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Frontier Models and Efficiency Measurement Lab Session 4: Panel Data

William Greene Stern School of Business New York University. Frontier Models and Efficiency Measurement Lab Session 4: Panel Data. 0 Introduction 1 Efficiency Measurement 2 Frontier Functions 3 Stochastic Frontiers 4 Production and Cost 5 Heterogeneity 6 Model Extensions

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Frontier Models and Efficiency Measurement Lab Session 4: Panel Data

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  1. William Greene Stern School of Business New York University Frontier Models and Efficiency MeasurementLab Session 4: Panel Data 0 Introduction 1 Efficiency Measurement 2 Frontier Functions 3 Stochastic Frontiers 4 Production and Cost 5 Heterogeneity 6 Model Extensions 7 Panel Data 8 Applications

  2. Group Size Variables for Unbalanced Panels

  3. 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 $

  4. Application to Spanish Dairy Farms N = 247 farms, T = 6 years (1993-1998)

  5. Exploring a Panel Data Set: Dairy REGRESS ; Lhs = YIT ; RHS = COBBDGLS ; PANEL $ REGRESS ; Lhs = YIT ; RHS = COBBDGLS ; PANEL ; Het = Group $

  6. Initiating a Panel Data Model

  7. Nonlinear Panel Data Models MODEL NAME ; Lhs = … ; RHS = … ; Panel ; … any other model parts … $ ALL PANEL DATA MODEL COMMANDS ARE THE SAME

  8. Panel Data Frontier Model Commands FRONTIER ; LHS = … [ ; COST ] ; RHS = … [; TECHEFF = …] ; Panel ; ... the rest of the model ; any other options $

  9. Pitt and Lee Random Effects FRONTIER ; LHS = … [ ; COST ] ; RHS = … [; EFF = …] ; Panel ; any other options $ This is the default panel model.

  10. Pitt and Lee Model

  11. Pitt and Lee Random Effects with Heteroscedasticity and Time Invariant Inefficiency FRONTIER ; LHS = … [ ; COST ] ; RHS = … [; EFF = …] ; Panel ; HET ; HFU = … ; HFV = … $

  12. Pitt and Lee Random Effectswith Heteroscedasticity and Truncation Time Invariant Inefficiency FRONTIER ; LHS = … [ ; COST ] ; RHS = … [; EFF = …] ; Panel ; HET ; HFU = … ; HFV = … ; MODEL = T ; RH2 = One,… $

  13. Pitt and Lee Random Effectswith HeteroscedasticityTime Invariant Inefficiency FRONTIER ; LHS = … [ ; COST ] ; RHS = … [; EFF = …] ; Panel ; HET ; HFU = … ; HFV = … $

  14. 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)

  15. 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.

  16. 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.

  17. 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

  18. 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….

  19. William Greene Stern School of Business New York University Frontier Models and Efficiency MeasurementLab Session 4: Model Building 0 Introduction 1 Efficiency Measurement 2 Frontier Functions 3 Stochastic Frontiers 4 Production and Cost 5 Heterogeneity 6 Model Extensions 7 Panel Data 8 Applications

  20. Modeling Assignment

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