TABLE 5.25 Effects of Income, Age, Education, Race, and Family Composition on the Share of Household Expenditures Attributable to Immigrant Labor

 

All Immigrants

Variable

Coefficient

Standard Error

Logarithm of household income

0.011

0.0000

Age

-0.001

0.0000

Age > 65

0.017

0.0002

Less than high school

-0.014

0.0001

Some college

0.021

0.0001

College degree

0.035

0.0001

Black

-0.004

0.0002

Other

0.006

0.0003

Husband, wife, no children, both work

0.000

0.0002

Husband, wife, and children < 6

-0.000

0.0004

Husband, wife, and children < 6, both work

-0.001

0.0003

Husband, wife, and children > 5

-0.001

0.0003

Husband, wife, and children > 5, both work

-0.001

0.0002

Single male parent

-0.000

0.0006

Single female parent

0.001

0.0003

Single males

0.002

0.0002

Single female

0.002

0.0002

Other composition

-0.000

0.0002

Note: The dependent variable is the share of expenditures attributable to immigrant labor multiplied by 100.

the lower portion of Table 5.24). This is so because these households spend a greater proportion of their income on services, in particular household services and food consumption away from home, both expenditure categories with relatively high immigrant labor shares.

As a final summary, Table 5.25 presents estimates that simultaneously examine the effects of various consumer characteristics—such as household income, education level and race of the head of household, and household composition—on the share of household expenditures attributable to immigrant labor. The estimates come from a linear regression model and so give differences in expenditure shares associated with particular characteristics, holding constant each of the other characteristics of the household. So, for example, the coefficient for college degree indicates that the share of expenditures attributable to immigrant labor among those with a college degree is on average 0.035 percentage point larger than the reference group (high school graduates) after adjustment for associated differences in average income levels, race, age, and household composition.

Controlling for all these variables together does not substantively alter any of the conclusions that one would derive from the simple averages presented earlier.



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