Housing and Setting Constraints: The Portuguese Evidence
Round 1
Reviewer 1 Report
Dear authors,
Firstly, I would like to congratulate you for your work. Please fing my commends below:
Line 43: What about the population? Locals? Foreigners? Any connection with the golden passport or permanent residence programmes?
What happened to the existing housing stock?
In my opinion chapter 2 needs more clarification. Why you chose this approach? Why is better than other ones? Any other methods that you tried?
Can you please explain clearer the multicollinearity matrix?
I would expect that the conclusions section should be stronger and more connected with the results
Some figures to be on appendix part
Author Response
Reviewer 1
Dear authors,
Firstly, I would like to congratulate you for your work. Please find my comments below:
Line 43: What about the population? Locals? Foreigners? Any connection with the golden passport or permanent residence programmes?
The question is pertinent. We did not consider the population because between the 2011 and 2021 Census the population variation was -2.1%, which means a certain stability of individuals for a decade (10,344,802 in 2021 compared to 10,562,178 in 2011), from according to the National Institute of Statistics.
It is the first time since 1970 that the country has lost population between censuses. The entire interior recorded a decrease in inhabitants compared to 2011. In this decade, the positive migratory balance was not enough to compensate for the negative natural balance (difference between births and deaths).
In 2021, around 50% of the population was concentrated in 31 of the 308 municipalities, located mostly in the Metropolitan Areas of Lisbon and Porto. The questionnaire, translated into five languages ten years ago, was translated into 11 other languages in 2021.
The Portuguese population today is strongly located on the coast, with the district of Algarve, Lisbon and Porto standing out, which together absorb around 55% of the total population. In fact, it is in these two cities and in this district that construction continues to increase. This paradox is due to the foreign demand for high incomes, made up of the French, English, Brazilians, Germans and Chinese.
What happened to the existing housing stock?
Construction was one of the sectors that best responded to the pandemic. Hand in hand with real estate development, it proved to be resilient, and the “rain” of projects born or coming out of paper in recent months is proof of that. Despite the dynamism in the sector, Portugal continues to struggle with the problem of the inadequacy of the supply of affordable housing to the disposable income of the Portuguese. The housing stock has stagnated in the last 10 years, showing a residual increase of only 1%. There is a lack of decent new houses, it is true, but building them is increasingly expensive, either because of the lack of labor or because of the increase in the prices of raw materials. The perfect storm that ends up being reflected in the final value of housing, which continues to rise.
In my opinion chapter 2 needs more clarification. Why you chose this approach? Why is better than other ones? Any other methods that you tried?
We choose this methodology due to the number of variables used in this study, not only to understand the correlation between variables (bi-variable correlation) but to understand the systemic result present when we study the relations among all the independent variables presented in this study. This was the moto to implement this method.
Can you please explain clearer the multicollinearity matrix?
Table 6 presents a bivariable analysis, a correlation between 2 variables, the multicollinearity analysis is presented Figures 4, 5, and 6.
I would expect that the conclusions section should be stronger and more connected with the results
Ok. I will attend to this statement and further strengthen the conclusions.
Some figures to be on appendix part
I'm not sure, but the displacement of figures to annexes should depend on the Journal, I believe. However, I am available to do so.
Reviewer 2 Report
This paper has presented a good study on the housing problem in the Portuguese, which is as well as a common problem in no matter developed and undeveloped countries. The authors also used several critical parameters to assess the housing and setting constraints. The work can be published before the authors added the concern. In the current version, the authors did not present the methodology for the data processing after Table 1 (parameters), or a detailed description of CATPCA, to make readers better understand the Tables and Figures of the results, also the two dimensions.
Author Response
Reviewer 2
This paper has presented a good study on the housing problem in the Portuguese, which is as well as a common problem in no matter developed and undeveloped countries. The authors also used several critical parameters to assess the housing and setting constraints. The work can be published before the authors added the concern.
In the current version, the authors did not present the methodology for the data processing after Table 1 (parameters), or a detailed description of CATPCA, to make readers better understand the Tables and Figures of the results, also the two dimensions.
We add a paragraph to fulfil the requirement of this pertinent input.
Reviewer 3 Report
Referee report on manuscript ID sustainability-1813557
The paper "Housing and setting constrains: the Portuguese evidence" provides an analysis of the housing market in Portugal for the years 2010-2019 via a categorical principal components analysis.
Overall, the paper needs to be structured more coherently and the exposition requires some restructuring. Below are further general remarks and specific comments.
Main comments:
-Title: The title should be more informative to draw a larger readership. Clearly indicate content-wise and from a methodological perspective what the reader can expect from the paper.
-Introduction: The introduction does not really motivate the methods that are employed subsequently. Indicate why the methods are required and what can be learned from applying them.
-Structure of the paper: the structure requires some more work, because the different parts of the paper are not separated and arranged in a coherent order. The following points are intended to help when re-writing this part of the paper:
Section '2 Research Methodology and Investigation Framework', is not self-contained as the methods are not clearly described and results are also presented here. Only describe the methods and analysis framework here. Next describe the data and data collection. The results and their discussion should be collected in a separate section.
-Terminology (e.g., p.11, l.207/208 and p.12, l.217): based on the CAPTCA analysis in Table 8, the variables are called 'significant'. As the reader might expect from the term that this refers to 'statistical significance', it might be more clarifying and appropriate here to state only that the variables are the 'most important in terms of variance explained'?
-Figure and Table captions should be more informative to make them self-contained. Clearly describe what is displayed for each Figure and Table.
Minor comments:
-p.7, l.152: variables are missing in the sentence explaining the formula
-p.8, l.167: should't this be Fig.5
-References: For some references, DOIs/URLs are given; this should be unified and given for all references.
-typos:
p.12, l.252
Author Response
Reviewer 3
The paper "Housing and setting constrains: the Portuguese evidence" provides an analysis of the housing market in Portugal for the years 2010-2019 via a categorical principal components analysis.
Overall, the paper needs to be structured more coherently and the exposition requires some restructuring. Below are further general remarks and specific comments.
Main comments:
-Title: The title should be more informative to draw a larger readership. Clearly indicate content-wise and from a methodological perspective what the reader can expect from the paper.
-Introduction: The introduction does not really motivate the methods that are employed subsequently. Indicate why the methods are required and what can be learned from applying them.
R: It was our purpose to analyse and verify the results of the applied model in relation to the variables taken into account. In any case, we will take your comment into consideration.
-Structure of the paper: the structure requires some more work, because the different parts of the paper are not separated and arranged in a coherent order. The following points are intended to help when re-writing this part of the paper:
Section '2 Research Methodology and Investigation Framework', is not self-contained as the methods are not clearly described and results are also presented here. Only describe the methods and analysis framework here. Next describe the data and data collection. The results and their discussion should be collected in a separate section.
-Terminology (e.g., p.11, l.207/208 and p.12, l.217): based on the CAPTCA analysis in Table 8, the variables are called 'significant'. As the reader might expect from the term that this refers to 'statistical significance', it might be more clarifying and appropriate here to state only that the variables are the 'most important in terms of variance explained'?
-Figure and Table captions should be more informative to make them self-contained. Clearly describe what is displayed for each Figure and Table.
R: Thanks for your suggestion. I would suggest that we just put it in the text instead of just changing “significant” to “statistical significant” and having a more political indication such as “The term “statistical significant” was added and, regarding the discussion of the results, the authors, as a matter of style of writing, considered that the results presented in chapter “4. Study Results and Data Collection””.
Minor comments:
-p.7, l.152: variables are missing in the sentence explaining the formula
R: This formula aimed to verify whether, in practice, the interest rate would have any relevant impact on the final results, but it did not. However, this did not happen, but we leave in the article the formula that the National Statistics Institute uses to determine the interest rate in studies on housing.
-p.8, l.167: shouldn’t this be Fig.5
The figures are correct.
-References: For some references, DOIs/URLs are given; this should be unified and given for all references.
We will take that into account.
-typos:
p.12, l.252
We will do that.
Round 2
Reviewer 1 Report
I have a clearer view after the responses I received on my questions. I would expect a better implementation on the paper's text though.
Author Response
Response to Reviewer 1 Comments
Point 1: I have a clearer view after the responses I received on my questions. I would expect a better implementation on the paper's text though.
Response 1: Thank you very much for your comment. In fact, the text could be improved, not least because no topic is exhausted. Therefore, we retain your comment for future investigations, on this or other future topics. More implementation could be improved, but we dare to go further on the topic. Thanks again for bringing your comment/suggestion to our attention.
In addition to what we said, we carried out a review of the English to improve the reading of the article.
Author Response File: 
Author Response.pdf
Reviewer 3 Report
Minor comments:
Figs.1-3: The captions are redundant
l.151: replace text marked in yellow by "statistically significant"
l.174: The formatting of the formula looks odd.
Author Response
Response to Reviewer 3 Comments
Point 1: Figs.1-3: The captions are redundant.
Response 1: We removed Figure 3.
Point 2: l.151: replace text marked in yellow by "statistically significant"
Response 2: We removed the word “significant”.
Point 3: l.174: The formatting of the formula looks odd.
Response 3: Thank you for your comment. Indeed, we removed from the article the reference to the formula and the text before and after it, which covers the paragraphs “A brief note on the interest rate implication considered. According to several authors, the variable that most influences real estate promotion and credit for home purchase is the implicit interest rate on credit (Brett et al., 2009), (Fang, 2019), (Marfatia, 2020). The opportunity cost is the lease through the market and the one that is sup-ported by the public authorities. The interest rate on home loans reflects the relation-ship between the total interest due in the reference month and the principal outstanding at the beginning of that month (before repayment). The interest rate of month m, for characteristic k, with periodicity of p months, is given by the following calculation formula (INE; 2021):
The characters are: is the total amount of interest due in month m for characteris-tic k, with amortization of p in p months, and is the total amount of outstanding credit, for characteristic k, whose reimbursement is paid from p to p months, at the time of collection of the previous repayment. This formula aimed to verify whether, in practice, the interest rate would have any relevant impact on the final results, as we will see later in the text. The present formula is used by the National Statistics Institute to determine the interest rate in studies on housing”.
Author Response File: Author Response.pdf
