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RE: st: Modelling extremely rare events (binary)


From   DE SOUZA Eric <eric.de_souza@coleurope.eu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Modelling extremely rare events (binary)
Date   Tue, 14 Jun 2011 11:47:43 +0200

If I'm not mistaken, Gary King is a Bayesian, which explains the title.
Best wishes,
Eric

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Markus Eberhardt
Sent: 14 June 2011 11:43
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Modelling extremely rare events (binary)

Eric, I am 'harvesting' the site as we speak. I like the title of one of his papers, "Estimating the Probability of Events that Have Never Occurred".
Best wishes
m

Markus Eberhardt
ESRC Post-doctoral Research Fellow, Centre for the Study of African Economies, Department of Economics, University of Oxford Stipendiary Lecturer, St Catherine's College, Oxford

web: http://sites.google.com/site/medevecon/home
email: markus.eberhardt@economics.ox.ac.uk
twitter: http://twitter.com/sjoh2052
mail: Centre for the Study of African Economies, Department of Economics, Manor Rd, Oxford OX1 3UQ, England




On 14 June 2011 10:37, DE SOUZA Eric <eric.de_souza@coleurope.eu> wrote:
> He has a whole page devoted to it:
> http://gking.harvard.edu/category/research-interests/methods/rare-even
> ts
>
>
> Eric de Souza
> College of Europe
> Brugge (Bruges), Belgium
> http://www.coleurope.eu
>
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Abhimanyu 
> Arora
> Sent: 14 June 2011 11:29
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: Modelling extremely rare events (binary)
>
> Hi
> Perhaps you could have a look at Gary Kings's -relogit-?
> Best
> Abhimanyu
>
> On Tue, Jun 14, 2011 at 10:05 AM, Markus Eberhardt <markus.eberhardt@economics.ox.ac.uk> wrote:
>> Hello everybody
>>
>> I have an empirical problem where for a very large dataset (panel, 
>> around 20,000 panel members with over 60,000 observations) I have two 
>> binary outcome variables A and B. The occurrence of either is 
>> extremely rare: only about 1.5% and 0.1% of observations for A and B 
>> respectively. I am for the time being treating this as a pooled 
>> panel, so not accounting for any fixed effects at the panel member 
>> level. My empirical model is made up of continuous and binary 
>> variables. In the logit and probit I am estimating A and B 
>> separately, for biprobit jointly, for mlogit I have four categories 
>> (0, A occurrs, B occurrs, both occurr). Ideally the analysis does 
>> account for the jointess of the decision as in the biprobit and mlogit approaches.
>>
>> Here are my questions:
>> (1) DOES THIS AT ALL MAKE SENSE? Having estimated logit, probit, 
>> bivariate probit and multinomial logit I am concerned about the 
>> viability of what I am doing to this data: given the minute share of 
>> actual events occurring (1s, rather than 0s) is it at all possible 
>> that a logit-type model could tell me anything meaningful? So far I 
>> am getting interpretable empirical results, but it was put to me that 
>> these were entirely unreliable (or even spurious) given the extreme 
>> rarety of the event. Note that there are strong priors (from the 
>> descriptive analysis) that a certain characteristic (binary) drives 
>> the outcomes, so I imagine that a fixed effect and/or an interaction 
>> of this binary characteristic with other (continuous) RHS variables 
>> may provide an intuitive 'fit', but I am unsure whether this is 
>> empirically satisfied.
>> (2) USEFUL DIAGNOSTICS? My diagnostics for the model(s) are hampered 
>> by the fact that it's difficult to get a handle on what constitutes a 
>> substantial deviation for the predicted from the observed outcomes.
>> Apart from -fitstat- type diagnostics, are there any other things I 
>> could do to chose between rival models and/or to convince myself that 
>> what I'm doing is at all meaningful in this challenging empirical 
>> case?
>> (3) ALTERNATIVE EMPIRICAL MODELS? Are there any other empirical 
>> specifications that are better suited to fit this data? I tried to 
>> search for extremely rare events such as earthquakes, but couldn't 
>> get much out of it.
>> (4) PANEL ELEMENT? Possibly a bridge too far, but would there be any 
>> option to get the panel element of the data to have a bearing on the 
>> empirics.
>>
>> Thanks a lot in advance.
>> markus
>>
>> Markus Eberhardt
>> ESRC Post-doctoral Research Fellow, Centre for the Study of African 
>> Economies, Department of Economics, University of Oxford Stipendiary 
>> Lecturer, St Catherine's College, Oxford
>>
>> web: http://sites.google.com/site/medevecon/home
>> email: markus.eberhardt@economics.ox.ac.uk
>> twitter: http://twitter.com/sjoh2052
>> mail: Centre for the Study of African Economies, Department of 
>> Economics, Manor Rd, Oxford OX1 3UQ, England
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