Сравнение методов

	Фурье-регрессия квантиль-по-квантилю	Тест на коинтеграцию ARDL с Фурье-преобразованием
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	2015-2020s	2001-2021
Автор метода	Extension combining Sim & Zhou (2015) QQ regression with Fourier flexible-form smoothing	Pesaran, Shin & Smith (ARDL foundation); Fourier extension by Nazlioglu and related authors
Тип	Nonparametric quantile regression with Fourier smoothing	Cointegration / bounds test
Основополагающий источник	Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8.	Nazlioglu, S., Gormus, A., & Soytas, U. (2021). Oil prices and monetary policy in emerging markets: structural breaks, asymmetries, and Fourier approximations. Energy Economics, 95, 105119.
Другие названия	Fourier QQ regression, Fourier-QQR, Fourier quantile regression with quantile regressors, smooth structural-break QQ regression	Fourier ARDL, Fourier bounds testing, ARDL with Fourier approximation, F-ARDL cointegration test
Связанные	6	5
Сводка	Fourier quantile-on-quantile regression extends the quantile-on-quantile (QQ) framework of Sim and Zhou (2015) by embedding Fourier trigonometric terms into the local linear quantile model. This allows the estimated dependence between the quantiles of one variable and the quantiles of another to vary smoothly over time, capturing gradual structural change without imposing a known break date.	The Fourier ARDL bounds test augments the Pesaran-Shin-Smith cointegration framework with trigonometric (Fourier) terms that capture gradual, smooth structural breaks in the data-generating process. It tests for a long-run level relationship between variables without requiring the researcher to specify the number, timing, or form of structural breaks in advance.