Predictive analytics using Big Data for the real estate market during the COVID-19 pandemic

As the COVID-19 pandemic came unexpectedly, many real estate experts claimed that the property values would fall like the 2007 crash. However, this study raises the question of what attributes of an apartment are most likely to influence a price revision during the pandemic. The findings in prior studies have lacked consensus, especially regarding the time-on-the-market variable, which exhibits an omnidirectional effect. However, with the rise of Big Data, this study used a web-scraping algorithm and collected a total of 18,992 property listings in the city of Vilnius during the first wave of the COVID-19 pandemic. Afterwards, 15 different machine learning models were applied to forecast apartment revisions, and the SHAP values for interpretability were used. The findings in this study coincide with the previous literature results, affirming that real estate is quite resilient to pandemics, as the price drops were not as dramatic as first believed. Out of the 15 different models tested, extreme gradient boosting was the most accurate, although the difference was negligible. The retrieved SHAP values conclude that the time-on-the-market variable was by far the most dominant and consistent variable for price revision forecasting. Additionally, the time-on-the-market variable exhibited an inverse U-shaped behaviour.

Time on the Market and Probability of Sale Using a Generalized Geometric Hazard Model

This study makes two main contributions to the applied econometrics literature. First, it shows how the all-important marginal effects for time on the market and probability of sale can be obtained from any hazard model. Second, it extends the generalization of the geometric due to Gómez-Déniz, E. 2010. “Another Generalization of the Geometric Distribution.” Test 19: 399–415 to include covariates for use in the estimation of time on the market and probability of sale regressions in real estate, thus creating an entirely new hazard model based on probability of sale rather than time on the market. For the generalized geometric we develop expressions for the marginal effects (with approximate standard errors) for both the probability of sale and time on the market. This formulation allows the impact of changes in independent variables on both the probability of sale and time on the market to be determined from a single regression model. For comparison, we also obtain these two sets of marginal effects for the popular Weibull hazard model. The geometric, generalized geometric, and Weibull hazard models, along with two sets of marginal effects for each, are estimated using data on condominium listings in a metropolitan area in Florida.

UNDERSTANDING SELLERS’ AGENTS IN THE RESIDENTIAL PROPERTY MARKET

Buyers in the property market often use an agent who is employed by the seller to assist their home searches. This unique and widely used agency arrangement in the property market is known as “sellers’ agents”. While principal-agent theory advocates that buyers should directly hire their agents (i.e., buyers’ agents) to do the home-hunting, search theory however implies that sellers would employ their agents (i.e., sellers’ agents) to increase the probability of the sale and selling prices. Although sellers’ agents and buyers’ agents are two very distinct institutions, many previous studies assume that their agency characteristics are identical and provide limited insights on how such a seemingly subtle but crucial agency arrangement affects transaction outcomes. Using transaction data from Wuhan China, this study disentangles the effects of the buyers’ and sellers’ agents on properties’ selling prices and their time on the market. The findings indicate that on average transactions conducted by sellers’ agents will be associated with a significant selling price premium of around 3.4%. As a critical test, we further show that the transactions completed by sellers’ agents with selling price premiums will have a shorter marketing time than those completed by buyers’ agents.

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.

ON ONE STRATEGY FOR THE INNOVATIVE DEVELOPMENT OF AN ENTERPRISE THAT GUARDS THE COUNTRY'SDRUG SECURITY

The proposed article is devoted to certain aspects of measuring the effectiveness of implementation development strategies of the economic subject. One of the enterprise-specific structures of St. Petersburg, operating in the format of small and medium-sized businesses for a long time on the market of biomedical and pharmaceutical products of the Northern capital, was chosen as the object of research. The studied company in its market activity adheres to the innovative path of development, which requires the attraction of significant investment influences, including state organizational and financial support. To implement the existing plans of the enterprise, the authors of the study developed a strategy of innovative development for three years, taking intoaccount the peculiarities of the formation of prices for medicines produced by the business structure. For obvious reasons, the authors assigned the company name “ABC” to the real economic entity. This company is part of the St. Petersburg medical-pharmaceutical cluster and successfully works on the production sites of the Special Economic Zone of the Technological and Innovative Type (SEZ TVT).

An Improved Approach for Constructing the Real Estate Price Index with Bargaining Effect

Bargaining game is ubiquitous in real estate markets due to its heterogeneity. Price index, the most important measurement the market condition, constructed with current approaches however cannot consider the effect of bargaining. Therefore, in this work, we provide a construction of price index including sellers’ bargaining power based on Nash bargaining theory and Heckman’s two-step regression. The sellers’ bargaining power is estimated from the aggregate data of list-price, sale-price and time-on-the-market. Using this method, the residential price index of an empirical example was conducted. The results are in reasonable agreement with the realistic situations, verifying the feasibility and applicability of the developed method.

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.