Article(id=1321914958451946051, tenantId=1146029695717560320, journalId=1146120045056339983, issueId=1321914957969601091, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1002-980X.J25051006, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1746806400000, receivedDateStr=2025-05-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793098686087, onlineDateStr=2026-10-27, pubDate=1769270400000, pubDateStr=2026-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793098686087, onlineIssueDateStr=2026-10-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793098686087, creator=13701087609, updateTime=1793098686087, updator=13701087609, issue=Issue{id=1321914957969601091, tenantId=1146029695717560320, journalId=1146120045056339983, year='2026', volume='45', issue='1', pageStart='1', pageEnd='130', issueExtLink='null', onlineDate='null', pubDate='1769270400000', pubDateStr='2026-01-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793098685972, creator='13701087609', updateTime=1793098877860, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321915762877509704, tenantId=1146029695717560320, journalId=1146120045056339983, issueId=1321914957969601091, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321915762877509705, tenantId=1146029695717560320, journalId=1146120045056339983, issueId=1321914957969601091, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=30, endPage=42, ext={EN=ArticleExt(id=1321914958686827076, articleId=1321914958451946051, tenantId=1146029695717560320, journalId=1146120045056339983, language=EN, title=The Structural Transition and Policy Response Mechanism of China's Short-term Cross-border Capital Flows under the Impact of Global Taxation: Embedding Analysis Based on Generative Artificial Intelligence Semantic Index, columnId=1149284495141983177, journalTitle=Journal of Technology Economics, columnName=Macro Technology Economics, runingTitle=null, highlight=null, articleAbstract=

In April 2025, the United States launched a new round of global tax restructuring, promoting a "reciprocal taxation" mechanism toward multiple trading partners, which quickly triggered countermeasures from China. The institutional reshaping of global tax rules has thus emerged as a novel external shock, intensifying international capital's arbitrage incentives and profit-seeking behavior in the short term and inducing cyclical mismatches and structural shifts in cross-border capital flows. Compared with traditional analytical frameworks based on interest rate differentials and exchange rate fluctuations, such institutional shocks are more likely to generate nonlinear responses through changes in policy expectations and amplified market sentiment, making their dynamic evolution difficult to capture using conventional methods. Against this background, the asymmetric adjustment mechanisms of China's short-term cross-border capital flows under global tax competition was examined. Using quarterly data from 2008 to 2024, a multiple-threshold regression model and introduce generative artificial intelligence was constructed to perform semantic modeling of policy texts, thereby developing a tax policy semantic intensity index (TPSI). The results show that global tax shocks significantly alter the response structure of capital flows to interest rate and exchange rate expectations, exhibiting clear regime shifts and asymmetric effects. The TPSI demonstrates strong leading properties in identifying the direction of capital sentiment and flow dynamics, effectively compensating for the lag of traditional variables in capturing policy expectation changes. Moreover, under high semantic intensity regimes, the marginal effectiveness of existing macroprudential tools weakens, increasing the risk of "high-frequency decoupling" in short-term capital flows. Accordingly, it proposes establishing a cross-border capital early-warning system based on semantic expectation identification, proactively enhancing capital flow governance, and actively participating in the reconstruction of global tax rules to strengthen China's institutional resilience and safeguard its tax sovereignty within the international financial system.

, authors=Haochen Guo1, Huihui Zhou2, Lun Gao3, Minfeng Lu4, authorsList=Haochen Guo, Huihui Zhou, Lun Gao, Minfeng Lu, authorCompany=null, correspAuthors=Lun Gao, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1321914958951068229, articleId=1321914958451946051, tenantId=1146029695717560320, journalId=1146120045056339983, language=CN, title=全球税收冲击下中国短期跨境资本流动的结构跃迁与政策响应机制——基于生成式人工智能语义指数的嵌入分析, columnId=1147991617132294261, journalTitle=技术经济, columnName=宏观技术经济, runingTitle=null, highlight=null, articleAbstract=

2025年4月,美国启动新一轮全球税收重构计划,推动对多国贸易伙伴实施“对等征税”机制,并迅速引发中国采取反制措施。全球税收规则的制度性重塑由此成为新型外部冲击源,在短期内强化国际资本的套利动机与趋利行为,诱发跨境资本流动的周期错配与结构跃迁。相较于传统基于利差与汇率波动的分析框架,此类制度性冲击更易通过政策预期变化与情绪放大效应触发非线性响应,传统方法难以刻画其动态演化过程。聚焦全球税收博弈背景下中国短期跨境资本流动的非对称调整机制,基于2008—2024年季度数据构建多门槛回归模型,并引入生成式人工智能对政策文本进行语义建模,构造税收政策语义强度指数(TPSI)。研究发现,全球税收冲击显著改变了资本对利差与汇率预期的响应结构,呈现区间跃迁与非对称特征;TPSI在识别资本情绪方向与流动趋势方面具有显著领先性;在高语义强度区间内,宏观审慎工具调节效应边际减弱,短期资本流动面临“高频脱锚”风险。基于此,建议建立以语义预期识别为基础的跨境资本预警机制,前瞻性提升资本流动治理能力,并积极参与全球税收规则重构进程,增强中国在国际金融体系中的制度韧性与税收主权保障能力。通过将生成式人工智能语义建模引入跨境资本非线性分析框架,拓展了制度性冲击下资本流动结构跃迁的识别方法,并为提升宏观审慎政策的前瞻性与精准性提供了新的实证依据。

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郭皓晨(1987—),博士,东南大学副教授,研究方向:金融工程与风险管理、金融理论与政策、金融安全与金融智能

周慧蕙(1998—),硕士,三江学院高级研究员,研究方向:普惠金融、数字经济

陆岷峰(1962—),博士,上海大学上海科技金融研究所教授,博士研究生导师,研究方向:宏观经济、商业银行。

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高伦(1995—),博士,南京大学应用经济学博士后,研究方向:金融工程与风险管理、金融理论与政策
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郭皓晨(1987—),博士,东南大学副教授,研究方向:金融工程与风险管理、金融理论与政策、金融安全与金融智能

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周慧蕙(1998—),硕士,三江学院高级研究员,研究方向:普惠金融、数字经济

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周慧蕙(1998—),硕士,三江学院高级研究员,研究方向:普惠金融、数字经济

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陆岷峰(1962—),博士,上海大学上海科技金融研究所教授,博士研究生导师,研究方向:宏观经济、商业银行。

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陆岷峰(1962—),博士,上海大学上海科技金融研究所教授,博士研究生导师,研究方向:宏观经济、商业银行。

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全球税收冲击下中国短期跨境资本流动的结构跃迁与政策响应机制——基于生成式人工智能语义指数的嵌入分析
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郭皓晨 1 , 周慧蕙 2 , 高伦 3 , 陆岷峰 4
技术经济 | 宏观技术经济 2026,45(1): 30-42
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技术经济 |宏观技术经济 2026 , 45 (1) : 30 -42
全球税收冲击下中国短期跨境资本流动的结构跃迁与政策响应机制——基于生成式人工智能语义指数的嵌入分析
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陆岷峰(1962—),博士,上海大学上海科技金融研究所教授,博士研究生导师,研究方向:宏观经济、商业银行。

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郭皓晨1, 周慧蕙2, 高伦3, 陆岷峰4
作者信息
  • 1.东南大学经济管理学院,南京 210096
  • 2.三江学院法商学院,南京 210012
  • 3.南京大学应用经济学博士后流动站,南京 210093
  • 4.上海大学上海科技金融研究所,上海 200444
通讯作者:
高伦(1995—),博士,南京大学应用经济学博士后,研究方向:金融工程与风险管理、金融理论与政策
作者简介:

郭皓晨(1987—),博士,东南大学副教授,研究方向:金融工程与风险管理、金融理论与政策、金融安全与金融智能

周慧蕙(1998—),硕士,三江学院高级研究员,研究方向:普惠金融、数字经济

陆岷峰(1962—),博士,上海大学上海科技金融研究所教授,博士研究生导师,研究方向:宏观经济、商业银行。

The Structural Transition and Policy Response Mechanism of China's Short-term Cross-border Capital Flows under the Impact of Global Taxation: Embedding Analysis Based on Generative Artificial Intelligence Semantic Index
Haochen Guo1, Huihui Zhou2, Lun Gao3, Minfeng Lu4
Affiliations
  • 1.School of Economics and Management, Southeast University, Nanjing 210096, China
  • 2.School of Business and Law, Sanjiang University, Nanjing 210012, China
  • 3.Postdoctoral Research Station of Applied Economics, Nanjing University, Nanjing 210093, China
  • 4.Shanghai Institute of Science and Technology Finance, Shanghai University, Shanghai 200444, China
出版时间: 2026-01-25 doi: 10.12404/j.issn.1002-980X.J25051006
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2025年4月,美国启动新一轮全球税收重构计划,推动对多国贸易伙伴实施“对等征税”机制,并迅速引发中国采取反制措施。全球税收规则的制度性重塑由此成为新型外部冲击源,在短期内强化国际资本的套利动机与趋利行为,诱发跨境资本流动的周期错配与结构跃迁。相较于传统基于利差与汇率波动的分析框架,此类制度性冲击更易通过政策预期变化与情绪放大效应触发非线性响应,传统方法难以刻画其动态演化过程。聚焦全球税收博弈背景下中国短期跨境资本流动的非对称调整机制,基于2008—2024年季度数据构建多门槛回归模型,并引入生成式人工智能对政策文本进行语义建模,构造税收政策语义强度指数(TPSI)。研究发现,全球税收冲击显著改变了资本对利差与汇率预期的响应结构,呈现区间跃迁与非对称特征;TPSI在识别资本情绪方向与流动趋势方面具有显著领先性;在高语义强度区间内,宏观审慎工具调节效应边际减弱,短期资本流动面临“高频脱锚”风险。基于此,建议建立以语义预期识别为基础的跨境资本预警机制,前瞻性提升资本流动治理能力,并积极参与全球税收规则重构进程,增强中国在国际金融体系中的制度韧性与税收主权保障能力。通过将生成式人工智能语义建模引入跨境资本非线性分析框架,拓展了制度性冲击下资本流动结构跃迁的识别方法,并为提升宏观审慎政策的前瞻性与精准性提供了新的实证依据。

全球税收博弈  /  短期资本流动  /  结构跃迁  /  生成式人工智能  /  宏观审慎政策

In April 2025, the United States launched a new round of global tax restructuring, promoting a "reciprocal taxation" mechanism toward multiple trading partners, which quickly triggered countermeasures from China. The institutional reshaping of global tax rules has thus emerged as a novel external shock, intensifying international capital's arbitrage incentives and profit-seeking behavior in the short term and inducing cyclical mismatches and structural shifts in cross-border capital flows. Compared with traditional analytical frameworks based on interest rate differentials and exchange rate fluctuations, such institutional shocks are more likely to generate nonlinear responses through changes in policy expectations and amplified market sentiment, making their dynamic evolution difficult to capture using conventional methods. Against this background, the asymmetric adjustment mechanisms of China's short-term cross-border capital flows under global tax competition was examined. Using quarterly data from 2008 to 2024, a multiple-threshold regression model and introduce generative artificial intelligence was constructed to perform semantic modeling of policy texts, thereby developing a tax policy semantic intensity index (TPSI). The results show that global tax shocks significantly alter the response structure of capital flows to interest rate and exchange rate expectations, exhibiting clear regime shifts and asymmetric effects. The TPSI demonstrates strong leading properties in identifying the direction of capital sentiment and flow dynamics, effectively compensating for the lag of traditional variables in capturing policy expectation changes. Moreover, under high semantic intensity regimes, the marginal effectiveness of existing macroprudential tools weakens, increasing the risk of "high-frequency decoupling" in short-term capital flows. Accordingly, it proposes establishing a cross-border capital early-warning system based on semantic expectation identification, proactively enhancing capital flow governance, and actively participating in the reconstruction of global tax rules to strengthen China's institutional resilience and safeguard its tax sovereignty within the international financial system.

global tax game  /  short-term capital flows  /  structural transition  /  generative artificial intelligence  /  macroprudential policy
郭皓晨, 周慧蕙, 高伦, 陆岷峰. 全球税收冲击下中国短期跨境资本流动的结构跃迁与政策响应机制——基于生成式人工智能语义指数的嵌入分析. 技术经济, 2026 , 45 (1) : 30 -42 . DOI: 10.12404/j.issn.1002-980X.J25051006
Haochen Guo, Huihui Zhou, Lun Gao, Minfeng Lu. The Structural Transition and Policy Response Mechanism of China's Short-term Cross-border Capital Flows under the Impact of Global Taxation: Embedding Analysis Based on Generative Artificial Intelligence Semantic Index[J]. Journal of Technology Economics, 2026 , 45 (1) : 30 -42 . DOI: 10.12404/j.issn.1002-980X.J25051006
  • 国家社会科学基金青年项目“基于生成式人工智能的金融安全风险测度及防控对策研究”(25CJY063)
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2026年第45卷第1期
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doi: 10.12404/j.issn.1002-980X.J25051006
  • 接收时间:2025-05-10
  • 首发时间:2026-10-27
  • 出版时间:2026-01-25
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  • 收稿日期:2025-05-10
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国家社会科学基金青年项目“基于生成式人工智能的金融安全风险测度及防控对策研究”(25CJY063)
作者信息
    1.东南大学经济管理学院,南京 210096
    2.三江学院法商学院,南京 210012
    3.南京大学应用经济学博士后流动站,南京 210093
    4.上海大学上海科技金融研究所,上海 200444

通讯作者:

高伦(1995—),博士,南京大学应用经济学博士后,研究方向:金融工程与风险管理、金融理论与政策
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2种不同金属材料的力学参数
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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