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on China |
| By: | Wenting Wei |
| Keywords: | Governance-E-Government Private Sector Development-Business Environment Macroeconomics and Economic Growth-Investment and Investment Climate |
| Date: | 2024–03 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:wboper:41326 |
| By: | Hiroaki MORI; Kiho MUROGA; Akira SASAHARA |
| Abstract: | Using the sharp increase in trade with China from 1995 to 2005 as a natural experiment, we examine the impact of international trade on Japan’s labor market and family formation. By exploiting sectoral differences in gender ratios and spatial variations in sectoral specialization, we construct gender-specific exposure measures to import competition from China and export opportunities to China and examine their effects. Our results show that import competition adversely affected manufacturing employment, reduced labor force participation, and increased unemployment rates, while export opportunities had the opposite effects. These labor market impacts were particularly pronounced among young individuals in their 20s and 30s. Additionally, we find that a trade-induced improvement in women’s relative labor market conditions increased the share of never-married men and women in their 30s and early 40s. |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:25031 |
| By: | Linda Glawe (University of Rostock); Jamel Saadaoui (University Paris 8); Can Xu (China Merchants Group) |
| Abstract: | This paper investigates nonlinearities in the inflation-growth-uncertainty relationship in Chinese provinces over the period 1992 to 2017 using nonlinear models and dynamic panel threshold models. We find that for the full sample period (1992–2017), inflation rates exceeding 9.7% are associated with a positive growth effect (β2 = 0.03). Below this threshold, the correlation is insignificant. Since inflation rates above 9.7% were mainly observed in the early to mid-1990s, we restrict the sample to 1999–2017. In this period, the inflation threshold lowers to approximately 5.1%. Moreover, the relationship between inflation and growth shifts across the two regimes: below 5%, inflation is positively associated with growth (β1 = 0.01), while above 5%, the effect turns negative and statistically insignificant. We further explore whether the effect of inflation on growth could be affected by uncertainty at the provincial level. For that purpose, we combine two recent uncertainty indices for the Chinese economy that are based on Chinese newspapers. We find that inflation only has a positive effect on growth for low-levels of uncertainty. For high-levels of uncertainty, the effect of inflation on growth turns negative and statistically insignificant. |
| Keywords: | Inflation, economic growth, Chinese economy, nonlinearities, uncertainty, dynamic panel threshold models |
| JEL: | E |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:inf:wpaper:2025.4 |
| By: | Wu, Qiang; Zhou, Peng (Cardiff Business School, Cardiff University) |
| Abstract: | Artificial intelligence (AI) is crucial in achieving the carbon peak and neutrality goals and mitigating climate change. Although previous studies have explored cross-sectional differences in corporate carbon emissions, temporal heterogeneities in firm lifecycles have been overlooked. Therefore, this study investigates the effect of AI adoption on carbon emission intensity over firm lifecycles and the micro-level mechanisms of this effect. This study examines panel data from Chinese listed companies (2010–2021) using a two-way fixed-effects model and the difference-in-differences method. The empirical results demonstrate that AI significantly reduces enterprises’ carbon emission intensity. However, this effect is mainly observed in growth-stage enterprises and not in decline-stage enterprises. The mechanism analysis reveals that AI primarily reduces enterprises’ carbon emission intensity by improving productivity and promoting innovation. The effect on productivity is particularly evident in growth-stage enterprises, whereas the effect on innovation is dominant in decline-stage enterprises. Heterogeneity tests indicate that the effect on state-owned enterprises, medium-sized enterprises, the manufacturing sector, heavily polluting industries, non-high-tech industries, and capital-intensive industries is more pronounced than that on other enterprises. These findings suggest that enterprises should actively adopt AI, and differentiated AI adoption strategies should be formulated based on the needs of enterprises at different lifecycle stages. |
| Keywords: | artificial intelligence; carbon emission intensity; firm lifecycle; productivity |
| JEL: | O31 O32 O33 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:cdf:wpaper:2025/9 |