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Am 10.12.2010 um 17:51 schrieb barney schwartz:
full file is attached
When you don’t write many formulas in your document you can use \asciimode which makes $ and & normal letters which can be written without a leading backslash, there is also a alternative mode for natural tables which is suitable for tables with many small fields. <example> \asciimode \starttext \chapter{Data Description} The data is from The Survey of Family Income and Expenditure for Taiwan. This is the micro response data provided by The Directorate General of Budget, Accounting and Statistics of the Republic of China. Taiwan also conducts a Monthly Manpower Utilization Survey. This survey is also run by DGBAS, however at a cost of \$80 per ten items and hundreds of items within the survey just one year of this data is beyond my meager resources. Zveglich et al used this survey. I chose the Survey of Family Income and Expenditure for the richness of the data set, and because it should be a representative sample of the Taiwan population. Also, it is comparable to the Current Population Survey (CPS) in the U.~S.~ and the Survey of Consumer Finances (SCF) in Canada. My data does not depend on sources of income, rather all components of income are included. It contains variables that will allow future in-depth research into the dynamics of income distribution in Taiwan. There is much yet to be done in this area. This survey is conducted annually. In all years it uses a two-stage stratified random sample of between 14,000 and 16,500 families by physical location. . It is an in-person survey conducted by interview. A small percentage of households are required to keep daily accounts of income and expenditures. These accounts are used to adjust figures in the remaining sample for inaccuracies of memory. \placetable[here,split][tab:five]{Descriptive Statistics for Salaried Men & Women} {\startTABLE[split=repeat] \startTABLEhead[style=bold] \NC Group \NC N \NC MEAN \NC STD \NC MIN \NC MAX \NC Gini \NC 80/20 \NC\NR \stopTABLEhead \startTABLEbody \NC[nc=8] 1980 \NC\NR \NC ALL \NC 14202 \NC $ 195,727.9 \NC 912.89 \NC $ 3600 \NC $ 1,320,000 \NC 0.278 \NC 4.54 \NC\NR \NC Men \NC 9852 \NC $ 224,678.5 \NC 1123.61 \NC $ 3600 \NC $ 1,320,000 \NC 0.242 \NC 3.68 \NC\NR \NC Women \NC 4350 \NC $ 130,159.7 \NC 991.05 \NC $ 5000 \NC $ 448,000 \NC 0.259 \NC 3.91 \NC\NR \NC[nc=8] 1982 \NC\NR \NC ALL \NC 14706 \NC $ 164,247 \NC 766 \NC $ 7200 \NC $ 1,257,630 \NC 0.284 \NC 4.59 \NC\NR \NC Men \NC 9943 \NC $ 201,482 \NC 1008 \NC $ 7200 \NC $ 1,257,630 \NC 0.247 \NC 3.79 \NC\NR \NC Women \NC 4673 \NC $ 19,910 \NC 951 \NC $ 12000 \NC $ 650,000 \NC 0.275 \NC 4.14 \NC\NR \NC[nc=8] 1984 \NC\NR \NC ALL \NC 15872 \NC $ 189,845 \NC 867 \NC $ 4000 \NC $ 1,500,000 \NC 0.286 \NC 4.54 \NC\NR \NC Men \NC 10291 \NC $ 222,035 \NC 1121 \NC $ 4000 \NC $ 1,500,000 \NC 0.249 \NC 3.75 \NC\NR \NC Women \NC 5581 \NC $ 130,488 \NC 917 \NC $ 7500 \NC $ 850,000 \NC 0.264 \NC 3.91 \NC\NR \NC[nc=8] 1986 \NC\NR \NC ALL \NC 16371 \NC $ 200,997 \NC 966 \NC $ 3,600 \NC $ 2,990,000 \NC 0.294 \NC 4.69 \NC\NR \NC Men \NC 10213 \NC $ 237,554 \NC 1299 \NC $ 5,000 \NC $ 2,990,000 \NC 0.257 \NC 3.94 \NC\NR \NC Women \NC 6158 \NC $ 140,367 \NC 1001 \NC $ 3,600 \NC $ 965,000\NC 0.273 \NC 4.08 \NC\NR \NC[nc=8] 1988 \NC\NR \NC ALL \NC 16032 \NC $ 234,304 \NC 1015 \NC $ 9,000 \NC $ 1,800,000 \NC 0.277 \NC 4.29 \NC\NR \NC Men \NC 10058 \NC $ 273,829 \NC 1306 \NC $ 9,000 \NC $ 1,800,000 \NC 0.238 \NC 3.55 \NC\NR \NC Women \NC 5974 \NC $ 167,760 \NC 1189 \NC $ 28,000 \NC $ XXXXXXX \NC 0.262 \NC 3.75 \NC\NR \NC[nc=8] 1990 \NC\NR \NC ALL \NC 16346 \NC $ 285,337.8 \NC 1209.26 \NC $ 11,200 \NC $ 4,500,000 \NC 0.272 \NC 4.21 \NC\NR \NC Men \NC 10147 \NC $ 332,687.1 \NC 1579.00 \NC $ 12,000 \NC $ 4,500,000 \NC 0.235 \NC 3.48 \NC\NR \NC Women \NC 6199 \NC $ 207,832.8 \NC 1387.20 \NC $ 11,200 \NC $ 1,800,000 \NC 0.26 \NC 3.77 \NC\NR \NC[nc=8] 1992 \NC\NR \NC ALL \NC 16346 \NC $ 285,337.8 \NC 1209.26 \NC $ 11,200 \NC $ 4,500,000 \NC 0.272 \NC 4.21 \NC\NR \NC Men \NC 10147 \NC $ 332,687.1 \NC 1579.00 \NC $ 12,000 \NC $ 4,500,000 \NC 0.235 \NC 3.48 \NC\NR \NC Women \NC 6199 \NC $ 207,832.8 \NC 1387.20 \NC $ 11,200 \NC $ 1,800,000 \NC 0.26 \NC 3.77 \NC\NR \NC[nc=8] 1994 \NC\NR \NC ALL \NC 16346 \NC $ 285,337.8 \NC 1209.26 \NC $ 11,200 \NC $ 4,500,000 \NC 0.272 \NC 4.21 \NC\NR \NC Men \NC 10147 \NC $ 332,687.1 \NC 1579.00 \NC $ 12,000 \NC $ 4,500,000 \NC 0.235 \NC 3.48 \NC\NR \NC Women \NC 6199 \NC $ 207,832.8 \NC 1387.20 \NC $ 11,200 \NC $ 1,800,000 \NC 0.26 \NC 3.77 \NC\NR \NC[nc=8] 1996 \NC\NR \NC ALL \NC 16346 \NC $ 285,337.8 \NC 1209.26 \NC $ 11,200 \NC $ 4,500,000 \NC 0.272 \NC 4.21 \NC\NR \NC Men \NC 10147 \NC $ 332,687.1 \NC 1579.00 \NC $ 12,000 \NC $ 4,500,000 \NC 0.235 \NC 3.48 \NC\NR \NC Women \NC 6199 \NC $ 207,832.8 \NC 1387.20 \NC $ 11,200 \NC $ 1,800,000 \NC 0.26 \NC 3.77 \NC\NR \NC[nc=8] 1998 \NC\NR \NC ALL \NC 16346 \NC $ 285,337.8 \NC 1209.26 \NC $ 11,200 \NC $ 4,500,000 \NC 0.272 \NC 4.21 \NC\NR \NC Men \NC 10147 \NC $ 332,687.1 \NC 1579.00 \NC $ 12,000 \NC $ 4,500,000 \NC 0.235 \NC 3.48 \NC\NR \NC Women \NC 6009 \NC $ 207,832.8 \NC 1387.20 \NC $ 11,200 \NC $ 1,800,000 \NC 0.26 \NC 3.77 \NC\NR \NC[nc=8] 1999 \NC\NR \NC ALL \NC — \NC $ 362,625.2 \NC 1775.50 \NC $ 25,247 \NC $ 10,600,000 \NC 0.269 \NC 3.99 \NC\NR \NC Men \NC 8034 \NC $ 419,193.3 \NC 2614.59 \NC $ 25,247 \NC $ 10,600,000 \NC 0.249 \NC 3.63 \NC\NR \NC Women \NC 6101 \NC $ 288,134.4 \NC 1861.66 \NC $ 54,000 \NC $ 1,900,000 \NC 0.249 \NC 3.52 \NC\NR \stopTABLEbody \stopTABLEfoot \NC[nc=8]* $ = New Taiwan Dollars \NC\NR \stopTABLEfoot \stopTABLE} Table~\in[tab:five] on page~\at[tab:five] gives the group in column one, number in sample in column two, mean in column three, standard deviation in column four, minimum salary in column five, maximum salary in column six, Gini coefficient in column seven and the 80/20 ratio in column eight. The overall mean as well as means for both men and women rose from 1980 through 1999. The population GINI fell while the GINI for men dropped between 1980 and 190, then rose from 1990 to 1999. The GINI for women fell continuously. The population 80/20 ration fell across years, while the men’s 80/20 ratio dropped then rose, and the women’s 80/20 ration fell continuously. However, these figures do not tell us what has happened within or between the distributions during this 20 year span. I used salaried earnings, \formula{SAL}; women’s salary, \formula{Y^f} and men’s salary, \formula{Y^m}, . I restricted my sample by \formula{AGE} to those of legal working age. In Taiwan these are individuals greater than 14 years old but less than 66. I also restrict to non-farm, full-time salaried employees. The primary reasons for restricting the sample to fulltime salaries employees is control for unobserved heterogeneity in the fulltime versus part time, and salaried versus self-employed decisions of individuals. \stoptext </example> Wolfgang