Konut Piyasası ve Ekonomik Büyüme İlişkisi: Türkiye Üzerine Zaman Serileri Analizi (2000-2012)

KARGI, Bilal (2013): Konut Piyasası ve Ekonomik Büyüme İlişkisi: Türkiye Üzerine Zaman Serileri Analizi (2000-2012). Published in: International Journal of Human Sciences , Vol. 10, No. 1 (February 2013): pp. 897-926.

Abstract

In this study, certain selected factors about growth data and housing market within last decade are examined. Housing is a human’s physiological need and economic development can be carried out by means of extending the possibility of satisfying this high valuable need or there can be shown a linkage between economic growth and processes at market. For this reason when we handle 2000-2012 period, the indicators about economic growth and housing acquisition are being searched to explain this main hypothesis. From the obtained quarter data about concerning period, correlation relations, augmented Dickey-Fuller Unit Root Test, Granger Causality Analysis and multiple regression models are researched. Housing is a basic need but has a high cost to be met by intense savings and high burrowing. For this reason; 1- consumers’ incomes increase, 2-credit opportunities widen and 3-continuity macroeconomic performance which is giving impression of being trustworthy of a long term expenditure item. This study assumes that the most important debility of Turkey’s economy is the sensitivity of political events but especially after 2002 it’s relatively stabilized. Under his two hypothesis, we can reach that the housing market is widened. The other factors that determine housing demand (as a result of macroeconomic stability) low housing interest rates, low increase of housing prices because of low inflation and extension of banking system credit capacity. The study result in under this fundamental frame as follows. Extension of credit capacity and sensitivity of housing expenditure to gross national product (GDP) is the sign that in Turkey’s economy there is no housing balloon. Especially extension of credit capacity and housing expenditures which are acting together with GDP until 3rd quarter of 2008 is keeping it’s sensitivity to the decrease of GDP after this period but not to the extension of banking system credit capacity. According to the intense of demand according to the GDP increase and economic stability, there can be price inflation by means of probable supply constriction in the market which is arranged by interest. Although it’s not mentioned in this study, housing prices are not increased very much and it shows that supply is enough. Housing interests are drop down according to the general interest drop down related to international liquidity wideness. For this reason quantity of housing credits usage is increased. But also the other reason of increase is the extend of fixed period of time. The source of the extend of fixed period of time is the arrangements made by the law 5582. But in spite of the highness of the housing purchase cost and long term credit sources, in conclusion we can say that the consumers are following the general statement of economy and sensitive to the usage of burrowing opportunities. Likewise, after the 3rd quarter of 2008 refraction period, according to the GDP fluctuate the credit usage level is not advance as the preceding period on the contrary has a horizontal movement. The most important conclusion from the number 5 equation of regression models is the finding the change of 1 unit housing interest in GDP housing(gsyihknt) variable shows the decrease of housing expenditure at -288,35 unit. But also at %5 meaning level, from kkfo to tufeknt Granger causality relation (0.02059) and the strong (0.720992) correlation relation between this two variables indicates that housing credits are effected from inflation before all else. Decrease of inflation is the reason of Granger (0.02975) regarding to increase at GDP and also found the negative correlation (-0.641993) between this two variables. At the other regression model number (6) equity explains the housing credits of banking system. According to this model also it has not an effective rank (-0.000474), the 1 unit increase of banking system capacity decrease (-0.000474) the housing credits. The main reason is (as shown in first chapter) excessive usage of credit by both households and private sector could be said. In the other hand increase at the inflation, decreases the banking system credit capacity (-1079.328) is observed. In addition to this explanations, the increase at the banking system credit capacity is effected very much from the decreasing of interest (kkfo=3.602.661). According to the number (7) equity, the (tufeknt) variable which is used as an indicator for the housing prices is explained by GDP (5.18) and the increase at GDP also rises housing prices. Related to this, the increase at banking system credit capacity has a positive (1.41) effect on housing interest. Especially at the relation between housing prices and housing credits, the increase at housing prices has a decreasing effect (-5.64) in housing credit capacity. Also the correlation level between prices and credits supports reverse aspect relation (-0.351545). It must be mentioned that no Granger causality determined between this two variables. But there is in model’s finding about Granger causality at a level of %5 that (0.00185) designation of housing prices by GDP. Finally the increase at housing prices, increases housing interests (0.207636) unit is observed. The findings about last regression model number (8) equity is as follows. At the designation of housing credit interest, the general trend of GDP increase (-4.97), housing expenditures (-1.11), banking system housing credits (-3.02) have negative effects. Hence explanation of the decrease of housing credits is this three basic variables increase. The widening at banking system credit capacity has an increasing effect (5.88) on housing credit interests. Inflation and housing prices (tufeknt) are the two variables increasing according to the housing credit interests. In the same way, correlation relation between housing credits and inflation (0.749064) and housing prices (0.720992) is strong. Within the Granger causality tests, from housing credits to inflation (0.00068) and housing prices (0.02059) Granger causality is found. Finally in the light of this findings in Turkey’s economy at the mentioned time period a unbalanced situation and balloon formation in housing market couldn't be found. Although there is a strong bound between housing expenditures and GDP but also has a correct way and weak relation with banking system credit capacity increasing rates. In the other words, households housing demand is effected and determined by decreasing credit interest rates and inflation with GDP not the credit expansion. Thus, this shows the households sensitivity to general economic trends and acting cautiously for a long term saving and borrowing coast as in housing expenditures.

• Item Type: MPRA Paper
• English Title: Housing market and economic growth relation: time series analysis over Turkey (2000-2012)
• Language: Turkish
• Keywords: Economic Growth, Housing Market, Housing Expenditures, Housing Interests, Turkish Economy.
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models; O - Economic Development, Innovation, Technological Change, and Growth > O4 - Economic Growth and Aggregate Productivity > O40 - General; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R2 - Household Analysis > R21 - Housing Demand

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