How we projected the GDP for states in Nigeria

The National Bureau of Statistics in 2013 released the Gross Domestic Product (GDP) estimates for each of the states in Nigeria and the Federal Capital Territory, Abuja for the year 2010. This is the one and only time that does figures have been calculated.

At Kingmakers.com we were curious to find out what each state’s GDP might further down the line and see how the different states are faring economically as a unit for our State of States Report.

Our approach was to try and forecast the GDP per Capita based on socioeconomic economic indicators that could influence it. To get our baseline figures, we took the GDP calculations for 2010 for each of the states as released by the National Bureau of Statistics used that to get an estimate of the GDP Per Capita for each state by dividing the GDP by the projected population in each state for the year 2010.

After going through several models in order to forecast the GDP for each of the state, we settle on a multiple regression model that forecast the change in the GDP Per Capita of each of the state.

We derived the model by looking at the change in the GDP per capita for the whole of Nigeria from 2010 to 2015 and then examined all the socioeconomic indicators we had available to us. We settled on the following 5 independent predictors when their relationships were looked at gave us the highest statistical relevance possible in determining the rate of change in GDP per capita.

The indicators included

  • Adult Life Expectancy
  • Infant Mortality Rate
  • Female Labour Participation Rate
  • Unemployment Rate
  • Adult Literacy Rate

The model used for calculating is shown below.

Y = b0 + b1X1 + b2X2 + b3X3 + b4X4 + b5X5

Y: Percentage in GDP per capita
b0: Intercept
b1: Adjusted percentage change in adult life expectancy
X1: Coefficient for percentage change in adult life expectancy
b2: Adjusted percentage change in infant mortality rate
X2: Coefficient for percentage change in infant mortality rate
b3: Adjusted percentage change in female labour participation rate
X3: Coefficient for percentage change in female labour participation rate
b4: Adjusted percentage change in unemployment rate
X4: Coefficient for percentage change in unemployment rate
b5: Adjusted percentage change in adult literacy rate
X5: Coefficient for percentage change in adult literacy rate

The value of each of variables were adjusted in order to deal with the wide variation in the changes to the value of the indicators on the national level as compared to those experienced on the state level. While the changes on the national level tended to be in small units, that on state level tended to be much larger, sometimes in the tens of units.

We adjusted the values being passed to the model to deal with the wide variations by multiplying the input value of the state with an indicator factor. The indicator factor was derived from finding the value of the percentage of in the indicator at a particular state level that gave a unit change in value at the national level.

Once we had the GDP per capita for each of the state, we were able to determine the GDP itself and the GDP growth from 2011 to 2015.

Like what you read? Give Obi Igbokwe a round of applause.

From a quick cheer to a standing ovation, clap to show how much you enjoyed this story.