Pub Date : 2025-11-20DOI: 10.1016/j.jempfin.2025.101670
Zhenshan Chen , Zhibing Li , Jie Liu , Xiaoyu Liu
We find that investor attention significantly increases stock price crash risk. To identify the causal effect, we employ daily repeated quasi-natural experiments where the difference of investor attention is not driven by stock fundamentals, but rather exogenous price rounding issue. This positive effect is more pronounced among firms with higher daily abnormal Baidu search index and higher abnormal small fund inflows ratio, but is mitigated for firms with more sophisticated investors, state-owned enterprise, and firms with relaxation of short-sale constraints. Additionally, we provide supporting evidence that information asymmetry triggered by noise attention serves as a channel through which investor attention amplifies stock price crash risk. Finally, we provide additional evidence illustrating the generalizability of our findings.
{"title":"Information salience, investor attention, and stock price crash risk","authors":"Zhenshan Chen , Zhibing Li , Jie Liu , Xiaoyu Liu","doi":"10.1016/j.jempfin.2025.101670","DOIUrl":"10.1016/j.jempfin.2025.101670","url":null,"abstract":"<div><div>We find that investor attention significantly increases stock price crash risk. To identify the causal effect, we employ daily repeated quasi-natural experiments where the difference of investor attention is not driven by stock fundamentals, but rather exogenous price rounding issue. This positive effect is more pronounced among firms with higher daily abnormal Baidu search index and higher abnormal small fund inflows ratio, but is mitigated for firms with more sophisticated investors, state-owned enterprise, and firms with relaxation of short-sale constraints. Additionally, we provide supporting evidence that information asymmetry triggered by noise attention serves as a channel through which investor attention amplifies stock price crash risk. Finally, we provide additional evidence illustrating the generalizability of our findings.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"85 ","pages":"Article 101670"},"PeriodicalIF":2.4,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145787455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-20DOI: 10.1016/j.jempfin.2025.101669
Chae-Deug Yi
This study investigates the dynamic structure of intraday volatility and jump behavior in the Chinese yuan and US dollar exchange market by employing a Gumbel-distribution-based threshold derived from extreme value theory. Using five-minute high-frequency data over 2,450 trading days, we construct a daily jump probability index and examine its responsiveness to major economic shocks, including the U.S.–China trade war and the COVID-19 pandemic. Regression and simulation analyses (5,000 replications) show that the Gumbel-based jump metric provides superior explanatory power in detecting large and irregular jumps. The Gumbel distribution offers a clear and theoretically grounded thresholding mechanism, making it particularly effective in identifying episodic volatility clusters during the 2010s. Tests by Lee and Hannig (2010) and Laurent and Shi (2020) also suggest that the Gumbel jump statistic is more appropriate for capturing the frequent and discontinuous jumps in foreign exchange volatility. Furthermore, after filtering for intraday periodicity, the estimated jump probabilities significantly decline, indicating the importance of periodicity adjustment. This study also confirms that jump probabilities were notably higher during the U.S.–China trade war and the COVID-19 pandemic than in the overall sample period. Sensitivity tests on volatility filtering and simulation parameters further demonstrate the robustness of the Gumbel-based jump distribution.
{"title":"Volatility and jumps in the Chinese Yuan using Gumbel distribution during the trade war and COVID-19 pandemic","authors":"Chae-Deug Yi","doi":"10.1016/j.jempfin.2025.101669","DOIUrl":"10.1016/j.jempfin.2025.101669","url":null,"abstract":"<div><div>This study investigates the dynamic structure of intraday volatility and jump behavior in the Chinese yuan and US dollar exchange market by employing a Gumbel-distribution-based threshold derived from extreme value theory. Using five-minute high-frequency data over 2,450 trading days, we construct a daily jump probability index and examine its responsiveness to major economic shocks, including the U.S.–China trade war and the COVID-19 pandemic. Regression and simulation analyses (5,000 replications) show that the Gumbel-based jump metric provides superior explanatory power in detecting large and irregular jumps. The Gumbel distribution offers a clear and theoretically grounded thresholding mechanism, making it particularly effective in identifying episodic volatility clusters during the 2010s. Tests by Lee and Hannig (2010) and Laurent and Shi (2020) also suggest that the Gumbel jump statistic is more appropriate for capturing the frequent and discontinuous jumps in foreign exchange volatility. Furthermore, after filtering for intraday periodicity, the estimated jump probabilities significantly decline, indicating the importance of periodicity adjustment. This study also confirms that jump probabilities were notably higher during the U.S.–China trade war and the COVID-19 pandemic than in the overall sample period. Sensitivity tests on volatility filtering and simulation parameters further demonstrate the robustness of the Gumbel-based jump distribution.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"85 ","pages":"Article 101669"},"PeriodicalIF":2.4,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.jempfin.2025.101667
Pierluca Pannella
This paper documents that the dividend payout ratios of larger US banks rise when interest rates increase. To account for this pattern, I develop a model of optimal investment and deposit issuance under a risk-based constraint. Smaller banks primarily generate profits from the Fed funds-deposit spread, which typically widens with higher rates. Larger banks, by contrast, hold a greater share of risky assets and keep government bonds mainly as precautionary buffers. In high-interest-rate environments, these larger banks see only a modest increase in profitability. Consequently, they have weaker incentives to expand their investments and instead opt to reduce their buffer of safe assets to distribute higher dividends. Empirical evidence on payout behavior and leverage across banks that gain different shares of income from government bonds aligns with the prediction of the model. The findings highlight the importance of monitoring banks’ payout and leverage during periods of rising interest rates.
{"title":"Bank dividends, interest expenses, and leverage","authors":"Pierluca Pannella","doi":"10.1016/j.jempfin.2025.101667","DOIUrl":"10.1016/j.jempfin.2025.101667","url":null,"abstract":"<div><div>This paper documents that the dividend payout ratios of larger US banks rise when interest rates increase. To account for this pattern, I develop a model of optimal investment and deposit issuance under a risk-based constraint. Smaller banks primarily generate profits from the Fed funds-deposit spread, which typically widens with higher rates. Larger banks, by contrast, hold a greater share of risky assets and keep government bonds mainly as precautionary buffers. In high-interest-rate environments, these larger banks see only a modest increase in profitability. Consequently, they have weaker incentives to expand their investments and instead opt to reduce their buffer of safe assets to distribute higher dividends. Empirical evidence on payout behavior and leverage across banks that gain different shares of income from government bonds aligns with the prediction of the model. The findings highlight the importance of monitoring banks’ payout and leverage during periods of rising interest rates.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101667"},"PeriodicalIF":2.4,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145516363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-16DOI: 10.1016/j.jempfin.2025.101666
Jiaxing Tian , Hong Xiang , Minghai Xu
We show that the insider trading pattern on anomaly long-short portfolio stocks can forecast anomaly returns. Specifically, we use the fraction of anomaly long-leg (short-leg) stocks being bought (sold) by insiders as a signal to extract insiders’ information on expected returns of the anomaly. Based on a composite anomaly measure that combines 11 prominent anomalies, we show that the insider trading signal significantly forecasts anomaly returns both in-sample and out-of-sample. These findings also help disentangle the risk-based and the mispricing-based explanations for anomaly returns.
{"title":"Insider trading and anomalies","authors":"Jiaxing Tian , Hong Xiang , Minghai Xu","doi":"10.1016/j.jempfin.2025.101666","DOIUrl":"10.1016/j.jempfin.2025.101666","url":null,"abstract":"<div><div>We show that the insider trading pattern on anomaly long-short portfolio stocks can forecast anomaly returns. Specifically, we use the fraction of anomaly long-leg (short-leg) stocks being bought (sold) by insiders as a signal to extract insiders’ information on expected returns of the anomaly. Based on a composite anomaly measure that combines 11 prominent anomalies, we show that the insider trading signal significantly forecasts anomaly returns both in-sample and out-of-sample. These findings also help disentangle the risk-based and the mispricing-based explanations for anomaly returns.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101666"},"PeriodicalIF":2.4,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-10DOI: 10.1016/j.jempfin.2025.101664
Yuqi Gu , Mahsa Kaviani , Lily Li , Hosein Maleki , Connie X. Mao
We examine the impact of Sinclair Broadcast Group, the largest conservative media network in the US local TV markets, on corporate innovation following its staggered expansion across the country. We find a significant reduction in innovation output two to three years after Sinclair entry. As a larger proportion of inventors self-identify as left-leaning, we find that the effect runs through two mutually non-exclusive channels: the inventor productivity channel and the talent replacement channel. Inventors become less innovative when they stay in Sinclair-exposed firms, and firms face challenges replacing departed talent upon the local ideology shock induced by Sinclair.
{"title":"Media, inventors, and corporate innovation","authors":"Yuqi Gu , Mahsa Kaviani , Lily Li , Hosein Maleki , Connie X. Mao","doi":"10.1016/j.jempfin.2025.101664","DOIUrl":"10.1016/j.jempfin.2025.101664","url":null,"abstract":"<div><div>We examine the impact of Sinclair Broadcast Group, the largest conservative media network in the US local TV markets, on corporate innovation following its staggered expansion across the country. We find a significant reduction in innovation output two to three years after Sinclair entry. As a larger proportion of inventors self-identify as left-leaning, we find that the effect runs through two mutually non-exclusive channels: the inventor productivity channel and the talent replacement channel. Inventors become less innovative when they stay in Sinclair-exposed firms, and firms face challenges replacing departed talent upon the local ideology shock induced by Sinclair.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101664"},"PeriodicalIF":2.4,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-10DOI: 10.1016/j.jempfin.2025.101663
Mengmeng Dong
I provide novel evidence supporting the robust predictability of the “signal zoo” by clustering and aggregating 84 signals based on economic similarity. Economic clusters not only exhibit high (low) within-cluster (between-cluster) signal correlations — comparable to -means clusters — but also produce composites that non-redundantly explain the cross-section of U.S. stock returns. All composites exhibit robust predictability in the U.S. and certain evidence in the global regions. Subsample and long-run return tests suggest that predictability primarily arises from risk, except for momentum, which is driven by mispricing. Composites generally outperform an average-signal strategy due to their superior ability to identify less noisy stocks.
{"title":"Economic aggregation of return signals in global markets","authors":"Mengmeng Dong","doi":"10.1016/j.jempfin.2025.101663","DOIUrl":"10.1016/j.jempfin.2025.101663","url":null,"abstract":"<div><div>I provide novel evidence supporting the robust predictability of the “signal zoo” by clustering and aggregating 84 signals based on economic similarity. Economic clusters not only exhibit high (low) within-cluster (between-cluster) signal correlations — comparable to <span><math><mi>k</mi></math></span>-means clusters — but also produce composites that non-redundantly explain the cross-section of U.S. stock returns. All composites exhibit robust predictability in the U.S. and certain evidence in the global regions. Subsample and long-run return tests suggest that predictability primarily arises from risk, except for momentum, which is driven by mispricing. Composites generally outperform an average-signal strategy due to their superior ability to identify less noisy stocks.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101663"},"PeriodicalIF":2.4,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-05DOI: 10.1016/j.jempfin.2025.101665
Yunqi Zhang , Yu Meng , Xiaoyu Zhang
Bankruptcy abuse prevention has been criticized for increasing foreclosure rates, imposing negative impacts on housing markets, and aggravating the financial crisis. By contrast, this paper documents that bankruptcy abuse prevention reduces household debt overhang, a phenomenon harmful to home values and housing markets. Using a difference-in-differences analysis, we find that households in recourse states increased their home improvement and maintenance expenditures after the Bankruptcy Abuse Prevention and Consumer Protection Act, a period during which the households paid considerable attention to the downside risk of the housing market, and that the effects vary by home equity level. The results remain unchanged with alternative specifications and cannot be explained by credit changes, judicial and nonjudicial foreclosures, homestead exemption, house sales, or heterogeneous expectations. Last but not least, we use entropy balancing to eliminate the differences between the treatment and control groups and get similar results.
{"title":"Household debt overhang and bankruptcy abuse prevention","authors":"Yunqi Zhang , Yu Meng , Xiaoyu Zhang","doi":"10.1016/j.jempfin.2025.101665","DOIUrl":"10.1016/j.jempfin.2025.101665","url":null,"abstract":"<div><div>Bankruptcy abuse prevention has been criticized for <em>increasing</em> foreclosure rates, imposing negative impacts on housing markets, and aggravating the financial crisis. By contrast, this paper documents that bankruptcy abuse prevention <em>reduces</em> household debt overhang, a phenomenon harmful to home values and housing markets. Using a difference-in-differences analysis, we find that households in recourse states increased their home improvement and maintenance expenditures after the Bankruptcy Abuse Prevention and Consumer Protection Act, a period during which the households paid considerable attention to the downside risk of the housing market, and that the effects vary by home equity level. The results remain unchanged with alternative specifications and cannot be explained by credit changes, judicial and nonjudicial foreclosures, homestead exemption, house sales, or heterogeneous expectations. Last but not least, we use entropy balancing to eliminate the differences between the treatment and control groups and get similar results.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101665"},"PeriodicalIF":2.4,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-17DOI: 10.1016/j.jempfin.2025.101652
Wei Hou, Esad Smajlbegovic, Daniel Urban
Researchers need to decide on which academic conferences to attend. To inform this decision, we track the publication status of 6805 research articles presented at 87 finance conferences between 2011 and 2015. We rank these conferences based on publication rates in top finance and economics journals. To complement these rankings, we also examine publication rates within specific research fields and citation scores. The rankings show considerable heterogeneity in conference quality and uncover three major conference clusters. We further examine the role and timing of conferences in the publication process, analyze important time trends, explore the relationship between conference size and publication success, and highlight the relatively low overlap in accepted papers across conferences.
{"title":"Ranking finance conferences: An update","authors":"Wei Hou, Esad Smajlbegovic, Daniel Urban","doi":"10.1016/j.jempfin.2025.101652","DOIUrl":"10.1016/j.jempfin.2025.101652","url":null,"abstract":"<div><div>Researchers need to decide on which academic conferences to attend. To inform this decision, we track the publication status of 6805 research articles presented at 87 finance conferences between 2011 and 2015. We rank these conferences based on publication rates in top finance and economics journals. To complement these rankings, we also examine publication rates within specific research fields and citation scores. The rankings show considerable heterogeneity in conference quality and uncover three major conference clusters. We further examine the role and timing of conferences in the publication process, analyze important time trends, explore the relationship between conference size and publication success, and highlight the relatively low overlap in accepted papers across conferences.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101652"},"PeriodicalIF":2.4,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145155649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-17DOI: 10.1016/j.jempfin.2025.101653
Soroush Ghazi , Mark Schneider , Jack Strauss
We present a representative agent model with probability weighting that predicts expected momentum returns decrease in market volatility and pessimism, and predicts the opposite for the equity premium. Hence, the model predicts that the expected market and momentum returns move in opposite directions and can be used to form a dynamic hedging strategy that conditions on market volatility and market pessimism. Our asset pricing model motivates an index of volatility-amplified pessimism (VAP) that predicts both momentum and market returns as well as a real-time trading strategy that uses the index to switch between the market and momentum portfolios. In high VAP states, the market generates high returns and Sharpe ratios, while momentum generates high returns and Sharpe ratios in low VAP states. Although most momentum strategies have recently disappeared we find that momentum is still there, conditional on the interaction between market pessimism and market volatility.
{"title":"Momentum is still there conditional on volatility-amplified pessimism","authors":"Soroush Ghazi , Mark Schneider , Jack Strauss","doi":"10.1016/j.jempfin.2025.101653","DOIUrl":"10.1016/j.jempfin.2025.101653","url":null,"abstract":"<div><div>We present a representative agent model with probability weighting that predicts expected momentum returns decrease in market volatility and pessimism, and predicts the opposite for the equity premium. Hence, the model predicts that the expected market and momentum returns move in opposite directions and can be used to form a dynamic hedging strategy that conditions on market volatility and market pessimism. Our asset pricing model motivates an index of volatility-amplified pessimism (VAP) that predicts both momentum and market returns as well as a real-time trading strategy that uses the index to switch between the market and momentum portfolios. In high VAP states, the market generates high returns and Sharpe ratios, while momentum generates high returns and Sharpe ratios in low VAP states. Although most momentum strategies have recently disappeared we find that momentum is still there, conditional on the interaction between market pessimism and market volatility.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101653"},"PeriodicalIF":2.4,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-16DOI: 10.1016/j.jempfin.2025.101654
Han Zhang , Xiong Xiong , Bin Guo
We provide empirical evidence that the average treasury bond yield across one- to ten-year maturities can negatively predict stock returns in the Chinese stock market. The substantial predictive power of bond yield underscores that the flight-to-safety effect associated with treasury bonds plays a predominant role in driving this predictive relationship. However, we find that bond yield does not operate as a systematic risk factor that explains cross-sectional variations in average stock returns, suggesting that it does not qualify as a state variable within the intertemporal capital asset pricing model framework proposed by Merton (1973). Using an affine market price of risk model, we demonstrate that the average bond yield serves as a pivotal determinant of the time-varying pattern of market prices for the market excess return factor, thereby establishing the theoretical foundation for its predictive power regarding stock returns.
{"title":"The stock return predictability of treasury bond yield in China","authors":"Han Zhang , Xiong Xiong , Bin Guo","doi":"10.1016/j.jempfin.2025.101654","DOIUrl":"10.1016/j.jempfin.2025.101654","url":null,"abstract":"<div><div>We provide empirical evidence that the average treasury bond yield across one- to ten-year maturities can negatively predict stock returns in the Chinese stock market. The substantial predictive power of bond yield underscores that the flight-to-safety effect associated with treasury bonds plays a predominant role in driving this predictive relationship. However, we find that bond yield does not operate as a systematic risk factor that explains cross-sectional variations in average stock returns, suggesting that it does not qualify as a state variable within the intertemporal capital asset pricing model framework proposed by Merton (1973). Using an affine market price of risk model, we demonstrate that the average bond yield serves as a pivotal determinant of the time-varying pattern of market prices for the market excess return factor, thereby establishing the theoretical foundation for its predictive power regarding stock returns.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101654"},"PeriodicalIF":2.4,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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