Analysis of Inequality Levels of Industrial Development in Rural Areas through Inequality Indices and Spatial Autocorrelation

Round 1

Reviewer 1 Report

Dear authors,

The subject is a very interesting one, and it would have beeneven more interesting if the approach had been topical. Below are my suggestions:

1. In the lower part of the introduction, perhaps the purpose of the study should be better highlighted/clarified.

2. In the methodology section (2.4.1.) perhaps a betterjustification of the selection of the areas analysed is needed. Why those areas and not others?

3. The main minus is that the data analysed are not at allcurrent, influencing the possible recommendations that can bemade in the current context.  In this timeframe, things canchange quite a lot. Perhaps a justification regarding therelatively outdated data used would be useful. I think thereneeds to be some justification for the fact that these data are not up to date.

4.​The "Discussion" section should provide an analysis of the results (which you have done) in comparison to existingresearch, so the bibliographic references would besubstantially improved.

All the best

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

I have read the paper Analysis of Inequality Levels of Industrial Development in Rural Areas through Inequality Indices and Spatial Autocorrelation and found it interesting. The study makes a nice contribution to the subject.  The literature is well written. It can be accepted after minor improvements.

The authors should also present: 

- the novelty of the study,

- the practical implications of this study and the comparison with other similar studies,

-what other factors affect inequality, as well as how these inequalities relate to economic growth  in rural areas.

 

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

- Please shortly present in Abstract: 1)research problem; 2) methods of research; and 3) main findings and  proposals:

- Not clear research problem? (in Introduction)

- Too old data (2010-2015). Now it is 2023. Is it possible to get older data? Situation after almost 8 years could change cardinally? Maybe you can compare 2015-2020 years data? 

I do not think, that it is limitation of research to get newer data from statistic.

Conclusions have to be from newest data.

 

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The manuscript clarifications seem to be fine.

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

There are no answers in the Abstract: What was the aim of the research?

Author Response

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Author Response File: Author Response.docx