1 / 8

Random Coefficients Regression

Random Coefficients Regression. RPD – Section 18.3. Basic Model. Simple Linear Regression where each of n experimental units is observed at t points in time (typically) . General Model ( Gumpertz and Pantula (1989)).

alka
Download Presentation

Random Coefficients Regression

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Random Coefficients Regression RPD – Section 18.3

  2. Basic Model • Simple Linear Regression where each of n experimental units is observed at t points in time (typically)

  3. General Model (Gumpertz and Pantula (1989)) • Possibly Multiple Linear Regression where each of n experimental units is observed at t points in time, based on regression with k parameters

  4. Estimating Individual/Population Regression Parameters

  5. Estimating Variance Parameters - I

  6. Estimating Variance Parameters - II

  7. Example – Annual Air Revenues for 10 Markets • Random Sample of n = 10 large air markets (City Pairs), each observed over 5 years • Y = ln(Average Fare * Average weekly Passengers) • X = Year (1996/7=0, 2000/1=4) – Note: All Cities have same levels of X (not necessary for the method)

  8. Air Revenue Data II

More Related