Tobias Adrian, Domenico Giannone, Matteo Luciani, and Mike WestCentral banks monitor macroeconomic risk through two traditions: scenario analysis, regularly used since the mid-1990s, and distributional forecasting, practiced since the late 1960s. The two are complementary but separate: scenarios provide narratives without probabilities, while predictive distributions provide probabilities with limited economic interpretation.
Hie Joo Ahn and Jeremy RuddThis paper estimates state-level trend unemployment rates (trend U-star) based on the trend components of unemployment inflows and outflows across unemployment durations. The estimated trend U-stars, particularly the portions attributable to long-termunemployment, have levels and dynamics that vary substantially across states.
Ozge Akinci, Sebnem Kalemli-Ozcan, and Albert QueraltoWe study how increased uncertainty about U.S. asset returns affects global asset prices and exchange rates in a two-country model with intermediary balance-sheet constraints. Empirically, uncertainty shocks widen global credit spreads, appreciate the dollar, and increase currency risk premia. In our model, higher uncertainty tightens intermediary constraints and lowers asset prices, reversing the counterfactual asset price increase in frictionless models.
This paper examines whether environmental policy uncertainty undermines clean-technology investment in the United States by weakening policy-induced investment incentives. Using quarterly project-level data on U.S. greenfield investments from 2007Q1 to 2019Q1, combined with novel news-based indices that separately measure environmental policy salience and environmental policy uncertainty, we find that policy uncertainty substantially offsets the positive investment effects of environmental policy.
Bank of England statement
Hyung Joo KimI propose a novel method to reliably estimate the conditional pricing kernel by incorporating conditioning variables. The VIX and the term spread are most informative variables for identifying state prices. The conditional kernel estimate exhibits significant time variation: the more favorable market expectations, the higher state prices in negative return states.
We analyze the Probability of Default (PD) of non-financial corporations in Europe using Random Forests (RF) and assess implications for stress testing the banking sector. To this end, we exploit data on firms’ financial statements (Orbis) and banks’ credit registry (Anacredit). We show that RF displays stronger risk sensitivity than logistic regression in stress testing, shedding new light on the non-linear effect of scenario severity on PD.
Martin Bodenstein and Junzhu ZhaoWe investigate Barro's random walk hypothesis according to which distortionary labor taxes should follow a random walk for any stochastic process of government expenditures, see Barro (1979). When agents experience cognitive discounting as in Gabaix (2020), they perceive government debt as wealth, and the random walk result breaks down except for knife-edge combinations of limited rationality by policymakers and the private sector.
Isabel Cairó, Hess Chung, Francesco Ferrante, Cristina Fuentes-Albero, Camilo Morales-Jimenez, and Damjan PfajfarLabor market variables frequently send conflicting signals about the degree of slack or tightness, often co
This paper investigates the interest rate pass-through of monetary policy in the euro area by focusing on the role of banks’ funding structures. We estimate the interest rate pass-through for loans to non-financial corporations using bank-level balance sheet data. In doing so, we interact the response of lending rates with characteristics of the funding structure, and show that banks that rely more on bond issuance than on the money market tend to be less responsive to policy changes.
