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RIF: st: mfx with xtlogit


From   "Mussida Chiara" <[email protected]>
To   <[email protected]>
Subject   RIF: st: mfx with xtlogit
Date   Tue, 26 Feb 2008 12:05:59 +0100

the mfx default does not correspond to the median of the dependent variable evaluated at sample means of independent variables? to evaluate at the mean I guess it is necessary to predict the mean of the dependent variable before mfx
 
chiara

	-----Messaggio originale----- 
	Da: [email protected] per conto di Johannes Geyer 
	Inviato: mar 26/02/2008 11.44 
	A: [email protected] 
	Cc: 
	Oggetto: Re: st: mfx with xtlogit
	
	

	Dear Alejandro,
	
	it happens that coefficients are significant and marginal effects not.
	They simply depend on all other coefficients which makes it hard to
	predict their significance - e.g. it might be important to decide whether
	to include insignificant coefficients of other variables in your
	calculation.
	You have to decide over which marginal effect to calculate - did you try
	-margeff- by Tamas Bartus? In my view it is more flexible than mfx. You
	can e.g. calculate average marginal effects, i.e. calculate the mean
	effect in your sample (margeff can do this) or simply evaluate your
	function at sample means (mfx default). If your sample is small you could
	also think of bootstrapping standard errors of marginal effects.
	
	Hope that helps,
	
	Johannes
	
	----------------------
	Johannes Geyer
	Deutsches Institut für Wirtschaftsforschung (DIW Berlin)
	German Institute for Economic Research
	Department of Public Economics
	DIW Berlin
	Mohrenstraße 58
	10117 Berlin
	Tel: +49-30-89789-258
	
	
	
	Alejandro Delafuente <[email protected]>
	Gesendet von: [email protected]
	26/02/2008 11:20
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	Thema
	st: mfx with xtlogit
	
	
	
	
	
	
	Dear statalisters,
	
	I estimated marginal effects after running xtlogit with fixed effects as
	follows:
	
	xtlogit depvar independentvars, i(folio) fe
	mfx, predict(pu0)
	
	Where depvar indicates reception of transfers. All the marginal effects of
	
	interest are insignificant (most of which are dummy variables), except for
	one
	variable which has few observations across my 3-round panel. This came as
	a
	surprise for two reasons:
	1) the xtlogit coefficients for some of those same
	variables were significant;
	2) I had run probit over the pooled sample (ie: dprobit depvar
	indepvars)and
	xtprobit (ie: xtprobit depvar indepvars, re) BEFORE xtlogit  and some of
	those
	same coefficients were highly significant as well.
	
	My understanding is that there isn't one single way for capturing marginal
	
	effects after xtlogit, but am a bit puzzled with what I've found thus far
	and
	wonder whether other commands for estimating mfx after xtlogit exist? Or
	any
	advice as to why this insignificancy might be taking place?
	
	Thanks,
	
	Alejandro
	--
	Alejandro de la Fuente
	Department of International Development/QEH
	University of Oxford, Mansfield Road, Oxford OX1 3TB
	Tel: 01865 281836
	
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