* Nonlinear Regression for Mutual Fund Fees * * Keywords: * regression, nonlinear, exponential, r-squared, autocorrelation, dw, * durbin-watson, test, mutual, fund, advisory, fees * * Description: * We illustrate how to estimate a Nonlinear Exponential Model for Mutual * Fund Advisory Fees, calculate R-Squared for this model and conduct * Durbin-Watson Autocorrelation Test * * Author(s): * Skif Pankov * * Source: * Damodar N. Gujarati and Dawn C. Porter, Basic Econometrics - 5th Edition * McGraw-Hill International Edition, Chapter 14, Example 14.1 (page 531) * sample 1 12 * Reading the datafile and naming variables read (data_14.1.shd) fee ast * Initiating nonlinear regression procedure, stating that 1 equation with * 2 coefficients should be estimated and storing the estimated derivatives, * coefficients, predicted values and residuals nl 1 / ncoef = 2 zmatrix = z coef = beta predict = feehat resid = reds * Writing up an equation we would like to estimate - coefficients are named * A and B eq fee = A*exp(B*ast) * Stating the initial values of coefficients - these shall be used as the starting * points in the process of iterative estimation coef A 0.5 B -0.5 end * Generating R^2 gen1 su2 = sum(reds**2) gen1 sy = sum((fee-sum(fee)/\$N)**2) gen1 r2 = 1 - (su2/sy) print r2 * Generating a linear pseudomodel and computing the Durbin-Watson p-value matrix feebar = fee - feehat + z*beta ols feebar z / noconstant dwpvalue stop * Note: * standard errors of the estimates will differ from those in the * book because the iteration technique used by the authors and SHAZAM * are different, which also caused the difference in R^2 and Durbin-Watson * test statistic