194
Ö. Akay et al.
the optimal number of clusters as 9. According to the result of clustering; The expectations of Turkish citizens living abroad and foreigners’ housing demands have shown
similarity.
Expatriates and foreigners mostly want the houses they buy for investment and
holiday purposes to be both economical and durable. Expatriates, who prefer summer
locations, hometowns and metropolitan cities in the purchase of real estate, revive
the housing market. In addition, the high course of foreign exchange, like expatriates,
stimulates foreign buyers in housing purchases. Experts in the housing sector state
that the VAT advantage granted to foreigners is also granted to Turks residing abroad
for more than 6 months with work and residence permits. As a result, the housing
market experts predict that there will be significant activity in the Turkish housing
market if foreign housing increases and private housing campaigns are provided to
expatriate Turks and foreigners.
References
Ahmad A, Iqbal N, Siddiqui R (2018) Determinants of housing demand in urban areas of Pakistan:
evidence from the PSLM. Pakistan Dev Rev 57:1–25
Akay Ö, Yüksel G (2018) Clustering the mixed panel dataset using Gower’s distance and
k-prototypes algorithms. Commun Stat Simul Comput 47:3031–3041
Akay Ö, Yüksel G (2019) Hierarchical clustering of mixed variable panel data based on new
distance. Commun Stat Simul Comput 1–16
Bajari P, Kahn ME (2005) Estimating housing demand with an application to explaining racial
segregation in cities. J Bus Econ Stat 2:20–33
Bonzo DC, Hermosilla AY (2002) Clustering panel data via perturbed adaptive simulated annealing
and genetic algorithms. Adv Comp Syst 5:339–360
Carliner G (1973) Income elasticity of housing demand. Rev Econ Stat 55:528–532
Charrad M, Ghazzali N, Boiteau V, Niknafs A (2012) NbClust package: finding the relevant number
of clusters in a dataset. J Stat Softw, Softw
Çelik C, Kıral G (2018a) Kümeleme yöntemiyle konut talebinin incelenmesi: Türkiye il grupları
üzerine bir uygulama. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 27:123–138
Çelik C, Kıral G (2018b) Yurtdı¸ sı yerle¸ siklerin ve dı¸ s ülkelerin konut taleplerini incelemede panel
kümeleme analizi: Türkiye illeri örne˘ gi. Çukurova Üniversitesi ˙ Iktisadi Ve ˙ Idari Bilimler Fakültesi
Dergisi 22:305–324
Davis M, Oliner S, Peter T, Pinto E (2017) The impact of interest rates on house prices and housing
demand: evidence from a quasi-experiment. Working Paper
Do TL, Nguyen TT, Grote U (2019) Livestock production, rural poverty, and perceived shocks:
evidence from panel data for Vietnam. J Dev Stud 55:99–119
Goodman AC (1988) An econometric model of housing price, permanent income, tenure choice,
and housing demand. J Urban Econ 23:327–353
Hanushek EA, Quigley JM (1980) What is the price elasticity of housing demand? Rev Econ Stat
62:449–454
Huarng KH, Yu THK, Rodriguez-Garcia M (2019) Qualitative analysis of housing demand using
Google trends data. Econ Res Ekonomska Istraživanja 409–419
Hou F, Ai K (2015) The empirical research of relationship between consumption and income for
Chinese urban residents. Open J Appl Sci 5:251
Huang ZX (1998) Extensions to the k-means algorithm for clustering large datasets with categorical
values. Data Min Knowl Disc 2:283–304
Ö. Akay et al.
the optimal number of clusters as 9. According to the result of clustering; The expectations of Turkish citizens living abroad and foreigners’ housing demands have shown
similarity.
Expatriates and foreigners mostly want the houses they buy for investment and
holiday purposes to be both economical and durable. Expatriates, who prefer summer
locations, hometowns and metropolitan cities in the purchase of real estate, revive
the housing market. In addition, the high course of foreign exchange, like expatriates,
stimulates foreign buyers in housing purchases. Experts in the housing sector state
that the VAT advantage granted to foreigners is also granted to Turks residing abroad
for more than 6 months with work and residence permits. As a result, the housing
market experts predict that there will be significant activity in the Turkish housing
market if foreign housing increases and private housing campaigns are provided to
expatriate Turks and foreigners.
References
Ahmad A, Iqbal N, Siddiqui R (2018) Determinants of housing demand in urban areas of Pakistan:
evidence from the PSLM. Pakistan Dev Rev 57:1–25
Akay Ö, Yüksel G (2018) Clustering the mixed panel dataset using Gower’s distance and
k-prototypes algorithms. Commun Stat Simul Comput 47:3031–3041
Akay Ö, Yüksel G (2019) Hierarchical clustering of mixed variable panel data based on new
distance. Commun Stat Simul Comput 1–16
Bajari P, Kahn ME (2005) Estimating housing demand with an application to explaining racial
segregation in cities. J Bus Econ Stat 2:20–33
Bonzo DC, Hermosilla AY (2002) Clustering panel data via perturbed adaptive simulated annealing
and genetic algorithms. Adv Comp Syst 5:339–360
Carliner G (1973) Income elasticity of housing demand. Rev Econ Stat 55:528–532
Charrad M, Ghazzali N, Boiteau V, Niknafs A (2012) NbClust package: finding the relevant number
of clusters in a dataset. J Stat Softw, Softw
Çelik C, Kıral G (2018a) Kümeleme yöntemiyle konut talebinin incelenmesi: Türkiye il grupları
üzerine bir uygulama. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 27:123–138
Çelik C, Kıral G (2018b) Yurtdı¸ sı yerle¸ siklerin ve dı¸ s ülkelerin konut taleplerini incelemede panel
kümeleme analizi: Türkiye illeri örne˘ gi. Çukurova Üniversitesi ˙ Iktisadi Ve ˙ Idari Bilimler Fakültesi
Dergisi 22:305–324
Davis M, Oliner S, Peter T, Pinto E (2017) The impact of interest rates on house prices and housing
demand: evidence from a quasi-experiment. Working Paper
Do TL, Nguyen TT, Grote U (2019) Livestock production, rural poverty, and perceived shocks:
evidence from panel data for Vietnam. J Dev Stud 55:99–119
Goodman AC (1988) An econometric model of housing price, permanent income, tenure choice,
and housing demand. J Urban Econ 23:327–353
Hanushek EA, Quigley JM (1980) What is the price elasticity of housing demand? Rev Econ Stat
62:449–454
Huarng KH, Yu THK, Rodriguez-Garcia M (2019) Qualitative analysis of housing demand using
Google trends data. Econ Res Ekonomska Istraživanja 409–419
Hou F, Ai K (2015) The empirical research of relationship between consumption and income for
Chinese urban residents. Open J Appl Sci 5:251
Huang ZX (1998) Extensions to the k-means algorithm for clustering large datasets with categorical
values. Data Min Knowl Disc 2:283–304