Análisis de los efectos no financieros de la política de distribución del ICMS para la Educación en Ceará

Carneiro, Diego; Silva, Cristiano; Irffi, Guilherme

doi:10.1590/S0104-40362025003305013

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ARTICLE • Ensaio: aval. pol. públ. educ. 33 (128) • Nov 2025 • https://doi.org/10.1590/S0104-40362025003305013 linkcopiar

Análisis de los efectos no financieros de la política de distribución del ICMS para la Educación en Ceará

Autoría SCIMAGO INSTITUTIONS RANKINGS

Resumen

Ceará se ha destacado por sus buenos resultados en las evaluaciones nacionales de la Educación básica, lo que se atribuye, en parte, por la literatura, al cambio realizado en 2007 en la forma de distribución del ICMS (Impuesto sobre la Circulación de Mercancías y Servicios), que comenzó a premiar a los municipios con buen desempeño en los primeros años de la Educación primaria. A pesar de que existe bastante evidencia que atestigua la eficacia de esta legislación, los mecanismos de su funcionamiento aún no están completamente aclarados. De esta manera, el presente trabajo investigó los efectos no financieros de la política, explorando una alteración en la ley que incluyó como criterio de distribución el desempeño en el 9º grado, pero que no produjo efectos prácticos. Así, se utilizó una combinación del modelo de diferencias en diferencias con emparejamiento genético para verificar si este nuevo cambio afectó el desempeño de los alumnos de las redes municipales. Se constató que el cambio “anunciado” elevó las calificaciones de los estudiantes del 9º grado en un 1,2%, lo que indica que la política de distribución tiene efectos independientes del aumento del gasto. Los resultados permanecen consistentes incluso al alterar el método de estimación y el grupo de control utilizados.

Palabras clave:
ICMS Educativo; Educación Básica; Ceará

Estates	Municipal schools (2015)	Municipal schools (2017)	Variation (%)	State schools (2015)	State schools (2017)	Variation (%)
Maranhão	95,31	93,09	-2.33%	11,79	8,77	-26%
Piauí	28,91	28,33	-2.02%	12,08	10,52	-13%
Ceará	89,54	92,96	3.82%	18,20	12,91	-29%
Rio Grande do Norte	18,03	19,31	7.11%	15,52	14,56	-6%
Paraíba	23,36	25,04	7.22%	19,26	18,14	-6%
Pernambuco	52,99	58,32	10.05%	51,32	42,36	-17%
Alagoas	27,35	26,49	-3.13%	11,19	10,66	-5%
Sergipe	12,05	11,70	-2.89%	11,17	9,67	-13%
Bahia	117,76	121,95	3.55%	52,60	43,21	-18%
Sudeste	323,54	270,51	-16.39%	677,74	55,94	-17%
Sul	81,02	85,32	5.30%	218,39	23,34	7%
Centro-Oeste	40,65	40,68	0.06%	138,28	14,37	4%
Norte	111,29	113,71	2.18%	135,77	13,43	-1%
Nordeste	465,29	477,19	2.56%	203,13	17,08	-16%
Brasil	1,021,80	987,41	-3.37%	1,373,31	12,42	-10%

		Ceará		Nordeste (excluding Ceará)
		Mean	Standard Deviation	Mean	Standard Deviation	Difference of Means
2015	Ln Mathematics	5.533	0.083	5.463	0.067	0.070*
	Ln Portuguese	5.525	0.068	5.446	0.080	0.079*
	Ind_Infraestructure	0.640	0.096	0.603	0.096	0.037*
	Ind_Socio_Economic	0.396	0.013	0.402	0.014	-0.006*
	Teachers_Higher_Educ	0.944	0.138	0.907	0.183	0.038*
	Employee_rate	0.568	0.222	0.556	0.205	0.011
	Participation_rate	0.968	0.066	0.842	0.121	0.126*
2017	Ln Mathematics	5.552	0.096	5.460	0.086	0.092*
	Ln Portuguese	5.560	0.075	5.468	0.083	0.092*
	Ind_Infraestructure	0.622	0.091	0.585	0.097	0.037*
	Ind_Socio_Economic	0.394	0.013	0.401	0.015	-0.008*
	Teachers_Higher_Educ	0.958	0.120	0.933	0.168	0.025*
	Employee_rate	0.621	0.274	0.601	0.377	0.020
	Participation_rate	0.970	0.069	0.862	0.114	0.108*

Regressors	Coefficient	Standard Error	p-value	Coefficient	Standard Error	p-value
Panel A: Pre-Genetic Matching Sample
	Mathematics			Portuguese
Constant	5.223*	0.03	<0.001	5.132*	0.032	<0.001
Time	-0.007*	0.002	<0.001	0.019*	0.002	<0.001
Treatament	0.049*	0.004	<0.001	0.059*	0.003	<0.001
Time* Treatament	0.025*	0.005	<0.001	0.017*	0.004	<0.001
Ind_Infraestructure	0.047*	0.01	<0.001	0.041*	0.01	<0.001
Ind_Socio_Economic	0.091*	0.067	0.175	0.264*	0.071	<0.001
Teachers_Higher_Educ	0.058*	0.005	<0.001	0.067*	0.006	<0.001
Employee_rate	0.013*	0.007	0.06	0.008	0.004	0.068
Participation_rate	0.137*	0.009	<0.001	0.139*	0.01	<0.001
Observations	7126			7126
R² / R² adjusted	0.190 / 0.189			0.222 / 0.222
Panel B: Post-Genetic Matching Sample
	Mathematics			Portuguese
Constant	5.236*	0.065	<0.001	5.168*	0.055	<0.001
Time	0.005	0.005	0.291	0.015*	0.004	<0.001
Treatament	0.02*	0.004	<0.001	0.021*	0.004	<0.001
Time* Treatament	0.012*	0.007	0.065	0.02*	0.006	<0.001
Ind_Infraestructure	-0.004*	0.018	0.811	-0.018	0.016	0.251
Ind_Socio_Economic	0.174*	0.14	0.216	0.406*	0.121	0.001
Teachers_Higher_Educ	0.034*	0.011	0.002	0.053*	0.01	<0.001
Employee_rate	0.015	0.024	0.552	0.007	0.013	0.595
Participation_rate	0.176*	0.029	<0.001	0.136*	0.022	<0.001
Observations	2534			2534
R² / R² adjusted	0.083 / 0.080			0.132 / 0.129

	Coefficient	Standard Error	p-value	Coefficient	Standard Error	p-value
Panel A: Pre-Genetic Matching Sample
	Mathematics			Portuguese
Constant	5.289	0.061	0.001*	5.211	0.050	0.001*
Time	-0.012	0.007	0.105	0.020	0.007	0.006*
Treatament	-0.003	0.006	0.593	-0.010	0.006	0.128
Time* Treatament	0.026	0.008	0.002*	0.012	0.008	0.121
Ind_Infraestructure	-0.051	0.02	0.01*	-0.045	0.016	0.005*
Continue
Continuation
Ind_Socio_Economic	0.103	0.133	0.439	0.383	0.110	0.001*
Teachers_Higher_Educ	0.013	0.014	0.33	0.025	0.012	0.037*
Employee_rate	0.009	0.004	0.008*	0.005	0.003	0.062
Participation_rate	0.225	0.027	0.001*	0.184	0.024	0.001*
Observations	2.394			2.394
R² / R² adjusted	0.052/0.048			0.096 / 0.093
Panel B: Post-Genetic Matching Sample
	Mathematics			Portuguese
Constant	5.289	0.061	0.001*	5.216	0.050	0.001*
Time	-0.012	0.007	0.11	0.019	0.007	0.008*
Treatament	-0.003	0.006	0.608	-0.009	0.006	0.148
Time* Treatament	0.026	0.008	0.002*	0.013	0.008	0.096
Ind_Infraestructure	-0.051	0.020	0.01*	-0.044	0.016	0.006*
Ind_Socio_Economic	0.103	0.133	0.438	0.367	0.110	0.001*
Teachers_Higher_Educ	0.013	0.014	0.328	0.024	0.012	0.048*
Employee_rate	0.009	0.004	0.008*	0.005	0.003	0.059
Participation_rate	0.224	0.028	0.001*	0.191	0.024	0.001*
Observations	2.394			2.394
R² / R² adjusted	0.053/0.049			0.096/0.093

	Coefficient	Standard Error	p-value	Coefficient	Standard Error	p-value
Panel A: Pre-Genetic Matching Sample
	Mathematics			Portuguese
Constant	5.126*	0.037	<0.001	4.931*	0.042	<0.001
Time	0.006*	0.002	0.013	0.026*	0.003	<0.001
Treatament	0.103*	0.005	<0.001	0.124*	0.005	<0.001
Time* Treatament	0.015*	0.007	0.039	0.006	0.006	0.326
Ind_Infraestructure	0.068*	0.013	<0.001	0.065*	0.014	<0.001
Ind_Socio_Economic	-0.429*	0.084	<0.001	-0.182*	0.094	0.054
Teachers_Higher_Educ	0.081*	0.006	<0.001	0.102*	0.007	<0.001
Employee_rate	0.019*	0.01	0.043	0.017*	0.007	0.019
Participation_rate	0.207*	0.013	<0.001	0.217*	0.014	<0.001
Observations	7.126			7.126
R² / R² adjusted	0.276 / 0.275			0.310 / 0.309
Panel B: Post-Genetic Matching Sample
	Mathematics			Portuguese
Constant	5.294*	0.088	<0.001	5.083*	0.082	<0.001
Time	0.014*	0.006	0.027	0.02*	0.006	0.001
Treatament	0.042*	0.006	<0.001	0.048*	0.006	<0.001
Time* Treatament	0.004	0.009	0.675	0.011	0.008	0.195
Ind_Infraestructure	0.009	0.03	0.76	-0.008	0.027	0.778
Ind_Socio_Economic	-0.660*	0.186	<0.001	-0.221	0.177	0.214
Teachers_Higher_Educ	0.044*	0.019	0.023	0.052*	0.018	0.004
Employee_rate	0.052*	0.011	<0.001	0.033*	0.01	0.001
Participation_rate	0.247*	0.036	<0.001	0.24*	0.035	<0.001
Observations	2.410			2.410
R² / R² adjusted	0.105 / 0.102			0.136 / 0.133

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[1] Source: Prepared by the authors (2025).

[TFN1] * p-valor < 0,05