Parametric decomposition of the input-oriented Malmquist productivity index: with an application to Greek aquaculture

Abstract

Malmquist productivity index, Stochastic input distance function, Greek aquaculture farms, C23, D24, Q22,

Parametric Decomposition of the Malmquist Index in Output-Oriented Distance Function: Productivity in Chinese Agriculture

“…In addition, this paper differs from other studies by expressing results in a discrete changes format, instead of derivatives. This is very useful in empirical studies because most economic variables are not presented as continuous, and the estimated productivity growth index using first order derivative can lead to incorrect results ( [9,20]). …”

“…According to [11] this specification fulfills a set of desirable characteristics: flexible, easy to derive and allowing the imposition of homogeneity. The flexible form of translog has been widely used to estimate distance functions as it meets all the required characteristics ( [4,6,9,10,12]). This paper will also adopt translog functional form.…”

“…The parametric approach provides a solution to address the shortcomings of nonparametric techniques and has been adopted by some recent studies in the estimation of the Malmquist index ( [4,8,9]). In the parametric approach, the Malmquist index is not directly obtained through the estimation of distance functions under differrent returns to scale technologies.…”

“…In the parametric approach, the Malmquist index is not directly obtained through the estimation of distance functions under differrent returns to scale technologies. Instead the Malmquist index and its components are calculated based on the fitted distance function with globally variable returns to scale, evaluated at adjacent time periods' input and output quantity, as implemented by [4,[8][9][10]. In addition to statistical testing, the parametric approach has the advantages of accommodating random errors and enabling different interactions between outputs and inputs if a flexible functional form is chosen to closely approximate the underlying production technology.…”

“…First, it decomposes the Malmquist productivity index into different components using an output distance function. Unlike [9] the decomposition of this paper is based on the geometric mean of two adjacent Malmquist index, filling a gap in the existing literature of productivity analysis. Second, it demonstrates the advantages of the parametric output distance function approach to characterizing the agricultural technology and productivity decomposition.…”