Figures and Tables for Corruption and Public Debt. March 20, 2015

Transcription

1 Figures and Tables for Corruption and Public Debt March 20,

2 1 Figures central government debt, % GDP ISL FIN SWE DNK AUS LUX AUT GBR IRL NOR DEU USA FRA BEL ESP PRT HUN corruption index SVK CZE GRC ITA datapoints of 2008 fitted values Figure 1: Central government debt vs. corruption in OECD countries Note Y-axis: central government debt, % GDP; datasource - World Bank s WDI. X-axis: index of corruption, 0 - smallest possible corruption, 1 - biggest possible corruption; datasource - Worldwide Governance Indicators, corruption index (linear transformation). Circles denote corresponding points in the dataset, dashed gray line is the trend line (fitted values). Slope coefficient of the trend line is 92.4 (statistically significant at 3% level) 2

3 Θ g 2 Θ g Θ g 8 Θ g Figure 2: Debt/capital dynamics Note Figures show transition paths of debt to capital ratio for different values of θ g - institutional checks on corruption. The computations are based on the following values for the model s parameters: θ τ = 0.7, ϕ = 1.3, η = 1, ϵ = 4, α = 3, µ =, d = 9, β =, γ = The initial values for state variables in all cases are k = , g = , b = 0 - as in the steady-state of the model without corruption and tax evasion. 3

4 tax rate corruption private capital public capital worker's productivity Θgov 6 Θgov 0.62 Figure 3: Selected variables dynamics under different θ g Note The computations are based on the following values for the model s parameters: θ τ = 0.7, ϕ = 1.3, η = 1, ϵ = 4, α = 3, µ =, d = 9, β =, γ = The initial values for state variables in all cases are k = , g = , b = 0 - as in the steady-state of the model without corruption and tax evasion. 4

5 government debt to GDP United States Turkey Italy Data source: IMF FAD Figure 4: Public debt dynamics in selected countries public debt, %GDP, without business cycles United States Turkey Italy Figure 5: Public debt net of business cycles in various countries Data source: IMF FAD, own calculations. Hodrick-Prescott filter, smoothing parameter Annual data, over

6 2 Tables Table 1: Equilibria with Different Institutional Safeguards against Corruption θ g τ u v b(1 + ϵ)/k Shortfall in y % % % % % % % % % % % % % % Notes: The computations are based on the following values for the model s parameters: κ = λ = 1, θ τ = 0.7, ϕ = 1.3, ϵ = 4, α = 3, µ =, d = 9, β =, γ =

7 Table 2: Budget Elasticity of Corruption θ g E t Notes: The computations are based on the following values for the model s parameters: κ = λ = 1, θ τ = 0.7, ϕ = 1.3, ϵ = 4, α = 3, µ =, d = 9, β =, γ = Table 3: Public debt and corruption (1) b/se control of corruption, WGI (6.852) real GDP per capita, USD (0.001) Constant 405 (5.844) N obs 51 Note: Standard errors in parentheses. * p <, ** p < 0.05, *** p < Dependent variable - public debt, %GDP. Sample: HIC and UMIC, non-rr, large. Large are countries with population over mln as of RR - resource-rich, according to the IMF s definition. HIC - high income countries, UMIC - upper middle countries, as of 2011, World Bank classification. All variables averaged over Regressions with additional controls have been tried. Results (signs and magnitudes of coefficients of interest) are qualitatively similar. 7

8 Table 4: Public debt cycles and corruption (1) b/se control of corruption, WGI (8.736) wgicor sq (3.949) real GDP per capita, USD (0.000) Constant (4.625) N obs 39 Note: Standard errors in parentheses. * p <, ** p < 0.05, *** p < Dependent variable - public debt cycles average amplitude, p.p. of GDP. Sample: HIC and UMIC, non-rr, large. Large are countries with population over mln as of RR - resource-rich, according to the IMF s definition. HIC - high income countries, UMIC - upper middle countries, as of 2011, World Bank classification. All variables averaged over Regressions with additional controls have been tried. Results (signs and magnitudes of coefficients of interest) are qualitatively similar. Table 5: Public debt, corruption, and economic growth (1) b/se L10.real GDP per capita, thousands USD (0.017) public debt, % GDP, av. last 10 years (0.005) control of corruption, av. last 10 years 77 (58) control of corruption X public debt (0.005) Constant (54) N obs 117 Note: Standard errors in parentheses. * p <, ** p < 0.05, *** p < Dependent variable - average GDP per capita growth in the last 10 years. Years included and 2011 (subject to availability of data on corruption). Sample: HIC and UMIC, non-rr, large. Large are countries with population over mln as of RR - resource-rich, according to the IMF s definition. HIC - high income countries, UMIC - upper middle countries, as of 2011, World Bank classification. Regressions with additional controls have been tried. Results (signs and magnitudes of coefficients of interest) are qualitatively similar. 8

9 Table 6: Variables used in regressions: Comparative statics UMICs included in sample HIC UMIC Name Source Mean S.d. Mean S.d. public debt, % IMF FAD GDP control of corruption, WGI WGI real GDP per WB WDI capita, thousand USD debt cycle amplitude, Section V p.p. GDP HICs included in Australia, Austria, Belgium, Canada, Cyprus, Czech Republic, Denmark, sample Estonia, Finland, France, Germany, Greece, Hong Kong, Hungary, Ireland, Israel, Italy, Japan, Korea, Netherlands, New Zealand, Portugal, Singapore, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, United Kingdom, United States Argentina, Belarus, Brazil, Bulgaria, Costa Rica, Croatia, Fiji, Jamaica, Latvia, Lebanon, Lithuania, Malaysia, Mauritius, Montenegro, Panama, Poland, Romania, Serbia, South Africa, Turkey, Uruguay Notes: Summaries for all variables are computed over HIC - high income countries, UMIC - upper middle income countries, as of 2011, World Bank classification. Excluded are small and resource-rich (RR) countries. Large are countries with population over mln as of RR - resource-rich, according to the IMF s definition. 9