Hi all, As I was trying to see how adf performs under different scenarios, I found somewhat surprising results. ADF seems to work fine when there are either an intercept, or a trend, or both. But when there are none, the distribution of the resulting p-value become an uniform distribution. What did I do wrong? Fred Here is the script to generate random walk series and then test to see how adf works or not working: # simulation of unit root process # y(t)=b0+rho*y(t-1)+b1*time+error # there are b0, rho, and b1 parameters to set scalar N = 50 # series length scalar R = 1000 # repeats or resampling nulldata N --preserve scalar rho = 1 # set rho from 0.0 to 1.0 scalar b0 = 0 # set intercept b0 = any value scalar b1 = 0 # set trend b1 to any value string outfilename = sprintf("unitroot,N=%d,b0=%3.0f,b1=%3.0f,rho=%3.2f.gdt",N,b0,b1,rho) loop R --progressive --quiet series e = normal(0,10) # error vector series y = 0 y = b0 + rho*y(-1) + b1*index + e ols y const y(-1) index --quiet scalar b_c = $coeff(const) scalar b_rho = $coeff[2] scalar b_t = $coeff[3] adf -1 y --ct --quiet scalar ct_p = $pvalue scalar ct_t = $test adf -1 y --c --quiet scalar c_p = $pvalue scalar c_t = $test adf -1 y --nc --quiet scalar nc_p = $pvalue scalar nc_t = $test print b_c b_rho b_t ct_p ct_t c_p c_t nc_p nc_t store "@outfilename" b_c b_rho b_t ct_p ct_t c_p c_t nc_p nc_t endloop open "@outfilename" freq b_c --plot=display freq b_rho --plot=display freq b_t --plot=display freq ct_p --plot=display #freq ct_t --plot=display freq c_p --plot=display #freq c_t --plot=display freq nc_p --plot=display #freq nc_t --plot=display