洪永淼，中國科學院數學與系統科學研究院冠名首席研究員、中國科學院大學經濟與管理學院院長、發展中國家科學院院士、計量經濟學會會士，并擔任中國教育部高等學校經濟學類專業教學指導委員會副主任委員。曾任康奈爾大學ErnestS.Liu經濟學與國際研究講席教授，北美華人經濟學家學會會長。研究領域涵蓋計量經濟學理論、時間序列計量經濟學、金融計量經濟學及統計學。其學術成果發表于Annals of Statistics、Biometrika、Econometric Theory、Econometrica、 International Economic Review、Journal of American Statistical Association、Journal of Businessand Economic Statistics、 Journal of Econometrics、Journal of Political Economy、Journal of Royal Statistical Society (Series B)等國際知名經濟、金融與統計期刊。其最新英文專著《現代計量經濟學基礎:統一框架》廣受學界關注。2014至2024年，連續11年入選愛思唯爾“中國高被引學者(經濟學/統計學)”榜單，并于2022年榮獲國家級教學成果獎(高等教育本科)一等獎。
報告摘要：
We introduce a novel consistent test for detecting structural changes in high-dimensional factor models, leveraging a discrete Fourier transform (DFT) approach. In scenarios where structural changes take place, the ability of conventional principal component analysis to accurately estimate common factors and factor loadings is compromised, leading to estimated residuals that embed signals of these changes. Therefore, we are equipped to assess the DFTs of estimated residuals against the null zero spectrum, which assumes no structural changes. The proposed test is consistent against a wide range of both smooth structural changes and abrupt structural breaks with a possibly unknown number of breaks and unknown break dates in time-varying factor loadings. Moreover, the test has an asymptotic N(0, 1) distribution under the null hypothesis, leading to a simple and convenient inference procedure.
Monte Carlo simulations confirm the test's reliability in terms of size and its exceptional power against a variety of structural changes in factor loadings. When applied to China's macroeconomic data, the proposed test reveals substantial and consistent time-varying factor loadings in the periods following a series of significant historical events, providing insights that may have been missed in prior analyses.
