Tobit or OLS? An Empirical Evaluation Under Different Diary Window Lengths

Time use researchers frequently debate whether it is more appropriate to fit censored regression (Tobit) models using maximum likelihood estimation or linear models using ordinary least squares (OLS) to explain individuals’ allocations of time to different activities as recorded in time-diary data. One side argues that estimation of Tobit models addresses the significant censoring (i.e., large numbers of zeros) typically found in time-diary data and that OLS estimation leads to biased and inconsistent estimates. The opposing side argues that optimization occurs over a longer period than that covered by the typical time diary, and thus that reported zeros represent measurement error rather than true non-participation in the activity, in which case OLS is preferred. We use the Australian Time Use Surveys, which record information for two consecutive diary days, to estimate censored and linear versions of a parental child care model for both 24-hour and 48-hour windows of observation in order to determine the empirical consequences of estimation technique and diary length. We find a moderate amount of measurement error when we use the 24-hour window compared to the 48-hour window, but a large number of zeros in the shorter window remain zeroes when we double the window length. Most of the qualitative conclusions we draw are similar for the two windows of observation and the two estimation methods, although there are some slight differences in the magnitudes and statistical significance of the estimates. Importantly, Tobit estimates appear to be more sensitive to window length than OLS estimates.Tobit; OLS; time-diary data

The Multitasking of Household Production

The standard household production model does not incorporate multitasking, although time-diary data reveal that individuals regularly multi-task. We formulate a model where time spent in child care can be sole-tasked or multitasked with other household production activities. This model implies associations between household productivity factors and both child outcomes and parental time use. We then use data from the Longitudinal Study of Australian Children and the Australian Time Use Surveys to examine the empirical validity of these implications. Consistent with our model's predictions, household productivity factors are associated both with child outcomes and parental time use.

The Multitasking of Household Production

The standard household production model does not incorporate multitasking, although time-diary data reveal that individuals regularly multitask. We formulate a model where time spent in child care can be sole-tasked or multitasked with other household production activities. This model implies associations between household productivity factors and both child outcomes and parental time use. We then use data from the Longitudinal Study of Australian Children and the Australian Time Use Surveys to examine the empirical validity of these implications. Consistent with our model’s predictions, household productivity factors are associated both with child outcomes and parental time use.multitasking, child care, household production

Time to Work or Time to Play: The Effect of Student Employment on Homework, Sleep, and Screen Time

We use detailed time-diary information on high school students’ daily activities from the 2003–2008 American Time Use Surveys (ATUS) to investigate the effects of employment on the time a student spends on homework and other major activities. Time-diary data are more detailed and accurate than data derived from responses to “usual activity” survey questions underlying other analyses and capture the immediate effects of working that may well accumulate over time to affect future outcomes. Our results suggest that employment decreases the time that high school students spend on homework, which is human-capital building, on all days, but also decreases screen time on non-school days, which may be considered unproductive time. Employed teens get more than the recommended amount of sleep on school days, and only slightly less on non-school days.teenagers, employment, high school, time allocation

Minimum Wages and Teen Employment: A Spatial Panel Approach

The authors employ spatial econometrics techniques and Annual Averages data from the U.S. Bureau of Labor Statistics for 1990-2004 to examine how changes in the minimum wage affect teen employment. Spatial econometrics techniques account for the fact that employment is correlated across states. Such correlation may exist if a change in the minimum wage in a state affects employment not only in its own state but also in other, neighboring states. The authors show that state minimum wages negatively affect teen employment to a larger degree than is found in studies that do not account for this correlation. Their results show a combined direct and indirect effect of minimum wages on teen employment to be -2.1% for a 10% increase in the real effective minimum wage. Ignoring spatial correlation underestimates the magnitude of the effect of minimum wages on teen employment.minimum wage, teen employment, spatial econometrics

Parental Transfers, Student Achievement, and the Labor Supply of College Students

Using nationally representative data from the NLSY97, financial motivations for and the effects of employment on U.S. college students’ academic performance are examined. While it is expected that fewer financial resources and a higher cost of college cause greater student employment, the data indicate that the number of hours a student works per week is unaffected by either the level of parental transfers or the cost of schooling. Contrary to existing evidence that a greater number of hours worked leads to poorer academic performance, the number of hours worked per week does not negatively affect a student’s GPA and may actually improve it.schooling, educational finance, grades, college students

Parental Transfers, Student Achievement, and the Labor Supply of College Students

Using nationally representative data from the NLSY97 and a simultaneous equations model, this paper analyzes the financial motivations for and the effects of employment on U.S. college students’ academic performance. The data confirm the predictions of the theoretical model that lower parental transfers and greater costs of attending college increase the number of hours students work while in school, although students are not very responsive to these financial motivations. They also provide some evidence that greater hours of work lead to lower grade point averages (GPAs).employment, transfers, GPA

Parental Transfers, Student Achievement, and the Labor Supply of College Students

Using nationally representative data from the NLSY97 and a simultaneous equations model, this paper analyzes the financial motivations for and the effects of employment on U.S. college students’ academic performance. The data confirm the predictions of the theoretical model that lower parental transfers and greater costs of attending college increase the number of hours students work while in school, although students are not very responsive to these financial motivations. They also show that increased hours of work lead to lower grade point averages (GPAs), at least for students attending four-year colleges.employment, transfers, GPA

Time to Work or Time to Play: The Effect of Student Employment on Homework, Housework, Screen Time, and Sleep

Recent research suggests that working while in high school reduces the amount of time students spend doing homework. However, an additional hour of work leads to a reduction in homework by much less than one hour, suggesting a reduction in other activities. This paper uses data from the 2003-2007 American Time Use Surveys (ATUS) to investigate the effects of market work on the time students spend on homework, sleeping, household work, and screen time. Results show that an increase in paid work reduces time spent in all of these activities by 84%, with the largest effect found for screen time.teenagers, time allocation, homework, screen time, sleep

Time to Work or Time to Play: The Effect of Student Employment on Homework, Sleep, and Screen Time

We use detailed time-diary information on high school students' daily activities from the 2003-2008 American Time Use Surveys (ATUS) to investigate the effects of employment on the time a student spends on homework and other major activities. Time-diary data are more detailed and accurate than data derived from responses to 'usual activity' survey questions underlying other analyses and capture the immediate effects of working that may well accumulate over time to affect future outcomes. Our results suggest that employment decreases the time that high school students spend on human-capital-building activities such as homework and extracurricular activities, but also decreases screen time, which may be considered unproductive time. Results for sleep suggest that working teens may not suffer from reduced sleep time.teenagers, employment, high school, time allocation