As part of an economic stimulus program, tax rebate checks were mailed to American households during the summer of 2001. Did households use these rebates in ways that would help stimulate the economy? Exploiting the panel data aspect of the CE, Johnson, Parker, and Souleles (2006) found that households spent roughly two-thirds of their rebate checks during the first six months after receipt. This study was possible because of the addition of questions to the CE to collect information about the amount of the stimulus checks and when they were received.
A similar economic stimulus program was initiated in May 2008. To analyze the 2008 stimulus, questions were again added to the CE about the rebate checks, including a question about what the households explicitly did with the checks. Paulin (2011) found that 49 percent of recipients used the money to pay off debt, while 30 percent reported that they spent the money. Younger recipients were more likely to spend the rebate than were older recipients.
CE Data Lead to a Better Understanding of the American Household
Gender Makes a Difference
Can the relative contributions to running a household by the members of that household be measured? Does gender make a difference in the value of the contribution? De Ruijter, Treas, and Cohen (2005) used data from the CE to “value” some routine domestic tasks, and categorized those tasks as typically “male” or “female.” For example, doing laundry might be a typically “female” task, while mowing the lawn a typically “male” task. They “valued” these tasks by equating their value with the amount households spent when they outsourced those specific domestic services. They also examined how those expenditures differ by living arrangement.
In an examination of the effect of gender on certain purchasing patterns, Kroshus (2008) assessed how much was spent by households on commercially prepared food (as a percent of total food expenditures) by gender and marital status. Not surprisingly, households headed by unmarried men spend a higher percent of their food expenditures on commercially prepared food.
Age Makes a Difference
Fisher et al. (2007) used 20 years of CE data to examine financial characteristics of older adults related to their home. As individuals grow older, their homes become increasingly mortgage-free. Even though this usually means that home equity also increases over this time period, few older