# Question: The table summarizes results of a logistic regression model for

The table summarizes results of a logistic regression model for predictions about first home purchase by young married households. The response variable is whether the subject owns a home (1 = yes, 0 = no). The explanatory variables are husband’s income, wife’s income (each in ten-thousands of dollars), the number of years the respondent has been married, the number of children aged 0–17 in the household, and an indicator variable that equals 1 if the subject’s parents owned a home in the last year the subject lived in the parental home.

a. Explain why, other things being fixed, the probability of home ownership increases with husband’s earnings, wife’s earnings, the number of children, and parents’ home ownership.

b. From the table, explain why the number of years married seems to show little evidence of an effect, given the other variables in the model.

Results of logistic regression for probability of home ownership

Source: Data from J. Henretta, “Family Transitions, Housing Market Context, and First Home Purchase,” Social Forces, vol. 66, 1987, pp. 520–536.

a. Explain why, other things being fixed, the probability of home ownership increases with husband’s earnings, wife’s earnings, the number of children, and parents’ home ownership.

b. From the table, explain why the number of years married seems to show little evidence of an effect, given the other variables in the model.

Results of logistic regression for probability of home ownership

Source: Data from J. Henretta, “Family Transitions, Housing Market Context, and First Home Purchase,” Social Forces, vol. 66, 1987, pp. 520–536.

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