MUITO ALÉM DO MÍNIMO: por que os municípios brasileiros alocam suas próprias receitas para a saúde?

Machado, José Angelo; Quaresma, Guilherme; Araújo, Carmem E. Leitão

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Sumário

Original Article • Rev. Bras. Ci. Soc. 36 (107) • 2021 • https://doi.org/10.1590/3610700/2021 copiar

MUITO ALÉM DO MÍNIMO: por que os municípios brasileiros alocam suas próprias receitas para a saúde?

Autoria SCIMAGO INSTITUTIONS RANKINGS

Resumo

O artigo identifica razões para a superalocação de receitas próprias com saúde pelos municípios brasileiros que, desde a promulgação da EC 29/2000, as ampliaram progressivamente até ultrapassar em muito o piso constitucional. Modelos de regressão linear com efeitos mistos em painel foram utilizados para o período 2008-2017. As hipóteses testadas estão relacionadas aos efeitos da escala populacional dos municípios; nível de desenvolvimento econômico e social da região em que se inserem; grau de incorporação de recursos tecnológicos de média e alta complexidade; esforço despendido com atenção básica; orientação político partidária dos governos municipais; além da alocação em outras funções e sub funções orçamentárias de interesse da saúde. Os resultados apontam para dois fatores que melhor explicam a variável dependente: escala populacional, em relação inversa, e concentração de serviços de maior complexidade tecnológica, em relação direta.

Palavras-chave:
Federalismo fiscal; Emenda Constitucional 29/2000; despesa com saúde; receitas próprias; municípios

Data source	Variables	Information
Siops	Own revenue expenditure on healthcare	Dependent variable in this research. It presents the municipality’s expenditure with their own revenue on healthcare as declared to Siops.
	Region where the municipality is located	IBGE regional division: North; Northeast; Southeast (reference); South; and Midwest.
	Population size of the municipality	Six categories of population size: up to 5,000 inhabitants; between 5 and 10 thousand inhabitants; between 10 and 20 thousand inhabitants; between 20 and 50 thousand inhabitants; between 50 and 100 thousand inhabitants; and over 100 thousand inhabitants.
Munic	Mayor’s gender	Gender was dichotomized between male (reference) and female.
	Mayor’s education level	Education divided into six categories: incomplete primary school; complete primary education; incomplete high school; complete high school; incomplete higher education; and complete higher education (reference).
	Age	The mayor's age divided between six categories: between 20 and 30 years (reference); between 30 and 40 years; between 40 and 50 years; between 50 and 60 years; between 60 and 70 years; and over 70 years.
	Ideological spectrum of the mayor’s party	Classification of the mayors’ parties: left; center-left; center-right (reference); right; other.
SIH	ICSAP	Hospitalizations for conditions which are sensitive to Primary Healthcare in the municipality.
SIH	Hospitalizations	Ratio between high and medium complexity hospitalizations in the municipality and resident population in the state, per thousand inhabitants.
Finbra / Siconfi	Primary Healthcare	Municipal expenditure using its own resources on primary healthcare.
	Hospital Care	Municipal expenditure using its own resources on hospital care.
	Health Surveillance	Municipal expenditure using its own resources on health surveillance.
	Employment	Municipal expenditure using its own resources on employment.
	Primary School	Municipal expenditure using its own resources on primary education.
	Sanitation	Municipal expenditure using its own resources on sanitation.
	Sport and Leisure	Municipal expenditure using its own resources on sport and leisure.

Year	Database	Existing	Percentage
2008	5,482	5,565	98.51%
2009	5,520	5,565	99.19%
2010	5,495	5,565	98.74%
2011	5,384	5,565	96.75%
2012	5,175	5,570	92.91%
2013	5,389	5,570	96.75%
2014	5,169	5,570	92.80%
2015	5,394	5,570	96.84%
2016	5,344	5,570	95.94%
2017	5,453	5,570	97.90%

Year	Estimates
Year	Min.	1st Qu.	Median	Mean	3rd Qu.	Max.
2008	7.03	206.44	297.90	359.67	442.42	2866.01
2009	0.10	198.87	299.88	357.64	445.39	2964.61
2010	16.02	213.49	322.56	384.43	475.57	2862.74
2011	5.21	231.59	347.74	416.20	518.00	3085.11
2012	34.99	240.12	371.46	443.13	552.50	3406.61
2013	54.08	248.45	382.65	452.00	567.81	3584.16
2014	27.34	255.38	399.20	471.84	589.93	3529.78
2015	35.91	255.71	399.81	472.30	600.82	3457.13
2016	65.52	246.36	384.96	453.39	570.67	2864.94
2017	69.04	259.24	411.92	480.27	607.68	3038.00

Variables	Category	Coefficient
Mean Intercept	–	305.2816
Year	–	8.0980
Gender	Male	Reference
Gender	Female	-1.7049
Education	Incomplete Primary School	1.8773
	Complete Primary School	3.9050
	Incomplete high school	-2.3450
	Complete high school	0.5098
	Incomplete Higher Education	2.6193
	Complete Higher Education	Reference
Age	Less than 30 years	Reference
	Between 30 and 40 years	4.6146
	Between 40 and 50 years	4.7595
	Between 50 and 60 years	2.7042
	Between 60 and 70 years	2.9472
	Over 70 years	1.7052
Region	North	-162.1816
	Northeast	-171.1055
	Southeast	Reference
	South	-36.4302
	Midwest	-34.1590
Population	Up to 5,000 inhabitants	232.8852
	Between 5,000 and 10,000 inhabitants	122.1706
	Between 10,000 and 20,000 inhabitants	74.3522
	Between 20,000 and 50,000 inhabitants	37.8609
	Between 50,000 and 100,000 inhabitants	15.7269
	Over 100,000 inhabitants	Referência
ICSAP	–	-0.1659
Hospital production per thousand inhabitants	Medium Complexity	0.7679
Hospital production per thousand inhabitants	High Complexity	12.8200
Municipal expenditures	Primary Healthcare	0.1035
	Hospital Care	0.1540
	Health Surveillance	0.2047
	Employment	0.0537
	Primary School	-0.0482
	Sanitation	0.0442
	Sport and Leisure	0.0397
Ideological spectrum	Left	2.4078
	Center-Left	4.4163
	Center-Right	Reference
	Right	7.6606
	Others	-1.8868
Ideological spectrum * Year (interactive term)	Left * Year	-0.7723
	Center-Left * Year	-1.0150
	Center-Right * Year	Reference
	Right * Year	-0.0959

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