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Working Paper
Optimal Dynamic Capital Requirements and Implementable Capital Buffer Rules
Canzoneri, Matthew B.; Diba, Behzad T.; Guerrieri, Luca; Mishin, Arsenii
(2020-08-06)
We build a quantitatively relevant macroeconomic model with endogenous risk-taking. In our model, deposit insurance and limited liability can lead banks to make risky loans that are socially inefficient. This excessive risk-taking can be triggered by aggregate or sectoral shocks that reduce the return on safer loans. Excessive risk-taking can be avoided by raising bank capital requirements, but unnecessarily tight requirements lower welfare by limiting liquidity producing bank deposits. Consequently, optimal capital requirements are dynamic (or state contingent). We provide examples in which ...
Finance and Economics Discussion Series
, Paper 2020-056
Working Paper
Simultaneous Spatial Panel Data Models with Common Shocks
Lu, Lina
(2017-08-09)
I consider a simultaneous spatial panel data model, jointly modeling three effects: simultaneous effects, spatial effects and common shock effects. This joint modeling and consideration of cross-sectional heteroskedasticity result in a large number of incidental parameters. I propose two estimation approaches, a quasi-maximum likelihood (QML) method and an iterative generalized principal components (IGPC) method. I develop full inferential theories for the estimation approaches and study the trade-off between the model specifications and their respective asymptotic properties. I further ...
Supervisory Research and Analysis Working Papers
, Paper RPA 17-3
Working Paper
High-Dimensional Copula-Based Distributions with Mixed Frequency Data
Patton, Andrew J.; Oh, Dong Hwan
(2015-05-19)
This paper proposes a new model for high-dimensional distributions of asset returns that utilizes mixed frequency data and copulas. The dependence between returns is decomposed into linear and nonlinear components, enabling the use of high frequency data to accurately forecast linear dependence, and a new class of copulas designed to capture nonlinear dependence among the resulting uncorrelated, low frequency, residuals. Estimation of the new class of copulas is conducted using composite likelihood, facilitating applications involving hundreds of variables. In- and out-of-sample tests confirm ...
Finance and Economics Discussion Series
, Paper 2015-50
Working Paper
Jointly Estimating Macroeconomic News and Surprise Shocks
Kilian, Lutz; Plante, Michael D.; Richter, Alexander W.
(2023-04-20)
This paper clarifies the conditions under which the state-of-the-art approach to identifying TFP news shocks in Kurmann and Sims (2021, KS) identifies not only news shocks but also surprise shocks. We examine the ability of the KS procedure to recover responses to these shocks from data generated by a conventional New Keynesian DSGE model. Our analysis shows that the KS response estimator tends to be strongly biased even in the absence of measurement error. This bias worsens in realistically small samples, and the estimator becomes highly variable. Incorporating a direct measure of TFP news ...
Working Papers
, Paper 2304
Working Paper
State-Dependent Local Projections
Goncalves, Silvia; Herrera, Ana María; Kilian, Lutz; Pesavento, Elena
(2023-04-19)
Do state-dependent local projections asymptotically recover the population responses of macroeconomic aggregates to structural shocks? The answer to this question depends on how the state of the economy is determined and on the magnitude of the shocks. When the state is exogenous, the local projection estimator recovers the population response regardless of the shock size. When the state depends on macroeconomic shocks, as is common in empirical work, local projections only recover the conditional response to an infinitesimal shock, but not the responses to larger shocks of interest in many ...
Working Papers
, Paper 2302
Working Paper
A Novel MIMIC-Style Model of European Bank Technical Efficiency and Productivity Growth
Murphy, Anthony; Mamatzakis, Emmanuel; Tsionas, Mike G.; Izzeldin, Marwan
(2020-05-19)
Using Bayesian Monte Carlo methods, we augment a stochastic distance function measure of bank efficiency and productivity growth with indicators of capitalization, return and risk. Our novel Multiple Indicator-Multiple Cause (MIMIC) style model generates more precise estimates of policy relevant parameters such as returns to scale, technical inefficiency and productivity growth. We find considerable variation in the performance of EU-15 banks over the period 2008 to 2015. For the vast majority of banks, productivity growth – the sum of efficiency and technical changes – is negative, ...
Working Papers
, Paper 2012
Working Paper
Commodity Exports, Financial Frictions and International Spillovers
Houssa, Romain; Mohimont, Jolan; Otrok, Christopher
(2022-12-17)
This paper offers a solution to the international co-movement puzzle found in open-economy macroeconomic models. We develop a small open-economy (SOE) dynamic stochastic general equilibrium (DSGE) model describing three endogenous channels that capture spillovers from the world to a commodity exporter: a world commodity price channel, a domestic commodity supply channel and a financial channel. We estimate our model with Bayesian methods on two commodity-exporting SOEs, namely Canada and South Africa. In addition to explaining international business cycle synchronization, the new model ...
Globalization Institute Working Papers
, Paper 419
Report
Measuring Real Activity Using a Weekly Economic Index
Mertens, Karel; Trivedi, Mihir; Lewis, Daniel J.; Stock, James H.
(2020-04-01)
This paper describes a weekly economic index (WEI) developed to track the rapid economic developments associated with the onset of and policy response to the novel coronavirus in the United States. The WEI is a weekly composite index of real economic activity, with eight of ten series available the Thursday after the end of the reference week. In addition to being a weekly real activity index, the WEI has strong predictive power for output measures and provided an accurate nowcast of current-quarter GDP growth in the first half of 2020. We document how the WEI responded to key events and data ...
Staff Reports
, Paper 920
Working Paper
Sequential Bayesian Inference for Vector Autoregressions with Stochastic Volatility
Zito, John; Bognanni, Mark
(2019-12-16)
We develop a sequential Monte Carlo (SMC) algorithm for Bayesian inference in vector autoregressions with stochastic volatility (VAR-SV). The algorithm builds particle approximations to the sequence of the model’s posteriors, adapting the particles from one approximation to the next as the window of available data expands. The parallelizability of the algorithm’s computations allows the adaptations to occur rapidly. Our particular algorithm exploits the ability to marginalize many parameters from the posterior analytically and embeds a known Markov chain Monte Carlo (MCMC) algorithm for ...
Working Papers
, Paper 19-29
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
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