Factors affecting housing prices in Izmir, Turkey: a quantile regression approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Onur Özsoy ◽  
Hasan Şahin
Keyword(s):  
Quantile Regression ◽  
House Prices ◽  
Housing Prices ◽  
Least Square ◽  
Policy Implications ◽  
Content Type ◽  
Factors Affecting ◽  
Ordinary Least Square ◽  
Major Factors ◽  
Quantile Regression Method

Purpose The purpose of this paper is to investigate empirically the main factors that affect the house prices in Izmir, Turkey using the quantile regression and ordinary least square approaches. Design/methodology/approach Sample data about the housing market for Izmir collected from the web pages of various real estate agencies during June 2018. Following this, the quantile regression method is used to estimate all possible effects of variables on each interested quantile to determine the factors that affect house prices to guide the potential consumers, house developers, city planners and the policymakers in Izmir, Turkey. Findings Results show that the age of the house, central heating and parking have no significant effect on prices. The size of the house, the existence of an elevator, fire and security have a positive and significant effect on prices. The number of rooms has lower values for high-priced houses, while the floor, the number of balconies, air conditioning, proximity to schools have a higher value for high-priced houses. The number of toilets, the number of bathrooms and the distance to the hospital have a lower value on the high-priced housing. The value of the distance from the city center and the shopping center is almost uniform in all quantiles and lowers the value of the higher-priced houses. With the exception of the value of the houses in the 10th percentile in Balcova district, the value of the houses in Konak, Balcova and Narlidere is lower prices in Karsiyaka. Originality/value This is the first comprehensive research to determine the major factors that affect house prices in Izmir. The second contribution of this paper is that it includes all possible variables and accordingly derives adequate policy implications, which could be used both by the public housing authority and private housing constructing companies in designing and implementing effective housing policies.

Determinants of dividend payout of Indian manufacturing companies

2018 ◽  
Vol 10 (4) ◽  
pp. 364-376 ◽  
Author(s):  
Bhanu Pratap Singh Thakur ◽  
M. Kannadhasan
Keyword(s):  
Quantile Regression ◽  
Dividend Policy ◽  
Least Square ◽  
Firm Characteristics ◽  
Manufacturing Companies ◽  
Growth Opportunities ◽  
Content Type ◽  
Ordinary Least Square ◽  
Quantile Regression Method ◽  
Different Levels

Purpose The purpose of this study is to examine the influence of firm characteristics such as profitability, growth opportunities, size, leverage and maturity on dividend policy of Indian firms. Design/methodology/approach The study analyzes the determinants of dividend policy of manufacturing firms in India using panel data. Because of the non-linearity behaviour of dividend pay-out by firms, the study uses quantile regression method to examine whether the determinants of dividends vary depending on the company’s level of dividends. Findings Overall, the results show important difference between ordinary least square and quantile regression estimates and depict differential effect on dividend at different levels. The notable difference occurs because either the significance changes (e.g. for profitability and growth opportunities) or because the magnitude of coefficients changes (e.g. for size, profitability and growth opportunities). Originality/value This finding is useful in identifying the dividend issuing companies. Further, results of this study would be helpful to the mangers to manage their financial positions that subsequently help in retaining and attracting the probable investors.

Dynamic effects and spatial heterogeneity of land supply on housing price: evidence from Nanchang, China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhijiang Wu ◽  
Yongxiang Wang ◽  
Wei Liu
Keyword(s):  
Spatial Heterogeneity ◽  
House Prices ◽  
Housing Prices ◽  
Housing Price ◽  
Dynamic Effects ◽  
Negative Effects ◽  
Land Supply ◽  
Content Type ◽  
Major Factors ◽  
The City

Purpose Economic fundamentals are recognized as determining factors for housing on the city level, but the relationship between housing price and land supply has been disputed. This study aims to examine what kind of impact housing prices have on land supply and whether there is heterogeneity in different regional spaces. Design/methodology/approach This study collects the relevant data of land supply and housing prices in Nanchang from 2010 to 2018, constructs a vector autoregression (VAR) model, including one external factor and four internal factors of land supply to explore the dynamic effects and spatial heterogeneity of land supply on housing prices through regression analysis. Also, the authors use the geographic detector to analyze the spatial heterogeneity of housing prices in Nanchang. Findings This study found that the interaction between land supply and housing price is extremely complex because of the significant differences in the study area; the variables of land supply have both positive and negative effects on housing price, and the actual effect varies with the region; and residential land and GDP are the two major factors leading to the spatial heterogeneity in housing price. Research limitations/implications The dynamic effects of land supply on housing price are mainly reflected in the center and edge of the city, the new development area, and the old town, which is consistent with the spatial pattern of the double core, three circles and five groups in Nanchang. Originality/value This is a novel work to analyze the dynamic effects of land supply on house prices, instead of a single amount of land supply or land prices. Furthermore, the authors also explore the spatial heterogeneity according to the regional characteristics, which is conducive to targeted policymaking.

scholarly journals Factors Affecting the Perceptions of Small-Scale Organic Farmers in South Africa: An OLS Approach

2018 ◽  
Vol 10 (2) ◽  
pp. 14
Author(s):  
Gabriel Adewunmi Eyinade ◽  
Celestine Ohi Akharume
Keyword(s):  
South Africa ◽  
Organic Farming ◽  
Least Square ◽  
Small Scale ◽  
Income Generation ◽  
Factors Affecting ◽  
Ordinary Least Square ◽  
Organic Farmers ◽  
Ordinary Least Square Regression ◽  
Major Factors

Much investments have been tailored towards organic farming by several stakeholders in recent years. Reasons for these are poverty mitigation, income generation as well as food security and good dietary diets. Unfortunately, there are no significant improvements in those areas where organic farming has been funded and encouraged. The study aims at identifying factors affecting the perceptions of small-scale organic farmers using ordinary least square regression model (OLS). One hundred and sixty structure questionnaires were administered on 160 small-scale organic farmers in Amathole District Municipality to gather data for the study. The results revealed that gender and educational level are the major factors affecting the perceptions of small-scale organic farmers in South Africa. Nevertheless, to open the prospective of smallscale organic farmers, the study suggested that these farmers should have greater access to extension services and support. This will go a long way in assisting the farmers to diversify and improve their production, thus enhancing livelihoods and creating markets for organic foods.  

scholarly journals Factors Affecting the Perceptions of Small-Scale Organic Farmers in South Africa: An OLS Approach

2018 ◽  
Vol 10 (2(J)) ◽  
pp. 14-19
Author(s):  
Gabriel Adewunmi Eyinade ◽  
Celestine Ohi Akharume
Keyword(s):  
South Africa ◽  
Organic Farming ◽  
Least Square ◽  
Small Scale ◽  
Income Generation ◽  
Factors Affecting ◽  
Ordinary Least Square ◽  
Organic Farmers ◽  
Ordinary Least Square Regression ◽  
Major Factors

Much investments have been tailored towards organic farming by several stakeholders in recent years. Reasons for these are poverty mitigation, income generation as well as food security and good dietary diets. Unfortunately, there are no significant improvements in those areas where organic farming has been funded and encouraged. The study aims at identifying factors affecting the perceptions of small-scale organic farmers using ordinary least square regression model (OLS). One hundred and sixty structure questionnaires were administered on 160 small-scale organic farmers in Amathole District Municipality to gather data for the study. The results revealed that gender and educational level are the major factors affecting the perceptions of small-scale organic farmers in South Africa. Nevertheless, to open the prospective of smallscale organic farmers, the study suggested that these farmers should have greater access to extension services and support. This will go a long way in assisting the farmers to diversify and improve their production, thus enhancing livelihoods and creating markets for organic foods.  

DETERMINANTS OF DEMAND FOR GAMBLING/OFFICE FOOTBALL POOL BETTING IN IBADAN, OYO STATE, NIGERIA

2013 ◽  
Vol 6 (2) ◽  
pp. 69-81
Author(s):  
Cecilia Nwigwe ◽  
S.A. Yusuf ◽  
V.O. Okoruwa
Keyword(s):  
Econometric Model ◽  
Statistical Significance ◽  
Demographic Variables ◽  
Least Square ◽  
Monthly Income ◽  
Factors Affecting ◽  
Ordinary Least Square ◽  
Government Involvement ◽  
Major Factors ◽  
Gambling Activities

In the present study, we evaluated the statistical significance of a number of socioeconomic and demographic variables on the demand for office football pool betting in Ibadan, Oyo State of Nigeria. The Ordinary Least Square (OLS) econometric model was employed. The study identifies the socioeconomic and demographic characteristics of the gamblers and econometrically analyzed the factors influencing gambling activities. The results showed that gender, age, household size, educational attainment, occupation, monthly income of pool bettors, as well as price of coupons, were among the major factors affecting the demand for office football pool betting. To the extent that our sample may be representative of a wide and broader set of circumstances, our finding led to the recommendation of policy and institutions that support government involvement in gambling activities, especially office football pool betting. 

Determinants of house price volatility in Namibia

2019 ◽  
Vol 12 (4) ◽  
pp. 807-823 ◽  
Author(s):  
Teresia Kaulihowa ◽  
Katrina Kamati
Keyword(s):  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Price Volatility ◽  
Policy Implications ◽  
Mortgage Loans ◽  
Causal Relations ◽  
Content Type ◽  
House Price Volatility ◽  
Macroeconomic Determinants

Purpose This paper aims to test the volatility and analyses the macroeconomic determinants of house price volatility in Namibia over the period 2007 Quarter 1 to 2017 Quarter 2. It further explores the causal relations between house price volatility and its determinants. Design/methodology/approach The study used autoregressive conditional heteroskedastic and generalized autoregressive conditional heteroskedastic models to test for volatility. The vector error correction model was used to analyse the determinants and causal relations. Findings The results support the hypothesis that house prices in Namibia exhibits persistent volatility. It was further established that past period volatility’ GDP and mortgage loans are the key determinants of house price volatility. Additionally’ there exists unidirectional causality from GDP and mortgage loans to house price volatility. Practical implications Policy implications emanating from the study implies that macroeconomic fundamentals should be monitored closely to mitigate the issues of house price volatility. Originality/value The study is the first of its kind in Namibia to address the pertinent issues of ever increasing housing prices.

scholarly journals The interaction between housing prices and housing credit: evidence from a country with rapid credit accumulation

2020 ◽  
Vol 48 (1) ◽  
pp. 191-209
Author(s):  
Juan Carlos Cuestas ◽  
Merike Kukk
Keyword(s):  
Design Methodology ◽  
House Prices ◽  
Housing Prices ◽  
Central Banks ◽  
Policy Implications ◽  
Real Economy ◽  
Content Type ◽  
Debt Accumulation ◽  
Econometric Methods ◽  
Hard Times

PurposeThis paper aims to investigate the mutual dependence between housing prices and housing credit in Estonia, a country that experienced rapid debt accumulation during the 2000s and big swings in house prices during that period.Design/methodology/approachThe authors use Bayesian econometric methods on data spanning 2000–2015.FindingsThe estimations show the interdependence between house prices and housing credit. More importantly, negative housing credit innovations had a stronger effect on house prices than positive ones.Originality/valueThe asymmetry in the linkage between housing credit and house prices highlights important policy implications, in that if central banks increase capital buffers during good times, they can release credit conditions during hard times to alleviate the negative spillover into house prices and the real economy.

Tacit knowledge transfer in coopetition

2017 ◽  
Vol 10 (4) ◽  
pp. 453-468 ◽  
Author(s):  
Amit Kumar ◽  
Swarup Kumar Dutta
Keyword(s):  
Knowledge Transfer ◽  
Tacit Knowledge ◽  
Least Square ◽  
Service Firms ◽  
Content Type ◽  
Ordinary Least Square ◽  
Tacit Knowledge Transfer ◽  
Potential Benefits ◽  
Ordinary Least Square Regression ◽  
Empirical Context

Purpose The purpose of this paper is to understand how firms affiliated to business groups (BGs) are able to improve their innovation capability (IC) when engaged in coopetition (collaboration between competing firms). This study aims to explore the relationship between coopetitive relationship strength (CRS), the extent of tacit knowledge transfer (TKT) and IC as well as examine the moderating effect of both BG affiliation and coopetitive experience. Design/methodology/approach The paper examines inter-firm relationships within the empirical context of Indian manufacturing and service firms, by adopting (ordinary least square) regression analysis to test the various hypotheses. The central thesis is that the TKT in coopetition constitutes an important driver to the IC. Findings The paper provides some evidence that inter-firm CRS influences the extent of TKT, and the extent of TKT affects firm IC. The results support that firms in coopetition gain more if their coopetitive partner has a BG affiliation. In absence of a BG affiliation of any of the coopetitive partners, the buildup of TKT reduces as CRS is increased. Research limitations/implications Additional large-sample of data may attempt to validate relationships. The study, however, did not consider all enablers that are critical for TKT. Despite these limitations, analysis provides important and novel perspectives. Practical implications The paper contributes to develop executives’ practices in understanding potential benefits of coopetitive relationship. The implications of this research are important for managers seeking understanding of the management of coopetition. Originality/value The paper makes a modest attempt to investigate the various scenarios of the presence or absence of the moderation of BGs and its impact on CRS in the buildup of TKT. This is the first attempt to link coopetition to the TKT in the BG literature. This study also contributes to our understanding of coopetition in a non-western context.

Exploring sectoral diversity in the timing of organizational blockchain adoption

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Cigdem Turhan ◽  
Ibrahim Akman
Keyword(s):  
New Technology ◽  
Organizational Factors ◽  
Ease Of Use ◽  
Least Square ◽  
Management Support ◽  
Perceived Ease Of Use ◽  
Organizational Strategies ◽  
Content Type ◽  
Factors Affecting ◽  
Blockchain Technology

PurposeBlockchain is a relatively new technology. Although it has a high potential to influence organizational strategies for adoption into respective operations, it has not been widely explored yet. This study aims to assess the sectoral diversity in the timing of organizational adoption of blockchain through selected organizational factors.Design/methodology/approachA survey was conducted based on a sample of 208 IT professionals. The data was collected using an instrument containing 17 questions. The existence of sector diversity was statistically analyzed using the Least Square Regression method.FindingsThe results indicate that, except for management support and perceived ease of use, all the other factors in the analysis significantly influence sector diversity in terms of blockchain adoption timing.Originality/valueAlthough blockchain has received attention from researchers, to the best of the authors' knowledge, there is no published work in the literature that explores the organizational factors influencing sectoral differences in the timing of blockchain technology adoption. Therefore, our work is unique in the related literature since we present analyses for the diversity between public and private sectors by modeling the factors affecting the intentions for the timing of blockchain adoption as part of the organizations' IT infrastructure.

Users’ perception of cybersecurity, trust and cloud computing providers’ performance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hongjiang Xu ◽  
Sakthi Mahenthiran
Keyword(s):  
Cloud Computing ◽  
Structural Equation ◽  
Design Methodology ◽  
Positive Relationship ◽  
Least Square ◽  
Equation Modeling ◽  
Content Type ◽  
Ordinary Least Square ◽  
Ordinary Least Square Regression ◽  
Computing Literature

Purpose This study aims to develop a scale to measure the cloud provider’s performance and it investigates the factors that impact that performance from the users’ perspective. Design/methodology/approach This paper proposes a research framework, develops hypotheses and conducts a survey to test the framework. Findings The results from both ordinary least square regression and structural equation modeling analyzes indicate that information technology complexity negatively and significantly affects users’ perception of the cloud computing providers’ performance. Additionally, the trust in the supervisor significantly enhances the otherwise insignificant positive relationship between providers’ cybersecurity capability and users’ perception of their providers’ performance. Originality/value The research makes important contributions to the cloud computing literature, as it measures users’ perception of the cloud computing provider’s performance and links it with cybersecurity, technical complexity and incorporates both the trust in the client firm’s supervisor and the strength of cybersecurity offered by cloud computing provider.

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