Air Transportation Income and Price Elasticities in Remote Areas: The Case of the Brazilian Amazon Region

Round 1

Reviewer 1 Report

This study investigates the income-price elasticity of air passenger demand in the remote areas of the Brazilian Amazon. The structure is well organised. research problems and objectives are clear. Various assumptions in applying method are logically demonstrated both in methodology and results section.  The results are also interesting that there is no income-price elasticity of air passenger demand in the remote regions.

However, the authors need to explain more in detail in the Discussion part in terms of the analysis results, the main reasons of results difference between remote case and the capital case, income and price elasticities of demand in the case of South America if you are available. 

Author Response

Please check the answer in the attached file

Response to Reviewer 1 Comments

Firstly, we would like to thank the reviewer, who showed interest in the article and made excellent suggestion for its improvement. We commented in red the corrections and suggestions in the text below.

Reviewer 1

Date of this review

04 Jul 2020 19:24:21

However, the authors need to explain more in detail in the Discussion part in terms of the analysis results, the main reasons of results difference between remote case and the capital case, income and price elasticities of demand in the case of South America if you are available.

Thanks to the referee observation. We explain more in detail in the Discussion and Conclusion section in terms of the analysis results. In the Discussion section, we changed paragraphs 3th, 4th, 6th and included a last paragraph (lines 529-576). In the Conclusions section, we changed the 1st, 4th and 5th paragraphs (lines 576-602). The information available is only for Brazil. As presented in the data description, the database used in the investigation includes commercialized price for air tickets provided by ANAC (National Civil Aviation Agency).

Author Response File: Author Response.pdf

Reviewer 2 Report

A lot of studies of the price and income elasticity of air transport demand have focused on international air travel and advanced economies; Investigación of remote and domestic air travel most in emerging market welcome.

Moreover knowledge of price and income elasticity is useful as it may help to predict the possible impact of price-reducing aviation policies such as taxation.

The broad trends are dealt with well, but the paper could draw on a wider body of literature, especially in the discussion of capital cities results. Numerous papers have examined the price and income elasticity of air transport in Africa in recent years and it would be good to mention some of these.

Abate, M. (2016). Economic effects of air transport market liberalization in Africa. Transportation Research Part A: Policy and Practice, 92, 326-337.

Adler, N., Njoya, E. T., & Volta, N. (2018). The multi-airline p-hub median problem applied to the African aviation market. Transportation Research Part A: Policy and Practice, 107, 187-202.

Ssamula, B. "Comparing air transport network operations in sparse networks in Africa." Research in Transportation Business & Management 4 (2012), 22-28.

One problem associated with the analysis of price and income elasticity of air transport demand is the endogeneity of price variable. The quantity and price are simultaneously determined in the market by the equilibrium of demand and supply, meaning that price is endogenous. Failure to account for endogeneity of price may result in bias in price elasticity estimate. One solution is to use instrumental variable technique. This could be mentioned as a possible limitation of the paper.

Why start in 2011? How might the choice of time period affect the results of the study? How does the choice of time period slot into the market conditions and liberal scenario, and airline decision to operate in remote ares mentioned in the introduction but not further developed later in the findings nor accounted for in the methodology. What developments took place during the six-year period that could have affected airline decisions and air travel demand? 

Moreover, the choice of the independent variables used in the regression analysis needs explaining. To what degree are these variables the sole ‘drivers of air traffic’? Why use GDP and not per capita GDP or better per capita disposable incomes?

How much of passenger air traffic might be resource / exploration driven? Or humanitarian air services, or business, leisure?

Detail

Page 7 line 297: replace 5,9% with 5.9%.

Author Response

Please check the answer in the attached file.

Firstly, we would like to thank the reviewer, who showed interest in the article and made excellent suggestion for its improvement. We commented in red in the attached file the corrections and suggestions in the text below.

Author Response File: Author Response.pdf