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Documentation: add missing author

pac-components
Johannes Pfeifer 2021-10-17 15:09:29 +02:00
parent 42165b9893
commit 226ed712bd
5 changed files with 9 additions and 9 deletions
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2
doc/manual/source/bibliography.rst
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@ -24,7 +24,7 @@ Bibliography
* Collard, Fabrice and Michel Juillard (2001a): “Accuracy of stochastic perturbation methods: The case of asset pricing models,” *Journal of Economic Dynamics and Control*, 25, 979–999.
* Collard, Fabrice and Michel Juillard (2001b): “A Higher-Order Taylor Expansion Approach to Simulation of Stochastic Forward-Looking Models with an Application to a Non-Linear Phillips Curve,” *Computational Economics*, 17, 125–139.
* Corana, Angelo, M. Marchesi, Claudio Martini, and Sandro Ridella (1987): “Minimizing multimodal functions of continuous variables with the “simulated annealing” algorithm”, *ACM Transactions on Mathematical Software*, 13(3), 262–280.
* Cuba-Borda, Pablo, Luca Guerrieri, and Matteo Iacoviello (2019): "Likelihood evaluation of models with occasionally binding constraints", Journal of Applied Econometrics, 34(7), 1073-1085
* Cuba-Borda, Pablo, Luca Guerrieri, Matteo Iacoviello, and Molin Zhong (2019): "Likelihood evaluation of models with occasionally binding constraints", Journal of Applied Econometrics, 34(7), 1073-1085
* Del Negro, Marco and Frank Schorfheide (2004): “Priors from General Equilibrium Models for VARs”, *International Economic Review*, 45(2), 643–673.
* Dennis, Richard (2007): “Optimal Policy In Rational Expectations Models: New Solution Algorithms”, *Macroeconomic Dynamics*, 11(1), 31–55.
* Duffie, Darrel and Kenneth J. Singleton (1993): “Simulated Moments Estimation of Markov Models of Asset Prices”, *Econometrica*, 61(4), 929-952.

6
doc/manual/source/the-model-file.rst
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@ -4712,7 +4712,7 @@ Occasionally binding constraints (OCCBIN)
Dynare allows simulating models with up to two occasionally-binding constraints by
relying on a piecewise linear solution as in *Guerrieri and Iacoviello (2015)*.
It also allows estimating such models employing either the inversion filter of
*Cuba-Borda, Guerrieri, and Iacoviello (2019)* or the piecewise Kalman filter of
*Cuba-Borda, Guerrieri, Iacoviello, and Zhong (2019)* or the piecewise Kalman filter of
*Giovannini, Pfeiffer, and Ratto (2021)*. To trigger computations involving
occasionally-binding constraints requires
@ -4953,7 +4953,7 @@ All of these elements are discussed in the following.
.. option:: likelihood_inversion_filter
Employ the inversion filter of *Cuba-Borda, Guerrieri, and Iacoviello (2019)* when estimating
Employ the inversion filter of *Cuba-Borda, Guerrieri, Iacoviello, and Zhong (2019)* when estimating
the model. Default: not enabled.
.. option:: likelihood_piecewise_kalman_filter
@ -4967,7 +4967,7 @@ All of these elements are discussed in the following.
.. option:: smoother_inversion_filter
Employ the inversion filter of *Cuba-Borda, Guerrieri, and Iacoviello (2019)* when running the
Employ the inversion filter of *Cuba-Borda, Guerrieri, Iacoviello, and Zhong (2019)* when running the
smoother. Default: not enabled.
.. option:: smoother_piecewise_kalman_filter

4
license.txt
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@ -29,7 +29,7 @@ Files: matlab/+occbin/IVF_core.m
matlab/+occbin/match_function.m
Copyright: none
License: public-domain-inversion-filter
Original authors: Pablo Cuba-Borda, Luca Guerrieri, and Matteo Iacoviello
Original authors: Pablo Cuba-Borda, Luca Guerrieri, Matteo Iacoviello, and Molin Zhong
Original file downloaded from:
http://www.lguerrieri.com/jae-replication.zip
Adapted for Dynare by Dynare Team.
@ -38,7 +38,7 @@ License: public-domain-inversion-filter
However the authors would appreciate acknowledgement of the source by
citation of any of the following papers:
.
Pablo Cuba-Borda, Luca Guerrieri, and Matteo Iacoviello (2019): "Likelihood evaluation of models
Pablo Cuba-Borda, Luca Guerrieri, Matteo Iacoviello, and Molin Zhong (2019): "Likelihood evaluation of models
with occasionally binding constraints", Journal of Applied Econometrics, 34(7), 1073-1085
Files: matlab/+occbin/make_chart.m

4
matlab/+occbin/IVF_core.m
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@ -19,7 +19,7 @@ function [filtered_errs, resids, Emat, stateval, error_code] = IVF_core(M_,oo_,o
% - obs [T by N_obs] observed data
% - init_val [N by 1] initial value of endogenous variables
% Original authors: Pablo Cuba-Borda, Luca Guerrieri, Matteo Iacoviello and Molin Zhong
% Original authors: Pablo Cuba-Borda, Luca Guerrieri, Matteo Iacoviello, and Molin Zhong
% Original file downloaded from:
% http://www.lguerrieri.com/jae-replication.zip
% Adapted for Dynare by Dynare Team.
@ -28,7 +28,7 @@ function [filtered_errs, resids, Emat, stateval, error_code] = IVF_core(M_,oo_,o
% However the authors would appreciate acknowledgement of the source by
% citation of any of the following papers:
%
% Pablo Cuba-Borda, Luca Guerrieri, and Matteo Iacoviello (2019): "Likelihood evaluation of models
% Pablo Cuba-Borda, Luca Guerrieri, Matteo Iacoviello, and Molin Zhong (2019): "Likelihood evaluation of models
% with occasionally binding constraints", Journal of Applied Econometrics,
% 34(7), 1073-1085

2
matlab/+occbin/match_function.m
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@ -28,7 +28,7 @@ function [resids, grad, state_out, E, M_, out] = match_function(err_0, obs_list,
% However the authors would appreciate acknowledgement of the source by
% citation of any of the following papers:
%
% Pablo Cuba-Borda, Luca Guerrieri, and Matteo Iacoviello (2019): "Likelihood evaluation of models
% Pablo Cuba-Borda, Luca Guerrieri, Matteo Iacoviello, and Molin Zhong (2019): "Likelihood evaluation of models
% with occasionally binding constraints", Journal of Applied Econometrics,
% 34(7), 1073-1085