Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Structural causal models for macro-variables in time-series   We consider a bivariate time series $(X_t,Y_t)$ that is given by a simple
linear autoregressive model. Assuming that the equations describing each
variable as a linear combination of past values are considered structural
equations, there is a clear meaning of how intervening on one particular $X_t$
influences $Y_{t'}$ at later times $t'>t$. In the present work, we describe
conditions under which one can define a causal model between variables that are
coarse-grained in time, thus admitting statements like `setting $X$ to $x$
changes $Y$ in a certain way' without referring to specific time instances. We
show that particularly simple statements follow in the frequency domain, thus
providing meaning to interventions on frequencies.

3
The categories of this paper are: physics
22
The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
20
The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
31
The categories of this paper are: ao-sci
24
The categories of this paper are: dg-ga