📖 Update manual

parent df084f8e
...@@ -44,6 +44,7 @@ Bibliography ...@@ -44,6 +44,7 @@ Bibliography
* Kim, Jinill and Sunghyun Kim (2003): “Spurious welfare reversals in international business cycle models,” *Journal of International Economics*, 60, 471–500. * Kim, Jinill and Sunghyun Kim (2003): “Spurious welfare reversals in international business cycle models,” *Journal of International Economics*, 60, 471–500.
* Kanzow, Christian and Stefania Petra (2004): “On a semismooth least squares formulation of complementarity problems with gap reduction,” *Optimization Methods and Software*, 19, 507–525. * Kanzow, Christian and Stefania Petra (2004): “On a semismooth least squares formulation of complementarity problems with gap reduction,” *Optimization Methods and Software*, 19, 507–525.
* Kim, Jinill, Sunghyun Kim, Ernst Schaumburg, and Christopher A. Sims (2008): “Calculating and using second-order accurate solutions of discrete time dynamic equilibrium models,” *Journal of Economic Dynamics and Control*, 32(11), 3397–3414. * Kim, Jinill, Sunghyun Kim, Ernst Schaumburg, and Christopher A. Sims (2008): “Calculating and using second-order accurate solutions of discrete time dynamic equilibrium models,” *Journal of Economic Dynamics and Control*, 32(11), 3397–3414.
* Komunjer, Ivana and Ng, Serena (2011): ”Dynamic identification of dynamic stochastic general equilibrium models”, *Econometrica*, 79, 1995–2032.
* Koop, Gary (2003), *Bayesian Econometrics*, John Wiley & Sons. * Koop, Gary (2003), *Bayesian Econometrics*, John Wiley & Sons.
* Koopman, S. J. and J. Durbin (2000): “Fast Filtering and Smoothing for Multivariate State Space Models,” *Journal of Time Series Analysis*, 21(3), 281–296. * Koopman, S. J. and J. Durbin (2000): “Fast Filtering and Smoothing for Multivariate State Space Models,” *Journal of Time Series Analysis*, 21(3), 281–296.
* Koopman, S. J. and J. Durbin (2003): “Filtering and Smoothing of State Vector for Diffuse State Space Models,” *Journal of Time Series Analysis*, 24(1), 85–98. * Koopman, S. J. and J. Durbin (2003): “Filtering and Smoothing of State Vector for Diffuse State Space Models,” *Journal of Time Series Analysis*, 24(1), 85–98.
...@@ -52,13 +53,16 @@ Bibliography ...@@ -52,13 +53,16 @@ Bibliography
* Liu, Jane and Mike West (2001): “Combined parameter and state estimation in simulation-based filtering”, in *Sequential Monte Carlo Methods in Practice*, Eds. Doucet, Freitas and Gordon, Springer Verlag. * Liu, Jane and Mike West (2001): “Combined parameter and state estimation in simulation-based filtering”, in *Sequential Monte Carlo Methods in Practice*, Eds. Doucet, Freitas and Gordon, Springer Verlag.
* Lubik, Thomas and Frank Schorfheide (2007): “Do Central Banks Respond to Exchange Rate Movements? A Structural Investigation,” *Journal of Monetary Economics*, 54(4), 1069–1087. * Lubik, Thomas and Frank Schorfheide (2007): “Do Central Banks Respond to Exchange Rate Movements? A Structural Investigation,” *Journal of Monetary Economics*, 54(4), 1069–1087.
* Murray, Lawrence M., Emlyn M. Jones and John Parslow (2013): “On Disturbance State-Space Models and the Particle Marginal Metropolis-Hastings Sampler”, *SIAM/ASA Journal on Uncertainty Quantification*, 1, 494–521. * Murray, Lawrence M., Emlyn M. Jones and John Parslow (2013): “On Disturbance State-Space Models and the Particle Marginal Metropolis-Hastings Sampler”, *SIAM/ASA Journal on Uncertainty Quantification*, 1, 494–521.
* Mutschler, Willi (2015): “Identification of DSGE models - The effect of higher-order approximation and pruning“, *Journal of Economic Dynamics & Control*, 56, 34-54.
* Pearlman, Joseph, David Currie, and Paul Levine (1986): “Rational expectations models with partial information,” *Economic Modelling*, 3(2), 90–105. * Pearlman, Joseph, David Currie, and Paul Levine (1986): “Rational expectations models with partial information,” *Economic Modelling*, 3(2), 90–105.
* Planas, Christophe, Marco Ratto and Alessandro Rossi (2015): “Slice sampling in Bayesian estimation of DSGE models”. * Planas, Christophe, Marco Ratto and Alessandro Rossi (2015): “Slice sampling in Bayesian estimation of DSGE models”.
* Pfeifer, Johannes (2013): “A Guide to Specifying Observation Equations for the Estimation of DSGE Models”. * Pfeifer, Johannes (2013): “A Guide to Specifying Observation Equations for the Estimation of DSGE Models”.
* Pfeifer, Johannes (2014): “An Introduction to Graphs in Dynare”. * Pfeifer, Johannes (2014): “An Introduction to Graphs in Dynare”.
* Qu, Zhongjun and Tkachenko, Denis (2012): “Identification and frequency domain quasi-maximum likelihood estimation of linearized dynamic stochastic general equilibrium models“, *Quantitative Economics*, 3, 95–132.
* Rabanal, Pau and Juan Rubio-Ramirez (2003): “Comparing New Keynesian Models of the Business Cycle: A Bayesian Approach,” Federal Reserve of Atlanta, *Working Paper Series*, 2003-30. * Rabanal, Pau and Juan Rubio-Ramirez (2003): “Comparing New Keynesian Models of the Business Cycle: A Bayesian Approach,” Federal Reserve of Atlanta, *Working Paper Series*, 2003-30.
* Raftery, Adrian E. and Steven Lewis (1992): “How many iterations in the Gibbs sampler?,” in *Bayesian Statistics, Vol. 4*, ed. J.O. Berger, J.M. Bernardo, A.P. * Dawid, and A.F.M. Smith, Clarendon Press: Oxford, pp. 763-773. * Raftery, Adrian E. and Steven Lewis (1992): “How many iterations in the Gibbs sampler?,” in *Bayesian Statistics, Vol. 4*, ed. J.O. Berger, J.M. Bernardo, A.P. * Dawid, and A.F.M. Smith, Clarendon Press: Oxford, pp. 763-773.
* Ratto, Marco (2008): “Analysing DSGE models with global sensitivity analysis”, *Computational Economics*, 31, 115–139. * Ratto, Marco (2008): “Analysing DSGE models with global sensitivity analysis”, *Computational Economics*, 31, 115–139.
* Ratto, Marco and Iskrev, Nikolay (2011): “Identification Analysis of DSGE Models with DYNARE.“, *MONFISPOL* 225149.
* Schorfheide, Frank (2000): “Loss Function-based evaluation of DSGE models,” *Journal of Applied Econometrics*, 15(6), 645–670. * Schorfheide, Frank (2000): “Loss Function-based evaluation of DSGE models,” *Journal of Applied Econometrics*, 15(6), 645–670.
* Schmitt-Grohé, Stephanie and Martin Uríbe (2004): “Solving Dynamic General Equilibrium Models Using a Second-Order Approximation to the Policy Function,” *Journal of Economic Dynamics and Control*, 28(4), 755–775. * Schmitt-Grohé, Stephanie and Martin Uríbe (2004): “Solving Dynamic General Equilibrium Models Using a Second-Order Approximation to the Policy Function,” *Journal of Economic Dynamics and Control*, 28(4), 755–775.
* Schnabel, Robert B. and Elizabeth Eskow (1990): “A new modified Cholesky algorithm,” *SIAM Journal of Scientific and Statistical Computing*, 11, 1136–1158. * Schnabel, Robert B. and Elizabeth Eskow (1990): “A new modified Cholesky algorithm,” *SIAM Journal of Scientific and Statistical Computing*, 11, 1136–1158.
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...@@ -9154,15 +9154,27 @@ Performing identification analysis ...@@ -9154,15 +9154,27 @@ Performing identification analysis
* minimal system as in *Komunjer and Ng (2011)* * minimal system as in *Komunjer and Ng (2011)*
* reduced-form solution and linear rational expectation model * reduced-form solution and linear rational expectation model
as in *Ratto and Iskrev (2011)* as in *Ratto and Iskrev (2011)*
Note that for orders 2 and 3, all identification checks are based on the pruned
state space system as in *Mutschler (2015)*. That is, theoretical moments and
spectrum are computed from the pruned ABCD-system, whereas the minimal system
criteria is based on the first-order system, but augmented by the theoretical
(pruned) mean at order 2 or 3.
2. Identification strength analysis based on sample information matrix as in 2. Identification strength analysis based on (theoretical or simulated) curvature of
*Ratto and Iskrev (2011)* moment information matrix as in *Ratto and Iskrev (2011)*
3. Parameter checks based on nullspace and multicorrelation coefficients to 3. Parameter checks based on nullspace and multicorrelation coefficients to
determine which (combinations of) parameters are involved determine which (combinations of) parameters are involved
*General Options* *General Options*
.. option:: order = 1|2|3
Order of approximation. At orders 2 and 3 identification is based on the
pruned state space system. Note that the order set in other functions does
not overwrite the default.
Default: ``1``.
.. option:: parameter_set = OPTION .. option:: parameter_set = OPTION
See :opt:`parameter_set <parameter_set = OPTION>` for See :opt:`parameter_set <parameter_set = OPTION>` for
...@@ -9220,13 +9232,15 @@ Performing identification analysis ...@@ -9220,13 +9232,15 @@ Performing identification analysis
* ``0``: efficient sylvester equation method to compute * ``0``: efficient sylvester equation method to compute
analytical derivatives analytical derivatives
* ``1``: kronecker products method to compute analytical * ``1``: kronecker products method to compute analytical
derivatives derivatives (only at order=1)
* ``-1``: numerical two-sided finite difference method * ``-1``: numerical two-sided finite difference method
to compute all identification Jacobians to compute all identification Jacobians (numerical tolerance
level is equal to ``options_.dynatol.x``)
* ``-2``: numerical two-sided finite difference method * ``-2``: numerical two-sided finite difference method
to compute derivatives of steady state and dynamic to compute derivatives of steady state and dynamic
model numerically, the identification Jacobians are model numerically, the identification Jacobians are
then computed analytically then computed analytically (numerical tolerance
level is equal to ``options_.dynatol.x``)
Default: ``0``. Default: ``0``.
...@@ -9297,7 +9311,7 @@ Performing identification analysis ...@@ -9297,7 +9311,7 @@ Performing identification analysis
.. option:: no_identification_spectrum .. option:: no_identification_spectrum
Disables computations of identification check based on Disables computations of identification check based on
Qu and Tkachenko (2012)'s G, i.e. Gram matrix of derivatives of *Qu and Tkachenko (2012)*'s G, i.e. Gram matrix of derivatives of
first moment plus outer product of derivatives of spectral density. first moment plus outer product of derivatives of spectral density.
.. option:: grid_nbr = INTEGER .. option:: grid_nbr = INTEGER
...@@ -9311,7 +9325,7 @@ Performing identification analysis ...@@ -9311,7 +9325,7 @@ Performing identification analysis
.. option:: no_identification_minimal .. option:: no_identification_minimal
Disables computations of identification check based on Disables computations of identification check based on
Komunjer and Ng (2011)'s D, i.e. minimal state space system *Komunjer and Ng (2011)*'s D, i.e. minimal state space system
and observational equivalent spectral density transformations. and observational equivalent spectral density transformations.
*Misc Options* *Misc Options*
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