Determinants of housing inflation in Turkey: a conditional frequency domain causality

• DOI: https://doi.org/10.1108/IJHMA-02-2021-0013
• Published date: 15 June 2021
• Date: 15 June 2021
• Pages: 478-499
• Subject Matter: Property management & built environment,Real estate & property,Housing markets
• Author: Mustafa Kırca,Şerif Canbay

Determinants of housing inf‌lation

in Turkey: a conditional

frequency domain causality

Mustafa Kırca and Serif Canbay

Department of Economics, Akçakoca Bey Faculty of Political Sciences,

Düzce University, Düzce, Turkey

Abstract

Purpose –This study aims to investigate whether changes in consumer interest rate, exchangerate and

housing supplyhave permanent effects on housing inf‌lation in Turkey.

Design/methodology/approach –For this purpose, data from 2010M01 to 2020M06 and changes in

consumer interest rate, exchange rate, housing supply and housing inf‌lation were used. Relationships

between variables are analyzed f‌irst by the Granger causality tests and then the conditional frequency

domain causality tests. The conditional frequency domaincausality test specif‌ically reveals the permanent

causalitybetween variables, whether there is a permanent effect.

Findings –Accordingto the Granger causality test results, there are causalityrelationships from changes in

the consumer interestrate and exchange rate to housing inf‌lation. However, there is no causalityrelationship

between housing supply and housinginf‌lation. According to the conditional frequencydomain causality test

results, there is causality for the permanent and mid-term from changes in the consumer interest rate to

housing inf‌lationand causality for the mid-term and temporary from changes in the exchangerate to housing

inf‌lation. Additionally, it was foundthat there are causality relationships between changes in the consumer

interestrate and changes in the exchange rate.

Research limitations/implications –The f‌irst limit of the study is that only 2010M01-2020M06

months can be considered. Because the date that variablesstarted common is 2010M01. Besides, there is a

limit in the study in variables used. Many variables, both micro and macro, can be added to affect housing

inf‌lation.

Originality/value –Housing inf‌lation is a remarkable issue in Turkey. There is an increase in the

number of studies on the subject in recent years. For this reason, the study is trying to contribute by

approaching the subject from a different angle. The most important contribution of the study is that it has

not been investigated whether the determinants of housing inf‌lation have perman ent or temporary effects,

which were not done in previous studies. In addition, the method used reveals how many months the

effects of changes in exchange rates, consumer interest rates and housing supply on housing inf‌lation last.

Based on the f‌indings obtained from the methods, important economic and political implications have

been put forward in depth.

Keywords Turkey, Housing supply, Real exchange rate, Conditional frequency domain causality,

Consumer interest rate, Housing inf‌lation

Paper type Research paper

Introduction

Turkey has struggled with inf‌lation for many years. Although Turkey was successful in

this combat in some years, it mostly failed in the f‌ight against inf‌lation. One of the most

important indicators is that inf‌lation rates are higher than the inf‌lation targets set by the

Central Bank of the Republic of Turkey (CBRT) (2020c). When the inf‌lation targets

calculated by the CBRT and the actual inf‌lation rates for the period 2002–2020 are

examined, it is seen that the inf‌lation rate was lower thanthe targeted inf‌lation rate between

IJHMA

15,2

478

Received3 February 2021

Revised22 March 2021

Accepted30 March 2021

InternationalJournal of Housing

Marketsand Analysis

Vol.15 No. 2, 2022

pp. 478-499

© Emerald Publishing Limited

1753-8270

DOI 10.1108/IJHMA-02-2021-0013

The current issue and full text archive of this journal is available on Emerald Insight at:

https://www.emerald.com/insight/1753-8270.htm

2002 and 2005 and in 2009 and 2010. Nevertheless, inf‌lation rateswere above targets in the

other 13years. There are many sectors (product groups) that cause deviations in inf‌lation

targeting, in other words, high inf‌lation, one of which is the housing sector. Korkmaz’s

(2020) study supports this f‌inding that increasesin house prices occurring in some parts of

Turkey lead to inf‌lationary pressures. Regarding the inf‌lation rate and housing inf‌lation

rate changes between 2011 and 2020, the housing inf‌lation rate for 6 years is higher than the

inf‌lation rate in the 10 years.The housing inf‌lation rate in the specif‌ied years was 12.18% on

average, while the overall inf‌lationrate was 10.21%[1].

The fact that the housing inf‌lation rate is higher than the inf‌lation rate also increases

the housing demand of people living in Turkey, especially for investment purposes.

The most important reason for such demand is to prevent the depreciation of owned

wealth against inf‌lation. Especially with both population growth and urbanization,

people’s demand for housing also increases. After people purchase their f‌irst home,

they demand more housing, both for their own children and for investment purposes.

Besides, as in many parts of the world, life expectancy and the increasing number of

retired people in Turkey, consequently, the increase of per capita income, developments

such as the increase in foreign exchange earnings of Turkish citizens living abroad and

the development of tourism activities, especially increases the demand for second

homes (Solak and Kabadayi, 2016;Özsoy and Sahin, 2009;Cerito

glu, 2019). Residences

built in areas with high physical attractiveness, which are used by the users for

entertainment and recreation purposes at certain times of the year by purchasing or

renting, except for their actual residence, are called second homes (Manisa and Görgülü,

2018, p. 69). However, the increase in the second housing demand is also an important

problem that causes the destruction of nature in many regions, especially in natural

beauty (Malekshahi and Hosainian, 2014). Housing prices rising with the continuous

increase in housing demand make it diff‌icultfor people with low income and minimum

wage to own a house. For this reason, it is important to reveal the effects of housing

price determinants on housing inf‌lation and, in this context, how to control housing

inf‌lation.

In this context, the housing sector (construction investments) has a signif‌icant

weight in the Turkish economy. To this end, TurkStat (2020a) data reveals that in

January 2013, 87,444 units of housing were sold throughout Turkey, while this number

was 136,744 units in September 2020. Although housing sales in Turkey decreased by

6.9% in September 2020 compared to the same month of the previous year, 1,161,278

housing sales were realized in the January-September period and housing sales

increased by 34.2% on a year-over-year basis. As in the studies conducted by Çoban et

al. (2015) and Ozkan et al. (2012), many scientif‌ic studies suggested that the

construction sector is effective in Turkey’seconomicgrowth.Inthecontextofits

relationship with the inf‌lation rate and the importance of the housing market in the

Turkish economy, the investigation of the variables that affect the housing price

(inf‌lation) is an important research question.

Many researchers such as Holly and Jones (1997),Meen(2002),Apergis (2003),Égert and

Mihaljek (2007),Gattini and Hiebert (2010),Çankaya (2013),Mahalik and Mallick (2016),

Kishor and Marfatia (2017),Jehani et al. (2020) examine the relationships between housing

inf‌lation and variables including gross domestic product, inf‌lation rate, interest rate,

exchange rate, supply/demand for housing, demographic factors and unemployment rate.

Previous studies conducted in the literature indicate that the most emphasized variables

among housing inf‌lationdeterminants are interest rates, exchange rate and housing supply-

demand quantity.

Conditional

frequency

domain

causality

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