Browsing by Subject "business cycles"

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  • Crowley, Patrick M.; Trombley, Christopher (2015)
    Bank of Finland Research Discussion Papers 11/2015
    Within currency unions, the conventional wisdom is that there should be a high degree of macroeconomic synchronicity between the constituent parts of the union. But this conjecture has never been formally tested by comparing sample of monetary unions with a control sample of countries that do not belong to a monetary union. In this paper we take euro area data, US State macro data, Canadian provincial data and Australian state data — namely real Gross Domestic Product (GDP) growth, the GDP deflator growth and unemployment rate data — and use techniques relating to recurrence plots to measure the degree of synchronicity in dynamics over time using a dissimilarity measure. The results show that for the most part monetary unions are more synchronous than non-monetary unions, but that this is not always the case and particularly in the case of real GDP growth. Furthermore, Australia is by far the most synchronous monetary union in our sample.
  • Starck, Christian; Virén, Matti (1992)
    Bank of Finland Research Discussion Papers 25/1992
    This paper explores the determinants of aggregate economic fluctuations in Finland. The analysis makes use of aggregate monthly time series for some financial and non-financial variables. covering the period 1922-1990. In particular, we scrutinize the role of bankruptcies in the propagation mechanism of aggregate economic shocks. In analyzing the role of bankruptcies we also try to find out whether money or credit helps more in predicting the movements in corporate failures and overall economic activity. The empirical analyses indicate that bankruptcies constitute an important ingredient as regards the determination of other variables. It also tuI1J.s out that overall liquidity and firm failures are c10sely related. In comparing money and credit the former appears to be much more important as regards the .propagation mechanism. We also find that the basic relationships are strikingly stable over long periods. Finally, we find some evidence of non-linearities' in the financial and non-financial time series.
  • Nissilä, Wilma (2020)
    BoF Economics Review 7/2020
    This article surveys both earlier and recent research on recession forecasting with probit based time series models. Most studies use either a static probit model or its extensions in order to estimate the recession probabilities, while others use models based on a latent variable approach to account for nonlinearities. Many studies find that the term spread (i.e, the difference between long-term and short-term yields) is a useful predictor for recessions, but some recent studies also find that the ability of spread to predict recessions in the Euro Area has diminished over the years. Confidence indicators and financial variables such as stock returns seem to provide additional predictive power over the term spread. More sophisticated models outperform the basic static probit model in various studies. An empirical analysis made for Finland strengthens the findings of earlier studies. Consumer confidence is especially useful predictor of Finnish business cycle and the accuracy of the static single-predictor model can be improved by using multiple predictors and by allowing the dynamic extension.
  • Ambrocio, Gene (2020)
    Review of Economic Dynamics January
    Published in Bank of Finland DP 24/2015 http://urn.fi/URN:NBN:fi:bof-201511261453
    I provide a theory of information production and learning that can help account for both the excessive optimism that fueled booms preceding crises and the slow recoveries that followed. In my theory, persistence and the size of expectation errors depend on information production about changes in aggregate fundamentals. In turn information production, via credit screening, tends to fall during both very good and very bad times. The former gives rise to episodes of rational exuberance in which optimistic beliefs may sustain booms even as fundamentals decline. I also document evidence from survey forecasts consistent with the model predictions.
  • Bank of Finland (2013)
    Research Newsletter 1/2013
    Editorial: Origin of aggregate shocks: size matters 1 Securitization, low interest rates and business cycle fluctuations: a bumpy ride with the shadow banking system 2 Correlation in the business cycles of emerging and advanced economies 5 Events 7 Recent Bank of Finland research publications 8
  • Silvo, Aino; Verona, Fabio (2020)
    Bank of Finland Research Discussion Papers 9/2020
    In this paper we present Aino 3.0, the latest vintage of the dynamic stochastic general equilibrium (DSGE) model used at the Bank of Finland for policy analysis. Aino 3.0 is a small-open economy DSGE model at the intersection of the recent literatures on so-called TANK (“Two-Agent New Keynesian”) and MONK (“Mortgages in New Keynesian”) models. It aims at capturing the most relevant macro-financial linkages in the Finnish economy and provides a rich laboratory for the analysis of various macroeconomic and macroprudential policies. We show how the availability of a durable consumption good (housing), on the one hand, and the presence of credit-constrained households, on the other hand, affect the transmission of key macroeconomic and financial shocks. We also illustrate how these new transmission channels affect model dynamics compared to the previous model vintage (the Aino 2.0 model of Kilponen et al., 2016).
  • Crowley, Patrick M.; Hughes Hallett, Andrew (2019)
    Bank of Finland Research Discussion Papers 23/2019
    Understanding the relationship between national income GDP components is an essential part of macroeconomics. This study investigates quarterly real GDP component data for the U.S. and the U.K. and applies continuous wavelet analysis on cross comparisons of the data, from both within and between the two datasets. The results show that the cyclical interactions between consumption and investment are the most complex and most substantial at several different frequencies. The relationship of exports with other macroeconomic variables has also developed over time, likely due to the evolution of an international business cycle.
  • Brand, Thomas; Isoré, Marlène; Tripier, Fabien (2017)
    Bank of Finland Research Discussion Papers 34/2017
    Published in Journal of Economic Dynamics and Control 99 ; February ; 2019.
    We develop a business cycle model with gross flows of firm creation and destruction.The credit market is characterized by two frictions. First,entrepreneurs undergo a costly search for intermediate funding to create a firm. Second, upon a match, a costlystate-verification contract is set up. When defaults occurs, banks monitor firms, seize their assets, and a fraction of financial relationships are severed. The model is estimated using Bayesian methods for the U.S. economy. Among other shocks, uncertainty in productivity turns out to be a major contributor to both macro-financial aggregates and firm dynamics.
  • Kerola, Eeva; Mojon, Benoît (2021)
    BOFIT Discussion Papers 1/2021
    Data available at https://www.bofit.fi/en/monitoring/statistics/china-statistics/
    It is important to understand the growth process under way in China. However, analyses of Chinese growth became increasingly more difficult after the real GDP doubling target was announced in 2012 and the official real GDP statistics lost their fluctuations. With a dataset covering 31 Chinese provinces from two decades, we have substantially more variation to work with. We find robust evidence that the richness of the provincial data provides information relevant to understand and project Chinese aggregates. Using this provincial data, we build an alternative indicator for Chinese growth that is able to reveal fluctuations not present in the official statistical series. Additionally, we concentrate on the determinants of Chinese growth and show how the drivers have gone through a substantial change over time both across economic variables and provinces. We introduce a method to understand the changing nature of Chinese growth that can be updated regularly using principal components derived from the provincial data.