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Optimal Automatic Stabilizers
McKay, Alisdair - 2016
Should the generosity of unemployment benefits and the progressivity of income taxes depend on the presence of business cycles? This paper proposes a tractable model where there is a role for social insurance against uninsurable shocks to income and unemployment, as well as inefficient business...
Persistent link: https://www.econbiz.de/10012456317
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A Conic Algorithm for the Group Minimization Problem
Simeone, Bruno - 1976
A new algorithm for the group minimization problem (GP) is proposed. The algorithm can be broadly described as follows …-known algorithm of Glover, and checked for non-negativity. The first non-negative point is an optimal solution of (GP). Advantages and … disadvantages of the algorithm are discussed; in particular, the implementation of the algorithm (which can be easily extended so as …
Persistent link: https://www.econbiz.de/10012478970
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Trading Votes for Votes. A Decentralized Matching Algorithm
Casella, Alessandra - 2015
allocation achieved via sequential pairwise trades, but lends only weak support to the dynamic algorithm itself … three central questions that have parallels in the matching literature: (1) Does a stable allocation of votes always exists …? (2) Is it reachable through a decentralized algorithm? (3) What welfare properties does it possess? We prove that a …
Persistent link: https://www.econbiz.de/10012457024
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A Maximum Likelihood Method for the Incidental Parameter Problem
Moreira, Marcelo - 2008
This paper uses the invariance principle to solve the incidental parameter problem. We seek group actions that preserve the structural parameter and yield a maximal invariant in the parameter space with fixed dimension. M-estimation from the likelihood of the maximal invariant statistic yields...
Persistent link: https://www.econbiz.de/10012464860
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Forming Priors for DSGE Models (and How it Affects the Assessment of Nominal Rigidities)
Del Negro, Marco - 2008
The paper discusses prior elicitation for the parameters of dynamic stochastic general equilibrium (DSGE) models, and provides a method for constructing prior distributions for a subset of these parameters from beliefs about the moments of the endogenous variables. The empirical application...
Persistent link: https://www.econbiz.de/10012464907
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Vector Multiplicative Error Models : Representation and Inference
Cipollini, Fabrizio - 2006
The Multiplicative Error Model introduced by Engle (2002) for positive valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation process with positive support. In this paper we propose a multi-variate extension of such a model, by taking into...
Persistent link: https://www.econbiz.de/10012465970
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Vector Multiplicative Error Models : Representation and Inference
Cipollini, Fabrizio - 2006
The Multiplicative Error Model introduced by Engle (2002) for positive valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation process with positive support. In this paper we propose a multi-variate extension of such a model, by taking into...
Persistent link: https://www.econbiz.de/10012465974
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Stereotypes
Bordalo, Pedro - 2014
We present a model of stereotypes in which a decision maker assessing a group recalls only that group's most representative or distinctive types relative to other groups. Because stereotypes highlight differences between groups, and neglect likely common types, they are especially inaccurate...
Persistent link: https://www.econbiz.de/10012458558
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How to Solve Dynamic Stochastic Models Computing Expectations Just Once
Judd, Kenneth L. - 2011
We introduce a technique called "precomputation of integrals" that makes it possible to compute conditional expectations in dynamic stochastic models in the initial stage of the solution procedure. This technique can be applied to any set of equations that contains conditional expectations, in...
Persistent link: https://www.econbiz.de/10012461240
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An Economic Approach to Regulating Algorithms
Rambachan, Ashesh - 2020
objective function for the algorithm designer and a model of their information sets and interaction. We build such a model that … allows the training data to exhibit a wide range of "biases." Prevailing wisdom is that biased data change how the algorithm … is trained and whether an algorithm should be used at all. In contrast, we find two striking irrelevance results. First …
Persistent link: https://www.econbiz.de/10012481694