TY - JOUR
T1 - Autoregressive wild bootstrap inference for nonparametric trends
AU - Friedrich, Marina
AU - Smeekes, Stephan
AU - Urbain, Jean Pierre
PY - 2020/1
Y1 - 2020/1
N2 - In this paper we propose an autoregressive wild bootstrap method to construct confidence bands around a smooth deterministic trend. The bootstrap method is easy to implement and does not require any adjustments in the presence of missing data, which makes it particularly suitable for climatological applications. We establish the asymptotic validity of the bootstrap method for both pointwise and simultaneous confidence bands under general conditions, allowing for general patterns of missing data, serial dependence and heteroskedasticity. The finite sample properties of the method are studied in a simulation study. We use the method to study the evolution of trends in daily measurements of atmospheric ethane obtained from a weather station in the Swiss Alps, where the method can easily deal with the many missing observations due to adverse weather conditions.
AB - In this paper we propose an autoregressive wild bootstrap method to construct confidence bands around a smooth deterministic trend. The bootstrap method is easy to implement and does not require any adjustments in the presence of missing data, which makes it particularly suitable for climatological applications. We establish the asymptotic validity of the bootstrap method for both pointwise and simultaneous confidence bands under general conditions, allowing for general patterns of missing data, serial dependence and heteroskedasticity. The finite sample properties of the method are studied in a simulation study. We use the method to study the evolution of trends in daily measurements of atmospheric ethane obtained from a weather station in the Swiss Alps, where the method can easily deal with the many missing observations due to adverse weather conditions.
KW - Nonparametric Estimation
KW - Bootstrap
KW - Confidence Intervals
KW - Trend analysis
KW - Missing data
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U2 - 10.1016/j.jeconom.2019.05.006
DO - 10.1016/j.jeconom.2019.05.006
M3 - Article
SN - 0304-4076
VL - 214
SP - 81
EP - 109
JO - Journal of Econometrics
JF - Journal of Econometrics
IS - 1
ER -