 Facts and figures about UK taxes, benefits and public spending.
Income distribution, poverty and inequality.
Analysing government fiscal forecasts and tax and spending.
Analysis of the fiscal choices an independent Scotland would face.
Case studies that give a flavour of the areas where IFS research has an impact on society.
Reforming the tax system for the 21st century.
A peer-reviewed quarterly journal publishing articles by academics and practitioners.
|
We consider the identification of a Markov process {Wt, Xt*} for t=1,2,...,T when only {Wt} for t=1, 2,..,T is observed. In structural dynamic models, Wt denotes the sequence of choice variables and observed state variables of an optimizing agent, while Xt* denotes the sequence of serially correlated state variables. The Markov setting allows the distribution of the unobserved state variable Xt* to depend on Wt-1 and Xt-1*. We show that the joint distribution of (Wt, Xt*, Wt-1, Xt-1*) is identified from the observed distribution of (Wt+1, Wt, Wt-1, Wt-2, Wt-3) under reasonable assumptions. Identification of the joint distribution of (Wt, Xt*, Wt-1, Xt-1*) is a crucial input in methodologies for estimating dynamic models based on the "conditional-choice-probability (CCP)" approach pioneered by Hotz and Miller.
Search |
|
|
|
© The Institute for Fiscal Studies
Limited by Guarantee,Registered in England: 954616 7 Ridgmount Street London WC1E 7AE Registered Charity: 258815 VAT no: GB 394 5830 17 Website design by Pynk and Fluffy |
||||||
