Replication and robustness analysis of ‘energy and economic growth in the USA: A multivariate approach’
Stephan B. Bruns,
Johannes König and
David Stern
Energy Economics, 2019, vol. 82, issue C, 100-113
Abstract:
We replicate Stern (1993), who argues and empirically demonstrates that it is necessary (i) to use quality-adjusted energy use and (ii) to include capital and labor as control variables in order to find Granger causality from energy use to GDP. Though we could not access the original dataset, we can verify the main original inferences using data that are as close as possible to the original. We analyze the robustness of the original findings to an alternative estimation approach, alternative definitions of variables, and alternative model specifications for both the (almost) original time span (1949–1990) and an extended time span (1949–2015). p-values tend to be substantially smaller if energy use is quality adjusted rather than measured by total joules and if capital is included. Including labor has mixed results. These findings tend to largely support Stern's (1993) two main conclusions and emphasize the importance of accounting for changes in the energy mix in time series modeling of the energy-GDP relationship and controlling for other factors of production. We also discuss how the inclusion of the original author in designing the replication study using a pre-analysis plan can help to counterbalance the incentive of replicating authors to disconfirm major findings of the original article to increase the probability of getting published.
Keywords: Replication; Robustness analysis; Sensitivity analysis; Energy; GDP; Divisia index; Granger causality (search for similar items in EconPapers)
JEL-codes: C32 C52 Q43 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)
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Working Paper: Replication and robustness analysis of 'energy and economic growth in the USA: a multivariate approach' (2018) 
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:82:y:2019:i:c:p:100-113
DOI: 10.1016/j.eneco.2018.10.007
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