Bootstrap tests for simple structures in nonparametric time series regression

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Testing and imposing Slutsky symmetry in nonparametric demand systems (2009, methodology): “Then, the bootstrap works because the residuals are mean independent and we only use the residuals for resampling (see also Kreiss et al., 2002).”
An updated review of Goodness-of-Fit tests for regression models (2013, background): “Kreiss et al. (2008) provided an extensive review on this type of tests, justifying the consistency of a variety of resampling procedures for test calibration (see also Franke et al. 2002).”
Estimation and inference in spatially varying coefficient models (2018, methodology): “As proved by Kreiss, Neumann, and Yao (2008), which considered the nonparametric bootstrap tests in a general nonparametric regression setting, asymptotically, the conditional distribution of the bootstrap test statistics is indeed the distribution of the test statistics under the null hypothesis,…”
Trending time-varying coefficient time series models with serially correlated errors (2007, background): “random variables with mean zero and unit variance; see Kreiss et al. (1998) for the detailed discussions.”