With the Continuing Increase in Sub-Saharan African Countries, Will Sustainable Development of Goal 1 Ever Be Achieved by 2030?
Round 1
Reviewer 1 Report
The article deals with a very interesting topic, namely the key drivers of poverty in SSA. The article is very well written, well documented, the ideas are presented concisely and in a logical order. I recommend publishing the article, but I have only one question.
The author should explain why the period 2015 to 2019 was considered and not considered a longer period, for example at least 10 years.
Author Response
Reviewer 1
Comment 1: The author should explain why the period 2015 to 2019 was considered and not considered a longer period, for example at least 10 years.
Response: Thank you for your suggestion, however, due to the unavailability of data with consistency, consistent data from 2015 to 2019 was chosen for the study.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
I understand that the calculations were made for the years 2015–2020. I am of the opinion that data from 6 years is insufficient to responsibly count regressions.
In addition, there are a lot of shortcomings in the article. For example, Fig. 5 – why the SSA region is not marked there, only other regions (e.g. East Africa) to which there are no references in the text. In addition, the linear scale (bar scale) is unreadable. Or in Figs. 1a and 1b there is an error in years, because there is an order: 1999, 1994, 1998, 2002, etc. – and 1990 should be given as the first year (because such is in the caption of the figure).
Author Response
Reviewer 2
Comments and Suggestions for Authors
Comment 1: I understand that the calculations were made for the years 2015–2019. I am of the opinion that data from 6 years is insufficient to responsibly count regressions.
In addition, there are a lot of shortcomings in the article. For example, Fig. 5 – why the SSA region is not marked there, only other regions (e.g. East Africa) to which there are no references in the text. In addition, the linear scale (bar scale) is unreadable. Or in Figs. 1a and 1b there is an error in years, because there is an order: 1999, 1994, 1998, 2002, etc. – and 1990 should be given as the first year (because such is in the caption of the figure).
Response: Thanks for the suggestion. Corrections have been done as suggested, see the manuscript
Line 392-394 and Line 143-145
Author Response File: Author Response.pdf
Reviewer 3 Report
The issue raised by the authors is indeed an important one, and is interesting from both scientific and practical perspectives. The literature review refers to the central issue of the paper, it is quite extensive, relevant and thorough. The review will be of interest to other researchers. I would like to mention that the authors have comprehensively studied the literature on the issue published over the last five years. References are correct. The conclusion is consistent with presented arguments and evidence. The results complete previous results on the matter and are supported by references. I would recommend that the authors indicate the period of analysis in the abstract, as well as list which research methods were used.
Author Response
Reviwer’3
Response: Can be improved
Comment 1:
Comments and Suggestions for Authors
The issue raised by the authors is indeed an important one and is interesting from both scientific and practical perspectives. The literature review refers to the central issue of the paper, it is quite extensive, relevant, and thorough. The review will be of interest to other researchers. I would like to mention that the authors have comprehensively studied the literature on the issue published over the last five years. References are correct. The conclusion is consistent with the presented arguments and evidence. The results complete previous results on the matter and are supported by references. I would recommend that the authors indicate the period of analysis in the abstract, as well as list which research methods were used.
Response: Thanks for the suggestion. Corrections have been done as suggested. Please see the manuscript, lines 12-13.
Author Response File: Author Response.pdf
Reviewer 4 Report
The paper is a good attempt to understand the poverty in African countries, but needs to be improved significantly before publication.
The classification of countries normally poor, moderately and extremely poor needs to be changed as per the international nomenclature. “Normally poor” meaning is confusing. In abstract you mentioned “Moreso, education (second-19 ary school ennoblement) is less important in reducing poverty than per capita personal consumer spending and GDP growth rate” . But in your analysis “per capita consumption” itself is taken as proxy indicator for poverty. There is something wrong with the above sentence.
In sentence in abstract “According to the proposed theoretical and numerical model, people in the normal, intermediate, and destitute classes may fall below the international poverty line (US$ 1.90 per day)” is meaningless unless you give magnitude in each class. Probably it is not class but country.
Please mention which countries are falling in each category of countries extremely poor countries (EPC), moderately poor countries (MPC) and normally poor countries (NPC).
In the model per capita PCE (a proxy for poverty) and per capita income (a measure of inequality) will be more or less same. One is dependent variable and other one is independent variable. Pls justify. Improve the model.
General observations
Overall, the English language of the paper is poor, needs to be improved.
Model should be built on theorical understanding and proper identification of dependent and independent variables with clarity in definition.
The analysis is good, but lot of extra text needs to be pruned and focus on the model, results and testing of robustness.
Pls go through the following paper
Reddy, A. A. (2015). Growth, structural change and wage rates in rural India. Economic and Political Weekly, 56-65. available at http://dspace.stellamariscollege.edu.in:8080/xmlui/bitstream/handle/123456789/5075/growth.pdf?sequence=1&isAllowed=y
Author Response
Reviewer’s 4
Comments 1: and Suggestions for Authors
The paper is a good attempt to understand the poverty in African countries but needs to be improved significantly before publication. The classification of countries normally poor, moderately, and extremely poor needs to be changed as per the international nomenclature. “Normally poor” meaning is confusing. In the abstract, you mentioned, “More so, education (second-19 school ennoblement) is less important in reducing poverty than per capita personal consumer spending and GDP growth rate”. But in your analysis “per capita consumption” itself is taken as a proxy indicator for poverty. There is something wrong with the above sentence.
Response
The classification of countries has been aligned to the international nomenclature using groups as established by the World’s Bank GNI per capita differentiation.
The sentence has been rewritten to be clearer and concise in meaning. It highlights indeed that per capita consumption is a better indicator of poverty which is consistent with the remark.
Comment 2: In the sentence in the abstract “According to the proposed theoretical and numerical model, people in the normal, intermediate, and destitute classes may fall below the international poverty line (US$ 1.90 per day)” is meaningless unless you give magnitude in each class. Probably it is not class but country.
Response
The sentence has been reformulated to give it a meaning. It specifies that the proposed model does not rule out groups of people within countries in higher categories to fall below the poverty line. (See lines 22 to 26 in the abstract)
Comment 3: Please mention which countries are falling into each category of countries extremely poor countries (EPC), moderately poor countries (MPC), and normally poor countries (NPC).
Response
Countries have been listed in chosen categories (see manuscripts)
Comment 4: In the model per capita PCE (a proxy for poverty) and per capita income (a measure of inequality) will be more or less the same. One is the dependent variable and another one is the independent variable. Pls, justify. Improve the model.
Response
Many experimental models were fitted on candidates’ proxy variables for poverty including (PCE and PCI). I chose the model that offered the best fit. In the model with poverty (PCE as a proxy) offering the best fit to the data, PCE becomes de facto the dependent variable. All other possible regression models with the data at hand had bad goodness of fit measures or validity issues with their residuals and partial residuals.
General observations
Comment 1: Overall, the English language of the paper is poor, and needs to be improved.
Response: Following the comment, the paper was submitted for proofreading to a language editor.
Comment 2 Model should be built on theoretical understanding and proper identification of dependent and independent variables with clarity in the definition.
Response:
The understanding of model dynamics was at the center of preoccupation since the beginning of this investigation. Historical data used for this analysis is openly available, and the fitted model that could give the soundest explanation of dynamics at play in the utmost respect of mathematical and statistical modeling principles was chosen as the one which could give the best insight into the unfolding interactions.
Comment 3: The analysis is good, but a lot of extra text needs to be pruned and focus on the model, results, and testing of robustness.
Response:
No effort was spared to make sure all comments made are addressed. I’m very thankful for the specific and general observations as I can see how each one of them improves substantially the quality of the analysis, they significantly ameliorate
Author Response File: Author Response.pdf
Round 2
Reviewer 4 Report
Still lot needs to be improved in the paper.
Theoretical explanation between poverty and other explanatory variables is not properly presented in the paper. Authors needs to see the literature linking poverty and other explanatory variable at country level. There are many studies authors can look in to before choosing the right variables to be included in the model. The paper is not acceptable in the current from.
Tsai, M. C. (2006). Economic and non-economic determinants of poverty in developing countries: competing theories and empirical evidence. Canadian Journal of Development Studies/Revue canadienne d'études du développement, 27(3), 267-285.
Adeyemi, S. L., Ijaiya, G. T., & Raheem, U. A. (2009). Determinants of poverty in sub-Saharan Africa. African Research Review, 3(2).
Reddy, A. A. (2015). Growth, structural change and wage rates in rural India. Economic and Political Weekly, 56-65.
Ravallion, M. (1995). Growth and poverty: Evidence for developing countries in the 1980s. Economics letters, 48(3-4), 411-417.
Specific suggestion
1. 1.9 USD or 1.9 PPP, authors should clarify which they have used. The 1.9 PPP is right, not the USD.
2. Poverty and percapita consumption are generally taken as one and the same and closely interrelated. Please clarify how percapita consumption determine poverty.
3. Figure 2 heading should be growth rate in GDP percapita
4. Instead of GDP, percapita consumption author should use internal conflicts, governance, agricultural productivity, urbanisation, openness, Trade-GDP ratio, credit growth, share of non-agricultural GDP, growth in service sector, literacy rate, gender gap in literacy rate as explanatory variables.
Author Response
Section: Health, Well-Being and Sustainability
Reviewer No 4
Comments and Suggestions for Authors
Still lot needs to be improved in the paper. Noted with thanks.
Comment 1
Theoretical explanation between poverty and other explanatory variables is not properly presented in the paper. Authors needs to see the literature linking poverty and other explanatory variable at country level. There are many studies authors can look in to before choosing the right variables to be included in the model. The paper is not acceptable in the current from.
Response
The theoretical explanations between poverty and the other explanatory variables in SSA have been reinforced in 1.1.Background Study, and a reference to the conceptual framework in one of the article had been added. The explanations had already been discussed in 1.1.1.The number of poor and the total population; 1.1.2. GDP growth rate per capita; 1.1.3.Inequality and Gini index; 1.1.4. Education; 1.1.5. Lack of essential services and agriculture; 1.1.6. Civil wars, conflicts, and unemployment ; 1.1.7. Diseases. There is also some discussions in 3.2 Determinants of economic factors and poverty in SSA. The suggested literature have been extensively consulted to enrich the additional comments. Many candidate variables were considered, and several different models were fitted. Subject to availability and reliability of the data, the retained variables were the most pertinent. The model settled on with the variables included, was the one offering the best statistical validity, in terms of interpretation of results and inferences. Almost all relevant variables to economic analysis of poverty were considered and examined. It is true that some other variables can always be included in any model, but again as explained above, many of the few available for the period under consideration did not yield any statistical significance, or model relevance. Poor coefficients of determination, failing validity checks on residuals.
Tsai, M. C. (2006). Economic and non-economic determinants of poverty in developing countries: competing theories and empirical evidence. Canadian Journal of Development Studies/Revue canadienne d'études du développement, 27(3), 267-285.
Adeyemi, S. L., Ijaiya, G. T., & Raheem, U. A. (2009). Determinants of poverty in sub-Saharan Africa. African Research Review, 3(2).
Reddy, A. A. (2015). Growth, structural change and wage rates in rural India. Economic and Political Weekly, 56-65.
Ravallion, M. (1995). Growth and poverty: Evidence for developing countries in the 1980s. Economics letters, 48(3-4), 411-417.
Specific suggestion
Comment 2
- 1.9 USD or 1.9 PPP, authors should clarify which they have used. The 1.9 PPP is right, not the USD.
Response
The methodological approach was aligned to the world bank classification, and that is perfectly in line with the ICP 2011 PPPs that gave the 1.9 Purchasing Power Parity.
Comment 3
Poverty and percapita consumption are generally taken as one and the same and closely interrelated. Please clarify how percapita consumption determine poverty.
Response
The argument here is made by the comment itself. The fact that per capita consumption is generally taken the same as poverty suffices to justify why per capita consumption can be used as a proxy for poverty.
Comment 4
Figure 2 heading should be growth rate in GDP per capita
Response
The heading was changed as recommended.
Comment 5
Instead of GDP, percapita consumption author should use internal conflicts, governance, agricultural productivity, urbanisation, openness, Trade-GDP ratio, credit growth, share of non-agricultural GDP, growth in service sector, literacy rate, gender gap in literacy rate as explanatory variables.
Response
This will amount to a totally different analysis altogether which could be carried on as a follow-up on the work done here. As explained above several of the variables mentioned here were considered and harvested, like literacy rate, gender gap in literacy rate (Male and Female school enrollment rates ) but many were discarded at a later stage because of partial or incomplete data set that would not have allowed for an objective analysis.
Author Response File: Author Response.pdf
Round 3
Reviewer 4 Report
Sentence in abstract: “it does not guarantee that people in the 23 UMIC, LMIC, and LIC countries may not fall below the international poverty line (US$ 1.90 per 24 day)”--- are you using PPP or USD in measuring poverty line.
Please add a few references to justify econometric models which included PCE as dependent variables and PCI as independent variable. For this you may refer (i) Tsai, M. C. (2006). Economic and non-economic determinants of poverty in developing countries: competing theories and empirical evidence. Canadian Journal of Development Studies/Revue canadienne d'études du développement, 27(3), 267-285. (ii) Adeyemi, S. L., Ijaiya, G. T., & Raheem, U. A. (2009). Determinants of poverty in sub-Saharan Africa. African Research Review, 3(2)., (iii) Reddy, A. A. (2015). Growth, structural change and wage rates in rural India. Economic and Political Weekly, 56-65., (iv) Ravallion, M. (1995). Growth and poverty: Evidence for developing countries in the 1980s. Economics letters, 48(3-4), 411-417.
Answer question of is there any difference among lower-middle, upper-middle and low income countries in respect of factors influencing poverty?
Introduction is too long, it should be focused on problem, questions to be answered and hypothesis.
Some graphs of introduction needs to be shifted to results section.
Overall, the paper can be acceptable with the above changes.
Author Response
Reviewer’s 4 Comment
Thank you for the suggestions, all comments have been addressed below.
Comments and Suggestions for Authors
Comment 1: Sentence in the abstract: “it does not guarantee that people in the 23 UMIC, LMIC, and LIC countries may not fall below the international poverty line (US$ 1.90 per 24 days)”--- are you using PPP or USD in measuring poverty line.
Response: It is the current $1.90 (international dollar) based on the PPPs released for the reference year 2011. The mention has been corrected in the abstract as $1.90 instead of US$1.90.
Comment 2: Please add a few references to justify econometric models which included PCE as the dependent variable and PCI as the independent variable. For this, you may refer to (i) Tsai, M. C. (2006). Economic and non-economic determinants of poverty in developing countries: competing theories and empirical evidence. Canadian Journal of Development Studies/Revue canadienne d'études du développement, 27(3), 267-285. (ii) Adeyemi, S. L., Ijaiya, G. T., & Raheem, U. A. (2009). Determinants of poverty in sub-Saharan Africa. African Research Review, 3(2)., (iii) Reddy, A. A. (2015). Growth, structural change, and wage rates in rural India. Economic and Political Weekly, 56-65., (iv) Ravallion, M. (1995). Growth and poverty: Evidence for developing countries in the 1980s. Economics Letters, 48(3-4), 411-417.
Response: The suggested additional references have been added.
Comment 3: Answer the question of is there any difference among lower-middle, upper-middle, and low-income countries in respect of factors influencing poverty?
Response: There are similarities in countries in lower-middle, upper-middle, and low-income countries, however factors influencing poverty are not the same in those three categories. Unequal distribution of income is an aggravating factor more severe in lower and low-income countries, while GDP growth and education levels are more impactful for poverty reduction in upper-middle countries than they are in the lower-middle and low-income countries. Poverty levels could be higher where intriguingly growth measures are higher, underlying the importance of social inequalities and wealth distribution in the analysis of poverty. Literacy level is a positive factor when it comes to poverty reduction for low and lower-middle-income countries.
Comment 4: The introduction is too long, it should be focused on the problem, questions to be answered, and hypothesis. Some graphs of the introduction need to be shifted to the results section.
Response: The introduction was shortened, figures were shifted to results as recommended the stylized facts subsection was moved to results.
Comment 5: Overall, the paper can be acceptable with the above changes.
Response: Thank you, all suggested changes were positively received and implemented as recommended.
Author Response File: Author Response.pdf
