We use textual analysis of high-dimensional data from patent documents to create new indicators of technological innovation. We identify significant patents based on textual similarity of a given patent to previous and subsequent work: these patents are distinct from previous work but are related to subsequent innovations. Our measure of patent significance is predictive of future citations and correlates strongly with measures of market value. We identify breakthrough innovations as the most significant patents – those in the right tail of our measure – to construct indices of technological change at the aggregate, sectoral, and firm level. Our technology indices span two centuries (1840-2010) and cover innovation by private and public firms, as well as non-profit organizations and the US government. These indices capture the evolution of technological waves over a long time span and are strong predictors of productivity at the aggregate and sectoral level.
{"title":"Measuring Technological Innovation Over the Long Run","authors":"B. Kelly, D. Papanikolaou, Amit Seru, Matt Taddy","doi":"10.2139/ssrn.3279254","DOIUrl":"https://doi.org/10.2139/ssrn.3279254","url":null,"abstract":"We use textual analysis of high-dimensional data from patent documents to create new indicators of technological innovation. We identify significant patents based on textual similarity of a given patent to previous and subsequent work: these patents are distinct from previous work but are related to subsequent innovations. Our measure of patent significance is predictive of future citations and correlates strongly with measures of market value. We identify breakthrough innovations as the most significant patents – those in the right tail of our measure – to construct indices of technological change at the aggregate, sectoral, and firm level. Our technology indices span two centuries (1840-2010) and cover innovation by private and public firms, as well as non-profit organizations and the US government. These indices capture the evolution of technological waves over a long time span and are strong predictors of productivity at the aggregate and sectoral level.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130518876","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}
Gabriel Ehrlich, J. Haltiwanger, Ron S. Jarmin, David Johnson, M. Shapiro
Key macro indicators such as output, productivity, and inflation are based on a complex system across multiple statistical agencies using different samples and levels of aggregation. The Census Bureau collects nominal sales, the Bureau of Labor Statistics collects prices, and the Bureau of Economic Analysis constructs nominal and real GDP using these data and other sources. The price and quantity data are integrated at a high level of aggregation. This paper explores alternative methods for reengineering key national output and price indices using item-level data. Such reengineering offers the promise of greatly improved key economic indicators along many dimensions.
{"title":"Minding Your Ps and Qs: Going from Micro to Macro in Measuring Prices and Quantities","authors":"Gabriel Ehrlich, J. Haltiwanger, Ron S. Jarmin, David Johnson, M. Shapiro","doi":"10.2139/ssrn.3318626","DOIUrl":"https://doi.org/10.2139/ssrn.3318626","url":null,"abstract":"Key macro indicators such as output, productivity, and inflation are based on a complex system across multiple statistical agencies using different samples and levels of aggregation. The Census Bureau collects nominal sales, the Bureau of Labor Statistics collects prices, and the Bureau of Economic Analysis constructs nominal and real GDP using these data and other sources. The price and quantity data are integrated at a high level of aggregation. This paper explores alternative methods for reengineering key national output and price indices using item-level data. Such reengineering offers the promise of greatly improved key economic indicators along many dimensions.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"186 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124931066","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}
How much do consumption patterns matter for the impact of international trade on inequality? In neoclassical trade models, the effects of trade shocks on consumers' purchasing power are governed by the shares of imports in consumer expenditures, under no parametric assumptions on preferences and technology. This paper provides in-depth measurement of import shares across the income distribution in the United States, using new datasets linking expenditure and customs microdata. Contrary to common wisdom, we find that import shares are flat throughout the income distribution: the purchasing-power gains from lower trade costs are distributionally neutral. Accounting for changes in wages in addition to prices in a unified nonparametric framework, we find substantial distributional effects that arise within, but not across, income and education groups. There is little impact of a fall in trade costs on inequality, even though trade shocks generate winners and losers at all income levels, via wage changes. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
{"title":"The Distributional Effects of Trade: Theory and Evidence from the United States","authors":"K. Borusyak, Xavier Jaravel","doi":"10.3386/W28957","DOIUrl":"https://doi.org/10.3386/W28957","url":null,"abstract":"How much do consumption patterns matter for the impact of international trade on inequality? In neoclassical trade models, the effects of trade shocks on consumers' purchasing power are governed by the shares of imports in consumer expenditures, under no parametric assumptions on preferences and technology. This paper provides in-depth measurement of import shares across the income distribution in the United States, using new datasets linking expenditure and customs microdata. Contrary to common wisdom, we find that import shares are flat throughout the income distribution: the purchasing-power gains from lower trade costs are distributionally neutral. Accounting for changes in wages in addition to prices in a unified nonparametric framework, we find substantial distributional effects that arise within, but not across, income and education groups. There is little impact of a fall in trade costs on inequality, even though trade shocks generate winners and losers at all income levels, via wage changes. \u0000 \u0000Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122524031","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 article provides a brief introduction to the physical science of climate change, aimed towards economists. We begin by describing the physics that controls global climate, how scientists measure and model the climate system, and the magnitude of human-caused emissions of carbon dioxide. We then summarize many of the climatic changes of interest to economists that have been documented and that are projected in the future. We conclude by highlighting some key areas in which economists are in a unique position to help climate science advance. An important message from this final section, which we believe is deeply underappreciated among economists, is that all climate change forecasts rely heavily and directly on economic forecasts for the world. On timescales of a half-century or longer, the largest source of uncertainty in climate science is not physics, but economics.
{"title":"An Economist's Guide to Climate Change Science","authors":"S. Hsiang, R. Kopp","doi":"10.1257/JEP.32.4.3","DOIUrl":"https://doi.org/10.1257/JEP.32.4.3","url":null,"abstract":"This article provides a brief introduction to the physical science of climate change, aimed towards economists. We begin by describing the physics that controls global climate, how scientists measure and model the climate system, and the magnitude of human-caused emissions of carbon dioxide. We then summarize many of the climatic changes of interest to economists that have been documented and that are projected in the future. We conclude by highlighting some key areas in which economists are in a unique position to help climate science advance. An important message from this final section, which we believe is deeply underappreciated among economists, is that all climate change forecasts rely heavily and directly on economic forecasts for the world. On timescales of a half-century or longer, the largest source of uncertainty in climate science is not physics, but economics.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126380362","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}
Pub Date : 2018-09-09DOI: 10.1108/S0277-283320190000033003
M. Kenney, J. Zysman
Abstract The emergence of the platform economy is reorganizing work, employment, and value creation. The authors argue that the digital platforms are fracturing work itself as the places and types of work are being reorganized into a myriad of platform organized work arrangements with workplaces being potentially anywhere with Internet connectivity. The authors differ from most traditional narratives that focus solely upon either work displacement, a single type of platform-organized value-creating activity, or David Weil’s concentration solely upon the workplace. The authors recognize that even as some work is replaced, other work is being transformed; new work and old work in new arrangements is being created and recreated. The taxonomy begins with the workers employed directly by the platform and its contractors. The authors then introduce the category, platform-mediated work, which we divide into three groups: marketplaces such as Amazon; in-person service provision such as Uber and Airbnb; and remote service provision such as Upwork. The next category, “platform-mediated content creation,” is complex. The authors identify three groups of activities: consignment content creators that include services such as the app stores, YouTube, and Amazon Self-Publishing; non-platform organization content producers, which refers to the enormous number of workers occupied with creating and maintaining websites; and user-generated content which is the non-compensated value creation that ranges from content uploaded to Facebook, Instagram, etc. to reviews on sites such as Yelp. It is only when work and value creation is considered in all of these platform-based manifestations that we can understand the ultimate dimensions of the platform economy and comprehensively understand its implications for work.
{"title":"Work and Value Creation in the Platform Economy","authors":"M. Kenney, J. Zysman","doi":"10.1108/S0277-283320190000033003","DOIUrl":"https://doi.org/10.1108/S0277-283320190000033003","url":null,"abstract":"Abstract \u0000The emergence of the platform economy is reorganizing work, employment, and value creation. The authors argue that the digital platforms are fracturing work itself as the places and types of work are being reorganized into a myriad of platform organized work arrangements with workplaces being potentially anywhere with Internet connectivity. The authors differ from most traditional narratives that focus solely upon either work displacement, a single type of platform-organized value-creating activity, or David Weil’s concentration solely upon the workplace. The authors recognize that even as some work is replaced, other work is being transformed; new work and old work in new arrangements is being created and recreated. The taxonomy begins with the workers employed directly by the platform and its contractors. The authors then introduce the category, platform-mediated work, which we divide into three groups: marketplaces such as Amazon; in-person service provision such as Uber and Airbnb; and remote service provision such as Upwork. The next category, “platform-mediated content creation,” is complex. The authors identify three groups of activities: consignment content creators that include services such as the app stores, YouTube, and Amazon Self-Publishing; non-platform organization content producers, which refers to the enormous number of workers occupied with creating and maintaining websites; and user-generated content which is the non-compensated value creation that ranges from content uploaded to Facebook, Instagram, etc. to reviews on sites such as Yelp. It is only when work and value creation is considered in all of these platform-based manifestations that we can understand the ultimate dimensions of the platform economy and comprehensively understand its implications for work.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124010557","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}
As technology platforms have created new markets and new ways of acquiring information, economists have come to play an increasingly central role in tech companies—tackling problems such as platform design, strategy, pricing, and policy. Over the past five years, hundreds of PhD economists have accepted positions in the technology sector. In this paper, we explore the skills that PhD economists apply in tech companies, the companies that hire them, the types of problems that economists are currently working on, and the areas of academic research that have emerged in relation to these problems.
{"title":"Economists (and Economics) in Tech Companies","authors":"S. Athey, Michael Luca","doi":"10.3386/w25064","DOIUrl":"https://doi.org/10.3386/w25064","url":null,"abstract":"As technology platforms have created new markets and new ways of acquiring information, economists have come to play an increasingly central role in tech companies—tackling problems such as platform design, strategy, pricing, and policy. Over the past five years, hundreds of PhD economists have accepted positions in the technology sector. In this paper, we explore the skills that PhD economists apply in tech companies, the companies that hire them, the types of problems that economists are currently working on, and the areas of academic research that have emerged in relation to these problems.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124244834","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}
Pub Date : 2018-09-01DOI: 10.5089/9781484378427.001
Nazim Belhocine, Daniel Garcia-Macia, José Garrido
The modernization of Italy’s insolvency framework has been the subject of much interest in recent years, related not least to its role in potentially facilitating an efficient allocation of resources. A unique feature of Italy’s insolvency framework is a special regime for large enterprises known as “extraordinary administration”. This paper evaluates the merits of this special regime by assessing its efficacy and success in achieving its stated goals and comparing its features to international standards and best practices. It finds that the special regime tends to impose large costs on creditors and the state. The regime results, in most cases, in the sale of parts of the group, followed by a liquidation phase of the remaining assets which can take longer than the general regime, hindering legal certainty for creditors and more generally economic efficiency, investment and job creation. Based on international best practices and experience, consideration should be given to folding the special regime into the general insolvency regime, possibly with provisions to allow for state intervention in specific well-defined circumstances.
{"title":"The Insolvency Regime for Large Enterprises in Italy: An Economic and Legal Assessment","authors":"Nazim Belhocine, Daniel Garcia-Macia, José Garrido","doi":"10.5089/9781484378427.001","DOIUrl":"https://doi.org/10.5089/9781484378427.001","url":null,"abstract":"The modernization of Italy’s insolvency framework has been the subject of much interest in recent years, related not least to its role in potentially facilitating an efficient allocation of resources. A unique feature of Italy’s insolvency framework is a special regime for large enterprises known as “extraordinary administration”. This paper evaluates the merits of this special regime by assessing its efficacy and success in achieving its stated goals and comparing its features to international standards and best practices. It finds that the special regime tends to impose large costs on creditors and the state. The regime results, in most cases, in the sale of parts of the group, followed by a liquidation phase of the remaining assets which can take longer than the general regime, hindering legal certainty for creditors and more generally economic efficiency, investment and job creation. Based on international best practices and experience, consideration should be given to folding the special regime into the general insolvency regime, possibly with provisions to allow for state intervention in specific well-defined circumstances.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134014275","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}
Charlie Eaton, Sabrina T. Howell, Constantine Yannelis
We study how private equity buyouts create value in higher education, a sector with opaque product quality and intense government subsidy. With novel data on 88 private equity deals involving 994 schools, we show that buyouts lead to higher tuition and per-student debt. Exploiting loan limit increases, we find that private equity-owned schools better capture government aid. After buyouts, we observe lower education inputs, graduation rates, loan repayment rates, and earnings among graduates. Neither school selection nor student body changes fully explain the results. The results indicate that in a subsidized industry, maximizing value may not improve consumer outcomes.Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
{"title":"When Investor Incentives and Consumer Interests Diverge: Private Equity in Higher Education","authors":"Charlie Eaton, Sabrina T. Howell, Constantine Yannelis","doi":"10.3386/W24976","DOIUrl":"https://doi.org/10.3386/W24976","url":null,"abstract":"We study how private equity buyouts create value in higher education, a sector with opaque product quality and intense government subsidy. With novel data on 88 private equity deals involving 994 schools, we show that buyouts lead to higher tuition and per-student debt. Exploiting loan limit increases, we find that private equity-owned schools better capture government aid. After buyouts, we observe lower education inputs, graduation rates, loan repayment rates, and earnings among graduates. Neither school selection nor student body changes fully explain the results. The results indicate that in a subsidized industry, maximizing value may not improve consumer outcomes.Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130874359","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 estimate the career and location preferences of students in U.S. doctoral programs in a major STEM field – chemistry. Our analysis is based on novel survey conducted in 2017 of 1,605 current Chemistry doctoral students enrolled in the top 54 U.S. research intensive universities. First, we estimate the career preferences of foreign and U.S. STEM students for different types of post-graduation jobs – postdocs, industry, or teaching positions – using both hypothetical choice methods and more standard Likert measures of preferences for different careers. We find that foreign students are generally more interested in academic careers than U.S. students, even when controlling for ability and comparing students from similar subfields and programs. Next, we estimate students’ location preferences using a hypothetical choice method: we ask respondents to choose between two postdoc job offers, where one offer is in the U.S. and one is abroad. We find that foreign students have a stronger preference for U.S. locations even after controlling for ability and career preferences. Our results suggest the U.S. is managing to retain talented foreign graduate students for postdoc positions.
{"title":"Will the U.S. Keep the Best and the Brightest (as Post-Docs)? Career and Location Preferences of Foreign Stem Phds","authors":"Ina Ganguli, P. Gaulé","doi":"10.3386/w24838","DOIUrl":"https://doi.org/10.3386/w24838","url":null,"abstract":"We estimate the career and location preferences of students in U.S. doctoral programs in a major STEM field – chemistry. Our analysis is based on novel survey conducted in 2017 of 1,605 current Chemistry doctoral students enrolled in the top 54 U.S. research intensive universities. First, we estimate the career preferences of foreign and U.S. STEM students for different types of post-graduation jobs – postdocs, industry, or teaching positions – using both hypothetical choice methods and more standard Likert measures of preferences for different careers. We find that foreign students are generally more interested in academic careers than U.S. students, even when controlling for ability and comparing students from similar subfields and programs. Next, we estimate students’ location preferences using a hypothetical choice method: we ask respondents to choose between two postdoc job offers, where one offer is in the U.S. and one is abroad. We find that foreign students have a stronger preference for U.S. locations even after controlling for ability and career preferences. Our results suggest the U.S. is managing to retain talented foreign graduate students for postdoc positions.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131418529","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}
Patenting in software, cloud computing, and artificial intelligence has grown rapidly in recent years. Such patents are acquired primarily by large US technology firms such as IBM, Microsoft, Google, and HP, as well as by Japanese multinationals such as Sony, Canon, and Fujitsu. Chinese patenting in the US is small but growing rapidly, and world-leading for drone technology. Patenting in machine learning has seen exponential growth since 2010, although patenting in neural networks saw a strong burst of activity in the 1990s that has only recently been surpassed. In all technological fields, the number of patents per inventor has declined near-monotonically, except for large increases in inventor productivity in software and semiconductors in the late 1990s. In most high-tech fields, Japan is the only country outside the US with significant US patenting activity; however, whereas Japan played an important role in the burst of neural network patenting in the 1990s, it has not been involved in the current acceleration. Comparing the periods 1970-89 and 2000-15, patenting in the current period has been primarily by entrant assignees, with the exception of neural networks.
{"title":"Some Facts of High-Tech Patenting","authors":"Michael Webb, Nick Short, N. Bloom, J. Lerner","doi":"10.2139/SSRN.3233722","DOIUrl":"https://doi.org/10.2139/SSRN.3233722","url":null,"abstract":"Patenting in software, cloud computing, and artificial intelligence has grown rapidly in recent years. Such patents are acquired primarily by large US technology firms such as IBM, Microsoft, Google, and HP, as well as by Japanese multinationals such as Sony, Canon, and Fujitsu. Chinese patenting in the US is small but growing rapidly, and world-leading for drone technology. Patenting in machine learning has seen exponential growth since 2010, although patenting in neural networks saw a strong burst of activity in the 1990s that has only recently been surpassed. In all technological fields, the number of patents per inventor has declined near-monotonically, except for large increases in inventor productivity in software and semiconductors in the late 1990s. In most high-tech fields, Japan is the only country outside the US with significant US patenting activity; however, whereas Japan played an important role in the burst of neural network patenting in the 1990s, it has not been involved in the current acceleration. Comparing the periods 1970-89 and 2000-15, patenting in the current period has been primarily by entrant assignees, with the exception of neural networks.","PeriodicalId":325993,"journal":{"name":"Ewing Marion Kauffman Foundation Research Paper Series","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132690441","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}
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