Investment and Dynamic Eco-Efficiency

By-production of undesirable output

Alfons Oude Lansink, Wageningen University, Netherlands

Hervé Dakpo – INRA, France

Background (1)

Investments in capital come with adjustment costs

Adjustment costs: learning, installation and administrative costs, reorganisation.

Adjustment costs increase with the level of investments

Adjustment costs in quasi-fixed inputs (like capital) prevent from instantaneous adjustment

Technical and eco-efficiency are not correctly measured if adjustment costs are not accounted for

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I 0

x z(x,I) •

gx

gI

Z’=(x-ßgx, I+ßgI)

ß=Dynamic Technical Inefficiency

Background (1)

Background (2)

Different approaches in the literature towards measuring eco-efficiency

Some authors introduced a dynamics into the model

● Skevas et al (2014) developed a dynamic DEA model in which negative externalities affect the future production conditions

● Kuosmanen and Kuosmanen incorporated the nutrient accumulation in a materials balance approach

So far, adjustment costs in investments have not been explicitly accounted for in eco-efficiency measurements

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Objectives

Extend the by-production model to account for adjustment costs

Measure dynamic eco-efficiency for a sample of French livestock farms – results are compared with the static approach

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Production Technologies

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Production Technologies

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We follow Dakpo (2015) and adapt the dependence constraints to link the two sub-

technologies:

Eco-efficiency is computed using a Russel type directional distance function :

Data French Livestock Farms (1978-2013)

Good Output (meat production)

Bad Output (CO2 equivalents, computed using LCA)

Variable inputs

● Operational costs

● Herd

Quasi-fixed input (Capital invested in machinery, buildings, land improvement)

Fixed inputs

● Land

● labor

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Dynamic Inefficiency

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1978-1989 1990-2001 2002-2013

Intermediate 0.080 0.063 0.088

Herd size 0.031 0.024 0.018

Investments 4.605 4.407 3.101

Meat 0.027 0.018 0.026

GHG emissions 0.066 0.054 0.066

Table 1: Dynamic Inefficiencies per period and variable

Static Inefficiency

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Table 2: Static Inefficiencies per period and variable

1978-1989 1990-2001 2002-2013

Intermediate 0.179 0.161 0.156

Herd size 0.080 0.114 0.107

Capital 0.467 0.376 0.396

Meat 0.014 0.009 0.015

GHG emissions 0.156 0.186 0.178

Static versus Dynamic

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Dynamic Static

Intermediate 0.076 0.165

Herd size 0.024 0.100

Investments/Capital 4.061 0.413

Meat 0.023 0.013

GHG emissions 0.062 0.173

Table 3: Dynamic and Static Inefficiencies

Conclusions

Developed a model that accounts for adjustment costs in by-production models

Static inefficiency in inputs tends to be bigger than dynamic inefficiency

Large inefficiency in the investments

Next step: Use this approach to measure dynamic environment adjusted total factor productivity growth

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Thank you!

Alfons Oude Lansink

Hervé Dakpo

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