Decentralization of public service provision has been at the top of policy agendas in numerous countries over the past decades, involving services such as education, health, public transport, energy supply, and water and sewerage systems. Developing and middle-income countries, in particular, have been transferring responsibilities from a central or regional level down to the municipal one. Recent examples are the experiences of Chile, Argentina, Bolivia, Brazil, and Colombia in Latin America; India, Thailand, Vietnam, and the Philippines in Southeast Asia; South Africa, Senegal, Ethiopia, and Uganda in Africa; Ukraine, Serbia, and Bulgaria in Eastern Europe.
This empirical analysis benefits through an unusually clean and simple decentralization criterion: autonomy over the education service was assigned to cities solely depending on whether they exceeded the threshold of 100,000 inhabitants in 2002. This criterion rules out some typical obstacles to the identification of the effects of higher local autonomy: endogenous selection into autonomy by a selected group of local authorities, or the impossibility of disentangling the decentralization process from nationwide changes occurring at the same time. The provision of public education in Colombia is a case worth analyzing, as it represents an instance of decentralization limited to a subset of local authorities, but without performance-driven selection into it: this paper is able to offer new insights on the service decentralization debate benefiting from a quasiexperimental setup. Moreover, this paper isolates the effects of devolving decision powers without the interference of contemporaneous fiscal or political changes – which often come along with decentralization processes. In fact, the Colombian reform transferred managerial responsibility to the local level but left local taxation powers and local representation unaltered.
The empirical strategy adopted in order to isolate the effects of local autonomy is a municipal and year fixed-effects model, which is able to account for permanent differences between local authorities and for nationwide changes over time. I verify that, before the decentralization reform, the performance trends of municipalities which would become autonomous in 2002 were comparable to those of their nontreated counterparts – even when looking within specific development ranges. Identification of the effect through a regression discontinuity (RD) design would, in principle, be suitable to the reform context as well, but it has been discarded due to the sample size being too modest for such a data-intensive strategy.
Using 13-year-long panel data on standardized student test scores, which proxy education quality, I show that higher autonomy has proven beneficial for highly developed municipalities, but it had detrimental effects for less-developed municipalities. The development-related performance differences grow stronger over time, indicating a gradual manifestation of the consequences of the change in management. The quality differences appear to affect the intensive margin of education quality, since they are not explained by changes in the size or socioeconomic composition of the student pool.
I explore the channels at work behind the arising gap in test scores, by studying the detailed municipal education expenditure data and a set of administration quality indicators. Due to the unavailability of pre-reform data, this part of the analysis is not causal but merely suggestive. Nevertheless, its results are helpful toward building a data-driven opinion on the mechanisms underlying the effects on education quality. Figures suggest that within-country heterogeneity in local administration capacity may have played an important role in explaining heterogeneity in outcomes. A contribution due to differences in local financial resources is not precisely identified but cannot be excluded.
The findings of this paper speak to the effects of large-scale administrative decentralization reforms and to their potentially heterogeneous effects in contexts characterized by significant subnational diversity. This message represents a relevant reference for future public service decentralization reforms, especially if planned in low- and middle-income contexts.
Heterogeneity in the effects of decentralization is modeled in work by Bardhan and Mookherjee (2000, 2002, 2005, 2006), who show how the combination of strong local elites and weak local institutions can cause decentralization to yield underprovision of services to the local poor. Further channels for diversity of impacts across places and people are illustrated in the reviews by Kaiser (2006) and, with a special focus on developing countries, Juetting et al. (2005). These reviews and the vast majority of empirical literature fail to establish any clear link between decentralization and poverty reduction, in addition to documenting higher advantages for the rich with respect to the poor in decentralized contexts.
Focusing on literature related to the key message of this paper – heterogeneity in the impact of decentralization across local development levels – we find studies describing correlations between indicators of local welfare and the spending decisions of local politicians, but without establishing causal relationships between the two. Reinikka and Svensson (2004) find that decentralized school grants in Uganda were subject to local elite capture, but less so in better-off communities. Local governments are found to be more responsive to citizen’s needs when the electorate is more informed and when better institutions are in place, in studies by Besley and Burgess (2002) on India and Ferraz and Finan (2011) on Brazil. Faguet and Sanchez (2008, 2014) focus on local financial independence: they look at Colombian municipalities’ balance sheet data and establish negative associations between dependence on central government transfers and expenditure on education, but a positive association with public and private school enrollment rates.
Turning the attention to causal analyses, there are a number of studies that aim at isolating the effects of
To the best of my knowledge, there are very few studies analyzing the effects of
Starting in the 1980s, Colombia has been undergoing a progressive decentralization process involving political governance, fiscal structure, and the delivery of public services; various authors have looked at the outcomes of this gradual process, some in a qualitative and some in a quantitative fashion. Focusing on education outcomes, Borjas and Acosta (2000), Vergara and Simpson (2001), and Caballero (2006) comprehensively illustrate the dynamics and descriptive trends of decentralizing the public education system over the 1990s, agreeing on generally undistinguished results. Sometimes, this type of administrative decentralization is labeled as “devolution” in literature, referring to situations in which the activities of subnational units of government are substantially outside the direct control of the central government (Rondinelli et al., 1983).
Colombia is structured into local authorities as follows: there are 32 departments, These represent the regional level, equivalent to “states” in the US or “provinces” in Argentina. Colombia is considered among the most administratively decentralized countries in Latin America, but it is fiscally very centralized (Alesina et al., 2000; Toro, 2006). Law 60 / 1993 (Congreso, 1993) (distributing competencies across levels of government and assigning resources accordingly), Law 115 / 1994 - the “Comprehensive Education Act” (Congreso, 1994), and respective follow-up decrees. For the official document motivating the reform, see: “
Regarding the management of public education, the reform Law 715/2001 (Congreso, 2001) yielded the fundamental change of a clear-cut allocation of responsibility over the service to either municipalities or departments. Municipalities that counted ≥100,000 inhabitants in the year 2002 became “certified in education”, meaning these became responsible for the public education service on their territories and recipients of the education transfers from the central government. I refer to these as “autonomous municipalities” hereafter. Municipalities with <100,000 inhabitants were “not certified”, and their public education was run by the departments they belonged to. I call these “nonautonomous municipalities”. The next subsection further clarifies the concept of autonomy and discusses the shift in responsibilities.
The 40 municipalities certified in 2001 account for around one third of Colombia’s population and pupil share; their size ranges from 105,000 to >2 million inhabitants.
The reform arranged for a transition period of 2 years, 2002 and 2003, during which autonomous local authorities took over the school infrastructure, prepared for the effective management of the service with the assistance of departments, and had the opportunity to reorganize staffing plans on their territories. During these 2 years, temporary financial transfer amounts were set, and from 2004 onward, the new transfer system became fully operational. During the transition period, the new city-level management was not operational yet – it is better described as a time of preparation for the upcoming change and, thus, analogous to pre-reform years.
The 2001 decentralization reform affected not only the education service but also the provision of health care and other smaller public services, such as water and sewerage management. Nevertheless, these other services were decentralized in
Table 1 summarizes the education competencies of local authorities before and after the 2001 reform, in addition to indicating the percentages of education transfers to which they are entitled.
Education Responsibilities and transfers by level of government
Central government | |||
---|---|---|---|
Set school curriculum | Set teacher wages | Set general guidelines | Financial transfers to local authorities |
Local authorities | |||
Up to 2002 (Law 60/1993) | From 2002 onward (Law 715/2001) | ||
Transfers: | 84% to department | Transfers: | 100% to municipality |
Teacher hiring, training and | Teacher hiring, training and | ||
placement | Departments and | placement | Municipality only |
Transfers: | 97% to department | ||
Teacher hiring, training and placement | Department only |
As illustrated in the table, the reform left the role of the central government unchanged but polarized managerial responsibilities and financial transfers among local authorities. Before decentralization, departments were recipients of the bulk of education transfers, and municipalities were de facto quite restrained in their decisions ( Municipalities were responsible for allocating teachers across schools With, currently, only 3% of the total funds still flowing to nonautonomous municipalities, and with predetermined use. These funds need to be spent entirely on school infrastructure and school material, according to departments’ directions (
The reform also brought an adjustment in the allocation formulas of education resources to local authorities. In broad outlines, up to 2001, the majority of education transfers were assigned based on the number and seniority of teachers employed, with some adjustment based on number of inhabitants, local poverty, and administrative efficiency. From 2002 onward, pupil headcount gained importance in the allocation criteria – even though the number of teachers kept playing a key role – with minor adjustments for local poverty and population density, as before. These changes applied to transfers to
The population figures that were used for the 2001 reform were released by the National Administrative Department of Statistics (
Beyond its use in the 2001 reform, the 100,000-inhabitant cutoff does not play any significant role in Colombia’s legislation and it is not used in other matters involving municipal public service provision. The 100,000 figure appears in a municipal classification scheme that is performed every fiscal year by the central government, based on a combination between current inhabitant count and current municipal revenues. In combination with appropriate current revenues, 100,000 inhabitants may represent the lower bound for a “first category” city. Law 136/1994 and Law 617/2000. The seven categories and their relative inhabitant cutoffs are as follows: Special (500,001 or above), First (100,001–500,000), Second (50,001–100,000), Third (30,001–50,000), Fourth (20,001–30,000), Fifth (10,001–20,000), and Sixth (10,000 or below).
The sharp population cutoff rule described above, which was used to assign autonomy to cities, probably calls to mind RD as an attractive identification strategy. In fact, a previously circulated version of this paper Published as This is the main sample used in the previous RD-based version of the analysis. The more restricted sample of Cortés (2010) includes cities between 20,000 and 180,000 inhabitants; the full sample includes cities between <10,000 and >500,000 inhabitants.
Colombia has a long running tradition of standardized testing in public schools; That is, students completing 11 years of schooling. The first 9 years are compulsory, and the final 2 years are optional. However, I show and briefly discuss the results for Critical Reading and Sciences as well.
The development level of Colombian municipalities is being evaluated periodically by government agencies: relevant data are collected by the National Statistics Office (DANE), and the summary indicators are calculated by the National Planning Department (DNP). Up to the year 2013, the most informative and widely used indicator on local development was the Municipal Development Index (hereafter, MDI Translation from the original
Districts are four large local authorities in Colombia, whose nature is mixed between departments and municipalities; previously, before 2002, these enjoyed autonomy over education matters, and they are excluded from the analysis. Bogotá, Barranquilla, Cartagena, and Santa Marta. The municipalities of Armenia (Department of Quindio) and San Juan de Pasto (Department of Nariño).
In a robustness check in Section A4 in Appendix, I change the sample by restricting it around the population threshold. This is done in order to alleviate concerns about city size or confounders related to it playing an important role in explaining the main results. The development-related heterogeneity in impact persists, and even strengthens, as I consider cities that are more similar to each other in size.
The aim is to identify the impact of municipal autonomy over education on student test scores and to pin down any heterogeneous patterns that the effect might display across different levels of local development. Student achievement across the national territory is likely to be code-termined by observable and unobservable factors that are specific to each local area and that might also correlate with city size or local development. A municipality fixed-effects model allows us to account for such factors in a flexible way, without the need for listing them all explicitly.
Let us begin with the following basic fixed-effects model:
where the test scores in municipality
I will call Eq. (1) the “naïve” model, because it can only estimate the
where
Achieving identification through our fixed-effects models (1) and (2) relies on the assumptions of linearity in the fixed effects, as well as on the conditional independence assumption
A particularly valuable asset in our context is the clear-cut autonomy assignment rule that was used: out of municipal control and a singular event in time. The same is true for the local development measure, which was taken
Standard errors are clustered by municipality in all main specifications. The municipal level is the level of treatment by reform design, and we expect most of the correlation in test scores to occur at the municipal level due to the institutional setting. Section A4.3 in Appendix addresses the different ways of computing standard errors.
In the baseline model (2), This is in the same spirit of the exercise performed by Galiani et al. (2008) in their paper on Argentinian school decentralization.
In order to verify whether the expected over-time consolidation of impact is actually corroborated in the data, after estimating the over-time average treatment effect, I run model (2) selecting postreform time periods that are increasingly distant from the year 2001. I predict that
Table 2 shows the main estimation of the consequences of the 2001 decentralization reform on local education quality. Column (1) shows the estimation of the “naïve” model: we can see that on average, emancipation on educational matters was beneficial for cities, as the mean test scores increased by 0.67 points – around 0.3 standard deviations of the municipal average test scores. This overall positive result, however, hides important heterogeneity – as hypothesized – which is unveiled in Column (2), which reports the results of our baseline model. I find a strong interaction between the level of local development at the time of autonomy acquisition and the impact of autonomy itself, and the linear approximation of such interaction is 0.06 points for each additional positive step on the MDI scale. These estimates imply that the average test scores in cities at the lower end of the MDI spectrum are negatively affected by autonomy, while those at the higher end of the spectrum are positively affected. The MDI threshold at which the effect point estimate switches from being negative to positive is around 40. Analyzing the MDI distribution in our sample (plotted in Figure 1; Figure A2 in Appendix), one can observe that two thirds of all municipalities lie below an MDI of 40, and close to 20% of those that acquired autonomy through the 2001 reform lie in this range.
The effect of municipal autonomy on test scores
Period average | Over-time evolution | ||||||
---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | |
Naive | Baseline | 2002–2003 | 2004–2005 | 2006–2007 | 2008–2009 | 2010–2012 | |
Autonomy | 0.67 | −2.53 | −0.67 | −1.17* | −1.47 | −2.73 | −5.54 |
(0.21) | (0.87) | (0.62) | (0.67) | (0.70) | (1.00) | (1.44) | |
Autonomy × MDI | 0.06 | 0.02 | 0.03* | 0.04 | 0.07 | 0.14 | |
(0.02) | (0.01) | (0.01) | (0.01) | (0.02) | (0.03) | ||
Municipality FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Time dummies | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
N | 8,734 | 8,734 | 2,742 | 2,665 | 2,707 | 2,705 | 3,367 |
N groups | 692 | 692 | 692 | 692 | 692 | 692 | 692 |
0.51 | 0.51 | 0.51 | 0.77 | 0.69 | 0.44 | 0.44 | |
Mean | 42.34 | 42.34 | 41.33 | 41.54 | 42.69 | 41.89 | 42.41 |
FE, fixed effects; SE, standard errors.
Table 2 continues with Columns (3)–(7), which report the results of the time-progression exercise described in Section 5.1. As expected from intuition, the reform impact and its heterogeneity across local development intensify over time. In the years immediately following the reform (2002–2003), no effects are detected at any MDI level. Starting 2004–2005, statistically significant positive effects appear for highly developed cities with MDI >70, extending to those >50 in the years 2006–2007. In 2008–2009, low-developed cities with MDI <20 start showing statistically significant losses with respect to the pre-reform period and, at the end of our observation window (2010–2012), those <30 also show the same. Using these estimates, I illustrate the over-time escalating heterogeneity in impact as follows. Figure 2 shows the coefficient estimates for
The descriptive statistics in Table A1 in Appendix shows that the pre-reform standard deviation of municipal average test scores is 1.52 points, and the postreform standard deviation is 2.30 points, which helps in assessing the proportion of the main results in Table 2.
On average, the 2001 reform increased local education quality by 0.44 pre-reform standard deviations (or 0.29 postreform ones) for autonomous cities, but with highly uneven distribution of the impact across development levels. Looking at the extremes of the development distribution, autonomous cities in the highest decile – characterized by a 2001 Development Index >60 – saw average test score increases of 0.70 pre-reform standard deviations (0.47 post-reform ones) over the 10 years following the reform. On the other hand, autonomous cities in the lowest development decile – characterized by a 2001 Development Index <33 – experienced test score deterioration of around 0.35 pre-reform standard deviations (0.24 postreform ones).
These effects are large and are characterized, as seen before, by a distinct intensification over time: by the end of the observation period – 10 years after the reform implementation – the impacts reach double the size of the aforementioned period averages. The decentralization reform induced substantial inequality in local education quality, to the favor of highly developed municipalities and to the loss of low-developed ones.
In Appendix Table A2 in Appendix, I also show the estimation results for two additional subjects, which are typically included in international assessment programs: Critical reading and Sciences. Both “Critical reading” and “Sciences” were introduced to Saber11 starting in 2014, as a result of a restructuring of the examination (ICFES, 2013); before that year, “Critical reading” was split into “Language” and “Philosophy” components, while “Sciences” was separated into “Physics”, “Chemistry”, and “Biology”. I therefore construct “Critical reading” and “Sciences” scores by taking the arithmetic mean of their 2000–2012 components.
While accounting for differences in levels, the fixed-effects strategy used for identification relies on the assumption that counterfactual This discussion is inspired by Angrist and Pischke (2009), Chapter 5.
Leads and lags
(1) | (2) | |
---|---|---|
Naive | Baseline | |
y2000 × Aut. (× MDI) | −0.42 | −0.01 |
y2001 × Aut. (× MDI) | −0.33 (0.22) | −0.01 |
y2003 × Aut. (× MDI) | −0.31 | −0.01 |
y2004 × Aut. (× MDI) | −0.33 | −0.01 |
y2005 × Aut. (× MDI) | −0.14 (0.18) | 0.00 (0.00) |
y2006 × Aut. (× MDI) | 0.20 (0.31) | 0.00 (0.01) |
y2007 × Aut. (× MDI) | 0.02 (0.17) | 0.00 (0.00) |
y2008 × Aut. (× MDI) | 0.43 | 0.01 |
y2009 × Aut. (× MDI) | 0.68 | 0.01 |
y2010 × Aut. (× MDI) | 1.12 | 0.03 |
y2011 × Aut. (× MDI) | 1.11 | 0.03 |
y2012 × Aut. (× MDI) | 0.68 | 0.02 |
Municipality FE | Yes | Yes |
Time dummies | Yes | Yes |
N | 8,734 | 8,734 |
N groups | 692 | 692 |
0.51 | 0.51 | |
Mean | 42.34 | 42.34 |
In Section A4, I show the results for an alternative method of seeking support for the hypothesis of common pre-reform behavior of treated and nontreated cities, by the level of development. It consists in augmenting the fixed-effects equations with development-specific time trends and check whether this addition makes the treatment redundant in explaining outcomes. This approach is used, among others, by Besley and Burgess (2004) in their paper on labor regulation in India.
If educational outcomes in cities characterized by different levels of development could be explained by distinct over-time evolution patterns, then autonomy assignment should not matter anymore and our estimates of Defined as MDI being above or below 40, which is the threshold at which the main results found the reform effect to switch from positive to negative.
I present an exercise based on the main results so far described, with the purpose of illustrating the over-time evolution in performance for highly developed and low-developed cities – both in absolute terms and relative to each other. It is important to emphasize that the following exercise and figures
Based on the results of Table 2, I divide cities into highly developed and low-developed depending on whether their MDI in 2001 was above or below 40: recall that cities with an MDI >40 improved, on average, their performance after obtaining autonomy, while those with MDI <40 declined on average. From Table 2, Column (2): 2.53 / 0.06 = 42.16, which I round to 40 for clarity and without changes in conclusions.
Subfigure (a) focuses on the highly developed group and shows the performance trends of autonomous and nonautonomous cities separately. One can observe that the performances were quite similar to each other during the pre-reform years (2000–2001) and during the transition period; then, a performance gap opens up, starting in the mid-2000s, growing wider over time. These patterns had emerged already in our main results. As an additional result, the figure suggests that the most dynamic group of the two is the autonomous one, whose performance improvement reveals itself as the driver of the test score divergence during the second half of the decade. Subfigure (b) looks at the low-developed group and again shows the performance of autonomous and nonautonomous cities separately. As for their highly developed counterparts, similar performance between autonomous and nonautonomous cities can be observed before the reform and during early postreform years, while a performance fork slowly opens up around the middle of our observation window. Once again, the driver of the divergence appears to be the autonomous group, as illustrated by its performance decline relative to the national average. Finally, Subfigure (c) plots the four groups of cities against each other. An additional upshot here is that even performance trends between highly developed and low-developed cities were not too distant from each other’s in the early 2000s. The subfigure also reveals that a more modest development-related performance gap arises over time even between nonautonomous cities (dashed lines), but the combination with autonomy greatly amplifies it (solid lines).
Section 3.2.1 and Table 1 described how the 2001 reform determined an important change of managerial regime for those municipalities that obtained autonomy over education, while those that did not can be considered “untreated”. Nevertheless, it may be worth devoting a discussion to the contingency in which nonautonomous municipalities were also in a certain sense treated by the reform – and there are two potential scenarios that come to mind. In the first, let us assume that, contrary to what is suggested by pre-reform reports and figures, municipalities did actually enjoy nonnegligible power on education matters (e.g., through unobserved lobbying actions) and lost it after 2001. In the second scenario, let us assume departments began behaving differently after the largest cities left their responsibility so that nonautonomous cities started to be treated differently by departments as a consequence of the reform.
In both of these cases, our reform estimates would represent a combination of the effect of greater autonomy for the larger cities and of the “other treatment” received by the smaller cities. In fact, we can show this more formally as follows Credit and thanks to an anonymous referee for this formalization.
be the outcomes for cities that receive autonomy in 2002 (Type-A cities), where (α
be the outcomes for cities that do not receive autonomy in 2002 (Type-B cities), where
where This embodies the classical assumption of no time-varying unobservables affecting the two groups differently.
The case that
after the reform, nonautonomous cities experienced changes, but these were unrelated to their level of development;
after the reform, nonautonomous cities experienced changes, with disproportional gain for highly developed cities and penalization of low-developed ones;
after the reform, nonautonomous cities experienced changes, with disproportional penalization for highly developed cities and gain for low-developed ones.
Option 1 clearly leaves the leading message unaltered. Option 2 would imply that baseline results represent, in fact, a lower bound of the true interaction between autonomy and development. I find that highly developed autonomous cities do better than what we would expect in the absence of autonomy, but if that expectation is based on “control” cities,
In sum, it is appropriate to recognize the impossibility of fully excluding the chance that cities with <100,000 inhabitants may have experienced changes in their education service after the 2001 reform – even though the analysis of the institutional setting and anecdotal evidence suggest otherwise. In this section, I have discussed how this possibility would affect the results of this paper, and conclude that its main contribution of showing development-contingent outcomes following the decentralization of public education would carry through.
One may wonder whether the estimated impacts represent an actual change in local education quality, or whether they might be explained by changes in the pool of test takers, i.e., a compositional effect. A possible conjecture, for instance, could be that low-developed cities used their autonomy to promote rather-inclusive education policies, while the highly developed ones favored upper-class policies instead. This would translate into wider high school participation but lower average grades in the former group, and more-restricted participation but higher average grades in the latter group. In fact, Faguet and Sanchez (2014) claim positive associations of the gradual decentralization process in Colombia with both public and private school enrollment rates over the period 1994–2004, and the previously mentioned RD-based working paper by Cortés (2010) finds positive effects on private enrollment from the 2001 reform.
I check for compositional effects of this sort by estimating the baseline model (2) using the number of test takers and the share of disadvantaged-background test takers as outcomes.
The number of test takers is log-transformed, so that the estimated impacts approximate the percentage changes. Disadvantaged-background test takers are those characterized by low socioeconomic status, defined by whether the family lives on <2 minimum salaries at the time in which the exam is taken, as self-reported by the student; the information is missing for years 2004–2007.
The results are illustrated in Figures 6 and 7, which are drawn based on the results reported in Tables A3 and A4 in Appendix. I find a 16% decrease in the size of the average test-taker pool of autonomous cities after the reform, but the reduction is not related to development at any point in time and is thus unable to explain the development-dependent pattern in test score outcomes. I am not able to pin down any significant changes in the number of test takers from private schools either (not shown).
In conclusion, I find no evidence to support the conjecture that the treatment effect on test scores are of compositional nature, and I attribute the differences in findings with respect to the two studies mentioned above to the differences in time periods examined and empirical methods used In particular, the 2010 paper uses data on the period 2002–2006 (only 2 years past the reform transition period) and is based on RD identification: see Subsection 3.2.2 for a discussion on why such results may have to be taken with caution. The 2014 paper looks at the decade prior to the reform I analyze and establishes correlations rather than causal impacts between public service outcomes and local financial independence measures.
In this section, I offer suggestive evidence that helps in inferring the channels through which the 2001 decentralization reform may have been inducing development-related performance differences between cities. Based on the literature on service delivery decentralization in developing countries, I explore two classical dimensions that have the potential to explain local performance differences: financial resources and skills (Rondinelli, 1981). By financial resources, I mean the amount of per capita funding that the local authority can rely on and spends on the service – in this case, education. By skills, I broadly mean local administration quality, which I additionally decompose into diligence (application of rules), capacity (amount of human and technological capital available to the administration), and corruption (fraudulent behavior involving the public administration).
Data on both funding and administration quality are available only for the postreform years – some starting in 2002, while others in 2005 or even 2008. Financial data stem from detailed balance sheet reports that municipalities are required to file at the end of each financial year to departments and to the central government. “ DNP-DDTS (
Due to the unavailability of pre-reform data and of financial data for nonautonomous cities, it is impossible to aim at producing causal evidence in this section. Comparisons between pre- and postreform behaviors or outcomes are not feasible. The following analysis focuses solely on autonomous cities and provides comparisons between highly developed and low-developed ones: the goal is to use the data to build informed opinions on the likelihood of each channel to have contributed to the policy effects. As in the illustration in Section 6.2, highly developed and low-developed cities are defined according to the MDI threshold emerging from the earlier main results: cities with an MDI >40, which on average gained due to the autonomy assignment; and cities with an MDI <40, which on average deteriorated in educational performance.
Table 4 compares the financial and administration indicators of highly developed and low-developed autonomous cities. Due to the small sample size available, only the most clear-cut differences are identified at statistically significant levels. Looking at per-pupil education spending, I am unable to pin down any statistically significant differences between the two groups, neither in the total amount nor in any of the three subcategories (salaries, infrastructure and material, and others). Considering point estimates of the total spending amount, highly developed cities exceed low-developed ones by 8% – which may indicate a nonnegligible difference in resources devoted to education. Still looking at nonprecise point estimates, the “Others” spending category – which includes items such as extracurricular activities, school transport, and additional teacher training programs – appears to be the most unbalanced toward high-development cities, with a 24% larger spending compared to the low- developed counterparts. On the other hand, and somewhat unsurprisingly, spending in infrastructure is approximately 11% higher in low-developed cities. Low-developed cities see, on average, 2.58 fewer students per teacher with respect to highly developed ones.
Education finance and administration quality in autonomous cities
High-D | Low-D | Difference (%) | N | N cities | ||
---|---|---|---|---|---|---|
Education finance | ||||||
Total spending | 1,175.24 (28.11) | 1,088.50 (61.19) | 86.74 (66.24) | (+8%) | 242 | 35 |
Salaries | 939.99 (21.00) | 861.49 (45.35) | 78.50 (49.41) | (+9%) | ||
Infrastructure and materials | 97.38 (6.44) | 109.75 (13.66) | −12.37 (15.10) | (−11%) | ||
Others | 87.18 (6.77) | 70.21 (13.12) | 16.97 (15.65) | (+24%) | ||
Student–teacher ratios | 27.33 (0.23) | 24.75 (0.36) | 2.58 | (+10%) | 145 | 35 |
Transfers received | 1,147.48 (48.92) | 1,130.76 (25.60) | 16.72 (60.20) | (+2%) | 334 | 35 |
Administrative indicators | ||||||
---|---|---|---|---|---|---|
Correctness standards | 79.30 (1.46) | 71.40 (4.93) | 7.90 | (+11%) | 236 | 35 |
Capacity | 72.46 (1.56) | 43.85 (4.20) | 28.61 | (+65%) | 236 | 35 |
Corruption | 98.70 (6.03) | 109.58 (22.94) | −10.88 (28.26) | (−10%) | 89 | 32 |
**
On the revenue side, there is no significant difference in per-student central government transfers that municipalities receive to finance education services (
Along the dimension of administration quality, the differences between the two groups of cities are more striking. The first indicator I look at measures the “correct application of accounting standards” (
In view of the above findings, it is not possible to exclude a contribution of the financial aspect toward explaining the different impacts that autonomy has had on highly developed and low-developed cities. The higher tax capacity of highly developed cities, combined with the new responsibility and accountability brought about by decentralization, may have spurred higher education spending and led to an improvement in quality. I am abstracting from issues such as different funding
In summary – while bearing in mind that the analysis illustrated in this section does not claim to prove causal relationships and, instead, provides merely suggestive evidence – the data at hand, combined with the decentralization theory and results of past empirical studies, support the hypothesis that the large heterogeneity in local administration capacity may have played an important role in explaining the discrepant impacts that educational autonomy has brought to Colombian cities. An additional contribution by differences in local financial resources cannot be ruled out.
In this paper, I took advantage of an unusually simple administrative decentralization reform setting to demonstrate that cities characterized by different levels of local development have been affected differently by receiving managerial autonomy over the public education service. In the 10 years following the responsibility takeover, cities in the higher development deciles have significantly improved their local test score performance, while test scores have declined for the lowest-developed cities. The secondary school test performance I use as an outcome in this analysis is considered to be a good indicator of education quality in the country, and I find that the effect is not driven by apparent changes in the composition of test takers. The reform effects, and thus the education quality gaps, arise in the postreform periods and are decisively growing stronger over time. The empirical identification strategy I use – a municipal and year fixed effects model – is simple but robust and well suited to the context being analyzed. I am able to convincingly support the hypothesis that autonomous and nonautonomous municipalities were on similar performance trends before decentralization was implemented, even when allowing for different local development levels. Considering the characteristics of the Colombian reform, which left unchanged local taxation powers and the political structure, the treatment effects I estimate can be attributed to the sole devolution of managerial responsibility to the local level.
This paper represents a relevant contribution to the empirical literature on administrative decentralization outcomes, which often struggles to isolate well-identified treatment effects due to complexities in reform content or in the institutional context. A further desirable addition to the decentralization debate is given by the specific focus on local development levels as drivers of inequality, when combined with managerial autonomy.
Looking for clues on the channels of impact heterogeneity, I study financial and administrative postreform data for individual municipalities. Due to data limitations, I am not able to provide causal evidence on these channels; however, the analysis is helpful toward building informed hypotheses. Highly developed and low-developed municipalities appear to benefit of the same per-pupil transfers from the central government, but I am not able to exclude with certainty that highly developed municipalities have been devoting additional own resources to the financing of local public education. Importantly, highly developed municipalities perform significantly better on different local administration quality indicators with respect to low-developed cities, in particular, the indicators measuring skills and capacity at the local authority’s disposal. One can picture the administrative bodies of low-developed cities being overwhelmed by the batch of new tasks and responsibilities that came along with the freedom over education management – and mistakes, delays, and bad decisions taking their toll on service quality. On the contrary, highly developed city administrations may have been better prepared to cope with the new duties, so that the benefits of decentralization dominated. These are conjectures formed on the basis of the data at hand and guided by the results of previous decentralization literature. They are consistent with this study’s main finding that the devolution of autonomy on public education has caused remarkably heterogeneous results, depending on municipal development levels, so that highly developed and low-developed cities have been drifting apart in their performance over the postreform years.
Colombia has been one of the Latin American leaders in education investment over the past decades, and it distinguished itself among the countries with the fastest progress in education quality (Barrera-Osorio et al., 2012). Nevertheless, not all Colombian education reforms have achieved their desired results, and some have failed to safeguard equity in the distribution of impacts. The findings of this paper sound a note of caution in the design of decentralization reforms, especially in contexts characterized by subnational heterogeneity in wealth and development. Oversimplified decentralization criteria might prove useful for subsequent impact evaluation studies but are certainly not the best guarantee of equity in outcomes across the involved parties. When handing responsibilities in public service delivery to the local level, less-advantaged local authorities may need additional and well-planned support in order to prevent regional inequality from growing and decentralization backfiring for some segments of the population.