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  • Markov-switching -- discontinuous region with missing values encountered

    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.

    I get the error

    Code:
    could not calculate numerical derivatives -- discontinuous region with missing values encountered
    r(430);
    The code I run is :
    Code:
    mswitch ar gdp_g  rain ,arswitch varswitch ar(1) emiter(10000) difficult
    The theoretical background is a model with a latent unit root; (AR(1)).

    All variables in the model are endogenous with a single lag


    Data sample is below.

    Thanks for any help!

    Mario


    [CODE]
    * Example generated by -dataex-. For more info, type help dataex
    clear
    input float(year gdp_g rain)
    1945 . 1
    1946 . .9972528
    1947 . .9980889
    1948 . .9615384
    1949 . .993081
    1950 . .992267
    1951 4.368974 .9502442
    1952 3.166667 .9955353
    1953 4.2041025 .9815832
    1954 3.747949 .9855515
    1955 4.621282 .9871795
    1956 3.6202564 .9950279
    1957 3.802564 .996744
    1958 2.4289474 .9734432
    1959 3.84359 .9708995
    1960 4.145641 1
    1961 4.126154 .9675417
    1962 4.0646152 .9976317
    1963 4.5764103 .969496
    1964 4.854103 .9722375
    1965 4.299487 1
    1966 3.906923 .9927331
    1967 4.1284614 .9595888
    1968 4.664359 .9677419
    1969 5.080513 .9677419
    1970 4.200513 .9622474
    1971 4.272826 .9621588
    1972 3.957447 .9406098
    1973 4.0885105 .9263393
    1974 2.440638 .9370707
    1975 1.0009303 .9783654
    1976 3.4987235 .9853051
    1977 2.846522 .9867347
    1978 2.955532 .9846154
    1979 2.0948937 .9394796
    1980 1.2640425 .9987913
    1981 1.2 .9974144
    1982 1.9678724 .9786684
    1983 1.5117022 .9928895
    1984 2.570638 1
    1985 .9210638 1
    1986 2.248085 1
    1987 1.0723404 .9941823
    1988 2.2489362 .9896051
    1989 2.1693618 .9966871
    1990 .25382978 .994654
    1991 -.2125532 .9749401
    1992 .317234 .9999377
    1993 1.3534043 .9604037
    1994 2.612128 .9677929
    1995 3.358936 .9669732
    1996 2.3597872 .9697465
    1997 3.0414894 .9518272
    1998 1.793617 .9739011
    1999 1.8717022 .9756181
    2000 3.385532 .9853424
    2001 2.0512767 .9921017
    2002 2.913404 .982967
    2003 3.017021 .985989
    2004 3.321915 1
    2005 2.6668086 1
    2006 2.732766 .9806319
    2007 2.8740425 .9940829
    2008 .04914893 1
    2009 -.9074468 .9828658
    2010 2.887234 .9681467
    2011 1.4131914 .9968072
    2012 .9474468 .9703073
    2013 1.3274468 .972676
    2014 .8512766 .9808435
    2015 2.0059574 .
    2016 .59042555 .
    2017 1.825532 .
    2018 1.508298 .
    2019 .9170213 .
    2020 1.8051064 .
    end
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