyer’s market that developed thereafter. Throughout the country, this new market environment paradigm forced home sellers and their real estate agents to reexamine the marketing tactics and transaction structures they could employ in order to offer the best chances of successfully selling their properties at reasonable prices and within acceptable timeframes. During the post-crisis period, many factors such as tightening credit markets, rising unemployment, and overall economic uncertainty worked against the probability of home sales. Therefore, the study of the means employed by sellers to attract buyers and agents in order to motivate home sales during such an enormously distressed real estate market is of particularly significant interest.

Literature includes research initiatives on the impacts of incentives offered by sellers to motivate property sale transactions, including financing considerations offered by sellers to buyers (for example, see Asabere and Huffman, 1997; Ferreira and Sirmans, 1989; Johnson, Anderson and Webb, 2000). Researchers have also studied both cash and non-cash incentives offered by sellers to selling agents (for example, see Anglin and Arnott, 1991; Johnson, Anderson, and Benefield, 2004; Geltner, Kluger and Miller, 1991; Munneke and Yavas, 2001; Zorn and Larsen, 1986). However, this study differs from previous research, as it is the first to examine the use of various seller-paid sales incentives offered to buyers and/or agents to motivate property sales. It is an important issue because successfully identifying strategies that effectively lead to higher sales prices and shorter sale periods will be useful to all real estate transaction participants. Transaction sales price and time on market are proxies I use to gauge the effectiveness of the offered incentives. Focusing on single-family residential homes in Montgomery, Alabama,1 this study examines 4,408 sales of properties listed for sale on or after March 1, 2008, and that sold on or before February 28, 2012 at prices between $75,000 and $375,000. The results are interesting because like previous research they show incentives

1 The data draws from the multiple listing service of the Montgomery Association of Realtors (MARMLS).

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offered to buyers can be effective in producing the desired outcomes of higher prices and shorter marketing periods. However, unlike previous studies, this research shows that under certain circumstances, incentives offered to agents are also effective in doing so. The remainder of this paper proceeds as follows: Section 2 describes the theoretical background and provides a literature review. Section 3 presents the hypotheses development, data, and methodology. Section 4 discusses the results and analysis. Section 5 provides concluding remarks.

Section 2. Theoretical Background and Literature Review

2.1. Agency Theory Researchers frequently apply agency theory to studies of the real estate brokerage industry. Marsh and Zumpano (1988) point out that real estate markets operate inefficiently because prices do not always reflect the real values of the underlying assets, since all information needed to correctly determine values is not readily available to all market participants. For example, not all sellers know the value of all other sellers’ homes just as not all buyers know the prices previously paid for all sold properties. Unlike transactions involving publicly traded companies, which take place on organized exchanges, and are subject to myriad regulations dictating extensive, complex information disclosures, real estate transactions generally occur in small, local markets and are not subject to information disclosure regulations. Multiple frictions within real estate markets contribute to market inefficiencies (e.g. high degrees of information asymmetry, costly discovery, conflicts of interest, adverse selection and moral hazard problems, income tax considerations, etc.). Real estate transactions are all uniquely different, quite complex, and involve participants with differing motivations. Moreover, because they involve properties that are non-homogeneous, information is difficult and often costly to obtain. This is why buyers and sellers, who are infrequent market participants, more often than not turn to intermediaries to assist them in buying or selling their properties. These intermediaries, known as real estate brokers (hereafter the terms “agent” and “broker” will have the same meaning) work through organized information exchanges (multiple listing services (MLS)) to gather, organize, track, and disseminate information about properties that are for sale or that have sold in the marketplace. Because they are engaged in the market regularly, real estate agents have more information than their clients do; therefore, in agency


theory parlance, there is a high degree of information asymmetry between brokers and their clients.

Yet information asymmetry is not the only aspect of agency theory applicable to the real estate brokerage industry; moral hazard and adverse selection are also prevalent. Moral hazard occurs because the seller cannot know, nor can he verify how much effort his agent exerts to find a buyer. Even though the seller can verify the presence of signs, placement of advertising, listing service exposure and the occurrence of marketing events such as open houses and invitation-only property previews, the seller cannot actually monitor all of the agent’s efforts. In other words, the seller cannot readily observe the amount of effort the agent exerts in locating potential buyers for his property. The listing agent knows he has other clients’ listings to service and will spend some of his time doing so. As he can easily rationalize that because he controls the listing, he will receive at least a portion of the commission when the property sells, in some ways he will rely on the efforts of other agents in the market to produce a buyer. Adverse selection occurs because the seller can never know in advance to what extent all that the listing agent has represented about his abilities, education, training, work ethic, professionalism, character and so forth is true. Sellers can mitigate agency problems relative to potential buyers, his broker, and other agents in the marketplace by sending all of them the right signals.

2.2. Signaling Theory Signaling theory springs from the seminal proposition that an informed party can reduce information asymmetries by engaging in efforts to communicate aspects of information it has to an uninformed party in order to influence a particular desired response (Spence 1973). In other words, the informed party sends signals that effectively reveal information to persuade the uninformed party to act in a way they otherwise would not. In sending signals, firms make decisions about the means they use, the amount of resources they will commit (the signal has to be costly so that it is not easily imitated or reproduced), and the actions they intend to motivate. In receiving signals, investors make decisions about the intended purpose of the signal, the credibility of the sender, and the accuracy of the information received.

2.3. Competitive Pricing In any type of market, competitive pricing is the key to attracting buyers and closing sales. For example, when buyers know what the

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real values are, overpriced automobiles usually remain unsold on a dealer’s lot. Likewise, informed investors generally refrain from buying stock in a company when they believe its shares are overvalued. The same holds true in the housing market. With only rare exceptions, in a competitive market buyers tend not to overpay for houses; surprisingly, buyers often refrain from underpaying as well because of their perceptions there may be problems associated with a house that is highly underpriced (Anglin et al., 2003). Hence, pricing property competitively is the most basic, if not the most important thing a seller can do to increase the probability it will sell at a fair price within an acceptable period. Because information asymmetry exists between sellers and buyers—sellers know more about their property than buyers—in order to increase their sales chances sellers use pricing to send signals to buyers about their level of motivation to sell.

The issue of pricing is highly significant and the real estate literature includes extensive research on the topic of initial list price. Although sellers are heterogeneous, those who plan to move to another home quickly tend to have shorter marketing durations and lower sales prices, yet their motivations do not necessarily affect initial list price (Glower et al. 1998). Knight (2002) finds that mispricing when establishing the initial list price proves costly to sellers as properties with larger changes in price during the listing period ultimately take longer to sell, and the sales occur at much lower prices. Springer (1996) suggests that in the face of financial distress or forced relocation, sellers initially price their homes below market value as a way to signal their motivation to the market. While mortgage interest rates influence marketing durations for houses of equal quality, over-pricing is not an effective strategy, even in robust housing markets (Hang and Gardner, 1989). Setting the initial list price too high or even too low impacts marketing success as buyers have difficulty correctly interpreting the motivations signaled by the seller (Anglin et al., 2003). Similarly, buyers limit their property search for homes within a certain list price range (Haurin, 1988). The greater the extent of overpricing, interpreted by buyers as signals of low seller motivation, the lesser the likelihood a sale will occur (Johnson et al., 2007). Benjamin and Chinloy (2000) argue sellers use initial list pricing at or below market value to signal their elevated level of motivation to buyers. Finally, Green and Vandell (1994) suggest there is an inverse relationship between property overpricing and the frequency of offers submitted by potential buyers.


2.4. Incentives to Buyers Sellers often seek to improve their chances of successfully procuring a sale by offering various cash incentives to buyers. For example, motivated sellers might express their willingness to pay for certain closing costs, such as a buyer’s mortgage loan origination fees or discount points, or costs for an appraisal, a survey, or a home warranty. Some sellers get even more creative by offering financial allowances for the replacement of flooring or roofing, or for making different types of repairs. More inventive still, some sellers might go so far as to offer to pay for property insurance, property taxes, or homeowners association dues. One builder in this study’s dataset even offered to pay for a prospective buyer’s mortgage payment for the first year. In some instances, non-cash incentives serve as the property sale motivator. In most markets, it is typical for the seller to leave built-in appliances and electronics such as hot water heaters, ovens, stoves, dishwashers, and alarm systems in place (Epley et al., 2002). However, removable items such as refrigerators, clothes washers and dryers, and televisions and surround sound systems are generally not included; sellers sometimes offer to include these removable items to provide added incentives to the buyer. On the extremely creative side—as evidenced in this study’s dataset—sellers enticed buyers with such non-cash incentives as airline tickets, cruises, club memberships, jewelry, and even fur coats.

Clearly, sellers can signal their level of motivation to buyers by offering any or a combination of any of these types of incentives; however, research is scarce on their use. Previous research largely focuses on sellers agreeing to pay for some or all of buyers’ closing costs, yet the results are somewhat mixed. In their examination of the combination of seller-paid closing costs and discount points, Johnson et al. (2000) stipulate that when a seller provides assistance with discount points, in effect, the seller is subsidizing the buyer’s debt service by reducing the amount the buyer borrows. However, closing cost assistance by the seller only serves to reduce buyers’ out of pocket expenses; in some cases, the buyer may actually find his debt service increases because of sales price premiums demanded by the seller in exchange for the closing costs concessions. They find full capitalization of the total amount of seller paid closing costs and discount points concessions into the contract sales price. Other research finds that when a sale is financed using non-conventional or “creative” financing (e.g. mortgage rate buy-downs, below market interest rates, mortgage assumptions, owner financing, etc.) only partial capitalization of closing costs and discount points in to the

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sales price occurs (Asabere and Huffman, 1997; Colwell et al., 1979; Guntermann, 1979; Smith and Sirmans, 1984; Zerbst and Brueggeman, 1977). In their study of the trade-off between sales price and marketing duration Ferreira and Sirmans (1989) concluded that in a healthy market sellers were able to capture sales price premiums when mortgages were assumed without exceeding the average time on market. However, unfavorable market conditions can force sellers to concede such price premiums in order to decrease time on market. More recently, Soyeh, Wiley, and Johnson (2014) study the use of buyer incentives in a down market. Their research is particularly germane to my study as the data for both derive from comparable post-crisis market periods. They find during market downturns, there is no capitalization of buyer incentives into the selling price, and that closing costs do significantly reduce marketing duration.

2.5. Incentives to Selling Brokers A seller can also offer incentives to the real estate agent responsible for procuring a buyer in hopes of maximizing their sales prices while minimizing selling time. As with incentives to buyers, sellers can offer agents a variety of cash and non-cash incentives. In a typical real estate transaction, there are two sides of the deal. The listing side involves a ‘listing agent’ who lists the seller’s property for sale, while the selling side involves a ‘selling agent’ who brings a buyer to the table. When a single agent handles both sides, he receives the entire commission—both the listing and the selling side. Although a single agent can handle both sides, in many cases there are two agents involved in the transaction. Therefore, sales commission split is important. It is typical in many markets throughout the U.S. for the listing agent to receive a larger portion of the sales commission than the selling agent (Miceli, 1991). The rationale behind this is that the listing agent establishes the relationship with the seller, procures the listing, and thereafter spends significant time, effort, and money marketing the property for sale.

The literature includes multiple studies that empirically examine agent incentives in a real estate transaction, yet the results reach different conclusions. Anglin and Arnott (1991) suggest that when applied to real estate listing contracts, agency theory overlooks the significant contract issues of robustness and costs of complexity. They note that typical contract price percentage-based listing contracts do an inadequate job of properly allocating risk between the seller and his agent. Furthermore, because the contract fails to


provide suitable incentives to the listing agent, he will often exert less effort than his client expects; hence, moral hazard is an issue from the outset. In their focus on flat-fee and contract price percentage-based sales commissions, Zorn and Larsen (1986) find that one arrangement does not motivate an agent to increase buyer search efforts more than the other does. Another study suggests no differences in sales prices or marketing durations between agents who work in a full commission brokerage office2 versus agents who work in a traditional brokerage office3 (Munneke and Yavas, 2001). Another study reveals somewhat counter-intuitive results by showing that sellers who offer a selling bonus to the selling agent4 experience not only a more prolonged marketing period, but also realize a smaller sales price when compared to properties listed without a selling bonus (Johnson et al., 2004).

Researchers have also studied the effectiveness of non-cash incentives; most studied is the use of imputed non-cash incentives derived from finite duration listing contracts. For example, Miceli (1989) found that compared to listing contracts of infinite duration, listing contracts with definitive expiration dates yielded increased broker efforts. The reason is that the broker realizes that time, money, and effort spent marketing the property for sale during the listing period will yield him no return if a sale does not occur within the listing contract term. A somewhat related work found that agents increase their efforts over time as the expiration of the listing term draws near. The reason is the same as with the previous study: no sale equals no income, and therefore, no return on the resources invested by the agent (Geltner et al., 1991). Longer-term listing contracts reduce agent marketing and buyer search efforts, and consequently, time on market increases (Waller et al., (2010). Similarly, lengthy listing contracts have the effect of brokers waiting until the end of the listing term to put forth marketing and buyer search efforts as they concentrate the bulk of their energies on their other listings that are closer to expiration (Brastow et al, 2011). To date there is no empirical research on the use of other types of non-cash incentives offered by sellers to the selling agent (e.g. airline 2 In a full commission brokerage office, agents pay for a portion of office overhead and keep the entire sales commission. 3 In a traditional brokerage office, the company provides office space, overhead, and secretarial support in exchange for a smaller split of the sales commission. 4 In this type of arrangement, a selling bonus is typically an additional flat-fee or percentage over and above the selling side of the sales commission.

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tickets, shopping sprees, spa packages, vacations, iPads, flat-screen televisions, hunting excursions, and sporting event tickets).

A possible conclusion from previous research is that from the perspectives of all of the transaction participants, seller paid concessions and incentives play an important role in the outcome of the residential real estate sales transaction. However, there is a gap in the literature on the use of seller paid incentives offered to buyers in combination with seller paid incentives offered to selling agents. It is an important issue to explore because to date, no one has examined how the use of multiple incentives offered by the seller might influence the outcome of a seller’s efforts to sell his property. Moreover, in a down market (i.e. such as that which occurred after the financial crisis), many sellers are typically anxious to sell their properties. Identifying sales strategies offering effective means for doing so will likely be of keen interest to academics and practitioners alike.

Section 3. Hypotheses Development, Data, and Methodology

3.1. Hypotheses Development The focus of this study is on the effectiveness of the use of seller paid incentives to both buyers and selling agents involved in residential real estate sales transactions after the financial crisis. During the post-crisis period decreasing residential housing values, increasing borrower qualification standards, rising unemployment, and surging foreclosures made selling a home in most markets extremely difficult. Therefore, to find success in such a challenging environment, sellers had to signal the level of their motivations to increase the probability their houses would sell. In this paper, I posit that many sellers turned to the use of various incentives as a means of signaling market participants they were motivated to sell, or at least were more motivated than those who did not offer such incentives. Accordingly, I propose the following hypotheses: H1a: Sellers who signal their motivation by offering incentives to

buyers will realize higher sales prices. H1b: Sellers who signal their motivation by offering incentives to

buyers will realize decreased marketing durations. H2a: Sellers who signal their motivation by offering incentives to

selling agents will realize higher sales prices.


H2b: Sellers who signal their motivation by offering incentives to selling agents will realize decreased marketing durations.

3.2. Data This study’s data include 4,408 observations of single-family residential homes located within the city limits of Montgomery, Alabama, listed for sale during the four-year period between March 1, 2008 and February 28, 2012, and that sold during the same period at prices between $75,000 and $375,000.5 The data include individual property’s information including location, physical characteristics, age, listing date, sale date, and occupancy and foreclosure status. Data also include indications of whether the seller is motivated, and how much, if any, the seller paid toward closing costs. Table 1 presents descriptions of the variables used. Table 1. Description of Variables.

Variable Description List Price Original list price of the property Sales Price Contract sales price of the property List Date Date of original contract listing of the property Sale Date Date of sale closing of the property Discount Equal to 1 - (Sales Price / List Price) Time Total number of days between list date and sales date Age Age of property in years Square Feet Total number of heated and cooled square feet in property 5 Bedrooms 1 if property has 5 bedrooms; 0 otherwise 4 Bedrooms 1 if property has 4 bedrooms; 0 otherwise 3 Bedrooms 1 if property has 3 bedrooms; 0 otherwise 2 Bedrooms 1 if property has 2 bedrooms; 0 otherwise Half-Bath 1 if property has half-bathrooms; 0 otherwise Fire 1 if property has a fireplace; 0 otherwise New 1 if property is new construction; 0 otherwise Energy 1 if property has energy efficiency features; 0 otherwise

Brick 1 if property exterior is brick, cement block, or cement board; 0 otherwise

Slab 1 if property is built on a concrete slab; 0 otherwise Pool 1 if property has a swimming pool; 0 otherwise

Unemployment Unemployment rate reported for Montgomery MSA in month property is listed

Interest Average interest rate on a 30-year, fixed-rate, conventional mortgage in month property is listed

Points Average points paid on a 30-year, fixed-rate, conventional mortgage in month property is listed

Inventory Total number of houses for sale divided by sales in month property is listed

5 The data were winsorized prior to reducing the sample to the stipulated price ranges.

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Spring 1 if property is listed in March, April or May; 0 otherwise Summer 1 if property is listed in June, July, or August; 0 otherwise

Fall 1 if property is listed in September, October, or November; 0 otherwise

Winter 1 if property is listed in December, January, or February; 0 otherwise

FC Year 1 1 if property is listed between March, 2008 - February, 2009; 0 otherwise




Vacant 1 if property is vacant; 0 otherwise Motivated 1 if seller is motivated; 0 otherwise Foreclosed 1 if property is foreclosed; 0 otherwise Buyer ~ Agent 1 if incentives are offered to either buyer or selling agent; 0 otherwise Buyer & Agent 1 if incentives offered to buyer & selling agent; 0 otherwise Buyer Only 1 if incentives offered to buyer; 0 otherwise Agent Only 1 if incentives offered to selling agent; 0 otherwise Buyer ~ Agent & Motivated

1 if incentives offered to buyer or agent & seller is motivated; 0 otherwise

Buyer & Agent & Motivated

1 if incentives offered to buyer & agent & seller is motivated; 0 otherwise

Buyer Only & Motivated 1 if incentives offered to buyer only & seller is motivated; 0 otherwise

Agent Only & Motivated 1 if incentives offered to agent only & seller is motivated; 0 otherwise

Buyer ~ Agent & Vacant

1 if incentives offered to buyer or agent & property is vacant; 0 otherwise

Buyer & Agent & Vacant

1 if incentives offered to buyer & agent & property is vacant; 0 otherwise

Buyer Only & Vacant 1 if incentives offered to buyer only & property is vacant; 0 otherwise

Agent Only & Vacant 1 if incentives offered to agent only & property is vacant; 0 otherwise

Table 2 presents summary statistics of the data sample. Table 2. Summary Statistics: 4,408 Observations.

Variable Mean Std. Dev. Min. Max. Range List Price $175,713 $70,819 $75,000 $375,000 $300,000 Sales Price $164,271 $67,065 $75,000 $375,000 $300,000 Discount 0.064 0.073 -0.284 0.599 0.883 Time 126.400 99.900 1.000 1116.000 1115.000 Age 26.900 21.600 0.000 132.000 132.000 Square Feet 1969.200 572.400 949.000 4979.000 4030.000 5 Bedrooms 0.038 0.192 0.000 1.000 1.000 4 Bedrooms 0.364 0.481 0.000 1.000 1.000 3 Bedrooms 0.568 0.495 0.000 1.000 1.000 2 Bedrooms 0.030 0.172 0.000 1.000 1.000 Half-Bath 0.176 0.381 0.000 1.000 1.000 Fire 0.845 0.362 0.000 1.000 1.000


New 0.157 0.364 0.000 1.000 1.000 Energy 0.658 0.475 0.000 1.000 1.000 Brick 0.716 0.451 0.000 1.000 1.000 Slab 0.898 0.302 0.000 1.000 1.000 Pool 0.098 0.298 0.000 1.000 1.000 Unemployment 0.081 0.020 0.036 0.104 0.068 Interest 0.052 0.007 0.039 0.065 0.026 Points 0.679 0.079 0.400 0.800 0.400 Inventory 7.700 2.960 4.010 16.110 12.100 Spring 0.329 0.470 0.000 1.000 1.000 Summer 0.273 0.446 0.000 1.000 1.000 Fall 0.205 0.404 0.000 1.000 1.000 Winter 0.193 0.395 0.000 1.000 1.000 FC Year 1 0.312 0.464 0.000 1.000 1.000 FC Year 2 0.296 0.456 0.000 1.000 1.000 FC Year 3 0.239 0.427 0.000 1.000 1.000 FC Year 4 0.153 0.360 0.000 1.000 1.000 Vacant 0.559 0.497 0.000 1.000 1.000 Motivated 0.099 0.299 0.000 1.000 1.000 Foreclosed 0.142 0.349 0.000 1.000 1.000 Buyer ~ Agent 0.339 0.474 0.000 1.000 1.000 Buyer & Agent 0.031 0.174 0.000 1.000 1.000 Buyer Only 0.278 0.448 0.000 1.000 1.000 Agent Only 0.092 0.289 0.000 1.000 1.000 Buyer ~ Agent & Motivated 0.063 0.242 0.000 1.000 1.000 Buyer & Agent & Motivated 0.005 0.074 0.000 1.000 1.000 Buyer Only & Motivated 0.036 0.185 0.000 1.000 1.000 Agent Only & Motivated 0.012 0.110 0.000 1.000 1.000 Buyer ~ Agent & Vacant 0.196 0.397 0.000 1.000 1.000 Buyer & Agent & Vacant 0.023 0.148 0.000 1.000 1.000 Buyer Only & Vacant 0.176 0.381 0.000 1.000 1.000 Agent Only & Vacant 0.056 0.231 0.000 1.000 1.000

The mean listing price is $175,713, the mean transaction sales price is $164,271, the mean selling discount is 6.40%, and the mean marketing duration is 126.4 days. On average, properties contain 1,969.2 heated and cooled square feet, and are 26.9 years old. 15.68% of the properties sold are newly constructed, 55.92% are vacant, and 14.22% are in foreclosure.

In this study, the variable of interest is the combination of incentives offered to the buyer and the selling agent. Buyer ~ Agent is a dummy variable taking a value of one if within either the public or agent remarks section of the property listing there are comments referencing any type of incentives offered to the buyer or the selling agent and zero otherwise. A few examples of words or phrases used to offer incentives to the buyer include ‘seller to pay closing costs,’ ‘refrigerator, washer, and dryer to remain,’ ‘seller will pay first

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year’s mortgage payment,’ or ‘free cruise with accepted offer.’ A few examples of words or phrases used to offer incentives to the selling agent include ‘$5,000 bonus to selling agent,’ ‘free iPad to selling agent,’ ‘extra 3% commission to selling agent,’ or ‘$1,000 shopping spree to selling agent.’ Either incentives offered to buyers or agents are present in 33.92% of all transactions. Buyer Only is a dummy variable taking the value of one if the seller offers incentives only to the buyer and zero otherwise, while Agent Only is a dummy variable taking the value of one if the seller offers incentives only to the agent and zero otherwise. Buyer incentives only occur in 27.84% of transactions, while 9.19% included incentives offered only to the agent. Buyer & Agent is an indicator variable taking a value of one if incentives are offered to both the buyer and the selling agent. Only 3.11% of transactions included incentives offered to both the buyer and the selling agent.

Time is the measurement for time on the market calculated as the number of days between listing date and sale date. Discount equals the value of 1 minus the ratio of Sales Price to List Price. Prior research shows the time of year a property is listed impacts time on market (Forgey et al., 1996; Kluger and Miller, 1990). Seasonal dummy variables are created to take when the properties are listed into account with Spring including properties listed in March, April, or May, Summer including properties listed in June, July, or August, Fall including properties listed in September, October, or November, and Winter including properties listed in December, January, or February. Dummy variables for each of the four years during the post-financial crisis time period studied include FC Year 1, FC Year 2, FC Year 3, and FC Year 4, respectively.

Following Glower et al. (1998), Knight (2002), and Springer (1996), Motivated is a dummy variable taking the value of one if either the public or agent remarks sections of the property listing include any words or phrases that indicate the seller is motivated to sell and zero otherwise. Some examples include such phrases as ‘seller motivated,’ ‘seller anxious,’ ‘seller says must sell, bring an offer,’ and ‘seller already packed and moved.’ Because whether or not a property is vacant is also an indicator of a seller’s motivation to sell (Knight, 2002; Springer, 1996), Vacant is a dummy variable taking the value of one if the property is vacant and zero otherwise. Studies show that distressed properties, including foreclosures also indicate a high level of seller motivation (Glower et al., 1998; Hardin and Wolverton, 1999; Springer, 1996). Foreclosed is a dummy variable indicating foreclosed status.


Because the purpose of this research is to study the influence of combinations of incentives offered to buyers and selling agents on sales prices and marketing duration outcomes, for robustness, a number of dummy variables provide differing combinations of buyer and agent incentives, and seller motivations (see Table 1). Although included in all models, foreclosed status is not included in the combinations of incentive-related variables used in the robustness check equations because motivations of lenders who are sellers are vastly different from those of sellers who are not lenders. This is because lenders, eager to rid themselves quickly of unwanted properties, are more likely to aggressively price properties, and/or offer highly atypical sales incentives.

Depressed market conditions during the study period strongly suggest the presence of buyer’s market. Relatively low mortgage interest rates enhanced such conditions. Nationally, interest rates on 30-year, fixed rate conventional mortgages rose slightly from 5.97% in March 2008, to a high of 6.48% in August 2008. Thereafter, however, rates generally declined to a low of 3.89% in February 2012. The amount of mortgage discount points borrowers were charged also rose during the study period from an average of 0.5 in March 2008, to 0.8 in February 2012, suggesting a higher risk lending environment as lenders sought to enhance their yields.6 Unemployment rates in the Montgomery, Alabama Metropolitan Statistical Area (MSA) also reflected weakness averaging 5.88%, 9.63%, 8.93%, and 8.70% annually during each of the four years in the study period.7 As further evidence of a weak market, as shown in Table 3, average days on market, monthly inventories of available housing, and months to sell available inventory rose each year during the study period.

Table 3. Monthly Averages of Days on Market, Monthly Inventory, and Months to Sell.

Time Period Days on Market Monthly Inventory Months to Sell Inventory

FC Year 1 104 751 5.82 FC Year 2 117 763 6.44 FC Year 3 126 820 8.41 FC Year 4 137 952 9.85

6 Unemployment rate data obtained from the U.S. Bureau of Labor Statistics available at: http://data.bla.gov/pdq/SurveyOutletServlet. 7 Mortgage interest rates and discount points data obtained from FreddieMac available at: http://www.freddiemac.com/pmms/pmms30.htm.

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Four variables control for market conditions. Interest and Points are the average interest rate, and average total discount points charged to a buyer, respectively, on a 30-year, fixed rate, conventional mortgage in the property-listing month. Unemployment is the unemployment rate for the Montgomery MSA in the property-listing month. Inventory is the quotient of the number of houses for sale divided by the number of sales closed in the property-listing month.

3.3. Methodology Using ordinary least squares regression (OLS), a hedonic pricing model estimates sales price using some of the variables described in Table 1. In keeping with the literature, I log the Sales Price and Square Feet variables.8 I use 2 Bedrooms, FC Year 4, and Winter as the base case for the set of dummy variables used. I use twelve separate models to estimate sales price by adding or excluding incentive-oriented variables using the following form:

Ln(Sales Price) = f { Age, Ln(Square Feet), Discount, 5 Bedrooms, 4 Bedrooms, 3 Bedrooms, Half-Bath, New, Fire, Energy, Brick, Slab, Pool, Foreclosed, Spring, Summer, Fall, FC Year 1, FC Year 2, FC Year 3, Unemployment, Interest, Points, and Inventory }

Using OLS, a marketing duration model estimates days on market using some of the variables described in Table 1. As in the sales price model, I log Sales Price and Square Feet, and 2 Bedrooms, FC Year 4, and Winter are the base case for the set of dummy variables used. I use twelve separate models to estimate marketing duration by adding or excluding incentive-oriented variables using the following form:

Time = f { Ln(Sales Price), Age, Ln(Square Feet), Discount, 5 Bedrooms, 4 Bedrooms, 3 Bedrooms, Half-Bath, New, Fire, Energy, Brick, Slab, Pool, Foreclosed, Spring, Summer, Fall, FC Year 1, FC Year 2, FC Year 3, Unemployment, Interest, Points, and Inventory }

8 For example, see Anglin, Rutherford, and Springer, 2003; Ferreira and Sirmans, 1989; Soyeh, Wiley, and Johnson, K.H., 2014; Springer, 1996; and, Waller, Brastow, and Johnson, 2010.


Section 4. Results and Analysis Tables 4, 5, and 6 present the sales price estimation results. A positive, significant coefficient for a particular incentive variable will suggest that offering such an incentive type will increase sales price, while a negative, significant coefficient will indicate that offering such an incentive type will decrease sales price. While four of the twelve incentive variables have statistically significant impacts on sales price, the results are interestingly different. When motivated sellers offer incentives to buyers and agents, or to agents only, sales prices increase (see Table 5, Equation 6: Buyer & Agent & Motivated, ! = 0.09; and, Table 5, Equation 8: Agent Only & Motivated, ! = 0.06). However, when sellers of vacant homes offer incentives to buyers and/or agents, or to agents only, sales prices decrease (see Table 6, Equation 9: Buyer ~ Agent & Vacant, ! = -0.03; and, Table 6, Equation 12: Agent Only & Vacant, ! = -0.04).

As shown in the sales price estimations presented in Tables 4, 5, and 6, the results suggest that many property characteristics also greatly influence sales price. For example, older homes sell at lower prices, while larger square footage homes with more bedrooms sell for higher prices. Homes that have half-baths, either brick or cement-board exteriors, fireplaces, and energy efficiency features also sell for higher prices, while homes that are not built on slabs sell for lower prices. During the study period, foreclosed homes sold for 16.2% to 20.7% less than non-foreclosed homes. Spring is the best season to list a property for sale, as doing so results in higher sales prices ranging from 2.8% to 3.0% during the time studied. During the first year of the post-crisis period, homes sold for higher prices than they did during the next two years.

Tables 7, 8, and 9 present the marketing duration results. A negative, significant coefficient for a particular incentive variable will suggest that offering such an incentive type will decrease time on market, while a positive, significant coefficient will indicate that offering such an incentive type will increase time on market. While three of the incentive variables have statistically significant impacts on marketing duration, the results suggest that sellers may have to wait longer to sell their homes by offering incentives than by not doing so. When motivated sellers offer incentives to buyers and/or agents, or to buyers only, marketing durations increase (see Table 8, Equation 17: Buyer ~ Agent & Motivated, ! = 17.08; and, Table 8, Equation 19: Buyer Only & Motivated, ! = 25.81). When non-motivated sellers of vacant homes offer incentives to buyers and/or

J. Reid Cummings 17

agents, time on market also increases (see Table 9, Equation 21: Buyer ~ Agent & Vacant, ! = 8.87).

In the marketing duration estimations, several control variables also produce interesting results. As shown on Tables 7, 8, and 9, property age was the most significant property characteristic influencing time on market, as older homes took longer to sell than newer homes. However, newly constructed homes took longer to sell than existing inventory. A possible explanation is that builders who were in various stages of unit construction had no choice but to list their properties for sale after completion in the early stages of the post-crisis period. Moreover, most likely in order to keep their businesses open, while they continued to build and list their homes, they did so at a slower pace. Properties with a swimming pool had increased selling times, while foreclosed properties sold very quickly. Properties listed in the spring sold faster than those listed in either the summer or the fall. Marketing durations were longer during the early years of the post-crisis period than during the later years. Unemployment rates and inventory levels were significant in all models. Vacant properties did not significantly lengthen marketing duration.

Table 4. Estimated Sales Price: Equations 1 - 4.

Independent Variables Eq. 1 Eq. 2 Eq. 3 Eq. 4 Coef. Coef. Coef. Coef. t-Stat. t-Stat. t-Stat. t-Stat.

Buyer ~ Agent -0.01 - - -

-1.10 - - - Buyer & Agent - 0.01 - -

- 0.54 - - Buyer Only - - 0.00 -

- - 0.30 - Agent Only - - - -0.02 - - - -1.45 Vacant -0.06*** -0.06*** -0.06*** -0.06***

-9.50 -9.55 -9.54 -9.49 Motivated 0.00 0.00 0.00 0.00

0.17 0.03 0.02 0.11 Age -0.01*** -0.01*** -0.01*** -0.01***

-42.05 -42.03 -42.02 -41.98 Ln(Square Feet) 0.99*** 0.99*** 0.99*** 0.99***

58.82 58.81 58.81 58.83 Discount -0.64*** -0.64*** -0.64*** -0.64***

-14.22 -14.17 -14.16 -14.22 5 Bedrooms -0.27*** -0.27*** -0.27*** -0.27***

-10.26 -10.25 -10.25 -10.27 4 Bedrooms -0.15*** -0.15*** -0.15*** -0.15***

-5.86 -5.85 -5.84 -5.86 3 Bedrooms -0.10*** -0.10*** -0.10*** -0.10***


-5.75 -5.75 -5.74 -5.76 Half-Bath 0.04*** 0.04*** 0.04*** 0.04***

4.15 4.14 4.14 4.15 New 0.08*** 0.07*** 0.07*** 0.07***

6.62 6.91 5.44 6.95 Fire 0.06*** 0.06*** 0.06*** 0.06***

7.01 7.06 7.07 7.00 Energy 0.03*** 0.03*** 0.03*** 0.03***

4.45 4.44 4.44 4.44 Brick 0.03*** 0.03*** 0.03*** 0.03***

3.71 3.70 3.71 3.74 Slab -0.21*** -0.21*** -0.21*** -0.21***

-17.31 -17.33 -17.33 -17.33 Pool 0.02 0.02 0.02 0.02

1.73 1.70 1.70 1.72 Foreclosed -0.16*** -0.16*** -0.16*** -0.16***

-17.42 -17.41 -17.39 -17.39 Spring 0.03* 0.03* 0.03* 0.03*

2.03 2.04 2.04 2.03 Summer 0.01 0.01 0.02 0.02

1.10 1.10 1.11 1.11 Fall 0.01 0.01 0.01 0.01

0.46 0.43 0.44 0.48 FC Year 1 0.13*** 0.13*** 0.13*** 0.13***

5.91 5.94 5.94 5.90 FC Year 2 0.08*** 0.08*** 0.08*** 0.08***

6.00 6.04 6.03 5.97 FC Year 3 0.08*** 0.08*** 0.08*** 0.07***

7.04 7.06 7.05 7.02 Unemployment -0.05 -0.06 -0.06 -0.04

-0.11 -0.12 -0.11 -0.09 Interest -2.27* -2.27* -2.27* -2.26*

-2.01 -2.00 -2.01 -2.00 Points 0.10 0.10 0.10 0.10

1.47 1.52 1.52 1.50 Inventory 0.00 0.00 0.00 0.00

-1.44 -1.46 -1.46 -1.44 Constant 4.97*** 4.97*** 4.97*** 4.97*** 34.73 34.68 34.66 34.72 R-Square 0.75 0.73 0.73 0.75 Adjusted R-Square 0.75 0.72 0.72 0.75 F-Statistic 498.34*** 498.02*** 498.17*** 498.47*** (Statistical significance = * <.05, ** < .01, *** <.001)



Buyer ~ Agent & Motivated -0.01 - - -

-0.84 - - - Buyer & Agent & Motivated - 0.09 - -

- 2.19 - - Buyer Only & Motivated - - 0.00 -

J. Reid Cummings 19

- - 0.09 - Agent Only & Motivated - - - 0.06 - - - 2.07 Age -0.01*** -0.01*** -0.01*** -0.01***

-42.64 -42.69 -42.64 -42.64 Ln(Square Feet) 0.99*** 0.99*** 0.99*** 0.99***

58.58 58.65 58.58 58.60 Discount -0.69*** -0.69*** -0.69*** -0.69***

-15.42 -15.48 -15.44 -15.51 5 Bedrooms -0.27*** -0.27*** -0.27*** -0.27***

-10.17 -10.23 -10.17 -10.20 4 Bedrooms -0.15*** -0.12*** -0.11*** -0.114***

-5.77 -5.83 -5.79 -5.82 3 Bedrooms -0.10*** -0.11*** -0.10*** -0.10***

-5.58 -5.63 -5.59 -5.62 Half-Bath 0.04*** 0.04*** 0.03*** 0.04***

4.12 4.18 4.14 4.17 New 0.05*** 0.05*** 0.05*** 0.05***

5.10 4.96 5.02 5.05 Fire 0.06*** 0.07*** 0.07*** 0.07***

7.18 7.19 7.21 7.22 Energy 0.03*** 0.03*** 0.03*** 0.03***

4.89 4.95 4.87 4.88 Brick 0.02*** 0.02*** 0.02*** 0.02***

3.59 3.56 3.58 3.54 Slab -0.21*** -0.22*** -0.22*** -0.22***

-17.86 -17.90 -17.86 -17.88 Pool 0.02 0.02 0.02* 0.02

1.99 1.97 1.99 1.95 Foreclosed -0.19*** -0.19*** -0.19*** -0.19***

-20.68 -20.65 -20.69 -20.65 Spring 0.03* 0.03* 0.03* 0.03*

2.17 2.16 2.16 2.13 Summer 0.01 0.01 0.01 0.01

1.07 1.02 1.06 1.03 Fall 0.01 0.01 0.01 0.01

0.53 0.52 0.52 0.49 FC Year 1 0.13*** 0.13*** 0.13*** 0.13***

5.78 5.80 5.77 5.79 FC Year 2 0.08*** 0.08*** 0.08*** 0.08***

5.73 5.79 5.71 5.76 FC Year 3 0.07*** 0.07*** 0.07*** 0.07***

6.89 6.93 6.86 6.90 Unemployment 0.09 0.08 0.09 0.08

0.20 0.18 0.20 0.17 Interest -1.85 -1.85 -1.84 -1.87

-1.62 -1.62 -1.62 -1.64 Points 0.10 0.10 0.09 0.09

1.42 1.43 1.40 1.41 Inventory -0.01 0.00 0.00 0.00

-1.37 -1.38 -1.38 -1.41 Constant 4.88*** 4.88*** 4.88*** 4.89*** 33.84 33.81 33.83 33.87


R-Square 0.75 0.75 0.75 0.75 Adjusted R-Square 0.75 0.75 0.75 0.75 F-Statistic 523.86*** 524.51*** 523.75*** 524.43*** (Statistical significance = * <.05, ** < .01, *** <.001)



Buyer ~ Agent & Vacant -0.03** - - -

-3.32 - - - Buyer & Agent & Vacant - 0.01 - -

- 0.64 - - Buyer Only & Vacant - - -0.01 -

- - -0.57 - Agent Only & Vacant - - - -0.04** - - - -3.11 Age -0.01*** -0.01*** -0.01*** -0.01***

-42.64 -42.64 -42.63 -42.51 Ln(Square Feet) 0.99*** 0.99*** 0.99*** 0.99***

58.67 58.58 58.58 58.61 Discount -0.69*** -0.69*** -0.69*** -0.69***

-15.49 -15.45 -15.44 -15.54 5 Bedrooms -0.27*** -0.27*** -0.27*** -0.27***

-10.21 -10.18 -10.17 -10.22 4 Bedrooms -0.12*** -0.11*** -0.11*** -0.11***

-5.83 -5.80 -5.78 -5.80 3 Bedrooms -0.10*** -0.10*** -0.10*** -0.10***

-5.67 -5.60 -5.60 -5.61 Half-Bath 0.04*** 0.04*** 0.04*** 0.04***

4.13 4.15 4.13 4.15 New 0.07*** 0.05*** 0.06*** 0.05***

5.98 4.96 4.64 5.10 Fire 0.06*** 0.06*** 0.06*** 0.06***

7.07 7.21 7.19 7.11 Energy 0.03*** 0.03*** 0.03*** 0.03***

4.90 4.88 4.87 4.77 Brick 0.02*** 0.02*** 0.02*** 0.03***

3.55 3.58 3.57 3.65 Slab -0.21*** -0.22*** -0.22*** -0.22***

-17.74 -17.87 -17.82 -17.81 Pool 0.02 0.02* 0.02* 0.02*

1.92 1.98 1.98 2.02 Foreclosed -0.19*** -0.19*** -0.19*** -0.19***

-20.56 -20.71 -20.64 -20.49 Spring 0.03* 0.03* 0.03* 0.03*

2.20 2.15 2.17 2.16 Summer 0.02 0.01 0.01 0.01

1.14 1.05 1.07 1.11 Fall 0.01 0.01 0.01 0.01

0.59 0.50 0.53 0.63 FC Year 1 0.13*** 0.13*** 0.13*** 0.13***

5.85 5.77 5.79 5.77

J. Reid Cummings 21

FC Year 2 0.08*** 0.08*** 0.08*** 0.08***

5.83 5.73 5.73 5.71 FC Year 3 0.07*** 0.07*** 0.07*** 0.07***

6.94 6.87 6.88 6.84 Unemployment 0.07 0.09 0.09 0.10

0.15 0.18 0.20 0.22 Interest -1.97 -1.83 -1.87 -1.93

-1.73 -1.60 -1.64 -1.70 Points 0.10 0.09 0.09 0.09

1.41 1.41 1.40 1.40 Inventory 0.00 0.00 0.00 0.00

-1.36 -1.37 -1.39 -1.39 Constant 4.89*** 4.88*** 4.88*** 4.89*** 33.92 33.80 33.84 33.93 R-Square 0.75 0.75 0.75 0.75 Adjusted R-Square 0.75 0.75 0.75 0.75 F-Statistic 525.50*** 523.82*** 523.80*** 525.30*** (Statistical significance = * <.05, ** < .01, *** <.001)

Table 7. Estimated Marketing Duration: Equations 13 - 16.


Buyer ~ Agent 5.47 - - -

1.55 - - - Buyer & Agent - 2.43 - -

- 0.32 - - Buyer Only - - 4.24 -

- - 1.02 - Agent Only - - - 4.93

- - - 1.07 Vacant 1.32 1.41 1.37 1.36

0.45 0.49 0.47 0.47 Motivated 16.90*** 17.54*** 17.09*** 17.44***

3.77 3.92 3.80 3.90 Ln(Sales Price) -3.75 -3.94 -3.95 -3.76

-0.55 -0.58 -0.58 -0.56 Age -0.35** -0.35** -0.35** -0.35**

-3.25 -3.28 -3.26 -3.29 Ln(Square Feet) 15.48 15.66 15.78 15.42

1.54 1.56 1.57 1.53 Discount 636.81*** 635.33*** 635.86*** 636.09***

31.00 30.95 30.97 30.97 5 Bedrooms -7.34 -7.58 -7.60 -7.33

-0.61 -0.63 -0.64 -0.61 4 Bedrooms 6.35 6.12 6.17 6.25

0.72 0.70 0.70 0.71 3 Bedrooms 7.45 7.28 7.29 7.41

0.93 0.91 0.91 0.92 Half-Bath 4.53 4.61 4.62 4.55

1.13 1.15 1.15 1.13 New 21.72*** 25.72*** 22.32*** 25.97***

4.01 5.43 3.82 5.50


Fire -5.93 -6.21 -6.14 -6.04

-1.47 -1.55 -1.53 -1.50 Energy 2.93 2.97 2.93 2.97

0.99 1.00 0.99 1.00 Brick 0.29 0.27 0.32 0.21

0.09 0.09 0.11 0.07 Slab -1.10 -1.00 -1.11 -0.98

-0.20 -0.18 -0.20 -0.18 Pool 9.70* 9.81* 9.74* 9.79*

2.09 2.12 2.10 2.11 Foreclosed -43.50*** -43.70*** -43.60*** -43.67***

-10.06 -10.10 -10.09 -10.10 Spring 9.89 9.79 9.83 9.83

1.61 1.60 1.61 1.60 Summer 18.37** 18.27** 18.33** 18.26**

3.20 3.19 3.20 3.19 Fall 10.61* 10.76* 10.74* 10.64*

2.04 2.06 2.06 2.04 FC Year 1 57.88*** 57.63*** 57.67*** 57.83***

5.70 5.68 5.68 5.70 FC Year 2 35.73*** 35.62*** 35.61*** 35.78***

6.02 6.00 6.00 6.03 FC Year 3 38.04*** 38.06*** 38.05*** 38.09***

7.98 7.98 7.98 7.99 Unemployment 439.83* 438.80* 439.95* 437.18*

2.08 2.08 2.08 2.07 Interest -167.09 -165.54 -162.82 -169.14

-0.33 -0.33 -0.32 -0.33 Points -27.26 -28.75 -27.62 -28.62

-0.92 -0.97 -0.93 -0.96 Inventory 2.14** 2.16** 2.15** 2.15**

2.76 2.79 2.78 2.77 Constant -56.08 -52.58 -54.93 -53.32 -0.77 -0.73 -0.76 -0.74 R-Square 0.24 0.24 0.24 0.24 Adjusted R-Square 0.23 0.23 0.23 0.23 F-Statistic 48.02*** 47.91*** 47.96*** 47.96*** (Statistical significance = * <.05, ** < .01, *** <.001)



Buyer ~ Agent & Motivated 17.08 - - -

3.10 - - - Buyer & Agent & Motivated - 10.77 - -

- 0.60 - - Buyer Only & Motivated - - 25.81*** -

- - 3.59 - Agent Only & Motivated - - - 13.17 - - - 1.09 Ln(Sales Price) -4.21 -4.60 -4.50 -4.70

-0.63 -0.69 -0.67 -0.70

J. Reid Cummings 23

Age -0.37** -0.37** -0.37** -0.37**

-3.42 -3.45 -3.43 -3.44 Ln(Square Feet) 16.16 16.40 16.60 16.36

1.61 1.63 1.66 1.63 Discount 641.43*** 642.88*** 640.66*** 642.31***

31.48 31.52 31.44 31.48 5 Bedrooms -7.17 -7.46 -8.27 -7.46

-0.60 -0.62 -0.69 -0.62 4 Bedrooms 6.46 6.87 5.99 6.83

0.74 0.78 0.68 0.78 3 Bedrooms 7.15 7.40 6.83 7.36

0.89 0.92 0.85 0.91 Half-Bath 4.59 4.38 4.71 4.40

1.14 1.09 1.17 1.09 New 24.28*** 25.62*** 24.37*** 25.73***

5.26 5.56 5.29 5.59 Fire -6.30 -6.62 -6.29 -6.58

-1.57 -1.64 -1.57 -1.63 Energy 2.97 3.34 3.32 3.29

1.00 1.13 1.12 1.11 Brick 0.27 0.33 0.35 0.27

0.09 0.11 0.11 0.09 Slab -1.06 -1.23 -1.26 -1.24

-0.19 -0.22 -0.23 -0.22 Pool 9.67* 9.80* 9.75* 9.73*

2.08 2.11 2.10 2.09 Foreclosed -44.22*** -44.01*** -43.67*** -43.97***

-10.52 -10.46 -10.39 -10.45 Spring 9.35 9.62 9.47 9.53

1.53 1.57 1.55 1.55 Summer 18.06** 18.16** 18.04** 18.13**

3.15 3.16 3.15 3.16 Fall 10.60* 10.86* 10.85* 10.79*

2.03 2.08 2.08 2.07 FC Year 1 57.51*** 57.82*** 57.62*** 57.80***

5.67 5.69 5.68 5.69 FC Year 2 35.72*** 36.08*** 35.55*** 36.10***

6.02 6.07 5.99 6.08 FC Year 3 38.23*** 38.81*** 38.05*** 38.81***

8.02 8.13 7.97 8.14 Unemployment 432.58* 430.65* 446.63* 428.57*

2.05 2.04 2.12 2.03 Interest -129.36 -145.03 -127.60 -151.32

-0.26 -0.29 -0.25 -0.30 Points -28.23 -26.26 -28.75 -26.38

-0.95 -0.88 -0.97 -0.89 Inventory 2.13** 2.15** 2.14** 2.14**

2.76 2.77 2.77 2.76 Constant -52.54 -50.04 -52.97 -47.89 -0.73 -0.70 -0.74 -0.67 R-Square 0.23 0.23 0.23 0.23 Adjusted R-Square 0.23 0.23 0.23 0.23 F-Statistic 51.30*** 50.84*** 51.46*** 50.88***


(Statistical significance = * <.05, ** < .01, *** <.001)



Buyer ~ Agent & Vacant 8.87* - - -

2.29 Buyer & Agent & Vacant - 3.27 - -

0.36 Buyer Only & Vacant - - 7.39 -

1.72 Agent Only & Vacant - - - 8.10 1.40 Ln(Sales Price) -3.70 -4.49 -4.37 -4.03

-0.55 -0.67 -0.65 -0.60 Age -0.36** -0.37** -0.37** -0.37**

-3.40 -3.44 -3.44 -3.45 Ln(Square Feet) 15.36 16.28 16.20 15.88

1.53 1.62 1.61 1.58 Discount 643.88*** 643.05*** 642.73*** 644.03***

31.59 31.53 31.53 31.57 5 Bedrooms -6.81 -7.28 -7.36 -6.96

-0.57 -0.61 -0.62 -0.58 4 Bedrooms 7.29 6.93 6.90 7.06

0.83 0.79 0.79 0.80 3 Bedrooms 7.92 7.44 7.53 7.57

0.99 0.92 0.94 0.94 Half-Bath 4.33 4.36 4.45 4.30

1.08 1.08 1.11 1.07 New 20.72*** 25.55*** 21.08*** 25.56***

4.07 5.53 3.96 5.55 Fire -6.28 -6.60 -6.45 -6.46

-1.56 -1.64 -1.60 -1.60 Energy 3.19 3.28 3.21 3.39

1.08 1.11 1.08 1.14 Brick 0.41 0.34 0.47 0.25

0.14 0.11 0.16 0.08 Slab -1.45 -1.19 -1.54 -1.21

-0.26 -0.21 -0.28 -0.22 Pool 10.01* 9.79* 9.92* 9.74*

2.16 2.11 2.14 2.10 Foreclosed -44.30*** -44.11*** -44.36*** -44.30***

-10.53 -10.47 -10.54 -10.52 Spring 9.41 9.60 9.42 9.58

1.53 1.57 1.54 1.56 Summer 17.88** 18.18** 17.93** 18.08**

3.11 3.17 3.12 3.15 Fall 10.58* 10.81* 10.64* 10.59*

2.03 2.07 2.04 2.03 FC Year 1 57.12*** 57.69*** 56.96*** 57.69***

5.62 5.68 5.60 5.68 FC Year 2 35.42*** 35.99*** 35.59*** 35.95***

J. Reid Cummings 25

5.96 6.06 5.99 6.06 FC Year 3 38.44*** 38.73*** 38.46*** 38.75***

8.06 8.12 8.06 8.13 Unemployment 438.09* 429.94* 430.66* 429.74*

2.07 2.03 2.04 2.03 Interest -105.18 -140.05 -104.16 -125.62

-0.21 -0.28 -0.21 -0.25 Points -26.77 -26.38 -26.27 -26.46

-0.90 -0.88 -0.88 -0.89 Inventory 2.14** 2.15** 2.16** 2.15**

2.76 2.78 2.79 2.78 Constant -56.07 -50.54 -53.27 -54.27 -0.78 -0.70 -0.74 -0.75 R-Square 0.23 0.23 0.23 0.23 Adjusted R-Square 0.23 0.23 0.23 0.23 F-Statistic 51.08*** 50.82*** 50.97*** 50.92*** (Statistical significance = * <.05, ** < .01, *** <.001)

Section 5. Concluding Remarks This study examines empirically the use of seller-paid incentives in the sale of residential real estate. It is the first study to examine the use of various incentives offered by the seller to the buyer in combination with various incentives offered by the seller to the selling agent in order to induce the sale of the seller’s property. The impacts examined are the transaction outcomes of sales price and marketing duration. The data include single-family residential properties sold in the Montgomery, Alabama MSA during the distressed real estate market conditions following the 2008-2009 financial crisis.

The results show incentives offered to buyers can be effective in leading to the desired outcomes of higher prices. However, results also show that under certain circumstances, incentives offered to agents can be effective as well. Incentives offered by motivated sellers to buyers and agents, and agents only, increase sales prices. Incentives offered by sellers of vacant properties to buyers or agents, and agents only, also lead to higher sales prices. However, contrary to the results of Soyeh, Wiley, and Johnson (2014), in this study, I did not find that using incentives resulted in decreased marketing duration.

This study yields interesting results and partial confirmation of previous research, providing value to both academics and practitioners. Yet this study also opens the door to future research that will provide even greater value to the practitioner. Consider that even though I examined twelve different incentive combinations,


because of initial data limitations, I was unable to examine the effects of specific types of incentives such as cash versus non-cash incentives. Deeper still, I was unable to investigate how a particular type of cash or non-cash incentive, offered either individually to a buyer or an agent, or to both, might impact the sales price or marketing duration.

For example, for the purposes of this study, if a seller indicated a willingness to pay for a home warranty, a survey, and/or closing costs, the estimations simply included the fact that the seller offered incentives. In a current project, using a significantly larger dataset derived from multiple MLS systems, I am working to disaggregate the data to enable identification of each of the individual incentive categories (cash or non-cash), buyer incentive types (warranty, closing costs, decorating allowances, prizes, gifts, etc.), and agent incentive types (higher commission split, selling agent bonus, prizes, gifts, etc.). I expect to be able to predict which particular incentive(s) or incentive combination(s) produce(s) the maximum utility for the seller. Arguably, the end goal of sellers and their agents is ultimately the same: achieve the highest possible price in the shortest possible time. Increased, more precise knowledge of how the use of sales incentives can work to achieve such goals will not only be of interest to academics, but will also provide significant value to sellers and practitioners alike.

J. Reid Cummings 27

References

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Asabere, P.K., Huffman, F.E. (1997). Discount Point Concessions and the Value of Homes with Conventional versus Nonconventional Mortgage Financing, Journal of Real Estate Finance and Economics, 15(3) 261–270.

Baker, D. (2008). The housing bubble and the financial crisis. Real-World Economics Review, 46(5) 73-81.

Benjamin, J.D., Chinloy, P. (2000). Pricing, exposure, and residential listing strategies. Journal of Real Estate Research, 20(1-2) 61-74.

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residential real estate realities after the financial ... · in the years since the great recession...

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