diff --git a/doc/userguide/ch-estadv.tex b/doc/userguide/ch-estadv.tex
index 04f2836f771dded41270405d7c385e1e197a115e..ac47ea5305faa7458ba2cf58931a7ea651c31293 100644
--- a/doc/userguide/ch-estadv.tex
+++ b/doc/userguide/ch-estadv.tex
@@ -225,7 +225,7 @@ end;}\\
 We add the following commands to ask Dynare to run a basic estimation of our model:\\
 \\
 \texttt{estimation(datafile=fsdat,nobs=192,loglinear,mh\_replic=2000,\\
-mode\_compute=4,mh\_nblocks=2,mh\_drop=0.45,mh\_jscale=0.65);}\\
+mode\_compute=6,mh\_nblocks=2,mh\_drop=0.45,mh\_jscale=0.65);}\\
 
 \textsf{\textbf{NOTE!}} As mentioned earlier, we need to instruct Dynare to log-linearize our model, since it contains non-linear equations in non-stationary variables. A simple linearization would fail as these variables do not have a steady state. Fortunately, taking the log of the equations involving non-stationary variables does the job of linearizing them.\\
 
@@ -234,19 +234,19 @@ We have seen each part of the .mod separately; it's now time to get a picture of
 \\
 \texttt{var m P c e W R k d n l Y\_obs P\_obs y dA; \\
 varexo e\_a e\_m;\\
-\\
-parameters alp, bet, gam, mst, rho, psi, del;
+parameters alp, bet, gam, mst, rho, psi, del;\\
 \\
 model;\\
 dA = exp(gam+e\_a);\\
 log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e\_m;\\
--P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))*k\textasciicircum (alp-1)\\
-*n(+1)\textasciicircum (1-alp)+(1-del)*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;\\
+-P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))\\
+*k\textasciicircum (alp-1)*n(+1)\textasciicircum (1-alp)+(1-del)\\
+*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;\\
 W = l/n;\\
 -(psi/(1-psi))*(c*P/(1-n))+l/n = 0;\\
 R = P*(1-alp)*exp(-alp*(gam+e\_a))*k(-1)\textasciicircum alp*n\textasciicircum (-alp)/W;\\
-1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e\_a))*k(-1)\textasciicircum alp*n\textasciicircum (1-alp)/(m*l*c(+1)*P(+1)) = 0;\\
-c+k = exp(-alp*(gam+e\_a))*k(-1)\textasciicircum alp*n\textasciicircum (1-alp)+(1-del)*exp(-(gam+e\_a))*k(-1);\\
+1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e\_a))*k(-1)\textasciicircum alp*n\textasciicircum (1-alp)/\\(m*l*c(+1)*P(+1)) = 0;\\
+c+k = exp(-alp*(gam+e\_a))*k(-1)\textasciicircum alp*n\textasciicircum (1-alp)+(1-del)\\*exp(-(gam+e\_a))*k(-1);\\
 P*c = m;\\
 m-1+d = l;\\
 e = exp(e\_a);\\
@@ -262,7 +262,7 @@ P\_obs (log(mst)-gam);\\
 Y\_obs (gam);\\
 end;\\
 \\
-unit\_root\_vars = P\_obs Y\_obs;\\
+unit\_root\_vars P\_obs Y\_obs;\\
 \\
 initval;\\
 k = 6;\\
@@ -298,7 +298,7 @@ stderr e\_m, inv\_gamma\_pdf, 0.008862, inf;\\
 end;\\
 \\
 estimation(datafile=fsdat,nobs=192,loglinear,mh\_replic=2000,\\
-mode\_compute=4,mh\_nblocks=2,mh\_drop=0.45,mh\_jscale=0.65);}\\
+mode\_compute=6,mh\_nblocks=2,mh\_drop=0.45,mh\_jscale=0.65);}\\
 \\
 
 \subsection{Summing it up}
diff --git a/doc/userguide/ch-estbase.tex b/doc/userguide/ch-estbase.tex
index 98232fa3a0744540ba10ef8a207cac95fd744e3f..c0568653caef067c5807593b2b0b7cb6310028c2 100644
--- a/doc/userguide/ch-estbase.tex
+++ b/doc/userguide/ch-estbase.tex
@@ -35,7 +35,7 @@ end;}\\
 \section{Declaring observable variables}
 This should not come as a surprise. Dynare must know which variables are observable for the estimation procedure. \textsf{\textbf{NOTE!}} These variables must be available in the data file, as explained in section \ref{sec:estimate} below. For the moment, we write:\\
 \\
-\texttt{varobs Y;}\\
+\texttt{varobs y;}\\
 
 \section{Specifying the steady state} \label{sec:ssest}
 Before Dynare estimates a model, it first linearizes it around a steady state. Thus, a steady state must exist for the model and although Dynare can calculate it, we must give it a hand by declaring approximate values for the steady state. This is just as explained in details and according to the same syntax outlined in chapter \ref{ch:solbase}, covering the \texttt{initval}, \texttt{steady} and \texttt{check} commands. In fact, as this chapter uses the same model as that outlined in chapter \ref{ch:solbase}, the steady state block will look exactly the same.\\
@@ -138,7 +138,8 @@ displayed). Actually seeing if the various blocks of Metropolis-Hastings runs co
 Finally, coming back to our example, we could choose a standard option:\\
 \\
 \texttt{estimation(datafile=simuldataRBC,nobs=200,first\_obs=500,\\
-mh\_replic=2000,mh\_nblocks=2,mh\_drop=0.45,mh\_jscale=0.8); }\\
+mh\_replic=2000,mh\_nblocks=2,mh\_drop=0.45,mh\_jscale=0.8,\\
+mode\_compute=6); }\\
 
 This ends our description of the .mod file.
 
@@ -147,7 +148,6 @@ To summarize and to get a complete perspective on our work so far, here is the c
 \\
 \texttt{var y c k i l y\_l w r  z;\\
 varexo e;\\
-\\
 parameters beta psi delta alpha rho epsilon;\\
 \\
 model;\\
@@ -162,7 +162,7 @@ model;\\
   z = rho*z(-1)+e;\\
 end;\\
 \\
-varobs Y;\\
+varobs y;\\
 \\
 initval;\\
   k = 9;\\
@@ -175,7 +175,6 @@ initval;\\
 end;\\
 \\
 steady;\\
-\\
 check;\\
 \\
 estimated\_params;\\
@@ -189,7 +188,8 @@ stderr e, inv\_gamma\_pdf, 0.01, inf;\\
 end;\\
 \\
 estimation(datafile=simuldataRBC,nobs=200,first\_obs=500,\\
-mh\_replic=2000,mh\_nblocks=2,mh\_drop=0.45,mh\_jscale=0.8); }
+mh\_replic=2000,mh\_nblocks=2,mh\_drop=0.45,mh\_jscale=0.8,\\
+mode\_compute=6); }
 \\
 
 
diff --git a/doc/userguide/ch-soladv.tex b/doc/userguide/ch-soladv.tex
index 5f5b358276a8190a77b00c9181a23cbc58093a01..6f39d29d23cc563395ee9ad56c3f30015e948b33 100644
--- a/doc/userguide/ch-soladv.tex
+++ b/doc/userguide/ch-soladv.tex
@@ -87,8 +87,9 @@ So that you can gain experience by manipulating the entire model, here is the co
 \\
 \\
 \texttt{var y, c, k, a, h, b;\\
-varexo e,u;\\
+varexo e, u;\\
 parameters beta, rho, alpha, delta, theta, psi, tau;\\
+\\
 alpha = 0.36;\\
 rho   = 0.95;\\
 tau   = 0.025;\\
@@ -96,6 +97,7 @@ beta  = 0.99;\\
 delta = 0.025;\\
 psi   = 0;\\
 theta = 2.95;\\
+\\
 phi   = 0.1;\\
 \\
 model;\\
diff --git a/doc/userguide/ch-solbase.tex b/doc/userguide/ch-solbase.tex
index bd37d28eeedd87f4c8b9d7b0411050d16b97ceea..d4ed41a7a57a3f1dd660e800d801d0290a814632 100644
--- a/doc/userguide/ch-solbase.tex
+++ b/doc/userguide/ch-solbase.tex
@@ -452,13 +452,14 @@ For completion's sake, and for the pleasure of seeing our work bear its fruits,
 
 \texttt{var y c k i l y\_l w r  z;\\
 varexo e;\\
-parameters beta psi delta alpha rho sigma epsilon;\\
+parameters beta psi delta alpha rho gamma sigma epsilon;\\
+\\
 alpha   = 0.33;\\
 beta    = 0.99;\\
 delta   = 0.023;\\
 psi     = 1.75;\\
-rho     = 0.95; \\ 
-sigma   = (0.007\/(1-alpha));\\
+rho     = 0.95;\\
+sigma   = (0.007/(1-alpha));\\
 epsilon = 10;\\
 \\
 model;\\
@@ -475,23 +476,22 @@ end;\\
 \\
 initval;\\
   k = 9;\\
-  c = 0.7;\\
+  c = 0.76;\\
   l = 0.3;\\
-  w = 2.0;\\
-  r = 0;\\
-  z = 0; \\
+  w = 2.07;\\
+  r = 0.03;\\
+  z = 0;\\
   e = 0;\\
 end;\\
 \\
 steady;\\
-\\
 check;\\
 \\
 shocks;\\
 var e = sigma\textasciicircum 2;\\
 end;\\
 \\
-stoch\_simul(periods=2100);}\\
+stoch\_simul(periods=2100);}
 
 \subsection{The deterministic model (case of temporary shock)}
 
@@ -502,7 +502,7 @@ alpha   = 0.33;\\
 beta    = 0.99;\\
 delta   = 0.023;\\
 psi     = 1.75;\\
-sigma   = (0.007\/(1-alpha));\\
+sigma   = (0.007/(1-alpha));\\
 epsilon = 10;\\
 \\
 model;\\
@@ -530,7 +530,7 @@ steady;\\
 check;\\
 \\
 shocks;\\
-var z;
+var z;\\
 periods 1:9;\\
 values 0.1;\\
 end;\\