From Colin Cameron

http://cameron.econ.ucdavis.edu/stata/stata.html
* This program does


*   (1) Poisson regression using Stata MATA matrix commands

*   (2) Poisson regression using Stata command poisson as check

* using number of bids data
* Invoke MATA

mata

// Create y vector as well as X matrix from Stat data set using st_view command

st_view(y=., ., “numbids”)

st_view(X=., ., (”leglrest”, “whtknght”, “bidprem”, “cons”))

Xnames = (”leglrest”, “whtknght”, “bidprem”, “cons”)   // used to label output

// Obtain starting values from ols regression of lny on x

b = invsym(X’X)*X’(ln(y+(y:==0)*0.1))

n = rows(X)

// Newton-Raphson iterations to computer Poisson MLE

// Loop until parameter modification less than 10^-16

cha = 1

iter = 1

do {

mu = exp(X*b)

sco = (X’(y-mu))/n

hes = -(X’(X:*mu))/n

bold = b

b = bold + invsym(-hes)*sco

cha = (bold-b)’(bold-b)/(b’b)

iter = iter + 1

} while (cha > 1e-16)

iter

bmle = b

// Compute standard errors using A^-1 * B * A^-1

k = cols(X)

gradmatrix = X:*(y-mu)

Vmle = invsym(-n*hes)*(gradmatrix’gradmatrix)*invsym(-n*hes)*(n/(n-k))

semle = sqrt(diagonal(Vmle))

tmle = bmle:/semle

pmle = 2*ttail(n-k, abs(tmle))

// Print results

(bmle, semle, tmle, pmle)

// Easier to read output includes regressor names

(Xnames’, strofreal(bmle), strofreal(semle), strofreal(tmle), strofreal(pmle))

end