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Study of air travel demand during economic crises using sparse high-dimensional econometric models and non-traditional covariates


The demand for air travel in emerging markets has idiosyncrasies scarcely explored by the international literature, which is in general focused on the attributes typically observed in developed region realities. Besides factors such as the economic activity and the price of airline tickets, for a country as Brazil some variables related to income distribution, access to credit and indebtedness, digital inclusion, among others, may constitute relevant predictive variables that should not be disregarded in sectoral empirical studies. This project aims to study the role of a wide range of these covariates, using a sparse high-dimensional econometric model applying the Post-Double Selection Lasso Estimator (PDS-LASSO). The relevance of non-traditional socioeconomic attributes will be analyzed and tested using as a case the period of remarkable increase in air travel demand observed in Brazil over the 2000s until the early 2010s, in which the growth rates of the sector were considerably higher than the overall growth of the economy. As a final result, a ranking with statistical and economic relevance of air travel demand indicators will be developed. Based on the identification and ranking of these regressors, the study aims to provide subsidies to the planning of airline network and to the investments in airport and air traffic infrastructure, possibly allowing more accurate projections of future demand in the period of economic recovery after the current crisis, in which the country may be involved within the next decades. (AU)

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(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
BRITO, IGOR R. S.; OLIVEIRA, ALESSANDRO V. M.; DRESNER, MARTIN E. An econometric study of the effects of airport privatization on airfares in Brazil. TRANSPORT POLICY, v. 114, p. 338-349, DEC 2021. Web of Science Citations: 0.

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