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statawalk4

# statawalk4 - Stata Walkthrough 4 Regression Prediction and...

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Stata Walkthrough 4: Regression, Prediction, and Forecasting Over drinks the other evening, my neighbor told me about his 25 - year - old nephew, who is dating a 35 - year - old woman. God, I can t see them getting married, he said. I raised my eyebrow, because as an economic demographer, I know that spouses ages are very predictable: they tend to be similar, with the husband just a couple of years older than his wife. Strange cases do occur, but they tend to involve older men and younger women. The opposite is fairly unlikely. However, I didn t know exactly what would constitute a range of likely outcomes for the age of the woman that a 25 - year - old guy would marry. In this Stata exercise, we re going to do two things: 1. We will use data on married couples ages to estimate the relationship between spouses ages. 2. We will use this to predict a range of likely outcomes for the age of the wife of a twenty - five - year - old man. You ll need to load the database of U.S. married couples, March 2005 ( marriedmar05.dta ) from my webpage. These data come from the Current Population Survey ( done by the Bureau of Labor Statistics ) , and they are a random sample of all households in the U.S. I have restricted the sample to only couples that identify themselves as married. We have 34,674 of these couples. In general, you should begin any project by exploring the data. In this case, that s simple, since this database contains two variables: hage and wage , the husband s age and the wife s age. First, let s look at some descriptive statistics: type summarize . Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- wage | 34674 45.78664 13.26782 15 79 hage | 34674 48.07369 13.62849 15 79 Values of each variable range from 15 to 79. The mean age of a married man is 48.1 years, and the mean age of a married woman is 45.8 years. We can see that there s a strong correlation between the two variables by typing corr hage wage :

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| wage hage -------------+------------------ wage | 1.0000 hage | 0.9243 1.0000 In other words, older men tend to be married to older women this should be no surprise. However, the sample means reveal that married men are older than married women on average, so we can also infer that typically each husband must be older than his wife. We might be interested in the distribution of the age difference, so let s create a new variable for the difference in ages: gen dage = hage – wage label variable dage "Difference between spouses' ages" Now let s look at the frequency distribution of this variable by typing histogram dage The image is a bit ugly. First, the graph goes from - 50 to +50, even though there s basically nobody out in those tails. ( There are some people, but they re not significant enough to register in the graph. ) For all practical purposes, the range goes from - 20 to +30, so we ll restrict it to that. Second, Stata is using a default bin - width of 2.44 units. There s a natural width in this case, I d think: one, a single year. Let s tell Stata to make each bin of width one. Third, there aren t nearly enough tick
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statawalk4 - Stata Walkthrough 4 Regression Prediction and...

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