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William Greene Stern School of Business New York University. Efficiency Measurement. Lab Session 5. Panel Data. Group Size Variables for Unbalanced Panels. Creating a Group Size Variable. Requires an ID variable (such as FARM) (1) Set the full sample exactly as desired

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William greene stern school of business new york university

William Greene

Stern School of Business

New York University

Efficiency Measurement


Lab session 5

Lab Session 5

Panel Data



Creating a group size variable
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 $


Application to spanish dairy farms
Application to Spanish Dairy Farms

N = 247 farms, T = 6 years (1993-1998)


Exploring a panel data set dairy
Exploring a Panel Data Set: Dairy

REGRESS ; Lhs = YIT

; RHS = COBBDGLS

; PANEL $

REGRESS ; Lhs = YIT

; RHS = COBBDGLS

; PANEL ; Het = Group $



Nonlinear panel data models
Nonlinear Panel Data Models

MODEL NAME ; Lhs = …

; RHS = …

; Panel

; … any other model parts … $

ALL PANEL DATA MODEL COMMANDS ARE THE SAME


Panel data frontier model commands
Panel Data Frontier Model Commands

FRONTIER ; LHS = … [ ; COST ]

; RHS = …

[; EFF = …]

; Panel

; ... the rest of the model

; any other options $


Pitt and lee random effects
Pitt and Lee Random Effects

FRONTIER ; LHS = … [ ; COST ]

; RHS = …

[; EFF = …]

; Panel

; any other options $

This is the default panel model.



Pitt and lee random effects with heteroscedasticity and time invariant inefficiency
Pitt and Lee Random Effects with Heteroscedasticity and Time Invariant Inefficiency

FRONTIER ; LHS = … [ ; COST ]

; RHS = …

[; EFF = …]

; Panel

; HET ; HFU = …

; HFV = … $


Pitt and lee random effects with heteroscedasticity and truncation time invariant inefficiency
Pitt and Lee Random Effectswith Heteroscedasticity and Truncation Time Invariant Inefficiency

FRONTIER ; LHS = … [ ; COST ]

; RHS = …

[; EFF = …]

; Panel

; HET ; HFU = …

; HFV = …

; MODEL = T ; RH2 = One,… $


Pitt and lee random effects with heteroscedasticity time invariant inefficiency
Pitt and Lee Random Effectswith HeteroscedasticityTime Invariant Inefficiency

FRONTIER ; LHS = … [ ; COST ]

; RHS = …

[; EFF = …]

; Panel

; HET ; HFU = …

; HFV = … $


Schmidt and sickles fixed effects
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)


True random effects time varying inefficiency
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.


True fixed effects time varying inefficiency
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.


Battese and coelli time varying inefficiency
Battese and CoelliTime Varying Inefficiency

FRONTIER ; LHS = … [ ; COST ] ; RHS = …

; Panel

; MODEL = BC

; EFF = … $

This is the default specification, u(i,t) = exp[h(t-T)] |U(i)|

To use the extended specification, u(i,t)=exp[d’z(i)] |U(i)|

; Het

; HFU = variables


Other models
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….