diff --git a/doc/dynare.texi b/doc/dynare.texi
index 16343cf1c..cc2427546 100644
--- a/doc/dynare.texi
+++ b/doc/dynare.texi
@@ -4759,7 +4759,11 @@ marginal log data density
 posterior mean and highest posterior density interval (shortest credible set) from posterior simulation
 
 @item
-Metropolis-Hastings convergence graphs that still need to be documented
+convergence diagnostic table when only one MCM chain is used or Metropolis-Hastings convergence graphs documented in @cite{Pfeifer (2014)} 
+in case of multiple MCM chains
+
+@item
+table with numerical inefficiency factors of the MCMC
 
 @item
 graphs with prior, posterior, and mode
@@ -4811,7 +4815,7 @@ set_dynare_seed('clock');
 
 @algorithmshead
 
-The Monte  Carlo Markov  Chain (MCMC) diagnostics  are generated  by the
+The Monte  Carlo Markov  Chain (MCMC) diagnostics are generated  by the
 estimation command if @ref{mh_replic} is  larger than 2000 and if option
 @ref{nodiagnostic} is not used. If @ref{mh_nblocks} is equal to one, the
 convergence diagnostics  of @cite{Geweke  (1992,1999)} is  computed.  It
@@ -4834,6 +4838,11 @@ used  to  aggregate  the  parameters   into  a  scalar  statistic  whose
 convergence is  then checked using  the @cite{Brooks and  Gelman (1998)}
 univariate convergence diagnostic.
 
+The inefficiency factors are computed as in @cite{Giordano et al. (2011)} based on 
+Parzen windows as in e.g. @cite{Andrews (1991)}.
+
+based on Parzen 
+
 @optionshead
 
 @table @code
@@ -13365,6 +13374,10 @@ Cycles: The Cycle is the Trend,'' @i{NBER Working Paper}, 10734
 @item
 Andreasen, Martin M., Jesús Fernández-Villaverde, and Juan Rubio-Ramírez (2013): ``The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications,'' @i{NBER Working Paper}, 18983
 
+@item
+Andrews, Donald W.K (1991): ``Heteroskedasticity and autocorrelation consistent covariance matrix estimation'', 
+@i{Econometrica}, 59(3), 817--858
+
 @item
 Backus, David K., Patrick J. Kehoe, and Finn E. Kydland (1992):
 ``International Real Business Cycles,'' @i{Journal of Political
@@ -13460,6 +13473,11 @@ International Meeting on Bayesian Statistics, pp. 169--194, Oxford University Pr
 Geweke, John (1999): ``Using simulation methods for Bayesian econometric models:
 Inference, development and communication,'' @i{Econometric Reviews}, 18(1), 1--73
 
+@item
+Giordani, Paolo, Michael Pitt, and Robert Kohn (2011): ``Bayesian Inference for Time Series State Space Models''
+in: @i{The Oxford Handbook of Bayesian Econometrics}, ed. by John Geweke, Gary Koop, and Herman van Dijk,
+Oxford University Press, 61--124
+
 @item 
 Goffe, William L., Gary D. Ferrier, and John Rogers (1994): ``Global Optimization 
 of Statistical Functions with Simulated Annealing,'' @i{Journal of Econometrics}, 60(1/2), 
@@ -13552,6 +13570,9 @@ of DSGE models''
 @item
 Pfeifer, Johannes (2013): ``A Guide to Specifying Observation Equations for the Estimation of DSGE Models''
 
+@item
+Pfeifer, Johannes (2014): ``An Introduction to Graphs in Dynare''
+
 @item
 Rabanal, Pau and Juan Rubio-Ramirez (2003): ``Comparing New Keynesian
 Models of the Business Cycle: A Bayesian Approach,'' Federal Reserve