Identificação de subcentros de emprego: o caso do Município de São Paulo, Brasil

Campos, Rodger Barros Antunes; Chagas, André Luis Squarize

doi:10.1590/0103-6351/6236

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Sumário

Articles • Nova econ. 31 (03) • Sep-Dec 2021 • https://doi.org/10.1590/0103-6351/6236 copiar

Identificação de subcentros de emprego: o caso do Município de São Paulo, Brasil

Autoria SCIMAGO INSTITUTIONS RANKINGS

Resumo

Modelos teóricos com múltiplos centros consolidaram no debate especializado a questão do espraiamento urbano do emprego. Todavia, os métodos que identificam os lugares centrais não são ponto pacífico. O objetivo deste artigo é identificar e caracterizar os subcentros (Small Business District - SBD) no município de São Paulo, utilizando uma nova metodologia. Propomos uma metodologia em dois estágios: 1) Análise de Exploratória de Dados Espaciais e 2) Modelo de Preços Hedônicos Espacial. Como resultado, encontramos sete regiões que podem ser consideradas SBD.

Palavras-chave:
Economia Urbana; Distrito Comercial Central; Distrito Comercial Subcentro; Econometria Espacial

	2000				2012
Rank	District	Zone Area	Total of Employ.	Relative Particip.	District	Zone Area	Total of Employ.	Relative Particip.
1º	Itaim Bibi	SZ1	139,679	5.96%	Itaim Bibi	SZ1	293,925	7.48%
2º	Jardim Paulista	CZ	108,027	4.61%	Santo Amaro	SZ1	159,349	4.05%
3º	Santo Amaro	SZ1	102,929	4.39%	Jardim Paulista	CZ	156,443	3.98%
4º	Vila Mariana	SZ1	81,897	3.49%	República	CZ	153,793	3.91%
5º	Sé	CZ	80,250	3.42%	Vila Mariana	SZ1	152,247	3.87%
6º	Pinheiros	WZ	80,184	3.42%	Bela Vista	CZ	117,479	2.99%
7º	República	CZ	76,757	3.27%	Pinheiros	WZ	113,005	2.88%
8º	Lapa	WZ	64,122	2.73%	Barra Funda	WZ	103,759	2.64%
9º	Moema	SZ1	64,075	2.73%	Lapa	WZ	102,899	2.62%
10º	Bela Vista	CZ	59,079	2.52%	Moema	SZ1	95,862	2.44%
	Total		2,345,294	-			3,930,013	-

Weight Matrix	Moran’s I	P-value
Distance	0.365373	0.000
Queen	0.592239	0.000
Rook	0.595834	0.000
K-neighbors (K6)	0.469755	0.000

Cluster	Rook	Queen	6 neighbors	Distance
HH	47	52	38	74
LL	74	75	91	116
LH	4	5	4	36
HL	0	0	0	3
Not significant	185	178	177	81

	Level-Level	Log-Level	Level-Level	Log-Level	Level-Level	Log-Level	Level-Level	Log-Level
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.
CBD	-2.9E^-02	-1.5E^-06	3.5E^-02	6.5E^-06	-4.2E^-02	-5.8E^-06	-4.8E^-03	-2.2E^-06
CBD²	-	-	-3.1E^-06	-3.9E^-10	-	-	-1.9E^-06	-1.8E^-10
CONST	4.0E⁺⁰³	8.1E⁺⁰⁰	3.9E⁺⁰³	8.1E⁺⁰⁰	3.9E⁺⁰³	8.1E⁺⁰⁰	3.8E⁺⁰³	8.0E⁺⁰⁰
Control	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
SBD	No	No	No	No	Yes	Yes	Yes	Yes
Time Dummy	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Adjusted R²	0.73	0.78	0.73	0.78	0.74	0.79	0.77	0.79
F test	278^***	361^***	273^***	354^***	170^***	220^***	170^***	220^***
Moran’s I test	3.97E^-02	3.87E^-02	4.00E^-02	3.93E^-02	1.90E^-02	1.58E^-02	1.88E^-02	1.60E^-02

	Level-Level	Log-Level	Level-Level	Log-Level	Level-Level	Log-Level	Level-Level	Log-Level	Level-Level	Log-Level	Level-Level	Log-Level
	(9)	(10)	(11)	(12)	(13)	(15)	(15)	(16)	(17)	(18)	(19)	(20)
	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.
CBD	1.7E^-01*	5.3E^-05*	2.4E^-01*	5.4E^-05**	1.9E^-01*	5.5E^-05*	2.5E^-01*	5.8E^-05*	2.3E^-01*	6.5E^-05*	2.9E^-01*	6.9E^-05***
WCBD	9.3E^-02	7.1E^-06	-1.6E^-01	-1.1E^-04**	-4.5E^-03	8.2E^-07	-2.3E^-01	-1.1E^-04**	-2.1E^-02	-4.4E^-06	3.0E^-02	-5.6E^-05
CBD²	-	-	-2.8E^-06	4.3E^-10	-	-	-3.5E^-06	2.0E^-10	-	-	-4.8E^-06	-1.9E^-10
WCBD²	-	-	1.2E^-05	5.4E^-09***	-	-	1.0E^-05	4.9E^-09**	-	-	-2.1E^-06	2.3E^-09
CONST	2.2E^+3*	7.2^***	2.3E^+3*	7.3^***	2.3E^+2*	7.6^***	2.8E^+3*	7.5^***	1.9E⁺³	7.6^***	3.2e^+3*	7.5^***
Controle	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
SBD	No	No	No	No	No	No	No	No	No	No	No	No
Time Dummy	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Adjusted R²	0.76	0.81	0.76	0.81	0.76	0.80	0.76	0.81	0.76	0.80	0.76	0.8
F statistic	180^***	230^***	178^***	226^***	179^***	228^***	174^***	223^***	179^***	228^***	175^***	223^***
Moran’s I test	-2.8E^-03	-6.1E^-03	-3.1E^-03	-5.7E^-03	-2.9E^-03	-4.8E^-03	-3.2E^-03	-5.1E^-03	-3.3E^-03	-5.2E^-03	-3.5E^-03	-4.9E^-03
Weight Matrix	Distance (threshold)				5% times threshold				10% times threshold

	LOG-LEVEL			LOG-LEVEL	LOG-LEVEL	LINEAR	LINEAR	LINEAR
	(17)			(18)	(19)	(20)	(21)	(22)
	Direct Effect	Indirect Effect	Global Effect	Global Effect	Global Effect	Global Effect	Global Effect	Global Effect
CBD	5.43E^-05***	-1.95E^-04***	-1.41E^-04	-2.08E^-04	-1.28E^-04	-2.38E^-01	-4.55E^-01	-1.36E^-01
A1	-2.92E^-05***	7.30E^-04***	7.01E^-04	5.94E^-04	-3.22E^-05	2.09E⁺⁰⁰	1.52E⁺⁰⁰	-1.2E^-01
A2	-3.59E^-06	9.54E^-05	-	-	-	-	-	-
A3	-4.98E^-06	3.92E^-04	-	-	-	-	-	-
A4	3.37E^-05	-1.87E^-04	-	-1.04E^-03	-8.73E^-04	-2.49E⁺⁰⁰	-5.15E⁺⁰⁰	-2.73E⁺⁰⁰
A5	4.45E^-05	8.81E^-04	-	-	-	-	-	-
A6	-3.87E^-05	-3.40E^-03***	-3.40E^-03	-3.50E^-03	-1.83E^-03	-1.05E⁺⁰¹	-8.90E⁺⁰⁰	-
A7	-7.04E^-06	-2.58E^-03***	-2.58E^-03	-2.27E^-03	-	-6.61E⁺⁰⁰	-4.60E⁺⁰⁰	-
A8	6.79E^-05	4.11E^-03^***	4.11E^-03	4.44E^-03	2.37E^-03	4.36E^-01	4.09E^-01	3.86E^-01
A9	9.06E^-07	-4.22E^-04	-	-5.95E^-04	-7.13E^-04	-	-2.59E⁺⁰⁰	-2.22E⁺⁰⁰
A10	-3.91E^-05	-4.00E^-03***	-4.00E^-03	-	-	-	-	-
A11	7.79E^-05	4.44E^-03***	4.44E^-03	3.16E^-03	-	1.01E⁺⁰¹	-	-
A12	-7.29E^-05	2.71E^-03*	2.71E^-03	-	-	-	-	-
A13	-4.03E^-05	3.87E^-04	-	3.11E^-03	2.69E^-03	-	1.06E⁺⁰¹	-
A14	7.25E^-06	-1.35E^-03	-	-	-	-	-	-
A15	1.62E^-05	-4.85E^-03***	-4.85E^-03	-4.29E^-03	-2.50E^-03	-1.14E⁺⁰¹	-8.95E⁺⁰⁰	-
A16	5.82E^-06	1.36E^-03**	1.36E^-03	1.41E^-03	1.69E^-03	6.59E⁺⁰⁰	6.61E⁺⁰⁰	5.38E⁺⁰⁰
A17	-1.71E^-04*	-5.18E^-03***	-5.35E^-03	-3.65E^-03	-4.74E^-03	-2.46E⁺⁰¹	-	-1.36E⁺⁰¹
A18	2.58E^-04*	2.12E^-03	2.58E^-04	2.32E^-04	-	1.03E⁺⁰⁰	-	-
A19	-1.08E^-04	4.13E^-03	-	8.48E^-03	-	-	3.10E⁺⁰¹	-
A20	9.83E^-05	2.35E^-03	-	1.39E^-04	1.39E^-04	4.93E^-01	6.02E^-01	6.48E^-01
A21	-1.47E^-04**	-5.77E^-03***	-5.92E^-03	-6.18E^-03	-8.01E^-03	-2.30E⁺⁰¹	-1.90E⁺⁰¹	-5.74E^-01
A22	5.32E^-05	3.74E^-03***	3.74E^-03	3.97E^-03	4.92E^-03	1.22E⁺⁰¹	7.48E⁺⁰⁰	9.27E⁺⁰⁰
A23	4.55E^-05**	1.50E^-03***	1.55E^-03	1.59E^-03	4.80E^-05	7.92E⁺⁰⁰	7.68E⁺⁰⁰	2.16E^-01
A24	-3.46E^-05	-9.03E^-04*	-9.03E^-04	-	-	-7.22E⁺⁰⁰	-6.84E⁺⁰⁰	-
A25	4.05E^-05	-3.58E^-04	-	-	-	-	-	-
A26	-1.65E^-04	8.27E^-03		-1.99E^-04	-2.53E^-04	3.21E⁺⁰¹	3.25E⁺⁰¹	-7.31E^-01
A27	2.62E^-04**	-1.80E^-03	2.62E^-04	2.80E^-04	2.57E^-04	1.28E⁺⁰⁰	-2.59E⁺⁰¹	1.17E⁺⁰⁰
A28	8.70E^-05	-3.27E^-02	-	-2.93E^-02	-3.43E^-02	-	-	-1.55E⁺⁰²
A29	-2.93E^-05	1.13E^-02	-	-	-	-	-	-
A30	-2.71E^-04	1.85E^-02	-	-	1.81E^-02	5.57E⁺⁰¹	6.08E⁺⁰¹	8.45E⁺⁰¹
A31	3.92E^-05	-4.97E^-04	-	-	-	-	-	-
A32	-3.90E^-05	-2.08E^-03	-	-2.81E^-03	-6.08E^-05	-9.53E⁺⁰⁰	-1.04E⁺⁰¹	-2.24E^-01
A33	-3.58E^-05	1.61E^-04	-	-	-	-	-	-
A34	4.06E^-05	2.44E^-03	-	-	3.38E^-03	-	-	-
A35	-1.10E^-04	-8.16E^-03	-	-8.70E^-03	-	-	-2.47E⁺⁰¹	-
A36	1.68E^-04*	4.66E^-03	1.68E^-04	6.96E^-03	5.74E^-03	1.20E⁺⁰⁰	1.11E⁺⁰⁰	1.03E⁺⁰⁰
CONST	7.61^***	-	7.61^***	7.95^***	7.497.95^***	1.79E⁰³	3.11 E^03*	1.99
Weight Matrix	K1			K2	K3	K1	K2	K3
Control	Yes			Yes	Yes	Yes	Yes	Yes
Time Dummy	Yes			Yes	Yes	Yes	Yes	Yes
Adjusted R²	0.8155			0.8139	0.8115	0.7793	0.7762	0.7731
F statistic	134^***			132^***	130^***	107^***	105^***	103^***
Moran’s I test	-5.43E-03			-4.79E-03	5.16E-03	-4.40E-03	-1.99E-03	-3.13E-03

Sector Activities	Subcenters
Sector Activities	Belém	Vila Mariana	Jd. Paulista	Santa Cecília	Pinheiros	Campo Belo	Itaim Bibi
Agriculture, forestry, breeding, plant extractivism	0,0%	0,0%	0,0%	0,0%	0,4%	0,0%	1,2%
Manufacturing	24,1%	3,7%	2,1%	9,2%	4,7%	4,5%	2,2%
Food, beverages, and Industrial utility services ethyl alcohol industry	4,2%	0,1%	0,1%	0,7%	1,5%	0,2%	2,0%
Industrial utility services	0,0%	0,0%	0,1%	0,0%	0,2%	0,0%	3,0%
Construction	4,0%	6,6%	2,8%	7,6%	16,7%	23,7%	5,6%
Retail trade	10,5%	9,6%	10,2%	14,3%	13,9%	19,0%	8,7%
Wholesale trade	6,2%	3,7%	2,5%	4,4%	2,9%	3,0%	3,8%
Credit institutions, insurance, and capitalization	1,0%	1,4%	2,5%	0,9%	5,6%	2,4%	26,0%
Management and administration, real estate, securities, technical service	23,3%	34,0%	12,4%	38,4%	28,6%	21,6%	17,8%
Transport and communications	3,3%	3,0%	3,6%	4,7%	4,6%	5,7%	3,2%
Accommodation, food, repair, maintenance,	16,4%	20,8%	10,4%	15,1%	17,4%	13,6%	13,9%
Medical, dental, and veterinary services	4,8%	9,6%	49,2%	2,0%	1,3%	2,4%	9,0%
Teaching	2,2%	7,5%	4,0%	2,7%	2,1%	4,0%	3,7%

Minimum Wage	Subcenters
Minimum Wage	Belém	Vila Mariana	Jd. Paulista	Santa Cecília	Pinheiros	Campo Belo	Itaim Bibi
More than 20	1%	1%	2%	1%	6%	1%	6%
20 - 10	2%	3%	6%	2%	10%	3%	12%
10 - 5	8%	9%	15%	8%	17%	9%	18%
4 - 2	31%	39%	44%	46%	36%	32%	34%
1,51 - 2	26%	25%	18%	23%	16%	29%	13%
1,5 - 1,1	30%	17%	12%	17%	12%	23%	13%
Less/iqual than 1	4%	4%	2%	4%	3%	2%	4%

Education	Subceters
Education	Belém	Vila Mariana	Jd. Paulista	Santa Cecília	Pinheiros	Campo Belo	Itaim Bibi
Incomplete High School	30%	32%	16%	34%	25%	42%	20%
Complete High School	54%	43%	45%	50%	34%	36%	31%
Incomplete Higher Education	5%	5%	4%	4%	8%	5%	9%
Complete Higher Education	11%	19%	34%	11%	33%	17%	39%
Master´s	0,2%	1%	0,4%	1%	1%	0,3%	1%
PhD	0,0%	0,3%	1%	0,3%	0,1%	0,1%	0,4%

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[1] About the authors

Rodger Barros Antunes Campos - rodgerantunes@gmail.com

Associate Researcher in the Regional and Urban Economics (NEREUS), University of São Paulo, São Paulo, SP, Brazil.

ORCID: https://orcid.org/0000-0001-5478-6510

André Luis Squarize Chagas - achagas@usp.br

Departments of Economics, University of São Paulo, São Paulo, SP, Brazil.

ORCID: https://orcid.org/0000-0001-7870-8736