Galton, Edgeworth, Frisch, and prospects for quantile regression in econometrics

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Smoothing Quantile Regressions (2019, background): “tial eects, quantile regressions are also interesting because they satisfy some equivariance and robustness principles. See Koenker and Bassett (1978) and Koenker (2005) for theoretical aspects; and Koenker (2000), Buchinsky (1998), Koenker and Hallock (2001), Koenker (2005) and references therein f”
Least absolute value regression: recent contributions (2005, background): “Koenker [20] provides an interesting review of historical connections to state-of-the-art aspects of LAV and quantile regression.”
The MM, ME, ML, EL, EF and GMM approaches to estimation: a synthesis (2002, background): “In his editorial in the inaugural issue of Sankhy¯ a, The Indian Journal of Statistics, Mahalanobis (1933) wrote, " . . . the history of modern statistics may be said to have begun from Karl Pearson's work on the distribution of χ 2 in 1900.”
Quantile Autoregression (2006, background): “A B-spline expansion QAR(1) model for Melbourne daily temperature is described in Koenker(2000) illustrating this approach.”
Local linear spatial quantile regression (2009, unknown): “see [29] or [30] for a review.”