## _wp06281 — References / Appendices (excerpt)

## Source details

**Canonical URL:** [_wp06281 — References / Appendices (excerpt)](https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2006/_wp06281.pdf)

## Other formats

- [Markdown version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2006/_wp06281.pdf.md)
- [Structured JSON version](/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2006/_wp06281.pdf.json)

---

### I. Purpose, dataset, and scope
- Focus: characterize differences in membership size of central bank implementation boards (MPCs) that decide on changing policy instruments to achieve a monetary policy target.
- Dataset: covers 84 central banks around the world at the end of 2003.
- Main data sources: Lybek and Morris (2004) for MPC size and (de jure) central bank characteristics, supplemented by Rose (2006), Morgan Stanley Central Bank Directory, Fry et al. (2000), Ize (2006), IMF International Financial Statistics, and exchange rate regime classifications from Levy-Yeyati and Sturzenegger (2005), Reinhart and Rogoff (2004), IMF (2003).
- Exclusions: advisory committees (no formal authority) are not included; different board functions and autonomy types are discussed in Appendix I and Lybek and Morris (2004).

### II. Theoretical considerations and trade-offs
- Core trade-off:
  - Benefits of larger MPCs:
    - Improved information processing via pooling of experiences, perspectives, models, information sets, and different objective functions.
    - Greater checks and balances and representation.
    - Supported by Condorcet’s jury theorem and literature (Gerlach-Kristen (2006), Berk and Bierut (2004), Blinder and Morgan (2005), Lombardelli et al. (2005)).
  - Costs of larger MPCs:
    - Greater difficulty and time in decision making; bilateral discussions scale as ½ (n^2 - n).
    - Increased preparatory communication and decision-making costs; possible freeriding as membership rises.
    - Diminishing marginal information benefits: B_ni > 0 and B_ni,ni ≤ 0; decision costs strictly convex: C_ni > 0 and C_ni,ni > 0.
- First-order condition for optimal size n_i*:
  - B_ni(x_i, n_i) = C_ni(x_i, n_i)
- Heterogeneity: optimal MPC size likely varies with country size, regional/industry diversity, political institutions, central bank functions, and autonomy type.

### III. Box 1 — A Simple Illustration (theoretical framework and hypotheses)
- Welfare maximization: W_i = B(x_i, n_i) – C(x_i, n_i).
- Special-case illustrative results:
  - If marginal benefits independent of n_i and marginal costs linear, b(x_i) = c n -> n_i* = b(x_i) / c.
  - If b(x_i) is concave, relationship between x_i and MPC size is concave.
- Qualitative hypotheses:
  - Diversity and country size increase MPC size.
  - Higher development (income, financial depth) associated with larger MPCs; greater openness may reduce required MPC size.
  - Stronger democratic institutions likely associated with larger MPCs.
  - Higher public debt may correlate with larger MPCs.
  - Floating exchange rate regimes likely associated with larger MPCs.
  - MPC size interacts with central bank independence, monetary policy strategy, staff size, operating expenditures, and term length.
  - Relationships may be non-linear.

### IV. Empirical approach and estimation
- MPC measure: board size index from Lybek and Morris (2004), grouped in classes of three members (1 = 1–3 members, 2 = 4–6 members, etc.). Sample size N = 84; Figure 1: N = 84 / mean = 2.85 / std. dev. = 0.87.
- Estimation methods:
  - Ordered probit for ordered MPC index (bivariate and augmented specifications).
  - Probit with binary dependent variable (MPC > 6 members).
  - Quadratic OLS specifications (MPC = α + β x + γ x^2 + ε) to allow non-linearities.
- Baseline multivariate specification (ordered probit) typically includes: population, real GDP per capita (USD), landlockedness, voice & accountability, and central bank staff (or operating expenditures).

### V. Key empirical associations and exact estimates (selected)
- Population (Table 1)
  - Bivariate ordered probit: 0.009** (0.002)
  - Augmented ordered probit: 0.010** (0.002)
  - Probit (binary dep. var.): 0.02* (0.01)
- Ethnolinguistic Fractionalization (Table 2)
  - Bivariate ordered probit: 1.12* (0.55)
  - Augmented ordered probit: 1.04# (0.61)
- Administrative Divisions (Table 2)
  - Bivariate ordered probit: 0.006# (0.003)
  - Probit (binary dep. var.): 0.02* (0.01)
- Landlocked (Table 3)
  - Bivariate ordered probit: -0.57* (0.26)
  - Augmented ordered probit: -0.51# (0.28)
- Trade Openness (Table 3)
  - Bivariate ordered probit: -0.005 (0.003) (negative sign, not statistically significant)
- Debt (percent of GDP) (Table 4)
  - Bivariate ordered probit: 0.009* (0.004)
  - Augmented ordered probit: 0.007# (0.004)
- Institutional quality measures (Table 4, augmented)
  - Voice & Accountability: 0.44** (0.16)
  - Government Effectiveness: 0.62** (0.19)
  - Regulatory Quality: 0.40* (0.19)
  - Rule of Law: 0.71** (0.24)
- Central bank independence and limits on financing (Table 5)
  - CB Independence Score (augmented): 0.02* (0.01)
  - Limited Central Bank Financing of Government Deficit (augmented): 1.41** (0.54)
- Exchange rate regime (Table 5, bivariate)
  - Floating Exchange Rate, RR: 0.90* (0.37)
  - Floating Exchange Rate, LYS: 0.67** (0.26)
  - Floating Exchange Rate, IMF: 0.40# (0.23)
- Central bank size and resources (Table 5, bivariate)
  - Staff: 0.10** (0.03)
  - Log Staff: 0.50** (0.09)
  - Operating Expenditures: 0.52** (0.19)
  - Log Operating Expenditures: 0.28** (0.09)

### VI. Nonlinear (quadratic) empirical findings (selected exact estimates)
- Population (Table 6 quadratic)
  - Coefficient 1 (β): 0.018** (0.007)
  - Coefficient 2 (γ on population^2): -0.00004# (0.00002)
  - Interpretation: concave relationship (marginal impact of population on MPC size declines at higher population levels).
- Term Length (Table 6 quadratic)
  - Linear term: -0.590** (0.204)
  - Quadratic term: 0.040** (0.012)
  - Interpretation: convex relationship—term length is significantly associated with MPC size only in non-linear specification.
- Other variables with significant concave relationships in quadratic specifications (selected):
  - Administrative Divisions: 0.024* (0.011) and -0.0001* (0.00005)
  - Government Effectiveness: 0.330* (0.140) and -0.307* (0.128)
  - Rule of Law: 0.399** (0.145) and -0.408** (0.146)
  - Debt: 0.029** (0.011) and -0.0002* (0.00007)
  - Staff: 0.131** (0.043) and -0.001# (0.0005)
- General pattern: variables with significant non-linear effects were also relevant in linear specifications; majority of non-linear effects are concave.

### VII. Multivariate results — core coefficients and fit (Table 7 summary)
- Selected baseline and alternative ordered probit coefficients (coefficient (standard error)):
  - Population: 0.744** (0.254) in baseline; other reported specs include 0.533 (0.325), 0.730 (0.456), 0.599* (0.263), 0.874** (0.278), 0.908* (0.435), 1.540** (0.394).
  - Area (alternative): 0.186* (0.081).
  - Real GDP per capita (USD): -0.431* (0.175); -0.463** (0.175); -0.473* (0.200); -0.593** (0.227); -0.389* (0.174); -0.608** (0.185); -0.697** (0.236); -0.378 (0.244).
  - Landlocked: coefficients range from -0.428 (0.280) to -0.990** (0.368) across specifications.
  - Voice & Accountability: coefficients range from 0.382* (0.166) to 0.707** (0.212).
  - Staff: 0.385** (0.131); other specifications show variation (e.g., 0.709 (0.464), 0.444** (0.169)).
  - Trade Openness: -0.004 (0.003) (not significant).
  - Business Cycle Correlation: 0.573 (0.447) (not significant).
  - CB Independence Score: 0.020* (0.009) (significant where included).
  - Float’g Exchange Rate, LYS: 0.482# (0.284) (marginally significant).
  - Term Length: -0.457# (0.271); Term Length Squared: 0.022 (0.016).
  - Limited Central Bank Financing of Government Deficit: 1.109# (0.601).
  - Ethnolinguistic Fractionalization: 1.485* (0.618).
- Sample sizes and fit:
  - Number Observations across specifications: 83, 83, 78, 53, 83, 64, 53, 50.
  - Count R2 by column: 0.542, 0.530, 0.551, 0.604, 0.530, 0.563, 0.604, 0.580.
  - Pseudo-R2 (McKelvey and Zavoina) by column: 0.334, 0.568, 0.368, 0.492, 0.356, 0.477, 0.469, 0.431.
  - Authors note Pseudo-R2 values are between 0.3 and 0.6; Count R2 generally in the 0.5 to 0.6 range. Robustness: OLS regressions (unreported) yield qualitatively unchanged coefficients and adjusted R2 typically on the upper end of the reported range.

### VIII. Synthesized empirical conclusions and institutional implications
- Observed MPC size reflects trade-off equating marginal benefits and marginal costs of membership size and varies with institutional and political frameworks.
- Expected associations (policy-relevant expectations preserved verbatim):
  - increases with greater diversity and country size;
  - is larger at higher levels of development, but decreases with greater openness;
  - is larger in the presence of stronger democratic institutions;
  - is larger in the presence of higher public debt levels;
  - is larger in the presence of a floating exchange rate system; and
  - interacts systematically with other elements of central bank design, including the degree of central bank independence, monetary policy strategy, staff size and operating expenditures, and the term length of MPC members.
- Nonlinearity: the relationship between any country characteristic and the number of MPC members may well be non-linear; empirical models should allow for non-linearities.
- Institutional implication: central bank governance appears tailored to country-specific factors; efficient MPC size likely varies across countries.

### IX. Appendix highlights, descriptive statistics, and visual analyses
- Types of autonomy (Appendix I): Limited autonomy, Instrument autonomy, Target autonomy, Goal autonomy; distinct board functions: policy decisions, implementation (MPC/implementation board), management, oversight.
- Sample: 84 economies (list provided in source).
- Selected descriptive statistics (exact figures preserved):
  - MPC: Obs. 84; Mean 2.85; Std. Dev. 0.87; Min 1; Max 5.
  - Population: Obs. 98; Mean 37.44; Std. Dev. 132.02; Min 0.27; Max 1262.65.
  - Area: Obs. 98; Mean 0.997; Std. Dev. 2.588; Min 0.0004; Max 17.075.
  - Real GDP (USD): Obs. 95; Mean 0.313; Std. Dev. 1.194; Min 0.0004; Max 10.300.
  - Real GDP per capita (USD): Obs. 94; Mean 10.02; Std. Dev. 9.53; Min 0.46; Max 35.13.
  - Ethnolinguistic Fractionalization: Obs. 62; Mean 0.38; Std. Dev. 0.29; Min 0.00; Max 0.93.
  - Landlocked: Obs. 98; Mean 0.21; Std. Dev. 0.41; Min 0; Max 1.
  - CB Independence (index): Obs. 98; Mean 2.67; Std. Dev. 0.83; Min 1; Max 4.
  - CB Independence Score (Fry et al.): Obs. 93; Mean 73.5; Std. Dev. 16.2; Min 24; Max 98.
  - Term Length: Obs. 70; Mean 5.19; Std. Dev. 1.97; Min 3; Max 14.
  - Staff: Obs. 89; Mean 4.04; Std. Dev. 18.03; Min 0.10; Max 150.00.
  - Establishment Year (central bank): Obs. 98; Mean 1939; Std. Dev. 59.33; Min 1668; Max 1997.
- Visual analyses: scatter plots illustrate relationships between board size and country size, heterogeneity measures, level of development, openness, political regime metrics, central bank characteristics, and term length (Panels A–D, VI).

_Source: _wp06281 — References, Box 1, Appendix VI (excerpt of IMF working paper content)._

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

### References

### I. Introduction — purpose and dataset
- Focus: characterize differences in membership size of central bank implementation boards (MPCs) that decide on changing policy instruments to achieve a monetary policy target.
- Dataset: covers 84 central banks around the world at the end of 2003.
- Data sources combined: Lybek and Morris (2004) for MPC size and (de jure) central bank characteristics, plus macroeconomic, structural, institutional, and central bank data.
- Observed cross-country facts and context:
  - Of the 82 central banks surveyed by Fry and others (2000), 55 institutions (67 percent) had policy committees with 5–10 members.
  - Examples of institutional board sizes: ECB’s Governing Council limited to 21 (future voting members), Bank of England Monetary Policy Committee = 9, Federal Reserve Federal Open Market Committee = 12.
- Central scope exclusions: advisory committees (no formal authority) are not included; different types of board functions and autonomy are discussed further in Appendix I and Lybek and Morris (2004).

### II. Key theoretical considerations and trade-offs
- Core trade-off determining optimal MPC size:
  - Benefits of larger MPCs:
    - Improved information processing via pooling of experiences, perspectives, models, information sets, and potentially different objective functions.
    - Greater checks and balances and representation of diverse groups.
    - Supported by theoretical and experimental literature (references in text: Condorcet’s jury theorem, Gerlach-Kristen (2006), Berk and Bierut (2004), Blinder and Morgan (2005), Lombardelli et al. (2005)).
  - Costs of larger MPCs:
    - Greater difficulty in decision making; discussions become more time consuming.
    - Increased preparatory communication and decision-making costs — potentially non-linear/exponential in n (number of members).
    - Incentives for freeriding on information-processing efforts of others as membership increases.
    - Diminishing marginal gains from additional members as board size grows.
- Formal observations and examples:
  - Bilateral discussions scale as ½ (n^2 - n).
  - Empirical and institutional concerns: Bundesbank’s 1992 reform to prevent MPC size increases after German unification; ECB (2003) concern that increased number of governors attending euro area MPC meetings “will not necessarily make deliberations easier....”
- Heterogeneity in optimal size:
  - Optimal MPC size likely varies across countries depending on economic size, diversity across regions and industries, political institutions, central bank functions, and type of autonomy (instrument, target, goal).
  - Goodfriend (2005, p. 85) quote: “the efficient size of a policy committee might vary across countries.”
  - Sibert (2006, p.1) related claim: “[A]s a result of shirking and coordination problems, smaller committees may be better than larger ones and the optimal size for a committee is an empirical issue.”

### III. Empirical associations and main findings (as reported)
- MPC size is strongly and plausibly associated with a number of country-specific characteristics:
  - Positive correlations:
    - Measures of country size and (population) heterogeneity — supporting the information-processing requirement hypothesis.
    - More democratic countries tend to have, on average, larger boards.
    - Central banks with greater formal autonomy over objectives and targets tend to have larger boards.
    - Central banks with a more complex monetary strategy, a longer history, and more staff typically have more board members.
  - Board member terms: larger boards tend to have members who serve, on average, shorter terms.
- Empirical approach overview:
  - Uses a simple theoretical model to illustrate linkages between country features and MPC size.
  - Explores empirical associations across a wide variety of country characteristics.
  - Data and empirical results are presented in Section III of the paper (tables and figures listed in front matter include Tables 1–7, Figure 1, Appendix material, and scatter plots).

### IV. Determinants discussed in detail
- Country size and heterogeneity:
  - Information processing requirements modeled as a positive function of diversity and country size.
  - Rationale: complex economies may require more MPC members to represent key sectors, regions, or to monitor diverse economic conditions.
- Political and institutional factors:
  - Political regime matters: in autocratic regimes a larger MPC may provide insulation from political pressures; less democratic regimes may prefer smaller boards.
  - The decision on MPC size may result from political bargaining among interest groups or be a deliberate design choice by policymakers, influenced by central bank independence (instrument vs. target vs. goal autonomy).
- Central bank internal design features:
  - Composition (internal vs. external members), meeting procedures (consensus vs. voting), role of the chairman, and term lengths can influence board dynamics but are considered outside the main empirical scope.
  - Full autonomy over objectives and instruments may be associated with larger MPCs.

### V. Methodology notes and literature context
- The paper organizes the literature and arguments around the cost–benefit trade-off of MPC size, citing Berger (2006), Sibert (2006), Goodfriend (2005), and empirical and experimental contributions (Blinder 1998; Blinder and Morgan 2005; Lombardelli et al. 2005; Gerlach-Kristen 2006; Riboni and Ruge-Murcia 2006; Méon 2006).
- Social psychology and group-size literature are noted as relevant (Schein 1999; Sibert 2006; Vandenbussche forthcoming).
- Appendix material (listed in front matter) provides:
  - Appendix I: Different Types of Autonomy and Monetary Policy Decisions.
  - Appendix II: Countries in The Sample.
  - Appendix III: Definitions and Sources of Variables.
  - Appendix IV: Descriptive Statistics.
  - Appendix V: Scatter Plots.
  - Appendix VI: Board Size and Term Length.
  - Box: A Simple Illustration.

*Source: _wp06281 - References (excerpt of IMF working paper content).*

### Box 1: A Simple Illustration

### Box 1: A Simple Illustration

### Theoretical framework
- Welfare maximization for country i:
  - W_i = B(x_i, n_i) – C(x_i, n_i)
  - C is strictly convex in n_i: C_ni > 0 and C_ni,ni > 0 (decision-costs rise with MPC size).
  - B is increasing in n_i at a non-increasing rate: B_ni > 0 and B_ni,ni ≤ 0 (marginal information benefits decline).
  - First-order condition for optimal MPC size n_i*:
    - B_ni(x_i, n_i) = C_ni(x_i, n_i)
- Implications:
  - n_i* depends on country-specific characteristics x_i and functional forms of B and C.
  - Any element of x_i may influence MPC size via benefits or costs; estimated impacts can be of any sign and possibly non-linear.
- Simple illustrative special case (scalar x_i, constant marginal-cost slope c):
  - If marginal benefits independent of n_i and marginal costs linear, b(x_i) = c n -> n_i* = b(x_i) / c.
  - If b(x_i) is concave, relationship between x_i and MPC size is concave.

### Hypotheses on determinants of MPC size (qualitative)
- Diversity and country size may increase MPC size (representation, information aggregation).
- Higher development (income, financial depth) may be associated with larger MPCs; but greater openness may reduce required MPC size.
- Stronger democratic institutions likely associated with larger MPCs.
- Higher public debt may correlate with larger MPCs (insulation against fiscal pressure).
- Flexible (floating) exchange rate regimes likely associated with larger MPCs.
- MPC size interacts with other central bank design features: central bank independence, monetary policy strategy, staff size, operating expenditures, term length of members.
- Relationships may be non-linear.

### Data and empirical approach (summary)
- MPC size measure: board size index from Lybek and Morris (2004), grouped in classes of three members (1 = 1–3 members, 2 = 4–6 members, etc.). Sample size N = 84 (countries).
- Figure 1 summary statistics: N = 84 / mean = 2.85 / std. dev. = 0.87.
- Main explanatory data sources: Rose (2006) plus Lybek and Morris (2004), Morgan Stanley Central Bank Directory, Fry et al. (2000), Ize (2006), IMF International Financial Statistics.
- Exchange rate regime classifications used: Levy-Yeyati and Sturzenegger (2005), Reinhart and Rogoff (2004), IMF (2003).
- Estimation strategy:
  - Ordered probit for ordered MPC index.
  - Reported: bivariate ordered probit, augmented ordered probit (controls: population and per capita income), and probit with binary dependent variable (MPC > 6 members).
  - Also estimate quadratic specifications (MPC = α + β x + γ x^2 + ε) to allow non-linearities.

### Key empirical findings (selected exact estimates preserved)
- Population (Table 1)
  - Bivariate ordered probit: 0.009** (0.002)
  - Augmented ordered probit: 0.010** (0.002)
  - Probit (binary dep. var.): 0.02* (0.01)
- Ethnolinguistic Fractionalization (Table 2)
  - Bivariate ordered probit: 1.12* (0.55)
  - Augmented ordered probit: 1.04# (0.61)
- Administrative Divisions (Table 2)
  - Bivariate ordered probit: 0.006# (0.003)
  - Probit (binary dep. var.): 0.02* (0.01)
- Landlocked (Table 3)
  - Bivariate ordered probit: -0.57* (0.26)
  - Augmented ordered probit: -0.51# (0.28)
- Trade Openness (Table 3)
  - Bivariate ordered probit: -0.005 (0.003) (consistent negative sign, not statistically significant)
- Debt (percent of GDP) (Table 4)
  - Bivariate ordered probit: 0.009* (0.004)
  - Augmented ordered probit: 0.007# (0.004)
- Voice & Accountability; Government Effectiveness; Regulatory Quality; Rule of Law (Table 4)
  - Voice & Accountability (augmented): 0.44** (0.16)
  - Government Effectiveness (augmented): 0.62** (0.19)
  - Regulatory Quality (augmented): 0.40* (0.19)
  - Rule of Law (augmented): 0.71** (0.24)
- Central bank independence and limits on central bank financing (Table 5)
  - CB Independence Score (augmented): 0.02* (0.01)
  - Limited Central Bank Financing of Government Deficit (augmented): 1.41** (0.54)
- Exchange rate regime (Table 5)
  - Floating Exchange Rate, RR (bivariate): 0.90* (0.37)
  - Floating Exchange Rate, LYS (bivariate): 0.67** (0.26)
  - Floating Exchange Rate, IMF (bivariate): 0.40# (0.23)
- Central bank size and resources (Table 5)
  - Staff (bivariate): 0.10** (0.03)
  - Log Staff (bivariate): 0.50** (0.09)
  - Operating Expenditures (bivariate): 0.52** (0.19)
  - Log Operating Expenditures (bivariate): 0.28** (0.09)

### Nonlinear (quadratic) findings (selected exact estimates preserved)
- Population (Table 6 quadratic)
  - Coefficient 1 (β): 0.018** (0.007)
  - Coefficient 2 (γ on population^2): -0.00004# (0.00002)
  - Interpretation: concave relationship (marginal impact of population on MPC size declines at higher population levels).
- Term Length (Table 6 quadratic)
  - Linear term: -0.590** (0.204)
  - Quadratic term: 0.040** (0.012)
  - Interpretation: convex relationship—term length is significantly associated with MPC size only in non-linear specification.
- Other variables with significant concave relationships in quadratic specifications (selected):
  - Administrative Divisions: 0.024* (0.011) and -0.0001* (0.00005)
  - Government Effectiveness: 0.330* (0.140) and -0.307* (0.128)
  - Rule of Law: 0.399** (0.145) and -0.408** (0.146)
  - Debt: 0.029** (0.011) and -0.0002* (0.00007)
  - Staff: 0.131** (0.043) and -0.001# (0.0005)
- General pattern: almost all variables with significant non-linear effects were also relevant in linear specifications; majority of non-linear effects are concave.

### Summing up: substantive conclusions (exact policy-relevant expectations)
- Observed MPC size will reflect the trade-off equating marginal benefits and marginal costs of membership size and will vary with institutional and political frameworks.
- In particular, we would expect that MPC size:
  - increases with greater diversity and country size;
  - is larger at higher levels of development, but decreases with greater openness;
  - is larger in the presence of stronger democratic institutions;
  - is larger in the presence of higher public debt levels;
  - is larger in the presence of a floating exchange rate system; and
  - interacts systematically with other elements of central bank design, including the degree of central bank independence, monetary policy strategy, staff size and operating expenditures, and the term length of MPC members.
- The relationship between any country characteristic and the number of MPC members may well be non-linear; empirical models should allow for non-linearities.

*Source: Box 1 from _wp06281 - Box 1: A Simple Illustration (IMF PDF).*

### Appendix VI, board members typically tend to have longer legislated terms in both relatively

### _wp06281 - Appendix VI, board members typically tend to have longer legislated terms in both relatively

### E. Multivariate Results — empirical approach and main correlates
- Empirical approach:
  - Selected a representative variable from each determinant group, prioritizing strong bivariate correlation with central bank board size and broad sample availability.
  - Baseline specification includes population, real GDP per capita (USD), landlockedness, voice & accountability, and central bank staff (operating expenditures yield similar results).
  - Estimation method: ordered probit regression (dependent variable: board size index). Pseudo-R2 is the McKelvey and Zavoina R2. Standard errors in parentheses. **, * and # denote significance at the 0.01, 0.05 and 0.10 level, respectively.

- Core multivariate findings (Table 7; coefficient (standard error)):
  - Population: 0.744** (0.254) in baseline; other specifications report 0.533 (0.325), 0.730 (0.456), 0.599* (0.263), 0.874** (0.278), 0.908* (0.435), 1.540** (0.394).
  - Area: 0.186* (0.081) reported in alternative specification replacing population.
  - Real GDP per capita (USD): -0.431* (0.175); -0.463** (0.175); -0.473* (0.200); -0.593** (0.227); -0.389* (0.174); -0.608** (0.185); -0.697** (0.236); -0.378 (0.244).
  - Landlocked: -0.428 (0.280); -0.485# (0.283); -0.563# (0.294); -0.990** (0.368); -0.433 (0.279); -0.544# (0.320); -0.842** (0.320); -0.931** (0.415).
  - Voice & Accountability: 0.425** (0.156); 0.382* (0.166); 0.386* (0.177); 0.395* (0.158); 0.375* (0.154); 0.707** (0.212); 0.429* (0.179); 0.497** (0.253).
  - Staff: 0.385** (0.131); 0.709 (0.464); 0.444** (0.169); 0.376# (0.217); 0.410** (0.120); 0.360** (0.087); 0.345# (0.200); 0.765 (0.508).
  - Trade Openness: -0.004 (0.003) (not significant in multivariate framework).
  - Business Cycle Correlation: 0.573 (0.447) (not significant in multivariate framework).
  - CB Independence Score: 0.020* (0.009) (statistically significant where included).
  - Float’g Exchange Rate, LYS: 0.482# (0.284) (marginally significant where included).
  - Term Length: -0.457# (0.271) (negative relation at shorter term lengths where included).
  - Term Length Squared: 0.022 (0.016) (reported when testing for nonlinearity).
  - Lim. CB Finan-cing of Gov’t Def.: 1.109# (0.601) (marginally significant where included).
  - Ethnolinguistic Fractionalization: 1.485* (0.618) (statistically significant where included).

- Sample sizes and goodness-of-fit:
  - Number Observations across reported specifications: 83, 83, 78, 53, 83, 64, 53, 50.
  - Count R2 reported: 0.542, 0.530, 0.551, 0.604, 0.530, 0.563, 0.604, 0.580 (by column).
  - Pseudo-R2 reported: 0.334, 0.568, 0.368, 0.492, 0.356, 0.477, 0.469, 0.431 (by column).
  - Authors note Pseudo-R2 values (McKelvey and Zavoina method) are between 0.3 and 0.6; Count R2 generally in the 0.5 to 0.6 range.
  - Robustness checks: OLS regressions (unreported) yield qualitatively unchanged coefficients and adjusted R2 typically on the upper end of the reported range.

- Interpretation of multivariate results:
  - Larger MPCs are associated with larger country size (population), more democratic political regimes (voice & accountability), and more central bank staff.
  - Richer countries (higher real GDP per capita) and landlocked countries tend to have smaller MPCs in multivariate specifications (though landlockedness significance varies).
  - Central bank independence and ethnolinguistic fractionalization show expected signs and are statistically highly significant in specifications where included.
  - Exchange rate regime (floating under Levy-Yeyati & Sturzenegger classification) and limits on central bank financing of government debt play at least marginal roles.
  - Trade openness and correlation with the world business cycle are not significant determinants in the multivariate framework.
  - Direction of multivariate relationships confirms earlier bivariate findings.

### IV. Conclusions — synthesized empirical implications and institutional relationships
- Data and scope:
  - Dataset covers de jure membership size of 84 central bank boards at end-2003 that decide interest rate changes to achieve a specified target.
  - Average MPC in the sample: 7–9 members (explicit statement).

- Theoretical framing:
  - Optimal MPC size depends on trade-offs: information-processing benefits (Condorcet’s jury theorem) versus coordination costs, decision delay, and freeriding incentives.
  - Political considerations: larger MPC size may enhance resistance to political pressure and reflect political power-sharing.
  - MPC size may be systematically related to other central bank design parameters (e.g., term length).

- Empirical conclusions:
  - MPC size tends to increase with country size and population heterogeneity (supporting information-processing requirement hypotheses).
  - More democratic countries tend to have larger boards on average.
  - Evidence of hump-shaped effects for some variables (nonlinearity tested via squared terms).
  - MPC size is often associated with other central bank characteristics:
    - Larger MPCs where central banks have more staff or higher operational expenditures.
    - Central banks in floating exchange rate regimes tend to have larger MPCs.
    - More independent central banks often have larger MPCs (CB Independence Score positive and significant in some specifications).
    - Negative relation between MPC size and length of terms served by MPC members (at least at shorter term lengths), suggesting interdependence of institutional features.

- Institutional implication:
  - Central bank governance appears tailored to country-specific factors; efficient MPC size likely varies across countries.

### Appendix highlights — supporting data, definitions, and descriptive statistics
- Types of autonomy and role of boards (based on Lybek and Morris (2004)):
  - Four autonomy types: Limited autonomy, Instrument autonomy, Target autonomy, Goal autonomy.
  - Distinct functions: policy decisions (determine target, prioritize goals), implementation decisions (MPC/implementation board), management (day-to-day), oversight (supervisory board). Advisory committees exist without formal authority.

- Countries in sample: list includes 84 economies (partial display in source).

- Key variables (definitions and sources):
  - MPC: Board size index; implementation board (Lybek and Morris).
  - Population, Area, Real GDP (USD), Real GDP (PPP), Ethnolinguistic Fractionalization, and many institutional and macroeconomic controls (sources: Rose, WDI, World Bank, IFS, Lybek and Morris, Fry et al., Reinhart and Rogoff, Levy-Yeyati & Sturzenegger, IMF, Central Bank Directory, Ize, etc.). (Full list of variables and sources provided in source content.)

- Descriptive statistics (selected exact figures from IV. Descriptive Statistics):
  - MPC: Obs. 84; Mean 2.85; Std. Dev. 0.87; Min 1; Max 5.
  - Population: Obs. 98; Mean 37.44; Std. Dev. 132.02; Min 0.27; Max 1262.65.
  - Area: Obs. 98; Mean 0.997; Std. Dev. 2.588; Min 0.0004; Max 17.075.
  - Real GDP (USD): Obs. 95; Mean 0.313; Std. Dev. 1.194; Min 0.0004; Max 10.300.
  - Real GDP per capita (USD): Obs. 94; Mean 10.02; Std. Dev. 9.53; Min 0.46; Max 35.13.
  - Ethnolinguistic Fractionalization: Obs. 62; Mean 0.38; Std. Dev. 0.29; Min 0.00; Max 0.93.
  - Landlocked: Obs. 98; Mean 0.21; Std. Dev. 0.41; Min 0; Max 1.
  - CB Independence (index): Obs. 98; Mean 2.67; Std. Dev. 0.83; Min 1; Max 4.
  - CB Independence Score (Fry et al.): Obs. 93; Mean 73.5; Std. Dev. 16.2; Min 24; Max 98.
  - Term Length: Obs. 70; Mean 5.19; Std. Dev. 1.97; Min 3; Max 14.
  - Staff: Obs. 89; Mean 4.04; Std. Dev. 18.03; Min 0.10; Max 150.00.
  - Establishment Year (central bank): Obs. 98; Mean 1939; Std. Dev. 59.33; Min 1668; Max 1997.

- Visual analyses:
  - Multiple scatter plots (Panels A–D, VI) illustrate relationships between board size and: country size, heterogeneity measures (ethnolinguistic, linguistic, religious fractionalization), level of development (real GDP per capita, Human Development Index), openness, political regime metrics (Democracy, Polity, Voice & Accountability, Government Effectiveness, Rule of Law), central bank characteristics (CB Independence index and score, FX regime indices, Term Length, Central Bank Staff, CB Establishment Year), and board size vs term length (Panel VI).

*Source: IMF Working Paper (content unit: _wp06281 - Appendix VI, board members typically tend to have longer legislated terms in both relatively).*

### REFERENCES

### _wp06281 - REFERENCES

### References

- Baldwin, Richard, Erik Berglöf, Francesco Giavazzi, and Mika Widgren, 2001, “Preparing the ECB for Enlargement,” CEPR Policy Paper No. 6 (London: Center for Economic Policy Research).
- Barber, Tony, 2001, “Casting Light on the ECB,” Financial Times Online, September 6.
- Benigno, Pierpaolo, 2004, “Optimal Monetary Policy in a Currency Area,” Journal of International Economics, Vol. 63 No. (2), pp. 293–320.
- Berger, Helge, 1997, “The Bundesbank’s Path to Independence: Evidence from the 1950’s,” Public Choice, Vol. 93 No. (3-4), pp. 427–53.
- ———, 2006, “Optimal Central Bank Design: Benchmarks for the ECB,” Review of International Organizations, forthcoming.
- ———, and Jakob de Haan, 2002, “Are Small Countries too Powerful Within the ECB?” Atlantic Economic Journal, Vol. 30 No. (3), pp. 1–20.
- ———, and Robert Inklaar, 2004, “Restructuring the ECB,” in Managing EU Enlargement, ed. by Helge Berger and Thomas Moutos (Cambridge, Massachusetts: MIT Press), pp. 29–66.
- Berger, Helge, Sylvester Eijffinger, and Jakob de Haan, 2001, “Central Bank Independence: An Update of Theory and Evidence,” Journal of Economic Surveys, Vol. 15 No. (1), pp. 3–40.
- Berger, Helge and Volker Nitsch, 2006, “Too Many Cooks? Committees in Monetary Policy”(unpublished); Freie Universität Berlin.
- Berk, Jan Marc, and Beata K. Bierut, 2004, “The Effects of Learning in Interactive Monetary Policy Committees,” Netherlands Central Bank, MEB Series No. 2004–01 (Amsterdam: De Netherlandsche Bank).
- Bindseil, Ulrich, 2001, “A Coalition-Form Analysis of the ‘One Country-One Vote’ Rule in the Governing Council of the European Central Bank,” International Economic Journal. 15 (1): pp. 141–64.
- Blinder, Alan, 1998, Central Banking in Theory and Practice (Cambridge, Massachusetts: MIT Press).
- ———, 2006, “Monetary Policy by Committee: Why and How?” DNB Working Paper No. 90 (Amsterdam: De Netherlandsche Bank).
- ——— and John Morgan, 2005, “Are Two Heads Better Than One? Monetary Policy by Committee,” Journal of Money, Credit and Banking, Vol. 37 No. (5), pp. 798–811.
- Chappell, Henry W. Jr., Rob Roy McGregor, and Todd Vermilyea, 2004, “Majority Rule, Consensus Building, and the Power of the Chairman: Arthur Burns and the FOMC,” Journal of Money, Credit, and Banking, Vol. 36 (June), pp. 407–22.
- D’Amato, Marcello, and Riccardo Martina, 2005, “Credibility and Commitment of Monetary Policy in Open Economies,” European Journal of Political Economy. Vol. 21 No. (4), pp. 872–902.
- Deutsche Bundesbank, 1992, “Restructuring the Bundesbank,” Monthly Report. (August): pp. 48–53.
- European Central Bank (ECB), 2003, “The Adjustment of Voting Modalities in the Governing Council,” Monthly Bulletin. (May): pp. 73–83.
- Fry, Maxwell, DeAnne Julius, Lavan Mahadeva, Sandra Roger, and Gabriel Sterne, 2000, “Key Issues in the Choice of Monetary Policy Framework,” in Lavan Mahadeva and Gabriel Sterne (eds.) Monetary Frameworks in a Global Context. (London: Routledge), pp. 1–216.
- Fujiki, Hiroshi, 2005, “The Monetary Policy Committee and the Incentive Problem: A Selective Survey,” Monetary and Economic Studies. (October): pp. 37–82.
- Gerlach-Kristen, Petra, 2006, “Monetary Policy Committees and Interest-Rate Setting,” European Economic Review. Vol. 50 No. (2), pp. 487–507.
- ———, Hans Peter Grüner, Alexandra Kiel, and Elisabeth Schulte, 2003, “Information Acquisition and Decision Making in Committees: A Survey,” European Journal of Political Economy. Vol. 21 No. (3), pp. 563–97.
- Goodfriend, Marvin, 2005, “Comment on Fujiki,” Monetary and Economic Studies. (October): pp. 83–87.
- Hermalin, Benjamin E., and Michael S. Weisbach, 2001, “Boards of Directors as an Endogenously Determined Institution: A survey of the Economic Literature,” NBER Working Paper #8161 (Cambridge: National Bureau of Economic Research).
- International Monetary Fund (IMF), 2003, Annual Report, Appendix II (Washington).
- Ize, Alain, 2006, “Spending Seigniorage: Do Central Banks Have a Governance Problem?” IMF Working Paper 06/58 (Washington: International Monetary Fund).
- Levy-Yeyati, Eduardo, and Sturzenegger, Federico, 2005, Classifying Exchange Rate Regimes: Deeds vs. Words, European Economic Review, Vol. 49 No. (6), pp. 1603–35.
- Lombardelli, Clare, James Proudman, and James Talbot, 2005, “Committees versus Individuals: An Experimental Analysis of Monetary Policy Decision Making,” International Journal of Central Banking. Vol. 1 No. (1), pp. 181–205.
- Lybek, Tonny, 1998, “Elements of Central Bank: Autonomy and Accountability,” Monetary and Exchange Affairs Department Operational Paper No. 98/1 (Washington: International Monetary Fund).
- ———, 1999, “Central Bank Autonomy, and Inflation and Output Performance in the Baltic States, Russia, and other Countries of the Former Soviet Union, 1995–97,” IMF Working Paper No. 99/4 (Washington: International Monetary Fund).
- ———, and JoAnne Morris, 2004, “Central Bank Governance: A Survey of Boards and Arrangements,” IMF Working Paper 04/226 (Washington: International Monetary Fund).
- Meade, Ellen, and Nathan Sheets, 2005, “Regional Influences on FOMC Voting Patterns,” Journal of Money, Credit, and Banking. Vol. 37 No. (4), pp. 661–677.
- Méon, Pierre-Guillaume, 2006, “Majority Voting with Stochastic Preferences: The Whims of a Committee are Smaller than the Whims of Its Members,” Working Paper No. 06-05, RS Dulbea, Université Libre de Bruxelles.
- Mirzoev, Tokhir, 2004, “Limited Commitment, Inaction and Optimal Monetary Policy,” Ohio State University.
- Parkinson, C. Northcote, 1957, Parkinson’s Law (New York: Ballantine Books), reprinted in September 1975.
- Piketty, Thomas, 1999, “The Information-Aggregation Approach to Political Institutions,” European Economic Review. Vol. 43 No. (4-6), pp. 791–800.
- Posen, Adam, 1995, “Declarations Are Not Enough: Financial Sector Sources of Central Bank Independence,” in Ben Bernanke and Julio Rotenberg (eds.) NBER Macroeconomics Annual 1995 (Cambridge: MIT Press).
- Reinhart, Carmen, and Kenneth Rogoff, 2004, “The Modern History of Exchange Rate Arrangements: A Reinterpretation,” Quarterly Journal of Economics, Vol. 119 No. (1), pp. 1–48.
- Riboni, Alessandro, and Francisco Ruge-Murcia, 2006, “The Dynamic (In)efficiency of Monetary Policy by Committee,” University of Montreal.
- Rogoff, Kenneth, 1985, “The Optimal Degree of Commitment to an Intermediate Monetary Target,” Quarterly Journal of Economics. Vol. 100 No. (4), pp. 1169–1190.
- Romer, David, 1993, “Openness and Inflation: Theory and Evidence,” Quarterly Journal of Economics. Vol. 108 No. (4), pp. 869–901.
- Rose, Andrew K, 2006, “Size Really Doesn’t Matter: In Search of a National Scale Effect,” Journal of the Japanese and International Economies. (forthcoming).
- Schein, Edgar H., 1999, Process Consultation Revisited, Addison-Wesley.
- Sibert, Anne, 2006, “Central Banking by Committee,” DNB Working Paper 91.
- Svensson, Lars E. S. O., 2001, Independent Review of the Operation of Monetary Policy in New Zealand: Report to the Minister of Finance. Available on the Reserve Bank of New Zealand’s website: www.rbnz.govt.nz/monpol/review/indrevopmonpol.pdf.
- Tuladhar, Anita, 2005, “Governance Structures and Decision-Making Roles in Inflation Targeting Central Banks,” IMF Working Paper WP/05/183 (Washington: International Monetary Fund).
- Vandenbussche, Jerome, 2006, “Preference and Judgment Aggregation in Monetary Policy Committees: A Survey,” IMF Working Paper. Forthcoming. (Washington: International Monetary Fund).
- Waller, Christopher, 1989, “Macroeconomic Policy Games and Central Bank Politics,” Journal of Money, Credit and Banking. 21 (November), pp. 422–31.
- ———, 1992, “A Bargaining Model of Partisan Appointments to the Central Bank,” Journal of Monetary Economics. Vol. 29 No. (3), pp. 411–28.
- ———, 2002, “Policy Boards and Policy Smoothing,” Quarterly Journal of Economics. Vol. 115 No. (1), pp. 305–39.
- ——— and Carl Walsh, 1996, “Central Bank Independence, Economic Behavior, and Optimal Term Length,” American Economic Review. Vol. 85 No. (5), pp. 1139–54.
- Woodford, Michael, 2003, Interest and Prices: Foundations of a Theory of Monetary Policy (Princeton, New Jersey: Princeton University Press).

*Content derived from the PDF chapter/section titled REFERENCES in _wp06281.*

---


_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2006/_wp06281.pdf_