Wepresent an analytically tractable dynamic stochastic general equilibrium model that incorporates micro-level fixed and convex adjustment costs. We provide an explicit characterization of equilibrium dynamics by a system of nonlinear stochastic difference equations. We provide general conditions under which our model features investment lumpiness at the microeconomic level, but aggregate dynam...

We consider Bayesian estimation of state space models when the measurement density is not available but estimating equations for the parameters of the measurement density are available from moment conditions. The most common applications are partial equilibrium models involving moment conditions that depend on dynamic latent variables (e.g., timevarying parameters, stochastic volatility) and dy...

We examine the linear-quadratic (LQ) approximation of non-linear stochastic dynamic optimization problems in macroeconomics, in particular for monetary policy. We make four main contributions: first, we draw attention to a general Hamiltonian framework for LQ approximation due to Magill (1977). We show that the procedure for the ‘large distortions’ case of Benigno and Woodford (2003, 2005) is e...

In 1953, Lloyd Shapley contributed his paper "Stochastic games" to PNAS. In this paper, he defined the model of stochastic games, which were the first general dynamic model of a game to be defined, and proved that it admits a stationary equilibrium. In this Perspective, we summarize the historical context and the impact of Shapley's contribution.

The design of China’s industrial carbon reduction policies is still in its early stages, so currently, comparing the effectiveness various emission can help China policies. This paper develops a dynamic stochastic general equilibrium (DSGE) model manufacturing industry and investigates impact innovation on environmental protection technology, emissions tax, government expenditures output indust...