We use non-Gaussian features in U.S. macroeconomic data to identify aggregate supply and demand shocks while imposing minimal economic assumptions. Recessions in the 1970s and 1980s were driven primarily by supply shocks, later recessions were driven primarily by demand shocks, and the Great...

We develop a parsimonious New Keynesian macro-finance model with downward nominal rigidities to understand secular and cyclical movements in Treasury bond premia. Downward nominal rigidities create state-dependence in output and inflation dynamics: a higher level of inflation makes prices more...

Using a unique data set of individual professional forecasts, we document disagreement about the future path of monetary policy, particularly at longer horizons. The stark differences in short rate forecasts imply strong disagreement about the risk-return trade-off of longer-term bonds....

Modeling short-term interest rates as following regime-switching processes has become increasingly popular. Theoretically, regime-switching models are able to capture rational expectations of infrequently occurring discrete events. Technically, they allow for potential time-varying stationarity....

The evolution of the yields of different maturities is related and can be described by a reduced number of commom latent factors. Multifactor interest rate models of the finance literature, common factor models of the time series literature and others use this property. Each model has advantages...

We study the term structure of default-free interest rates in a sticky-price model with an occasionally binding effective lower bound (ELB) constraint on interest rates and recursive preferences. The ELB constraint induces state-dependency in the dynamics of term premiums by affecting...

We analyze optimal monetary policy and its implications for asset prices, when aggregate demand has inertia and responds to asset prices with a lag. If there is a negative output gap, the central bank optimally overshoots aggregate asset prices (asset prices are initially pushed above their...

Görtz et al. (2022) estimate the effects of innovations to future total factor productivity (TFP) on financial markets. In a Bayesian vector autoregression, they identify a TFP news shock as one that explains the largest share of 40-quarter ahead forecast error variance (FEV) of TFP. Their...

VARs are a popular tool for forecasting and structural analysis, but ill-suited to handle occasionally binding constraints, like the effective lower bound on nominal interest rates. We extend the VAR framework by modeling interest rates as censored observations of a latent shadow-rate process,...