Recent empirical work in several economic fields, particularly environmental and energy economics, has adapted the regression discontinuity (RD) framework to applications where time is the running variable and treatment begins at a particular threshold in time. In this guide for practitioners,...

The accuracy of particle filters for nonlinear state-space models crucially depends on the proposal distribution that mutates time t-1 particle values into time t values. In the widely-used bootstrap particle filter, this distribution is generated by the state-transition equation. While...

The main econometric issue in testing the Lucas hypothesis (1973) in a times series context is the estimation of the variance conditional on past information. The ARCH model, proposed by Engle (1982), is one way of specifying the conditional variance. But the assumption underlying the ARCH...

Nonlinearity is an important consideration in many problems of finance and economics, such as pricing securities, computing equilibrium, and conducting structural estimations. We extend the transform analysis in Duffie, Pan, and Singleton (2000) by providing analytical treatment of a general...

We explore a view of the crisis as a shock to investor sentiment that led to the collapse of a bubble or pyramid scheme in financial markets. We embed this view in a standard model of the financial accelerator and explore its empirical and policy implications. In particular, we show how the...

An iconic model with high leverage and overvalued collateral assets is used to illustrate the amplification mechanism driving asset prices to 'overshoot' equilibrium when an asset bubble bursts--threatening widespread insolvency and what Richard Koo calls a 'balance sheet recession'. Besides...

Considerable debate rages about whether Federal Reserve policy was too lax in the early part of the 2000s, thereby fueling the home-price bubble that was the proximate cause of the global financial crisis. We present evidence that the view that modest alterations to monetary policy have vast...

This paper studies the pruned state-space system for higher-order approximations to the solutions of DSGE models. For second- and third-order approximations, we derive the statistical properties of this system and provide closed-form expressions for first and second unconditional moments and...

We develop a nonlinear state-space model that captures the joint dynamics of consumption, dividend growth, and asset returns. Our model consists of an economy containing a common predictable component for consumption and dividend growth and multiple stochastic volatility processes. The...

Recent research has proposed the state space (88) framework for decomposition of GNP and other economic time series into trend and cycle components, using the Kalman filter. This paper reviews the empirical evidence and suggests that the resulting decomposition may be spurious, just as...