House Prices, Bank Instability, and Economic Growth: Evidence from the Threshold Model (Digest Summary)

The authors explore how U.S. house prices affect the instability of banks under different income growth levels. They use disaggregated data in order to take into account the heterogeneity of housing markets and acknowledge that home price effects on bank stability may be different during an economic boom than during a bust.

The recent financial crisis revealed that the state of the U.S. real estate market is indicative of the state of the U.S. economy as a whole. Given the size of the real estate market, it is reasonable to expect this dynamic to remain in place in the future. The authors focus on residential property because it accounts for 76% of outstanding debt, on average. They consider house price indices as well as price deviations from long-run fundamental values.

The authors theorize that a persistent rise in home prices increases the appetite for risk in commercial banks and thereby attracts risky borrowers. Their regression results confirm this so-called deviation hypothesis. More precisely, the authors find that house price deviations have a significantly negative impact on nonperforming loans below a certain income threshold. Above this threshold, the opposite seems to be true: Increased collateral values have a positive influence on bank stability. The authors suggest that bounded rationality may be a reason for this finding. The asymmetrical behavior of banks during booms and busts may be driven by “local thinking” (i.e., neglecting or mispricing risk, which leads to abnormal issuance of new securities). Any surprise or shock curbing a long-enduring increase in home prices can lead to severely adverse consequences.

By linking home prices to bank instability, the authors also provide some evidence for policymaking. Within metropolitan statistical areas (MSAs), there is clearly a positive long-run relationship among house prices, personal income, and labor force growth. No such relationship is found for non-MSAs. The authors further report that much larger house price deviations in non-MSAs are indicative of significant heterogeneity in housing markets throughout these areas. Thus, policies promoting personal income and labor force growth may not have a significant impact on house prices in non-MSAs.

The authors use data for MSAs for the period from 1Q1990 to 4Q2010 and define MSAs by social and economic integration. Home prices are adjusted for appraisal bias. MSAs are chosen such that there are no missing values over the sample period. To characterize bank performance, the authors use standard measures of capitalization, earnings, and liquidity. In their regressions, the authors control for such variables as bank-specific risk and overall financial conditions and then estimate a number of income thresholds sequentially. The corresponding coefficients of house price indicators are used to test the alternate hypotheses—namely, the collateral value hypothesis versus the deviation hypothesis.

The authors make certain statements about the fragility of banks as a function of house prices. Notwithstanding the side story of the direction of causality, according to this study, certain thresholds separate two regimes: When income growth is too low, overvalued home prices lead to excessive risk taking, whereas above the threshold, the increase in collateral value leads to fewer nonperforming loans. These results provide an important message for policymakers because they reveal a need for differentiation.