Loan to value ratios and housing prices. Evidence from Central and Eastern Europe

Abstract

By the use of econometric methods and a panel of nine Central-Eastern Europe countries (CEE-9), this thesis analyzes the effect of existing limits on loan-to-value (LTV) ratio on housing prices and, and at the same time, it looks for evidence of existing financial accelerator mechanism in CEE-9 countries over 2006q1 to 2014q1 period. Based on the model for constrained housing demand presented by Almeida et al. (2002), this thesis takes an advantage of high cross-country variability in limits on maximum LTV ratio in CEE-9 countries in order to provide evidence supporting financial accelerator theory and compare the results with the one presented by Almeida et al. (2006). The main reason why financial accelerator effect is possible with household spending is that households finance their spending by borrowing. In contrast to firms, households have no possibility to rise funds by issuing shares or bonds. They have fewer external finance alternatives. The use of property as a collateral for housing loans increases the risk of spill-over effects between housing prices and households ability to borrow. In the short-run analysis of CEE-9 countries, this thesis finds evidence supporting the hypothesis that financial accelerator is present when collateral constraint binds since the income-price sensitivity is increasing in the limits on LTV ratio and this effect is statistically significant from zero. Moreover, this effect appears to be similar in CEE-9 and OECD-26 countries. When long-run dynamics are included in the analysis (by constructing an equilibrium correction model (ECM) for housing prices), the income-price sensitivity remains statistically significant and a positive effect of a change in household income is increasing in the limits on LTV ratio as well. The use of the final consumption expenditure of households as another proxy for household income provides a robustness check for the results obtained by analyzing ECM for housing prices. Based on the results presented by the dynamic simulations, this thesis finds that higher maximum LTV ratio is associated with higher real housing price volatility.