Identification of Wealthy Households from the Residential Property Price Index Database for Sample Selection for Household Surveys

Identification of Wealthy Households from the Residential Property Price Index Database for Sample Selection for Household Surveys

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Evren Ceritoğlu, Özlem Sevinç

English

October 2020

This paper aims to identify wealthy households in Turkey for sample selection for household surveys. In the absence of income and wealth tax data, we analyze house prices from the Residential Property Price Index (RPPI), which is constructed by the Central Bank of the Republic of Turkey (CBRT) from dwelling appraisal reports to monitor price movements. RPPI is announced monthly by the CBRT for Turkey and 26 geographical regions at NUTS2 level since 2012, but data actually starts from January 2010. The RPPI database comprises more appraisal observations from İstanbul and western provinces, where house prices are significantly higher than country average. However, the number of appraisal observations is low for the Eastern provinces, since the number of house sales is limited in poor and small provinces. Moreover, the percentage of mortgaged house sales is even lower in these regions, whereas the RPPI database is based on dwelling appraisal reports on house sales, which are subject to mortgage loans.

We examine unit house prices from the CBRT – RPPI database from 2010 to 2018 at province, district and neighborhood levels. Unit house prices are calculated by dividing the value (TL) to the gross usage area (m2) at current prices. Only neighborhoods with 30 or more observations are examined in the analysis. We discuss the validity of the hypothesis that there is a direct relationship between unit house prices and the number of home appraisals. We regress the natural logarithm of the number of home appraisals on the natural logarithm of unit house prices using mean values. We perform fixed effects regressions at both neighborhood and province levels using our unbalanced and balanced panel data sets. We control for year effects by introducing time dummy variables into the regressions. We find that there is a positive and statistically significant relationship between unit house prices and the number of home appraisals. Moreover, we perform the same regressions for neighborhoods that have more than 100 observations as a robustness check. We observe that the size and the sign of the regression coefficients do not change when we restrict our data set.

The direction of the relationship might be from the number of home appraisals to unit house prices or it could be both ways. For that reason, as another robustness check, we regress the natural logarithm of unit house prices on the natural logarithm of the number of home appraisals. We observe that there is a statistically significant relationship between the number of home appraisals and unit house prices. However, the size of the regression coefficients is considerably lower in this case. As a result, our empirical analysis indicates that the number of observations is higher in administrative units, where house prices are higher. Therefore, we argue that identification of wealthy households according to their neighborhoods using the RPPI database is a reliable and consistent method for oversampling for household surveys in Turkey.

Unit house prices, Wealthy households, Panel data, Sampling design, Oversampling

C33; C83; R21; R31; R32