Boosted regression trees

2014 ◽  
Vol 19 (2) ◽  
pp. 152-167 ◽  
Author(s):  
William J. McCluskey ◽  
Dzurllkanian Zulkarnain Daud ◽  
Norhaya Kamarudin
Keyword(s):  
Real Estate ◽  
Regression Trees ◽  
Heterogeneous Data ◽  
Boosted Regression Trees ◽  
Categorical Variables ◽  
Percentage Error ◽  
Residential Property ◽  
Data Set ◽  
Content Type ◽  
Real Estate Valuation

Purpose – The purpose of this paper is to apply boosted regression trees (BRT) to a heterogeneous data set of residential property drawn from a jurisdiction in Malaysia, with the objective to evaluate its application within the mass appraisal environment in Malaysia. Machine learning (ML) techniques have been applied to real estate mass appraisal with varying degrees of success. Design/methodology/approach – To evaluate the performance of the BRT model two multiple regression analysis (MRA) models have been specified (linear and non-linear). One of the weaknesses of traditional regression is the need to a priori specify the functional form of the model and to ensure that all non-linearities have been accounted for. For a BRT model the algorithm does not require any predetermined model or variable transformations, making the process much simpler. Findings – The results show that the BRT model outperformed the MRA-specified models in terms of the coefficient of dispersion and mean absolute percentage error. While the results are encouraging, BRT models still lack transparency and suffer from the inability to translate variable importance into quantifiable variable effects. Practical implications – This paper presents a useful alternative modelling technique, BRT, for use within the mass appraisal environment in Malaysia. Its advantages include less intensive data cleansing, no requirement to specify the predictive underlying model, ability to utilise categorical variables without the need to transform them and not as data hungry, as for example, MRA. Originality/value – This paper adds to the knowledge in this area by applying a relatively new ML model, BRT to residential property data from a jurisdiction in Malaysia. BRT has shown promise as a strong predictive model when applied in other disciplines; therefore this research empirically tests this finding within real estate valuation.

Spatial effects and non-linearity in hedonic modeling

2018 ◽  
Vol 36 (1) ◽  
pp. 32-49 ◽  
Author(s):  
Marcelo Cajias ◽  
Sebastian Ertl
Keyword(s):  
Real Estate ◽  
Functional Form ◽  
Asymptotic Properties ◽  
Additive Model ◽  
Percentage Error ◽  
Spatial Effects ◽  
Hedonic Models ◽  
Data Set ◽  
Content Type ◽  
Out Of Sample

Purpose The purpose of this paper is to test the asymptotic properties and prediction accuracy of two innovative methods proposed along the hedonic debate: the geographically weighted regression (GWR) and the generalized additive model (GAM). Design/methodology/approach The authors assess the asymptotic properties of linear, spatial and non-linear hedonic models based on a very large data set in Germany. The employed functional form is based on the OLS, GWR and the GAM, while the estimation methodology was chosen to be iterative in forecasting, the fitted rents for each quarter based on their 1-quarter-prior functional form. The performance accuracy is measured by traditional indicators such as the error variance and the mean squared (percentage) error. Findings The results provide evidence for a clear disadvantage of the GWR model in out-of-sample forecasts. There exists a strong out-of-sample discrepancy between the GWR and the GAM models, whereas the simplicity of the OLS approach is not substantially outperformed by the GAM approach. Practical implications For policymakers, a more accurate knowledge on market dynamics via hedonic models leads to a more precise market control and to a better understanding of the local factors affecting current and future rents. For institutional researchers, instead, the findings are essential and might be used as a guide when valuing residential portfolios and forecasting cashflows. Even though this study analyses residential real estate, the results should be of interest to all forms of real estate investments. Originality/value Sample size is essential when deriving the asymptotic properties of hedonic models. Whit this study covering more than 570,000 observations, this study constitutes – to the authors’ knowledge – one of the largest data sets used for spatial real estate analysis.

Decision time for ACEES Group LLC: to buy or to lease?

2018 ◽  
Vol 14 (4) ◽  
pp. 394-426
Author(s):  
Sanjay Kudrimoti ◽  
Raminder Luther ◽  
Sanjay Jain
Keyword(s):  
Real Estate ◽  
Interest Rates ◽  
Cash Flow ◽  
Financial Management ◽  
Business Students ◽  
Primary Source ◽  
Decision Time ◽  
Business Incubator ◽  
Content Type ◽  
Real Estate Valuation

Synopsis As the move from the business incubator loomed, Abdul Khan had to decide where his business should relocate to. ACEES Group LLC, a small consulting firm, had grown from three friends working out of Abdul Khan’s house to a 20-person firm generating more than a million dollars in revenue within five years. This growth had necessitated the need for a larger and more prominent place. Although Abdul knew he did not want to renew the lease at the incubator, and he did not want to move his business too far from its current location, but the decision he had to make was whether ACEES Group should lease a commercial place or buy its own property. He was particularly torn because the real estate prices had fallen considerably, and were now on the mend and interest rates were still low. Research methodology The primary source of materials in the case was an interview with the owner (pseudo name: Abdul Khan). The owner wishes to remain anonymous. The financial statements of the firm produced in the case have been modified by a fixed factor so as to disguise the actual numbers but not materially alter the information in any fashion. Other secondary sources of materials include information about the business incubator program, the MBE certification and its benefits through the State of Florida, real estate and lease rates in Central Florida and other economic information. Relevant courses and levels This case is primarily intended for undergraduate students taking a course in entrepreneurship, real estate investments or financial management, with emphasis on real estate valuation, cash flow forecasting and/or valuation of business. Students should be familiar with time value of money concepts, understand the concept of NPV and IRR, and preferably be comfortable in the use of Excel. This instructor manual provides all calculations of space needs analysis, and discounted cash flow analysis for lease vs buy analysis. A few suggestions to discuss qualitative aspects of this decision making are also included.

Real estate development in the city of Athens during the financial crisis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maria Nikitidou ◽  
Fragiskos Archontakis ◽  
Athanasios Tagkalakis
Keyword(s):  
Financial Crisis ◽  
Real Estate ◽  
Structural Characteristics ◽  
House Prices ◽  
Real Estate Market ◽  
Structural Factors ◽  
Data Set ◽  
Content Type ◽  
Capital Financing ◽  
The City

Purpose This study aims to determine how the prices of residential properties in the Greek real estate sector are affected by their structural characteristics and by the prevailing economic factors during recession. Design/methodology/approach Based on 13,835 valuation reports for the city of Athens, covering a period of 11 years (2006–2016), this study develops a series of econometric models, taking into account both structural characteristics of the property market and the macroeconomic relevant variables. Finally, the city of Athens is divided into sub-regions and the different effects of the structural factors in each area are investigated via spatial analysis confirming the validity of the baseline model. Findings Findings show that the size, age, level, parking and storage space can explain the property price movements. Moreover, the authors find evidence that it is primarily house demand variables (e.g. the annual average wage, the unemployment rate, the user cost of capital, financing constraints and expectations about the future course of the house market) that affect house prices in a statistically significant manner and with the correct sign. Finally, using a difference-in-differences approach, this study finds that an increase in house demand (on account of net migration) led to higher house prices in smaller and older than in larger and younger apartments in areas with high concentration of immigrants. Originality/value This study uses a novel data set to help entities, individuals and policy-makers to understand how the recent economic and financial crisis has affected the real estate market in Athens.

House price index (HPI) and Covid-19 pandemic shocks: evidence from Turkey and Kazakhstan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yeşim Aliefendioğlu ◽  
Harun Tanrivermis ◽  
Monsurat Ayojimi Salami
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Housing Prices ◽  
House Price ◽  
Monthly Basis ◽  
Data Set ◽  
House Price Index ◽  
Content Type ◽  
Asymmetric Pricing ◽  
Long Run

Purpose This paper aims to investigate asymmetric pricing behaviour and impact of coronavirus (Covid-19) pandemic shocks on house price index (HPI) of Turkey and Kazakhstan. Design/methodology/approach Monthly HPIs and consumer price index (CPI) data ranges from 2010M1 to 2020M5 are used. This study uses a nonlinear autoregressive distributed lag model for empirical analysis. Findings The findings of this study reveal that the Covid-19 pandemic exerted both long-run and short-run asymmetric relationship on HPI of Turkey while in Kazakhstan, the long-run impact of Covid-19 pandemic shock is symmetrical long-run positive effect is similar in both HPI markets. Research limitations/implications The main limitations of this study are the study scope and data set due to data constraint. Several other macroeconomic variables may affect housing prices; however, variables used in this study satisfy the focus of this study in the presence of data constraint. HPI and CPI variables were made available on monthly basis for a considerably longer period which guaranteed the ranges of data set used in this study. Practical implications Despite the limitation, this study provides necessary information for authorities and prospective investors in HPI to make a sound investment decision. Originality/value This is the first study that rigorously and simultaneously examines the pricing behaviour of Turkey and Kazakhstan HPIs in relation to the Covid-19 pandemic shocks at the regional level. HPI of Kazakhstan is recognized in the global real estate transparency index but the study is rare. The study contributes to regional studies on housing price by bridging this gap in the real estate literature.

Residential property market determinants: evidence from the 2018 Australian market downturn

2019 ◽  
Vol 38 (2) ◽  
pp. 157-175
Author(s):  
Peng Yew Wong ◽  
Woon-Weng Wong ◽  
Kwabena Mintah
Keyword(s):  
Housing Market ◽  
Economic Conditions ◽  
Residential Property ◽  
Investment Fund ◽  
Property Market ◽  
Data Set ◽  
Content Type ◽  
Econometric Methods ◽  
Residential Market ◽  
Australian Bureau Of Statistics

Purpose The purpose of this paper is to validate and uncover the key determinants revolving around the Australian residential market downturn towards the 2020s. Design/methodology/approach Applying well-established time series econometric methods over a decade of data set provided by Australian Bureau of Statistics, Reserve Bank of Australia and Real Capital Analytics, the significant and emerging drivers impacting the Australian residential property market performance are explored. Findings Besides changes in the significant levels of some key traditional market drivers, housing market capital liquidity and cross-border investment fund were found to significantly impact the Australian residential property market between 2017 and 2019. The presence of some major positive economic conditions such as low interest rate, sustainable employment and population growth was perceived inadequate to uplift the Australian residential property market. The Australian housing market has performed negatively during this period mainly due to diminishing capital liquidity, excess housing supplies and retreating foreign investors. Practical implications A better understanding of the leading and emerging determinants of the residential property market will assist the policy makers to make sound decisions and effective policy changes based on the latest development in the Australian housing market. The results also provide a meaningful path for future property investments and investigations that explore country-specific effects through a comparative analysis. Originality/value The housing market determinants examined in this study revolve around the wider economic conditions in Australia that are not new. However, the coalesce analysis on the statistical results and the current housing market trends revealed some distinguishing characteristics and developments towards the 2020s Australian residential property market downturn.

scholarly journals Tax increment financing and major league venues

2020 ◽  
Vol 10 (4) ◽  
pp. 495-517
Author(s):  
Robert Sroka
Keyword(s):  
Real Estate ◽  
Future Research ◽  
Real Estate Development ◽  
Tax Increment Financing ◽  
General Reference ◽  
Data Set ◽  
Content Type ◽  
Capital Costs ◽  
Major League ◽  
Sports Venues

PurposeThis article intends to shine a light on venue-related tax increment financing (TIF) through the first comprehensive inventory of its use at the major league level.Design/methodology/approachFor each 2018 venue in the five North American major leagues, data was collected on TIF contributions to direct venue capital costs as well as to projects using TIF to enable real estate development ancillary to a venue. Neighborhoods surrounding a venue were also assessed for the presence of a TIF district. With both the direct and ancillary elements, data was collected from government, industry, academic, mapping and media sources. A review of this data set and findings are followed by a discussion of implications and directions for future work.FindingsOver one-third of the TIF eligible permanent stadiums and arenas studied in the five major leagues have a direct or strong TIF connection. Direct TIF contributions to sports venues, as well as TIF use intended to generate real estate development around these venues, are most frequent and financially significant in arenas and soccer-specific stadiums. Additionally, arena and stadium projects using TIF often accompany ancillary real estate development.Originality/valueA primary purpose of this article is to provide a previously missing general reference resource to governments and citizens of jurisdictions considering facility TIF use on the scope, nature, extent and identity of TIF projects related to major league sports venues. More generally, the inventory and assessment of TIF use in professional sports venues offered by this article sets the stage for future research on associative relationships between TIF contributions and facility finance outcomes as well as the normative value of venue-related TIF.

Capitalisation rates for commercial real estate investment decisions

2015 ◽  
Vol 33 (3) ◽  
pp. 242-255 ◽  
Author(s):  
John McDonald
Keyword(s):  
Real Estate ◽  
Commercial Real Estate ◽  
Office Buildings ◽  
Office Building ◽  
Vacancy Rate ◽  
Recent Past ◽  
Content Type ◽  
Empirical Results ◽  
Real Estate Valuation ◽  
Capitalization Rate

Purpose – The purpose of this paper is to present a basic model of commercial real estate valuation in which the capitalization rate is the critical variable, and to present empirical results for a study of office building capitalization rates. Design/methodology/approach – The model is derived from standard economic and financial theories. The empirical study uses data from the sale of office buildings in 37 downtown markets for 2012. The empirical results are related to concepts of asset market efficiency. Findings – The empirical results show that capitalization rates depend on features of the office buildings, vacancy rate, and recent change in the office building market as captured by the vacancy rate. In other words, investors are using variables implied by standard economic and financial theory and basic economic data from the recent past to determine the capitalization rate. Practical implications – The empirical results show how investors determine capitalization rates for office buildings, so potential investors can gauge the state of a property market. Originality/value – The paper shows that changes in capitalization rates are predictable; investors use past data to adjust their capitalization rates. Furthermore, if an investor does not agree that current trends will continue, then the investment decision should be determined accordingly. For example, if an investor thinks that the future will not be as robust as the recent past, then other investors will bid more than the investor thinks is reasonable. However, if the investor sees a future that is brighter than the recent past, it is time to buy.

Farm income and output and lending by the farm credit system

2017 ◽  
Vol 77 (1) ◽  
pp. 125-136 ◽  
Author(s):  
Denis Nadolnyak ◽  
Xuan Shen ◽  
Valentina Hartarska
Keyword(s):  
Real Estate ◽  
Financial Markets ◽  
Fixed Effects ◽  
Balance Sheet ◽  
State Level ◽  
Farm Income ◽  
Full Time ◽  
Data Set ◽  
Content Type ◽  
Rural Financial Markets

Purpose The purpose of this paper is to provide evidence of the positive impact of the FCS lending on farm incomes which should be useful to policymakers as they consider reforms and further support for this 100-year-old major agricultural lender. Design/methodology/approach The authors construct a panel for the 1991-2010 period from the FCS financial statements and evaluate how lending by the FCS institutions has affected farm incomes and farm output. The authors use fixed effects estimations and control for credit by other agricultural lenders as well as the stock of capital, prices, and interest rates. Since previous work suggests that rural financial markets are segmented and the FCS serves larger full-time farmers with mostly real-estate backed loans, the authors evaluate the impacts of farm real-estate backed loans and of short-term agricultural loans separately for a shorter period for which the data is available. The authors also perform robustness checks with alternative estimation techniques. Findings The authors found a positive association between credit by the FCS institutions and farm income and output. The magnitude of the estimated impact is larger during the 1990s than in the 2000s. Research limitations/implications The positive link between the FCS institutions’ credit and farm incomes and output supports the notion that the FCS lending was beneficial to farmers. The evidence also supports the segmentation hypothesis of rural financial markets. The financial reports data for 1991-2010 are from the ACAs and FLCAs aggregated on the regional level because there is no clear way to classify FCS lending to a more disaggregate level like the state. The authors also assemble and analyze a state-level data set that contains state-level balance sheet data for the period 1991-2003. Originality/value The authors are not aware of another work that directly links (real estate and non-real estate) credit by FCS institutions to agricultural output and farm incomes.

A computer-assisted expert algorithm for real estate valuation in Spanish cities

2020 ◽  
pp. 239980832094772
Author(s):  
Beatriz Larraz ◽  
José-Luis Alfaro-Navarro ◽  
Emilio L Cano ◽  
Esteban Alfaro-Cortes ◽  
Noelia Garcia ◽  
...  
Keyword(s):  
Real Estate ◽  
Arithmetic Mean ◽  
Percentage Error ◽  
Computer Assisted ◽  
Weighted Estimator ◽  
Large Cities ◽  
Equal Importance ◽  
Comparison Approach ◽  
Real Estate Valuation ◽  
Banking Institutions

Some of the most overlooked valuation systems in current literature are those based on expert algorithms. Yet these algorithms can form the basis of a good estimation of the value of real estate since they allow simple computational methods that use big data to be integrated with the appraiser’ own knowledge of the situation. The main usefulness of the methodology is an ongoing mortgage risk appraisal for banking institutions. The current expert algorithms based on the sales comparison approach use the arithmetic mean of the comparable prices. But this mean gives equal importance to all neighbouring dwellings instead of giving more importance to those dwellings which are more similar and are nearer to the target dwelling. Improving the classical arithmetic mean or the more robust median, this article proposes a computer-assisted expert algorithm which includes a weighted estimator able to consider the differences in characteristics compared to similar properties and their relative locations. It allows to estimate, in a simple and rapid way using objective criteria, the value of any residential property in Spain. The results show good fit for large cities in terms of the usual error margins while improving the results with regards to smaller cities. In all cases, in terms of mean absolute percentage error, the weighted estimator improves the arithmetic mean or median results.

Transport infrastructure, accessibility and residential property values: evidence from Hong Kong

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jayantha Wadu Mesthrige ◽  
Tayyab Maqsood
Keyword(s):  
Hong Kong ◽  
Fixed Effects ◽  
Property Values ◽  
Transport Infrastructure ◽  
Residential Property ◽  
Fixed Effects Model ◽  
Data Set ◽  
Content Type ◽  
Residential Properties ◽  
Residential Property Values

PurposeHong Kong, like many other developed cities and countries, invests heavily in transport development. This study investigates whether the speculative benefits of future improvements in accessibility, brought about by impending transport development, will be capitalized into nearby residential property values even prior to the opening of the development.Design/methodology/approachDeviating from the standard hedonic price approach, the present study employed a fixed-effects model with a large data set of residential property transactions in the vicinity of three-stations situated along a newly proposed mass-transit-railway line in Hong Kong.FindingsThe results suggest that the values of residential properties close to stations do reflect the accessibility enhancements to be brought about by transport improvements even before the opening of the line. Results revealed a 6.5% of property value premium after the announcement of construction; and higher up to 6.7% after the operation of the line. This indicates that forthcoming new transport-infrastructure development produces changes in spatial price-gradients for neighbouring residential properties. Findings indicate that potential buyers/investors recognized the positive benefits of the planned transportation development, even before completion of the project, and are ready to pay a premium for those properties close to railway stations, representing clear evidence that residential property prices/values, near stations, reflect anticipated accessibility enhancements brought about by transport improvements.Originality/valueThis study, using a novel approach – a fixed-effects model to capture the speculative benefits of future improvements in transport infrastructure – provides a positive hypothesis that expected benefits of future improvements in accessibility are capitalized into property values.

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