A divide and conquer algorithm for exploiting policy function monotonicity is proposed and analyzed. To solve a discrete problem with n states and n choices, the algorithm requires at most n log2(n) 5n objective function evaluations. In contrast, existing methods for non-concave problems require...

A divide and conquer algorithm for exploiting policy function monotonicity is proposed and analyzed. To solve a discrete problem with n states and n choices, the algorithm requires at most nlog2(n)+5n objective function evaluations. In contrast, existing methods for nonconcave problems require...

I study optimal monetary policy in a simple New Keynesian model with portfolio adjustment costs. Purchases of long-term debt by the central bank (quantitative easing; ‘QE') alter the average portfolio return and hence influence aggregate demand and inflation. The central bank chooses the...

Structural estimation of macroeconomic models and new HANK-type models with extremely high dimensionality require fast and robust methods to efficiently deal with occasionally binding constraints (OBCs). This paper proposes a novel algorithm that solves for the perfect foresight path of...

In this paper we outline the Lagrangian constrained optimization method to solve complex problems subject to constraints. Firstly we summarize the Lagrangian constrained optimization routine. Secondly we outline a detailed implementation strategy. Thirdly and finally we provide example and solve...

This article presents an algorithm that extends Ljungqvist and Sargent's (2012) dynamic Stackelberg game to the case of dynamic stochastic general equilibrium models including forcing variables. Its first step is the solution of the discounted augmented linear quadratic regulator as in Hansen...

This algorithm extends Ljungqvist and Sargent (2012) algorithm of Stackelberg dynamic game to the case of dynamic stochastic general equilibrium models including exogenous forcing variables. It is based Anderson, Hansen, McGrattan, Sargent (1996) discounted augmented linear quadratic regulator....

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)....

Models in the infinite horizon macro-housing literature often assume that borrowers are constrained exclusively by the loan-to-value (LTV) ratio. Motivated by the Swedish micro-data, I explore an alternative arrangement where borrowers are constrained by the feasibility of repayment, but choose...

Models in the infinite horizon macro-housing literature often assume that borrowers are constrained exclusively by the loan-to-value (LTV) ratio. Motivated by the Swedish micro-data, I explore an alternative arrangement where borrowers are constrained by the feasibility of repayment, but choose...