TY  - INPR
CY  - Cambridge
ID  - publications50299
UR  - http://tse-fr.eu/pub/130200
A1  - Higgins, Ayden
A1  - Jochmans, Koen
Y1  - 2024/12//
N2  - We consider the problem of identifying the parameters of a time-homogeneous
bivariate Markov chain when only one of the two variables is observable. We show that, subject to conditions that we spell out, the transition kernel and the distribution of the initial condition are uniquely recoverable (up to an arbitrary relabelling of the state space of the latent variable) from the joint distribution of four (or more) consecutive time-series observations. The result is, therefore, applicable to (short) panel data as well as to (stationary) time series data.
PB  - Cambridge University press
JF  - Econometric Theory
KW  - dynamic discrete choice
KW  - finite mixture
KW  - Markov process
KW  - regime switching
KW  - state dependence
SN  - 0266-4666
TI  - Learning Markov Processes with Latent Variables
AV  - public
ER  -