Count Data Models Example

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Poisson Model, Negative Binomial Model, Hurdle Models, Zero-Inflated Models Example
  1. econometricsacademy
  2. Count data models
  3. Zero-inflated models
  4. Truncated models
  5. Hurdle models
  6. Poisson regression
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Clarification: the Poisson coefficient beta is the difference between the log expected counts beta=log(mu_(x+1))-log(mu_x). Reworking this expression the percent change in counts equals That's why at 2:38 and 5:44 in the video, I interpreted the coefficient approximately as a percent change in counts.

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