Time On Market Research Articles

Pricing strategies in the Silicon Valley housing market: an update on TOM and recent events

Purpose This study aims to explore the relationship between house prices and time-on-market (TOM) in Silicon Valley. Previous findings have been inconclusive due to variations in property characteristics. This paper highlights the discrepancy between listing and selling prices and identifies differences among housing types such as condominiums, detached houses and townhouses based on housing orientations and customer groups. Additionally, this study considers the impact of the COVID-19 pandemic and the Fed’s interest rate policies on the housing market. Design/methodology/approach The authors analyze 63,853 transactions from the Bay East Board of Realtors’ Multiple Listing Service during 2018 to 2022. The study uses a multiple-stage methodology, including a nonlinear hedonic pricing model, search theory and two-stage least squares method to address concerns relating to endogeneity. Findings The Silicon Valley housing market shows resilience, with low-end properties giving buyers more bargaining power without significant price drops. High-end properties, on the other hand, attract more attention over time, leading to aggressive bidding and higher final sale prices. The pandemic, despite reducing housing supply, did not dampen demand, leading to price surges. Post-COVID, price correlations with TOM changed, indicating a more cautious buyer approach toward high premiums. The Fed’s stringent monetary policies post-2022 intensified these effects, with longer listing times leading to greater price disparities due to financial pressures on buyers and shifting dynamics in buyer interest. Practical implications Results reveal a nonlinear positive correlation between TOM and the price formation process, indicating that the longer a listed property is on the market, the greater the price changes. For low-end properties, TOM becomes significantly negative, while for high-end properties, the coefficient becomes significantly positive, with effects and magnitudes varying by type of dwelling. Moreover, external environmental factors, especially those leading to financial strain, can significantly impact the housing market. Originality/value The experience of Silicon Valley is valuable for cities using it as a development model. The demand for talent in the tech industry will stimulate the housing market, especially as the housing supply will not improve in the short term. It is important for government entities to plan for this proactively.

Local constant-quality housing market liquidity indices

Market liquidity is an important aspect of housing market developments. The time on market (TOM) of sold properties is frequently used by researchers, practitioners, and policymakers as a market liquidity indicator. Compared to research on house price indices, the literature is very sparse on constructing housing market liquidity indices. This paper proposes a new method to construct constant-quality market liquidity indices based on TOM. The first contribution is that the method improves end-of-sample reliability resulting in fewer revisions. This increases the practical usefulness for business and policy purposes. The second contribution is that the applied structural time series method is designed to work in thin markets. This allows index construction at the local level.

A comparison of banks and real estate intermediaries as house sellers

The foreclosure crisis associated with the banking crisis transformed banks in the hardest-hit countries into real estate brokers. The main novelty of this paper is to study banks as sellers of their own foreclosed properties and compare banks’ sales outcomes with those of traditional agents in the real estate market. We compare the list price, selling price, time on market and price discount of traditional real estate companies (TRECs) and bank-owned real estate companies (BRECs). We find evidence of a higher selling price, higher list price and longer time on market (TOM) for BRECs than for TRECs. Our findings are consistent with BRECs displaying greater patience as well as lower risk aversion. However, these explanations are not enough to fully account for the magnitudes of the coefficients. The empirical estimates suggest that information in the housing market may also be a source of distortions. In fact, the main aim of the sale varies depending on the incentives of the company. BREC sellers are banks that own the properties for sale, so their incentives are to maximize selling prices to reduce the loss charged to their annual results, while TRECs seek to minimize the TOM.

The Impacts of Property Features on Time on Market of Real Estate Assets in Lagos Metropolis, Nigeria

It has been observed that real estate assets stay for a reasonably long period of time in the market before it was actually sold. This study therefore, examined the impacts of property features on time-on-market (TOM) of real estate assets in Lagos Metropolis, Nigeria. The study administered 65 questionnaires on estate firms actively involved in the sales of real estate assets in the study area. Information on property features and TOM of completed sales transactions were collected from 149 transactions. Data were collected and analysed using cross tabulation and regression analysis. The study revealed that there is a strong significant (0.05 level) relationship between TOM of real estate asset and title document, location condition and asset class while there is no significant relationship between TOM and repair condition, level of finishing, property description and property location. However, the result of regression analysis revealed that repair condition, asset class and title document are the only property features that have positive impacts on TOM. The study recommends that property developers should take notice of the identified property features that influence TOM of real estate assets which could improve the marketability of their assets and decrease the TOM of real estate asset..

Technical condition of houses: a framework for the Czech market

PurposeThis study aims to provide a framework for assessing the technical condition of a house to determine its market value, including the identification of other price-setting factors and their statistical significance. Time on market (TOM) in relation to the technical condition of a house is also addressed.Design/methodology/approachThe primary database contains 631 houses, and the initial asking price and selling price are examined. All the houses are located in the Brno–venkov district in the Czech Republic. Regression analysis was used to test the influence of price-setting factors. The standard ordinary least squares estimator and the maximum likelihood estimator were used in the frame of generalized linear models.FindingsUsing envelope components of houses separately, such as the façade condition, windows, roof, condition of interior and year of construction, brings better results than using a single factor for the technical condition. TOM was found to be 67 days lower for houses intended for demolition – as compared to new houses – and 18 days lower for houses to refurbishment.Originality/valueTo the best of the authors’ knowledge, this paper is original in the substitution of specific price-setting factors for factors relating to the technical condition of houses as well as in proposing the framework for professionals in the Czech Republic.

The Impact of Virtual Marketing Strategies on the Price-TOM Relation

Virtual tours such as pre-recorded videos or self-guided virtual reality (VR) tours represent marketing strategies that agents can use to promote homes for sale. Assuming agents aim at maximizing their net commissions, we expect virtual tours, which require more agent effort and are more costly, to be used for homes that are difficult to show due to being owner- or tenant-occupied. Using 34,359 single-family transactions from multiple US markets, we show that virtual tours impact the sales prices of occupied homes (1) directly (main effect) and (2) indirectly through an interaction with time on market (TOM). However, this impact differs in directionality and size across price segments and occupier type. The use of virtual tours has no effect on the sales prices of vacant homes. Our results suggest that virtual tours are effective strategies to overcome the difficulty of showing homes and moderate the price-TOM relation.

Time on Market and the Cash Discount for Condos

We investigate whether the cash discount for condos is affected by time on market (TOM). Theoretically and empirically, we show that the cash discount has two components: First, condos purchased with cash sell at a discount compared to mortgage-financed condos, which is in line with the cash discount identified in the housing literature. The second component is a TOM-variable cash discount that increases the longer a condo is on the market. In addition, our empirical analysis suggests the cash discount only exists for low-price condos and disappears in higher price segments. In particular, for low-price condos, the cash discount comprises of a 9.42% fixed cash discount and 0.1% per day TOM-variable cash discount. Our results suggest TOM represents an additional explanation for the cash discount in condos and moderates the relation between cash purchase and sales price.

TIME ON THE MARKET OF RESIDENTIAL CONDOMINIUM UNITS WITH PRE-SALE ARRANGEMENT IN COLOMBO DISTRICT

The purpose of this paper is to study the time on market (TOM) for residential condominium units under pre sales arrangements and what key factors drive that TOM. The contextual understanding of previous studies on TOM for residential properties confined for properties sold either in the secondary market or properties where construction is completed. This study focuses on the relationships among TOM, listed price, and basic property characteristics of residential condominium units sold under the provisional condominium plan in Colombo, Sri Lanka. Following non-probability sampling technique, this study examines TOM of 189 pre-sale residential condominium units in Colombo district which came into market between 2016 January to 2019 January. Developers were approached to collect required data such as transaction price, transaction date, final listed date listed price, number of bedrooms, number of bathrooms, floor area, floor level, construction completion, discounting rates likewise. Data analysis followed descriptive statistics, Pearson Correlation, and multiple regression model. The analysis highlighted that from January-2016 to January-2019, TOM of provisional residential condominiums of Colombo varied from 12.76 to 5.51 months. The results further highlighted that the TOM of a pre-sale provisional residential condominium unit is a function of floor area, number of bathrooms, level of the unit, construction completion & discount rate. The study highlights that during the period considered, the floor area units of 744sqft at the initial stage of construction with a discount rate between 10% to 20% from the listed price can predicted to have the lowest TOM..
 Keywords: Time on the Market; Pre-sale; Residential Condominium Units; Listed Price; TransactionPrice.

Impact of urban rehabilitation: evidence from subdivided units in Hong Kong

Purpose This paper aims to explore one question: to what extent does urban rehabilitation impact the housing search cost of the low-income tenants. Design/methodology/approach This paper adopts the fixed effects time-on-market (TOM) model and pricing model to study the research question. Findings Urban rehabilitation lifts the subdivided units (SDUs’) prices by around 7%. For the SDU located in old districts, urban rehabilitation gives rise to the rental price up by 11%–12%. The SDUs in the area without urban rehabilitation experience a short marketing period of 16%–17%. The SDU located in the old district that is without urban rehabilitation would have a short marketing time. Originality/value To the best of the authors’ knowledge, this is the pioneering research to investigate the relationship between rehabilitation and low-income rental housing from the improved search theory. The improved search theory posits that under the circumstance of urban rehabilitation, low-income tenants’ options are limited and the search behavior will be restricted in the affordable areas, and then TOM will be shortened. With the concentration of SDUs in Hong Kong, the test of the search theory is broken down into two hypotheses. (H1) Urban rehabilitation leads to low-income housing prices increase. (H2) Low-income housing located in areas without urban rehabilitation has a shorter TOM.

The influence of design-related features on houses time-on-market: a statistical analysis

PurposeResearchers have not widely explored design-based factors that govern buildings’ physical properties and human–building interactions. This paper aims to understand the influence of design-related factors on the time-on-market (TOM) of listed houses and, consequently, study the effect of design features on the desirability of a given house.Design/methodology/approachThis research analyzes a dataset of listed houses, provided by the REALTORS® Association of Edmonton (RAE) and covers a period extending from January 2009 to August 2019, using Cox proportional-hazards regression model to identify building features that influence people purchasing decisions.FindingsThe research findings affirm the statistical insignificance of the price on the TOM compared to other design features, such as the construction method, the installed mechanical systems and cladding materials.Research limitations/implicationsThe data used in the analysis comes from a single North American region, i.e. Edmonton, Alberta, Canada. Also, the data provided by the RAE includes only records that involve a realtor.Practical implicationsThe observations of the research presented in this paper influence the housing market players’ decisions about housing designs, mainly those concerned with building new residential dwellings such as speculative builders and designers.Originality/valueThe research novelty stems from two aspects: the medium used for analysis, i.e. Cox proportional-hazards regression model, which allows considering the listed-but-not-sold units and helps to eliminate the survivorship bias that leads to over-optimistic outcomes; and the assessment of design-related features which allows to understand people’s preferences in design alternatives.

The Price–Time-on-Market Puzzle Revisited: Evidence from Big Data

This paper provides new evidence on the relationship between time-on-market (TOM) and house prices. Using big data techniques, we construct a rich dataset on residential transaction prices in England between 2018 and 2020, their listing information, energy performance, and property taxes. We use two novel instrumental variables (IVs) – the price revision duration and the council tax band for TOM and price respective. We show a positive and simultaneously determined relationship between price and TOM, in line with search theory. We also demonstrate that sellers not looking to use the proceeds from the sale as a down-payment for a new property, i.e. ’chain-free’ sellers, list and transact at a lower price, all else equal.

Average time to sell a property and credit conditions: Evidence from the Italian housing market survey

AbstractThis study examines the influence of housing credit conditions on the time on market (TOM) for residential properties in Italy, using a unique dataset from the Bank of Italy survey on the Italian housing market. The analysis was carried out on a sample of roughly 1000 real estate agents over the period 2011–2015 using panel data techniques. The results support the view that an increase in housing market liquidity, measured by the loan‐to‐value ratio, reduces the average TOM of a property, thus improving the matching process between buyers and sellers. The results are found to be robust to specifications including the traditional determinants of TOM, used as controls (i.e., price revisions, potential buyers, mandates to sell, the role of brokers, and so on). The results also show that a higher price reduction, possibly associated with an initial mispricing by the seller when setting the initial listing price, seems to be associated with a higher TOM for residential properties.

House Hedging Model — which income group is more affected by risk?

This paper investigates the housing market dynamics based on the individual choices of tenants and homeowners. We integrate Han (2008)’s individual homeowners’ transaction choice model with tenants’ housing tenure choice into a single, new model, and take tenants’ and homeowners’ decision into account jointly. As a result, our new model can capture the interaction between the transaction and rental markets and hence is more realistic. The model is applicable to Hong Kong and other countries of which the rental market is a significant proportion of the whole property market. We solve the new model in an analytical way. In addition, we conduct an agent-based simulation on the model. Compared with Han (2008)’s hump-shaped life-cycle paths, our results show that the life-cycle paths are irregular. Nevertheless, the middle-income households are least affected by housing price risk. Moreover, the average Time on Market (TOM) is significantly positively affected by housing vacancy rate under the exogenous price assumption. Finally, the trend of homeownership rate in a relatively closed market is not significantly affected by the specific housing price or rent process. Policy makers can make use of our model to implement more appropriate housing policies to regulate the housing market.

Local Constant-Quality Housing Market Liquidity Indices

The average time on market (TOM) of sold properties is frequently used by practitioners and policymakers as a market liquidity indicator. This figure might be misleading as the average TOM only considers properties that have been sold. Furthermore, traded properties are heterogeneous. Since these features differ over the cycle, the average TOM could provide wrong signals about market liquidity. These problems are more severe in markets where properties trade infrequently. In this paper, a methodology is provided that allows for the construction of constant-quality housing market liquidity indices in thin markets that can be estimated up to the end of the sample. The latter is particularly important since market watchers are generally interested in the most recent information regarding market liquidity and less in historical information. Using individual transactions data on three different types of Dutch municipalities (small, medium, and large) it is shown that the average TOM overestimates market liquidity in bad times and underestimates market liquidity in good times. The option to withdraw is the most important reason why the average TOM is misleading. Furthermore, constant-quality liquidity leads the average TOM and price changes. The indices not only show that illiquidity is higher during busts, but also that liquidity risk is higher. Additional results suggest that setting a high list price relative to the estimated value results in a higher TOM, but this effect differs over time. Both the list price premium and the effect on sale probability are higher during busts. Differences in housing quality over the cycle, however, also play a significant role. Finally, the method allows for the construction of indices that are more robust to revisions, especially in thinner markets.

Time on market (TOM): The impact of new residential stamp duty

This paper is the pioneer research considering impacts of new residential stamp duty on TOM. This paper covers space and time information of property transaction via spatial–temporal model, which overcomes the deficits of previous studies by only capturing temporal information. A spatial model selection scheme is adopted in this paper which largely reduces the subjective model selection bias. The results of this paper enable to test and support the important housing theory: when the new residential stamp duty is executed, buyers’ options are limited then TOM is reduced. The reduced TOM implied that buyers intend to suffer high transaction tax of the property on the condition that new residential stamp duty is enforced. They believe that performance of property asset still outperforms the other investment vehicles in Hong Kong. The results of this paper provide valuable information on policy making.

Exploring the determinants of liquidity with big data – market heterogeneity in German markets

PurposeThe purpose of this paper is to examine the market liquidity (time-on-market (TOM)) and its determinants, for rental dwellings in the largest seven German cities, with big data.Design/methodology/approachThe determinants of TOM are estimated with the Cox proportional hazards model. Hedonic characteristics, as well as socioeconomic and spatial variables, are combined with different fixed effects and controls for non-linearity, so as to maximise the explanatory power of the model.FindingsHigher asking rent and larger living space decrease the liquidity in all seven markets, while the age of a dwelling, the number of rooms and proximity to the city centre accelerate the letting process. For the other hedonic characteristics heterogeneous implications emerge.Practical implicationsThe findings are of interest for institutional and private landlords, as well as governmental organisations in charge of housing and urban development.Originality/valueThis is the first paper to deal with the liquidity of rental dwellings in the seven most populated cities of Europe’s second largest rental market, by applying the Cox proportional hazards model with spatial gravity variables. Furthermore, the German rental market is of particular interest, as approximately 60 per cent of all rental dwellings are owned by private landlords and the German market is organised polycentrically.

The influence of estate agencies’ location and time on Internet

It is widely known, that home buyers and tenants increasingly rely on the Internet, when searching for homes; as shown in different studies over the years. This paper analyses the relationship between listing price and time-on-Internet compared to the estate agents’ locations. Many studies analysed the time on market (TOM) in relationship to the selling price and focused on different characteristics e.g. housing attributes, location characteristics and special findings like overpricing effects. In contrast to the established TOM analyses, which analyse the actual duration of commercialization from starting the marketing to the successful sale, this paper focuses on the online marketing time. The methodology follows the setting of the TOM literature and applies: OLS, hazard and 2sls modelling. We use Viennese real estate offers from an Internet platform covering 2010–2011. We find the time on Internet to significantly increase, if the agent is located outside of Vienna. Although the real estate prices of estate agents outside Vienna are significantly lower than from estate agents inside Vienna.

Market Conditions, Marketing Time, and House Prices

We examine whether the relationship between marketing time and selling price changes with conditions in the Auckland housing market. Our sample covers periods when house prices rise (2006:Q1–2007:Q3), then decline (2007:Q4–Q4 2008:Q4), and lastly resume appreciating (2009:Q1–2010:Q3). We estimate hedonic pricing models for each identified subperiod. Our results indicate that the coefficient of time-on-market (TOM) is clearly influenced by the changing market conditions. In buoyant market conditions, houses that remain unsold are subject to a stigma discount. TOM, however, does not significantly impact price in a falling market.

How do market conditions impact price-TOM relationship? Evidence from real estate owned (REO) sales

Empirical evidence on the relationship between real estate price and selling time (time-on-market (TOM)) is mixed as to whether the price-TOM relationship is positive or negative. Competing theories also suggest opposite predictions about TOM’s impact on selling price. The article examines the price-TOM relationship against the background of varying market conditions and highlights the impact of these conditions on the relationship. The theoretical analysis extends search theory and Lazear’s model to changing market conditions and reconciles their predictions on the relationship. The empirical analysis refines the investigation of the price-TOM relationship by revealing the cross-effect of market conditions and TOM on price. The findings confirm that the price-TOM relationship can indeed be positive or negative depending on these conditions. However, except for the case of an extremely bad market, the relationship is generally positive. This outcome occurs because search effort (indicated by TOM) brings significant price benefit that is large enough to offset all but the worst market price declines. Additional analysis confirms that the findings are not altered by the potential endogeneity between price and TOM.

The Role of Transaction Costs in Impeding Market Exchange in Real Estate: Evidence from Virginia

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 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.