Search results

The purpose of this paper is to examine the effects of the 2007-2009 uncertainty shocks on policymakers’ behavior.

Uncertainty shocks in the US credit, financial and production markets are represented by extraordinary events. As in Bloom (2009), these events are associated with significant economic and political shocks (e.g. Lehman Brothers’ collapse). Credit markets uncertainty shocks, which played a crucial role in the aftermath of the house prices collapse in the USA, are first analyzed in a bivariate VAR context, and then, embodied in a simple theoretical framework.

The empirical evidence suggests that the US credit, financial and production markets have been affected by a relative large number of uncertainty shocks (i.e. rare events). In a Brainard’s (1967) uncertainty scenario, it is shown that a bizarre money-liquidity relationship exacerbates the “policymakers’ cautiousness-aggressiveness trade-off.” In addition, the model suggests that a “double” dose of policy, in presence of a global credit crunch, might be useless.

This paper improves the existing literature in two main directions. First, it provides novel empirical evidence on the unusual dynamics of the US credit market and its effects on the real economic activity during the crisis. Second, in a very simple theoretical framework accounting for parameter uncertainty, it addresses whether a bizarre money-credit relationship affects policymakers’ behavior (i.e. cautiousness vs aggressiveness).

This chapter explores the impact of international financial integration on credit markets in Latin America, using a cross-country dataset covering 17 countries between 1996 and 2008. It is found that financial integration amplifies the impact of international financial shocks on aggregate credit and interest rate fluctuations. Nonetheless, the net impact of integration on deepening credit markets dominates for the large majority of states of nature. The chapter also uses a detailed bank-level dataset that covers more than 500 banks for a similar time period to explore the role of financial integration – captured through the participation of foreign banks – in propagating external shocks. It is found that interest rates charged and loans supplied by foreign-owned banks respond more to external financial shocks than those supplied by domestically owned banks. This does not hold for all foreign banks. Spanish banks in the sample behave more like domestic banks and do not amplify the impact of foreign shocks on credit and interest rates.

This paper aims to simulate the potential impact of increasing non-performing loans (NPLs) on capital adequacy, interest income and firm value of banks and credit unions in the Eastern Caribbean Currency Union (ECCU) using stress tests.

A financial stress testing model was deployed at the levels of individual financial intermediary (FI), sectoral loan portfolio composition, individual member country, and the ECCU collectively, to investigate the impact of NPL shocks on FI stability.

The authors find that shocks impact the capital adequacy of banks less than that of credit unions, but that firm value of banks is more susceptible to increases in NPLs. Interest income responses to NPL shocks were linked to credit exposure from the tourism sector, which also reduced capital adequacy more than other economic sectors. Findings show that while the COVID-19 pandemic occasioned some increase in NPLs, the magnitude of impact was significantly mitigated by pro-stability policies including loan repayment moratoria and restructuring, guidance on the distribution of profits and deleveraging by financial institutions leading up to 2020.

The paper is among the first to use stress testing on the Caribbean in response to the COVID-19 pandemic. Past studies which have used stress test models in the region have not explicitly investigated the impact of credit shocks on risk-weighted assets or interest income as done herein, nor do they include credit unions in the modeling. The results offer novel evaluations as well as implications for FIs in other developing economies, especially those that share a comparable financial and economic architecture.

In this paper we investigate the relationship between loose monetary policy, low inflation, and easy bank credit and house price booms.

Using a panel of 11 OECD countries from 1920 to 2011 we estimate a panel VAR in order to identify loose monetary policy shocks, low inflation shocks, bank credit shocks, and house price shocks.

We show that during boom periods there is a heightened impact of all three “policy” shocks with the bank credit shock playing an important role. However, when we look at individual house price boom episodes the cause of the price boom is not so clear. The evidence suggests that the house price boom that occurred in the United States during the 1990s and 2000s was not due to easy bank credit.

Shocks from the shadow banking system are not separately identified. These are incorporated into the fourth “catch-all” shock.

Our evidence on housing price booms that expansionary monetary policy is a significant trigger buttresses the case for central banks following stable monetary policies based on well understood and credible rules.

This paper uses historical evidence to evaluate the relative importance of three main causes of house price booms. Our results bring into question the commonly held view that loose bank credit was to blame for the U.S. house price bubble of the later 1990s.

The purpose of this paper is to examine how shocks suffered by rural households in Ethiopia influence their decision to borrow and the source of credit.

First, suppose a household faces a set of four borrowing alternatives: only formal borrowing, only informal borrowing, both formal and informal borrowing, and non-borrowing. Second, the paper assumes that the random component is independently and identically distributed in accordance with the extreme value distribution. These assumptions lead to the multinomial logit model. The paper estimates the model using data from a survey of 350 rural households in Southern Ethiopia.

The paper finds that shocks are important factors in explaining both the decision to borrow and the source of credit. In particular, negative shocks that affect household's assets, such as the seizing of farmland and theft, or human capital, such as the death of the family head, reduce the probability of borrowing from formal lenders or from both formal and informal lenders at the same time. The study supports only to some extent the assumption that informal credit contributes to smooth consumption. Last, networking effect is very significant and demonstrates how the two markets interact.

A model that would consider dynamic consumption patterns would have been more appropriate. In fact, one of the limitations of the study is the reliance on a cross-section analysis and the data is limited to just one village. Further research would extend the data set geographically and across time.

The formal lenders are not willing to provide contingent loans, maybe because of a limited ability to assess and diversify risk. Besides, the available formal credit products are not proper to finance long term risk management strategies but pesticides, fertilizers and improved seeds that are entirely used in every agricultural cycle. In this regard, proper risk transfer strategies and instruments, as well as better tailored loan products, are needed in order to increase outreach into the rural areas.

To the authors’ knowledge, this is the first paper that investigates how shocks influence the decision to borrow and the source of credit in Ethiopia.

This study aims to determine whether the transmission of monetary policy to the real economy depends on the structural conditions of financial stability. In particular, the paper shows that the effects of shocks to financial stability on output and inflation is conditional on the state of credit in the economy, measured broadly as a credit-to-GDP.

The authors use a threshold vector autoregression model with Bayesian techniques to investigate the impact of private nonfinancial sector credit on the dynamic relationship between financial conditions, monetary policy transmission mechanism and macroeconomic performance in Kazakhstan from 2005:Q1 to 2020:Q1.

In the modeled threshold vector autoregression (VAR) specification, the authors document that when the credit-to-GDP gap is low or the credit is below its trend, an increase to the interest rate leads to a short-term economic expansion. However, when the credit-to-GDP gap is high or the nonfinancial credit is above its trend, a tightening in monetary policy leads to an economic contraction with domestic financial conditions being weaker compared to a low credit environment.

The outcome is consistent with the related literature, which argues that a more sustained increase in credit is followed by a sharper economic contraction, but only when the economy is in the high credit state. These results highlight that financial stability measures (e.g. credit state) is important to take into account when conducting monetary policy in emerging economies.

In this paper, the authors use the balance sheet data to investigate the interconnectedness and risk contagion effects in China's banking sector. They firstly study the network structure and centrality of the interbank network. Then, they investigate how and to what extent the credit shock and liquidity shock can lead to the risk propagation in the banking network.

Referring to the theoretical framework by Haldane and May (2011), this paper uses the network topology theory to analyze the contagion mechanism of credit shock and liquidity shock. Centrality measures and log-log plot are used to evaluate the interconnectedness of China's banking network.

The network topology has shown clustering effects of large banks in China's financial network. If the Industrial and Commercial Bank of China (ICBC) is in distress, the credit shock has little impact on the Chinese banking sector. However, the liquidity shock has shown more substantial effects than that of the credit shock. The discount rate and the rollover ratio play significant roles in determining the contagion effects. If the credit shock and liquidity shock coincide, the contagion effects will be amplified.

The results of this paper reveal the network structure of China's interbank market and the resilience of banking system to the adverse shock. The findings are valuable for regulators to make policies and supervise the systemic important banks.

The balance sheet data of different types of banks are used to construct a bilateral exposure matrix. Based on the matrix, this paper investigates the knock-on effects of credit shock triggered by the debt default in the interbank market, the knock-on effects of liquidity effects, which is featured by “fire sale” of bank assets, and the contagion effects of combined shocks.

The Iranian banking industry has been greatly affected by dramatic changes in macroeconomic conditions over the past several decades owing to volatile oil revenues, changing fiscal and monetary policies, and the imposition of US sanctions. The main objective of this paper is to estimate potential credit losses in the Iranian banking sector due to macroeconomic shocks and assess the minimum economic capital requirements under the baseline and distressed scenarios. The paper also contrasts the applications of linear and nonlinear models in estimating the impacts of macroeconomic shocks on financial institutions.

The paper uses a multistage approach to derive the portfolio loss distribution for banks. In the first step, the dynamic relationship between the selected macroeconomic variables are estimated using a VAR model to generate the stress scenarios. In the second step, the default probabilities are estimated using a quantile regression model and the results are compared with those of the conventional linear models. Finally, the default probabilities are simulated for a one-year time horizon using Monte-Carlo method and the portfolio loss distribution is calculated for hypothetical portfolios. The expected loss includes the loss given default for loans drawn randomly and uniformly distributed and exposed at default values when loans are assigned a fixed value.

The results indicate that the loss distributions under all scenarios are skewed to the right, with the linear model results being very similar to those of quantile at the 50% quantile, but very unlike those at the 10% and 90% quantiles. Specifically, the quantile model for the 90% (10%) quantile generates estimates of minimum economic capital requirement that are considerably higher (lower) than those using the linear model.

The study has focused on credit risk because of lack of data on other types of risk at individual bank level. The future studies can estimate the aggregate economic capital using a risk aggregation approach and a panel data (not presently available), which could further improve the accuracy of the estimates.

The fiscal and monetary authorities in developing countries, specially oil-exporting countries, can follow the risk assessment approach to assess the health of their banking system and adapt policies to mitigate the impacts of large macroeconomic shocks on their financial markets.

This is the first paper estimating the portfolio loss distribution for the Iranian banks under turbulent macroeconomic conditions using linear and nonlinear models. The case study can be applied to other developing and emerging countries, particularly those highly dependent on natural resources, prone to extreme macroeconomic shocks.