Abstract: We evaluate how a country’s governance structure for macroprudential policy affects its implementation of Basel III macroprudential capital buffers. We find that the probabilities of using the countercyclical capital buffer (CCyB) are higher in countries that have financial stability committees (FSCs) with stronger governance mechanisms and fewer agencies, which reduces coordination problems. These higher probabilities are more sensitive to credit growth, consistent with the CCyB being used to mitigate systemic risk. A country’s probability of using the CCyB is even higher when the FSC or ministry of finance has direct authority to set the CCyB, perhaps because setting the CCyB involves establishing a new macro-financial analytical process to regularly assess systemic risks and allows these new entities to influence the process. These results are consistent with elected officials creating the FSCs with the strongest governance and fewer agencies for functional delegati on reasons, but most FSCs are created for symbolic political reasons.
Abstract: This technical note describes the Forward-Looking Analysis of Risk Events (FLARE) model, which is a top-down model that helps assess how well the banking system is positioned to weather exogenous macroeconomic shocks. FLARE estimates banking system capital under varying macroeconomic scenarios, time horizons, and other systemic shocks.
Abstract: Standard structural VAR models and estimation using Romer and Romer (2004) monetary policy shocks show that, in samples after the 1980s, a contractionary conventional monetary policy shock generates smaller and sometimes perversely-signed impulse responses compared to earlier samples. Using insights from the central bank information effects literature, we show that the analyses producing these results suffer from an omitted variables problem related to forward-looking information emanating from Federal Reserve forecasts. Transmission of conventional monetary policy shocks takes on the standard signs, and is typically significant, once Fed forward-looking information is taken into account. This reconciliation does not follow from adding private sector forecasts to the estimation frameworks.
Abstract: We investigate how macroeconomic drivers affect the predictive inflation distribution as well as the probability that inflation will run above or below certain thresholds over the near term. This is what we refer to as Inflation-at-Risk–a measure of the tail risks to the inflation outlook. We find that the recent muted response of the conditional mean of inflation to economic conditions does not convey an adequate representation of the overall pattern of inflation dynamics. Analyzing data from the 1970s reveals ample variability in the conditional predictive distribution of inflation that remains even when focusing on the post-2000 period of stable and low mean inflation. We also document that in the United States and in the Euro Area tight financial conditions carry substantial downside inflation risks, a feature overlooked by much of the literature. Our paper offers a new empirical perspective to existing macroeconomic models, showing that changes in credit conditions are also key to understand the dynamics of the inflation tails.
Keywords: Quantile Regression, Inflation Risks.
Abstract: What is the output gap and when do we know it? A factor stochastic volatility model estimates the common component to forecasts of the output gap produced by the staff of the Federal Reserve, its time-varying volatility, and time-varying, horizon-specific forecast uncertainty. The common factor to these forecasts is highly procyclical, and unexpected increases to the common factor are associated with persistent responses in other macroeconomic variables. However, output gap estimates are very uncertain, even well after the fact. Output gap uncertainty increases around business cycle turning points. Lastly, increased macroeconomic uncertainty, as measured by the output gap's time-varying volatility, produces pronounced negative responses to other macroeconomic variables.
Evaluating the Success of President Johnson's War on Poverty: Revisiting the Historical Record Using a Full-Income Poverty Measure
Abstract: We evaluate progress in President's Johnson's War on Poverty. We do so relative to the scientifically arbitrary but policy relevant 20 percent baseline poverty rate he established for 1963. No existing poverty measure fully captures poverty reductions based on the standard that President Johnson set. To fill this gap, we develop a Full-income Poverty Measure with thresholds set to match the 1963 Official Poverty Rate. We include cash income, taxes, and major in-kind transfers and update poverty thresholds for inflation annually. While the Official Poverty Rate fell from 19.5 percent in 1963 to 12.3 percent in 2017, our Full-income Poverty Rate based on President Johnson's standards fell from 19.5 percent to 2.3 percent over that period. Today, almost all Americans have income above the inflation-adjusted thresholds established in the 1960s. Although expectations for minimum living standards evolve, this suggests substantial progress combatting absolute poverty since the War on Poverty began.
Abstract: Local projections (LPs) are a popular tool in applied macroeconomic research. We survey the related literature and find that LPs are often used with very small samples in the time dimension. With small sample sizes, given the high degree of persistence in most macroeconomic data, impulse responses estimated by LPs can be severely biased. This is true even if the right-hand-side variable in the LP is iid, or if the data set includes a large cross-section (i.e., panel data). We derive a simple expression to elucidate the source of the bias. Our expression highlights the interdependence between coefficients of LPs at different horizons. As a byproduct, we propose a way to bias-correct LPs. Using U.S. macroeconomic data and identified monetary policy shocks, we demonstrate that the bias correction can be large.
Abstract: By stepping between bilateral counterparties, a central counterparty (CCP) transforms credit exposure. CCPs generally improve financial stability. Nevertheless, large CCPs are by nature concentrated and interconnected with major global banks. Moreover, although they mitigate credit risk, CCPs create liquidity risks, because they rely on participants to provide cash. Such requirements increase with both market volatility and default; consequently, CCP liquidity needs are inherently procyclical. This procyclicality makes it more challenging to assess CCP resilience in the rare event that one or more large financial institutions default. Liquidity-focused macroprudential stress tests could help to assess and manage this systemic liquidity risk.
Abstract: Treasury securities normally possess unparalleled safety and liquidity and, consequently, carry a money premium. We use recent debt limit impasses, which temporarily increased the riskiness of Treasuries, to investigate the relationship between the money premium, safety, and liquidity. Our results shed light on Treasury market dynamics specifically, and debt more generally. We first establish that a decline in the perceived safety of Treasuries erodes the money premium at all times. Meanwhile, changes in liquidity only affected the money premium during the impasses. Next, we show that Treasury safety and liquidity dynamics are generally consistent with the theory of the information sensitivity of debt.
Abstract: We test for racial discrimination in the prices charged by mortgage lenders. We construct a unique dataset where we observe all three dimensions of a mortgage's price: the interest rate, discount points, and fees. While we find statistically significant gaps by race and ethnicity in interest rates, these gaps are offset by differences in discount points. We trace out point-rate schedules and show that minorities and whites face identical schedules, but sort to different locations on the schedule. Such sorting may reflect systematic differences in liquidity or preferences. Finally, we find no differences in total fees by race or ethnicity.
Abstract: Global and local methods are widely used in international macroeconomics to analyze incomplete-markets models. We study solutions for an endowment economy, an RBC model and a Sudden Stops model with an occasionally binding credit constraint. First-order, second-order, risky steady state and DynareOBC solutions are compared v. fixed-point-iteration global solutions in the time and frequency domains. The solutions differ in key respects, including measures of precautionary savings, cyclical moments, impulse response functions, financial premia and macro responses to credit constraints, and periodograms of consumption, foreign assets and net exports. The global method is easy to implement and faster than local methods for the endowment model. Local methods are faster for the RBC model and the global and DynareOBC solutions are of comparable speed. These findings favor global methods except when prevented by the curse of dimensionality and urge caution when using local methods. Of the latter, first-order solutions are preferable because results are very similar to second-order methods.
Abstract: This paper explores the microfoundations of consumption models and quantifies the macro implications of consumption heterogeneity. We propose a new empirical method to estimate the response of consumption to permanent and transitory income shocks for different groups of households. We then apply this method to administrative data from Denmark. The large sample size, along with detailed household balance sheet information, allows us to finely divide the population along relevant dimensions. We find that households that stand to lose from an interest rate hike are significantly more responsive to income shocks than those that stand to gain. Following a 1-percentage-point interest rate increase, we estimate that consumption growth decreases by a 1/4 percentage point through this interest rate exposure channel alone, making this channel substantially larger than the intertemporal substitution channel that is at the core of representative agent New Keynesian models.
Confidence, financial literacy and investment in risky assets: Evidence from the Survey of Consumer Finances
Abstract: We employ recent Survey of Consumer Finances (SCF) microdata from the US to analyze the impacts of confidence in one's own financial knowledge, confidence in the economy, and objective financial literacy on investment in risky financial assets (equity and bonds) on both the extensive and intensive margins. Controlling for a rich set of covariates including risk aversion, we find that objective financial literacy is positively related to investment in risky assets as well as debt securities. Moreover, confidence in own financial skills additionally increases the probability of holding risky assets and bonds. While these relationships are rather robust for the extensive margin, they break down with regard to the conditional share of financial wealth in risky assets of those who actually hold them. The relevance of financial literacy as well as confidence varies considerably with the distribution of wealth as well as across several socio-economic dimensions such as age, education and race.
Abstract: This paper uses aggregate data to estimate and evaluate a behavioral New Keynesian (NK) model in which households and firms plan over a finite horizon. The finite-horizon (FH) model outperforms rational expectations versions of the NK model commonly used in empirical applications as well as other behavioral NK models. The better fit of the FH model reflects that it can induce slow-moving trends in key endogenous variables which deliver substantial persistence in output and inflation dynamics. In the FH model, households and firms are forward-looking in thinking about events over their planning horizon but are backward looking regarding events beyond that point. This gives rise to persistence without resorting to additional features such as habit persistence and price contracts indexed to lagged inflation. The parameter estimates imply that the planning horizons of most households and firms are less than two years which considerably dampens the effects of expected fut ure changes of monetary policy on the macroeconomy.
Keywords: Finite-horizon planning, learning, monetary policy, New Keynesian model, Bayesian estimation.
Abstract: This paper examines whether monetary policy pass-through to mortgage interest rates affects household fertility decisions. Using administrative data on mortgages and births in the UK, our empirical strategy exploits variation in the timing of when families were eligible for a rate adjustment, coupled with the large reductions in the monetary policy rate that occurred during the Great Recession. We estimate that each 1 percentage point drop in the policy rate increased birth rates by 2 percent. In aggregate, this pass-through of accommodative monetary policy to mortgage rates was sufficiently large to outweigh the headwinds of the Great Recession and prevent a "baby bust" in the UK, in contrast to the US. Our results provide new evidence on the nature of monetary policy transmission to households and suggest a new mechanism via which mortgage contract structures can affect both aggregate demand and supply.
Abstract: We apply textual analysis tools to the narratives that accompany Federal Reserve Board economic forecasts to measure the degree of optimism versus pessimism expressed in those narratives. Text sentiment is strongly correlated with the accompanying economic point forecasts, positively for GDP forecasts and negatively for unemployment and inflation forecasts. Moreover, our sentiment measure predicts errors in FRB and private forecasts for GDP growth and unemployment up to four quarters out. Furthermore, stronger sentiment predicts tighter than expected monetary policy and higher future stock returns. Quantile regressions indicate that most of sentiment's forecasting power arises from signaling downside risks to the economy and stock prices.