## _wp06212

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---

### Objective and key hypothesis
- Purpose: empirically determine the causes of worldwide diversity of inflation volatility.
- Core hypothesis: political and institutional factors are main determinants of inflation volatility; politically-unstable countries are more susceptible to political shocks, leading to discontinuous monetary and fiscal policies and higher inflation volatility.
- Sample: panel data set covering around 100 countries for the period 1975–99.
- Dependent variable: Log[SD(Inflation)] — natural logarithm of the standard deviation of inflation for consecutive 3-year periods (periods: 1975–77, 1978–80, 1981–83, 1984–86, 1987–89, 1990–92, 1993–95, and 1996–99).

### Data and empirical model
- Data sources: Database of Political Institutions (DPI); Cross National Time Series Data Archive (CNTS); Annual Report of the Economic Freedom of the World (EFW); World Bank’s World Development Indicators (WDI); Global Development Network Growth Database (GDN); IMF’s International Financial Statistics (IFS).
- Model specification (panel): Log[SD(Inflation)]it = β'Xit + νi + δt + εit, with country-specific effects (ν) and time-specific effects (δ).
- Explanatory variables (3-year averages unless noted):
  - Lagged Log[SD(Inflation)] (-1).
  - Structural variables: Agriculture (percent of GDP); GDP per capita (PPP); Trade (percent of GDP).
  - Economic performance/external shocks: SD(GDP growth) (-1); Real overvaluation (-1); Log(Inflation); Change in oil prices.
  - Political/institutional variables: Executive changes (-1) (number of times effective control of the executive changes in a year); Index of economic freedom (EFW).
- Estimation approach: within groups (fixed effects) estimator preferred (Hausmann tests); country and time-period dummies included. SD(GDP growth), Real overvaluation and Executive changes are lagged one period.

### Empirical findings — main results
- Persistence:
  - Lagged Log[SD(Inflation)] (-1) coefficient = -0.042 (t-statistic -0.92) — not statistically significant; inflation volatility is not persistent along three-year periods.
- Correlation:
  - correlation between average inflation and its standard deviation for 3-year periods = 77.5 percent.
- Log(Inflation):
  - coefficient = 0.833 (t-statistic 11.8) — highly statistically significant when included.
- Political/institutional effects (column 3 baseline with political variables):
  - Executive changes (-1): coefficient = 0.410 (t-statistic 2.59) — greater political instability associated with higher inflation volatility. An additional executive change increases the standard deviation of the inflation rate by a factor of 1.51 ≈ exp(0.410), i.e., by 151 percent.
  - Index of economic freedom: coefficient = -0.672 (t-statistic -4.33) — lower economic freedom associated with higher inflation volatility. A decrease of one point of the Index of economic freedom increases the standard deviation by a factor of 1.96 ≈ exp(0.672).
- Structural and economic controls (selected coefficients from Table 1):
  - Agriculture (percent of GDP): coefficients across columns include 0.029 (t 2.2), 0.067 (t 3.42), 0.054 (t 2.75), 0.058 (t 2.81), 0.028 (t 1.24), 0.028 (t 1.24), 0.051 (t 2.62).
  - GDP per capita: coefficient values include -0.00005 (t -2.33), -0.00010 (t -8.03), -0.00010 (t -4.59), -0.00010 (t -4.79), -0.00010 (t -3.15), -0.00010 (t -3.18), -0.00010 (t -3.24) — higher GDP per capita associated with lower inflation volatility.
  - Real overvaluation (-1): coefficients include 0.001 (t 0.56), 0.002 (t 2.21), 0.002 (t 2.00), 0.002 (t 2.03), -0.001 (t -0.45), -0.001 (t -0.45), 0.002 (t 2.21).
- Political fragmentation and polarization (columns 4–6):
  - Ideological polarization: coefficient = 0.286 (t 2.33) — higher ideological polarization → higher inflation volatility.
  - Herfindhal index of parties’ shares: coefficient = -0.877 (t -2.10) — lower Herfindhal (more fragmentation) associated with higher inflation volatility.
  - Fractionalization index: coefficient = 0.854 (t 2.11) — higher fractionalization associated with higher inflation volatility.
- Sample and fit:
  - Number of observations across columns include 427, 569, 593, 563, 549, 515, 515, 437.
  - Number of countries across columns include 97, 97, 90, 90, 90, 98, 89, 69.
  - Adjusted R2 values reported include 0.69, 0.51, 0.58, 0.60, 0.60, 0.60, 0.54.
- Robustness:
  - Results for developing countries (column 7) similar to entire sample (column 3).
  - For industrialized countries results are weaker: Executive changes and Real overvaluation marginally significant; remaining explanatory variables not significant.
  - Additional robustness checks (summary): higher inflation volatility associated with greater turnover of central bank presidents; more leftist governments; lower U.S. Treasury ... (text truncated in source).

### Interpretation and mechanisms
- Mechanisms linking political/institutional variables to inflation volatility:
  - Political instability and fragmentation increase reliance on seigniorage revenues and produce discontinuities in fiscal and monetary policies, raising both inflation levels and volatility.
  - Ideological polarization increases heterogeneity of preferences for economic policies, causes delays in implementation of stabilization programs, and increases policy discontinuity, raising inflation volatility.
  - Lower economic freedom (weaker legal structures, larger government, less sound money, restrictions on exchange) is associated with environments where seigniorage and distortionary taxation are more prevalent, increasing inflation volatility.

### Policy-relevant conclusions
- Empirical conclusion: Higher degrees of political instability, ideological polarization and fragmentation of the political system, and lower economic freedom are associated with higher inflation volatility.
- Normative implication: Given the high costs of inflation volatility for economic growth and welfare, strengthening political stability, reducing ideological fragmentation in policy-making, and promoting economic freedom can contribute to lower inflation volatility.

### Section 2 — Major conclusion
- Policymakers in developing countries should be aware that, to obtain long-run economic prosperity, it is essential to reform institutions and create viable mechanisms conducive to long-run price stability.

### Section 2 — Empirical associations and robustness notes
- More volatile outcomes are associated with:
  - higher bill rates;
  - more flexible exchange rate regimes;
  - higher or more volatile external debt as a percentage of GDP;
  - more volatile central government debt.
- When the standard deviation of the annual change in M2 is used as the dependent variable, results are similar to those reported in Table 1.
- Results not shown in the paper are available upon request.

*Source: WP/06/212, Ari Aisen and Francisco José Veiga, September 2006.*

### Section 1

### Political Instability and Inflation Volatility

### Objective and key hypothesis
- Purpose: empirically determine the causes of worldwide diversity of inflation volatility.
- Core hypothesis: political and institutional factors are main determinants of inflation volatility; politically-unstable countries are more susceptible to political shocks, leading to discontinuous monetary and fiscal policies and higher inflation volatility.
- Sample: panel data set covering around 100 countries for the period 1975–99.
- Dependent variable: Log[SD(Inflation)] — natural logarithm of the standard deviation of inflation for consecutive 3-year periods (periods: 1975–77, 1978–80, 1981–83, 1984–86, 1987–89, 1990–92, 1993–95, and 1996–99).

### Data and empirical model
- Data sources: Database of Political Institutions (DPI); Cross National Time Series Data Archive (CNTS); Annual Report of the Economic Freedom of the World (EFW); World Bank’s World Development Indicators (WDI); Global Development Network Growth Database (GDN); IMF’s International Financial Statistics (IFS).
- Model specification (panel): Log[SD(Inflation)]it = β'Xit + νi + δt + εit, with country-specific effects (ν) and time-specific effects (δ).
- Explanatory variables (3-year averages unless noted):  
  - Lagged Log[SD(Inflation)] (-1).  
  - Structural variables: Agriculture (percent of GDP); GDP per capita (PPP); Trade (percent of GDP).  
  - Economic performance/external shocks: SD(GDP growth) (-1); Real overvaluation (-1); Log(Inflation); Change in oil prices.  
  - Political/institutional variables: Executive changes (-1) (number of times effective control of the executive changes in a year); Index of economic freedom (EFW).  
- Estimation approach: within groups (fixed effects) estimator preferred (Hausmann tests); country and time-period dummies included. SD(GDP growth), Real overvaluation and Executive changes are lagged one period.

### Empirical findings — main results
- Persistence: Lagged Log[SD(Inflation)] (-1) coefficient = -0.042 (t-statistic -0.92) — not statistically significant; inflation volatility is not persistent along three-year periods.
- Correlation: correlation between average inflation and its standard deviation for 3-year periods = 77.5 percent.
- Log(Inflation): coefficient = 0.833 (t-statistic 11.8) — highly statistically significant when included.
- Political/institutional effects (column 3 baseline with political variables):  
  - Executive changes (-1): coefficient = 0.410 (t-statistic 2.59) — greater political instability associated with higher inflation volatility. An additional executive change increases the standard deviation of the inflation rate by a factor of 1.51 ≈ exp(0.410), i.e., by 151 percent.  
  - Index of economic freedom: coefficient = -0.672 (t-statistic -4.33) — lower economic freedom associated with higher inflation volatility. A decrease of one point of the Index of economic freedom increases the standard deviation by a factor of 1.96 ≈ exp(0.672).  
- Structural and economic controls (selected coefficients from Table 1):  
  - Agriculture (percent of GDP): coefficients across columns include 0.029 (t 2.2), 0.067 (t 3.42), 0.054 (t 2.75), 0.058 (t 2.81), 0.028 (t 1.24), 0.028 (t 1.24), 0.051 (t 2.62).  
  - GDP per capita: coefficient values include -0.00005 (t -2.33), -0.00010 (t -8.03), -0.00010 (t -4.59), -0.00010 (t -4.79), -0.00010 (t -3.15), -0.00010 (t -3.18), -0.00010 (t -3.24) — higher GDP per capita associated with lower inflation volatility.  
  - Real overvaluation (-1): coefficients include 0.001 (t 0.56), 0.002 (t 2.21), 0.002 (t 2.00), 0.002 (t 2.03), -0.001 (t -0.45), -0.001 (t -0.45), 0.002 (t 2.21).  
- Political fragmentation and polarization (columns 4–6):  
  - Ideological polarization: coefficient = 0.286 (t 2.33) — higher ideological polarization → higher inflation volatility.  
  - Herfindhal index of parties’ shares: coefficient = -0.877 (t -2.10) — lower Herfindhal (more fragmentation) associated with higher inflation volatility.  
  - Fractionalization index: coefficient = 0.854 (t 2.11) — higher fractionalization associated with higher inflation volatility.
- Sample and fit: Number of observations across columns include 427, 569, 593, 563, 549, 515, 515, 437 (table shows varying Ns); Number of countries across columns include 97, 97, 90, 90, 90, 98, 89, 69 (as reported in Table 1); Adjusted R2 values reported include 0.69, 0.51, 0.58, 0.60, 0.60, 0.60, 0.54.
- Robustness: Results for developing countries (column 7) similar to entire sample (column 3). For industrialized countries results are weaker: Executive changes and Real overvaluation marginally significant; remaining explanatory variables not significant.
- Additional robustness checks (summary): higher inflation volatility associated with greater turnover of central bank presidents; more leftist governments; lower U.S. Treasury ... (text truncated in source).

### Interpretation and mechanisms
- Mechanisms linking political/institutional variables to inflation volatility:  
  - Political instability and fragmentation increase reliance on seigniorage revenues and produce discontinuities in fiscal and monetary policies, raising both inflation levels and volatility.  
  - Ideological polarization increases heterogeneity of preferences for economic policies, causes delays in implementation of stabilization programs, and increases policy discontinuity, raising inflation volatility.  
  - Lower economic freedom (weaker legal structures, larger government, less sound money, restrictions on exchange) is associated with environments where seigniorage and distortionary taxation are more prevalent, increasing inflation volatility.

### Policy-relevant conclusions
- Empirical conclusion: Higher degrees of political instability, ideological polarization and fragmentation of the political system, and lower economic freedom are associated with higher inflation volatility.
- Normative implication: Given the high costs of inflation volatility for economic growth and welfare, strengthening political stability, reducing ideological fragmentation in policy-making, and promoting economic freedom can contribute to lower inflation volatility.

*Source: WP/06/212, Ari Aisen and Francisco José Veiga, September 2006.*

### Section 2

### _wp06212 - Section 2

### Major conclusion
- Policymakers in developing countries should be aware that, to obtain long-run economic prosperity, it is essential to reform institutions and create viable mechanisms conducive to long-run price stability.

### Empirical associations and robustness notes
- More volatile outcomes are associated with:
  - higher bill rates;
  - more flexible exchange rate regimes;
  - higher or more volatile external debt as a percentage of GDP;
  - more volatile central government debt.
- When the standard deviation of the annual change in M2 is used as the dependent variable, results are similar to those reported in Table 1.
- Results not shown in the paper are available upon request.

### References cited (selected bibliographic details preserved exactly as in source)
- Acemoglu, Daron, Simon Johnson, James Robinson, and Yunyong Thaicharoen, 2003, “Institutional Causes, Macroeconomic Symptoms: Volatility, Crises and Growth,” Journal of Monetary Economics, Vol. 50, pp. 49–123.
- Aisen, Ari, and Francisco José Veiga, 2005, “The Political Economy of Seigniorage,” IMF Working Paper 05/175 (Washington: International Monetary Fund).
- _________, 2006, “Does Political Instability Lead to Higher Inflation? A Panel Data Analysis,” Journal of Money, Credit and Banking, Vol. 38, No. 5, pp. 1379–90.
- Alesina, Alberto, and Allan Drazen, 1991, “Why Are Stabilizations Delayed?” American Economic Review, Vol. 81, No. 5, pp. 1170–88.
- Castro, Vítor, and Francisco José Veiga, 2004, “Political Business Cycles and Inflation Stabilization,” Economics Letters, Vol. 83, No. 1, pp. 1–6.
- Cukierman, Alex, Sebastian Edwards, and Guido Tabellini, 1992, “Seignioriage and Political Instability,” American Economic Review Vol. 82, No. 3, pp. 537–55.
- Fatás, Antonio, and Ilian Mihov, 2005, “Policy Volatility, Institutions and Economic Growth,” CEPR Discussion Paper No. 5388 (London: Centre for Economic Policy Research).
- Fischer, Stanley, Ratna Sahay, and Carlos Végh, 2002, “Modern Hyper- and High Inflations,” The Journal of Economic Literature Vol. 40, No. 3, pp. 837–80.
- Friedman, Milton, 1977, “Nobel Lecture: Inflation and Unemployment,” Journal of Political Economy, Vol. 85, pp. 451–72.
- Rother, Philipp C., 2004, “Fiscal Policy and Inflation Volatility,” ECB Working Paper No. 317 (Frankfurt: European Central Bank).
- Woo, Jaejoon, 2003, “Economic, Political, and Institutional Determinants of Public Deficits,” Journal of Public Economics, Vol. 87, pp. 387–426.

*Source: _wp06212 - Section 2*

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