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From |
<Jean-Francois.Bertrand@fin.gc.ca> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: Hessian trigger "too many literals" error with "ml model" |

Date |
Wed, 29 Feb 2012 15:33:10 -0500 |

Hello all, I work with STATA 11, 64 bit. I am estimating a discrete labour supply model for single individuals. My model is similar to what is done in many economic paper on this topic. When I use a quadratic utility function including fixed cost for working such that: U = beta_y * income + beta_h * hours + alpha_ysq * income square + alpha_hsq * hours square + alpha_yh * (hours times income) y = Y - gamma_fcw * dummy_if_working - gamma_fcwft * dummy_if_working_40_hours_per_week Where y = income, h = hours, ysq = income square, hsq = hours square and yh = interaction between hours and income and where Y represent income net of taxes. Ml model works perfectly with d0, d1 and d2 approach (d2 being much faster and stable). When I relax the independence of irrelevant alternative of my extreme value distribution by using simulated maximum likelihood approach to include a random term with income for example (I am using Halton generated numbers), d2 stop working as I get a "too many literals" with my Hessian, but d0 and d1 provides me with similar results. If I omit fixed cost of working variables, d2 works. Is there a way to increase the number of "literals" as d2 is much faster? Cheers, Jean-François * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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