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Where do people really work the longest hours?


One of the central questions in macroeconomics is why income per capita differs so dramatically across countries. The companion policy question is what low-income countries can do to bring about sustained improvements in their average living standards. Unfortunately, economists are still a long way from delivering reliable policy recommendations about how to create development. Good policy recommendations require a clear understanding of the determinants of development, and research on this important topic is still in many ways in its infancy.

One approach taken by macroeconomists in this literature is ‘development accounting’, which tries to account for cross-country differences in output per worker using measurable differences in inputs per worker. In an influential study, Caselli (2005) concluded that differences in inputs could account for at most half of the vast differences in output per worker observed in the Penn World Tables. The lesson is that to understand development, researchers should focus their attention on theories working through total factor productivity, which captures the overall efficiency of input use, rather than the accumulation of those inputs themselves. Of course this is not an easy task, but at least development accounting provides some guidance on what types of models to develop and test.1

Unfortunately, the conclusions from development accounting are only as reliable as the cross-country data on output per worker and productive inputs per worker, and neither are measured with great precision. Consider the basic question: Do adults in rich countries work more hours on average than adults in poor countries? Existing cross-country evidence does not provide an answer, even though aggregate labour input is one of the basic components of productive inputs.

Conventional wisdom says that low labour effort could be the cause of low income in the tropics, where most of the world’s poor countries are located. Landes (1999), for example, emphasised how the hot and humid climate of the tropics made it very difficult to supply labour.

Our new paper is the first to assemble an internationally comparable data set on average hours worked per adult across the full world income distribution (Bick et al. 2016). Much of the paper addresses measurement issues that have hampered cross-country comparability in previous studies, like how to deal with multiple jobs (we include all of them) or jobs that may be informal (we include them) or which measure of hours to use (we use ‘actual hours last week,’ not ‘usual hours per week’). We also deal with seasonality of hours over the year by only relying on surveys that cover the whole year. We do not want to include surveys that cover a country only during one month, which may be the period right before the harvest when workers are mostly idle, or mid-August, when Europeans all seem to be taking their synchronised beach holidays.

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