We define a combined DEA score to evaluate efficiency in agricultural research. The production model we propose considers efficiency measurements under variable returns to scale for each year in the period 2012–2017. We postulate a first-order autoregressive process in the presence of covariates, to explain efficiency. Powers of the autocorrelation coefficient estimated assuming a dynamic panel...

This paper shows how one can infer the nature of local returns to scale at the inputor output-oriented efficient projection of a technically inefficient inputoutput bundle, when the inputand output-oriented measures of efficiency differ. Journal of Economic Literature Classification: D2, C6

Data envelopment analysis (DEA) is a technique used to evaluate the relative efficiency of comparable decision making units (DMUs) with multiple input-output. It computes a scalar measure of efficiency and discriminates between efficient and inefficient DMUs. It can also provide reference units for inefficient DMUs without consideration of the decision makers’ (DMs) preferences. In this paper, ...

Malmquist Productivity Index (MPI) is a numeric index that is of great importance in measuring productivity and its changes. In recent years, tools like DEA have been utilized for determining MPI. In the present paper, some models are recommended for calculating MPI when there are just ratio data available. Then, using DEA and DEA-R, some models are proposed under the constant returns to scale ...

Abstract Conventional models of data envelopment analysis (DEA) are based on the constant and variable returns-to-scale production technologies. Any optimal input output weights multiplier DEA these technologies interpreted as being most favorable for decision making unit (DMU) under assessment when latter is benchmarked against set all observed DMUs. In this paper we consider a very large clas...

The data envelopment analysis (DEA) model is extensively used to estimate efficiency, but no study has determined the DEA that delivers most precise estimates. To address this issue, we advance Monte Carlo simulation-based generation process proposed by Kohl and Brunner (2020). developed generates an artificial dataset using Translog production function (instead of commonly Cobb Douglas) constr...

A new approach or model to the dynamic DEA, referred to as the adjusted dynamic DEA, is proposed in this study. Adjusted dynamic DEA optimizes the production activity of DMUs by introducing adjustment variables to modify the interconnecting activities between consecutive terms, solving conflicts that arise between terms and between management and shareholders. The non-oriented SBM model is used...