Knowledge that Transforms

In this study, we provide empirical evidence on the portfolio rebalancing of European equity mutual funds following both conventional (CMP) and unconventional monetary policies (UMP). We use 1772 equity mutual funds’ portfolio holdings over the period 2002Q4–2016Q4. This level of granularity allows us to characterise the funds’ asset allocation in different portfolio dimensions: the size, style, currency, and domicile of the stocks, and managers’ preferred investment strategies. Using a panel fixed effect estimator, our results support the existence of portfolio rebalancing across equity categories following UMP. European equity mutual funds’ assets are, on average, reallocated towards mid-cap, and core stocks and developing economies, and shifted away from small-cap and value stocks and home as well as developed countries. Furthermore, mutual funds seem to concentrate on their preferred and historical investment strategies. These two results suggest that managers are more willing to invest in safer and familiar stocks following UMP announcements thereby decreasing the risk of asymmetry of information. We finally show that the funds size, returns volatility and expense ratio affect the strength of the rebalancing.

This paper investigates the counterparty credit risk of interest rate swaps positions using the credit valuation adjustment (CVA) measure, and examines the potential dependence relationships between the probability of default (PD) and exposure at default (EAD). We empirically tested, using interest rate swaption implied market volatilities, six tail dependence models: a Basel III Committee independent model, a Gaussian, Student’s t, Gumbel, Clayton, and a wrong way risk (WWR) copula with dependence approach. The results show that the CVA underestimation when using a Clayton copula for modelling the dependence of PD and EAD is about 10%–856% compared to using WWR, and the underestimation between using the standardised Basel independent model and using the Gaussian copula is about 552%–2621%, including the period of the 2007/2008 crisis, signalling that dependence is more important than tail dependence for CVA measurement. This has important implications for regulators, financial institutions, and credit risk managers when calculating counterparty risk.

This paper investigates how environmental regulation and action affect analyst behaviour. Exploiting staggered enactment of low carbon city (LCC) initiatives in a difference-in-differences (DiD) setting, we observe that analyst forecast accuracy (dispersion) is significantly lower (greater) for client firms headquartered in cities covered by the LCC pilot programme, especially among firms with a low-quality information environment. The LCC effort affects analyst behaviour via increased firm risk and reduced earnings predictability, causing enhanced site visits and coverage. The results are stronger in cities with more rigorous enforcement and regulation intensity, for private firms with high business complexity and in heavily polluting industries. Results are robust to DiD models with entropy balancing matching, placebo tests, parallel trend tests, and a battery of fixed effects. Collectively, they reveal that environmental regulation has real impacts on analyst forecast behaviour.

We construct a model of a bank’s optimal funding choice, where the bank negotiates with both safety-driven short-term bondholders and (mostly) risk-taking long-term bondholders. We establish that investor demands for safety create a negative relationship between the bank’s capital choices and short-term funding, as well as negative relationships between capital and common measures of bank liquidity. Short-term investors’ demands for safety force the bank to hold more collateral, which diminishes the demands by long-term bondholders for higher holdings of bank capital. Consistent with our model, our bank-level empirical analysis of these capital–liquidity trade-offs shows that bank liquidity measures have a strong and negative relationship to the capital ratio. Furthermore, we show that this trade-off does not appear to be regulation related and has diminished in size over time.

China’s climb to a trading powerhouse has changed its position in the world and therefore its relationships with other economies. As a result, its sovereign credit risk, which we measure by the pricing of its credit default swaps (CDS), now has the potential to greatly impact other sovereign CDS spreads. Employing a dynamic approach, we find that changes in China’s sovereign risk has strong contagion effects on its goods and service providers, while China is vulnerable to contagion effects from its major importers, suggesting sovereign risk spills over to other regions via the global supply chain. China’s success hurts some of the weaker countries in Europe by competing for their customers, while China faces strong competition itself from its export-focused neighbors. FDI and portfolio investment also affect the CDS relationships between China and other economies.

We exploit an exogenous change in the coverage of insured deposits following the passage of the Emergency Economic Stabilization Act (2008) to investigate the impact of deposit insurance on the volume, composition and quality of credit union lending. Using a difference-in-difference approach, we find changes in the volume, composition and riskiness of credit union lending. Specifically, we find that affected credit unions increase total and unsecured lending, leading to a decline in loan quality. Overall, our results suggest that an increase in the maximum coverage of insured deposits induces credit unions to lend more at the expense of loan quality.

This paper studies the effects of the release of a limit on banks’ maturity transformation – akin to the Net Stable Funding Ratio – for mortgage supply and house prices. After the regulatory easing, credit supply increased only for the banks that were previously constrained by the regulation and not for the others. We also show that the expansion in mortgages triggered by the deregulation accelerated house prices. The effect was channeled through higher demand for housing and the relaxation of borrowers’ financial constraints. Even though the impact of the credit supply shock persisted, the interaction between credit and house prices was not conducive to a housing market overheating.

We study the economics- and finance-scholars’ reaction to the 2008 financial crisis using machine learning language analyses methods of Latent Dirichlet Allocation and dynamic topic modelling algorithms, to analyze the texts of 14,270 NBER working papers covering the 1999–2016 period. We find that academic scholars as a group were insufficiently engaged in crises’ studies before 2008. As the crisis unraveled, however, they switched their focus to studying the crisis, its causes, and consequences. Thus, the scholars were “slow-to-see,” but they were “fast-to-act.” Their initial response to the ongoing Covid-19 crisis is consistent with these conclusions.

This paper explores the foundations for the application of the empirical growth-at-risk (GaR) approach to the assessment and design of macroprudential policies. It starts considering a stylized benchmark linear specification of the empirical GaR approach in combination with a linear–quadratic social welfare criterion that rewards expected GDP growth and penalizes the gap between expected GDP growth and GaR. If the growth rate follows a normal distribution, this welfare criterion can be microfounded as consistent with expected utility maximization under preferences for GDP levels exhibiting constant absolute risk aversion. The benchmark formulation implies an optimal policy rule linear in the risk indicator and an optimal gap between expected growth and GaR that does not depend on the time-varying risk indicator and is inversely related to the cost-effectiveness of macroprudential policy and the risk preference parameter. Extensions of the benchmark formulation show the potential to adapt the analysis and its insights to the richer specifications typically considered in empirical work.

That firms actively influence public policy to advance private interests is taken for granted in most economies. In China, the activism of public actors in shaping private interests suggests that the public rather than private sector is more influential to the political economy. In this paper, we test the extent to which this is true in among Chinese provinces. We conduct a cluster quasi-experiment using the 2012 anti-corruption campaign. We find that the declining involvement of public actors in economic decisions during the campaign did not result into lower productivity in provinces with higher private sector participation, especially in unregulated industries and those not dominated by state-owned enterprises. De facto political power from 30-years of private wealth accumulation may have helped establish market-driven norms of economic behavior, strengthening the political economy against the vicissitudes of public actors.