Author: Shlair Abdulkhaleq Al-Zanganee1
1Department of Business and Management, Faculty of Administrative Science and Economics, Ishik University, Erbil, Iraq
Abstract: Brazil, a country of a massive land areas and a population of 202 million, is endowed with an immense range of diversified natural resources including metallic minerals and oil reserves. For the last decade, Brazil became an attraction for international investors and foreign direct investment initiatives due to rapid industrialization and accelerated rates of growth. In 2012, Brazil’s economy was classified by the International Monetary Fund (IMF) as the world’s seventh largest economy, both in terms of nominal Gross Domestic Product (GDP) and Purchasing Power Parity (PPP) (IMF Annual Report, 2012). To predict Brazil’s potential economic growth, this paper used a regression forecasting model to forecast Brazil’s per capita GDP annual percentage growth rate as a function of fixed capital formation growth rate, growth rate of the labor force population, and inflation measured by the annual growth rate
of the GDP implicit deflator. The regression model used a growth equation that was derived from a study conducted by the International Monetary Fund to measure economic growth in New Zealand. The data was taken from the World Bank’s database of World’s Development Indicators during the period between the years 1971-2010. The model’s validity test reported that it did not violate any of the classical linear model assumptions for time series regression. Thus, the estimated coefficients are the Best Linear Unbiased Estimators (BLUE) of the population coefficient. The regression forecast of 2010 per capita GDP growth rate approximately equaled 8%. The forecast’s 90% confidence interval ranged between a minimum value of 4.7683996, and a maximum value of 11.193217. Brazil’s 2010 per capita GDP annual percentage growth rate was also forecasted using an Autoregressive Integrated Moving
Average (ARIMA) Model. The dependent variable’s time series was transformed by taking the first difference to overcome the problem of non-stationarity. The autocorrelation and the partial autocorrelation functions indicated that the ARIMA model should include one Moving Average (MA) term. The ARIMA 2010 forecast approximately equaled 6% annual growth rate. The forecast’s 90% confidence interval ranged between a minimum value of -4.769585, and a maximum value of 7.851028.
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International Journal of Social Sciences & Educational Studies
ISSN 2409-1294 (Print), June 2014, Vol.1, No.4