The Timing of Maternal Work and Time with Children

I use data from the American Time Use Survey to examine how maternal employment affects when during the day that mothers of pre-school-age children spend doing enriching childcare and whether they adjust their schedules to spend time with their children at more-desirable times of day. I find that employed mothers shift enriching childcare time from workdays to nonwork days. On workdays, full-time employed parents shift enriching childcare time toward evenings, but there is little shifting among part-time employed mothers. I find no evidence that full-time employed mothers adjust their schedules to spent time with their children at more-preferred times of day, whereas part-time employed mothers shift employment to later in the day.timing of activities, time use, childcare

Tobit or Not Tobit?

Time-use surveys collect very detailed information about individuals’ activities over a short period of time, typically one day. As a result, a large fraction of observations have values of zero for the time spent in many activities, even for individuals who do the activity on a regular basis. For example, it is safe to assume that all parents do at least some childcare, but a relatively large fraction report no time spent in childcare on their diary day. Because of the large number of zeros Tobit would seem to be the natural approach. However, it is important to recognize that the zeros in time-use data arise from a mismatch between the reference period of the data (the diary day) and the period of interest, which is typically much longer. Thus it is not clear that Tobit is appropriate. In this study, I examine the bias associated with alternative estimation procedures for estimating the marginal effects of covariates on time use. I begin by adapting the infrequency of purchase model, which is typically used to analyze expenditures, to time-diary data and showing that OLS estimates are unbiased. Next, using simulated data, I examine the bias associated with three procedures that are commonly used to analyze time-diary data—Tobit, the Cragg (1971) two-part model, and OLS—under a number of alternative assumptions about the data-generating process. I find that the estimated marginal effects from Tobits are biased and that the extent of the bias varies with the fraction of zero-value observations. The two-part model performs significantly better, but generates biased estimated in certain circumstances. Only OLS generates unbiased estimates in all of the simulations considered here.Tobit, time use

Tobit or Not Tobit?

Time-use surveys collect very detailed information about individuals' activities over a short period of time, typically one day. As a result, a large fraction of observations have values of zero for the time spent in many activities, even for individuals who do the activity on a regular basis. For example, it is safe to assume that all parents do at least some childcare, but a relatively large fraction report no time spent in childcare on their diary day. Because of the large number of zeros Tobit would seem to be the natural approach. However, it is important to recognize that the zeros in time-use data arise from a mismatch between the reference period of the data (the diary day) and the period of interest, which is typically much longer. Thus it is not clear that Tobit is appropriate. In this study, I examine the bias associated with alternative estimation procedures for estimating the marginal effects of covariates on time use. I begin by adapting the infrequency of purchase model, which is typically used to analyze expenditures, to time-diary data and showing that OLS estimates are unbiased. Next, using simulated data, I examine the bias associated with three procedures that are commonly used to analyze time-diary data – Tobit, the Cragg (1971) two-part model, and OLS – under a number of alternative assumptions about the data-generating process. I find that the estimated marginal effects from Tobits are biased and that the extent of the bias varies with the fraction of zero-value observations. The two-part model performs significantly better, but generates biased estimated in certain circumstances. Only OLS generates unbiased estimates in all of the simulations considered here.Tobit, time use

What Do Male Nonworkers Do?

Although male nonworkers have become a larger fraction of the population since the late 1960s, labor economists know very little about them. Using data from several sources--the March CPS, the National Longitudinal Survey of Youth, and the 1992-94 University of Maryland Time Diary Study--this paper fills that void.  The picture that emerges is that there is a small cadre of marginal workers who often do not work for periods of a year or more and tend to work relatively few weeks in the years that they do work. The vast majority of nonworking men (men who do not work at all during the year) receive unearned income from at least one source, and the amount of unearned income received varies significantly by reason for not working. Family members provide an important alternative source of support for nonworking men who have little or no unearned income of their own. For the most part, these nonworking men are not substituting nonmarket work for market work. Most of the time that is freed up by not working is spent in leisure activities and sleep.male nonworkers, time use, unearned income

"How Does Household Production Affect Earnings Inequality?: Evidence from the American Time Use Survey"

Although income inequality has been studied extensively, relatively little attention has been paid to the role of household production. Economic theory predicts that households with less money income will produce more goods at home. Thus extended income, which includes the value of household production, should be more equally distributed than money income. We find this to be true, but not for the reason predicted by theory. Virtually all of the decline in measured inequality, when moving from money income to extended income, is due to the addition of a large constant--the average value of household production--to money income. This result is robust to alternative assumptions that one might make when estimating the value of household production.

Why Do BLS Hours Series Tell Different Stories About Trends in Hours Worked?

Hours worked is an important economic indicator. In addition to being a measure of labor utilization, average weekly hours are inputs into measures of productivity and hourly wages, which are two key economic indicators. However, the Bureau of Labor Statistics’ two hours series tell very different stories. Between 1973 and 2007 average weekly hours estimated from the BLS’s household survey (the Current Population Survey or CPS) indicate that average weekly hours of nonagricultural wage and salary workers decreased slightly from 39.5 to 39.3. In contrast, average hours estimated from the establishment survey (the Current Employment Statistics survey or CES) indicate that hours fell from 36.9 to 33.8 hours per week. Thus the discrepancy between the two surveys increased from about two-and-a-half hours per week to about five-and-a-half hours. Our goal in the current study is to reconcile the differences between the CPS and CES estimates of hours worked and to better understand what these surveys are measuring. We examine a number of possible explanations for the divergence of the two series: differences in workers covered, multiple jobholding, differences in the hours concept (hours worked vs. hours paid), possible overreporting of hours in CPS, and changes in the length of CES pay periods. We can explain most of the difference in levels, but cannot explain the divergent trends.of work, Comparison of household and establishment surveys

How to Think About Time-Use Data: What Inferences Can We Make About Long- and Short-Run Time Use from Time Diaries?

Time-use researchers are typically interested in the time use of individuals, but time use data are samples of person-days. Given day-to-day variation in how people spend their time, this distinction is analytically important. We examine the conditions necessary to make inferences about the time use of individuals from a sample of person-days. We also discuss whether and how surveys with multiple household members or multiple days are an improvement over single-diary surveys.time use, estimation, survey methods

How to Think About Time-Use Data: What Inferences Can We Make About Long- and Short-Run Time Use from Time Diaries?

Time-use researchers are typically interested in the time use of individuals, but time use data are samples of person-days. Given day-to-day variation in how people spend their time, this distinction is analytically important. We examine the conditions necessary to make inferences about the time use of individuals from a sample of person-days. We also discuss whether and how surveys with multiple household members or multiple days are an improvement over single-diary surveys.Time use, survey methods, estimation

How Does Household Production Affect Earnings Inequality? Evidence from the American Time Use Survey

Although income inequality has been studied extensively, relatively little attention has been paid to the role of household production. Economic theory predicts that households with less money income will produce more goods at home. Thus extended income, which includes the value of household production, should be more equally distributed than money income. We find this to be true, but not for the reason predicted by theory. Virtually all of the decline in measured inequality when moving from money income to extended income is due to the addition of a large constant--the average value of household production--to money income. This result is robust to alternative assumptions that one might make when estimating the value of household production.Inequality, Household Production, Time Use