Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Oracle Efficient Estimation of Structural Breaks in Cointegrating
  Regressions   In this paper, we propose an adaptive group lasso procedure to efficiently
estimate structural breaks in cointegrating regressions. It is well-known that
the group lasso estimator is not simultaneously estimation consistent and model
selection consistent in structural break settings. Hence, we use a first step
group lasso estimation of a diverging number of breakpoint candidates to
produce weights for a second adaptive group lasso estimation. We prove that
parameter changes are estimated consistently by group lasso and show that the
number of estimated breaks is greater than the true number but still
sufficiently close to it. Then, we use these results and prove that the
adaptive group lasso has oracle properties if weights are obtained from our
first step estimation. Simulation results show that the proposed estimator
delivers the expected results. An economic application to the long-run US money
demand function demonstrates the practical importance of this methodology.

23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
37
The categories of this paper are: supr-con
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
33
The categories of this paper are: plasm-ph