Announcement

Collapse
No announcement yet.
X
  • Filter
  • Time
  • Show
Clear All
new posts

  • State-Space Models with Regime Switching

    Hello,

    I try to estimate a growth model with Markov-switching models with AR(1) with both expansion and recession states. That is two states, expansion and recession.

    Mainly the impact of a number of indicators(index1 index2 form1 form2) on the growth rate(gdp_g), for expansion and recession.

    The theoretical background is a state space model with a latent unit root; (AR(1)).

    All variables in the model are endogenous with a single lag. I saw the help file, but I didn't understand how it is done in state space form, when other endogenous parameters affect it...

    One step ahead, prediction should be added in addition to address expectations.

    Data sample is below.

    Thanks for any help!

    Mario

    ----------------------- copy starting from the next line -----------------------
    Code:
    * Example generated by -dataex-. For more info, type help dataex
    clear
    input float(year gdp_g index1 index2 form1 form2)
    1980 1.2640425 -1.8494064  -.4919946  .1752619 .8247381
    1981       1.2 -1.4651397  -.5348802  .2135585 .7864415
    1982 1.9678724 -1.1484452  -.7147316  .3413058 .6586943
    1983 1.5117022  1.6252997  1.8567197 .26389787 .7361021
    1984  2.570638  2.4657974  2.1658478 .18436745 .8156326
    1985  .9210638  3.1889434  2.9895875  .1516645 .8483355
    1986  2.248085   5.396011  4.5956273 .19957983 .8004202
    1987 1.0723404   3.104351   3.289934 .23287007   .76713
    1988 2.2489362  1.2033308  .53224826 .22385173 .7761483
    1989 2.1693618   .6751824 -.16877118 .23149644 .7685035
    1990 .25382978  .05228972  -.3444368 .27984852 .7201515
    1991 -.2125532    .935702   .3012117  .3284199 .6465201
    1992   .317234  4.1132245  3.1708634  .3083437  .691594
    1993 1.3534043   5.108476  2.5406225 .24354993 .7332776
    1994  2.612128   3.425388   1.768389 .23602992 .7400631
    1995  3.358936   3.972118  2.3609061 .27747253 .7225274
    1996 2.3597872   6.033151   4.661421   .325723  .674277
    1997 3.0414894   3.793532   3.347975 .30558395 .6757603
    1998  1.793617  3.7508705   3.940954 .29313186 .6818681
    1999 1.8717022   2.980336   3.343685 .28042582 .7138736
    2000  3.385532   2.734389   1.775652  .2688356 .7311644
    2001 2.0512767   .7556655    1.75466  .2554258 .7445742
    2002  2.913404   1.386648  2.0334747  .2105769  .789423
    2003  3.017021  1.5340753  1.0089021  .1955357 .8044643
    2004  3.321915    1.81795   .5531137  .2408904 .7591096
    2005 2.6668086 -.29726213  -.7515011  .2480769 .7519231
    2006  2.732766  -2.838431 -2.9404194  .2673077 .7326923
    2007 2.8740425 -1.5961655 -1.8205668 .26824456 .7317554
    2008 .04914893  -1.881141  -3.931049  .2303533 .7696467
    2009 -.9074468  -.8101007  -1.919522 .23055235 .7694477
    2010  2.887234 -2.2245317 -1.8109186 .29588655 .7041135
    2011 1.4131914  -1.431529 -1.4509507  .3009355 .6958717
    2012  .9474468 -2.6042926 -3.2060516 .25005552 .7229174
    2013 1.3274468  -.8640846 -2.6833265 .20782596 .7834868
    2014  .8512766  -.6784925  -2.421195 .22527473 .7747253
    2015 2.0059574          .          .         .        .
    2016 .59042555          .          .         .        .
    2017  1.825532          .          .         .        .
    2018  1.508298          .          .         .        .
    2019  .9170213          .          .         .        .
    2020 1.8051064          .          .         .        .
    end
Working...
X