Technical efficiency and CO2 reduction potentials — An analysis of the German electricity and heat generating sector

Seifert, Stefan; Cullmann, Astrid; Hirschhausen, Christian von

doi:10.1016/j.eneco.2016.02.020

Cited by 30 publications

(16 citation statements)

References 38 publications

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“…The estimates of scale elasticity obtained are in line with more recent studies' findings on scale elasticities in fossil fuel electricity generation, as e.g., Kumbhakar and Tsionas (2016). Compared to Seifert et al (2016) and Seifert (2015) also analyzing German electricity generation, results differ in a few points. Seifert et al (2016) The results of this analysis also need to be interpreted with caution.…”

Section: Scale Efficiency and Scale Elasticitysupporting

confidence: 78%

“…Thus, the plants could produce 12.6% additional output by using best practice with the same input endowment. This expected inefficiency deviates considerably from the results in Seifert (2015) and Seifert et al (2016), which are both based on similar samples. However, the observation period of both studies end one in 2010, one year before the data in our sample, and one year before the considerable down-turn in gas-fired electricity generation in Germany (see Figure 2).…”

Section: Data Sources Key Variables and Descriptive Statisticscontrasting

confidence: 45%

“…Compared to Seifert et al (2016) and Seifert (2015) also analyzing German electricity generation, results differ in a few points. Seifert et al (2016) The results of this analysis also need to be interpreted with caution. While the StoNED estimator allows a very flexible estimation, it is also subject to the curse of dimensionality, i.e., estimated efficiency can only increase with an increasing number of right-hand side variables.…”

Section: Scale Efficiency and Scale Elasticitymentioning

confidence: 95%

“…Ghosh and Kathuria (2016) indicate strong positive scale effects for India's coal-fired generation, and Akkemik (2009) finds considerable scale economies in the Turkish electricity generating sector. Based on estimates using DEA and StoNED Seifert et al (2016) and Seifert (2015) indicate that losses due to suboptimal scale size in Germany's electricity generation depend on fuel sources. Overall, the early literature indicates IRS in electricity generation, while more recent studies suggest constant returns-to-scale (CRS) or DRS, supporting the argument that perceived RTS may have been exploited.…”

mentioning

confidence: 99%

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Semi-Parametric Measures of Scale Characteristics of German Natural Gas-Fired Electricity Generation

Seifert

2016

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract Scale characteristics are key properties of production functions that determine optimal firm sizes, and have considerable policy implications for sectors undergoing restructuring. However, estimates of scale characteristics typically vary with the assumptions of the underlying empirical model. This paper derives estimators of scale efficiency and scale elasticity for semi-parametric stochastic nonsmooth envelopment of data (StoNED) that are based on few assumptions and rely neither on a functional form nor on distributional assumptions, but satisfy basic microeconomic properties. The estimators are applied to a unique sample covering 124 natural gas-fired power plants operating in Germany in 2011. Terms of use: Documents inResults indicate that on average plants operate under constant to slightly decreasing returns-to-scale, and scale inefficiency is found to be overall rather low. However, considerable improvement potential exists due to technical inefficiency. The results allow the strong fragmentation of gas-fired electricity generation in Germany, but emphasize the importance of using best practices on plant level.JEL-Codes: D24,C14,O13,L94

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Section: Scale Efficiency and Scale Elasticitysupporting

confidence: 78%

Section: Data Sources Key Variables and Descriptive Statisticscontrasting

confidence: 45%

Section: Scale Efficiency and Scale Elasticitymentioning

confidence: 95%

mentioning

confidence: 99%

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Semi-Parametric Measures of Scale Characteristics of German Natural Gas-Fired Electricity Generation

Seifert

2016

SSRN Journal

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“…or plant fuels (e.g. Seifert et al, 2014;. Accounting for such technological differences when measuring productivity developments allows for the identification of productivity trends as well as the major components on sectoral and subtechnological level, i.e.…”

Section: Measuring Productivity Growth In Electricity Generationmentioning

confidence: 99%

Measuring Productivity When Technologies are Heterogeneous: A Semi-Parametric Approach for Electricity Generation

Seifert

2015

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWhile productivity growth in electricity generation is associated with multiple positive effects from an economic and environmental perspective, measuring it is challenging. This paper proposes a framework to estimate and decompose productivity growth for a sector characterized by multiple technologies. Using a metafrontier Malmquist decomposition and frontier estimation based on stochastic non-smooth envelopment of data (StoNED) allows for productivity estimation with few microeconomic assumptions. Additionally, evaluation of productivity at representative hypothetical units permits distribution-free analysis for the whole distribution of power plant sizes. The proposed framework is used to analyze a unique and rich dataset of coal, lignite, gas, and biomass-fired generators operating in Germany from 2003 to 2010. The results indicate stagnating productivity for the sector as a whole, technical progress for biomass plants, and very high productivity for gas-fired plants. JEL-Codes: D24,C14,O13,L94

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Efficiency assessment of electricity generation from renewable and non‐renewable energy sources using Data Envelopment Analysis

Rodríguez-Lozano

Cifuentes-Yate

2021

Int J Energy Res

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Summary This study assesses the efficiency of electricity generation from renewable and non‐renewable energy sources, by evaluating 126 countries selected as decision‐making units from different continents in the period between 2000 and 2016, using the Data Envelopment Analysis methodology. The model used is Banker‐Charnes‐Cooper output‐oriented, taking into account the totality of electricity generation. Input variables correspond to capacities of electricity generation, such as coal, oil, natural gas, nuclear, hydroelectric, wind, solar, geothermal, tidal, biomass and waste. Output variables are the amounts of electricity produced by each of these sources and carbon dioxide equivalent avoided by each country due to the use of renewable energies in electricity production. Results show that units' efficiency is often set between 60.0% and 79.9%, and countries such as Saudi Arabia, Bahrain, Canada, China, South Korea, the United States, France, Paraguay, Russia and South Africa are efficient throughout the study period. It is highlighted that Oceanian countries obtained the highest average efficiency among other evaluated countries, discriminated by continents.

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Technical efficiency and CO2 reduction potentials — An analysis of the German electricity and heat generating sector

Cited by 30 publications

References 38 publications

Semi-Parametric Measures of Scale Characteristics of German Natural Gas-Fired Electricity Generation

Semi-Parametric Measures of Scale Characteristics of German Natural Gas-Fired Electricity Generation

Measuring Productivity When Technologies are Heterogeneous: A Semi-Parametric Approach for Electricity Generation

Efficiency assessment of electricity generation from renewable and non‐renewable energy sources using Data Envelopment Analysis

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