Better Residential than Ethnic Discrimination! Reconciling Audit's Findings and Interviews' Findings in the Parisian Housing Market

This article investigates discrimination and the interplay of residential and ethnic stigma on the French housing market using two different methods: paired-testing audit study of real-estate agencies and face-to-face interviews with real-estate agents. Findings lead to a paradox: interviews reveal high levels of ethnic discrimination but little to no residential discrimination, while the audit study shows that living in deprived suburbs is associated with a lower probability of obtaining an appointment for a housing vacancy but ethnic origin (signalled by the candidate’s name) has no significant discriminatory effect. We have three priors potentially consistent with this apparent paradox and re-evaluate their likelihood in light of these findings: (1) agents make use of any statistical information about insolvency, including residency; (2) there are two distinct and independent taste discriminations, one about space and one about ethnicity; (3) these two dimensions exist and complement each other.

PurposeThe purpose of this study is to analyze and compare the level of professionalization of the real estate broker's occupation in Victoria, Australia, and Sweden. As previous studies have indicated that the real estate agent occupation in both regions is experiencing low levels of trust, an analysis of the level of professionalization is warranted.Design/methodology/approachThe data used in the analysis in this paper have been gathered from a number of different high-quality sources. In Sweden, information has been obtained from the Swedish Real Estate Agents Inspectorate, the Association of Swedish Real Estate Agents and the Swedish Real Estate Agents Association, and Real Estate Statistics. For the Victorian case, information has been obtained from the Real Estate Institute of Victoria, which is the leading professional body in organizing real estate agents. Furthermore, information has also been sourced from the Business Licensing Authority as well as Consumer Affairs Victoria. The focus of the analysis has been on the institutional changes of the real estate profession, including the education required to become an agent, the legislation and supervision of real estate agents and the role of the professional bodies that organize the real estate agents. 10;FindingsThe analysis shows that both the real estate brokerage market in Victoria and Sweden could be characterized as mature. Using the definition of a profession from Millerson (1964), the authors conclude that the brokerage industry has a number of the characteristics of a profession such as a long albeit interdisciplinary education, strong professional bodies, code of conduct and some level of self-regulation.Research limitations/implicationsThis research examines two countries, both considered mature in their house market process. Findings may be very different if the research methodology was applied to house markets that do not exhibit the same level of regulatory control.Practical implicationsEven though the real estate occupation can be considered as a semi-profession, there is still room for improvement when it comes to how consumers perceive the trustworthiness of real estate agents. Therefore, the professional bodies ought to strive to find ways on increasing the status and trustworthiness of the profession. These could include increasing the transparency as well as continuing education for its members.Social implicationsUsers of real estate services need to have confidence in the skills and expertise of real estate agents they engage. The magnitude of the monies associated with real estate transactions should cause users to seek out agents who are proficient in what they do, and to this end, the professionalism of agents is critical to the provision of accurate and informative information to guide users toward positive and beneficial outcomes.Originality/valueTo the best of the authors’ knowledge, this is the first study that analyzes and compares the development of the real estate profession in Victoria and Sweden, using theories from the study of professions.

How does ethnic discrimination on the housing market differ across neighborhoods and real estate agencies?

Until recently, research trend in real estate has been focused on real estate market and the market analysis. But the studies on real estate training program development for real estate agents to improve their job performance are relatively short in numbers. Thus, this study shows empirical analysis of the needs for the training programs for real estate agents in Cheonan to improve their job performance. The results are as follows. First, in the survey of asking what educational contents they need in order to improve real estate agents` job performance, most of the respondents show their needs for the analysis of house`s value, legal knowledge, real estate management, accounting, real estate marketing, and understanding of the real estate policy. This is because they are well aware that the best way of responding to the changing clients` needs comes from training programs. Secondly, asked about real estate marketing strategies, most of respondents showed their awareness of new strategies to meet the needs of clients. This is because new forms of marketing strategies including internet ads are needed in the field as the paradigm including Information Technology changes. Thirdly, asked about the need for real estate-related training programs, 92% of the respondents answered they need real estate education programs run by the continuing education centers of the universities. In addition, the survey showed their needs for retraining programs that utilize the resources in the local universities. Other than this, to have effective and efficient training programs, they demanded running a training system by utilizing the human resources of the universities under the name of the department of `Real Estate Contract` for real estate agents` job performance. Fourthly, the survey revealed real estate management(44.2%) and real estate marketing(42.3%) is the most chosen contents they want to take in the regular course for improving real estate agents` job performance. This shows their will to understand clients` needs through the mind of real estate management and real estate marketing. The survey showed they prefer the training programs as an irregular course to those in the regular one. Despite the above results, this study chose subjects only in Cheanan and thus it needs to research more diverse areas. The needs of programs to improve real estate agents job performance should be analyzed empirically targeting the real estate agents not just in Cheonan but also cities like Pyeongchon, Ilsan and Bundang in which real estate business is booming, as well as undergraduate and graduate students whose major is real estate studies. These studies will be able to provide information to help develop the customized training programs by evaluating elements that real estate agents need in order to meet clients satisfaction and improve their job performance. Many variables of the program development learned through these studies can be incorporated in the curriculum of the real estate studies and used very practically as information for the development of the real estate studies in this fast changing era.

In Korea, brokerage firms have been managing the traditional brokerage commission split model, but the United States has been seeking continuous development of brokerage firms by developing various brokerage commission models for the survival and expansion of brokers. Keller Williams and eXp Realty introduced cloud brokerage to reduce fixed costs, to reduce broker acquisition costs, and incentives to strengthen broker belonging. In particular, there are many implications of the eXp Realty revenue sharing model, which has little initial franchise cost, and is a cloud-based real estate brokerage program that divides profits with expert support without fees for desks and tasks. It encourages start-ups and intermediaries with unique models that give incentives to real estate agents and brokers. It also develops models of three ways in which real estate agents and intermediaries generate revenue, providing real estate sales, revenue sharing and shareholder revenue. It offers a revenue-sharing program that allows real estate agents and brokers to receive both revenue and common stock incentives. In addition, real estate brokers and agents build their own businesses by owning direct equity as shareholders and business partners. In particular, it has revolutionized the existing real estate brokerage model by providing an opportunity for compensation for common stock. Cloud-based brokerage operated by brokers provides maximum value to real estate agents and brokers while building a global brand. The management method of these real estate brokerage firms has many implications for domestic brokerage firms.

Case studies have illuminated that U.S. real estate agents, as key housing market gatekeepers, continue to maintain racial residential stratification well into the twenty-first century. We use novel survey data gathered from real estate agents across the United States to descriptively explore agents’ ideas about clients of color in the housing market, as well as their practices, such as conducting business through social networks. Our findings provide evidence of the subtle and more overt ways that these ideas and practices that, when taken together, constitute what we call racialized real estate agency and contribute to ongoing racial segregation. We issue a call for future research to continue examining the ways agents’ and other gatekeepers’ ideas and practices contribute to or mitigate stratifying processes and describe the utility of such research for policy.

The study examined consumers’ complaints against real estate agents in Lagos Metropolis, Nigeria with a view to providing information that could ensure effective service orientation and high consumers’ satisfaction. Data were elicited from real estate agents and consumers in the study area through self-administered questionnaire and analyzed with the use of frequency distribution, percentages and mean rating. The study found some level of dissatisfaction as 35.3% representing 61 of the real estate agency consumers were dissatisfied with real estate agency related services. 30.1% of the respondents objected to the possibility of repeat business with their real estate agent while 33% rejected the possibility of recommending their agents to others. The most common complaint against real estate agents was ‘fee levels too high’ as reported by 81 respondents representing 31% of the study population. The study also revealed that real estate agency consumers complained about communication problems, over pricing of property, agents providing wrong information, agents not delivering what was required, agents pressurizing customers, delays, deadlines not met, galumphing, agents providing wrong information, mismanagement of the property in their care etc. Therefore real estate service consumers’ complaints must be thoroughly attended to as these may lead to consumers’ dissatisfaction. Real estate agents must ensure that customer service remains high so as to experience consumers’ satisfaction, retention and successful businesses. Keywords : Consumers’ Complaints, Real Estate Agents, Nigeria DOI: 10.7176/CER/13-4-05 Publication date: July 30 th 2021

The real estate sector is one of the most important sectors of the economy for developing countries. The housing market is directly related to the performance of economy. The impact of this market is measured through the volume of various transactions, such as real estate sales, lease contracts, construction contracts, import transactions, foreign exchange, transactions of financial intermediaries and real estate agencies, employment contracts, etc. The real estate market is directly influenced by housing policies, the level of financial system development, visible additional costs (tax rates and credit costs) and its invisible costs (which is informality and information asymmetry). Hypotheses: The housing market operates according the rules of the supply-demand and the factors that affect the fluctuation of housing prices. The purpose of the article is to evaluate the demand factors in the performance of house prices in Albania. Methodology: The study employs an exploratory analysis based on the literature review, the secondary data and empirical analysis. The authors make a comparison between the factors identified by the literature review, the analysis of the secondary data for the Albanian real estate market, and statistical relationships of individual factors as well: GDP/capita, Exchange rate, Interest rates in ALL, Interest rates EURO, Remittances and the level of mortgage loans in EURO. In the conclusions of the paper, some of the factors that have directly influenced the fluctuations in real estate prices in Albania are: the demand and the supply of real estate; the change in the value of the functional currency; state intervention through fiscal policies and urban planning; credit financing to businesses and individuals, etc.

This study aims to investigate to which extent the ethnic and socio-economic composition of the neighbourhood is related to levels of discrimination in the rental housing market and how this is linked to theories of ethnic discrimination. Hereby, we divide the context into the neighbourhood of the dwelling and the real estate agency, using data from 2385 correspondence tests conducted among realtors in the city of Antwerp in Belgium. Regarding the neighbourhood of the dwelling, we find a tipping point at one third ethnic minorities whereafter ethnic discrimination decreases, which is in line with the perceived preference hypothesis and customer-based prejudice. A lower socio-economic composition relates to lower general invitation rates, which we describe as an elaboration of Putnam’s hunkering down hypothesis. Regarding the neighbourhood of the real estate agency, a higher percentage of ethnic minorities leads to lower general invitation rates, also referring to the hunkering down hypothesis. The socio-economic neighbourhood composition of the agency, however, has no impact.

В статье представлены результаты контент-анализа объявлений сайта «Авито» о продаже жилья в трех городах Приволжского федерального округа: Казани, Кирове и Нижнем Новгороде. Цель данной статьи — оценить жилищно-пространственное неравенство и состояние жилищного фонда в городах сквозь призму предложений рынка жилья. Для формирования эмпирической базы был собран сплошной массив объявлений о продаже жилья за фиксированный отрезок времени и проведен структурный контент-анализ информации о продаваемых объектах. Также проведена серия экспертных интервью с риелторами в изучаемых городах. Систематизированы базовые и факультативные параметры, влияющие на ценообразование и престиж недвижимости. В ходе статистического анализа параметров продаваемого жилья сформирован и рассчитан интегральный показатель качества и престижа недвижимости, позволяющий ранжировать объекты рынка жилья с позиции жилищной стратификации. В соответствии с интегральным показателем в каждом городе выделены четыре типа микрорайонов по качеству жилья и степени однородности застройки, определены специфические черты жилищного фонда трех городов. На основе полученных данных построены карты городов, отражающие жилищно-пространственную дифференциацию микрорайонов. Апробированная методика контент-анализа объявлений о продаже жилья может быть использована для исследования жилищной дифференциации других городов, позволяет прогнозировать рыночную стоимость жилья в зависимости от его параметров и престижа районов города, судить о наполненности жилищных классов горожан, выявлять ключевые тенденции изменений жилищного фонда в регионах. Благодарность. Статья подготовлена при поддержке Российского фонда фундаментальных исследований (РФФИ), грант № 18-011-00627 «Особенности жилищного неравенства в современных российских городах».

Most real estate agents develop new objects by visiting unfamiliar clients, distributing leaflets, or browsing other real estate trading website platforms, whereas consumers often rely on websites to search and compare prices when purchasing real property. In addition to being time consuming, this search process renders it difficult for agents and consumers to understand the status changes of objects. In this study, Python is used to write web crawler and image recognition programs to capture object information from the web pages of real estate agents; perform data screening, arranging, and cleaning; compare the text of real estate object information; as well as integrate and use the convolutional neural network of a deep learning algorithm to implement image recognition. In this study, data are acquired from two business-to-consumer real estate agency networks, i.e., the Sinyi real estate agent and the Yungching real estate agent, and one consumer-to-consumer real estate agency platform, i.e., the, FiveNineOne real estate agent. The results indicate that text mining can reveal the similarities and differences between the objects, list the number of days that the object has been available for sale on the website, and provide the price fluctuations and fluctuation times during the sales period. In addition, 213,325 object amplification images are used as a database for training using deep learning algorithms, and the maximum image recognition accuracy achieved is 95%. The dynamic recommendation system for real estate objects constructed by combining text mining and image recognition systems enables developers in the real estate industry to understand the differences between their commodities and other businesses in approximately 2 min, as well as rapidly determine developable objects via comparison results provided by the system. Meanwhile, consumers require less time in searching and comparing prices after they have understood the commodity dynamic information, thereby allowing them to use the most efficient approach to purchase real estate objects of their interest.

This book examines how housing market professionals—including housing developers, real estate agents, mortgage lenders, and appraisers—construct twenty-first-century urban housing markets in ways that contribute to or undermine racial segregation. Drawing on extensive ethnographic and interview data collected in Houston, Texas, the book shows that housing market professionals play a key role in connecting people—or refusing to connect people—to housing resources and opportunities. They make these brokering decisions through reference to racist or equitable, people-affirming ideas. Typically, White housing market professionals draw from racist ideas that rank order people and neighborhoods according to their perceived economic and cultural housing market value, entwining racism with their housing market activities and interactions. Racialized housing market routines encourage this entwinement by naturalizing racism as a professional tool. The book tracks how professionals broker racism across the housing exchange process—from the home’s construction to real estate brokerage, mortgage lending, and home appraisals. In doing so, it shows that professionals make housing exchange a racialized process that contributes to neighborhood inequality and racial segregation. However, in contrast to the racialized status quo, a small number of housing market professionals—almost all of color—draw on equitable, people-affirming ideas and strategies to extend equal opportunities to individuals and neighborhoods, denaturalizing housing market racism. The book highlights the imperative to interrupt the racism that pervades White housing market professionals’ work, dismantle the racialized routines that underwrite such racism, and cultivate a fair housing market.

The purpose of this paper is to determine the impact of real estate agents on the price of houses that are located close to an environmental disamenity using Rosen's (1974) hedonic price model. Our main hypothesis is that real estate agents obtain higher prices than those theoretically expected when the houses are located closer to an environmental disamenity. We attribute this result to differences in information about the presence of the environmental disamenity between buyers, sellers, and their real estate agent, that ultimately have an impact on their bargaining position. Our analysis is based on 2,967 transactions involving houses located close to four landfills in Franklin County, Ohio, in 1990. Using an estimated hedonic price model, we predict house values for transactions made with and without a real estate agent, and calculate their percentage differences at various distance intervals from the landfills. On average, results suggest that at distances less than 1 mile away from the landfills, the percentage increase in the house price obtained by a real estate agent is greater than the commission rate. For example, the weighted predicted rent for transactions made through a real estate agent at an interval distance of 0.75 miles away from the landfills is $7,680.37, while the predicted rent for transactions made without an agent is $6,780.71. The difference between these two predicted house values is 13.27 percent. For an average real estate commission rate of 7 percent, real estate brokered sales results in surplus for houses closer to landfills. This effect erodes as distance away from the landfill is increased. These findings are consistent with theoretical expectations about differences between prices obtained by real estate agents and prices obtain by individual house sellers. In addition to the effects that real estate agents may have on house prices, results of this paper may be of interest to individuals using multiple listing service (MLS) data alone for hedonic studies. That is, our paper provides evidence that estimating hedonic price models with MLS data can downwardly bias estimated impacts of an environmental disamenity.

Zillow. Zillow Real Estate Metrics: For-Sale Inventory, Raw | State: California | Zip Code: 90069 | Zip Code Name: WEST HOLLYWOOD (90069), 01/2010 - 10/2016. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 068-001-035 Dataset: Reports the median of a weekly snapshot of for-sale homes within a region for a given month. Zillow® real estate metrics are based on its database of more than 100 million homes in the United States, including homes for sale, homes for rent and homes not currently on the market. Included in the dataset are estimated market value of homes and estimated prices of monthly rents, termed Zestimates®. All valuations are based on public records and user-submitted data and are calculated using a proprietary formula that takes into account property physical attributes, tax assessments, and prior and current transactions. Also included in the dataset are counts of homes for rent and for sale, list and sales prices, and metrics related to foreclosures. Currency and availability for subnational geographies may vary by indicator. The accuracy of Zillow metrics is dependent on the data received; estimates of accuracy for major metropolitan areas can be found at http://www.zillow.com/howto/DataCoverageZestimateAccuracy.htm . The data included in Data-Planet are provided courtesy of Zillow® Real Estate Research. http://www.zillowblog.com/research/data/#bulk Category: Housing and Construction Subject: Housing Market, Housing Inventory Source: Zillow Zillow is a home and real estate marketplace launched in 2006 that aims to assist homeowners, home buyers, sellers, renters, real estate agents, mortgage professionals, landlords and property managers locate and share information about homes, real estate and mortgages. Zillow uses a priority formula to estimate home and rental housing market value, termed a Zestimate, using its database of over 110 million homes in the United States. The Zestimate is calculated from public and user submitted data. http://www.zillow.com/

Zillow. Zillow Real Estate Metrics: Median Home Value - All Homes | State: Colorado | Zip Code: 80123 | Zip Code Name: LITTLETON (80123), 04/1996 - 06/2017. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 068-001-001 Dataset: Presents the median of Zillow's estimated market value of homes in the United States by geographic area. The estimated market value (termed a Zestimate®) is computed using a proprietary formula. Zillow® real estate metrics are based on its database of more than 100 million homes in the United States, including homes for sale, homes for rent and homes not currently on the market. Included in the dataset are estimated market value of homes and estimated prices of monthly rents, termed Zestimates®. All valuations are based on public records and user-submitted data and are calculated using a proprietary formula that takes into account property physical attributes, tax assessments, and prior and current transactions. Also included in the dataset are counts of homes for rent and for sale, list and sales prices, and metrics related to foreclosures. Currency and availability for subnational geographies may vary by indicator. The accuracy of Zillow metrics is dependent on the data received; estimates of accuracy for major metropolitan areas can be found at http://www.zillow.com/howto/DataCoverageZestimateAccuracy.htm . The data included in Data-Planet are provided courtesy of Zillow® Real Estate Research. https://www.zillow.com/research/data/#bulk Category: Housing and Construction Subject: Housing Market, Housing Inventory Source: Zillow Zillow is a home and real estate marketplace launched in 2006 that aims to assist homeowners, home buyers, sellers, renters, real estate agents, mortgage professionals, landlords and property managers locate and share information about homes, real estate and mortgages. Zillow uses a priority formula to estimate home and rental housing market value, termed a Zestimate, using its database of over 110 million homes in the United States. The Zestimate is calculated from public and user submitted data. http://www.zillow.com/