Erin Troland, Isabella Agnes, Jessica Liu, Fatimah Shalaan, Michelle Tran, and Douglas WebberIn the pandemic era, people moved from high-density, expensive areas to more affordable areas, putting upward pressure on local housing prices. We examine the geographic distribution of rent growth during this time and its effects on renters.
Rehim KilicThis paper examines which representations of persistence and nonlinearity are most useful for forecasting realized volatility and whether machine learning adds value beyond econometric models designed for long memory and regime dependence. We compare HAR, ARFIMA, threshold HAR, smooth-transition HAR, and Markov-switching HAR with XGBoost and several neural-network models for the S&P 500 and 40 U.S. equities.
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.
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.
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
Colin Caines, Florian Hoffmann, Gueorgui KambourovWe document a strong, positive relationship between occupational problem complexity, measured from US data on problem-solving requirements, and occupational wage growth since 1980. In contrast, employment shifts toward more complex occupations have been modest, suggesting a race between the demand for and supply of complex skills.
Ayelen Banegas, Lucas Devigne, Mulalo Mamburu, Kleopatra Nikolaou, Anna Samarina, Fabio TamburriniThis paper synthesizes the literature on vulnerabilities in government bond-backed repo markets, focusing on the features that contribute to both the fragility and stability of these markets.
