Time On The Market Research Articles

The effect of the COVID-19 pandemic on TOM in the housing market

Purpose The COVID-19 pandemic, a sudden and disruptive external shock to the USA and global economy, profoundly affected various operations. Thus, it becomes imperative to investigate the repercussions of this pandemic on the US housing market. This study investigates the impact of the COVID-19 pandemic on a crucial facet of the real estate market: the Time on the Market (TOM). Therefore, this study aims to ascertain the net effect of this unprecedented event after controlling for economic influences and real estate market variations. Design/methodology/approach Monthly time series data were collected for the period of January 2010 through December 2022 for statistical analysis. Given the temporal nature of the data, we conducted the Durbin–Watson test on the OLS residuals to ascertain the presence of autocorrelation. Subsequently, we used the generalized regression model to mitigate any identified issues of autocorrelation. However, it is important to note that the response variable derived from count data (specifically, the median number of months), which may not conform to the normality assumption associated with standard regression models. To better accommodate this, we opted to use Poisson regression as an alternative approach. Additionally, recognizing the possibility of overdispersion in the count data, we also explored the application of the negative binomial model as a means to address this concern, if present. Findings This study’s findings offer an insightful perspective on the housing market’s resilience in the face of COVID-19 external shock, aligning with previous research outcomes. Although TOM showed a decrease of around 10 days with standard regression and 27% with Poisson regression during the COVID-19 pandemic, it is noteworthy that this reduction lacked statistical significance in both models. As such, the impact of COVID-19 on TOM, and consequently on the housing market, appears less dramatic than initially anticipated. Originality/value This research deepens our understanding of the complex lead–lag relationships between key factors, ultimately facilitating an early indication of housing price movements. It extends the existing literature by scrutinizing the impact of the COVID-19 pandemic on the TOM. From a pragmatic viewpoint, this research carries valuable implications for real estate professionals and policymakers. It equips them with the tools to assess the prevailing conditions of the real estate market and to prepare for potential shifts in market dynamics. Specifically, both investors and policymakers are urged to remain vigilant in monitoring changes in the inventory of houses for sale. This vigilant approach can serve as an early warning system for upcoming market changes, helping stakeholders make well-informed decisions.

Efficiency of distressed property sales in Lagos city, Nigeria

With recourse to data obtained from the online multiple listing services (MLS) of the Nigerian Property Centre, this study evaluated the efficiency of sale of distressed properties in Lagos city using a 6-month interval of observations protocol, comprising of listings of less than 6 months, 7 to 12 months, 13 to 18 months, and 19 to 24 months respectively. Time-on-the-market (TOM) in this study was perceived to be the duration (in months) from the listing date to the date of data collection. Results of selected parametric and non- parametric statistical tests indicated that there was an insignificant difference in the observation of distressed properties that have remained on the market for at most 6 months and those with marketing time beyond 6 months. Similarly, properties listed for distressed sales in Lagos city were found to have continuously attracted lower purchase rates in the same manner as the non-distressed properties. These results avowed the phenomenon of inefficient sale of distressed properties in Lagos city, Nigeria. It was recommended by the study that individuals and institutions in property brokerage business in Lagos city should conduct a risk assessment of the diminishing likelihood of distressed sales and the incremental losses associated with lengthy listing periods.

The Odd One Out? The Impact of Property Uniqueness on Selling Time and Selling Price

We employ machine learning to develop measures of residential real estate uniqueness from written advertisements. These measures are exogenous from sale prices. We distinguish the effect of market uniqueness (comparing houses for sale at the same time) from the effect of universal uniqueness (comparing houses in the same sub-market) on sale prices and time on the market (TOM). The hedonic models show that a one-standard-deviation increase in market uniqueness leads to a 13% ($48,490) increase in sale prices at the cost of delaying the transaction for 1.7 days, whereas a one-standard-deviation increase in universal uniqueness leads to only an 11% ($41,030) increase in sale prices at the cost of delaying the transaction for 3 days. We validated the impact of uniqueness on TOM using two hazard models. Our results highlight the importance of uniqueness and market timing in real estate.

Selling Prices and Time on the Market of Houses Sold through Relocation Management Companies

Employers contract with relocation management companies (RMCs) to help employees transfer from one location to another. In an efficient market, the selling price and time on the market (TOM) should not vary based on the nature of the seller. However, RMCs provide sellers with relocation package benefits that may affect TOM and selling price. This study examines a sample of 24,493 sales from 1998 to 2017, which includes 831 relocation sales. Relocation properties are more expensive, newer, and have more amenities than other transactions. The properties are less likely to be occupied during the listing period. Relocation sales of smaller properties sell 22.7% more quickly and at a 3.3% price premium in 1998–2007. TOM is 29.7% shorter for larger relocation properties in 2012–2017, suggesting more generous relocation packages for higher-level employees.

Financial conditions, local competition, and local market leaders: The case of real estate developers

AbstractThis paper studies whether (and how) corporate decisions are affected by internal factors (e.g., the financial conditions of own company) and external factors (e.g., the actions of local competitors) in an imperfectly competitive environment. We study the listed real estate developers in Beijing as a case study. Our hand‐collected dataset includes transaction‐level information booked indicators (e.g., profitability, liability, and liquidity) and unbooked financial indicators (political connections). Our multi‐step empirical model shows that both the firm's financial conditions and its competitors' counterparts are essential but play different roles in the output design, pricing, and the time‐on‐the‐market (TOM). Internal versus external factors' relative importance relates nonlinearly to the degrees of market concentration. Market leaders' existence alters the small firms' strategy and leads to higher selling prices and slower selling pace in the local market. Our comprehensive financial indicators (booked and unbooked) better predict corporate behaviors than traditional measures.

Financial Conditions, Local Competition, and Local Market Leaders: The Case of Real Estate Developers

This paper studies whether (and how) corporate decisions are affected by internal factors (such as the financial conditions of own company) and external factors (such as the actions of local competitors) in an imperfectly competitive environment. We study the listed real estate developers in Beijing as a case study. Our hand-collected dataset includes transaction-level information booked indicators (such as profitability, liability, and liquidity) and un-booked financial indicators (political connections). Our multi-step empirical model shows that both the firm's financial conditions and her competitors' counterparts are essential but play different roles in the output design, pricing, and the time-on-the-market (TOM). Internal versus external factors' relative importance relates to the degrees of market concentration in a nonlinear manner. Local market leaders' existence alters the small firms' strategy and leads to higher selling prices and slower selling pace in the local market. Our findings survive various robust checks.

The Omission of House Age in MLS Database Listings: The Effect on Selling Price and Time on Market

An asymmetric information problem occurs in the home buying process when sellers know more about a house than potential buyers. The listing agent must decide how much of this information to report in the local MLS and to syndicate to other sites. In some MLS datasets, the agent can choose to mark the age as “unknown,” essentially omitting this listing information. The omission raises several relevant questions, such as, why does age omission occur, how do age-omitted listed properties differ in characteristics from age-listed properties, and what effect does age omission have on a property’s time on the market and selling price? The findings show that age omission is more likely to occur when listing agents are less productive, and when homes are older and smaller, but in better condition relative to their peers. Age omission does not increase the property’s time on the market (TOM). When including time on market in the pricing model, however, omitted age properties appear to sell at a 4.7% discount. But age-omission properties have latent characteristics, and when correcting for this sample selection bias, the discount declines to a statistically insignificant 2%. The findings suggest that if less productive agents perceive an advantage to omitting a house’s age, real estate market pricing efficiency removes any significant benefit from using the strategy. The market appears to reduce the potential price incurred by the seller resulting from the omission of a property’s age.

Key determinants of time on the market: an analysis of residential housing market in Sri Lanka

Purpose Developing residential units is crucial in the socio-economic development of a country. The investor faces not only uncertain transaction price (price risk), but also uncertainties about the marketing period risk. Predicting when the incurred money is being realized is difficult because of the imperfect nature of the real estate market. Thus, the purpose of this study is to analyze the variables that explain the time on the market (TOM) of housing units, identifying the relationships in-between and the effects on TOM of residential properties. Design/methodology/approach Following a multi-stage sampling process, a random sample of 120 housing units was selected. Data were collected using a self-administered questionnaire. The questionnaire contained 57 variables that can affect TOM. Semi-structured interviews were conducted to confirm some of the data and information on residential units from the developers. Direct observations were conducted to verify certain physical attributes and, finally, they were comprehensively analyzed using quantitative analysis techniques in SPSS 16.0 Statistical package. Findings Results confirmed that lesser advertising prices, attractive environment, proximity to the city center and proper shape of lands reduce the TOM. Similarly, higher prices, longer distance to the city center and irregular shape of land increase the TOM. The results strengthen the necessity of a comfortable environment appropriate to live, probably with greenery or water bodies, which is a key influential factor that reduces the TOM in Sri Lanka. Originality/value wIn the Sri Lankan context, there are few contributions to the real estate literature in this regard. Many scholars have concentrated on physical and economic characteristics, whereas this research adds the environmental factors. Therefore, this research makes a significant contribution to the body of knowledge in this area, as it puts more attention on including several variables, as well as newly introduced variables as determinants. Consumers can apply the research findings to assess the relative importance of housing attributes and services which they perceive most valuable, and then to make their purchase decisions. The findings also contribute to the investigations of the behavior of housing attributes and enable knowing as to what factors are to be promoted and what to be omitted to gain a shorter TOM.

New House Premiums, Market Conditions, and the Decision to Purchase a New Versus Existing House

In this paper, we examine how the new house premium has changed over time. We propose that the new home premium can largely be attributed to the “lemons problem” from Akerlof (1970). Recent research suggests that the growth of the Internet has significantly reduced the lemons problem for many products. Our results suggest that the new house premium is about 5.6% without considering time-on-the-market (TOM) and has been declining. This premium ranges from 14.6% (1998) to −2.8% (2010). The average new house premium is 13.3% considering TOM, and ranges from 22.5% (1998) to 5.0% (2010). A trend analysis reveals that new house premiums have fallen 0.8%–0.9% annually, consistent with the Internet, information sharing, and reputation feedback mechanisms reducing the lemons problem associated with asymmetric information.

A hybrid approach to optimize initial design strategies for pre-sale housing projects

Purpose The purpose of this paper is to propose a hybrid decision-making model for optimizing the initial design strategies of pre-sales housing, identifying factors affecting the initial design of housing, and developing different initial design approaches and strategies based on buyers’ preferences. Design/methodology/approach Indicators and factors in line with the local initial planning and design are created according to the design quality indicator framework. The important indicators and factors are screened out preliminarily with the fuzzy Delphi method and decision-making trial and evaluation laboratory based analytic network process. The performances of two actual cases under similar site conditions are checked with regard to the overall residential sales rate and time on the market (TOM). Findings The result shows that the proposed model can effectively improve the sales rate, shorten the TOM and better complies with buyer design strategy demands, and thus positively correlating to economic value. Originality/value Pre-sales make possible the customized strategy of allowing future residents to participate in the housing design process. However, buyers’ participation in the design process is highly limited, and developers usually determine their planning and initial residential design strategies based on experience and intuition. With the proposed approach, the initial residential design of a project can be effectively intervened, so that home users can truly participate in the design, and the residential construction service can be provided in a unique, but non-universal way.

The Impact of TOM on Prices in the US Housing Market

Search theory shows that real property prices and marketing durations are simultaneously determined and positively related. Yet, empirical studies find positive, negative, and insignificant parameter estimates on the time-on-the-market (TOM) variable in price models. Using a dataset well suited to the research question, this article investigates reasons for the divergence between the theoretical and empirical results. Our test equations examine the quality of instrumental variables, severe overpricing, atypicality, structure quality, loss aversion, market tightness as well as measures unique to our data such as sellers’ income levels, reasons for sale, and urgency. We find that weak instrumental variables account for the varied empirical relations between transaction prices and TOM.

The Role of Transaction Costs in Impeding Market Exchange in Real Estate

We examine the role transaction costs play, particularly the costs related to search and bargaining, in impeding or delaying real estate market transactions. In a theoretical model, we show that agents' incentives are influenced by transaction costs in a way that will increase a home's marketing duration and decrease the probability a home will sell. Exploiting a decade of transactions from Virginia, we use a variety of empirical modeling techniques to estimate the effect of transaction costs on a property's time on the market (TOM) and its probability of sale. We find that factors associated with high search and bargaining costs increase a home's TOM and reduce the probability that it will sell.

FOR SALE… BUT FOR HOW LONG? A METHODOLOGICAL PROPOSAL FOR ESTIMATING TIME-ON-THE-MARKET

Residential real estate assumes crucial importance in a country's socioeconomic development. It is an important field of study, and much work has gone into better understanding the sector and the factors determining sales within it, such as time-on-the-market (TOM). TOM can be influenced by a variety of elements; a fact that in effect raises a lot of issues, because these determinants are often interpreted in an ambiguous or unstructured way. This study aims to bring greater accuracy and structure to our understanding of these factors, by showing that the integrated use of cognitive mapping with the Analytic Hierarchy Process (AHP) can give rise to a conceptually coherent and empirically valid framework to calculate TOM indices in the residential real estate market. Because it takes into account both tangible and intangible characteristics of a house, this measurement framework also boosts strategic planning support and allows for more informed business planning, which we believe can be a real contribution to the development of the real estate market. The practical implications and limitations of this evaluation system are also discussed.

Determinants of Time on the Market Reference to Residential Land Market in Matara District, Sri Lanka

Low level of liquidity is one of the main unique characteristics of the real property which effect on the performances of the real estate market. This character is measured by the time that a property remains in the market and is called as time on the market (TOM). In other terms this is the ‘reasonable time period’ expected to remain in the market as defined in the market value of the property. Sellers face a trade-off between two conflicting requirements that is to maximize sale price while minimizing the time until sale. The TOM is affected by many factors which are beyond full control of the seller and is not adequately analyzed in Sri Lanka.This paper mainly focuses on the determinants of TOM in residential land market in the context of Sri Lanka. Data collected from 128 blocks of lands available in land sales within four different segments based on the distance from Matara town was used in the analysis. It is revealed that the average TOM in the four segments is 14 (Weragampita), 53 (Walgama), 83 (Kamburugamuwa) and 100 (Thelijjawila) days respectively and there is a significant difference of the TOM in between the four segments. Correlation results indicate that there is a significant negative correlation between the TOM and the rate per perch, the distance from main road and positive correlation between TOM and distances from Main town. Therefore, sellers should be aware on the factors such as the rate per perch and the distance in order to maximize their profit through controlling the TOM in a particular location.

IDENTIFYING KEY DETERMINANTS OF HOUSING SALES AND TIME-ON-THE-MARKET (TOM) USING FUZZY COGNITIVE MAPPING

Price and residential housing attributes have long been identified as key determinants of home sales and, as such, they can explain time-on-the-market (TOM). It is acknowledged, however, that there are other factors (or determinants) that influence home sales and TOM, which are of great importance but seldom taken into account in the appraisal process of residential real estate. Based on the use of fuzzy cognitive mapping, we propose a framework that adds value to the way that key determinants of housing sales and TOM are identified. This framework is the result of a process involving several residential real estate experts (i.e.appraisers and realtors), and follows a constructivist approach. Our findings suggest that the use of fuzzy cognitive maps (FCMs) allows the number of omitted determinants to be reduced and the understanding of the relationships between them to be improved. The strengths and weaknesses of our methodological framework are also discussed.

The Benefit of Search in Housing Markets

Unlike in an efficient market where buyers and sellers are mere price-takers, participants in the real estate market are able to influence ultimate transaction prices through individual search efforts. Such benefit can offset the negative price trend of a declining market and compound the positive price trend of a growing market, suggesting an asymmetric effect of the price and time-on-the-market (TOM) relation. In other words, search mitigates the downside risk and magnifies the upside potential for the seller, which is an important advantage for real estate investors. In this study, we uncover the asymmetric price–TOM relation, and demonstrate the value of search using empirical data from the residential real estate market. Based on a large sample of home sales in the Virginia Beach–Norfolk, Virginia metropolitan area during an extended period of time, our findings clearly reveal an asymmetric search effect on price: longer TOM is strongly correlated with higher selling prices, but more interestingly, even in a declining market, the effect of the search (or the impact of TOM) on price is still positive, albeit smaller, suggesting the benefit of search is more than enough to potentially offset a negative market impact.

Determinants of Time on the Market in a Thin Real Estate Market

In the paper we investigate the factors that affect a property’s time on the market (TOM) in the residential real estate market in the case of a thin, illiquid market, such as those found in Central and Eastern European (CEE) countries. In contrast to liquid markets, the time it takes to sell a property can vary from a few days to a few months. In Slovenia a residential property’s marketability depends strongly on the price dynamics of the market, housing characteristics and the degree of overpricing. The most important determinants of the marketing time are the cost and availability of housing finance as well as the housing price index, and all three can be directly related to the affordability of housing. We develop a two-stage model of the determinants of TOM and a duration model. The results of the list price model show that as the age of property increases, its (list) price decreases with diminishing pace, while the size of the property has the opposite dynamic. The presence and size of parking lots also has a positive effect on the (list) price. The results of the Time on the Market model show that property characteristics, market conditions and macroeconomic determinants are all statistically significant determinants of TOM. The degree of overpricing turned out to be a statistically significant determinant of time on the market. However, this effect does not seem to be statistically significantly non-linear (U-shaped). Higher house prices (at the national level) and the average interest rate on housing loans both extend a property’s time on the market while better availability of housing loans, in contrast, shortens the TOM. We additionally estimated a proportional hazard model of the TOM that yielded consistent results.DOI: http://dx.doi.org/10.5755/j01.ee.26.1.3905

Motivated sellers and predation in the housing market

We develop an equilibrium search model of the housing market where sellers may become distressed as they are unable to sell. A unique steady state equilibrium exists where distressed sellers attempt liquidation sales by accepting prices that are substantially below fundamental values. During periods where a large number of sellers are forced to liquidate customers exhibit ‘predation’: they hold off purchasing and strategically slow down the speed of trade, which in turn causes more sellers to become distressed. The model naturally suggests several proxies of liquidity. Interestingly, the average time on the market (TOM), one of the most frequently used statistics in the literature, does a poor job within the context of liquidation sales and predation. Specifically we show that TOM falls during periods of predatory buying, which, if interpreted on face value, indicates that the market becomes more liquid with predation. We propose an alternative proxy – the profit loss in fire sales – which appears to be a more robust measure of liquidity than TOM.

Time on the Market and Sale Price of Non-Performing Loan Assets

The correlation between time on the market (TOM) and offer price or transaction price has been analyzed in a number of studies. Unlike previous studies, this paper focuses on atypical property (non-performing assets (NPAs)) and adopts a two-stage least squares regression (2SLS) model to test whether value enhancement strategies would enhance the disposal price in Kaohsiung city. The empirical results show that investors can’t profit just from increasing the time on the market (TOM). Investors have to adopt an enhancement strategy to increase NPA value as well. This is the important finding from the comparison of auction and value enhancement strategy in this paper. The Taiwanese experience reported in this paper shows that value increment can be achieved via the combination of longer TOM and value enhancement strategy.

The Role of Bidding in Determining Sales Price for Residential Property

Theoretical models of the house selling process have shown the number of bidders involved to be an important factor in explaining sales price; however, empirical models have not included specific variables capturing the dynamic process that occurs during time on the market (TOM). This paper addresses this gap by including explicit bidding variables, as well as TOM in a hedonic pricing model. The results confirm the importance of the number of bidders in understanding the direction of the relationship between price and TOM, identifying that the outcome of multiple bidder sales are more predictable than properties sold with a single bidder.