Model building: What accounts for the variation in Brazilian state GDP?

This is the first attempt to build a model that accounts for some of the observed variability in the Brazilian state GDP values.  The investigation is attached as a PDF because some of the Minitab output does not retain its original format when it is pasted into WordPress.

Here are the potential predictor variables, their type, measurement, and the source used to obtain the data:

State contribution to national GDP Quantitative Year 2010, measured in R$ 1,000,000 IBGE
Population Quantitative Year 2010, measured by individuals IBGE
Municipalities Quantitative Year 2010, measured by individual municipalities Fundação Joaquim Nabuco
Region Qualitative Year 2010, the federal government identifies five regions (more details below) Fundação Joaquim Nabuco

 

Foreign Border Qualitative Year 2010, border is defined as “yes” or “no” Consult any modern day geopolitical map of Brazil.
Border with MERCOSUR country Qualitative Year 2010, border is defined as “yes” or “no”; MERCOSUR is defined as sharing a border with Argentina, Uruguay, Paraguay, or Venezuela.  Venezuela was admitted to MERCOSUR in 2012, but its inclusion was considered important for the economic impact it could have had on border states Consult any modern day geopolitical map of Brazil.
Foreign Presence Quantitative This is defined as the number of consulates in a given state.  This would probably be more meaningful if we exclude the Federal District. Wikipedia
Ocean Port Quantitative The number of ports in the state (measured by various sources between the years 2009 and 2015) Wikipedia

 

 

River Port Quantitative The number of ports in the state (measured by various sources between the years 2009 and 2015).  I also considered making the predictor variables for ocean and river port qualitative. Wikipedia

 

Soy Quantitative The amount of thousand tons exported during the two harvests of year of the growing year 2010/2011. CONAB
Corn Quantitative The amount of thousand tons exported during the two harvests of year of the growing year 2010/2011. CONAB

Corn and soy account for about 80% of the grains produced in Brazil.  Soy has “immediate liquidity” since it is an international commodity while corn historically was used for internal supply (EMBRAPA).

When I look for significance of “region”, I should be aware that the sample size of each region is very small.  There are 3 to 9 observations per group, with 9 for the Northeast being more the exception than the rule.  I suspect this variable might have been significant if we coded municipalities per region and used their relative GDP instead of that for the state.  If we opted to include this variable in the model, we would have included four dummy variables and chosen one baseline region.

After looking at associations, I could be interesting to see if the deleted residual for the Federal District makes the point influential.  This unit is an anomaly in a few categories, especially in regards to the “foreign presence”.

Finally, I understand that with more time I would have consulted original sources instead of using data from second-hand sources.

I begin by a simple matrix plot of each variable regressed against the other.

12-23-16-brazil-post-image-1

Visually we can identify a few associations between variables:

  • Population and number of municipalities
  • Population and state GDP
  • Soy and corn exports

Correlation: Population, Municipalities, GDP, Soy, Corn

 

                    Population     Municipalities         GDP             Soy

Municipalities           0.762

GDP                      0.953           0.629

Soy                      0.072           0.292           0.064

Corn                     0.353           0.607           0.313           0.860

 

Cell Contents: Pearson correlation

 

To a lesser degree, associations exist between:

·         Foreign Presence and GDP

·         Soy and GDP

·         Corn and GDP

Correlation: Foreign Presence, GDP, Soy, Corn

 

                 Foreign Presence               GDP               Soy

GDP                          0.357

Soy                         -0.067             0.064

Corn                        -0.032             0.313             0.860

 

Cell Contents: Pearson correlation

 The rest of this investigation can be found via this link: 12-00-16-brazilian-gdp-project.

 

 

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