The effect on the Swedish real economy of the financial crisis

Abstract

This article investigates the effects of the financial crisis on the Swedish real economy. In order to do this, an index which describes the financial conditions of the Swedish economy is developed. The index indicates that domestic Swedish financial conditions have deteriorated substantially during 2008 and are now at the highest level since the crisis of the early 1990s. A Bayesian Vector Autoregression (BVAR) model with both US and Swedish variables is used to assess the quantitative effects of the financial crisis on Swedish real Gross Domestic Product (GDP) growth. Results suggest that the growth of the Swedish economy will be substantially slower in the next couple of years due to the financial crisis.

Acknowledgements

I am grateful to Anders Bergvall, Henrik Braconier, Kristian Jönsson and seminar participants at the Ministry of Finance and the National Institute of Economic Research for valuable comments.

Notes

¹ We use used inflation rather than inflation expectations to calculate the real interest rate because the latter can be motivated by agents having backward looking expectations.

² The risk appetite aspect of the short interbank spread can also be seen by recalling that it includes flight-to-quality effects.

³ Other variables–such as implied volatilities, corporate bond spreads, Credit Default Swap (CDS) spreads or expected default frequencies–could obviously also be of interest, but long enough time series are not available for Swedish data. No measure of credit conditions–similar to, for example, the Federal Reserve's ‘Senior loan officer opinion survey on bank lending practices’–is available either.

⁴ The three variables are accordingly considered equally important for describing the financial conditions. This approach can be contrasted with, for example, Guichard and Turner (2008) who base the weight a variable receives on the relative effect it has on GDP after four to six quarters. We prefer to first build the index and then investigate its effects on the real economy.

⁵ The high-yield bond spread is sometimes interpreted as reflecting risk appetite–see, for example, Levy Yeyati and González Rozada (2005) and Österholm and Zettelmeyer (2008)–and is here seen as a ‘sufficient statistic’ for the US part of the financial crisis. No equivalent series is available for Sweden and we accordingly use the slightly wider measure that the financial index constitutes. The high-yield bond spread should also be a good variable for modelling the US block of the BVAR as it has been shown to have predictive power for the US real economy (see, e.g. Mody and Taylor, 2003).

⁶ The business cycle indicator is based on a dynamic factor model used for GDP growth forecasting (see Hansson et al., 2005 for details).

⁷ See, for example, Tierny (1994) for a technical discussion.

⁸ The difference between the unconditional and conditional forecasts is that in the unconditional case, the entire vector generated randomly at each horizon. In the conditional case, only the orthogonal shocks belonging to the US and Swedish GDP growth, household confidence and the business cycle indicator are created randomly. The shocks of the high-yield bond spread and the financial index are implied by the assumed conditioning paths. For a given set of randomly generated orthogonal shocks of the variables that have not been conditioned upon and a given path of the conditioning variables, the implicit shocks of the conditioning variables and the forecasts for all variables are generated sequentially, one horizon at a time.

⁹ See, for example, International Monetary Fund (IMF, 2008).