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    <title>Kawasaki, Y.</title>
    <link>http://repub.eur.nl/res/aut/10270/</link>
    <description>List of Publications</description>
    <language>en</language>
    <image>
      <url>http://repub.eur.nl/static-eur/img/logo.png</url>
      <title>RePub, Erasmus University Rotterdam</title>
      <link>http://repub.eur.nl</link>
    </image>
    <item>
      <title>Do seasonal unit roots matter for forecasting monthly industrial production? (Article)</title>
      <link>http://repub.eur.nl/res/pub/2167/</link>
      <pubDate>2004-03-03T00:00:00Z</pubDate>
      <description>We investigate the seasonal unit root properties of monthly industrial production series for 16 OECD countries within the context of a structural time series model. A basic version of this model assumes that there are 11 such seasonal unit roots. We propose to use model selection criteria (AIC and BIC) to examine if one or more of these are in fact stationary. We generally find that when these criteria indicate that a smaller number of seasonal unit roots can be assumed and hence that some seasonal roots are stationary, the corresponding model also gives more accurate one-step-ahead forecasts</description>
    </item> <item>
      <title>Detecting seasonal unit roots in a structural time series model (Article)</title>
      <link>http://repub.eur.nl/res/pub/2165/</link>
      <pubDate>2003-01-01T00:00:00Z</pubDate>
      <description>In this paper, we propose to detect seasonal unit roots within the context of a structural time series model. Such a model is often found to be useful in practice. Using Monte Carlo simulations, we show that our method works well. We illustrate our approach for several quarterly macroeconomic time series variables.</description>
    </item>
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