A previdência pública impacta a nutrição de trabalhadores migrantes: evidências do seguro de pensão urbana na China

He, Zhipeng; Deng, Ye; Yu, Kang; Li, Lei

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Sumário

RURAL SOCIOLOGY • Cienc. Rural 51 (12) • 2021 • https://doi.org/10.1590/0103-8478cr20200829 copiar

A previdência pública impacta a nutrição de trabalhadores migrantes: evidências do seguro de pensão urbana na China

Autoria SCIMAGO INSTITUTIONS RANKINGS

RESUMO:

Este artigo usa os dados da pesquisa de “Emprego e demanda alimentar dos trabalhadores migrantes urbanos” para analisar empiricamente o impacto do seguro patrimonial urbano na estrutura de ingestão nutricional dos trabalhadores migrantes. O estudo constatou que: o seguro-pensão urbano mudou a estrutura de ingestão nutricional dos trabalhadores migrantes. Gordura e proteína substituíram os carboidratos e se tornaram a principal fonte de nutrição dos trabalhadores migrantes. Depois de controlar fatores como a renda e a intensidade do trabalho dos trabalhadores migrantes, o seguro de pensão urbana aumentou significativamente a ingestão de gordura e proteína dos trabalhadores migrantes em 13,5% e 8,8%, respectivamente, enquanto a ingestão de carboidratos dos trabalhadores migrantes não foi afetada. Significativamente afetado. A transformação da estrutura de ingestão nutricional dos trabalhadores migrantes aumentou sua ingestão calórica em 6,8%. Os testes de endogenia e robustez mostram que as conclusões acima são robustas. A análise de heterogeneidade mostra que não há diferença significativa no efeito do seguro previdenciário urbano sobre o aumento da ingestão de calorias para trabalhadores migrantes de diferentes níveis de renda e diferentes grupos etários.

Palavras-chave:
seguro previdenciário urbano; trabalhadores migrantes; ingestão calórica; estrutura nutricional; incerteza

Universidade Federal de Santa Maria Universidade Federal de Santa Maria, Centro de Ciências Rurais , 97105-900 Santa Maria RS Brazil , Tel.: +55 55 3220-8698 , Fax: +55 55 3220-8695 - Santa Maria - RS - Brazil
E-mail: cienciarural@mail.ufsm.br

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[1] E-mail: yukang888@163.com. ^*Corresponding author

Variables		Mean	Unit	Std. Err.
Dependent variables	Carbohydrate	305.75	g/day	122.07
	Fat	65.06	g/day	53.36
	Protein	67.27	g/day	30.61
	Calorie	2069.40	kcal/day	811.30
Independent variables	Urban pension insurance	0.17	%	0.37
Control variables	Monthly income（RMB）	3340.43	RMB	2859.41
	Light manual labour	0.16	%	0.37
	Middle manual labour	0.57	%	0.50
	Heavy manual labour	0.27	%	0.44
	BMI	22.23	Kg/m²	3.06
	Gender	0.58	%	0.49
	Age	35.84	year	11.10
	Middle school and below	0.66	%	0.47
	High school or junior college	0.30	%	0.46
	Bachelor and above	0.04	%	0.19
	Beijing	0.19	%	0.39
	Guang Dong	0.20	%	0.40
	Shan Dong	0.20	%	0.40
	Si Chuan	0.20	%	0.40
	Zhe Jiang	0.21	%	0.41
Observations	------------------------------------------------------------3315--------------------------------------------------------

Variables	Carbohydrate	Fat	Protein	Calorie
Urban pension insurance	0.026(0.021)	0.135^***(0.043)	0.088^***(0.021)	0.068^***(0.019)
Log of average	-0.019(0.018)	0.222^***(0.039)	0.075^***(0.019)	0.051^***(0.016)
Middle manual labour	0.012(0.021)	0.008(0.045)	0.011(0.021)	0.006(0.018)
Heavy manual labour	0.072^***(0.025)	0.115^**(0.056)	0.034(0.026)	0.061^***(0.022)
BMI	0.003(0.002)	-0.002(0.005)	0.001(0.003)	0.002(0.002)
Gender	0.164^***(0.017)	0.132^***(0.036)	0.131^***(0.017)	0.147^***(0.015)
Age	0.019^***(0.004)	0.014(0.009)	0.017^***(0.004)	0.016^***(0.004)
Age squared	-0.000^***(0.000)	-0.000^**(0.000)	-0.000^***(0.000)	-0.000^***(0.000)
High school or junior college	0.000(0.017)	0.088^**(0.035)	0.043^***(0.016)	0.021(0.015)
Bachelor and above	-0.023(0.038)	0.147^*(0.087)	0.080^**(0.040)	0.047(0.034)
Guangdong	-0.020(0.023)	0.596^***(0.051)	0.136^***(0.024)	0.142^***(0.021)
Shandong	-0.023(0.021)	-0.208^***(0.055)	-0.002(0.023)	-0.044^**(0.020)
Sichuan	-0.206^***(0.024)	0.477^***(0.048)	-0.012(0.023)	-0.010(0.020)
Zhejiang	-0.114^***(0.019)	0.029(0.050)	-0.067^***(0.023)	-0.087^***(0.019)
Constant term	5.279^***(0.156)	1.574^***(0.335)	3.069^***(0.158)	6.698^***(0.137)
Observations	3315	3315	3315	3315
R-squared	0.102	0.130	0.071	0.094

Variables	Carbohydrate	Fat	Protein	Calorie
Urban pension insurance	-0.004 (0.040)	0.199^** (0.081)	0.095^** (0.039)	0.083^** (0.034)
Urban pension insurance ^* middle-income group	0.054 (0.045)	-0.111 (0.091)	-0.024 (0.045)	-0.029 (0.039)
Urban pension insurance ^* high income group	-0.003 (0.071)	0.001 (0.139)	0.046 (0.071)	0.012 (0.062)
Log of average monthly income	-0.020 (0.019)	0.225^*** (0.042)	0.073^*** (0.019)	0.051^*** (0.017)
Other control variables	controlled	controlled	controlled	controlled
Observations	3315	3315	3315	3315
R-squared	0.102	0.130	0.072	0.094

Variables	Carbohydrate	Fat	Protein	Calorie
Urban pension insurance	0.024 (0.023)	0.131^*** (0.047)	0.077^*** (0.023)	0.065^*** (0.021)
Urban pension insurance ^* above 45 years old	0.013 (0.051)	0.022 (0.103)	0.058 (0.048)	0.015 (0.044)
Log of average monthly income	-0.019 (0.018)	0.222^*** (0.039)	0.076^*** (0.019)	0.051^*** (0.016)
Other control variables	controlled	controlled	controlled	controlled
Observations	3315	3315	3315	3315
R-squared	0.102	0.130	0.072	0.094

Carbohydrate	Fat	Protein	Calorie
H₀：ρ=0	H₀：ρ=0	H₀：ρ=0	H₀：ρ=0
ρ=-0.054 χ²(1)=0.40 p[χ²(1)>0.40]=0.52	ρ=-0.044 χ²(1)=0.09 p[χ²(1)>0.09]=0.77	ρ=-0.053 χ²(1)=0.22 p[χ²(1)>0.22]=0.64	ρ=-0.054 χ²(1)=0.24 p[χ²(1)>0.24]=0.62
accept the null hypothesis	accept the null hypothesis	accept the null hypothesis	accept the null hypothesis

Variables		Mean		Standardized mean difference（%）	Reduction in absolute value standardized difference（%）	T value
		Treated	Control
Ln monthly income	U	7.9259	7.9911	-14.5		-3.03^***
Ln monthly income	M	7.9262	7.9279	-0.4	97.5	-0.06
Gender	U	0.53916	0.59328	-10.9		-2.35^**
Gender	M	0.53931	0.55096	-2.4	78.5	-0.39
Age	U	35.559	35.896	-3.2		-0.65
Age	M	35.547	35.352	1.8	42.3	0.32
Age square	U	1362.3	1416.7	-6.7		-1.37
Age square	M	1361.7	1348.8	1.6	76.4	0.28
BMI	U	22.122	22.256	-4.3		-0.94
BMI	M	22.122	22.106	0.5	88.2	0.09
High school or junior college	U	0.44627	0.27585	36.0		8.00^***
High school or junior college	M	0.44607	0.46694	-4.4	87.8	-0.69
Bachelor and above	U	0.08015	0.03145	21.3		5.37^***
Bachelor and above	M	0.07861	0.07827	0.2	99.3	0.02
Middle manual labour	U	0.69217	0.54194	31.3		6.53^***
Middle manual labour	M	0.69104	0.68106	2.1	93.4	0.36
Heavy manual labour	U	0.0929	0.30694	-55.5		-10.47^***
Heavy manual labour	M	0.09324	0.10367	-2.7	95.1	-0.58
Guang Dong	U	0.27322	0.18619	20.8		4.67^***
Guang Dong	M	0.27422	0.26827	1.4	93.2	0.22
Shan Dong	U	0.2204	0.19812	5.5		1.19
Shan Dong	M	0.22121	0.21314	2.0	63.8	0.32
Si Chuan	U	0.25865	0.18547	17.7		3.94^***
Si Chuan	M	0.25594	0.27146	-3.7	78.8	-0.58
Zhe Jiang	U	0.13479	0.22343	-23.3		-4.68^***
Zhe Jiang	M	0.13528	0.13053	1.2	94.6	0.23

Variables	-------------------------------------The influence of urban pension insurance-------------------------------------
	Carbohydrate	Fat	Protein	Calorie
The nearest neighbour matches	0.020 (0.029)	0.155^** (0.074)	0.082^** (0.034)	0.067^** (0.029)
Radius matching	0.014 (0.026)	0.146^** (0.063)	0.081^*** (0.028)	0.065^** (0.026)
Nuclear matching	0.014 (0.026)	0.145^** (0.061)	0.083^*** (0.029)	0.065^** (0.026)
OLS	0.026 (0.021)	0.135^*** (0.043)	0.088^*** (0.021)	0.068^*** (0.019)