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The intention of this research project was to build an empirically based model that could be used to prepare a forecast of future consumption. The first step that must be taken is to study the effects of income and interest rates on the consumption of non-durable goods for the years 1990 to 1994. To forecast future consumption, Microsoft EXCEL was used to produce both simple and multiple regressions from the data period 1991 through 1993 data. In the simple regression model, income was used as the independent variable. Interest rates along with income provided the independent variables in the multiple regression analysis. The best resulting regression equations were determined and used to forecast consumption for the year 1994.
Regression analysis is the statistical technique most frequently used in the field of economics to process empirical evidence and to test the explanatory power of theoretical models. In order to forecast future consumption and compare the results to theoretical models, simple and multiple regressions were run. All data needed to run the regression was taken from the Federal Reserve Bank of St. Louis data bank (FREDDATA). Monthly data in chained 1992 dollars is used for both consumption expenditure and disposable income. The monthly data was lagged five to twelve months and analyzed to find the best equation. The lag was needed so that it could not be argued that changes in income cause changes in spending, or that changes in spending cause changes in income. The seasonally adjusted annual rate (SAAR) also played a role in the data transformation process so that no other outside factors, such as the seasons, could be responsible for the regression results.
After the regression analysis was finished, the next step was to determine which; of the economic theories best explained the results of the data analysis. To help explain these theories and results, Miller's Economics Today, Picconi, Romano, and Olson's Business Statistics: Elements and Applications, Wyrick's The Economist's Handbook: A Research and Writing Guide, and Neufeld's Learning Business Statistics with Microsoft Excel 97, were used as resources. In the next few pages, information from these texts will be utilized to explain economic theories, regressions, and results dealing with the relationship between disposable income and interest rates and consumption of non-durable goods.
In this analysis, I will show that the regression data partially agrees with both Keynes's theory of consumption as well as the classical model of consumption. In order to predict future consumption expenditures, it was necessary to rely on both theories of consumption since income and interest rates were the two variables concerned. The following paragraphs will describe these two economic theories.
To prepare this analysis it was essential to rely on Keynes' theories about consumption. Keynes' consumption function argued that saving and consumption decisions depend primarily on an individual's current real disposable income (Miller, 272). This differs from the Classical Model, in which interest rates determine consumption. According to Keynes, the interest rate is not the most important determinant of an individual's saving and consumption decisions. Keynes' proposition stated that how much a person earns determines how much they will consume.
At the middle of Keynes' theory was the idea that as real disposable income increases; planned consumption will also increase, but not as significantly. Under the assumption of a fixed price model, Keynes stated that a change in consumption would have the same sign as a change in income. In Lehman's terms the more people make, the more they will spend. When consumers predict or experience an increase in real income, they will be more likely to spend that income rather than save it for the future. In contrast, if the consumer were to anticipate a decrease in real income, they will tend to save their income rather than consum
Quotes talked about in this paper
Names mentioned in this research paper
Neufeld, Keynes, Picconi, Miller, Sir John R. Hicks, James D. Duesendary, Roger L., Albert; Olson, Mario J.; Romano, John L. Learning,
Organizations referenced in this research paper
the MAPEs, Federal Reserve Bank,
Locations talked about in this report
St. Louis, New York, MA, Saddle River, St. Paul, MN,
Facility included in this term paper
R Square, Prentice Hall,
Companies talked about in this research material
Microsoft, Lehman, FREDDATA, Addison-Wesley, HarperCollins, West Publishing Company,
Keywords mentioned in this research material
interest rates, multiple regressions, regression analysis, disposable income, p value, real income, Keynes, disposable personal income, consumption function, theory, regression line, model, MAPE, Business Statistics, results, microsoft excel, determinant, classical theory, forecast, Keynesian theory, expenditures, seasonally adjusted annual rate, data analysis, independent variables, Neufeld, high level, mean absolute percentage error, data transformation, data bank, Federal Reserve Bank, economic model, Upper Saddle River, durable goods, West Publishing Company, coefficients, statistically significant, explanatory power, fixed price, two tail test, Prentice Hall, research project, main point, New York, lagged, consumer, next year, theoretical, forecasting, step, unpredictability,