Abstract

This paper empirically investigates the effect of the number of households on housing sales prices from a long-run perspective using the DOLS(Dynamic Ordinary Least Squares) model. Estimation results show that most of the variable estimators included in the DOLS model are consistent with the theoretical sign and are statistically significant at the 1% significance level. First, it is found that a cointegration relationship exists between housing prices, the number of households, the population, the average wage of regular workers, and the interest rate of mortgage loans. Second, the growth rate coefficient of the number of households representing the number of households showed a positive(+) value, and the t-value was greater than 2, so it was statistically significant at the 1% significance level. This means that a 1% increase in the number of households will increase housing prices by 0.18% in the long run. Therefore, for housing policies to show significant effectiveness in stabilizing housing prices, It is necessary to proactively implement housing policies by developing a prediction and evaluation simulation model based on close monitoring of the trend of growth rate of households.

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