Abstract
In this chapter, we illustrate the classical problem of quantile regression for cross-sectional data. We develop one practical exercise using R. We visualize and interpret our results, where quantile regression is used to explain which factors affect excess consumption of electricity by a sample of US households with different characteristics. These results are helpful to evaluate the risk of disproportionate consumption. Our innovation here, rather than the method, is our practical approach. We fully develop our example, guiding the reader step by step from the previsualization of the data to the interpretation of the coefficients and the diagnostics tests to be performed before and after the estimation of the parameters.
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Uribe, J.M., Guillen, M. (2020). Cross-sectional Quantile Regression. In: Quantile Regression for Cross-Sectional and Time Series Data. SpringerBriefs in Finance. Springer, Cham. https://doi.org/10.1007/978-3-030-44504-1_4
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DOI: https://doi.org/10.1007/978-3-030-44504-1_4
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