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Assessment of the relationship of government spending on social assistance programs with Brazilian macroeconomic variables

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  • de Senna, Viviane
  • Souza, Adriano Mendonça

Abstract

Since the 1988 Federal Constitution social assistance has become a duty of the State and a right to everyone, guaranteeing the population a dignified life. To ensure these rights federal government has created programs that can supply the main needs of people in extreme poverty. Among the programs that provide social assistance to the population, the best known are the ”Bolsa Família” Program — PBF and the Continuous Cash Benefit - Continuous Cash Benefit — BPC. This research’s main purpose is to analyze the relationship between the main macroeconomic variables and the Federal government spending on social welfare policy in the period from January 2004 to August 2014. The used methodologies are the Vector auto regression model — VAR and Error Correction Vector — VEC. The conclusion, was that there is a meaningful relationship between macroeconomic variables and social assistance programs. This indicates that if the government takes a more abrupt resolution in changing the existing programs it will result in fluctuations in the main macroeconomic variables interfering with the stability of Brazilian domestic economy up to twelve months.

Suggested Citation

  • de Senna, Viviane & Souza, Adriano Mendonça, 2016. "Assessment of the relationship of government spending on social assistance programs with Brazilian macroeconomic variables," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 21-30.
    • Handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:21-30
    DOI: 10.1016/j.physa.2016.05.022
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    References listed on IDEAS

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    Cited by:

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    4. Ueda, Renan Mitsuo & Souza, Adriano Mendonça & Menezes, Rui Manuel Campilho Pereira, 2020. "How macroeconomic variables affect admission and dismissal in the Brazilian electro-electronic sector: A VAR-based model and cluster analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    5. de Souza Ramser, Claudia Aline & Souza, Adriano Mendonça & Souza, Francisca Mendonça & da Veiga, Claudimar Pereira & da Silva, Wesley Vieira, 2019. "The importance of principal components in studying mineral prices using vector autoregressive models: Evidence from the Brazilian economy," Resources Policy, Elsevier, vol. 62(C), pages 9-21.
    6. Alina Źróbek-Różańska & Marek Ogryzek & Anna Źróbek-Sokolnik, 2022. "Creating a Healthy Environment for Children: GIS Tools for Improving the Quality of the Social Welfare Management System," IJERPH, MDPI, vol. 19(12), pages 1-19, June.
    7. Zhang, Chi & Zhou, Kaile & Yang, Shanlin & Shao, Zhen, 2017. "Exploring the transformation and upgrading of China’s economy using electricity consumption data: A VAR–VEC based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 144-155.

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