Pub Date : 2020-09-01DOI: 10.5089/9781513556857.001.A001
D. Baksa, Aleš Bulíř, Dyna Heng
The paper describes a semistructural macrofiscal approach to simulating and forecasting macroeconomic policies. Our canonical model is adapted to Cambodia and we demonstrate its application with an illustrative scenario of macroeconomic effects of the Covid-19 pandemic. Complemented with near-term forecasting tools and expert judgment, the dynamics of the model helps to inform policymakers about medium-term transmission channels and thus guide policy advice.
{"title":"A Simple Macrofiscal Model for Policy Analysis: An Application to Cambodia","authors":"D. Baksa, Aleš Bulíř, Dyna Heng","doi":"10.5089/9781513556857.001.A001","DOIUrl":"https://doi.org/10.5089/9781513556857.001.A001","url":null,"abstract":"The paper describes a semistructural macrofiscal approach to simulating and forecasting macroeconomic policies. Our canonical model is adapted to Cambodia and we demonstrate its application with an illustrative scenario of macroeconomic effects of the Covid-19 pandemic. Complemented with near-term forecasting tools and expert judgment, the dynamics of the model helps to inform policymakers about medium-term transmission channels and thus guide policy advice.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134421385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We examine whether investors react to a significant change in balance sheets absent a significant change in underlying economics. Beginning in 2019, ASC 842 requires the recognition of operating leases, which were previously only disclosed in the footnotes. This change in accounting standard has no effect on firms' economics but results in firms with significant operating leases recognizing a considerable increase in debt. We find that firms with significant operating leases, on average, earn negative returns around the initial recognition of their operating leases. For example, firms in the top decile of operating lease intensity experience a mean abnormal return of -3.10% around their first quarter 2019 earnings announcements. Our results provide timely, new evidence consistent with equity market prices failing to reflect an adequate level of fundamental analysis.
{"title":"Did the Recognition of Operating Leases Cause a Decline in Equity Valuations?","authors":"Jonathan A. Milian, E. Lee","doi":"10.2139/ssrn.3509373","DOIUrl":"https://doi.org/10.2139/ssrn.3509373","url":null,"abstract":"We examine whether investors react to a significant change in balance sheets absent a significant change in underlying economics. Beginning in 2019, ASC 842 requires the recognition of operating leases, which were previously only disclosed in the footnotes. This change in accounting standard has no effect on firms' economics but results in firms with significant operating leases recognizing a considerable increase in debt. We find that firms with significant operating leases, on average, earn negative returns around the initial recognition of their operating leases. For example, firms in the top decile of operating lease intensity experience a mean abnormal return of -3.10% around their first quarter 2019 earnings announcements. Our results provide timely, new evidence consistent with equity market prices failing to reflect an adequate level of fundamental analysis.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116900829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yangyang Chen, W. Saffar, Chenyu Shan, Sarah Qian Wang
Credit default swaps (CDSs) are an effective tool to trade credit risk, and they can improve the corporate information environment. We find that firms use more public debt and less bank debt when CDSs reference their debt start trading. The results are robust to the endogeneity of CDS trading. Furthermore, the increase in public debt is concentrated in senior bonds and notes, which are the most common CDS reference assets. The effect of CDS trading is most pronounced when bond underwriters take a net selling CDS position and for informationally opaque firms. These findings suggest that the hedging and informational roles of CDSs have real effects on corporate debt structure.
{"title":"Credit Default Swaps and Corporate Debt Structure","authors":"Yangyang Chen, W. Saffar, Chenyu Shan, Sarah Qian Wang","doi":"10.2139/ssrn.3170485","DOIUrl":"https://doi.org/10.2139/ssrn.3170485","url":null,"abstract":"Credit default swaps (CDSs) are an effective tool to trade credit risk, and they can improve the corporate information environment. We find that firms use more public debt and less bank debt when CDSs reference their debt start trading. The results are robust to the endogeneity of CDS trading. Furthermore, the increase in public debt is concentrated in senior bonds and notes, which are the most common CDS reference assets. The effect of CDS trading is most pronounced when bond underwriters take a net selling CDS position and for informationally opaque firms. These findings suggest that the hedging and informational roles of CDSs have real effects on corporate debt structure.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"36 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123352122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
During the past two decades, the Cboe Volatility Index (VIX® Index), a key measure of investor sentiment and 30-day future volatility expectations, has generated much investor attention because of its unique and powerful features. The introduction of VIX futures in 2004, VIX options in 2006, and other volatility-related trading instruments provided traders and investors access to exchange-traded vehicles for taking long and short exposures to expected S&P 500 Index volatility for a particular time frame. Certain VIX-related tradable products may provide benefits when used as tools for tail-risk hedging, diversification, risk management, or alpha generation. Gauges of expected stock market volatility for various regions include the VIX Index (United States), AXVI Index (Australia), VHSI Index (Hong Kong), NVIX Index (India) and VSTOXX Index (Europe). All five of these volatility indexes had negative correlations with their related stock indexes price movements, and all five volatility indexes rose more than 50% in 2008. Although the five volatility indexes are not investable, investors can explore VIX-based benchmark indexes that show the performance of hypothetical investment strategies using VIX futures or options. Before investing in volatility-related products, investors should closely study the pricing, roll cost, and volatility features of the tradable products and read the applicable prospectuses and risk disclosure statements.
{"title":"The VIX Index and Volatility-Based Global Indexes and Trading Instruments - A Guide to Investment and Trading Features","authors":"M. Moran, Berlinda Liu","doi":"10.2139/ssrn.3668983","DOIUrl":"https://doi.org/10.2139/ssrn.3668983","url":null,"abstract":"During the past two decades, the Cboe Volatility Index (VIX® Index), a key measure of investor sentiment and 30-day future volatility expectations, has generated much investor attention because of its unique and powerful features. The introduction of VIX futures in 2004, VIX options in 2006, and other volatility-related trading instruments provided traders and investors access to exchange-traded vehicles for taking long and short exposures to expected S&P 500 Index volatility for a particular time frame. Certain VIX-related tradable products may provide benefits when used as tools for tail-risk hedging, diversification, risk management, or alpha generation. Gauges of expected stock market volatility for various regions include the VIX Index (United States), AXVI Index (Australia), VHSI Index (Hong Kong), NVIX Index (India) and VSTOXX Index (Europe). All five of these volatility indexes had negative correlations with their related stock indexes price movements, and all five volatility indexes rose more than 50% in 2008. Although the five volatility indexes are not investable, investors can explore VIX-based benchmark indexes that show the performance of hypothetical investment strategies using VIX futures or options. Before investing in volatility-related products, investors should closely study the pricing, roll cost, and volatility features of the tradable products and read the applicable prospectuses and risk disclosure statements.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114881301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper examines the role of corporate social performance in the CDS market, with a focus on the differential effect conditional on the lengths of time horizons. We find that strong social performance is negatively associated with the slope of CDS term structure, by reducing the long-term credit risk and increasing the short-term credit risk. After controlling for credit ratings in a “path analysis”, we find that the direct effect of social performance remains significant, suggesting that CDS market participants incorporate this information more efficiently than credit rating agencies. Furthermore, the effects of social performance are stronger for firms with speculative-grade ratings, smaller size, or less analyst coverage.
{"title":"Corporate Social Responsibility and the Term Structure of CDS Spreads","authors":"Feng Gao, Yubin Li, Xinjie Wang, Z. Zhong","doi":"10.2139/ssrn.3356165","DOIUrl":"https://doi.org/10.2139/ssrn.3356165","url":null,"abstract":"This paper examines the role of corporate social performance in the CDS market, with a focus on the differential effect conditional on the lengths of time horizons. We find that strong social performance is negatively associated with the slope of CDS term structure, by reducing the long-term credit risk and increasing the short-term credit risk. After controlling for credit ratings in a “path analysis”, we find that the direct effect of social performance remains significant, suggesting that CDS market participants incorporate this information more efficiently than credit rating agencies. Furthermore, the effects of social performance are stronger for firms with speculative-grade ratings, smaller size, or less analyst coverage.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129042685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper evidences the explanatory power of managers’ uncertainty for cross-sectional stock returns. I introduce a novel measure of the degree of managers’ uncertain beliefs about future states: manager uncertainty (MU), defined as the count of the word “uncertainty” over the sum of the count of the word “uncertainty” and the count of the word “risk” in filings and conference calls. I find that manager’s level of uncertainty reveals valuation information about real options and thereby has significantly negative explanatory power for cross-sectional stock returns. Beyond existing market-based uncertainty measures, the manager uncertainty measure has incremental pricing power by capturing information frictions between managers’ reported uncertainty and investors’ perception of uncertainty. Moreover, a short-long portfolio sorted by manager uncertainty has a significantly positive premium and cannot be spanned by existing factor models. An application on COVID-19 uncertainty shows consistent results.
{"title":"Manager Uncertainty and the Cross-Section of Stock Returns","authors":"Tengfei Zhang","doi":"10.2139/ssrn.3654376","DOIUrl":"https://doi.org/10.2139/ssrn.3654376","url":null,"abstract":"This paper evidences the explanatory power of managers’ uncertainty for cross-sectional stock returns. I introduce a novel measure of the degree of managers’ uncertain beliefs about future states: manager uncertainty (MU), defined as the count of the word “uncertainty” over the sum of the count of the word “uncertainty” and the count of the word “risk” in filings and conference calls. I find that manager’s level of uncertainty reveals valuation information about real options and thereby has significantly negative explanatory power for cross-sectional stock returns. Beyond existing market-based uncertainty measures, the manager uncertainty measure has incremental pricing power by capturing information frictions between managers’ reported uncertainty and investors’ perception of uncertainty. Moreover, a short-long portfolio sorted by manager uncertainty has a significantly positive premium and cannot be spanned by existing factor models. An application on COVID-19 uncertainty shows consistent results.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114142252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We create a culture dictionary using one of the latest machine learning techniques—the word embedding model—and 209,480 earnings call transcripts. We score the five corporate cultural values of innovation, integrity, quality, respect, and teamwork for 62,664 firm-year observations over the period 2001–2018. We show that an innovative culture is broader than the usual measures of corporate innovation – R&D expenses and the number of patents. Moreover, we show that corporate culture correlates with business outcomes, including operational efficiency, risk-taking, earnings management, executive compensation design, firm value, and deal making, and that the culture-performance link is more pronounced in bad times. Finally, we present suggestive evidence that corporate culture is shaped by major corporate events, such as mergers and acquisitions.
{"title":"Measuring Corporate Culture Using Machine Learning","authors":"Kai Li, Feng Mai, R. Shen, Xinyan Yan","doi":"10.2139/SSRN.3256608","DOIUrl":"https://doi.org/10.2139/SSRN.3256608","url":null,"abstract":"\u0000 We create a culture dictionary using one of the latest machine learning techniques—the word embedding model—and 209,480 earnings call transcripts. We score the five corporate cultural values of innovation, integrity, quality, respect, and teamwork for 62,664 firm-year observations over the period 2001–2018. We show that an innovative culture is broader than the usual measures of corporate innovation – R&D expenses and the number of patents. Moreover, we show that corporate culture correlates with business outcomes, including operational efficiency, risk-taking, earnings management, executive compensation design, firm value, and deal making, and that the culture-performance link is more pronounced in bad times. Finally, we present suggestive evidence that corporate culture is shaped by major corporate events, such as mergers and acquisitions.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122487497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The default rules of corporate law make shareholders’ control rights a function of their voting power. Whether a director is elected or a merger is approved depends on how shareholders vote. Yet, in private corporations, shareholders routinely alter their rights by contract. This phenomenon of shareholder agreements—contracts among the owners of a firm—has received far less attention than it deserves, mainly because detailed data about the actual contents of shareholder agreements has been lacking. Private companies disclose little, and shareholder agreements are thought to play a trivial or nonexistent role in public companies. I show that this is false—15% of corporations that go public in recent years do so subject to a shareholder agreement. With this dataset in hand, I show the dramatic extent to which these shareholders redefine their control rights by contract. Shareholders restrict the sale of shares and waive aspects of the duty of loyalty. Above all, however, shareholders use their agreements to bargain with each other over votes for directors, and to bargain with the corporation itself for other control rights, such as vetoes over major corporate actions. In essence, while statutory corporate law makes control rights a function of voting power, shareholder agreements make control rights a function of contract instead, separating voting and control. Studying this phenomenon raises new questions of doctrine, theory, and empirics that go to foundational issues in corporate law. Is it desirable to let shareholders redesign corporate control rights wholesale by contract? What should be the law that governs their contracts when they do so? I provide a novel account of shareholder agreements’ use in public firms, before offering preliminary views on their welfare effects, implications for corporate theory, and on their governing law, which remains strikingly underdeveloped.
{"title":"The Separation of Voting and Control: The Role of Contract in Corporate Governance","authors":"G. Rauterberg","doi":"10.2139/ssrn.3637204","DOIUrl":"https://doi.org/10.2139/ssrn.3637204","url":null,"abstract":"The default rules of corporate law make shareholders’ control rights a function of their voting power. Whether a director is elected or a merger is approved depends on how shareholders vote. Yet, in private corporations, shareholders routinely alter their rights by contract. This phenomenon of shareholder agreements—contracts among the owners of a firm—has received far less attention than it deserves, mainly because detailed data about the actual contents of shareholder agreements has been lacking. Private companies disclose little, and shareholder agreements are thought to play a trivial or nonexistent role in public companies. \u0000 \u0000I show that this is false—15% of corporations that go public in recent years do so subject to a shareholder agreement. With this dataset in hand, I show the dramatic extent to which these shareholders redefine their control rights by contract. Shareholders restrict the sale of shares and waive aspects of the duty of loyalty. Above all, however, shareholders use their agreements to bargain with each other over votes for directors, and to bargain with the corporation itself for other control rights, such as vetoes over major corporate actions. In essence, while statutory corporate law makes control rights a function of voting power, shareholder agreements make control rights a function of contract instead, separating voting and control. \u0000 \u0000Studying this phenomenon raises new questions of doctrine, theory, and empirics that go to foundational issues in corporate law. Is it desirable to let shareholders redesign corporate control rights wholesale by contract? What should be the law that governs their contracts when they do so? I provide a novel account of shareholder agreements’ use in public firms, before offering preliminary views on their welfare effects, implications for corporate theory, and on their governing law, which remains strikingly underdeveloped.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115067917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The geography of a firm’s assets is an important determinant of its investment decisions and productivity, which, in turn, drives stock returns. We construct a novel measure of the returns earned by private market investors in the metropolitan areas where each equity REIT owns properties. We then risk-adjust this geographically weighted proxy for each REIT’s property portfolio return (PPR) by regressing it against the sensitivity of the REIT’s returns to systematic risk factors. We find that this risk-adjusted property portfolio return (αPPR) predicts the cross-section of returns in the public REIT market, suggesting a slow diffusion of asset-level information into stock returns. Our findings also suggest it is the slow diffusion of information about “local” prices changes, not current rental income or local liquidity, that predicts REIT returns. Moreover, the αPPRs associated with REIT allocations to major “gateway” markets are more predictive of REIT returns than the property portfolio returns produced by allocations to secondary and tertiary markets. This study improves our understanding of the extent to which “local” information about the productivity of a firm’s assets is capitalized into stock prices and the speed at which it is capitalized. This study also contributes to the literature on the predictability of REIT returns and the relation between private and public CRE returns using firm-level, instead of index level, returns.
{"title":"Asset Productivity, Local information Diffusion, and Commercial Real Estate Returns","authors":"David C. Ling, Chongyu Wang, Tingyu Zhou","doi":"10.2139/ssrn.3628872","DOIUrl":"https://doi.org/10.2139/ssrn.3628872","url":null,"abstract":"The geography of a firm’s assets is an important determinant of its investment decisions and productivity, which, in turn, drives stock returns. We construct a novel measure of the returns earned by private market investors in the metropolitan areas where each equity REIT owns properties. We then risk-adjust this geographically weighted proxy for each REIT’s property portfolio return (PPR) by regressing it against the sensitivity of the REIT’s returns to systematic risk factors. We find that this risk-adjusted property portfolio return (αPPR) predicts the cross-section of returns in the public REIT market, suggesting a slow diffusion of asset-level information into stock returns. Our findings also suggest it is the slow diffusion of information about “local” prices changes, not current rental income or local liquidity, that predicts REIT returns. Moreover, the αPPRs associated with REIT allocations to major “gateway” markets are more predictive of REIT returns than the property portfolio returns produced by allocations to secondary and tertiary markets. This study improves our understanding of the extent to which “local” information about the productivity of a firm’s assets is capitalized into stock prices and the speed at which it is capitalized. This study also contributes to the literature on the predictability of REIT returns and the relation between private and public CRE returns using firm-level, instead of index level, returns.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127083309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Venture capital is associated with some of the most high-growth and influential firms in the world. Academics and practitioners have effectively articulated the strengths of the venture model. At the same time, venture capital financing also has real limitations in its ability to advance substantial technological change. Three issues are particularly concerning to us: 1) the very narrow band of technological innovations that fit the requirements of institutional venture capital investors; 2) the relatively small number of venture capital investors who hold and shape the direction of a substantial fraction of capital that is deployed into financing radical technological change; and 3) the relaxation in recent years of the intense emphasis on corporate governance by venture capital firms. While our ability to assess the social welfare impact of venture capital remains nascent, we hope that this article will stimulate discussion of and research into these questions.
{"title":"Venture Capital's Role in Financing Innovation: What We Know and How Much We Still Need to Learn","authors":"Josh Lerner, Ramana Nanda","doi":"10.2139/ssrn.3633054","DOIUrl":"https://doi.org/10.2139/ssrn.3633054","url":null,"abstract":"Venture capital is associated with some of the most high-growth and influential firms in the world. Academics and practitioners have effectively articulated the strengths of the venture model. At the same time, venture capital financing also has real limitations in its ability to advance substantial technological change. Three issues are particularly concerning to us: 1) the very narrow band of technological innovations that fit the requirements of institutional venture capital investors; 2) the relatively small number of venture capital investors who hold and shape the direction of a substantial fraction of capital that is deployed into financing radical technological change; and 3) the relaxation in recent years of the intense emphasis on corporate governance by venture capital firms. While our ability to assess the social welfare impact of venture capital remains nascent, we hope that this article will stimulate discussion of and research into these questions.","PeriodicalId":375725,"journal":{"name":"SPGMI: Capital IQ Data (Topic)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114513272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：