Using Individualised HDI Measures for Predicting Educational Performance of Young Students—A Swedish Case Study

Round 1

Reviewer 1 Report

Thank you for the opportunity to revise this paper, which I found interesting, well-written, and dealing with a relevant topic.

I think the paper has several strengths, but also I have some comments that I hope the authors take as constructive suggestions:

• I would recommend clarifying in the title that the context of the study is Sweden, so readers can know from the beginning what they will find in the paper.
• Although the authors mention what are the benefits of their study (in terms of the policy implications that the results can help derive), I would also recommend the authors to clearly state the research question (and if possible with a clear question mark that helps the reader see in a nutshell how the paper aims to make a contribution).
• I would recommend that the authors include the descriptive statistics of all the variables in the models in Table 1.
• Could you also report collinearity statistics (correlation matrix, Variance inflation Factors, etc)?
• I would suggest that some space for limitations of the study should be included. Same for future areas of research.
• Linked to the previous point, to what extent the results are applicable to other countries/regions? To what extent are they valid beyond the specific year of analysis? Would it be possible to run robustness tests with other years than 2014?
• While the policy implications are clear, does the study make any contribution to the literature?

I wish the authors luck with their project!

Author Response

Response to reviewer 1

Comment: Thank you for the opportunity to revise this paper, which I found interesting, well-written, and dealing with a relevant topic.

 Answer: Many thanks for your kind and constructive review – it has helped us improve the manuscript.

I think the paper has several strengths, but also I have some comments that I hope the authors take as constructive suggestions:

Comment: “I would recommend clarifying in the title that the context of the study is Sweden, so readers can know from the beginning what they will find in the paper.”

Answer: Thanks – we have now rewritten the title to: “Using Individualised HDI Measures for
Predicting Educational Performance of Young Students – a Swedish Case Study”

Comment: Although the authors mention what are the benefits of their study (in terms of the policy implications that the results can help derive), I would also recommend the authors to clearly state the research question (and if possible with a clear question mark that helps the reader see in a nutshell how the paper aims to contribute).

Answer: Thank you, we have now clarified the question better in the last paragraph of the introduction.

Comment: I would recommend that the authors include the descriptive statistics of all the variables in the models in Table 1.

Answer: Thanks- we have extended Table 1 with the descriptive statistics of all variables used in the analysis.

Comment: Could you also report collinearity statistics (correlation matrix, Variance inflation Factors, etc)?

Answer: Thank you very much. The last column of Table 2 now includes VIFs-and indicate that we didn’t have multicollinearity issues.

Comment: I would suggest that some space for limitations of the study should be included. Same for future areas of research.

Answer: Thank you very much for this suggestion. We’ve added a paragraph to conclusions on this. Even though our analysis reveals strong explanatory power of the local HDI in explaining student success both at the neighbourhood and student level, we have not explicitly quantified inequality of opportunities as measured by the local HDI. This is both a limitation of our study but also suggestion for future studies to test the local HDI in different countries.

Comment: Linked to the previous point, to what extent the results are applicable to other countries/regions?

Answer: Unlike typically used predictors of student performance- such as gender, parental background-the local HDI does not require student-level information. A measure of life expectancy, human capital and income at an aggregate (neighbourhood) level would suffice to repeat our analysis in other countries.  This point is now made clear in conclusions.

Comment: To what extent are they valid beyond the specific year of analysis? Would it be possible to run robustness tests with other years than 2014?

Answer: Thanks for this comment. We have repeated the analysis for the years 2015,2016 and 2017. Since some of the key variables (like voter participation) is only available for the year 2014, we ran a null multilevel model and a model with the local HDI for each year. The results confirm our main findings.

While the policy implications are clear, does the study make any contribution to the literature?

Answer: Thank you very much. We have added a few sentences to conclusions to highlight our contribution to the literature.

I wish the authors luck with their project!

Many thanks ?

Reviewer 2 Report

61-62: ...the equality of educational opportunity varies between locations ... It is not clear what you mean, as equality cannot vary. Please rephrase this sentence. 

Please bring arguments, why a study with data from 2013/2014 brings results that are relevant for 2021.

Author Response

Response to reviewer 2

Many thanks for you review.

Comment: “61-62: ...the equality of educational opportunity varies between locations ... It is not clear what you mean, as equality cannot vary. Please rephrase this sentence.”

Answer: thanks, we agree the sentence was unclear – we have altered the text to: “However, in Sweden, like in all countries, access to quality education varies between locations, and between socio-demographic groups.”

Comment: “Please bring arguments, why a study with data from 2013/2014 brings results that are relevant for 2021.”

Answer: Register data of this kind is only available to researchers a few years after the year of observation. The main reason is that especially taxation and income data may need several years to settle in the national databases (all income data are based on final tax registers). This means that the last available register data year in our database is 2017, and since we are dependent on election participation from national elections we use data from the last available year (elections were held …, 2012, 2014 and 2018) but since the last election (2018) was held later than the last year of data we had to use 2014 as the year of study. The year 2013 is used for two purposes – to see which individuals that migrated between 2013 and 2014, and to register the last known coordinates (2013) for individuals that died during 2014. We have strengthened this part in the manuscript so that the selection of years become clearer – also by discussing the choice of year in the introduction. 

Round 2

Reviewer 1 Report

No further comments for the authors