You are interested in the effect that different patterns of time use have on performance at...

 

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You are interested in the effect that different patterns of time use have on performance at university. You survey n = 250 students, asking them to record how much time they spend per week in study, sleep, (paid) work or leisure, during term. (All activities must be classified into one of the four categories, so that for each student the total hours recorded across the four activities must add up to 168 hours.) For each of these students, you also record their performance on a piece of work assessed at the end of the term (score). You formulate the causal model score = Bo + Bistudy + B₂sleep + B3work + Bleisure + u (1) (a) In the model (1), can 31 be interpreted as the causal effect of study on score? Does it make sense to hold sleep, work and leisure constant while varying study? (b) Could the model (1) be estimated by OLS, using the data you have collected? (c) Explain how you could reformulate the model (1) so that its parameters can be more usefully interpreted, and be estimated by OLS regression. You are interested in the effect that different patterns of time use have on performance at university. You survey n = 250 students, asking them to record how much time they spend per week in study, sleep, (paid) work or leisure, during term. (All activities must be classified into one of the four categories, so that for each student the total hours recorded across the four activities must add up to 168 hours.) For each of these students, you also record their performance on a piece of work assessed at the end of the term (score). You formulate the causal model score = Bo + Bistudy + B₂sleep + B3work + Bleisure + u (1) (a) In the model (1), can 31 be interpreted as the causal effect of study on score? Does it make sense to hold sleep, work and leisure constant while varying study? (b) Could the model (1) be estimated by OLS, using the data you have collected? (c) Explain how you could reformulate the model (1) so that its parameters can be more usefully interpreted, and be estimated by OLS regression.

Answer rating: 100% (QA)

a Yes it makes sense to keep all other variables at constant if we want to know the ... View the full answer