On Fri, 28 Jan 2011, GREg Ory wrote: > I need some tips on estimating panel data using nonlinear switching > regression technique. AFAIK there are two ways of solving it. > > The model I estimate is the following: > panel Price const Cost logist Domestic_Sales Export_Sales Soda PCFT > Total_import > > Logistic function is given as logist = 1/(1+exp(1,81*(mu-HHI)/sig)). > > Height of the logistic function is between 0.025 and 0.975. > Mu = mean(height) > Sig = var(height) > > The datafile is attached in case anybody wants to help tackle the > model directly. The theoretic foundation for this analysis is also > attached in the PDF article. I tried to use simultaneous equations to > estimate this model properly but to no avail. > > Second best option is to use loop constructs to model all possible > parameter values in the given range then to choose the model with the > highest $rsq. Mu should be in the range of 0.28 to 0.501 and sig > between 0.01 and 0.201. However I have a problem with implementing a > proper loop. Here is an example > > nulldata 100 > set seed 2478 > HHI =randgen(u,0.21,0.27) > P = randgen(u,100,300) > # open two loops for estimated params > loop for (mu=0.28; mu<0.501; mu+=.01) > loop for (sig=0.01; sig<0.201; sig+=.01) > # construct the dependent variables > genr height = randgen(u,0.025,0.975) > genr mu = mean(height) > genr sig = var(height) > genr logist = 1/(1+exp((mu-HHI)/sig)) > # run OLS regression as an example > ols P const logist > # grab the coefficient estimates and R-squared > genr b1 = $coeff(const) > genr b2 = $coeff(logist) > genr r2 = $rsq > print a b r2 > store coeffs.gdt a b r2 > endloop > endloop
Comments: * In the inner loop you define b1 and b2, but you attempt to print and save a and b (both undefined). Easily fixed, of course. * The saving of scalar values to file via "store" is supported only for "progressive" loops, so you'd have to append the --progressive flag to the inner loop command to get this effect. * However, that would not do what you want: since the "store" occurs in the inner loop, coeffs.gdt would be over-written on each iteration of the outer loop and at the end would contain only the values for mu = 0.5. * Your loops may well be infinite (and in case are not doing what you want) because of the way you use mu and sig as loop control variables but also reset their values within the inner loop: > genr mu = mean(height) > genr sig = var(height) You need to use different names for these inner variables. * You don't actually _read_ mu or sig, as set by the loop control "for" expressions, anywhere inside the loop, so I'm left without much idea of what the loop is actually trying to do. Allin Cottrell
