CORRELATION
ANALYSIS OF EXPORTS OF MANUFACTURED PRODUCTS AND BASIC PRODUCTS IN THE STATE OF
SÃO PAULO
Gabriel
Nery da Silva
University of
Mogi das Cruzes, Brazil
E-mail:
nery.gal.nery@gmail.com
Submission: 29/03/2018
Accept: 29/03/2018
ABSTRACT
Participation
in international trade has been important for national economy and keeps
increasing over the years, and it may be noted by the importation and
exportation activities. In this sense this study aims to verify whether there
is correlation between exports of manufactured and basic products in the State
of São Paulo, as well as between them and time. Therefore it was used data
available at Ministério da Indústria,
Comércio Exterior e Serviços (MDIC) website relating to the amount in US$
of both manufactured products and basic products exported in the State of São
Paulo from 2006 to 2016. The analysis was performed by using simple linear
regression statistical calculation, aiming to verify whether there is
correlation. Findings indicate there is strong correlation between the exports
of basic products and time; there is no correlation between the exports of
manufactured products and time; there is no correlation between the exports of
basic products and the exports of manufactured products. Findings may help
practitioners in forecasting demands as well as the understanding about exports
behaviors when making-decisions.
Keywords: Exportation, Manufactured Product,
Basic Product, State of São Paulo, Correlation.
1. INTRODUCTION
In
this globalized scenario international trades have grown more and more and have
been shown as one of the most profitable ways for a nation’s economy, i.e.
participation in international trade takes a nation to increase its capital and
its economy.
The
rule for a good economic scenario of a country is to export more than import.
Brazil is currently in the Emerging countries (E7) group. In general, these
countries are those underdeveloped countries who present a picture of
prosperous economic growth and socioeconomic characteristics that differentiate
them from the other peripheral economies (SCHMIELE, 2012; ALBERT et al., 2014).
Brazil
has as predominant source of wealth generation the low value-added products,
which are sold and exported in commodities, which can be checked, e.g., in the
list published at ADVFN Brazil (2017) website, a financial market website. In
order of larger exports (quantity) the sequence is as follows: soybeans whether
or not broken (10%); iron ores and concentrates (7.2%); crude oils (5.4%); cane
sugar in the rough (4%); and frozen, fresh or chilled chicken meat, including
offal (3.2%). This last one was topic of study for Sartin et al. (2015) in an analysis of correlation between them and beef
exports.
Although
Brazil has, as mentioned, its source of income concentrate in low value-added
products, it also exports high value-added products, and in this case the
largest parcel is for passengers or loads transportation, i.e. passenger cars
(2.5%), and airplanes (2.3%) (MDIC, 2017).
The
main destinations of Brazil’s exportations are China (19%), The United States
(12.5%), and Argentina (7.24%), respectively.
According
to Portal Brasil (BRASIL, 2014) and Ministério da Indústria, Comércio Exterior e
Serviços (MDIC, 2017), the State of São Paulo has the greatest participation
both in the exportation of certain products and in the national GDP. The export
destinations of the State of São Paulo has an order of participation little
different from Brazil’s. In this specific State the sequence is The United
States (17%), Argentina (12%), and China (8.4%).
Also
according to MDIC (2017) website, which provides, among others, local,
regional, and national data of imports and exports in Brazil, the State of São
Paulo had participation of 24.9% in the exports performed in Brazil in 2016 and
of 37.6% in the imports performed in the same period. These values result in
the State cash deficit of US$ 5.5 billion (MDIC, 2017), thus highlighting
Brazil’s inadequate characteristic of importing more than exporting.
Given
this importance of the State of São Paulo for Brazil’s importation and
exportation activities as well as for national economy, it was decided to
analyze the exportation activity performed in this State, in order to know its
behavior and correlations.
Figure 1: Brazilian exports by
aggregate factor - State: São Paulo (2006-2016)
Source: MDIC (2017), adapted.
Data
were extracted from MDIC (2017) website for helping this analysis. First of all
it notices in Figure 1 the exports history performed in the State of São Paulo
over the last eleven years. It is possible to notice the predominant
participation of manufactured products in the performed exportation (on average
75%). Figure 2 describes the characteristics of these products classified in
main groups. Airplanes (8.4%) and passenger cars (4.8%) stand out among the
manufactured products. Soybeans whether or not broken (3.1%) stand out among
the basic products.
Figure 2: Exported products overview - State: São Paulo
(classification: main exported products and value-added)
Source: MDIC (2017), adapted.
Considering
the data mentioned above, it is investigated whether there is correlation
between the behaviors of the exports of these products based on the assumptions
represented in Figure 3.
Figure 3: Assumptions
Source: the author.
So,
exports of manufactured products, exports of basic products, and time are the
variables to be investigated in this study. Then in this way we have as
assumptions the following:
·
Exports of manufactured products variable is dependent
on time variable.
·
Exports of basic products variable is dependent on
time variable.
·
Exports of basic products variable is dependent on
exports of manufactured products variable.
This
study is organized as follows: section 2 exposes the theoretical references and
the concepts addressed in the study. In section 3 there is the description of
the adopted method for the study performing, as well as the study
classification as regards to its kind. Section 4 discusses the findings.
Section 5 finishes the study with final considerations and suggests issues for
further researches.
2. THEORETICAL REFERENCE
2.1.
Brazil
and international trade
Brazil does part of the E7 countries, which are
countries in development and tend to become great world powers. One of the
reasons for is linked to both participation in international trade and
investment on production and commercialization of high value-added goods.
As Brazil is in the E7 countries it becomes a target
for studies and discussions especially because of those countries whom Brazil
has commercial relations with, such as China and The United States. China in
turn is very present in studies perhaps because of both its much-criticized
production policy and its market share in the global market (e.g. COELHO;
MORALES, 2013; DELVAUX, 2016; SALAMA, 2016; IJPDLM[1], 2017).
2.2.
Manufactured
products: characteristics, economic importance and related studies
Manufactured products are finished products, i.e.
products ready to be used by the buyer. This kind of products spares manpower
from who acquires it, and because that it has higher cost.
Among the main manufactured products, high technology
products stand out in importance, such as electronics and transportation. In
this way it is strategically feasible to keep the country economy supported by
the production of this kind of goods.
Recent studies in Brazil analyze the Brazilian
economic performance in relation to the commerce of these products, e.g. Avelar
et al. (2015) studied issues related to MERCOSUR, indicating an improvement in
Brazilian commercial relations with countries of the bloc; and Ramos Filho and
Ferreira (2016), for both statistical purposes and economic analysis, analyzed
issues related to the sectors of Brazilian manufacturers in order to detect
whether or not there exists the J Curve phenomenon in the relation between
commercial balance and exchange rate.
2.3.
Basic
products: characteristics, economic importance and related studies
Basic products are inputs that passed through little
or no preparation and/or treatment work. They are commercialized in
commodities.
This kind of products is destined to meet internal or
external raw material demands. Its cost is lower and it requires manpower from
who acquires it to transform it into finished product.
Brazilian economy is predominantly supported by this
kind of products (42.7%, according to MDIC). Soybeans whether or not broken,
iron ores and concentrates, and crude oils stand out among them.
As studies addressing basic products topics there are
some analysis or discussions about the Real (Brazilian currency) linked to the
scheme of commodities (e.g. ALBERT et al.,
2014; BRANCO, 2016). Espíndola and Araújo Jr. (2017) discuss about the
commercial relations between Brazil and Spain. Regarding the relation between
Brazil and China, Salama (2016) points out some aspects of it that negatively
impact on Brazilian economic development, also highlighting Brazil’s insistence
to bet on basic products more than on manufactured products.
2.4.
Statistics
and correlation analysis and simple linear regression
Statistics is important for providing methods to
collect, organize, describe, analyze and interpret data (TIBONI, 2010). Its
results help the planning, formulation of decisions, understanding of characteristics
and behaviors of some population, or decision-making (TRIOLA, 2005; TIBONI,
2010).
Therefore one of its analysis tools is the
investigation of correlation between variables. In linear correlation there is
a trend relation in the distribution of points, which makes possible to notice
certain behavior pattern of the variables and between them, in case of
dependence between the variables (TRIOLA, 2005; TIBONI, 2010).
Correlation analysis and simple linear regression is
done by means of linear correlation coefficient formula. Linear correlation
coefficient r (Pearson’s r) is calculated by the formula
represented in Equation (1).
|
|
|
(1) |
Where
n = number of
observations of the variables
xi =
independent variable
yi =
dependent variable
R
represents the intensity of correlation between the variables. By definition r value[2]
is −1 ≤ r ≤ +1, where:
0 ≤ r < 0.3 = inexistent or
weak correlation between the variables;
0.3 ≤ r < 0.6 = low to
medium correlation between the variables; and
0.6 ≤ r ≤ 1 = medium to strong
correlation between the variables.
Linear regression is the function (mathematical
expression) characterized (or represented) by a straight line (first-degree
polynomial function) that best fits the points of the variables plotted on the
graph. This line is a linear model that associates the independent variable x and the dependent variable y, it is expressed by means of Equation
(2) (TIBONI, 2010).
|
|
|
(2) |
Where
y = dependent
variable
x = independent
variable
a (constant
value) = coefficient of the regression line (or slope of the line)
b (constant value) = point of intersection between the
line and the vertical axis y (it is
the value of y when x is zero)
The values of the constants a and b are given
respectively by Equation (3) and Equation (4) (TRIOLA, 2005).
|
|
|
(3) |
||
|
|
|
(4) |
||
3. METHOD
This study based on Sartin et al.’s (2015) study, which verifies correlation between exports
of beef and chicken in Brazil. From it the replica of their logical model was
done but by addressing the exportation activity in the State of São Paulo and
limiting to manufactured products and basic products.
It is a descriptive study of quantitative nature.
First of all it was collected the data available at
MDIC website that refer to values in annual billions US$ of exports performed
in the State of São Paulo that comprise the years from 2006 to 2016 and refer
to exports of manufactured products and basic products.
Next, it was considered the assumptions of dependency
relation between the variables (see Figure 3) and with the data it was made
calculations through Equation (1), Equation (2), Equation (3) and Equation (4),
according to the need, to verify whether there is correlation between the
variables in study and which would be the linear regression line that would
represent this correlation.
Finally, findings are discussed in section 4, followed
by final considerations and suggestions for further researches in section 5.
4. FINDINGS AND DISCUSSION
The data collected from MDIC website are organized in
Table 1. It describes the amount in billions US$ of exports of manufactured
products and basic products in the State of São Paulo from 2006 to 2016.
The exports of manufactured products have average of
US$ 38.94 billion per year and standard deviation of 5.25. The exports of basic
products have average of US$ 4.64 billion per year and standard deviation of
1.25.
Table 1: Brazilian annual
exports of manufactured products and basic products from 2006 to 2016 in
billions US$
|
|
2006 |
2007 |
2008 |
2009 |
2010 |
2011 |
2012 |
2013 |
2014 |
2015 |
2016 |
|
Manufactured products (in billions US$) |
37.7 |
42.1 |
46.5 |
32.91 |
39.23 |
45.06 |
44.04 |
40.73 |
35.71 |
32.45 |
31.81 |
|
Basics products (in billions US$) |
2.82 |
3.55 |
4.58 |
2.94 |
3.97 |
4.6 |
4.77 |
5.22 |
6.63 |
6.08 |
5.85 |
Source:
the author based on data extracted from MDIC (2017).
It notices in Figure 4 that both exportations had
similar behaviors over the first five years. It also notices that both kept an
increasing over the first three considered years, when they had a decline (in
the case of manufactured products, the decline was over than US$ 10 billion),
possibly due to the global economic crisis in 2008, the Great Recession, as it
became known.
Figure 4: Behavior over the
years of exports of manufactured products and basics products in the State of
São Paulo
Source:
the author.
Another pertinent observation is that from 2011
onwards the exports behaviors become different from each other.
Through Equation (1), Equation (2), Equation (3) and
Equation (4), the findings are as follows:
Time and exports of manufactured products:
Representative line: ; and r = 0.2113
(inexistent correlation). See Figure 5.
Figure 5: Manufactured products
x time
Source:
the author.
Time and exports of basic products:
Representative line: ; and r = 0.7835
(strong correlation). See Figure 6.
Figure 6: Basics products x
time
Source:
the author.
Manufactured products and basic products:
Representative line: ; and r = 0.0489
(inexistent correlation). See Figure 7.
Figure 7: Basic products x
manufactured products
Source:
the author.
Findings make possible to understand the behavior of
the exportation activities and thus help in formulating decision and planning.
For example, the fact of the strong correlation between basic products and time
can assist in forecasting demand, and it also indicates that the quantity tends
to grow over the years, if we consider the current scenario and practices. In
the opposite direction the same can be seen in the others two analyzed
relations. As their correlation coefficients r do not point out correlation,
these relations should not be considered for formulations or decision-making,
among others attitudes; which exclude possible misunderstanding of considering
some correlation.
5. FINAL CONSIDERATIONS
This study aimed to verify correlation between time,
exports (in billions US$) of manufactured products and basic products in the
State of São Paulo, based on the adopted assumptions. As the analysis shows,
there is only one strong correlation between the variables, which refers to
basic products and time.
One thing to note in this strong correlation is the
fact, and not so positive, that Brazil tends to continue and increase, given
the growing upward trend in the calculations, its investments on and exports of
inputs, still going against the general view that the good business is to
product and export more and more products with high value-added.
As for the exports of manufactured products, it seems
it may be linked to economic factors. This assumption is a suggestion topic for
further research.
5.1.
Suggestions
for further researches
It suggests for further researches to verify whether
there is correlation between exports and imports of manufactured products in
the State of São Paulo, also considering factors as the economic scenario,
since the time variable has shown not having correlation.
6. ACKNOWLEDGEMENTS
The author thanks the University of Mogi das Cruzes
and the Federal Institute of São Paulo for their support.
7. REFERENCES
ADVFN BRASIL. (2016) Lista dos principais produtos exportados pelo Brasil em junho de 2016.
Available at: http://br.advfn.com/jornal/2016/07/lista-dos-principaisprodutos-exportados-pelo-brasil-em-junho-de-2016.
Accessed 13 Apr. 17.
ALBERT,
F. M. C.; COTI-ZELATI, P. E.; ARAÚJO, D. L. A. (2014) Is the Brazilian real a
commodity currency? Large sample empirical evidence. Independent Journal of Management & Production (IJM&P), v.
5, n. 1, p. 1-24, doi: 10.14807/ijmp.v5i1.119.
AVELAR, F. M.; STAMM, C.; GONÇALVES
JR., C. A. (2016) A Liberalização Comercial Brasileira vista no âmbito do
Mercosul a partir dos produtos manufaturados (2000 a 2010). Redes,
v. 20, n. 3, p. 401-425, doi: 10.17058/redes.v20i3.5076.
BRANCO, R. (2016) Commodity
currencies: um fenômeno real no Brasil?. Revista
de Economia Contemporânea, Rio de Janeiro, v. 20, n. 1, p. 92-112, Apr.,
doi: 10.1590/198055272014.
BRASIL. (2014) Portal Brasil. São Paulo lidera ranking de exportação em junho. Available
at: http://www.brasil.gov.br/economia-e-emprego/2014/07/sao-paulo-lidera-ranking-de-exportacao-em-junho.
Accessed 13 Apr. 17.
COELHO,
C. F.; MORALES, G. (2013) Sustainability in pelletizing iron ore through the
industrial ecology and cleaner production program. Independent Journal of Management & Production (IJM&P), v.
4, n. 1, p. 36-54, doi: 10.14807/ijmp.v4i1.55.
DELVAUX, J. (2016) La dynamique des partenariats
<<sud-sud>> : un outil au service d'une conquête hégémonique?
Analyse du partenariat stratégique global sino-brésilien. 2016. 56 f.
Mémoire. (Maîtrise en sciences politiques, orientation générale, à finalité
spécialisée en relations internationales) Université de Liège, Liège, Belgique.
ESPÍNDOLA,
C. J.; ARAUJO JR., A. M. (2017) Breves consideraciones sobre las relaciones
comerciales entre Brasil y España. Revista de Estudios Brasileños, v. 4, n. 6, p. 161-175, doi: 10.3232/REB.2017.V4.N6.2557.
INTERNATIONAL
JOURNAL OF PHYSICAL DISTRIBUTION & LOGISTICS MANAGEMENT – IJPDLM. (2017)
United Kingdom: Emerald Insight. Special Issue: Strategic supply chain and logistics management in
Greater China: evolution, innovation and future challenges, v. 47, n. 9.
Available at: http://www.emeraldinsight.com/toc/ijpdlm/47/9. Accessed 01 Dec.
2017.
MINISTÉRIO DA INDÚSTRIA, COMÉRCIO EXTERIOR E SERVIÇOS
– MDIC. Homepage.
Available at: http://www.mdic.gov.br/comercio-exterior/estatisticas-de-comercio-exterior/comex-vis. Accessed 12 Apr.
17.
RAMOS FILHO, H. S.; FERREIRA, M. E. P. (2016) A taxa
de câmbio e os ajustes no saldo da balança comercial brasileira: uma análise
setorial da Curva J. Nova Economia, Belo
Horizonte, v. 26, n. 3, p. 887-907, Dec., doi: 10.1590/0103-6351/2471.
SALAMA, P. (2016)
Chine-Brésil: je t’aime, moi non plus. Novos Cadernos NAEA,
v. 19, n. 1, p. 9-25, jan-abr., doi: 10.5801/ncn.v19i1.3390.
SARTIN, K. R.; JOHANN, A. R. G; SOUZA, C. B.;
NASCIMENTO, A. R.; SILVEIRA, M. A. (2015) Análise de Correlação e Regressão das
Exportações de Carne Bovina e de Frango Brasileira. Conjuntura Econômica Goiana, n. 34, p. 43-59, set. Available
at: http://www.imb.go.gov.br/pub/conj/conj34/artigo_04.pdf.
SCHMIELE, A.
(2012) Drivers for international innovation activities in developed and
emerging countries. Journal of
Technology Transfer, v. 37, n. 1, p. 98-123, doi: 10.1007/s10961-011-9221-z.
TIBONI, C. G. R. (2010) Estatística Básica: para os cursos de administração, ciências
contábeis, tecnológicos e de gestão. São Paulo: Atlas.
TRIOLA, M. F. (2005) Introdução à estatística; tradução: Vera Regina Lima de Farias e
Flores, Rio de Janeiro: LTC.