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Date of Award
The purpose is to apply the new ARFIMA methodology to distinguish between different models of long-run behavior i.e. nesting the difference stationary and trend stationary models. In particular, we analyze the long-term dynamic behavior of discreetly observed data at monthly and quarterly frequencies for the G-7 countries spanning the period from 1961 through 2000. First, in this dissertation fractional time series models are estimated using a relatively new maximum likelihood procedure (Li and McLeod, 1986; and Sowell, 1990b). Second, we provide some international evidence on persistence using post war data for the G-7 countries. Finally, the data set includes two output measures, two components of the gross domestic product (GDP), two measures of inflation, two measures of interest rates, a broad money stock measure and the real effective exchange rate.
Chenoweth, Gregg A., "Non-profit and for-profit workers during organizational innovation :" (2003). Wayne State University Dissertations. 3275.