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Jel Classification:C63 

Working Paper
The market resources method for solving dynamic optimization problems

We introduce the market resources method (MRM) for solving dynamic optimization problems. MRM extends Carroll?s (2006) endogenous grid point method (EGM) for problems with more than one control variable using policy function iteration. The MRM algorithm is simple to implement and provides advantages in terms of speed and accuracy over Howard?s policy improvement algorithm. Codes are available.
Globalization Institute Working Papers , Paper 274

Report
Approximating Grouped Fixed Effects Estimation via Fuzzy Clustering Regression

We propose a new, computationally-efficient way to approximate the “grouped fixed-effects” (GFE) estimator of Bonhomme and Manresa (2015), which estimates grouped patterns of unobserved heterogeneity. To do so, we generalize the fuzzy C-means objective to regression settings. As the regularization parameter m approaches 1, the fuzzy clustering objective converges to the GFE objective; moreover, we recast this objective as a standard Generalized Method of Moments problem. We replicate the empirical results of Bonhomme and Manresa (2015) and show that our estimator delivers almost identical ...
Staff Reports , Paper 1033

Working Paper
Occupational Choice, Retirement, and the Effects of Disability Insurance

There is much variation in the physical requirements across occupations, giving rise to great differences in later-life productivity, disability risk, and the value of Social Security Disability Insurance (SSDI). In this paper, I look at how such differences across occupations affect initial career choice as well as the extent to which SSDI, which insures shocks to productivity due to disability, prompts more people to choose physically intense occupations. Using data from the Health and Retirement Study (HRS) and the Current Population Survey (CPS), I estimate a dynamic model of occupational ...
Finance and Economics Discussion Series , Paper 2016-051

Working Paper
A Generalized Approach to Indeterminacy in Linear Rational Expectations Models

We propose a novel approach to deal with the problem of indeterminacy in Linear Rational Expectations models. The method consists of augmenting the original state space with a set of auxiliary exogenous equations to provide the adequate number of explosive roots in presence of indeterminacy. The solution in this expanded state space, if it exists, is always determinate, and is identical to the indeterminate solution of the original model. The proposed approach accommodates determinacy and any degree of indeterminacy, and it can be implemented even when the boundaries of the determinacy region ...
Finance and Economics Discussion Series , Paper 2019-033

Working Paper
Risk Management for Sovereign Debt Financing with Sustainability Conditions

We develop a model of debt sustainability analysis with optimal financing decisions in the presence of macroeconomic, financial and fiscal uncertainty. We define a coherent measure of refinancing risk, and trade off the risks of debt stock and flow dynamics, subject to debt sustainability constraints and endogenous risk and term premia. We optimize both static and dynamic financing strategies, compare them with several simple rules and consol financing to demonstrate economically significant effects of optimal financing, and show that the stock-flow tradeoff can be critical for ...
Globalization Institute Working Papers , Paper 367

Working Paper
Applications of Markov Chain Approximation Methods to Optimal Control Problems in Economics

In this paper we explore some of the benefits of using the finite-state Markov chain approximation (MCA) method of Kushner and Dupuis (2001) to solve continuous-time optimal control problems. We first show that the implicit finite-difference scheme of Achdou et al. (2017) amounts to a limiting form of the MCA method for a certain choice of approximating chains and policy function iteration for the resulting system of equations. We then illustrate the benefits of departing from policy function iteration by showing that using variations of modified policy function iteration to solve income ...
Working Papers , Paper 21-04

Working Paper
Finite-State Markov-Chain Approximations: A Hidden Markov Approach

This paper proposes a novel finite-state Markov chain approximation method for Markov processes with continuous support, providing both an optimal grid and transition probability matrix. The method can be used for multivariate processes, as well as non-stationary processes such as those with a life-cycle component. The method is based on minimizing the information loss between a Hidden Markov Model and the true data-generating process. We provide sufficient conditions under which this information loss can be made arbitrarily small if enough grid points are used. We compare our method to ...
Finance and Economics Discussion Series , Paper 2023-040

Working Paper
Efficient Computation with Taste Shocks

Taste shocks result in nondegenerate choice probabilities, smooth policy functions, continuous demand correspondences, and reduced computational errors. They also cause significant computational cost when the number of choices is large. However, I show that, in many economic models, a numerically equivalent approximation may be obtained extremely efficiently. If the objective function has increasing differences (a condition closely tied to policy function monotonicity) or is concave in a discrete sense, the proposed algorithms are O(n log n) for n states and n choice--a drastic improvement ...
Working Paper , Paper 19-15

Working Paper
Finite-Order VAR Representation of Linear Rational Expectations Models: With Some Lessons for Monetary Policy

This paper considers the characterization via finite-order VARs of the solution of a large class of linear rational expectations (LRE) models. I propose a unified approach that uses a companion Sylvester equation to check the existence and uniqueness of a solution to the canonical (first-order) LRE model in finite-order VAR form and a quadratic matrix equation to characterize it decoupling the backward- and forward-looking aspects of the model. I also investigate the fundamentalness of the shocks recovered. Solving LRE models by this procedure is straightforward to implement, general in its ...
Globalization Institute Working Papers , Paper 285

Working Paper
The Dynamic Striated Metropolis-Hastings Sampler for High-Dimensional Models

Having efficient and accurate samplers for simulating the posterior distribution is crucial for Bayesian analysis. We develop a generic posterior simulator called the "dynamic striated Metropolis-Hastings (DSMH)" sampler. Grounded in the Metropolis-Hastings algorithm, it draws its strengths from both the equi-energy sampler and the sequential Monte Carlo sampler by avoiding the weaknesses of the straight Metropolis-Hastings algorithm as well as those of importance sampling. In particular, the DSMH sampler possesses the capacity to cope with incredibly irregular distributions that are full ...
FRB Atlanta Working Paper , Paper 2014-21

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