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A kibocsátási rés becslése többváltozós állapottérmodellekben. Szuperhiszterézis és további empirikus eredmények
[Estimating output gap in multivariate state space models. Super-hysteresis and further empirical evidence]

Author

Listed:
  • Mellár, Tamás
  • Németh, Kristóf

Abstract

A reál-GDP ciklikus komponensének megbízható becslése különösen fontos a gazdaságpolitika számára. A kibocsátási rés különböző típusú modellekből kapott értékei olykor jelentősen eltérő, akár egymásnak ellentmondó képet mutatnak a konjunktúra alakulásáról. Mivel a hagyományos eljárások (HP-szűrő, termelési függvény) nem képesek megragadni a makrogazdasági egyensúly komplex, többdimenziós jellegét, ezért a kibocsátási rés becslésének több lehetséges módszerét ismertetjük, kiemelve a többváltozós megközelítéseket. Azt vizsgáljuk, hogy a többváltozós állapottér- modellek mennyiben használhatók a magyar gazdaság ciklikus pozíciójának értékelésére. Mivel az egyes modellekben eltérő módon ragadható meg a többváltozós makrogazdasági egyensúly, az eredmények bizonyos időszakokban komoly eltéréseket mutatnak. A különböző modellekből származó becslések összevetése ugyanakkor hasznos tanulságokkal szolgálhat. Eredményeink alapján három lényegi következtetésre jutunk: 1. a pozitív rés elsősorban nem a válságot közvetlenül megelőző években alakult ki, hanem 2004 és 2006 között; 2. 2016 végére a negatív kibocsátási rés bezárult; 3. a gazdaság növekedési képessége a válságot követően tartósan és jelentősen csökkent. A potenciális növekedés korábbi, évi 4 százalékos üteme a felére esett a vizsgált periódusban.* Journal of Economic Literature (JEL) kód: C32, C51, E66.

Suggested Citation

  • Mellár, Tamás & Németh, Kristóf, 2018. "A kibocsátási rés becslése többváltozós állapottérmodellekben. Szuperhiszterézis és további empirikus eredmények [Estimating output gap in multivariate state space models. Super-hysteresis and furt," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 557-591.
    • Handle: RePEc:ksa:szemle:1774
    DOI: 10.18414/KSZ.2018.6.557
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    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions

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