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Working Paper
Occupational Choice, Retirement, and the Effects of Disability Insurance
Jacobs, Lindsay (2016-06)
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
Tractable latent state filtering for non-linear DSGE models using a second-order approximation
Kollmann, Robert (2013)
This paper develops a novel approach for estimating latent state variables of Dynamic Stochastic General Equilibrium (DSGE) models that are solved using a second-order accurate approximation. I apply the Kalman filter to a state-space representation of the second-order solution based on the ?pruning? scheme of Kim, Kim, Schaumburg and Sims (2008). By contrast to particle filters, no stochastic simulations are needed for the filter here--the present method is thus much faster. In Monte Carlo experiments, the filter here generates more accurate estimates of latent state variables than the ...
Globalization Institute Working Papers , Paper 147

Working Paper
Replicating and Projecting the Path of COVID-19 with a Model-Implied Reproduction Number
http://fedora:8080/fcrepo/rest/objects/authors/; Seitelman, Lily; Glick, Reuven; Lansing, Kevin J.; Petrosky-Nadeau, Nicolas (2020-06-30)
We fit a simple epidemiology model to daily data on the number of currently-infected cases of COVID-19 in China, Italy, the United States, and Brazil. These four countries can be viewed as representing different stages, from late to early, of a COVID-19 epidemic cycle. We solve for a model-implied effective reproduction number Rt each day so that the model closely replicates the daily number of currently infected cases in each country. Using the model-implied time series of Rt, we construct a smoothed version of the in-sample trajectory which is used to project the future evolution of Rt and ...
Working Paper Series , Paper 2020-24

Working Paper
Finite-Order VAR Representation of Linear Rational Expectations Models: With Some Lessons for Monetary Policy
Martinez-Garcia, Enrique (2016-09-01)
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
Search Complementarities, Aggregate Fluctuations, and Fiscal Policy
Yu, Yang; Mandelman, Federico S.; Zanetti, Francesco; Fernández-Villaverde, Jesús (2019-05-01)
We develop a quantitative business cycle model with search complementarities in the inter-firm matching process that entails a multiplicity of equilibria. An active equilibrium with strong joint venture formation, large output, and low unemployment coexists with a passive equilibrium with low joint venture formation, low output, and high unemployment. {{p}} Changes in fundamentals move the system between the two equilibria, generating large and persistent business cycle fluctuations. The volatility of shocks is important for the selection and duration of each equilibrium. Sufficiently adverse ...
FRB Atlanta Working Paper , Paper 2019-9

Working Paper
A Generalized Approach to Indeterminacy in Linear Rational Expectations Models
Bianchi, Francesco; Nicolo, Giovanni (2019-05)
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
A Matter of Perspective: Mapping Linear Rational Expectations Models into Finite-Order VAR Form
Martinez-Garcia, Enrique (2020-05-29)
This paper considers the characterization of the reduced-form solution of a large class of linear rational expectations models. I show that under certain conditions, if a solution exists and is unique, it can be cast in finite-order VAR form. I also investigate the conditions for the VAR form to be stationary with a well-defined residual variance-covariance matrix in equilibrium, for the shocks to be recoverable, and for local identification of the structural parameters for estimation from the sample likelihood. An application to the workhorse New Keynesian model with accompanying Matlab ...
Globalization Institute Working Papers , Paper 389

Working Paper
Constructing Applicants from Loan-Level Data: A Case Study of Mortgage Applications
Elzayn, Hadi; Freyaldenhoven, Simon; Shin, Minchul (2025-02-04)
We develop a clustering-based algorithm to detect loan applicants who submit multiple applications (“cross-applicants”) in a loan-level dataset without personal identifiers. A key innovation of our approach is a novel evaluation method that does not require labeled training data, allowing us to optimize the tuning parameters of our machine learning algorithm. By applying this methodology to Home Mortgage Disclosure Act (HMDA) data, we create a unique dataset that consolidates mortgage applications to the individual applicant level across the United States. Our preferred specification ...
Working Papers , Paper 25-05

Working Paper
Learning Monetary Policy Strategies at the Effective Lower Bound with Sudden Surprises
Rottner, Matthias; Melosi, Leonardo; Krane, Spencer D. (2023-06-07)
Central banks around the world have revised their operating frameworks in an attempt to counter the challenges presented by the effective lower bound (ELB) on policy rates. We examine how private sector agents might learn such a new regime and the effect of future shocks on that process. In our model agents use Bayesian updating to learn the parameters of an asymmetric average inflation targeting rule that is adopted while at the ELB. Little can be discovered until the economy improves enough that rates would be near liftoff under the old policy regime; learning then proceeds until either the ...
Working Paper Series , Paper WP 2023-22

Working Paper
Filling in the Blanks: Network Structure and Interbank Contagion
von Peter, Goetz; Craig, Ben R.; Anand, Kartik (2014-10-02)
The network pattern of financial linkages is important in many areas of banking and finance. Yet bilateral linkages are often unobserved, and maximum entropy serves as the leading method for estimating counterparty exposures. This paper proposes an efficient alternative that combines information-theoretic arguments with economic incentives to produce more realistic interbank networks that preserve important characteristics of the original interbank market. The method loads the most probable links with the largest exposures consistent with the total lending and borrowing of each bank, yielding ...
Working Papers (Old Series) , Paper 1416

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