Abstract
A macroeconomic model that explicitly incorporates financial sector influences is estimated. A survey of lending standards in the Eurozone countries is informative about aggregate economic activity. I also ask whether policy rate shocks influence lending standards, and whether these standards also have an effect on monetary policy. Briefly, the paper finds that inclusion of indicators of financial frictions in standard macromodels is essentials. Some of the results also suggest that in 2011–2012, the European Central Bank made financial conditions worse by not only raising the policy rate but by implementing a very gradual reduction in monetary conditions over the next 2 years.
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Notes
Indeed, data from only a very few so-called periphery countries are available making it impractical to perform a proper test of differences between the two groups of economies.
This is not to suggest that other elements are not present or potentially important. However, surveys of the kind used in the empirical work to follow are one of the few available reliable quantitative indicators of credit conditions.
‘Within our mandate, the ECB is ready to do whatever it takes to preserve the euro. And believe me, it will be enough’, Extract from remarks Draghi made in London, 26 July 2012. See http://www.ecb.europa.eu/press/key/date/2012/html/sp120726.en.html.
This is the policy whereby the ECB undertakes to purchase, in secondary markets, the sovereign debt of Eurozone member states, provided they meet strict conditions. See the press release at http://www.ecb.europa.eu/press/pr/date/2012/html/pr120906_1.en.html.
A recent strand of the literature takes the position that the connection between lending practices and credit conditions should be investigated with bank level data. More disaggregated data are certainly useful to understand the myriad non-price factors that can impact credit conditions as well as the effects of micro-prudential standards on bank behavior. However, central banks set monetary policy on the basis of forward-looking views of aggregate economic outcomes. Also, the global financial crisis raised the profile of macro-prudential attempts to influence credit conditions. Understanding the impact of these types of policies require a macro perspective on the state of credit conditions.
In the foregoing expressions we exclude other exogenous variables. These can easily be added without jeopardizing the thrust of the discussion so far.
The long-term interest rate in the euro zone economies less the Euribor (3 month euro interbank offer rate) is used to measure the term spread. The latter series are widely used short-term interest rate indicators for the euro zone.
The ECB does publish commodity price series of various kinds for a shorter sample. The behavior of their series is not out of line with the WTI series.
The US data referred to below is also from FRED II. See also Siklos and Lavender (2015) for additional details.
As loan officers must revise their views in real-time, an assessment of credit standards relying on real-time data may well provide a different interpretation of the role of non-price elements in lending than would be obtained if revised data are used. Again, as the ECB makes available vintages of data (http://sdw.ecb.europa.eu/browse.do?node=9484612) we could investigate the real time role of the bank lending surveys. Space limitations prevent further analysis along this line. See, however, Siklos and Lavender (2015) for an example relying on the United States and Canadian data.
Although, the restriction of a single principal component is imposed separate estimation which asks how many principal components exists, using maximum likelihood estimation, yields the same answer.
Siklos (2014) investigates the implications of these differences in greater detail.
Cyprus only serves to illustrate the potential of the BLS to reveal underlying credit conditions. As the data are only available since 2009 they were not included in the econometric estimates reported below.
It is not too difficult to find examples where policy makers in Europe underestimated the internal difficulties that would eventually erupt in 2010. For example, from a speech by Jürgen Stark in 2008 celebrating the first 10 years of the euro: ‘In these demanding times, some widely-recognized core principles have helped the ECB to weather the storm. … The ECB has demonstrated its ability to act even under extraordinary circumstances – without compromising its price stability mandate. This has strengthened the ECB’s credibility.’ See http://www.ecb.europa.eu/press/key/date/2008/html/sp081114_1.en.html.
There are potentially 36 such impulse response functions since the estimated VAR contains six series.
In VAR analysis these confidence bands are pseudo standard errors. The ones plotted are generated from an analytical expression for an approximation of a 95% confidence interval.
When the observed policy rate is replace by the shadow rate the results (not shown) as virtually identical.
Recall that a rise in the financial factor is equivalent to a deterioration in financial conditions.
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Siklos, P. Macroeconomic Implications of Financial Frictions in the Euro Zone. Comp Econ Stud 57, 222–242 (2015). https://doi.org/10.1057/ces.2015.16
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DOI: https://doi.org/10.1057/ces.2015.16