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INTOP4014 Theory and Practice of Efficiency and Productivity

    • Number of credits
      5
    • Teaching semester
      2023 Spring, 2024 Spring
    • Language of instruction
      English
    • Campus
      Lillehammer
Course content

The topics covered are:

  • Cross-sectional stochastic frontier (SF) models
    • Estimating firm specific inefficiency, determinants of inefficiency, alternative SF models (mixture models/ZISF), estimation/inference of cross-sectional SF models in R
  • Panel data stochastic frontier (SF) models
    • History of panel data stochastic frontier models, first generation panel data models, second generation panel data models, the closed skew normal distribution, estimation/inference of panel data SF models in Stata
  • Semi/Nonparametric production frontiers
    • Nonparametric estimation of the determinants of inefficiency, estimation of non/semiparametric SF models in R
  • Modeling multiple outputs
    • The input/output distance function
  • Other issues/aspects
    • Endogeneity (endogeneity in the cross-sectional SF model, endogeneity in the panel data SF model)
    • Spatial SF models
  • Alternative uses of stochastic frontier analysis

Learning Outcome

Knowledge

Upon completion of the course, the candidate shall:

  • have advanced knowledge to characterize efficiency and productivity growth from a primal, dual and distance function perspective
  • have detailed knowledge about decomposing productivity growth that explicitly accounts for the presence of inefficiency
  • know how to define of variables of interest to be employed in analyses (goods and services; inputs, outputs, environmental, nonmarket goods/services)
  • have in-depth knowledge about the appropriate use of parametric and nonparametric approaches given the data and problem setting (understanding the advantages and disadvantages of both perspectives)
Skills

Upon completion of the course, the candidate shall be able to:

  • use these approaches to articulate the forces driving efficiency gains and productivity growth
  • apply these approaches for benchmarking, identifying best practice to plan for performance and enhancements/gains
General competence

Upon completion of the course, the candidate shall be able to:

  • understand sources of efficiency from the perspective of technical feasibility, allocating scarce resources among competing ends, and the firms scale of operations
  • complete research projects using input and output perspectives of technical and allocative efficiency
Teaching and working methods

The following teaching methods will be used:

  • Lectures
  • Problem solving sessions
  • Tutorial videos

The course consists of theory and method sessions in the morning followed by an afternoon lab session. The computer lab will include applications of the theory, computer analyses with actual data sets, and interpretations in practice. Applications to various economic examples will be considered such as agriculture, manufacturing, service industries, banking and finance, health, and electrical power generation/distribution.

Required coursework
  • Reading the course materials, attendance on at least 80% (4 days) of the courses lectured teaching, lab exercises. (The requirement for receiving 2 ECTS.)
  • Submission of a term paper after the course. This should be like a full scientific paper. Maximum 8000 words. (The requirement for receiving additional 3 ECTS, 5 ECTS in total.)
Form of assessment

Submission of a term paper after the course.

Reading list

Faculty
Inland School of Business and Social Sciences
Department
Department of Business Administration