Skills, Population Aging, and the Pattern of Trade

Gu, Ke; Stoyanov, Andrey

doi:10.2139/ssrn.3115922

Cited by 2 publications

(4 citation statements)

References 29 publications

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“…Gregory and Patuelli (2015) and Arntz and Gregory (2014) meanwhile focus on the effect of age structure on regional development within Germany. Gu and Stoyanov (2019) find that the changing age structure of advanced economies has changed what industries these countries have comparative advantage in, and has thus shifted their trade patterns.…”

Section: Related Literaturementioning

confidence: 96%

“…This implies that regional and national policymakers should both pay attention to demographic projections, and incentivise the emergence of industries that can thrive in their particular demographic environment in the long run. In other words, similarly to Gu and Stoyanov (2019), this study emphasises the connection between the comparative advantage of an economy and its age structure.…”

Section: Retirement Agementioning

confidence: 96%

“…vocabulary) peak around ages 40-55 (Hartshorne and Germine, 2015;Whitley et al, 2016). In addition, Gu and Stoyanov (2019) reviews an extensive literature suggesting that older people find it harder to adapt to changes and learn new skills. Firmlevel evidence also suggests that different age groups are not perfectly substitutable.…”

Section: Related Literaturementioning

confidence: 99%

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Age diversity and aggregate productivity

Zelity

2022

J Popul Econ

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This research explores theoretically, empirically and quantitatively the role of age diversity in determining aggregate productivity and output. Age diversity has two conflicting effects on output. On the one hand, due to skill complementarity across different cohorts, age diversity may be beneficial. On the other hand, rapid skill-biased technological change makes age diversity costly as up-to-date education tends to be concentrated among younger cohorts. To study this trade-off, I first build an overlapping-generations (OLG) model which, in view of these two opposing forces, predicts a hump-shaped relationship between age diversity and GDP per capita. This prediction is established analytically, and also quantitatively using real-world population data in an extended computational version of the model. The prediction is then tested using country-level panel data with a novel instrument, and regional data from Europe. Moving one standard deviation closer to the optimal level of age diversity is associated with a 1.5% increase in GDP per capita. In addition, consistent with the predictions of the model, the optimal level of age diversity is lower in economies where skill-biased technological change is more prevalent.

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Section: Related Literaturementioning

confidence: 96%

Section: Retirement Agementioning

confidence: 96%

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Age diversity and aggregate productivity

Zelity

2022

J Popul Econ

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“…Referring to the studies on aging and export, it is observable that the quantity of labor forces would affect a country's export structure. A country with higher proportion of aging population would accumulate capital factor, thus it will export capital-intensive products due to more comparative advantage in this segment [2][8].…”

Section: Research On the Relationship Between Aging And Exportmentioning

confidence: 99%

Study on the Impact of Aging Population on China’s Manufacturing Export Structure

Fu¹,

Liu²

2023

Advances in Computer Science Research

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China has entered the aging phase since late 1990s and the process has been accelerating in recent years. Aging population has gradually affected China's demographic dividend and applied potential impact on international trade. This paper reviews literatures in this territory and compares both the aging status and high-tech manufacturing export structure within main economies. An empirical analysis with 26 provincial and 15 year-long panel statistics has been conducted in the paper. The results indicate a positive impact that China's aging population has on the country's manufacturing export structure. Meanwhile, manufacturing development level, FDI, human capital as well as R&D input also have respective relationship with the studying object. Corresponding suggestions based on the analysis have been proposed to optimize the country's export.

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Skills, Population Aging, and the Pattern of Trade

Cited by 2 publications

References 29 publications

Age diversity and aggregate productivity

Age diversity and aggregate productivity

Study on the Impact of Aging Population on China’s Manufacturing Export Structure

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