Proxy variable estimation of productivity and efficiency.

We model productivity and inefficiency jointly, instead of modeling and estimating either only productivity or only inefficiency with many variable and quasi‐fixed inputs. In the first model, we use a multi‐step procedure. We use the proxy variable method based on the first‐order condition (FOC) of...

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Publicado en:Southern Economic Journal Vol. 89; no. 3; pp. 885 - 924
Autores principales: Tsionas, Mike G., Kumbhakar, Subal C.
Formato: Artículo
Publicado: Wiley-Blackwell Jan2023
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jan2023
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        atl: Proxy variable estimation of productivity and efficiency.
      aug:
        au:
          Tsionas, Mike G.
          Kumbhakar, Subal C.
        affil:
          Department of Economics, Montpellier Business School, Montpellier, France & Lancaster University Management School, Lancaster, UK
          Department of Economics, State University of New York, Binghamton & Inland Norway University of Applied Sciences, Lillehammer, Norway
      su:
        Food industry
        Profit maximization
        Set functions
        Endogeneity (Econometrics)
      sug:
        subj:
          Food industry
          Perishable Prepared Food Manufacturing
          All Other Miscellaneous Food Manufacturing
          Profit maximization
          Set functions
          Endogeneity (Econometrics)
      keyword:
        endogeneity
        inefficiency
        productivity
        stochastic frontiers
        variable inputs
        endogeneity
        inefficiency
        productivity
        stochastic frontiers
        variable inputs
      ab: We model productivity and inefficiency jointly, instead of modeling and estimating either only productivity or only inefficiency with many variable and quasi‐fixed inputs. In the first model, we use a multi‐step procedure. We use the proxy variable method based on the first‐order condition (FOC) of expected profit maximization with respect to the single variable input to take care of the endogeneity problem arising from both productivity and inefficiency. To separate mean inefficiency from mean productivity we assume them nonparametric functions of different sets of exogenous variables. In the second model, we consider a novel system consisting of the production function and the FOCs of expected profit maximization for the multiple variable inputs. Distributional assumptions are made on all the random errors associated with the production function, the FOCs, productivity, and inefficiency functions in the second model. We use the Colombian food manufacturing data as an application of our model.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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