Can Energy Efficiency Promote Human Development in a Developing Economy?

Round 1

Reviewer 1 Report

1.     The abstract should provide specific quantified results on the effect of  efficiency in the generation of electricity on the per capita GDP in India.

2.     There are too many long sentences in this research. All you have done is to present that information in a way that is easy for the reader to absorb at a first reading.

3.  The Introduction needs to be restructured so it does not read so much like a background. The authors should provide a pithy context paragraph and then proceed to explain the problem their research is addressing, the significance, and the unique nature of their approach,i.e. new contribution to the scholarship.

4.     In equation (1). What does the index ”t” mean?

5.      In section 3, p2. “(see https://kof.ethz.ch/en/forecasts-and-indicators/indicators/kof-globali-sation-index.html)’ .  It is an informal reference format.

6.     In equation（2）， why ‘log’ is lost?

7.     In section 1, P.3. I don't think time series is better than panel models.

8.     In section 3, there is a lack of data description.

9.     The language should be polished, entirely by a native English speaker.

Author Response

We have attached our response to Reviewer 1's comments. 

REVIEWER 1

 

Comments and Suggestions for Authors

1. The abstract should provide specific quantified results on the effect of efficiency in the generation of electricity on the per capita GDP in India.

The abstract has been re-written following the advice of the reviewer. We have added the quantified results. The added segment is highlighted.

 

2. There are too many long sentences in this research. All you have done is to present that information in a way that is easy for the reader to absorb at a first reading.

Some of the sentences have been re-written.

3. The Introduction needs to be restructured so it does not read so much like a background. The authors should provide a pithy context paragraph and then proceed to explain the problem their research is addressing, the significance, and the unique nature of their approach, i.e. new contribution to the scholarship.

The introduction is re-written, see paragraph 1, paragraph 2 and paragraph 3 on pp. 1-2. We appreciate this comment, which allows us to rewrite the introduction.

4. In equation (1). What does the index ”t” mean?

The correction is made on p.11 after equation (1).

5. In section 3, p2. “(see https://kof.ethz.ch/en/forecasts-and-indicators/indicators/kof-globali-sation-index.html)’ .  It is an informal reference format.

The correction is made in Section 3 on p. 11.

6. In equation（2），why ‘log’ is lost?

The changes are made on p. 11 before equation (2).

7. In section 1, P.3. I don't think time series is better than panel models.

Lest the misunderstanding creeps in, we have added Footnote 1 to explain why time series analysis is a more suitable for the research problem. Necessary corrections are made so that time series analysis appears to be a better analysis than panel data analysis.

 

8. In section 3, there is a lack of data description.

The description of data is added on p. 11.

9. The language should be polished, entirely by a native English speaker.

It has been polished by a native speaker.

Reviewer 2 Report

Find attached the review comments.

Comments for author File: Comments.pdf

Author Response

REVIEWER 2:

Can Energy Efficiency in Electricity Generation Promote Human Development in a

Developing Economy?

I commend the authors for such an interesting article.

I suggest minor revision

.

[1] Title: I suggest the authors modify the title to reflect the true content of the paper.

The paper assesses not just energy efficiency in electricity generation.

We have modified the title. See the potion deleted.

[2] Abstract: Why does the author connote energy efficiency to access to energy and

clean water? The linkage not clear

We have re-written the abstract. See the segment highlighted in the abstract as the new bit.

[3] Introduction.

 

The gap identified in erstwhile studies not clear. A mere ensemble of variables in a

single framework cannot be said to be a contribution at all. “Our paper aims to fill this gap

in the literature by considering human development, efficiency in electricity generation,

increased uses of labour and capital inputs in the Indian electricity sector, and globalisation

in a single econometric framework.”

 

I suggest the authors provide the gap in previous studies, necessitating this current

research. Clearly and concisely present evidence of what has been done so far regarding this

topic, the missing element(s), and how this study extends current knowledge. Such narration

will help further highlight the authors’ novel contribution

We are grateful to the referee for this recommendation. We have re-written the introduction and add the first two paragraphs and the abstract.

 

[4] The authors need to elucidate further on the key contribution of this present study. Be

clear about the specific significant contributions of this current study.

We have highlighted the key contributions right from the abstract, introduction, models, findings and conclusion - highlighted.

 

[5] The author posited to have followed the paper by Acheampong et. al (2021). There

are, however, key fundamental differences between this current paper and the paper

by Acheampong et.al (2021): Clearly, this present paper focuses on energy efficiency

whiles the paper by Acheampong focuses on access to energy access.

 

Again, differing measurements of the constructs account for differences in these

two papers. Acheampong measured human development using InHDI (Human

Development Index sourced from UNDP, different from the measurement in this

present paper.

We have highlighted the difference and the rationale for the differences. The HDI dataset is available from early 1990s while the per capita gdp for India is available for about four decades (see Footnote 1).    

 

[6] I suggest the authors look at the links between energy efficiency and energy access.

The authors need to improve the literature review by providing narration on the

synergy between energy efficiency and renewable energy as demonstrated by the

previous studies.

See

• du Can, S. D. L. R., Pudleiner, D., & Pielli, K. (2018). Energy efficiency as a

means to expand energy access: A Uganda roadmap. Energy Policy, 120, 354-

364.

This is an enormously interesting paper. We have benefitted immensely from du Can et al. The paper is re-written using du Can et al. (2018).

 

 

[7] “improvements in access to energy are accompanied with decreases in energy

efficiency – we argue – improved access to energy will have a deleterious effect on

human development”

This statement happens to be the core of this present work. Such contextual

backbone must be situated well in the literature. Clearly from that sentence, it seems

to have been relied on only a single work. I suggest the authors improve their narration

and cite more references to support the strong assertion.

This is an important point. We have used several new references to improve the narrative.

 

[8] The authors formed some biased opinion such as the assertion below

“improvements in access to energy are accompanied with decreases in energy

efficiency ( Page 2) . It will be prudent for the authors to support their assertion with

citations from key authorities.

This point is rectified: one the one hand, improving energy access lowers energy poverty and promotes human development. On the other hand, deterioration in energy efficiency lowers human development and adversely impinges on energy poverty. Thus, the net effect depends on the relative strengths of these two opposite effects.

 

[9] The nexus between energy poverty and access to energy needs to be elucidated further.

The section 2.1 needs to be improved.

We are grateful to the referee and have added the following on pp.6-7.

The role of energy efficiency in promoting global sustainability is discussed in IEA (2016). Li et al. (2016) highlight various methodologies for measuring energy efficiency in high energy consuming industries to lower carbon footprints.  Craig and Feng (2017) utilised state level data for the US to explore how fuel types in the generation of electricity and electricity consumption of the residential sectors impact carbon emissions and what role energy efficiency has to capture the adverse effects of energy use on carbon footprints.  Sanstad et al. (2014) re-evaluated the load forecasting models to highlight how better forecasts can improve US energy efficiency and, thereby, lower carbon footprints and achieve sustainability.  Trianni et al. (2016) examine the effect of energy efficiency on the competitiveness of small and medium-sized enterprises in the Northern Italy. They advocate the targeted measures of popularising energy efficiency for non-energy benefits as a means for improving mitigation strategies.

 

 

[10] What is the methodological contribution of this paper? The author needs to pinpoint

the exact methodological contribution of this present paper.

The methodological contribution is highlighted on pp. 2 and we added the following:

For exploring this missing link, we apply the standard autoregressive distributed lag (ARDL) model and extend our analysis by using the novel dynamic ARDL simulations (dynardl) model and the frequency domain causality test. The dynardl is a machine learning based algorithm for testing cointegration after controlling for nonlinearity, additivity and heterogeneity.  We thereby highlight the inner dynamics of energy efficiency as a major determinant of the effects of access to energy upon human development. The dynardl model can simultaneously explore short-run and long-run relationships, in both levels and differences in variables of interest, and extract the individual effects of explanatory variables on the dependent variable. It also offers visual confirmation of the effect of a counterfactual change in an explanatory variable on the dependent variable holding all other explanatory variables unchanged (ceteris paribus). 

 

[11] The discussion of the study needs to be improved. I suggest the authors provide the

implications, inferences, and plausible reasons accounting for those results. The discussion of the results of this current study, in reference to findings from recent similar studies, seems limited and warrants critical attention. I suggest the author further compares the results of the current study with similar erstwhile studies to corroborate or contrast the findings. Clearly and concisely present the key findings of this present study vis-à-vis results from similar works whilst providing appropriate citations, and highlighting how this current study extends current knowledge. Such narration will help further highlight the authors’ novel contribution.

We are grateful to the referee for the suggestion. On pp. 19-20, we have added the following segments in a blue font on pp. 19-20:

 

The result is in consonance with the findings of Goulder and Schneider (1999).    This result has a special significance for the finding of Acheampong et al. (2021) who note that energy access worsens human development in South Asia. This is feasible, as our work highlights, if energy efficiency declines with rising energy access. We, hence, provide a economic rationale for the findings of Acheampong et al. (2021).

Growth in labour input (GEL) in the electricity sector – from the novel dynamic ARDL simulations - has an adverse short-term impact on human development that is statistically significant. There is no statistically significant impact of GEL on human development in the long-run.  The impact of employment in energy sector on overall human development is expected. In the extant literature, there is no prior work to shed light on this effect. Intuitively, the results from the ARDL model for GEL can be justified in terms of low technological frontier (see Zhang, 2013; Rajbhandari and Fan, 2018):  this result implies that, ceteris paribus, increases in production of energy by increasing employment lower energy efficiency and increases the cost of energy production, which results in lower human development.   We find that growth in capital input (GEK) in the energy sector, ceteris paribus, has neither long-term nor short-term impacts on human development from the ARDL model.  The findings of the novel dynamic ARDL simulations are different from the findings from the standard ARDL models for the long-run as well as for the short-run. From the novel dynamic ARDL model, we see that GEK has an adverse impact on human development. This result can be justified in terms of the crowding out effect of increases in investment in energy sector -  as shown by Goulder and Mathai (2000); Goulder (1995). Hence, we find that the key driver of human development is energy efficiency in the electricity sector of India. Globalisation (LX1) has a strong and positive short-run effect on human development, though there is no evidence of any long-run impact. The effect of globalisation from the standard ARDL model is different from the predictions of the dynamic ARDL simulations for the long-run. The dynamic ARDL model concurs with the findings of Acheampong et al. (2021) that external sector promotes human development.

 

We have also added the following to the Concluding comments on p.26:

first, instead of focussing upon the total energy output, which determines energy access by enlarging the total energy pool, we focus upon the energy efficiency in the electricity sector in India. Secondly, using the per capita GDP as a proxy for human development, we found that energy efficiency in the electricity sector plays a pivotal role in driving economic development in India. If improvements in access to energy are attained using increases in GEK, GEL with decreases in energy efficiency in the electricity sector, then improved access to energy can trigger decreases in human development.

 

 

Reviewer 3 Report

The paper is very interesting and well-written. My suggestions for improvement are mainly with regards to the discussion and conclusion part:

1.) It would be nice if you added a figure with your research model, showing your hypothesised relationships, so that the reader can visually understand your approach.

2.) I suggest that in the conclusion the authors explain the abbreviations once more, so that the reader doen to have to scroll back to the beginning

3.) I also suggest that the authors add a discussion section before the conclusions section, in which they can reflect on the evidence they have provided in the first half of the paper (in their literature review), and explain how their findings fare in connection to existing evidence (confirm or reject existing findings), and how they contribute to theory and practice.

4.) Please double check that the two major drivers of per capita GDP that you describe in the conclusions of your study are indeed correctly phrased. As they are written, it looks like there is a relationship that only runs in one direction. However, it may be logical to also think that the oposite direction may also be valid (e.g. that increases in per capita GDP may lead to increases in energy efficiency in the generation of electricity - in cases where energy efficiency measures are costly and drive energy prices to rise e.g. if renewable sources of energy have to be added in order to increase energy efficiency in the generation part). Make sure that a uni-directional relationship is not possible here (based on your own findings as well as literature).

5.) Study limitations (e.g. the fact that this study was performed in only one country, etc.) and the corresponding suggestions for future research need to be added to the conclusion.

6.) The authors cite two of their already published papers. Please make sure that they are necessary to cite. If not, I would simply omit them to reduce the posibility of scrutiny for self-citations.

Author Response

We have uploaded a file to explain our response to the comments of Reviewer 3.

 

1.) It would be nice if you added a figure with your research model, showing your hypothesised relationships, so that the reader can visually understand your approach.

We are grateful to the referee for suggesting the possibility of using a figure. We tried but our efforts did not yield any satisfactory outcome.

2.) I suggest that in the conclusion the authors explain the abbreviations once more, so that the reader doen to have to scroll back to the beginning

We have amended the conclusion to incorporate the advice. Our specific addition to the conclusion to as a response it as follows:

Our departure from the current literature is twofold: first, instead of focussing upon the total energy output, which determines energy access by enlarging the total energy pool, we focus upon the energy efficiency in the electricity sector of India. Secondly, using the per capita GDP as a proxy for human development, we found that energy efficiency in the electricity sector plays a pivotal role in driving economic development in India. If improvements in access to energy are attained using increases in capital input (GEK) and increases in labour input (GEL) with decreases in energy efficiency in the electricity sector, then improved access to energy can trigger decreases in human development.

3.) I also suggest that the authors add a discussion section before the conclusions section, in which they can reflect on the evidence they have provided in the first half of the paper (in their literature review), and explain how their findings fare in connection to existing evidence (confirm or reject existing findings), and how they contribute to theory and practice.

We have amended the discussion section (4.1) to incorporate the advice. Our specific response is in a blue font and as follows:

The results of novel dynamic simulated ARDL error correction models are reported in Table 7: one of the main findings is that EFF increases human development in the long-run and not in the short-run: 1% increase in EFF will result in 0.39% increases in human development, measured by the per capita GDP (X₂), in the long-run. The short-run effect is not statistically significant. The effects of EFF from the standard ARDL model, given in Table 5 and Table 6, are different from the findings from the novel dynamic ARDL simulations mainly for the short-run. The result is in consonance with the findings of Goulder and Schneider (1999).    This result has a special significance for the finding of Acheampong et al. (2021) who note that energy access worsens human development in South Asia. This is feasible, as our work highlights, if energy efficiency declines with rising energy access. We, hence, provide a economic rationale for the findings of Acheampong et al. (2021).

Growth in labour input (GEL) in the electricity sector – from the novel dynamic ARDL simulations - has an adverse short-term impact on human development that is statistically significant. There is no statistically significant impact of GEL on human development in the long-run.  The impact of employment in energy sector on overall human development is expected. In the extant literature, there is no prior work to shed light on this effect. Intuitively, the results from the ARDL model for GEL can be justified in terms of low technological frontier (see Zhang, 2013; Rajbhandari and Fan, 2018):  this result implies that, ceteris paribus, increases in production of energy by increasing employment lower energy efficiency and increases the cost of energy production, which results in lower human development.   We find that growth in capital input (GEK) in the energy sector, ceteris paribus, has neither long-term nor short-term impacts on human development from the ARDL model.  The findings of the novel dynamic ARDL simulations are different from the findings from the standard ARDL models for the long-run as well as for the short-run. From the novel dynamic ARDL model, we see that GEK has an adverse impact on human development. This result can be justified in terms of the crowding out effect of increases in investment in energy sector -  as shown by Goulder and Mathai (2000); Goulder (1995). Hence, we find that the key driver of human development is energy efficiency in the electricity sector of India.

Globalisation (LX1) has a strong and positive short-run effect on human development, though there is no evidence of any long-run impact. The effect of globalisation from the standard ARDL model is different from the predictions of the dynamic ARDL simulations for the long-run. The dynamic ARDL model concurs with the findings of Acheampong et al. (2021) that external sector promotes human development.

The error correction term (ECT) is negative and statistically significant, though the error correction rate is low (about 20%). The R-squared value shows that 55% of the variability in the dependent variable (X₂) are explained by the chosen regressors. The projected F-statistics and the associated P value show that the proposed model is a good fit.

4.) Please double check that the two major drivers of per capita GDP that you describe in the conclusions of your study are indeed correctly phrased. As they are written, it looks like there is a relationship that only runs in one direction. However, it may be logical to also think that the oposite direction may also be valid (e.g. that increases in per capita GDP may lead to increases in energy efficiency in the generation of electricity - in cases where energy efficiency measures are costly and drive energy prices to rise e.g. if renewable sources of energy have to be added in order to increase energy efficiency in the generation part). Make sure that a uni-directional relationship isnot possible here (based on your own findings as well as literature).

We have checked the reverse causality, which is rejected by the frequency domain causality. If not rejected, we would have to apply the var framework and not the ARDL framework. This is explained in the conclusion. We have added a section in the conclusion, which is given in our response to point 5 below.

5.) Study limitations (e.g. the fact that this study was performed in only one country, etc.) and the corresponding suggestions for future research need to be added to the conclusion.

We are grateful to the referee for this comment. Our response in the appendix is as follows:

The main weakness of our analysis is mutual dependence of the chosen variables, which can significantly compromise the ARDL models. The frequency domain causality ensures that there is no mutual dependence. The future research will explore time-varying causality.  

6.) The authors cite two of their already published papers. Please make sure that they are necessary to cite. If not, I would simply omit them to reduce the posibility of scrutiny for self-citations.

These references are relevant for the methodology that we have used.