Browsing by Subject "Norja"

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  • Koskela, Erkki; Virén, Matti (1982)
    Bank of Finland. Monthly Bulletin 56 ; 10 ; October
  • Hyytinen, Ari (1999)
    Suomen Pankin keskustelualoitteita 19/1999
    This paper investigates the evolution of the (conditional) volatility of returns on three Scandinavian markets (Finland, Norway and Sweden) over the turbulent period of the past decade, namely the overlapping periods of financial liberalisation, drastically changing macroeconomic conditions and banking crisis. We find that even over this relatively turbulent period volatility is in most cases successfully captured by past volatility and shocks to past volatility, ie by a (symmetric) GARCH process.In each country banking crisis has induced regime shifts in (unconditional) volatility.We also find evidence for cross-country volatility spillovers during the banking crisis episodes.The estimated volatility patterns suggest that even though the volatility of returns was of very high magnitude during the years of banking crisis, developments within the banking industry were not reflected in market uncertainty until all the damage had been done and the severe problems afflicting banks began to be realised in full. Key words: GARCH, conditional volatility, banking crisis, volatility spillovers
  • Vauhkonen, Jukka; Westman, Hanna (2013)
    Euro & talous. Rahoitusjärjestelmän vakaus 2
    Suomen pankkijärjestelmän rakenne on haavoittuva pankkijärjestelmän kasvaneen koon, suuren keskittyneisyyden, pankkien kansallisen ja pohjoismaisen voimakkaan kytkeytyneisyyden ja joidenkin pankkiryhmien systeemisen merkittävyyden vuoksi. Suomessa tulee olla valmius asettaa joko kaikille pankeille tai osalle pankeista EU:n vakavaraisuusdirektiivin sallimia lisäpääomavaatimuksia.
  • Honkapohja, Seppo (2012)
    Bank of Finland Research Discussion Papers 36/2012
    The financial liberalization in the four Nordic countries (Denmark, Finland, Norway, and Sweden) that took place mostly in the 1980s led to a major financial crisis in three of those countries. The crises in Finland, Norway, and Sweden are among the deepest financial crises in advanced market economies since World War II. Denmark experienced some banking problems but managed to avoid a systemic crisis. This paper reviews the process of liberalization and discusses the reasons why Finland, Norway, and Sweden drifted into financial and economic crises. Keywords: financial repression, credit rationing, capital account controls, financial deregulation JEL classification numbers: E42, F36, G28
  • Honkapohja, Seppo (2009)
    Bank of Finland Research Discussion Papers 5/2009
    The current financial crisis, which has lasted almost one and a half years, is the 19th such crisis in the post-war period in advanced economies. Recent literature classifies the Nordic crises in Norway, Sweden and Finland in late 1980's and early 1990 s among the Big Five crises that have happened before the current crisis, which is now of a global nature. This paper outlines the developments of the Nordic crises, reasons behind them and crisis management by the authorities. Relatively more emphasis is placed on the Finnish crisis, as it was the deepest one. The paper concludes by considering the lessons that can be drawn from the Nordic crises
  • Iacoviello, Matteo; Minetti, Raoul (2000)
    Suomen Pankin keskustelualoitteita 14/2000
    This paper tests for the presence of a credit channel (particularly a bank-lending sub-channel) for monetary policy in the housing market.We argue that the importance of this channel for investment in residential housing is highly dependent on the structural features, and particularly the efficiency and institutional organization, of housing finance.We employ a VAR methodology to analyse this issue with respect to the housing markets of four European countries (Finland, Germany, Norway and the United Kingdom), which differ greatly in terms of structural features.Our results are generally consistent with the existence of a broad credit channel, whereas the bank-lending channel seems to be operational only under certain conditions.More importantly, our results are consistent with previous analyses of housing market efficiency, which strongly suggests the existence of a clear relationship between the presence of a credit (bank lending) channel, the efficiency level of housing finance, and the type of institutions that are active in mortgage provision. Keywords: monetary transmission, bank lending channel, house prices, vector autoregressions
  • Peura, Tapio; Kollster, Uwe (1989)
    Bank of Finland Research Discussion Papers 24/1989
    Vaihtotase on ollut talouspolitiikan huolenaiheena kaikissa Pohjoismaissa 1980-luvulla. Tanskalla on ollut pysyvä, verrattain suuri alijäämä ja ulkomaanvelka on noussut korkeaksi. Tämä on edellyttänyt rajoittavaa talouspolitiikkaa jo vuosia. Suomessa muita maita nopeampi talouskasvu on heikentänyt ulkoista tasapainoa vähitellen ja nähtävissä oleva velkaantumiskehitys on noussut talouspolitiikan keskeiseksi huoleksi. Norjan vaihtotase kääntyi suurista ylijäämistä selvästi alijäämäiseksi 1980-luvun puolivälissä öljyn hinnan laskun seurauksena. Tämä on aiheuttanut sopeutumisongelmia koko taloudessa. Ruotsi on kireällä talouspolitiikalla onnistunut tasapainottamaan sekä julkisen talouden että vaihtotaseen. Ulkomaisen velkaantumisen, palvelutaseen heikkenemisen ja tulonsiirtojen kasvun ·seurauksena vaihtotaseeseen on syntynyt kaikissa Pohjoismaissa "rakenteellinen" alijäämäosa, mikä vastaa noin kolmea prosenttia bruttokansantuotteesta. Vaihtotaseen tasapainon parantaminen edellyttäisi tuntuvaa ylijäämää tavaroiden kaupassa, mikä puolestaan edellyttäisi taloudellisen aktiviteetin heikentymistä suhteessa muihin maihin.
  • Honkapohja, Seppo (2009)
    Bank of Finland. Bulletin 1
    The current financial turmoil has now lasted almost two years. In the post-war period, the current crisis is the 19th in advanced economies and the first in the 21st century. In a recent paper, Carmen Reinhart and Kenneth Rogoff (2008) divide the 18 crises before the current US subprime crisis into the big five and a number of smaller crises. The big five include the crises in Norway, Finland and Sweden that occurred mostly in the early 1990s. The Norwegian crisis began already in the late 1980s, but continued into the 1990s.
  • Pesola, Jarmo (2001)
    Bank of Finland. Discussion papers 6/2001
    The macroeconomic reasons for the recent banking crises in the Nordic countries are analysed using an econometric model estimated with panel data from the 1980s and 1990s.Two alternative dependent variables are used: the ratio of banks' loan losses to lending and enterprise bankruptcies per capita.The explanatory variables are the lagged dependent variable, lagged percentage change in GDP, an income surprise variable combined with lagged aggregate indebtedness, a real interest rate surprise variable combined with lagged aggregate indebtedness, and a deregulation dummy.The innovation in this paper is the use of surprise variables based on macroeconomic forecasts.According to the results, high indebtedness combined with negative macroeconomic surprises contributed to the recent banking crises in Sweden, Norway and Finland.Also the effects of the preceding financial liberalization and lending boom on bankruptcies and loan losses can be traced in the results.The econometric testing did not indicate direct effects of the exchange rate or the terms of trade on the banking crises.Denmark did not suffer a banking crisis because the macroeconomic surprises were smaller there and the initial debt burden was lighter than in the other Nordic countries.This was the result of, among other things, earlier financial deregulation, which was conducted in a fairly balanced way, and a different economic policy regime, as Denmark belonged to the ERM.Key words: financial deregulation, indebtedness, shock, loan loss, banking crisis
  • Bask, Mikael; Liu, Tung; Widerberg, Anna (2006)
    Bank of Finland Research Discussion Papers 9/2006
    Published in Physica A, 376, 2007: 565-572
    The aim of this paper is to illustrate how the stability of a stochastic dynamic system is measured using the Lyapunov exponents. Specifically, we use a feedforward neural network to estimate these exponents as well as asymptotic results for this estimator to test for unstable (chaotic) dynamics.The data set used is spot electricity prices from the Nordic power exchange market.Nord Pool, and the dynamic system that generates these prices appears to be chaotic in one case.Key words: feedforward neural network, Nord Pool, Lyapunov exponents, spot electricity prices, stochastic dynamic system JEL classification numbers: C12, C14, C22
  • Parviainen, Seija (2008)
    Suomen Pankki. BoF online 2008/8
    Kansainvälisissä vertailuissa Suomen työllisyysasteen on usein todettu olevan alempi kuin muissa Pohjoismaissa. Tämä peittää kuitenkin alleen muita eroja pohjoismaisten työmarkkinoiden rakenteissa, jotka selittävät tätä havaintoa. Merkittävin ero Pohjoismaiden työmarkkinoiden välillä on osa-aikatyön yleisyydessä, mikä vaikeuttaa työllisyysvertailujen tulkintaa. Vaikka naisten työhönosallistumisaste on kaikissa Pohjoismaissa kansanvälisesti katsottuna korkea, tekevät naiset Suomessa muita Pohjoismaita yleisemmin kokoaikatyötä
  • Milne, Alistair (2005)
    Bank of Finland Research Discussion Papers 16/2005
    The developed world exhibits substantial but poorly understood differences in the efficiency and quality of low-value payment services.This paper compares payments arrangements in the UK, Norway, Sweden, and Finland, and discusses the impact of network effects on incentives to adopt new payments technology.A model is presented, in which private benefits for investment in shared inter-bank payments infrastructure are weak.In contrast, due to 'account externalities', there are strong incentives for investment in intra-bank payment systems.These two features, distinguishing bank payments from other network industries, can help explain some of the observed cross country differences in payments arrangements. Key words: network effects, incentives, payment technology, externalities JEL classification numbers: G21, L14