4 citations · 4 across the 2 of their papers we have counts for
3 papers
econ.EM2023
Sparse High-Dimensional Vector Autoregressive Bootstrap
Robert Adamek, Stephan Smeekes, Ines Wilms
We introduce a high-dimensional multiplier bootstrap for time series data based on capturing dependence through a sparsely estimated vector autoregressive model. We prove its consi…
econ.EM2022★ 4 cited
Local Projection Inference in High Dimensions
Robert Adamek, Stephan Smeekes, Ines Wilms
In this paper, we estimate impulse responses by local projections in high-dimensional settings. We use the desparsified (de-biased) lasso to estimate the high-dimensional local pro…
econ.EM2020
Lasso Inference for High-Dimensional Time Series
Robert Adamek, Stephan Smeekes, Ines Wilms
In this paper we develop valid inference for high-dimensional time series. We extend the desparsified lasso to a time series setting under Near-Epoch Dependence (NED) assumptions a…