معضل صاحبخانه: مهار در معاملات دارایی واقعی مسکونی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|6987||2013||17 صفحه PDF||سفارش دهید||10212 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Economic Behavior & Organization, Volume 89, May 2013, Pages 76–92
We examine whether, and how, listing strategies impact sale prices in residential home sales. Literatures in housing economics, negotiations, and auctions offer diverse predictions around this question. On the one hand, housing studies typically treat home prices as an objective function of property and neighborhood characteristics. Yet, the large and robust literature on anchoring effects (Tversky and Kahneman, 1974) suggests a positive relationship between listing prices and sale prices. Finally, evidence from the auctions literature suggests the opposite pattern through herding behaviors. We analyzed more than 14,000 transactions, taking into account observable property heterogeneity, geographical location and timing of the sales. We find that higher starting prices are indeed associated with higher selling prices, consistent with anchoring. For the average home in our sample, over-pricing between 10 and 20% leads to an increase in the sale price of $117–$163. This effect is particularly strong in areas with higher rates of mortgage foreclosure or serious delinquency. Additional analyses show that our results are unlikely to be driven by seller motivations or unobserved home qualities. We contrast our findings with recommendations and private beliefs of real estate agents, who provide services and advice for about 90% of home sales in the US.
For the vast majority of homeowners, the home is the dominant asset in their portfolio. For younger home-owning households, the house value can be several times the value of the household's net wealth (Flavin and Yamashita, 2002). Thus the sale of a home is likely to be the most significant financial transaction of the owners’ lifetimes, and one that a typical home-owning household faces repeatedly: over a two-year period, 12% home-owning households in the US move (Ferreira et al., 2008, based on 1985–2005 AHS data). Among the many stressful decisions that go into a home sale, perhaps the most agonizing one involves the setting of the initial “listing price.” Yet, despite the importance and frequency of home sales, the research literature is yet to offer a clear recommendation as to the basic strategy sellers should pursue. In the present research we explore this issue from the vantage points of three different literatures, analyze a large and diverse data set of market transactions, and contrast our findings with realtors’ recommendations as well as their private beliefs. Research on anchoring and insufficient adjustment (Tversky and Kahneman, 1974) has repeatedly demonstrated that exposure to even irrelevant numbers makes individuals’ subsequent quantitative judgments assimilate to the “anchor.” Anchoring affects the price that consumers are willing to pay for goods and experiences (Ariely et al., 2003, Green et al., 1998, Northcraft and Neale, 1987 and Simonson and Drolet, 2004) and the outcomes of distributive negotiations (Galinsky et al., 2002, Galinsky et al., 2005 and Galinsky and Mussweiler, 2001). The available evidence for anchoring effects suggests that home sellers would benefit from setting higher listing prices. This conclusion, however, is in direct contrast with most of the economic literature that considers housing prices to be rational, and ultimately determined by characteristics such as location and amenities (Sheppard, 1999). From this perspective, market forces are expected to correct any strategic pricing behaviors. Laboratory results demonstrating a relationship between opening prices and selling prices are generally dismissed as the product of experimental demand in absence of real market conditions. Conversely, demonstrations of anchoring-like effects using market data are often critiqued for failing to sufficiently control for potential confounds. A third literature, one dealing with auction behavior (Gneezy, 2005 and Gneezy and Smorodinsky, 2006) offers yet another set of predictions. A typical home sale begins with an auction-like process, where one or more buyers might submit an offer in response to a listing price. Recent findings show that auctions that open with low asking prices generate a greater number of bids and ultimately finish with higher closing prices (Ku et al., 2005, Ku et al., 2006 and Simonsohn and Ariely, 2007). This pattern has been explained through “herding” behavior (Banerjee, 1992) whereby bids by earlier aspiring buyers signal that a particular item is competitively priced and lead others to enter the bidding. Indeed, an analysis of real estate-related web content reveals that professional consensus favors pricing a home low, in the hopes of starting a “bidding war.” Work by Janiszewski and Uy (2008) recently examined the effect of listing prices in the residential housing market. These authors however, were interested in the effect of price precision, and thus chose to eliminate all transactions with multiple offers from their data set, leaving no room for testing herding behavior as an alternative explanation. Thus the question of whether a seller ought to price a good relatively high or relatively low in the context of a consequential information-rich market transaction remains very much unanswered. In the current paper, we examine the question of initial listing prices in the real estate market using two methods. First, we gather professional advice available to homeowners with access to the internet. We analyzed the content and the tone of the published articles to find out what strategy real estate agents recommend. We further investigate private beliefs of real estate agents by soliciting their recommendations regarding specific, randomly chosen properties in their general geographical area of practice (Study 1). We then compare these recommendations and beliefs to findings based on data concerning all single-family home sales in Delaware, New Jersey and Pennsylvania listed through the Multiple Listing Service (MLS) between January 2005 and April 2009 (Study 2).1 While the online recommendations of real estate agents seem to favor underpricing, alluding to a potential herding effect, our market data do not provide any support for this strategy. In fact, underpriced homes systematically fared less well in the data we examined, even in hot markets with frequent transactions. On the other hand, our market data show evidence of an anchoring effect, even after controlling for “fishing” behaviors whereby home sellers wait for a longer period of time in order to receive a higher offer (Bokhari and Geltner, 2011). Private beliefs of agents seemed to be in line with our market findings, and not their public recommendations. When surveyed anonymously, real estate agents predicted that higher listing prices would lead to higher sale prices, even after we account for individual differences, property fixed effects, and listing time expectations. We go beyond the prior literature in several ways. First we demonstrate the effect of listing strategies on final prices using a large data set of real market data, in the context of a high-stakes, information-rich transaction. Secondly, we utilize several novel empirical approaches to rule out alternative explanations that have plagued such attempts in the past. Finally, by comparing market data to recommendations of professional realtors we demonstrate a likely gap in lay knowledge regarding the most consequential financial transaction of most consumers’ lifetimes.
نتیجه گیری انگلیسی
A home sale is the most significant financial transaction undertaken by the average home-owning household. Despite the high-stakes and deliberative nature of this transaction, prior research has not offered a conclusive answer regarding the optimal strategy that sellers should pursue. Our work shows that although most professional advice recommends under-pricing, over-pricing one's home relative to any of several benchmarks used in our analyses results in a higher sale price, controlling for how long one waits to sell. These results emerge when we include a variety of controls for unobserved home quality and time-on-market. Because we use data from a high-stakes, information-rich context, it cannot be argued that the observed effect is merely the result of individuals’ failure to sufficiently consider their actions, lack of available decision aids, or absence of other alternatives. The effect we demonstrate is robust and significant. Our research goes beyond prior attempts to demonstrate pricing effects in the real-estate domain. First, we use a more comprehensive data set that allows us to experiment with a wide array of reference points and to more fully alleviate concerns about unobserved variables, including home qualities, marketing strategies promoted by the listing offices, time on market, as well as zip code, school district, listing office, year and month fixed effects. Secondly, we explore the possibility that over- and under-pricing might vary by the local market conditions. We use both the zip code-level transaction volume changes and information on listing price heterogeneity to provide a more rigorous test of both the herding and anchoring hypotheses. Contrary to commonly cited anecdotes concerning market excitement and bidding wars, our results point to little or no herding effect in a hot market. Our findings prompt the question as to why we did not observe a herding effect, given the frequency of references to bidding wars in lay discourse. The literature on auction behavior makes it clear that herding requires a thick market with multiple buyers acting concurrently. It may be the case that this is simply not possible in the case of residential real-estate where buyers are too few and too dispersed to influence each other. Furthermore, the only prior evidence of herding in real-estate contexts comes from anecdotal accounts of bidding wars in extremely “hot” markets. Such accounts are suspect for at least three reasons. First, realtors labor under an agency problem whereby they are incentivized to set prices lower in order to increase the probability of a home sale (Levitt and Syverson, 2008). Thus relating stories about bidding wars is very much in line with their self-interest. Secondly, the availability heuristic (Tversky and Kahneman, 1974) might lead “bidding war” stories to appear more frequent than they really are because they are more memorable than more prosaic home-selling experiences. Finally, due to the nature of anecdotal evidence, even in the case of a bidding war, we can never know what the sale price would have been had the listing price been higher. While our findings directly contradict the advice most real-estate professionals offer to their clients, they seem to be in line with the private beliefs of realtors. Participants in Study 1 recommended under-pricing in the majority of cases, while at the same time expecting this strategy to lead to lower sale prices. The flavor of the warnings against over-pricing common in the online content we collected is well-captured by an article from About.com with the attention-grabbing headline “The Worst Home Selling Mistake.” The article relates the history of a specific house that according to the author never sold due to agent inexperience and seller greed. It is now “…stale, dated, a market-worn home that was over-priced for too long.” Our findings based on market data, however, should give serious pause to any seller who is tempted to under-price a property in the hopes of generating a “bidding war” per the advice of their realtor.