Booming house prices are historically correlated with loose lending standards. Nonetheless, in Spain the loan-to-value (LTV) ratio failed to capture imbalances during the last housing boom. Using loan-level data from millions of mortgages we show that inflated collateral valuations, used by banks as a mechanism to circumvent regulation, distorted the informative value of LTV, and masked the accumulation of risk. We identify that regulation relying upon a single measure is more prone to suffer from regulatory arbitrage, and that the optimal policy mix varies over the financial cycle. Overall, our study provides useful insights for the implementation of borrower-based measures. 

I uncover heterogeneous effects of macroprudential policy on GDP growth distribution by bringing together the literature on the impact of macroprudential policy and recent developments on the use of quantile regressions. I identify important benefits of macroprudential policy on the left-tail of the GDP growth distribution which contrast with the negative effects found in previous studies using conditional mean models. These benefits may offset the deterioration on growth-at-risk produced by the build-up of cyclical vulnerabilities and the materialization of financial crises. I also find that the impact of macroprudential policy is dependent on the position in the financial cycle, the type of instrument, and the time elapsed since its implementation. In particular, tightening capital measures during expansions may take up to two years to show evidence of benefits on growth-at-risk, while the positive impact of borrower-based measures is rapidly observed. Conversely, in downturns the benefits of loosening capital measures are more immediate, while those of borrower-based measures are limited. This suggests the importance of timing in macroprudential policy. Overall, this study provides a useful framework to assess the impact of macroprudential policy in terms of GDP growth and to identify the term-structure of specific instruments. 

We assess, for the first time in the literature, the impact of green credit on bank efficiency. We find that green credit has a negative impact on bank efficiency. However, the effect is heterogeneous among different types of banks. While small and low capitalized banks are more affected, the impact is lower in banks with higher levels of risk. On the other hand, we find that highly capitalized banks can offset the negative effects of green credit, while large banks and those highly involved in green credit, benefit from this activity. 

The credit-to-GDP gap, as proposed by the Basel methodology, is the reference measure for the activation of the Countercyclical Capital Buffer. However, most of the countries implementing this instrument in recent years are not following its signals due to the large downward biases that it is presenting after the last financial crisis that do not reflect properly the current macrofinancial environment. In this context, credit gap measures that incorporate economic fundamentals may provide more accurate signals of cyclical systemic risk. We propose two alternative model-based indicators that account for these factors. We assess their performance using time series data from the 1970s for six European countries and compare them to the Basel gap. We find that our proposed models provide more accurate early warning signals of the build-up of cyclical systemic risk than the Basel gap, as well as lower biases after rapid changes in fundamentals. Furthermore, we identify the model specifications that are optimal for each of the countries considered. Our flexible approach can easily accommodate national specificities, which are key to maximize the performance of the models.

We analyse the drivers of total factor productivity of Spanish banks from early 2000, including the last financial crisis and the post-crisis period. This allows us to study changes in productivity following a major restructuring process in the banking sector such as the one experienced in Spain. Overall, we find that following a period of continued growth, productivity declined after the height of the crisis, though large banks were less affected. We also find that risk, capital levels, competition and input prices were important drivers of the differences in productivity change between banks. Finally, our results suggest that, by the end of our sample period, there was still some room for potential improvements in productivity via exploiting scale economies and enhancing cost efficiency. These opportunities appear to be generally greater for the smaller banks in our sample.

This paper shows evidence on the influence of risk-taking on bank efficiency in emerging markets and identifies heterogeneity in the way risk affects banks with different characteristics. We fit a stochastic frontier model with random inefficiency parameters to a sample of Colombian banks. The model provides accurate cost and profit efficiency estimates. The effects of risk-taking on efficiency vary with size and affiliation. Large and foreign banks benefit more from higher exposure to credit and market risk, while domestic and small banks from being more capitalised. We identify some channels explaining these differences and provide insights for prudential regulation. 

Firms face a continuous process of technological and environmental changes that requires them to make managerial decisions in a dynamic context. However, costs and constraints prevent firms from making instant adjustments towards optimal conditions and may cause inefficiency to persist in time. We propose a dynamic inefficiency specification that captures differences in the adjustment costs among firms and non-persistent effects of inefficiency heterogeneity. The model is fitted to a ten year sample of Colombian banks. The new specification improves model fit and have effects on efficiency estimations. Overall, Colombian banks present high inefficiency persistence but important differences between institutions are found. In particular, merged banks present low adjustment costs that allow them to recover rapidly efficiency losses derived from merging processes. 

The electricity reform in Colombia has exhibited gains in terms of reliability but its effects on firm efficiency and service quality have not been clear. Previous studies evaluating the performance of distribution companies after the reform have not found evidence of improvements, although large differences in efficiency have been found among firms. This suggests high inefficiency persistence and heterogeneity in the Colombian distribution sector. In this paper, we propose an extension of dynamic stochastic frontier models that accounts for unobserved heterogeneity in the inefficiency persistence and in the technology. The model incorporates total expenses, service quality and energy losses in an efficiency analysis of Colombian distributors over fifteen years after the reform. We identify the presence of high inefficiency persistence in the sector, and important differences between firms. In particular, rural companies and firms with small customers present low persistence and evidence the largest gains in efficiency during the period. However, increases in efficiency are only manifested during thelast five years when the main improvements in service quality and energy losses are presented. Overall, inefficiency persistence, customer density and consumption density are found to be important criteria to be considered for regulatory purposes.

Estimation of the one sided error component in stochastic frontier models may erroneously attribute firm characteristics to inefficiency if heterogeneity is unaccounted for. However, unobserved inefficiency heterogeneity has been little explored. In this work, we propose to capture it through a random parameter which may affect the location, scale, or both parameters of a truncated normal inefficiency distribution using a Bayesian approach. Our findings using two real data sets, suggest that the inclusion of a random parameter in the inefficiency distribution is able to capture latent heterogeneity and can be used to validate the suitability of observed covariates to distinguish heterogeneity from inefficiency. Relevant effects are also found on separating and shrinking individual posterior efficiency distributions when heterogeneity affects the location and scale parameters of the one-sided error distribution, and consequently affecting the estimated mean efficiency scores and rankings. In particular, including heterogeneity simultaneously in both parameters of the inefficiency distribution in models that satisfy the scaling property leads to a decrease in the uncertainty around the mean scores and less overlapping of the posterior efficiency distributions, which provides both more reliable efficiency scores and rankings.

I show that macroprudential policy has significant heterogeneous and time-varying effects on the credit growth distribution. These effects are particularly evident in reducing rightward skewness during expansionary periods of the financial cycle, thereby mitigating the upside risk of credit growth. Conversely, during financial crises, the relaxation of macroprudential policy positively impacts the left tail, reducing the risk of severe credit contractions. These findings align with previously documented benefits of macroprudential policy on the downside risk of GDP growth, providing evidence of the mechanism through which these policies act via credit growth. I also identify interactions between macroprudential policy, bank profitability and monetary policy. High bank profitability limits the effectiveness of macroprudential policy in curbing excessive credit growth, while macroprudential policy complements monetary policy by targeting tail risks, which affects the credit growth distribution more uniformly. I also find significant disparities based on the type of tool implemented and the sector targeted. Borrower-based measures are particularly effective in moderating household credit during expansions, whereas capital releases are especially supportive of credit to non-financial corporations during crises.

We provide compelling evidence of the association between credit standards at loan origination in the corporate sector and default risk, a topic that has received little attention in the literature in comparison to the study of this relationship in the mortgage market. Using data from the Spanish credit register merged with corporate balance sheet information spanning the last financial cycle, we demonstrate that leverage and debt burden ratios at loan origination are key predictors of future corporate loan defaults. We also show that the deterioration in lending standards is strongly correlated to the buildup of cyclical systemic risk during periods of financial expansions. Specifically, limits on the debt-to-assets ratio and the interest coverage ratio could serve as effective tools to mitigate credit risk during economic expansions. We identify that the strength of these associations varies significantly across different sectors and is dependent on firms’ size, age and the existence of prior relationships with the bank. Real estate firms and small and medium-sized enterprises exhibit the strongest relationship between credit standards and future default. Overall, our findings provide strong support for the effectiveness of macroprudential measures targeting the corporate sector and contribute to providing guidance for the implementation of borrower-based measures in key segments of corporate credit.

The countercyclical capital buffer (CCyB) has become a very important macroprudential tool to strengthen banks’ resilience. However, there is still limited evidence of its impact on lending over the cycle. Using data of 170 banks in 25 European Union countries, we provide a comprehensive assessment of how the CCyB release during the pandemic and its earlier accumulation impacted lending activity. We find that the CCyB has significant effects on lending, but that these effects are highly dependent on banks’ capitalization levels and, more importantly, on their headroom over regulatory requirements. We show that the release of the CCyB in response to the pandemic had a positive impact on lending, especially for banks with the lowest headroom over requirements, and that this effect was larger than the negative impact of its previous accumulation. While the CCyB accumulation had a short-term negative impact on lending for the most capitalconstrained banks, this effect quickly diluted due to their enhanced solvency position, potentially allowing them to lower their cost of equity. Our results provide evidence of the benefits of the CCyB, especially in supporting lending during adverse events, while emphasising the need for policymakers to consider the heterogeneous effects across banks when deploying this tool.