prdk_day3a

# prdk_day3a - A d v a n c e d P r o g r a m m i n g i n Q u...

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Unformatted text preview: A d v a n c e d P r o g r a m m i n g i n Q u a n t i t a t i v e E c o n o m i c s Introduction, structure, and advanced programming techniques 17 – 21 August 2009, Aarhus, Denmark Charles Bos [email protected] VU University Amsterdam Tinbergen Institute Advanced Programming in Quantitative Economics – p. 1 Tutorial Day 3 - Morning 10.30P Tutorial ◦ Loglikelihood duration model ◦ Standard deviations ◦ Analytical score 12.00 Lunch Advanced Programming in Quantitative Economics – p. 2 Duration: The (simplified) model As a reminder: Durations y i are assumed to be distributed according to y ∼ Weib ( α,λ ) f ( y ; α,λ ) = αλ α y α − 1 exp( − λ α y α ) Dependence on personal characteristics can be introduced by taking λ i ≡ exp( X i β ) y i ∼ Weib ( α,λ i ) Make sure you have data available, e.g. in data/genrdur.fmt , or download a file from the web. Advanced Programming in Quantitative Economics – p. 3 Duration: Optimisation Central to optimisation is the log likelihood function. In this case, itCentral to optimisation is the log likelihood function....
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prdk_day3a - A d v a n c e d P r o g r a m m i n g i n Q u...

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