Exact nonradial input, output, and productivity measurement

Chambers, Robert G.

doi:10.1007/s001990100231

Cited by 178 publications

(133 citation statements)

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“…Similarly, in the volume indicator, the simple average of the input prices serves as the weight for the change in input quantities. For these indicators to make sense, the prices must be 'deflated' by some general measure (see Balk, 2008Balk, , 2010Chambers, 2001Chambers, , 2002Chambers and Färe, 1998). In our case, all prices are deflated in each period by the total value of the input bundle.…”

Section: Indicatorsmentioning

confidence: 99%

“…Also note that ) 1 8 Chambers (2002;p. 757) shows that if the firm minimizes cost, and the directional input distance function is quadratic and satisfies the translation property, the Bennet cost measure is "a superlative input indicator in the sense that it is an exact measure for a second order flexible representation of the technology."…”

Section: Indicatorsmentioning

confidence: 99%

“…12 were used to construct estimates of the levels as well as growth rates of the output and input aggregates. 13 …”

Section: The Datamentioning

confidence: 99%

“…3 This indicator requires data on both prices and quantities of outputs and inputs, much like the Fisher and Törnqvist indexes. And, like the Fisher and Törnqvist indexes, it can be derived based on a test approach (see Diewert, 2005) or through its dual, the Luenberger productivity indicator (see Chambers et al, 1996, Chambers, 2002. The Bennet (1920) indicator satisfies many desirable properties.…”

Section: Introductionmentioning

confidence: 99%

“…The second objective is to study the contribution of energy to productivity growth in Diewert, 2005) or through its dual, the Luenberger productivity indicator (see Chambers et al, 1996, Chambers, 2002. The Bennet (1920) indicator satisfies many desirable properties.…”

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confidence: 99%

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The role of energy productivity in U.S. agriculture

et al. 2015

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This paper investigates the role of energy on U.S. agricultural productivity using panel data at the state level for the period 1960-2004. We first provide a historical account of energy use in U.S. agriculture. To do this we rely on the Bennet cost indicator to study how the price and volume components of energy costs have developed over time. We then proceed to analyze the contribution of energy to productivity in U.S. agriculture employing the IntroductionThe purpose of this study is to investigate the role that energy plays in the U.S.agricultural sector, both in terms of its role as a factor of production and its role as a contributor to productivity growth. Our analysis employs a unique data series compiled by the U.S. Department of Agriculture's Economic Research Service (ERS).The data consist of a state-by-year panel, which will allow us to assess the impact of technological advances over the study period as well as the effect of volatile energy prices. Of particular interest are the effects of major energy market shocks (e.g. the oil price shocks of the 1970s) on energy productivity and the profitability of the U.S.agriculture. The data set includes three outputs and six inputs; the latter include direct energy use in agriculture as well as indirect energy use as, for example, consumption of agricultural chemicals. 1 Both price and quantity data are available. A more detailed description of the data set is given in Section 3 below.Our first objective is to give an historical accounting of energy consumption in U.S.agriculture. While direct energy consumption in the agricultural sector represents only a very small fraction of the total U.S. energy use, changes in the energy market can have a large impact on costs and, therefore, on profitability of the sector as well as on food prices. 2 The effects of energy costs on profitability may also be greatly exacerbated by changes in fertilizer and pesticide costs, both of which are significant energy users. Here we rely on a Bennet (1920) indicator decomposition of profit into price and volume indicators, which can also be decomposed into changes over time and space. This decomposition is possible due to the additive structure of the Bennet indicator. This is not possible with the more familiar Fisher and Törnqvist indexes.Thus our work will provide an additional tool for the analysis of the role of energy in agriculture.1 Energy inputs feature in every stage of agricultural production, from making and applying chemicals to fueling farm machinery used in tillage and harvesting of crops, and to electricity for livestock housing facilities. Such reliance on energy consumption has left farmers vulnerable to high energy costs and volatile energy market fluctuations, thereby highlighting the importance of efficient use of energy for farm profitability and for more sustainable agricultural practices (see Levine, 2012). 2 For example, Wang and McPhail (2012) report that in addition to global food demand, energy shocks also play an important role in explaini...

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Section: Indicatorsmentioning

confidence: 99%

Section: Indicatorsmentioning

confidence: 99%

“…12 were used to construct estimates of the levels as well as growth rates of the output and input aggregates. 13 …”

Section: The Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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The role of energy productivity in U.S. agriculture

et al. 2015

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Analysing determinate components of an approximated Luenberger–Hicks–Moorsteen productivity indicator: An application to German dairy‐processing firms

Ang,

Ramsden

2024

Agribusiness

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The Luenberger–Hicks–Moorsteen (LHM) total factor productivity (TFP) indicator has sound theoretical properties, but its decomposition yields indeterminate components of technical change and scale efficiency change that can become infeasible. The current paper decomposes the approximating Bennet indicator, which results in determinate components of technical change, technical efficiency change, scale efficiency change and mix efficiency change that are always feasible. The application focuses on the German dairy‐processing sector, an important postfarm supply chain actor. We compute 558 growth rates for the period 2011–2020. The results show that the LHM‐approximating Bennet indicator decreases by on average 1.14% p.a., with substantial annual fluctuations. The underlying components of output‐ and input‐oriented technical change also fluctuate substantially, and often conflict. Moreover, output‐ and input‐oriented TFP efficiency change fluctuate moderately on average, which is mainly driven by scale efficiency change and mix efficiency change. The components of technical efficiency change remain relatively stable on average. Indeterminateness is a relevant problem when decomposing the original LHM indicator for the current sample: depending on the specification, the proportion of infeasibilities when decomposing the original LHM indicator ranges between 6.09% and 15.95%. Our proposed determinate decomposition is thus a valuable complement. [EconLit Citations: D24, D25, Q13].

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Indicators and indexes of directional output loss and input allocative inefficiency

Fukuyama

Weber

2008

Manage Decis Econ

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We extend Grosskopf et al.'s method and create an output loss indicator using directional output distance functions that allows non-radial efficiency gains in output. We compare our new output loss indicator with an indicator of input allocative inefficiency and derive the necessary and sufficient condition for equivalence between the two indicators. We also present an output loss index and corresponding input allocative inefficiency index and consider how indexes are related. Then we extend our analysis to productivity change and derive the necessary and sufficient condition for an output loss change indicator to be equivalent to an indicator of input allocative inefficiency change. Copyright © 2008 John Wiley & Sons, Ltd.

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Exact nonradial input, output, and productivity measurement

Cited by 178 publications

References 14 publications

The role of energy productivity in U.S. agriculture

The role of energy productivity in U.S. agriculture

Analysing determinate components of an approximated Luenberger–Hicks–Moorsteen productivity indicator: An application to German dairy‐processing firms

Indicators and indexes of directional output loss and input allocative inefficiency

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