| dc.description.abstract | This paper uses Maddison data on GDP in major oil-producing countries to analyze whether correlations exist between metric tonnage of oil produced and the economic development of the country. For my purposes I use GDP per capita to measure economic development. The countries studied include: Argentina, Canada, Colombia, the United States, Mexico, Venezuela, Peru, and Indonesia. The dates of analysis are different for every country due to data reliability. This paper focuses mainly on a time series analysis of the correlations between GDP and oil data. GDP is compared to oil production to determine if any statistically significant relationships exist, both conterminously and with GDP lagged behind oil production by one or two years. I examine discontinuities, or sudden changes in oil data that might indicate a significant development in that year. Most data produced correlation coefficients between .60 and .90, showing overall strong positive relationships between oil production and GDP. This is to be expected since the countries picked for this analysis were chosen because of their prominence as major oil producers. None of the countries studied produced a negative correlation, meaning that as petroleum increased, so did GDP. The countries in which GDP and oil output were almost or exactly coterminous, it can be inferred that the economy is less diverse; that is, the fewer the variables available to affect the economy, the more likely it is that the variable will have a strong effect. Venezuela showed the strongest coterminous relationship and Mexico showed the weakest statistical correlations. Because oil eventually ceases to produce exponentially growing profits, the corresponding results appear as a “curse” or negative economic effects. The oil production is essentially a catalyst in the resource cycle. | en |
