A Model of Time‐on‐Market and Real Estate Price Under Sequential Search with Recall

This article develops a model and provides a closed‐form formula to uncover the theoretical relationship between real estate price and time on market (TOM). Our model shows a nonlinear positive price‐TOM relationship, and it identifies three economic factors that affect the impact of TOM on sale price. We demonstrate that conventional metrics for real estate return and risk, which are borrowed in a naïve fashion from finance theory, do not account for marketing period risk and tend to overestimate real estate returns and underestimate real estate risks. Our model provides a simple way to correct such bias. This theory helps to explain the apparent “risk‐premium puzzle” in real estate.     

Listing Price, Time on Market, and Ultimate Selling Price: Causes and Effects of Listing Price Changes

Information about price changes during a home's marketing period is typically missing from data used to investigate the listing price, selling price, and selling time relationship. This paper incorporates price revision information into the study of this relationship. Using a maximum-likelihood probit model, we examine the determinants of list price changes and find evidence consistent with the theory of pricing behavior under demand uncertainty. Homes most likely to undergo list price changes are those with high initial markups and vacant homes, while homes with unusual features are the least likely to experience a price revision. We also explore the impact of missing price change information on estimating a representative model of house price and market time. Our results suggest that mispricing the home in the initial listing is costly to the seller in both time and money. Homes with large percentage changes in list price take longer to sell and ultimately sell at lower prices.     

Real Estate Returns and Risk with Heterogeneous Investors

This article develops a theoretical framework and formulates a unified risk metric that integrates both real estate price risk and uncertainty of time on market (TOM). We demonstrate that real estate sellers with different degrees of financial distress face not only different marketing period risks, but also receive different return distributions upon successful sales. The major findings of this article can be summarized as follows. First, we show that real estate return and risk, which account for both price and TOM risk, are investor specific, varying over investors with different financial circumstances and holding periods. Second, the traditional valuation of real estate return and risk, which is based solely on the return distribution of a successful sale without considering the uncertainty of TOM and the investor's financial circumstances, underestimates real estate risk and exaggerates real estate return. Third, our empirical applications in both residential and commercial real estate markets show that the Sharpe ratio estimated by the traditional approach is seriously overstated—to the largest extent for investors with high financial distress. In addition, we find that, given the typical 5‐ to 7‐year holding period for real estate, the Sharpe ratios estimated by integrating both price and TOM risk are much in line with the performance of financial assets. These findings can help to explain the apparent “risk‐premium puzzle” in real estate.     

The Gender Gap in Real Estate Sales: Negotiation Skill or Agent Selection?

This study examines differences in net selling price for residential real estate across male and female agents. A sample of 2,020 home sales transactions from Fulton County, Georgia, are analyzed in a two‐stage least squares, geospatial autoregressive corrected, semi‐log hedonic model to test for gender and gender selection effects. Although agent gender seems to play a role in naïve models, its role becomes inconclusive as variables controlling for possible price and time on market expectations of the buyers and sellers are introduced to the models. Clear differences in real estate sales prices, time on market and agent incomes across genders are unlikely due to differences in negotiation performance between genders or the mix of genders in a two‐agent negotiation. The evidence suggests an interesting alternative to agent performance: that buyers and sellers with different reservation price and time on market expectations, such as those selling foreclosure homes, tend to select agents along gender lines.     

Time on the Market and Selling Price

This study is primarily an analysis of tradeoff between selling time and price, both on a nominal and real basis. Sellers are seen as desiring to maximize their discounted real selling price and trading off the nominal selling price with expected selling time. The time a property remains on the market is important, not only because of its reflection on price, but also because of its possible reflection on the issue of submarket equilibrium—an assumption in most urban price studies. The empirical results of this study shed light on how similar studies can easily misinterpret the implications of time on the market on price and how further work may be improved.     

The Strategic Role of Listing Price in Marketing Real Estate: Theory and Evidence

The seller of a real estate property and his broker have two primary goals: to sell the properly for as high a price as possible and as quickly as possible. While these are separate objectives, they are closely related through the listing price of the seller. The listing price affects how long it takes to find a buyer (i.e., Time On the Market = TOM), and TOM influences the price that results from the bargaining between the seller and the buyer. This leaves the seller and his agent with an important question: What is the optimal price to be asked for the property? The objective of this research is to provide a theoretical and empirical analysis of the impact of listing price on TOM and the transaction price.     

Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the United States and the Netherlands

This article assesses the predictive power of variables that measure market tightness, such as seller's bargaining power and sale probabilities, on future home prices. Theoretical insights from a stylized search‐and‐matching model illustrate that such indicators can be associated with subsequent home price appreciation. The empirical analysis employs listings data on residential units offered for sale through a real estate broker in the Netherlands and for certain U.S. regions. Individual records are used to construct quarterly home price indices, an index that measures seller's bargaining power and (quality‐adjusted) home sale probabilities. Using conventional time‐series models we show that current sale probabilities and bargaining power can significantly reduce home price appreciation forecast errors and help to predict turning points in local area housing markets. The measures and approaches in this article help to demonstrate ways in which researchers and practitioners can leverage listings data to gain knowledge about the current and future state of the housing market.     

Is Selection Bias Inherent in Housing Transactions? An Equilibrium Approach

We develop an equilibrium model for residential housing transactions in an economy with houses that differ in their quality and households that differ in their planned holding horizon. We show that, in equilibrium, a clientele effect persists, with long‐horizon buyers overwhelmingly choosing higher quality properties and short‐horizon buyers settling for lower quality properties. This clientele effect creates a sample selection bias: the properties that are on the market are predominantly of lower quality. Since these are the preferred choice of short‐horizon buyers, they demonstrate a faster turnover. Both the clientele effect and the selection bias are more pronounced with an increase in the variance of house quality and in the variance of the planned holding horizon. Our theoretical model supports empirical evidence on the existence of such bias in home price indices and explains it by the differences in ex ante holding horizons.     

Search and Liquidity in Single-Family Housing

A two-stage least squares model of housing prices is estimated with data collected from 3358 single-family home transactions. The results provide evidence for an optimal marketing period and indicate that a liquidity premium is priced in single-family home sales. Consistent with the hypothesis derived from economic search models, the model shows higher selling prices for houses having longer expected marketing periods. The model also shows a price premium for houses that sell faster than expectations. This effect supports the concept that liquidity is a value-enhancing characteristic.     

To Sell or Not to Sell: Measuring the Heat of the Housing Market

Combining list‐price, sale‐price and time‐on‐the‐market data, we estimate an index that summarizes housing market conditions and that has a direct economic interpretation. The index measures seller's bargaining power in a structural search model of home seller behavior. Structural estimation uncovers an analytical relationship between reduced form coefficients of hedonic and marketing‐time equations and structural parameters. Thus, the index can be estimated using individual‐level or aggregate data. Using housing transactions data from the Washington, D.C., area, we show that index trends coincide with the up and downturns in home appreciation rates and with popular perceptions about the “heat” of the market.     

Price Dispersion Over the Business Cycle: Evidence from the Airline Industry

This study provides empirical evidence documenting how price dispersion moves with the business cycle in the airline industry. Performing a fixed‐effects panel analysis on seventeen years of data covering two business cycles, we find that price dispersion is highly pro‐cyclical. This effect is especially pronounced for legacy carriers relative to low‐cost carriers. We show that our empirical result is consistent with firms' implementing second‐degree price‐discrimination tactics.     

Asymmetric Price Effects of Competition

When price dispersion is prevalent, a relevant question is what happens to the whole distribution of equilibrium prices when the number of firms changes. Using data from the gasoline market in the Netherlands, we find, first, that markets with N competitors have price distributions that first‐order stochastically dominate the price distributions in markets with N+1 firms. Second, the effect of competition is stronger for the medium to upper percentiles of the price distribution. Finally, consumer gains from competition are larger for relatively well‐informed consumers. To account for these empirical patterns, we extend Varian's [1980] model by allowing for richer heterogeneity in consumer price information.     

Selling Time and Selling Price: The Influence of Seller Motivation

We consider the role that seller motivation plays in determining selling time, list price and sale price. A new survey of home sellers suggests that sellers are heterogeneous in their motivation to sell. Our findings are that a seller who, at the time of listing, has a planned date to move sells more quickly than one who does not. Also, the shorter the planned time until a move at the time of listing, the shorter the actual duration of marketing time. We find that seller motivation affects sale price, but not the list-price markup. Our results suggest that theoretical models of the housing search process should be recast to allow for heterogeneous sellers.     

Flooding and Liquidity on the Bayou: The Capitalization of Flood Risk into House Value and Ease‐of‐Sale

The existing literature focuses on how perceived flood risk affects house value. Search theory, however, implies that flood risks will be capitalized into both house price and liquidity. This article draws on search theory to develop an empirical approach for estimating flood risk capitalization into both price and selling time. The results show the mix of price and liquidity capitalization varies by level of flood risk as well as across housing market phases. Regardless of the specific capitalization pattern, the results illustrate that focusing solely on price without allowing for concomitant liquidity capitalization can yield estimates that understate the full impact of flood risk on house transactions.     

Optimal Selling Mechanism,Auction Discounts and Time on Market

This article examines the optimal selling mechanism problem in real estate market using mean‐variance analysis and downside risk analysis. When sellers can choose between accepting the first offer above a reservation price or auctions (waiting an optimal and fixed time), sellers having higher risk aversion choose auctions and wait a fixed time while sellers having lower risk aversion choose an optimal reservation price and wait a random time. Positive auction discounts are compensated by reduced risks, and there exists a connection between liquidity risk and conditional auction discount. More (Fewer) sellers will choose to sell their houses through auctions in a hot (cold) market or when holding cost increases (decreases). When sellers choose auctions, sellers having higher risk aversion who have lower holding cost wait longer and obtain higher sale price. Loss‐averse sellers unanimously choose the mechanism of setting an optimal reservation price.     

Does Regulation Trade Off Quality against Inequality? The Case of German Architects and Construction Engineers

We exploit an exogenous price increase of 10 per cent for architectural services to answer the question how price regulation affects income inequality and service quality. Using individual‐level data from the German microcensus for the years 2006–2012, we find a significant reform effect of 8 per cent on personal net income for self‐employed architects and construction engineers. This group moved from the second lowest to the highest quintile of the net income distribution. This increase in inequality is associated with a deterioration of service quality. The reform reduced average scores of a peer ranking for architects by 18 per cent.     

The Effect of Sales Force Adoption on New Product Selling Performance

Although several studies have suggested that the sales force is a major contributing factor to new product success, few studies have focused on new product adoption by the sales force, particularly with respect to its relationship with selling performance. The present article presents empirical evidence on the impact of sales force adoption on selling performance. We defined sales force adoption as the combination of the degree to which salespeople accept and internalize the goals of the new product (i.e., commitment) and the extent to which they work hard to achieve those goals (i.e., effort). It was hypothesized that the impact of sales force adoption on selling performance will be contingent on supervisory factors (sales controls, internal marketing of the new product, training, trust, and supervisor's field attention), and market volatility. Therefore, this article also provides evidence of the conditions under which sales force adoption of a new product is more or less effective in engendering successful selling performance. The hypothesized relationships were tested with data provided by 97 high technology firms from The Netherlands. The results show that sales force adoption is positively related to selling performance. This finding suggests that salespeople who simultaneously exhibit commitment and effort will achieve higher levels of new product selling performance. Outcome based control, internal marketing and market volatility are also positively related to new product selling performance. The effect of sales force adoption on selling performance is stronger where outcome based control is used and where the firm provides information on the background of the new product to salespeople through internal marketing. Training and field attention weaken the adoption‐performance linkage. These findings may indicate that salespeople in The Netherlands interpret training as “micromanaging” and field attention as “looking over their shoulder.” We conclude with implications of our study for research and managerial practice.     

Competition and Price Discrimination: Evidence from the Parking Garage Industry

We study the relationship between competition and price discrimination through an empirical examination of hourly price schedules in the parking garage industry. We find that the degree of price schedule curvature decreases with competition, implying a greater proportionate drop in low‐end prices than in high‐end prices when competition intensifies. Our findings suggest that competition constrains a firm's capacity to exercise price discrimination, confirming the classic textbook theory. We also offer possible explanations for our findings, including a search cost explanation, for which we find some support in the data.     

Do Low‐Price Guarantees Guarantee Low Prices? Evidence from Competition between Amazon and Big‐Box Stores

It has long been understood in theory that price‐match guarantees can be anticompetitive, but to date, scant empirical evidence is available outside of some narrow markets. This paper broadens the scope of empirical analysis, studying a wide range of products sold on a national online market. Using an algorithm that extracts data from charts, I obtain a novel source of data from online price trackers. I examine prices of goods sold on Amazon before and after two big‐box stores (Target and Best Buy) announced a guarantee to match Amazon's prices. Employing both difference‐in‐difference and regression‐discontinuity approaches, I robustly estimate a positive causal effect of six percentage points. The effect was heterogeneous, with larger price increases for initially lower‐priced items. My results support anticompetitive theories which predict price increases for Amazon, a firm that did not adopt the guarantee, and are consistent with plausible mechanisms for the heterogeneous impact.     

Estimating Bargaining Effects in Hedonic Models: Evidence from the Housing Market

Bargaining is common in markets for heterogeneous goods and differences in bargaining power between buyer and seller affect the negotiated transaction price. Previous research has found systematic evidence in the housing markets that weak buyers pay higher prices and weak sellers receive lower prices for their homes. Earlier work has modeled the bargaining effect as a parallel shift in the hedonic function, implicitly assuming that attribute shadow prices were unaffected by the bargaining process. In this paper, we use a sample of home sales where the seller's bargaining power is weakened by the fact that the home is vacant at the time of sale to test whether the effect of bargaining is best captured by a shift in the hedonic constant or whether the attribute shadow prices vary as well. The question is significant for property valuation where estimation of the marginal value of an attribute is commonly used to adjust comparable sales data. We find strong confirmation that bargaining power influences the negotiated price. We also find evidence that bargaining power alters attribute prices, although we do not find a consistent pattern across markets.