HOW CAN WE PREDICT THE GROSS DOMESTIC PRODUCT (GDP) OF A STATE? Gyasi Bawuah
The object of this project was to look at a predictability model for Gross Domestic Product (GDP), and to evaluate whether or not the proposed minimum wage increase by the US government would automatically increase GDP as analysts have stated. The study examined all the states in the US with emphasis on their minimum wages, unemployment rates, population sizes, and state/local spending. All the factors were found to have varying positive relationships with productivity, however, not all were found to be statistically significant at .05 level of significance. A multi-collinearity test proved that the Population and S/L spending which defined the model of this study, did not affect each other (VIF= 0.01 ), and hence, were valid. The conclusion was that variations in Gross Domestic Product (GDP) can best be explained or predicted up to 96% by an association of population and State/Local spending in the following model: GDP = - 3.15 + 0.000001 POPULATION + 0.898 S/L SPENDING.
And that, minimum wage alone or unemployment rates alone were statistically inadequate in predicting Gross Domestic Product (GDP)
Introduction and Literature Review
The Bureau of Economic Analysis of the US Department of Commerce define Gross Domestic Product as the output of goods and services produced by labor and property. They have explained that GDP decreased at an annual rate of 0.1 percent in the fourth quarter of 2012 (that is, from the third quarter to the fourth quarter), and increased in the third quarter by 3.1 percent. They attribute the decrease in real GDP in the fourth quarter primarily to negative contributions from private inventory investment, federal government spending, and exports that were partly offset by positive contributions from personal consumption expenditures (PCE), nonresidential fixed investment, and residential fixed investment. Secondly, The current debate in America about Government’s decision to increase minimum wage to $9.0 has led many economic and business analysts like the Economic Policy Institute to conclude that increased wages contribute to GDP growth, which in turn leads to modest employment growth. Forbes blogger, Patton, draws a negatively strong relationship between unemployment and GDP, and argues that when you include all calendar quarters from January 1948 through the end of the second quarter 2012, all the times GDP increased, unemployment was tremendously low. Dobbie, P. (in the article; Why we need population growth) posits that Australia’s high population growth helped the economy to grow through economic downturn, and to a large extent, where there was labor shortage, migrants came in as a supplement. Hence, the numbers are significantly critical. All the paragraphs above make some reference to productivity when any of the factors are manipulated. However, what the analysts don’t tell us is the proportion of the GDP which their acclaimed predictors (State/Local spending, Minimum wage, Low unemployment, and Population growth) can help estimate, and in the model of Y= a + X1 + ……Xα
The aim of this study is to provide both a model for predicting the Gross Domestic Product (GDP) of a state, and the proportion of the GDP in the model which can sufficiently be predicted or explained by what factors. Another objective is to evaluate the proposed minimum wage increase by the US Government, and whether or not the move would automatically improve productivity.
Minitab v 6 was used to analyze data collected on the 50 States in the US from the US Department of Labor, and Census Bureau. A correlation test was conducted on GDP versus the independent variables which gave the following correlations: Minimum wage (.142), Unemployment (.350), Population(.953), and S/L spending (.979). although, all the variables...
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