18 Using Clustering of Panel Data to Examine Housing Demand …
185
The study consists of five section. In the first section of the study, the importance
of housing demand in terms of Turkey’s economy, Turks living abroad and foreign
countries interest in housing demand from Turkey are described. The second part
consists of extensive literature research. In the third part of the study, clustering
of panel data, k-prototype algorithm and cluster validity indexes are disclosed to
be used in the application phase. The fourth part of the research consists of the
application Clustering of panel data were made by using k-prototype algorithm for
both expatriate Turks and foreign countries with the factors affecting housing demand
and interpreted in detail. In the last section of the study, the results are given. This
study carries original research quality since clustering of panel data were made by
using k-prototypes algorithm in order to determine interest of the individuals living
outside Turkey who are demanding house in Turkey.
18.2 Literature Review
Carliner (1973) offered new evidence based on better data than has been available
to earlier researchers. Using a four-year panel study which followed up movers,
permanent income was defined and calculated in two ways. Then regressions were
run on house value and rent on permanent income, price, age, race and sex of head.
The results obtained are robust with respect to the definition of permanent income,
and considerably lower than results from time series analysis or from cross-section
studies that relied on grouped rather than individual data.
Hanushek and Quigley (1980) focused on household price sensitivity. However
other changes such as income or family size in household conditions clearly
affect housing consumption. Actually, given limited longitudinal data, information
about other demand adjustments provides valuable information about consumption
dynamics, given limited longitudinal data. Price changes can be seen as one of the
various external effects on housing demand.
Goodman (1988) addressesed the determination of permanent income, housing
price,housing demand and tenure choice. Full housing demand elasticities incorporate the interactive effects among the four stages of the model. Price and income
have major effects in the tenure choice equation. Socio demographic variables, such
asage, have complex effects that may be lost in simpler forms of estimation.
Bajari and Kahn (2005) presented a three-stage, nonparametric estimation procedure to recover willingness to pay for housing attributes. Firstly, they estimated
a nonparametric hedonic home price function. Secondly, they recovered each
consumer’s taste parameters for product characteristics using first-order conditions
for utility maximization. Finally, they estimated the distribution of household tastes
as a function of household demographics.
Nunes and Serrasqueiro (2007) showed that internal and external financing are
not perfect substitutes using panel data for the period 1999–2003, not corroborating
the theorem of Modigliani and Miller.
185
The study consists of five section. In the first section of the study, the importance
of housing demand in terms of Turkey’s economy, Turks living abroad and foreign
countries interest in housing demand from Turkey are described. The second part
consists of extensive literature research. In the third part of the study, clustering
of panel data, k-prototype algorithm and cluster validity indexes are disclosed to
be used in the application phase. The fourth part of the research consists of the
application Clustering of panel data were made by using k-prototype algorithm for
both expatriate Turks and foreign countries with the factors affecting housing demand
and interpreted in detail. In the last section of the study, the results are given. This
study carries original research quality since clustering of panel data were made by
using k-prototypes algorithm in order to determine interest of the individuals living
outside Turkey who are demanding house in Turkey.
18.2 Literature Review
Carliner (1973) offered new evidence based on better data than has been available
to earlier researchers. Using a four-year panel study which followed up movers,
permanent income was defined and calculated in two ways. Then regressions were
run on house value and rent on permanent income, price, age, race and sex of head.
The results obtained are robust with respect to the definition of permanent income,
and considerably lower than results from time series analysis or from cross-section
studies that relied on grouped rather than individual data.
Hanushek and Quigley (1980) focused on household price sensitivity. However
other changes such as income or family size in household conditions clearly
affect housing consumption. Actually, given limited longitudinal data, information
about other demand adjustments provides valuable information about consumption
dynamics, given limited longitudinal data. Price changes can be seen as one of the
various external effects on housing demand.
Goodman (1988) addressesed the determination of permanent income, housing
price,housing demand and tenure choice. Full housing demand elasticities incorporate the interactive effects among the four stages of the model. Price and income
have major effects in the tenure choice equation. Socio demographic variables, such
asage, have complex effects that may be lost in simpler forms of estimation.
Bajari and Kahn (2005) presented a three-stage, nonparametric estimation procedure to recover willingness to pay for housing attributes. Firstly, they estimated
a nonparametric hedonic home price function. Secondly, they recovered each
consumer’s taste parameters for product characteristics using first-order conditions
for utility maximization. Finally, they estimated the distribution of household tastes
as a function of household demographics.
Nunes and Serrasqueiro (2007) showed that internal and external financing are
not perfect substitutes using panel data for the period 1999–2003, not corroborating
the theorem of Modigliani and Miller.