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Why do living standards differ so much across countries? A consensus in the development literature is that differences in productivity are a dominant source of these differences. But what accounts for productivity differences across countries? One explanation is that frontier technologies and best practice methods are slow to diffuse to low income countries. The recent literature on misallocation offers a distinct but complementary explanation: low income countries are not as effective in allocating their factors of production to their most efficient use. We provide our perspective on three key questions. First, how important is misallocation? Second, what are the causes of misallocation? And third, beyond the direct cost of lower contemporaneous output, are there additional costs associated with misallocation? A summary of our answers is as follows. Misallocation appears to be a substantial channel in accounting for productivity differences across countries, but the measured magnitude of the effects depends on the approach and context. Researchers have not yet found a dominant source of misallocation; instead, many specific factors seem to contribute a small part of the overall effect. Beyond the static cost of misallocation, we believe that the dynamic effects of misallocation on productivity growth are significant and deserve much more attention going forward.
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We document a robust negative relationship between the log of mean annual hours in an occupation and the standard deviation of log annual hours within that occupation. We develop a unified model of occupational choice and labor supply that features heterogeneity across occupations in the return to working additional hours and show that it can match the key features of the data both qualitatively and quantitatively. We use the model to shed light on gender differences in labor market outcomes that arise because of gender asymmetries in home production responsibilities. Our model generates large gender gaps in hours of work, occupational choices, and wages. In particular, an exogenous difference in time devoted to home production of ten hours per week increases the observed gender wage gap by roughly eleven percentage points and decreases the share of females in high hours occupations by fourteen percentage points. The implied misallocation of talent across occupations has significant aggregate effects on productivity and welfare.
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Why do living standards differ so much across countries? A consensus in the development literature is that differences in productivity are a dominant source of these differences. But what accounts for productivity differences across countries? One explanation is that frontier technologies and best practice methods are slow to diffuse to low income countries. The recent literature on misallocation offers a distinct but complementary explanation: low income countries are not as effective in allocating their factors of production to their most efficient use. We provide our perspective on three key questions. First, how important is misallocation? Second, what are the causes of misallocation? And third, beyond the direct cost of lower contemporaneous output, are there additional costs associated with misallocation? A summary of our answers is as follows. Misallocation appears to be a substantial channel in accounting for productivity differences across countries, but the measured magnitude of the effects depends on the approach and context. Researchers have not yet found a dominant source of misallocation; instead, many specific factors seem to contribute a small part of the overall effect. Beyond the static cost of misallocation, we believe that the dynamic effects of misallocation on productivity growth are significant and deserve much more attention going forward.
Choose an application
We document a robust negative relationship between the log of mean annual hours in an occupation and the standard deviation of log annual hours within that occupation. We develop a unified model of occupational choice and labor supply that features heterogeneity across occupations in the return to working additional hours and show that it can match the key features of the data both qualitatively and quantitatively. We use the model to shed light on gender differences in labor market outcomes that arise because of gender asymmetries in home production responsibilities. Our model generates large gender gaps in hours of work, occupational choices, and wages. In particular, an exogenous difference in time devoted to home production of ten hours per week increases the observed gender wage gap by roughly eleven percentage points and decreases the share of females in high hours occupations by fourteen percentage points. The implied misallocation of talent across occupations has significant aggregate effects on productivity and welfare.
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