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SAS coding Fit an OLS regression model to these data. a. Analyze the residuals and comment on model adequacy. b. Fit the lagged variables regression
SAS coding
Fit an OLS regression model to these data.
a. Analyze the residuals and comment on model adequacy.
b. Fit the lagged variables regression models shown in Eqs. (3.119) and (3.120) to these data. How do these models compare with the OLS model in part a?
Table B.20 US Internal Revenue Tax Refunds | ||
Source: US Department of Energy - Internal Revenue Service, SOI Tax Stats - Individual Time Series Statistical Tables, http://www.irs.gov/taxstats/indtaxstats/article/0,,id=96679,00.html | ||
Fiscal Year | Amount Refunded, millions dollars | National Population, thousands |
1987 | 96,969 | 242,289 |
1988 | 94,480 | 244,499 |
1989 | 93,613 | 246,819 |
1990 | 99,656 | 249,464 |
1991 | 104,380 | 252,153 |
1992 | 113,108 | 255,030 |
1993 | 93,580 | 257,783 |
1994 | 96,980 | 260,327 |
1995 | 108,035 | 262,803 |
1996 | 132,710 | 265,229 |
1997 | 142,599 | 267,784 |
1998 | 153,828 | 270,248 |
1999 | 185,282 | 272,691 |
2000 | 195,751 | 282,193 |
2001 | 252,787 | 285,108 |
2002 | 257,644 | 287,985 |
2003 | 296,064 | 290,850 |
2004 | 270,893 | 293,657 |
2005 | 255,439 | 296,410 |
2006 | 263,501 | 299,103 |
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