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William Greene Stern School of Business New York University. Efficiency Measurement. Lab Session 4. 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 4

Lab Session 4

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….

lab session 41

Lab Session 4

Model Building

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