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Mixed-data sampling (MIDAS) regressions allow to estimate dynamic equations that explain a low-frequency variable by … high-frequency variables and their lags. When the difference in sampling frequencies between the regressand and the … macroeconomic applications, however, differences in sampling frequencies are often small. In such a case, it might not be necessary …
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Classical regression analysis is usually performed in two steps. In a first step an appropriate model is identified to describe the data generating process and in a second step statistical inference is performed in the identified model. An intuitively appealing approach to the design of...
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We consider a high-dimensional regression model with a possible change-point due to a covariate threshold and develop the Lasso estimator of regression coefficients as well as the threshold parameter. Our Lasso estimator not only selects covariates but also selects a model between linear and...
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We consider the estimation of a semiparametric location-scale model subject to endogenous selection, in the absence of an instrument or a large support regressor. Identification relies on the independence between the covariates and selection, for arbitrarily large values of the outcome. In this...
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