Staying in Power: How Does Political Continuity Shape Debt
Jaime Bonet, Jhorland Ayala, and Jorge Guerra
XIII Jornadas Iberoamericanas de Financiación Local
The findings and opinions are those of the authors and do not reflect the views of Banco de la República or its Board of Directors
Introduction and motivation
Empirical strategy and data
Results
Conclusions
Content
Political leeway: Intensive and Extensive margin
Introduction and motivation
Political leeway: Intensive and Extensive margin
Empirical strategy and data Results
Results
Content
Summary
municipal level in Colombia.
exogenous variation given for the electoral win/loss margin.
– Municipalities governed by the same political party across successive elections tend to see a 0.25% increase in debt levels for every percentage point increase in their win margin.
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Literature review and contribution
(1) Literature: How politicians change fiscal policy to remain in power:
electoral cycles at subnational levels (Drazen and Eslava, 2010; Raveh and Tsur, 2020) .
outcomes (Frey, 2021; Chortareas et al., 2016; Litschig and Morrison, 2010).
subnational levels (Hallerberg and Strauch, 2002).
(2) Main contribution: How fiscal policy changes once politicians hold in power
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The capacity for indebtedness is being mismanaged at the local levels
Source: Calculations by the authors based on information from the National Planning Department (DNP) and the Ministry of Finance.
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0
20
40
60
80
100
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
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2015
2016
2017
2018
2019
2020
Interest payments/operational savings
Departments
Municipalities
Legal Limit
Payment capacity Solvency indicator
120 100
90
0
10
20
30
50
40
60
70
80
1994
1995
1996
1997
1998
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2003
2004
2005
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2008
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2010
2011
2012
2013
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2015
2016
2017
2018
2019
2020
debt/current fiscal revenue
Departments
Municipalities
Legal limit
However, some municipalities have substantially increased their indebtedness
same mayor serving three of those terms.
2022.
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Conclusions
Content
Introduction and motivation
Political leeway: Intensive and Extensive margin
Empirical strategy and data
Results
Data
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Data: win margin vs vote share - 2015
The graph shows the total vote share for the repeater party plotted against the repeater win-loss margin—the difference between the repeater party’s vote share and the largest non-repeater party’s vote share—both in 2015. Observations within 2 percentage points of the threshold at zero are in black. The diagonal line is the hypothetical one-to-one relationship between the two variables in an election with only two parties.
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Repeaters
Non-repeaters
Having won or lost by a narrow voting margin
Kink Discontinuity Regression Design: Identification
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Kink Discontinuity Regression Design: Estimation
Results
Content
Introduction and motivation
Political leeway: Intensive and Extensive margin
strategy
Empirical strategy and data
Municipalities governed by the same political party across successive elections have an
0.25% increase in debt levels for each pp in win margin
Note: The figure displays the log of 2016 per capita debt across eight percentage bins against the 2015-win margin. The left side illustrates the relationship between non-repeaters (who won in 2011 but lost in 2015). The right side illustrates the relationship between repeaters (who won both in 2011 and 2015).
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Outcome | Municipal gross per capita debt (log) | ||||
| (1) | (2) | (3) | (4) | (6) |
Main explanatory variables | |||||
non-treated: β | 0.012 | 0.012 | -0.006 | 0.003 | -0.007 |
| (0.036) | (0.036) | (0.036) | (0.035) | (0.035) |
jump: τ | -0.01 | -0.011 | -0.007 | -0.009 | -0.008 |
| (0.013) | (0.013) | (0.012) | (0.012) | (0.012) |
Slope difference: ϕ | 0.211*** | 0.209*** | 0.239*** | 0.222*** | 0.251*** |
| (0.066) | (0.066) | (0.066) | (0.066) | (0.066) |
| | | Covariates | | |
Historic Inst. Acc. | ✘ | | | | |
Cont.Int. Acc. | ✘ | ✘ | | | |
Geography | ✘ | ✘ | ✘ | | |
Fixed effects | ✘ | ✘ | ✘ | ✘ | |
Outcome mean (level) | 0.068 | 0.068 | 0.068 | 0.068 | 0.068 |
Banwidth | 1 | 1 | 1 | 1 | 1 |
R2 | 0.030 | 0.032 | 0.058 | 0.112 | 0.176 |
Observations | 707 | 707 | 707 | 707 | 707 |
Robust to:
This debt increase is more pronounced during election years
It the effect high or low ? Barranquilla case
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Debt per capita (million COP)
Introduction and motivation
Conclusions
Content
Political leeway: Intensive and Extensive margin
Empirical strategy and data Results
Conclusions & policy recommendations
prevent unsustainable debt accumulation due to political continuity.
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Thanks
More information about CEER
Notes: Columns 1 and 2 reports the mean of each variable for repeaters and non-repeaters respectively. The third column presents the difference between the two groups and the fourth has the p-value correspondent.
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Data Descriptives | Repeater | Non-repeater | Difference | P-value difference |
| (1) | (2) | (3) | (4) |
Main outcome variable | | | | |
Municipal per capita debt (millions COP) | 0.11 | 0.09 | 0.02 | 0.00 |
Main explanatory variables | | | | |
Repeater | 1.00 | 0.00 | 1.00 | 0.00 |
Win margin (pp) | 0.13 | -0.16 | 0.30 | 0.00 |
Vote share (%) | 0.45 | 0.20 | 0.25 | 0.00 |
Council share (%) | 0.37 | 0.24 | 0.13 | 0.00 |
Covariates | | | | |
Historic institutional access | | | | |
Year of creation | 1865.77 | 1869.31 | -3.53 | 0.30 |
Distance to coloniral royal road (km) | 20.03 | 28.35 | -8.33 | 0.00 |
Contemporary institutional access | | | | |
Rurality index (% rural population) | 0.58 | 0.55 | 0.04 | 0.00 |
Distance to department capital (km) | 76.20 | 82.61 | -6.40 | 0.00 |
Geography | | | | |
Population (thousands) | 30.21 | 37.21 | -7.00 | 0.06 |
MASL | 1250.97 | 1111.09 | 139.88 | 0.00 |
Latitude | 5.91 | 5.63 | 0.27 | 0.00 |
Longitude | -74.67 | -74.76 | 0.09 | 0.04 |
Distance to Magdalena River (km) | 96.99 | 99.75 | -2.76 | 0.18 |
Distance to coast (km) | 215.64 | 216.82 | -1.17 | 0.75 |
Observations | 225 | 482 | 707 | 707 |
Assumptions: no manipulation – McCrary test
Note: The figure displays a histogram of the win-loss margin to visually examine whether the margin is continuous at the threshold. The bins are set at 1 percentage point (pp). Below is the density plot from the McCrary (2008) test, which assesses the presence of any discontinuity in the density of the win-loss margin. The Kernel used is triangular.
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Assumptions: continuity across covariates
Note: Table presents regressions of the main control variables against the running variable. This graph displays local averages of the outcomes in 8-percent bins plotted against the win margin, complemented by overlaid smoothed linear regression lines based on raw data on each side of the cutoff
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Distance to colonial road
Distance to dept. capital
Longitude
Assumptions: continuity across covariates
Note: Table presents regressions of the main control variables against the running variable. This graph displays local averages of the outcomes in 8-percent bins plotted against the win margin, complemented by overlaid smoothed linear regression lines based on raw data on each side of the cutoff
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Population
Year of creation
Rurality index
Main results: bandwidths
Note: The table presents the parameter ϕ across different bandwidths for the study of political continuity's effect on municipal debt, including all covariates and fixed effects. The first column uses the entire range from
-1 to 1 as the bandwidth. The second column applies an optimal bandwidth (h^*) of 0.154 based on the minimum standard error method, covering 430 observations. The third column doubles this optimal bandwidth to include more observations. The fourth column explores a bandwidth of 0.27, positioned between the optimal and double bandwidth, to examine the sensitivity of the estimated effects.
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Outcome | Municipal gross per capita debt (log) | |||
Bandwidth | Global | h* | 2h* | ℎ∗ ≤ ℎ ≤ 2ℎ∗ |
| (1) | (2) | (3) | (4) |
non-treated: β | -0.007 | 0.015 | 0.057 | 0.061 |
| (0.035) | (0.117) | (0.059) | (0.07) |
jump: τ | -0.008 | 0.016 | -0.012 | -0.013 |
| (0.012) | (0.015) | (0.014) | (0.015) |
Slope difference: ϕ | 0.251*** | -0.134 | 0.23** | 0.255** |
| (0.066) | (0.186) | (0.106) | (0.124) |
Covariates | All | All | All | All |
Fixed effects | | | | |
Outcome mean | 0.068 | 0.066 | 0.066 | 0.067 |
Banwidth | 1 | 0.154 | 0.308 | 0.27 |
R2 | 0.176 | 0.243 | 0.201 | 0.200 |
Observations | 707 | 430 | 622 | 590 |
Main results: placebo test (changing pseudorandom v)
Note: Figure 9 displays the results of the permutation test for the RDK analysis, where each estimate is derived from randomly assigning the dependent variables of one municipality to another while keeping overall debt levels constant. Panel (a) shows the probability density functions for all ϕ placebos in gray and the actual ϕ in black, with its confidence intervals marked by continuous and dotted lines. Panel (b) presents the cumulative density functions, illustrating that the bulk of placebo effects cluster below the lower confidence limit of the actual effect, reinforcing the non-random nature of electoral impacts on municipal debt, and affirming the methodological soundness of the RDK approach.
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PDF CDF
Main results: changing electoral results (2011, 2019)
Note: Table 5 explores the impact of electoral results from different years (2011 and 2019) in 2016 municipal debt levels, holding debt constant to test the influence of political continuity. Results across all columns show no significant differences, confirming the null hypothesis that variations in electoral outcomes do not affect municipal debt levels in 2016, suggesting the debt observed is independent of past or future election results.
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Outcome | Municipal gross debt | ||
| Actual | Placebo | Placebo |
Treated and 𝑣𝑖 from | 2015 | 2011 | 2019 |
Debt from | 2016 | 2016 | 2016 |
non-treated: β | -0.007 | -0.0 | 0.031 |
| (0.035) | (0.04) | (0.035) |
jump: τ | -0.008 | 0.004 | -0.018 |
| (0.012) | (0.012) | (0.011) |
Slope difference: ϕ | 0.251*** | -0.072 | -0.023 |
| (0.066) | (0.072) | (0.073) |
Outcome mean | 0.068 | 0.063 | 0.066 |
R2 | 0.176 | 0.318 | 0.294 |
Covariates | Yes | Yes | Yes |
Fixed effects | Yes | Yes | Yes |
Observations | 707 | 339 | 501 |
What if we switch 2015 v data for 2011 and 2019 v data
Should be no effect
Possible mechanism: council share
Note: Table 5 explores the impact of electoral results from different years (2011 and 2019) in 2016 municipal debt levels, holding debt constant to test the influence of political continuity. Results across all columns show no significant differences, confirming the null hypothesis that variations in electoral outcomes do not affect municipal debt levels in 2016, suggesting the debt observed is independent of past or future election results.
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