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85 lines
2.8 KiB
Plaintext
85 lines
2.8 KiB
Plaintext
9 months ago
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help for {hi:espoisson} {right:(SJ4-1: st0057)}
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{hline}
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{title:FIML endogenous switching Poisson model}
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{p 8 13 2}{cmd:espoisson}{space 2}{it:depvar} [{it:varlist}]
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[{cmd:if} {it:exp}] [{cmd:in} {it:range}] {cmd:,}
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{cmdab:ed:ummy(}{it:varname}{cmd:)} [ {cmdab:s:witch(}{it:varlist}{cmd:)}
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{cmdab:q:uadrature(}{it:#}{cmd:)} {cmd:rho0(}{it:#}{cmd:)}
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{cmd:sigma0(}{it:#}{cmd:)} {cmd:exs} {it:maximize_options}]
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{p 8 8 2}Note: the vector {it:varlist} should include the switch variable
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(endogenous dummy) as one of its elements.{p_end}
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{p 4 4 2} The syntax of {help predict} after {cmd:espoisson} is
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{p 8 16 2}{cmd:predict} {it:newvar} [{cmd:if} {it:exp}]
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[{cmd:in} {it:range}] [{cmd:,} n ]
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{p 4 4 2}where,
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{p 8 21 2}{cmd:n}{space 9}predicted number of events (default){p_end}
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{title:Description}
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{p 4 4 2}{cmd:espoisson} fits a FIML endogenous switching Poisson model.
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An endogenous dummy variable is present in the vector of explanatory
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variables, and there is unobserved individual heterogeneity. The endogenous
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dummy variable indicates the realization of two different regimes. The
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endogenous switching model corrects for the simultaneous equation bias that
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the presence of the endogenous dummy may induce in a standard exogenous-switch
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count model.
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{p 4 4 2}This program uses {cmd:ml d0} method.
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{title:Options}
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{p 4 8 2}{cmd:edummy(}{it:varname}{cmd:)} (required) specifies the endogenous
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dummy variable.
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{p 4 8 2} {cmd:switch(}{it:varlist}{cmd:)} specifies explanatory variables for
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the index function governing the endogenous dummy. If {cmd:switch()} is
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unspecified then a constant-only model is fitted.
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{p 4 8 2}{cmd:quadrature(}{it:#}{cmd:)} specifies the number of quadrature
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points for the Gauss-Hermite integral. Six points are used by default.
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{p 4 8 2}{cmd:rho0(}{it:#}{cmd:)} specifies initial value for rho. If
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unspecified, {cmd:rho0()}=0.01.
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{p 4 8 2}{cmdab:sigma0(}{it:#}{cmdab:)} specifies initial value for sigma. If
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unspecified, {cmd:sigma0()}=1.0.
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{p 4 8 2}{cmdab:exs} causes the program to fit an exogenous switching
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model.
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{title:Examples}
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{p 8 12 2}{cmd:. espoisson y x1 x2, ed(x2) s(x1) q(16)}{p_end}
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{p 8 12 2}{cmd:. predict yhat, n}{p_end}
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{p 8 12 2}{cmd:. espoisson y x1 x2, ed(x2) s(x1) q(16) exs}{p_end}
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{p 8 12 2}{cmd:. predict yhat, n}{p_end}
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{title:Author}
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{p 4 8 2}{bf: Alfonso Miranda}{p_end}
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{p 4 8 2} Economics Department, Warwick University, CV4 7AL, UK.{p_end}
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{p 4 8 2}E-mail: Alfonso.Miranda-Caso-Luengo@warwick.ac.uk{p_end}
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{title:Also see}
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{p 4 14 2}Manual: {hi:[U] 23 Estimation and post-estimation commands},{p_end}
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{p 13 13 2}{hi:[U] 29 Overview of model estimation in Stata},{p_end}
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{p 13 13 2}{hi:[R] poisson}
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{p 4 13 2}Online: help for {help ml}, {help glm}, {help nbreg}, {help svypois},
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{help xtpois}, {help zip}
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