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on China |
| By: | Shi, Xiangyu |
| Abstract: | Why China was not the origin of the Industrial Revolution but rose from imperial dynasties and experienced a growth miracle in the past four decades? We find that its root is China's imperial examination system (keju), which explains the fall and rise of historical, modern, and contemporary China. Using three instrumental variable approaches, we find that keju significantly facilitates contemporary innovation and business creation, by raising the contemporaneous level of human capital, shaping an innovative and productive culture, and fostering efficient institutions. Keju had positive effects on the development of modern China before the People's Republic of China era, but its effects were most salient after the economic reform in 1978. In historical periods, keju diverted talents away from scientific/technological sectors, leading to sluggish development in the Ming and Qing dynasties. |
| Keywords: | imperial examination system, human capital, culture, institution, innovation, business creation, China |
| JEL: | D2 E2 J2 N3 O1 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:121348 |
| By: | Robert Flynn; Britta Glennon; Raviv Murciano-Goroff; Jiusi Xiao |
| Abstract: | This paper examines the impact of rising U.S.-China geopolitical tensions on three main dimensions of science: STEM trainee mobility between these countries, usage of scientific works between scientists in each country, and scientist productivity in each country. We examine each dimension from a “U.S.” perspective and from a “China” perspective in an effort to provide evidence around the asymmetric effects of isolationism and geopolitical tension on science. Using a differences-in-differences approach in tandem with CV and publication data, we find that between 2016 and 2019 ethnically Chinese graduate students became 16% less likely to attend a U.S.-based Ph.D. program, and that those that did became 4% less likely to stay in the U.S. after graduation. In both instances, these students became more likely to move to a non-U.S. anglophone country instead. Second, we document a sharp decline in Chinese usage of U.S. science as measured by citations, but no such decline in the propensity of U.S. scientists to cite Chinese research. Third, we find that while a decline in Chinese usage of U.S. science does not appear to affect the average productivity of China-based researchers as measured by publications, heightened anti-Chinese sentiment in the U.S. appears to reduce the productivity of ethnically Chinese scientists in the U.S. by 2-6%. Our results do not suggest any clear “winner, ” but instead indicate that increasing isolationism and geopolitical tension lead to reduced talent and knowledge flows between the U.S. and China, which are likely to be particularly damaging to international science. The effects on productivity are still small but are likely to only grow as nationalistic and isolationist policies also escalate. The results as a whole strongly suggest the presence of a “chilling effect” for ethnically Chinese scholars in the U.S., affecting both the U.S.’s ability to attract and retain talent as well as the productivity of its ethnically Chinese scientists. |
| JEL: | F22 F6 O3 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:32622 |
| By: | Shi, Xiangyu; Gong, Jiaowei; Zhang, Xin; Wang, Chang |
| Abstract: | Using a novel city-level high-frequency panel data set of social and public events in Chinese cities, we document that extreme high temperatures significantly reshape social dynamics. Extreme high temperatures lead to an increase in social cooperation, and the effects are more salient when productivity is lower and labor is more intensively used. This implies extreme high temperatures boost the relative returns of cooperation given lowered productivity. Our estimates and quantitative model suggest that the human race adapts to global warming by reshaping its social dynamics: adaptation via social dynamics offsets about one-third of the negative impacts of extreme high temperatures on the economy. |
| Keywords: | Social dynamics; Public events; Social cooperation; Protest; Temperatures; Climate change; China |
| JEL: | D7 D9 O1 Q5 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:121358 |
| By: | Yanqing Yang; Xingcheng Xu; Jinfeng Ge; Yan Xu |
| Abstract: | This paper aims to explore the application of machine learning in forecasting Chinese macroeconomic variables. Specifically, it employs various machine learning models to predict the quarterly real GDP growth of China, and analyzes the factors contributing to the performance differences among these models. Our findings indicate that the average forecast errors of machine learning models are generally lower than those of traditional econometric models or expert forecasts, particularly in periods of economic stability. However, during certain inflection points, although machine learning models still outperform traditional econometric models, expert forecasts may exhibit greater accuracy in some instances due to experts' more comprehensive understanding of the macroeconomic environment and real-time economic variables. In addition to macroeconomic forecasting, this paper employs interpretable machine learning methods to identify the key attributive variables from different machine learning models, aiming to enhance the understanding and evaluation of their contributions to macroeconomic fluctuations. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.03595 |
| By: | Shi, Xiangyu; Wang, Chang |
| Abstract: | Input-output linkages among sectors and firms are largely overlooked when assessing regulatory policies. Using a carbon emissions regulation in China as an example, we find that the regulation facilitates the transition to green technologies and reduces entry and carbon emissions in the regulated sectors with large carbon emissions. We also find unintended spillovers via the input-output network, resulting in more entry and innovation in the downstream sectors; and less entry and innovation in the upstream sectors. These facts can be rationalized by a firm-dynamics model with input-output linkages. The results of quantitative exercises are much different when taking input-output linkages into account. |
| Keywords: | carbon emissions regulation; firm dynamics; innovation; input-output networks |
| JEL: | C1 D2 E2 L2 Q5 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:121359 |
| By: | Mr. Diego A. Cerdeiro; Parisa Kamali; Siddharth Kothari; Mr. Dirk V Muir |
| Abstract: | This paper estimates the costs of ‘de-risking’ scenarios between China and OECD members at the aggregate and sectoral levels. Aggregate large-scale de-risking – reshoring by increasing reliance on domestic production and friend-shoring by reducing imports from specific foreign countries – is quantified with the IMF’s GIMF model, suggesting significant permanent effects on the global economy. Returning integration to 2000 levels translates into long-term global GDP losses of 4.5 percent under reshoring and as much as 1.8 percent under friend-shoring. Friend-shoring does not necessarily deliver a boon to third countries as trade diversion benefits might be largely offset by contractions in China and OECD members. Sectoral de-risking, where all trade between rivals is eliminated in specific products, is quantified through empirical estimation of the scope for quality downgrading. The results demonstrate the potential for significant losses in input quality should there be an escalation in export bans. Losses are asymmetric against China in the specific case of semiconductors but can be significant for both sides in other sectors—including in critical areas such as environmental goods. |
| Keywords: | De-risking; fragmentation; reshoring; friend-shoring; export bans; quality downgrading. |
| Date: | 2024–06–21 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2024/122 |
| By: | Ling Cen; Lauren Cohen; Jing Wu; Fan Zhang |
| Abstract: | Using both the onset of the US-China trade war in 2018 and the most recent Russia-Ukraine war and associated trade tensions, we show a counterintuitive pattern in global trade. Namely, while the average firm trading with these nations significantly decreases their trade with these jurisdictions following sanctions, government-linked firms show a marked contrast. In particular, government-linked firms actually significantly increase their trading activity following the onset of formal sanctions. The increase is large - roughly 33% (t=4.01). We find no increase broadly to other countries (even countries in the same regions) at the same time, nor of these same firms in these same regions at other times. In terms of mechanism, government-linked supplier firms are nearly twice as likely to receive tariff exemptions. More broadly, these effects are increasing in the level of government connection. For instance, firms geographically closer to the government agencies they supply increase their imports more acutely. Using micro-level data, government-supplying firms recruiting more employees with past government work experience also increase trading activity more – particularly when the past employee worked in a government-contracting role. Lastly, this results in sizable accrued benefits in terms of firm-level profitability, market share gains, and outsized stock returns. |
| JEL: | F42 F51 G15 G38 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:32621 |