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Efficiency Measurement

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Stochastic Frontiers. 4 Production and Cost. 5 Heterogeneity. 6 Model Extensions. 7 Panel Data. 8 ... Modeling Consumer Decision Making and Discrete Choice Behavior – PowerPoint PPT presentation

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Title: Efficiency Measurement


1
Efficiency Measurement
  • William Greene
  • Stern School of Business
  • New York University

2
Lab Session 4
  • Panel Data

3
Group Size Variables for Unbalanced Panels
Farm Milk Cows FarmPrds
1 23.3 10.7 3
1 23.3 10.6 3
1 25 9.4 3
2 19.6 11 2
2 22.2 11 2
3 24.7 11 4
3 25.4 12 4
3 25.3 13.5 4
3 26.1 14.5 4
4 55.4 22 2
4 63.5 22 2
4
Creating a Group Size Variable
  • Requires an ID variable (such as FARM)
  • (1) Set the full sample exactly as desired
  • (2) SETPANEL Group the id variable
    Pds the name you want limdep
    to use for
    the periods variable
  • SETPANEL Group farm pds ti

5
Application to Spanish Dairy Farms
N 247 farms, T 6 years (1993-1998)
Input Units Mean Std. Dev. Minimum Maximum
Milk Milk production (liters) 131,108 92,539 14,110 727,281
Cows of milking cows 2.12 11.27 4.5 82.3
Labor man-equivalent units 1.67 0.55 1.0 4.0
Land Hectares of land devoted to pasture and crops. 12.99 6.17 2.0 45.1
Feed Total amount of feedstuffs fed to dairy cows (tons) 57,941 47,981 3,924.14 376,732
6
Exploring a Panel Data Set Dairy
REGRESS Lhs YIT RHS
COBBDGLS PANEL REGRESS
Lhs YIT RHS COBBDGLS
PANEL Het
Group
7
Initiating a Panel Data Model
8
Nonlinear Panel Data Models
MODEL NAME Lhs
RHS Panel
any other model parts ALL
PANEL DATA MODEL COMMANDS ARE THE SAME
9
Panel Data Frontier Model Commands
  • FRONTIER LHS COST
  • RHS
  • EFF
  • Panel
  • ... the rest of the model
  • any other options

10
Pitt and Lee Random Effects
  • FRONTIER LHS COST
  • RHS
  • EFF
  • Panel
  • any other options
  • This is the default panel model.

11
Pitt and Lee Model
12
Pitt and Lee Random Effects with
Heteroscedasticity and Time Invariant
Inefficiency
  • FRONTIER LHS COST
  • RHS
  • EFF
  • Panel
  • HET HFU
  • HFV

13
Pitt and Lee Random Effectswith
Heteroscedasticity and Truncation Time Invariant
Inefficiency
  • FRONTIER LHS COST
  • RHS
  • EFF
  • Panel
  • HET HFU
  • HFV
  • MODEL T RH2
    One,

14
Pitt and Lee Random Effectswith
HeteroscedasticityTime Invariant Inefficiency
  • FRONTIER LHS COST
  • RHS
  • EFF
  • Panel
  • HET HFU
  • HFV

15
Schmidt and Sickles Fixed Effects
  • REGRESS LHS RHS
  • PANEL
  • PAR FIXED
  • CREATE AI ALPHAFE ( id )
  • CALC MAXAI Max(AI)
  • CREATE UI MAXAI AI
  • (Use Minimum and AI MINAI for cost)

16
True Random EffectsTime Varying Inefficiency
  • FRONTIER LHS COST RHS
  • FRONTIER LHS COST RHS
  • Panel Halton (a good idea)
    PTS number for the
    simulations
  • RPM FCN ONE (n)
  • EFF
  • Note, first and second FRONTIER commands are
    identical. This sets up the starting values.

17
True Fixed EffectsTime Varying Inefficiency
  • FRONTIER LHS COST RHS
  • FRONTIER LHS COST RHS
  • Panel
  • FEM
  • EFF
  • Note, first and second FRONTIER commands are
    identical. This sets up the starting values.

18
Battese and CoelliTime Varying Inefficiency
  • FRONTIER LHS COST RHS
  • Panel
  • MODEL BC
  • EFF
  • This is the default specification,
    u(i,t) exph(t-T) U(i)
  • To use the extended specification,
    u(i,t)expdz(i) U(i)
  • Het
  • HFU variables

19
Other Models
  • There are many other panel models with time
    varying and time invariant inefficiency,
    heteroscedasticity, heterogeneity, etc.
  • Latent class,
  • Random parameters
  • Sample selection,
  • And so on.

20
(No Transcript)
21
Lab Session 4
  • Model Building

22
Modeling Assignment
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