Monte Carlo Simulations<BR>Monte Carlo experiments are powerful techniques very often used in applied econometric analyses<BR>to asses the small sample behavior of estimator and test statistics. A Monte Carlo experiment<BR>consists in di¤erent parts.<BR>1. De…ne the issue to analyze<BR>2. The data generating process (DGP) where your develop your known process<BR>3. Generating numbers at random<BR>4. Estimation and test statistics for one replication of the loop. Use of procedures<BR>5. Storage and computation of summary statistics over the M replications<BR>To illustrate these di¤erent steps, let us consider the relationship between two independent random<BR>walks (with drifts). Engle and Granger (1987) and Phillips (1996) show that if we regress these<BR>variables on each other, there is a tendency to obtain spurious regressions. This phenomenon is<BR>characterized by values of t&#1048576; ratios for which we would reject the null hypothesis of no<BR>relationships at any sensible signi…cance levels. Moreover the R2 are high because of the common<BR>stochastic trends.<BR>For the data generating process (DGP), let us generate the following independent bivariate process:<BR>