Socioeconomic Aspects of Sugarcane Producing Municipalities in Brazil

SOCIOECONOMIC ASPECTS OF SUGARCANE PRODUCING MUNICIPALITIES IN BRAZIL

Pedro Gerber Machado, M.Sc
*

Introduction

Government policies to support the production of ethanol from sugar cane , large availability of land and a favorable climate , ie tropical, with good rainfall and temperatures , have made Brazil a global leader in this field . In 2009, Brazil accounted for 33 % of global production of ethanol and was also the largest exporter (HERRERAS, 2013). The importance of the sector to the economy has taken large proportions, especially in the last four decades. In 2008 participation in the Brazilian GDP reached 2 %, generating more than 1,280,000 formal jobs (UNICA, 2011). The number of plants in 2010 was 413, with 103 producing only ethanol, 11 producing sugar and 297 mixed (MAPA, 2010).

The scale of production of sugarcane and ethanol, as well as the growth of consumption, which is a consequence of the introduction and success of flex vehicles in the Brazilian fleet, justifies the analysis not only of environmental aspects, but also social and economic issues, including its contribution to the development of the country and the regions in which it operates

This article aims to analyze the socio-economic aspects associated with the production of sugarcane in two major producing states: São Paulo, the largest producer in the Center-South region, and in the country, and Alagoas, the largest producer in the Northeast. To do so, regularly compiled municipal indicators were used and disclosed by official Brazilian government agencies. The cluster method was used to separate in a non-biased way two groups: with higher and lower socioeconomic indicators.

Methodology

Data collection for this study was performed prioritizing official databases from the Brazilian government and state institutions, with public access. Priority was given to electronic databases of IPEADATA, the Institute for Applied Economic Research (IPEA). Three categories of data are available: Macroeconomic, regional and social. Given the nature of research, the social category was prioritized, and six indicators and two indices for the years 1980, 1991, 2000 and 2010 were selected.

Despite the effort in creating methodologies for sustainability assessment, whether in public, private or community environments, the choice of indicators depends mainly on the availability of data, especially when it is a temporally and spatially extensive study. Following Oliveira (2011), the choice of indicators for this study was intended to encompass several subdivisions of social, economic and also taking into account the existence of data in years and municipalities. Frame 1 shows the selected indicators and their corresponding category.

After the selection of indicators, a cluster analysis is performed within the sugarcane producing municipalities, in order to divide them in two groups: One with better indicators, hence better quality of life, and one with worst.

In order to verify the differences between these two groups, as economic activity goes, the mean of five indicators is calculated and then compared using a Mann-Whitney’s test: Participation of sugarcane in local GDP, Participation of Industry in local GDP, Participation of Services in local GDP, Participation of agriculture in Local GDP and Percentage of rural population.

In cluster analysis the aim is to find patterns in data to group the observations of the sample in great clusters, in which these observations are similar, but the groups are as different as possible.

There are three methods to divide observation into groups: joining or tree clustering, two-way joining and K - means clustering. Only the latter was used in this work and therefore will be treated here. In the technique of cluster K –means, first K centroids are chosen, usually the average of the sample, where K is the number of centroids specified by the researcher or user. The sample points are then assigned to groups whose centroids are closest, and a new centroid is calculated. The centroids are calculated until no individual is relocated to a different group (TAN et al., 2006).

Results

The results for the average comparison between the groups with highest and lowest quality of life (represented by the unbiased groups formed after the clustering) show two particularly different scenarios for the state of São Paulo and Alagoas.

The state of São Paulo has a systematic evolution throughout the years, with the best group with lower averages of sugarcane participation in the GDP. Also, the group with higher industry participation in its GDP is the best group, except for 1991. As it is for sugarcane, the group with higher agriculture participation in the GDP is the worst group.

Table 1 - Comparison of averages between groups for the state of São Paulo 1970-2010 (decimal)

*Highest value, when statistically different (at 5%).

The state of Alagoas, on the other hand, has a different and interesting evolution. Until 2000, it follows the same patterns as São Paulo, but in 2010 the group with best development has higher sugarcane participation in its GDP, in contrast with agriculture participation (the worst group has higher average).

Table 2 - Comparison of averages between groups for the state of Alagoas 1970-2010 (decimal)

*Highest value, when statistically different (at 5%).

Conclusion

The states of São Paulo and Alagoas are two important sugarcane producers in Brazil. The importance of this culture for the local development in both states is historically known. The numbers, on the other hand, show that most of the activities with higher value added (as the industry sector) have better impacts on the local quality of life, than those of the primary sector.

The year 2010 in the state of Alagoas shows a different scenario. In this particular year, the sugarcane participation indicates a positive impact in the quality of life of sugarcane production. Possibly due to the higher importance of the culture in the state, and also to the value it represents for local economy, and the growth in sugarcane prices over the last decade.

References

HERRERAS, Sara et al. Analysis of socio-economic impacts of sustainable sugarcane–ethanol production by means of inter-regional Input–Output analysis: Demonstrated for Northeast Brazil. Renewable And Sustainable Energy Reviews, Utrecht, v. 1, n. 28, p.290-316, ago. 2013.

UNICA. Relatório de Sustentabilidade 2010. São Paulo, 2011. 128 p.

MAPA. Relação das unidades produtoras cadastradas no Departamento da Cana-de-açucar e Agronergia. Brasilia, 2010.

IPEADATA. Dados sociais e regionais do Brasil. Disponível em: <http://www.ipeadata.gov.br>. Acesso em: 10 jan. 2012.

OLIVEIRA, Janaína Garcia. Estudo dos impactos socioeconômicos regionais do setor sucroalcooleiro. 2011. 211 f. Tese (Doutorado) - Unicamp, Campinas, 2011.

TAN, Pang-ning; STEINBACH, Michael; KUMAR, Vipin. Cluster Analysis: Basic Concepts and Algorithms. Em: TAN, Pang-ning; STEINBACH, Michael; KUMAR, Vipin. Introduction to Data Mining. Michigan State University: Michigan State University, 2006. p. 487-588.