## _wp0821 - Appendix II. Data Definitions and Series

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---

### Introduction and Research Questions
- Objective: Assess whether the eight Central and Eastern European countries that acceded to the EU in 2004 (EU8) can achieve sufficiently low inflation to satisfy the Maastricht inflation criterion and adopt the euro.
- Premise: Headline inflation is decomposed into a common-origin component (shocks affecting all EU25 countries) and an idiosyncratic component (country-specific).
- Focus:
  - Extract common-origin inflation for the 25 pre-2007 EU members (EU25).
  - Explain cross-country differences in common-origin inflation using structural, macroeconomic, and institutional indicators.
  - Assess the effect of idiosyncratic inflation on the Maastricht reference rate and on the selection of countries that determine the criterion.

### Methodology: GDFM Approach
- Model: Generalized dynamic factor model (GDFM) following Forni and others (1999) and Forni and Lippi (2001).
- Key model structure:
  - Each observed series x_jt = χ_jt + ζ_jt.
  - χ_jt is driven by q common factors μ_ht with finite moving-average representation b_j(L) μ_t.
  - ζ_jt is an idiosyncratic disturbance orthogonal to common shocks.
- Advantages:
  - Accommodates very large cross-section/time-series datasets and uses nonprice as well as price series to reveal common demand-and-supply shocks.
  - Produces a common-origin inflation measure analogous to a core inflation cleaned of idiosyncratic shocks.
- Factor selection and estimation details:
  - Spectral PCA chosen q = two principal components.
  - Rationale: two principal components explain 40 percent of data variability at the policy-relevant frequency of 1½ years, rising to 50 percent in the long run.
  - Threshold for identifying common shocks set at 40 percent.
  - Bai and Ng (2002) panel algorithm selects 16 static factors.
  - Implied lags of the dynamic common factors: seven.

### Data: composition, frequency, transformations
- Data set size and composition (exact counts):
  - Total variables: 3,344.
  - HICP series: 2,259.
  - PPI series: 497.
  - Industrial production: 533.
  - Long-term nominal interest rate: 24.
  - Short-term nominal interest rate: 13.
  - M1: 10.
  - Nominal effective exchange rate: 23.
  - Oil price: 1.
  - Unemployment rate: 21.
  - Growth rate of credit to private sector: 22.
  - Nominal effective exchange rate of euro: 1.
- Frequency and sample:
  - Monthly data.
  - Main sample period for EU25: January 2001 to December 2005.
  - Longer sample for EU15: January 1996 to December 2005 (where available).
- Transformations and preprocessing:
  - Seasonal adjustment (EViews’ X12) for all variables except interest rates and unemployment rates (which remain in percent).
  - Log-differencing for stationarity (except interest and unemployment).
  - Standardization by subtracting means and dividing by standard deviations.

### Results — Common-Origin Inflation Properties and Cross-Country Levels (2001–2005 averages)
- Decomposition behavior:
  - Common-origin inflation tracks broad trends in headline inflation but smooths cross-section and high-frequency noise.
  - Long-term common-origin inflation excludes components with periodicities of less than one year for further smoothing.
- Share of inflation variability explained by common shocks:
  - Average across EU25: a little under 40 percent of headline inflation variability is attributable to common shocks.
  - Country extremes:
    - Netherlands: more than 80 percent of headline inflation variability is explained by common shocks.
    - Czech Republic and Slovak Republic: little more than one-tenth of inflation variability is attributable to common shocks.
  - By groups:
    - Contribution of common factors to inflation variability is about equal (around 35 percent) in the EU15 and the Baltics.
    - Considerably lower in the five Central European countries (CEE5), pulled down by Poland and the Czech and Slovak Republics.
- Trade openness relation:
  - The impact of common shocks on inflation variability is stronger in more open economies, especially for tradable goods inflation.
- Cross-country common-origin inflation (2001–2005 averages, year-on-year, in percent; numbers preserved exactly):
  - Czech Republic: Common-origin inflation 1.6; Long-term common-origin inflation 1.6; Headline inflation 1.4
  - Hungary: Common-origin inflation 5.1; Long-term common-origin inflation 5.1; Headline inflation 5.1
  - Poland: Common-origin inflation 2.1; Long-term common-origin inflation 2.1; Headline inflation 2.1
  - Slovak Republic: Common-origin inflation 5.7; Long-term common-origin inflation 5.7; Headline inflation 5.6
  - Slovenia: Common-origin inflation 4.9; Long-term common-origin inflation 4.8; Headline inflation 4.9
  - Estonia: Common-origin inflation 3.3; Long-term common-origin inflation 3.2; Headline inflation 3.1
  - Latvia: Common-origin inflation 4.4; Long-term common-origin inflation 4.4; Headline inflation 4.5
  - Lithuania: Common-origin inflation 1.0; Long-term common-origin inflation 0.9; Headline inflation 0.8
  - Baltic average: Common-origin inflation 2.92; Long-term common-origin inflation 2.92; Headline inflation 2.8
  - CEE5 average: Common-origin inflation 3.93; Long-term common-origin inflation 3.93; Headline inflation 3.8
  - EU8 average: Common-origin inflation 3.53; Long-term common-origin inflation 3.53; Headline inflation 3.4
  - EU15 average: Common-origin inflation 2.32; Long-term common-origin inflation 2.32; Headline inflation 2.3
  - Selected EU15 members:
    - Austria: Common-origin inflation 1.6; Headline inflation 1.8
    - Germany: Common-origin inflation 1.5; Headline inflation 1.5
    - Spain: Common-origin inflation 3.2; Headline inflation 3.3
    - Ireland: Common-origin inflation 3.0; Headline inflation 3.3
- Interpretation:
  - During 2001–05, average common-origin inflation in the EU15 was 2.32 percent, compared with 3.53 percent in the EU8 and 2.92 percent in the Baltics.

### Determinants of Cross-Country Common-Origin Inflation
- Estimation approach:
  - Cross-section regressions of country-level common-origin inflation on relative development, macroeconomic, institutional, and political variables.
  - Variables defined relative to EU-average benchmarks.
  - Some regressions use a sample restricted to 22 countries due to missing institutional indicators for Cyprus, Luxembourg, and Malta.
- Regressors considered (as defined in Appendix II):
  - Development/macro: initial relative price level (measured as of 2001), change in the nominal effective exchange rate, size of government, trade openness.
  - Institutional: unionization coverage, quality of the legal system, restrictiveness of labor and product market regulations, political stability.
- Main empirical findings (summary):
  - Initial price level and nominal effective exchange rate behavior are important macroeconomic determinants of common-origin inflation differentials.
  - Institutional quality matters: labor market flexibility and legal system effectiveness account for a sizable amount of cross-country heterogeneity in common-origin inflation.
  - Trade openness increases the share of inflation variability explained by common shocks.

### Idiosyncratic Inflation and Maastricht Criterion Implications
- Properties of idiosyncratic inflation:
  - Country-specific inflations typically modest but occasionally substantial; during 2001–05, country-specific inflations lay within +/− 3.5 percent for the 25 countries; for the EU15 the range was [−3.1, +2.8 percent].
  - Among the EU8, idiosyncratic inflation closely tracked contributions from changes in regulated prices and indirect taxes, indicating policy-induced price changes are an important source of own price shocks.
- Effects on the Maastricht inflation criterion:
  - Negative idiosyncratic shocks in low-headline-inflation countries lowered the calculated level of the Maastricht reference inflation rate (recently on the order of 0.2 percentage point, but reached ½ percentage point at times during 2003-05).
  - Country selection bias: countries selected to set the criterion based on headline inflation can differ from those with the lowest common-origin inflation; selection has typically been influenced by negative idiosyncratic shocks.
  - Historical example: Greece’s qualification for euro adoption (March 2000) hinged on a sizable negative idiosyncratic shock—the difference between headline and common-origin inflations was about 1½ percentage points—attributable to indirect tax cuts, limited administered price adjustments, and informal agreements to cap price increases.
- Near-term factors and risks:
  - Introduction of lower value-added tax rates on services in a number of EU countries could exacerbate the criterion’s downward bias.
  - In the EU8, harmonization of indirect taxes and increases in some domestic energy prices (e.g., convergence of domestic natural gas prices to world levels) could produce positive own idiosyncratic shocks that push up headline inflation.
- Policy stance on idiosyncratic component:
  - Eliminating the idiosyncratic component from inflation assessments is not appropriate because it would ignore business-cycle differences that are not fully synchronized within the EU.

### Persistence, Policy Constraints, and Specific Implications for the EU8
- Persistence and adjustment:
  - High inertia in common-origin inflation differentials within the EU because important regressors are structural or institutional and evolve slowly or require extended implementation time to change.
  - Institutional de jure changes can occur in the short run, but payoffs in economic flexibility and legal certainty depend on implementation and may take considerable time to materialize.
- Price level gaps and near-term prospects for EU8:
  - Price level gaps are among the most important explanations of inflation divergence for the EU8 (excluding Slovenia), pushing up common-origin inflation by 1-2 percentage points relative to the EU average and exhausting the 1½ percentage point Maastricht buffer.
  - Institutional underpinnings for low inflation are generally present in several EU8 countries: EU8 (excluding the Baltics and Slovenia) score highly or very highly on a combined measure of labor market flexibility and legal system quality, often outranking many current euro members.
  - Near-term risks: relative underdevelopment and negative price gaps imply ceteris paribus higher common-origin inflation in non-euro EU8 countries; institutional improvements take time, so EU8 may need to rely on sizable negative idiosyncratic inflation shocks to reduce headline inflation to Maastricht levels in the near term.

### Appendix II — Variable definitions (selected)
- Dependent variable:
  - Average inflation iπx = Average over all months Jan 2002-Dec 2005 of log(common-origin inflation indext) - log(common-origin inflation indext-12). Common-origin inflation index assumes two common factors. Redefined as deviation from the mean by calculating x – sample mean.
- Independent variables (examples, with construction notes preserved):
  - Relative price level: Logarithm of relative price level in 2001, centered around sample mean of 0.
  - Nominal effective appreciation: Average over all months Jan 2002-Dec 2005 of log(nominal effective exchange ratet) nominal effective exchange ratet-12). NEER assumes 41 partner countries. Source: Eurostat. Redefined as deviation from the mean by calculating x – sample mean.
  - Average trade openness: Average exports and imports 2002-2005 in percent of average GDP 2002-05, centered around sample mean of 0.
  - Labor market flexibility: First principal component of 9 labor variables from Fraser Institute (F) and World Bank Doing Business (W). Higher index = greater flexibility. Principal component centered at zero; redefined to be positive with a minimum of 0 by calculating x + minimum(x); redefined as sample mean=1 by calculating x / mean(x).
  - Product market flexibility: First principal component of 9 competition variables from Fraser Institute (F) and World Bank Doing Business (W). Higher index = greater flexibility. Principal component centered at zero; redefined to be positive with a minimum of 0 by calculating x + minimum(x); redefined as sample mean=1 by calculating x / mean(x).
  - Legal quality: First principal component of 10 legal variables from Fraser Institute (F) and World Bank Doing Business (W). Higher index = better rule of law. Principal component centered at zero; redefined to be positive with a minimum of 0 by calculating x + minimum(x); redefined as sample mean=1 by calculating x / mean(x).
  - Political instability (CNTS): First principal component of 3 measures from the Cross-National Time Series Database (average executive, cabinet, legislative changes 1999-2003). Higher index = higher instability. Centered at zero; redefined to be positive with a minimum of 0 by calculating x + minimum(x); redefined as sample mean=1 by calculating x / mean(x).
  - Political stability (Kaufmann-Kray): Average 2002-2005. Redefined to be positive with a minimum of 0 by calculating x + minimum(x); then redefined as sample mean=1 by calculating x / mean(x).

- Key quantitative points (preserved exactly):
  - Data set: 3,344 variables (total).
  - HICP series: 2,259.
  - PCA choice: two principal components explain 40 percent of data variability at the 1½-year frequency, rising to 50 percent in the long run.
  - Static factors chosen: 16; implied lags of dynamic factors: seven.
  - Average share of headline inflation variability due to common shocks across EU25: a little under 40 percent.
  - Group averages of common-origin inflation (2001–2005):
    - EU15 average: 2.32 (common-origin inflation).
    - EU8 average: 3.53 (common-origin inflation).
    - Baltic average: 2.92 (common-origin inflation).
    - CEE5 average: 3.93 (common-origin inflation).

*Source: Appendix II. Data Definitions and Series (content unit: _wp0821 — IMF staff estimates and analysis as presented in the provided excerpt).*

### References..............................................................................................................

### _wp0821 - References............................................................................................................................... 32

### References
- Page: 32

### Appendix I.  Implementing the GDFM
- Page: 37

*Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2008/_wp0821.pdf*

### Appendix II. Data Definitions and Series ...............................................................................

### Appendix II. Data Definitions and Series

### Introduction and Research Questions
- Objective: Assess whether the eight Central and Eastern European countries that acceded to the EU in 2004 (EU8) can achieve sufficiently low inflation to satisfy the Maastricht inflation criterion and adopt the euro.
- Premise: Headline inflation is decomposed into a common-origin component (shocks affecting all EU25 countries) and an idiosyncratic component (country-specific).
- Focus: (i) extract common-origin inflation for the 25 pre-2007 EU members (EU25); (ii) explain cross-country differences in common-origin inflation using structural, macroeconomic, and institutional indicators; (iii) assess the effect of idiosyncratic inflation on the Maastricht reference rate and on the selection of countries that determine the criterion.

### Methodology: GDFM Approach
- Model: Generalized dynamic factor model (GDFM) following Forni and others (1999) and Forni and Lippi (2001).
- Key model structure:
  - Each observed series x_jt = χ_jt + ζ_jt.
  - χ_jt is driven by q common factors μ_ht with finite moving-average representation b_j(L) μ_t.
  - ζ_jt is an idiosyncratic disturbance orthogonal to common shocks.
- Advantages:
  - Accommodates very large cross-section/time-series datasets and uses nonprice as well as price series to reveal common demand-and-supply shocks.
  - Produces a common-origin inflation measure analogous to a core inflation cleaned of idiosyncratic shocks.

### Data
- Data set size and composition:
  - About 3,400 time series used overall (text uses “about 3,400”); precise count used in implementation: 3,344 variables.
  - HICP series: 2,259.
  - PPI series: 497.
  - Industrial production: 533.
  - Long-term nominal interest rate: 24.
  - Short-term nominal interest rate: 13.
  - M1: 10.
  - Nominal effective exchange rate: 23.
  - Oil price: 1.
  - Unemployment rate: 21.
  - Growth rate of credit to private sector: 22.
  - Nominal effective exchange rate of euro: 1.
  - Total: 3,344.
- Frequency and sample:
  - Monthly data.
  - Main sample period for EU25: January 2001 to December 2005.
  - Longer sample for EU15: January 1996 to December 2005 (where available).
- Transformations:
  - Seasonal adjustment (EViews’ X12) for all variables except interest rates and unemployment rates (which remain in percent).
  - Log-differencing for stationarity (except interest and unemployment).
  - Standardization by subtracting means and dividing by standard deviations.

### Factor Selection and Estimation Details
- Spectral PCA findings:
  - Two principal components chosen as dynamic common factors.
  - Rationale: first two principal components explain 40 percent of data variability at the policy-relevant frequency of 1½ years, rising to 50 percent in the long run.
  - Threshold chosen for identifying common shocks: 40 percent (somewhat lower than 50 percent used in other studies to avoid high-frequency noise).
- Static factors and lag structure:
  - Bai and Ng (2002) panel algorithm selects 16 static factors.
  - Together with two dynamic common shocks, this implies seven lags of the dynamic common factors are used in the moving-average representation.

### Results — Common-Origin Inflation Properties
- Decomposition behavior:
  - Common-origin inflation tracks broad trends in headline inflation but smooths cross-section and high-frequency noise.
  - Long-term common-origin inflation excludes components with periodicities of less than one year for further smoothing.
- Share of inflation variability explained by common shocks:
  - Average across EU25: a little under 40 percent of headline inflation variability is attributable to common shocks.
  - Country extremes:
    - More than 80 percent of headline inflation variability is explained by common shocks in the Netherlands.
    - Little more than one-tenth of inflation variability is attributable to common shocks in the Czech Republic and the Slovak Republic.
  - By groups:
    - Contribution of common factors to inflation variability is about equal (around 35 percent) in the EU15 and the Baltics.
    - Considerably lower in the five Central European countries (CEE5), pulled down by Poland and the Czech and Slovak Republics.
- Trade openness relation:
  - The impact of common shocks on inflation variability is stronger in more open economies.
  - Effect is especially pronounced for tradable goods inflation.
  - For the most open economies, the trend line is steeper, indicating stronger propagation of common shocks via trade.

### Cross-Country Levels of Common-Origin Inflation (2001–2005 averages)
- Selected country and group averages (year-on-year, in percent; averages over 2001–2005 as reported in Table 2):
  - Czech Republic: Common-origin inflation 1.6; Long-term common-origin inflation 1.6; Headline inflation 1.4
  - Hungary: Common-origin inflation 5.1; Long-term common-origin inflation 5.1; Headline inflation 5.1
  - Poland: Common-origin inflation 2.1; Long-term common-origin inflation 2.1; Headline inflation 2.1
  - Slovak Republic: Common-origin inflation 5.7; Long-term common-origin inflation 5.7; Headline inflation 5.6
  - Slovenia: Common-origin inflation 4.9; Long-term common-origin inflation 4.8; Headline inflation 4.9
  - Estonia: Common-origin inflation 3.3; Long-term common-origin inflation 3.2; Headline inflation 3.1
  - Latvia: Common-origin inflation 4.4; Long-term common-origin inflation 4.4; Headline inflation 4.5
  - Lithuania: Common-origin inflation 1.0; Long-term common-origin inflation 0.9; Headline inflation 0.8
  - Baltic average: Common-origin inflation 2.92; Long-term common-origin inflation 2.92; Headline inflation 2.8
  - CEE5 average: Common-origin inflation 3.93; Long-term common-origin inflation 3.93; Headline inflation 3.8
  - EU8 average: Common-origin inflation 3.53; Long-term common-origin inflation 3.53; Headline inflation 3.4
  - EU15 average: Common-origin inflation 2.32; Long-term common-origin inflation 2.32; Headline inflation 2.3
  - Selected EU15 members (examples):
    - Austria: Common-origin inflation 1.6; Headline inflation 1.8
    - Germany: Common-origin inflation 1.5; Headline inflation 1.5
    - Spain: Common-origin inflation 3.2; Headline inflation 3.3
    - Ireland: Common-origin inflation 3.0; Headline inflation 3.3
- Interpretation:
  - During 2001–05, average common-origin inflation in the EU15 was 2.32 percent, compared with 3.53 percent in the EU8 and 2.92 percent in the Baltics.
  - Income and price convergence, differing HICP weights, and variation in how common shocks load on national series explain cross-country differences.

### Determinants of Cross-Country Common-Origin Inflation
- Estimation approach:
  - Cross-section regressions of country-level common-origin inflation on relative development, macroeconomic, institutional, and political variables.
  - Variables defined relative to EU-average benchmarks.
  - Sample restricted to 22 countries in some regressions due to missing institutional indicators for Cyprus, Luxembourg, and Malta.
- Regressors considered:
  - Development/macro: initial relative price level (measured as of 2001), change in the nominal effective exchange rate, size of government, trade openness.
  - Institutional: unionization coverage, quality of the legal system, restrictiveness of labor and product market regulations, political stability.
- Main empirical findings (summary):
  - Initial price level and nominal effective exchange rate behavior are important macroeconomic determinants of common-origin inflation differentials.
  - Institutional quality matters: labor market flexibility and legal system effectiveness account for a sizable amount of cross-country heterogeneity in common-origin inflation.
  - Trade openness increases the share of inflation variability explained by common shocks.

### Idiosyncratic Inflation and Maastricht Criterion Implications
- Idiosyncratic inflation effects:
  - At times sizable idiosyncratic inflation has lowered the Maastricht inflation criterion through a selection bias: countries with the lowest headline inflation are systematically found to have had negative idiosyncratic shocks that qualified them as low-inflation countries.
  - A favorable country-specific shock enabled one current euro member to pass the inflation hurdle when qualifying for euro adoption.
- Convergence outlook:
  - Inertial convergence processes could keep inflation differences elevated for several more years among non-euro EU8 members.
  - High institutional quality can help offset elevated differences by promoting flexible responses to shocks.

### Key Quantitative Points (preserved exactly as in source)
- Data set: 3,344 variables (total).
- HICP series: 2,259.
- PCA choice: two principal components explain 40 percent of data variability at the 1½-year frequency, rising to 50 percent in the long run.
- Static factors chosen: 16; implied lags of dynamic factors: seven.
- Average share of headline inflation variability due to common shocks across EU25: a little under 40 percent.
- Country/group averages of common-origin inflation (2001–2005) include:
  - EU15 average: 2.32 (common-origin inflation).
  - EU8 average: 3.53 (common-origin inflation).
  - Baltic average: 2.92 (common-origin inflation).
  - CEE5 average: 3.93 (common-origin inflation).

*Source: Appendix II. Data Definitions and Series (content unit: _wp0821 - Appendix II. Data Definitions and Series) — IMF staff estimates and analysis as presented in the provided excerpt.*

### conclusions.

### _wp0821 - conclusions

### Empirical decomposition and methodology
- Applied a GDFM to partition observed inflation in the EU25 into common-origin and idiosyncratic components.
- Common-origin inflation interpreted as headline inflation removed of country- and sector-specific factors.
- Inclusion of all 25 countries justified by finding that common shocks account for a similar proportion of observed inflation variability in the EU8 and the EU15.
- The share of inflation variability attributed to common shocks is higher in more open economies (as measured by trade openness with the EU), implying foreign trade is an important channel for propagating price pressures.

### Determinants of cross-country differences in common-origin inflation
- Initial relative price level (log function) is significantly negatively correlated with differences in common-origin inflation across the EU:
  - Countries with initial prices below (above) the EU average will experience higher- (lower-) than-average inflation rates.
  - Negative price gaps have a proportionately larger effect on inflation differentials than positive price gaps.
  - Relative underdevelopment (negative price level gap) raises common-origin inflation in non-euro EU8 countries by about 1-2 percentage points relative to the EU average; in the Slovak Republic the effect exceeded 2¼ percentage points.
  - Relative price levels changed in absolute terms only by a cumulative 3 percentage points on average during 2002-05.
- Nominal effective exchange rate changes:
  - Negative coefficient: more rapid nominal effective depreciation than the EU average ceteris paribus leads to inflation in excess of the group average.
  - Nominal effective appreciations produced the largest negative contributions in Lithuania (owing to litas peg to the US dollar and a strengthening U.S. dollar against the euro).
  - Nominal effective depreciations added more than 1¼ percentage points to common-origin inflation differentials in Hungary and Slovenia.
- Institutional and flexibility factors:
  - More flexible labor market institutions (higher index value = greater flexibility) are associated with smaller inflation differentials.
  - Legal system quality (higher value = better rule of law) is significant when interacted with labor market flexibility: an efficient and independent legal system can mitigate the adverse inflationary impact of labor market rigidities.
  - Rigid labor markets raised inflation differentials by 1 percentage point or more in Slovenia, Portugal, Greece, Spain, and France.
  - Very flexible labor markets narrowed inflation differentials by between ¾ and almost 1½ percentage points in the Czech Republic and, to a lesser extent, the U.K., Belgium, and Denmark.
  - Trade union density and product market regulation flexibility were not found to significantly influence common-origin inflation differentials in this sample.
- Variables not significant or limited in relevance within the EU sample:
  - Political stability and central bank independence are either not relevant or not statistically significant, partly reflecting limited variability across EU25 countries.
  - Trade openness and size of government were not significant factors in explaining intra-EU common-origin inflation variation (though trade openness is associated with a larger contribution of common to headline inflation variance in other contexts).

### Persistence and policy-adjustment constraints
- High inertia in common-origin inflation differentials within the EU because important regressors are structural or institutional and evolve slowly or require extended implementation time to change.
- Institutional de jure changes can occur in the short run, but payoffs in economic flexibility and legal certainty depend on implementation and may take considerable time to materialize.

### Idiosyncratic inflation and implications for the Maastricht inflation criterion
- Country-specific (idiosyncratic) inflations typically modest but occasionally substantial; during 2001–05, country-specific inflations lay within +/− 3.5 percent for the 25 countries; for the EU15 the range was [−3.1, +2.8 percent].
- Among the EU8, idiosyncratic inflation closely tracked contributions from changes in regulated prices and indirect taxes, indicating policy-induced price changes are an important source of own price shocks.
- Idiosyncratic shocks affect the Maastricht criterion in two ways:
  - Negative idiosyncratic shocks in low-headline-inflation countries lowered the calculated level of the Maastricht reference inflation rate (recently on the order of 0.2 percentage point, but reached ½ percentage point at times during 2003-05).
  - Country selection bias: countries selected to set the criterion based on headline inflation can differ from those with the lowest common-origin inflation, so selection has typically been influenced by negative idiosyncratic shocks.
- Historical example: Greece’s qualification for euro adoption (March 2000) hinged on a sizable negative idiosyncratic shock—the difference between headline and common-origin inflations was about 1½ percentage points—attributable to indirect tax cuts, limited administered price adjustments, and informal agreements to cap price increases.
- Idiosyncratic shocks can both facilitate and hinder compliance with the Maastricht test and introduce random noise into assessment outcomes.
- Recent and near-term factors:
  - Introduction of lower value-added tax rates on services in a number of EU countries could exacerbate the criterion’s downward bias.
  - In the EU8, harmonization of indirect taxes and increases in some domestic energy prices (e.g., convergence of domestic natural gas prices to world levels) could produce positive own idiosyncratic shocks that push up headline inflation.
- Policy implication: eliminating the idiosyncratic component from inflation assessments is not appropriate because it would ignore business-cycle differences that are not fully synchronized within the EU.

### Specific implications for the EU8’s ability to meet Maastricht
- Price level gaps are among the most important explanations of inflation divergence for the EU8 (excluding Slovenia), pushing up common-origin inflation by 1-2 percentage points relative to the EU average and exhausting the 1½ percentage point Maastricht buffer.
- Institutional underpinnings for low inflation are generally present in several EU8 countries:
  - EU8 (excluding the Baltics and Slovenia) score highly or very highly on a combined measure of labor market flexibility and legal system quality, often outranking many current euro members.
  - Good performance on these institutional measures provides flexibility to accommodate shocks while maintaining low common-origin inflation.
- Near-term risks to meeting the inflation criterion for some EU8:
  - Relative underdevelopment and negative price gaps imply ceteris paribus higher common-origin inflation in non-euro EU8 countries.
  - Institutional improvements take time; therefore, EU8 may need to rely on sizable negative idiosyncratic inflation shocks to reduce headline inflation to Maastricht levels in the near term.

*Source: _wp0821 - conclusions.*

### REFERENCES

### _wp0821 - REFERENCES

### References (selected citations from the source)
- Aisen, A., and F. Jose Viega, 2005, “Does Political Instability Lead to Higher inflation? A Panel Data analysis,” IMF Working Paper 05/49 (Washington: International Monetary Fund).
- Alesina, Alberto, and Lawrence H. Summers, 1993, “Central Bank Independence and Macroeconomic Performance: Some Comparative Evidence,” Journal of Money, Credit, and Banking, Vol. 25, (No. 2), pp. 151–62.
- Altissimo, Filippo, Pierpaolo Benigno, and Diego Rodrigues Palenzuela, 2005, “Long-Run Determinants of Inflation Differentials in a Monetary Union,” NBER Working Paper No. 11473 (Cambridge, Massachusetts: National Bureau of Economic Research).
- Altissimo, Filippo, and others, 2001, “EuroCOIN: A Real Time Coincident Indicator of the Euro Area Business Cycle,” CPER Discussion Paper No. 3108 (London: Centre for Economic Policy Research).
- Angeloni, Ignazio, and Michael Ehrmann, 2004, “Euro Area Inflation Differentials,” ECB Working Paper No. 388 (Frankfurt: European Central Bank).
- Assenmacher-Wesche, Katrin, and Stefan Gerlach, 2006, “Interpreting Euro Area Inflation at High and Low Frequencies,” CEPR Discussion Paper No. 5632 (London: Centre for Economic Policy Research).
- Bai, Jushan, and Serena Ng, 2002, “Determining the Number of Factors In Approximate Factor Models,” Econometrica, Vol. 70 (No. 1), pp. 191–221.
- Bofinger, Peter, 1992, “The European Central Bank: Reshaping Monetary Politics in Europe: Discussion” in Establishing a Central Bank: Issues in Europe and lessons from the U.S., pp. 77–80, (Cambridge: Cambridge University Press).
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### Appendix I. Implementing the GDFM
- Two-step estimation procedure for the Generalized Dynamic Factor Model (GDFM).
- Step 1 — Derive covariance matrices of common and idiosyncratic components:
  - Determine number of dynamic common factors, q, by performing principal component analysis on the spectral density matrices of the dataset calculated over a grid of frequencies in [-π, π].
  - Eigenvalues represent the share of total data variance explained by corresponding principal components at each frequency and are ordered descending.
  - Choose q by setting a threshold for the proportion of total variability accounted for by the common factors and selecting the first q eigenvalues that produce this cumulative variance contribution.
  - Obtain spectral density matrices of the common components at each frequency by pre- and post-multiplying the diagonal matrix of the first q eigenvalues with the matrix of corresponding eigenvectors and its transposed complex conjugate.
  - Estimate spectral density matrices of idiosyncratic components as the difference between the spectral density matrices of the data and the common component.
  - Apply the inverse Fourier transform to these spectral density matrices to produce time-series dimension covariance matrices of the common and idiosyncratic components at all lags.
- Step 2 — Estimate the common components:
  - “Flatten” the q dynamic common factors and their lags into r = q(s+1) separate static factors.
  - Determine the number of static factors using the panel criterion of Bai and Ng (2002).
  - Obtain the r static factors by solving the generalized eigenvalue problem involving the covariance matrix of the common component at lag zero, Γχ(0), weighted by the diagonal matrix of variances of idiosyncratic components, Γζ(0).
  - The procedure finds contemporaneous linear combinations of the xjt’s that minimize the ratio of the variance of the idiosyncratic and common components.
  - Combine observed data with the first r generalized eigenvectors to produce estimated static factors.
  - Derive common components by projecting on the r static factors and the covariance matrix of the common components from Step 1.

### Appendix II. Data definitions and series
- Dependent variable
  - Average inflation iπx = Average over all months Jan 2002-Dec 2005 of log(common-origin inflation indext) - log(common-origin inflation indext-12).
  - Common-origin inflation index assumes two common factors.
  - Redefined as deviation from the mean by calculating x – sample mean.
- Independent variables
  - Relative price level: Logarithm of relative price level in 2001, centered around sample mean of 0.
  - Relative GDP per capita: Logarithm of relative GDP per capita in 2001, centered around sample mean of 0.
  - Nominal effective appreciation: Average over all months Jan 2002-Dec 2005 of log(nominal effective exchange ratet) nominal effective exchange ratet-12). NEER assumes 41 partner countries. Source: Eurostat. Redefined as deviation from the mean by calculating x – sample mean.
  - Average trade openness: Average exports and imports 2002-2005 in percent of average GDP 2002-05, centered around sample mean of 0.
  - Average import share of GDP: Average imports 2002-2005 in percent of average GDP 2002-05, centered around sample mean of 0.
  - Labor market flexibility: First principal component of 9 labor variables from Fraser Institute (F) and World Bank Doing Business (W): Difficulty of hiring (W), difficulty of firing (W), Hiring cost (W), Firing cost (W), Rigidity of employment (W), Rigidity of hours (W), Effective minimum wage (F), Coverage of collective bargaining (F), Hiring and Firing Practices (F). Higher index = greater flexibility. The principal component is centered around zero. Therefore, redefined to be positive with a minimum of 0 by calculating x + minimum(x). Redefined as sample mean=1 by calculating x / mean(x).
  - Product market flexibility: First principal component of 9 competition variables from Fraser Institute (F) and World Bank Doing Business (W): Closing cost (W), years to close (W), recovery value in bankruptcy (W), startup cost (W), startup procedures (W), startup days (W), startup capital (W), administrative barriers to startup (F), survey answers that startup is easy (F). Higher index = greater flexibility. The principal component is centered around zero. Therefore, redefined to be positive with a minimum of 0 by calculating x + minimum(x). Redefined as sample mean=1 by calculating x / mean(x).
  - Legal quality: First principal component of 10 legal variables from Fraser Institute (F) and World Bank Doing Business (W): legal procedures (W), legal cost (W), legal days (W), property registration cost (W), property registration procedures (W), property registration days (W), rule of law (F), impartial courts (F), independent judiciary (F), law and order (F). Higher index = better rule of law. The principal component is centered around zero. Therefore, redefined to be positive with a minimum of 0 by calculating x + minimum(x). Redefined as sample mean=1 by calculating x / mean(x).
  - Political instability (CNTS): First principal component of 3 measures of political instability from the Cross-National Time Series Database: average number of executive changes 1999-2003, average number of cabinet changes 1999-2003, average number of legislative changes 1999-2003. Higher index = higher instability. The principal component is centered around zero. Therefore, redefined to be positive with a minimum of 0 by calculating x + minimum(x). Redefined as sample mean=1 by calculating x / mean(x).
  - Political stability (Kaufmann-Kray): Average 2002-2005, source: Kaufmann and Kray (2006). Redefined to be positive with a minimum of 0 by calculating x + minimum(x). Then redefined as sample mean=1 by calculating x / mean(x).

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