NPSS: Stata module to estimate nonparametric heteroskedastic state space models

Irene Botosaru and Yuya Sasaki

Statistical Software Components from Boston College Department of Economics

Abstract: This program estimates nonparametric conditionally heteroskedastic state space models based on Botosaru and Sasaki (2018). Consider a state space model y(it) = u(it) + v(it), where y(it) is observed (e.g., earnings), u(it) is unobserved (e.g., permanent component of earnings), and v(it) is unobserved (e.g., transitory component of earnings), with the process u(it) = u(it-1) + w(it). Taking y(i1) and y(i2) as input, the command nonparametrically estimates and draws the density functions of u(i1) and v(i1). Taking y(i1), y(i2) and y(i3) as input, the command also nonparametrically estimates and draws the conditional skedastic function of u(i2) given u(i1), e.g., as a measure of heterogeneous risks in permanent component of earnings.

Language: Stata
Requires: Stata version 14.2
Keywords: state space; nonparametric; heteroskedasticity (search for similar items in EconPapers)
Date: 2020-04-26, Revised 2022-03-18
Note: This module should be installed from within Stata by typing "ssc install npss". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/n/npss.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/n/npss.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/e/example_2006_2008_2010.dta sample data file (application/x-stata)

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