Random coefficients regression
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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)).

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Random Coefficients Regression

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Random coefficients regression

Random Coefficients Regression

RPD – Section 18.3


Basic model

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

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


Estimating individual population regression parameters

Estimating Individual/Population Regression Parameters


Estimating variance parameters i

Estimating Variance Parameters - I


Estimating variance parameters ii

Estimating Variance Parameters - II


Example annual air revenues for 10 markets

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)


Air revenue data ii

Air Revenue Data II


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