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Understanding inflation dynamics in the Euro Area: deviants and commonalities across member countries

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Abstract

Central to this paper is the analysis of inflation dynamics in the Euro Area as well as in eleven individual Euro Area member countries between 1990 and 2012. Based on the hybrid new Keynesian Phillips curve, the analyses include survey measures from Consensus Economics to compare inflation dynamics across Euro Area member countries. Particular focus is set on the choice of suitable measures of real marginal cost. In addition to the well-known output gap, the role of finance-neutral output gaps and unemployment gaps is examined. Throughout the analyses, price setting is found to be largely backward-looking, but with a decreasing trend over time. Countries’ varying sensitivity to the different measures of real marginal cost is highlighted, which may indicate persistent heterogeneity in Euro Area inflation dynamics. With the onset of the financial crisis, finance-neutral output gaps outperform alternative measures of real marginal cost.

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Notes

  1. EA data is calculated as the weighted average of EA11 countries based on quarterly Gross Domestic Product (GDP) weights; in the case of GDP and credit data, sums of absolute values are included.

  2. Forecast errors are determined as mean absolute percentage errors (MAPE) and found to be smaller than 20 basis points in the majority of countries. Thus, forecasts are considered overall unbiased. The fact that forecasters themselves (among them Consensus Economics forecasters) rely on Phillips curve relationships when forming expectations on macroeconomic variables (Fendel et al. 2011) is considered a further viable justification for using Consensus Economics inflation forecasts.

  3. An exception to the broad literature supporting survey measures of inflation expectations has been Nunes (2010) who finds the weight of rational expectations to be comparably higher and concludes that survey expectations do not correspond to ‘true’ inflation expectations.

  4. A detailed description of variables and data sources is provided in the “Appendix 1”. Given the varying availability of data for EA countries, time series are slightly shorter in some cases, which is indicated in Tables 1, 2, 3, 4 and 5.

  5. HAC weight matrix using Bartlett (Newey-West) kernel with a lag length of four is chosen here.

  6. Following Borio et al. (2007), the trade-weighted output gap takes into account the share of EA10 related imports relative to total imports of one country in the respective quarter. The weight is calculated based on information of the IMF Direction of Trade Database.

  7. Correlations between the output gap and the EA-weighted output gap are >0.99 in all EA-countries. A detailed description of trade weight derivations and estimation results are available upon request.

  8. Testing for the inflationary pressure of real effective exchange rates in a similar set-up to that of oil prices does, nonetheless, not yield significant insights into the inflation formation process. Both results are available upon request.

  9. Testing for weak instruments indicates that the hypothesis of weak instruments can be rejected only at the >10 % confidence interval for the following countries: Austria, Finland, France, and Ireland.

  10. Estimation results are not reported separately, but are available upon request.

  11. Despite technical disadvantages of the HP filter compared to other filtering methods, e.g. band-pass filters, it is preferred due to the possibility of estimating it in state space form.

  12. In line with the traditional HP filter, \(\lambda \) is set to 1600, determined by the error variances of the respective state and observation equation. In order to ensure that implicit business cycle frequencies correspond to those of the standard HP filter in the baseline specification, \(\lambda \) is set in line with Borio et al. (2014). Particular attention is paid to \(\beta \), as values close to one would estimate unit root output gaps, but, with the exception of the EA aggregate, values never approach the upper limit of 0.95.

  13. Various additional variables may be included to represent the financial cycle, among them measures of credit quality and spreads, financial firm indicators as well as leverage and liquidity. With respect to limited availability of data for EA11 countries, preference is given to the estimation of finance-neutral output gaps for all EA11 countries, accepting a smaller set of financial cycle variables.

  14. Due to partially short time series for residential property prices, this time series has been excluded from the observation equation when the number of observations was reduced extensively. Table 3 indicates where this is the case.

  15. As the post-2007 data sample is still rather small, analyses are expected to be more informative as longer time series become available.

  16. Testing for a break in 1999 (2001 in the case of Greece) in response to the changeover to the Euro indicates a decrease in \(\gamma _b\) in the majority of countries. No systematic differences are, nonetheless, observed for the role of the output gap.

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Authors and Affiliations

  1. Department of Economics, WHU – Otto Beisheim School of Management, Vallendar, Germany

    Johanna Amberger & Ralf Fendel

Authors
  1. Johanna Amberger
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  2. Ralf Fendel
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Corresponding author

Correspondence to Ralf Fendel.

Appendices

Appendix 1: Variables and data sources

Variable

Source

Comment

Time span

HICP: Inflation Year-over-year (yoy) change harmonized index of consumer prices (HICP) in %

Eurostat OECD

HICP inflation (Eurostat), beginning of 1990s complemented with CPI inflation (OECD)

Q1 1990-Q4 2012

CHICP: Core inflation yoy change CHICP in %

Eurostat OECD

CHICP inflation (Eurostat), before 1997 complemented with core CPI inflation (OECD)

Q1 1990-Q4 2012

IFC: Inflation expectations Survey measure of expected inflation for the current and coming year

Consensus Economics

Quarterly data based on monthly forecasts for current and coming year

Q1 1990-Q4 2012

GAP: Output gap Deviation of GDP from HP filtered GDP in % of HP filtered GDP

Eurostat AMECO

Real GDP in mEUR seasonally adjusted and adj. by working days

Q1 1979-Q4 2012

FNGAP: Finance-neutral output gap (1) log real credit to the private non-financial sector in bnEUR (2) log real residential property price index

OECD

Both time series are demeaned using Cesàro means

Q1 1990-Q4 2012

UGAP: Unemployment gap Deviation of the harmonized unemployment rate from its structural level

OECD

Annual NAIRU estimates (OECD) for four quarters of the respective year

Q1 1990-Q4 2012

OIL: Oil price Crude oil, Brent in EUR yoy growth in %

Thomson Reuters Ecowin

Quarterly oil price corresponds to three-month averages

Q1 1990-Q4 2012

NULC: Nominal unit labour cost yoy change in NULC in %

Eurostat AMECO

Seasonally adjusted and adj. by working days (Eurostat), complemented with AMECO data

Q1 1990-Q4 2012

RULC: Real unit labor cost yoy change in RULC in %

Eurostat AMECO

Seasonally adjusted and adj. by working days (Eurostat), complemented with AMECO data

Q1 1990-Q4 2012

I3M: Short-term interest rate 3-month Euribor/3-month money market rates in %

Eurostat

3-month money market rates before 1999

Q1 1990-Q4 2012

I10Y: Long-term interest rate 10-year government bond interest rates

Eurostat

EMU convergence criterion bond yields

Q1 1990-Q4 2012

SPREAD: Interest rate spread Difference between long- and short-term interest rates

own calculations

–

Q1 1990- Q4 2012

REERL/REERC: Real effective exchange rate Index (level values) or yoy growth in %

BIS

Index values or yoy growth included depending on correlation statistics

Q1 1990-Q4 2012

CAPAL/CAPAC: Capacity utilization Share of total in % or yoy growth in %

European Commission

Business and Consumer Survey, question #13; index values or yoy growth included depending on correlation statistics

Q1 1990-Q4 2012

Appendix 2: Baseline specification rolling regression estimation results

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Amberger, J., Fendel, R. Understanding inflation dynamics in the Euro Area: deviants and commonalities across member countries. Empirica 44, 261–293 (2017). https://doi.org/10.1007/s10663-016-9322-x

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