We first present methods of data analysis in defining stochastic mathematical models suitable for use in forecasting financial markets. With the purpose of multi-period portfolio selection via model predictive control, we focus on input-output model structures. By capturing cause-and-effect dynamic behaviors these models exhibit improved fidelity in simulation. Second we present a probabilistic approach for augmenting the identified models with auxiliary speculative/subjective information derived from analyst and regulatory reports. The technique is an application of the Kalman filter and can be interpreted as a logical extension — to a multi-period framework — of the well-known single-period Black-Litterman approach from portfolio optimization.
{"title":"Grey-Box Methods in Forecasting Financial Markets","authors":"J. Sørlie","doi":"10.2139/ssrn.2359057","DOIUrl":"https://doi.org/10.2139/ssrn.2359057","url":null,"abstract":"We first present methods of data analysis in defining stochastic mathematical models suitable for use in forecasting financial markets. With the purpose of multi-period portfolio selection via model predictive control, we focus on input-output model structures. By capturing cause-and-effect dynamic behaviors these models exhibit improved fidelity in simulation. Second we present a probabilistic approach for augmenting the identified models with auxiliary speculative/subjective information derived from analyst and regulatory reports. The technique is an application of the Kalman filter and can be interpreted as a logical extension — to a multi-period framework — of the well-known single-period Black-Litterman approach from portfolio optimization.","PeriodicalId":129620,"journal":{"name":"ERN: Input-Output Models (Topic)","volume":"14 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132579848","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}
Accounting is studied in this paper as an evolving artificial language that enables economic agents to manipulate symbolically networks of economic events. Expenditures, expenses, revenues, and cash flows are classes of processes, called actions, which affect the reservoirs of agents’ economic interests, called accounts: physical assets, financial assets, financial liabilities, and earnings. While the independence of actions (causes) from accounts (effects) is widely adopted by accounting scholars, it is systematically violated in all accounting databases. While the structural coupling of physical actions (expenditures, expenses, and revenues) with financial actions (cash flows) is widely discussed by scholars, it remains obscured. Finally, this paper discloses the compositionality of accounting transactions, i.e., the hierarchical structure {flow, [action, (credited account, debited account)]}, which automates the syntactic/semantic control of accounting data and reduces auditing to only pragmatic relevance. These three properties constitute an accounting theory that explains all paradoxes of the current double-entry theory of financial statements and resolves the debates on the causes of the nonarticulation of accounting information that undermines the consensus on the Conceptual Framework. In Part II, this theory is mathematically formalized for making the recording, reporting, and econometrics of complex empirical facts efficient and effective.
{"title":"The Accounting Properties of Economic Events (Part I: A Network Perspective)","authors":"K. R. Pertsemlidis","doi":"10.2139/ssrn.2041156","DOIUrl":"https://doi.org/10.2139/ssrn.2041156","url":null,"abstract":"Accounting is studied in this paper as an evolving artificial language that enables economic agents to manipulate symbolically networks of economic events. Expenditures, expenses, revenues, and cash flows are classes of processes, called actions, which affect the reservoirs of agents’ economic interests, called accounts: physical assets, financial assets, financial liabilities, and earnings. While the independence of actions (causes) from accounts (effects) is widely adopted by accounting scholars, it is systematically violated in all accounting databases. While the structural coupling of physical actions (expenditures, expenses, and revenues) with financial actions (cash flows) is widely discussed by scholars, it remains obscured. Finally, this paper discloses the compositionality of accounting transactions, i.e., the hierarchical structure {flow, [action, (credited account, debited account)]}, which automates the syntactic/semantic control of accounting data and reduces auditing to only pragmatic relevance. These three properties constitute an accounting theory that explains all paradoxes of the current double-entry theory of financial statements and resolves the debates on the causes of the nonarticulation of accounting information that undermines the consensus on the Conceptual Framework. In Part II, this theory is mathematically formalized for making the recording, reporting, and econometrics of complex empirical facts efficient and effective.","PeriodicalId":129620,"journal":{"name":"ERN: Input-Output Models (Topic)","volume":"29 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116564415","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}
After defining biproportion (or RAS) rigorously, we recall two fundamental theorems: unicity of biproportion (any biproportional algorithm leads to the same solution than biproportion, which turns biproportion into a mathematical tool as indisputable than proportion), ineffectiveness of separability (premultiplying or post multiplying the initial matrix by a diagonal matrix does not change the biproportional solution) and its corollary (it is equivalent to do a separable modification of the initial matrix or to do a proportional change of each biproportional factors). We then apply these theorems to show immediately that: i) no difficulties are encountered when solving the biproportional program, particularly for the question of the exponential; ii) the equivalence between applying biproportion on coefficient matrices and on transaction matrices is obvious; iii) normalizing the initial values of the biproportional factors obviously do not change anything (even if it is not possible to normalize the final value of these factors unless normalization is scalar); iv) the gravity model is equivalent to biproportion; v) biproportion and entropy give the same result; vi) when ineffectiveness of separability do not hold, the results are different as for added information. To the total, these theorems avoid re-demonstrating most properties.
{"title":"Six Matrix Adjustment Problems Solved by Some Fundamental Theorems on Biproportion","authors":"Louis de Mesnard","doi":"10.2139/ssrn.1692512","DOIUrl":"https://doi.org/10.2139/ssrn.1692512","url":null,"abstract":"After defining biproportion (or RAS) rigorously, we recall two fundamental theorems: unicity of biproportion (any biproportional algorithm leads to the same solution than biproportion, which turns biproportion into a mathematical tool as indisputable than proportion), ineffectiveness of separability (premultiplying or post multiplying the initial matrix by a diagonal matrix does not change the biproportional solution) and its corollary (it is equivalent to do a separable modification of the initial matrix or to do a proportional change of each biproportional factors). We then apply these theorems to show immediately that: i) no difficulties are encountered when solving the biproportional program, particularly for the question of the exponential; ii) the equivalence between applying biproportion on coefficient matrices and on transaction matrices is obvious; iii) normalizing the initial values of the biproportional factors obviously do not change anything (even if it is not possible to normalize the final value of these factors unless normalization is scalar); iv) the gravity model is equivalent to biproportion; v) biproportion and entropy give the same result; vi) when ineffectiveness of separability do not hold, the results are different as for added information. To the total, these theorems avoid re-demonstrating most properties.","PeriodicalId":129620,"journal":{"name":"ERN: Input-Output Models (Topic)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134436443","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}
Portuguese Abstract: Este trabalho teve como objetivo analisar as contribuicoes do turismo a economia brasileira, considerando-se a sua estrutura produtiva de 1999. Para isso, procurou-se caracterizar as relacoes intersetoriais, destacando-se os setores que compoem o segmento do turismo. Para realizacao deste trabalho, foi necessario desagregar a matriz de insumo-produto construida para o pais em setores que foram considerados turisticos e nao-turisticos. Na analise foram utilizados os indices de ligacoes de Hirschmann-Rasmussem, o campo de influencia e os indices puros de ligacoes. Os indices de ligacoes intersetoriais permitiram a identificacao dos setores-chave, considerando-se o modelo de insumo-produto aqui construido e o nivel de agregacao utilizado. Dentre os setores classificados como setores-chave, utilizando-se o conceito mais abrangente, seis foram inicialmente considerados como componentes do segmento do turismo: transporte aereo regular, transporte aereo nao-regular, agencias e organizadores de viagens, atividades auxiliares dos transportes aereos, estabelecimentos hoteleiros e outros tipos de alojamento temporario e restaurantes e outros estabelecimentos de servicos de alimentacao. Diante disso, ressalta-se a importância da implantacao de politicas e programas para promover o desenvolvimento do segmento turistico do Brasil, tendo em vista que o turismo contribui para o crescimento da economia nacional.English Abstract: This study aimed to analyze the tourism contributions to the Brazilian economy, considering the productive framework of 1999. For that, it was aimed to characterize the inter-sectors relations focusing on sectors that form the tourism segment. In order to perform this study, it was needed to share the input-output matrix constituted to the country into sectors which were considered touristy and non-touristy. In the analysis, it was used, the linkage index of Hirschmann-Rasmussem, the field of influence, the pure linkage. The linkages inter-sector indexes allowed the identification of key-sectors, considering the input-output model here developed and the level of aggregation used. Among the sectors classified as key-sectors, using the most extensive concept, six (06) were initially considered as compounds of the tourism segment: regular air transport, non-regular air transport, travel agents and agencies, supporting activities of air transport, hotels and other types of temporary accommodation, restaurants and other food establishments. In face of this, it is pointed out the importance of implementing policies and programs to promote the development of the sector of tourism in Brazil, considering that tourism contributes to the growth of the national economy.
{"title":"Matriz De Insumo-Produto Para a Economia Turística Brasileira: Construção E Análise Das Relações Intersetoriais (Input-Output Matrix for the Brazilian Tourism Economy: Construction and Analysis of Intersectoral Relationships)","authors":"F. Filho, J. Guilhoto","doi":"10.2139/SSRN.2410386","DOIUrl":"https://doi.org/10.2139/SSRN.2410386","url":null,"abstract":"Portuguese Abstract: Este trabalho teve como objetivo analisar as contribuicoes do turismo a economia brasileira, considerando-se a sua estrutura produtiva de 1999. Para isso, procurou-se caracterizar as relacoes intersetoriais, destacando-se os setores que compoem o segmento do turismo. Para realizacao deste trabalho, foi necessario desagregar a matriz de insumo-produto construida para o pais em setores que foram considerados turisticos e nao-turisticos. Na analise foram utilizados os indices de ligacoes de Hirschmann-Rasmussem, o campo de influencia e os indices puros de ligacoes. Os indices de ligacoes intersetoriais permitiram a identificacao dos setores-chave, considerando-se o modelo de insumo-produto aqui construido e o nivel de agregacao utilizado. Dentre os setores classificados como setores-chave, utilizando-se o conceito mais abrangente, seis foram inicialmente considerados como componentes do segmento do turismo: transporte aereo regular, transporte aereo nao-regular, agencias e organizadores de viagens, atividades auxiliares dos transportes aereos, estabelecimentos hoteleiros e outros tipos de alojamento temporario e restaurantes e outros estabelecimentos de servicos de alimentacao. Diante disso, ressalta-se a importância da implantacao de politicas e programas para promover o desenvolvimento do segmento turistico do Brasil, tendo em vista que o turismo contribui para o crescimento da economia nacional.English Abstract: This study aimed to analyze the tourism contributions to the Brazilian economy, considering the productive framework of 1999. For that, it was aimed to characterize the inter-sectors relations focusing on sectors that form the tourism segment. In order to perform this study, it was needed to share the input-output matrix constituted to the country into sectors which were considered touristy and non-touristy. In the analysis, it was used, the linkage index of Hirschmann-Rasmussem, the field of influence, the pure linkage. The linkages inter-sector indexes allowed the identification of key-sectors, considering the input-output model here developed and the level of aggregation used. Among the sectors classified as key-sectors, using the most extensive concept, six (06) were initially considered as compounds of the tourism segment: regular air transport, non-regular air transport, travel agents and agencies, supporting activities of air transport, hotels and other types of temporary accommodation, restaurants and other food establishments. In face of this, it is pointed out the importance of implementing policies and programs to promote the development of the sector of tourism in Brazil, considering that tourism contributes to the growth of the national economy.","PeriodicalId":129620,"journal":{"name":"ERN: Input-Output Models (Topic)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121931481","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 explicitly formulate (optimization) problems of finding a key sector and a key group of sectors within the framework of a hypothetical extraction method (HEM), and derive their solutions in terms of simple measures termed industries' factor worths. It is shown that the top k >= 2 sectors with the largest total contributions to some factor, in general, do not constitute the key group of k sectors, the issue which is totally ignored in the input-output linkage literature. The link to the fields of influence approach is discovered, which gives an alternative economic interpretation for the HEM problems in terms of sectors' input self-dependencies. Further, we examine how a change in an input coefficient affects the importance of an industry. The key group problem is applied to the Australian economy for factors of water use, CO2 emissions, and generation of profits and wages.
{"title":"A Generalized Hypothetical Extraction Analysis","authors":"U. Temurshoev","doi":"10.2139/ssrn.1350754","DOIUrl":"https://doi.org/10.2139/ssrn.1350754","url":null,"abstract":"We explicitly formulate (optimization) problems of finding a key sector and a key group of sectors within the framework of a hypothetical extraction method (HEM), and derive their solutions in terms of simple measures termed industries' factor worths. It is shown that the top k >= 2 sectors with the largest total contributions to some factor, in general, do not constitute the key group of k sectors, the issue which is totally ignored in the input-output linkage literature. The link to the fields of influence approach is discovered, which gives an alternative economic interpretation for the HEM problems in terms of sectors' input self-dependencies. Further, we examine how a change in an input coefficient affects the importance of an industry. The key group problem is applied to the Australian economy for factors of water use, CO2 emissions, and generation of profits and wages.","PeriodicalId":129620,"journal":{"name":"ERN: Input-Output Models (Topic)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128088125","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}
Chiara Broccolini, Alessia Lo Turco, A. Presbitero, S. Staffolani
The aim of this paper is to empirically evaluate the relative effects of international outsourcing of materials and services and of ICT capital deepening on wage inequality between blue and white collars in the Italian manufacturing industry during the period 1985-1999. We merge an administrative data set on workers' wages and individual characteristics with data on imported inputs from Italian input-output tables and other sector-level variables. Our results con firm that both material and service outsourcing widen the skilled/unskilled wage gap while ICT capital deepening positively affects real wages regardless of the worker's status. However, important differences emerge when the overall sample is split between traditional and innovative sectors.
{"title":"Individual Earnings, International Outsourcing and Technological Change","authors":"Chiara Broccolini, Alessia Lo Turco, A. Presbitero, S. Staffolani","doi":"10.2139/ssrn.1313811","DOIUrl":"https://doi.org/10.2139/ssrn.1313811","url":null,"abstract":"The aim of this paper is to empirically evaluate the relative effects of international outsourcing of materials and services and of ICT capital deepening on wage inequality between blue and white collars in the Italian manufacturing industry during the period 1985-1999. We merge an administrative data set on workers' wages and individual characteristics with data on imported inputs from Italian input-output tables and other sector-level variables. Our results con firm that both material and service outsourcing widen the skilled/unskilled wage gap while ICT capital deepening positively affects real wages regardless of the worker's status. However, important differences emerge when the overall sample is split between traditional and innovative sectors.","PeriodicalId":129620,"journal":{"name":"ERN: Input-Output Models (Topic)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116796765","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 use of input-output analysis for the computation of secondary effects of final demand changes is well-known. These 'final demand effects' can be calculated using technical coefficients and the inverse of the Leontief matrix. This paper offers an alternative to the use of technical coefficients. Its goal is threefold. First of all degrees of dependency are defined and it is shown how they can be used to compute secondary effects. Their definition is based on an input-output table. Secondly the concept of secondary effects is extended to what is called indirect effects. These indirect effects are not only related to final demand but to total industry output. It is shown how these indirect effects can be calculated using technical coefficients or degrees of dependency. The method used is a variant of the so-called Hypothetical Extraction Methods. Double counting is avoided, as such the resulting multipliers are 'net multipliers'. It is formally demonstrated that technical coefficients and degrees of dependency give the same results when a recent input-output table is available. If this is not the case then the results are different. It is impossible to say which of the two estimates is better. Since technical coefficients are already broadly accepted, some examples are given to justify the use of degrees of dependency. Finally it is explained how the unavailability of an input-output table can be solved. Starting from the supply-use tables a 'quick and dirty method' to infer an input-output table is provided. This topic is justified by the fact that for Belgium input-output tables are only published for those years that are divisible by five, with a three year lag. A short empirical analysis, based on currently available data, shows that technical coefficients and degrees of dependency have comparable performance, with a slight advantage for the technical coefficients. This performance is measured relative to a 'right' result, being the indirect effects for the year 2000 computed using the now available input-output table for the year 2000. This result is called 'right' because it does not make any assumptions on stability of technical coefficients nor of degrees of dependency. The empirical analysis also compares the use of a recent supply-use table to the use of an old input-output table. Supply-use tables on average overestimate the 'right' result. They are however often closest to the 'right' result at the first level. Since these conclusions are based on limited data further analysis is required as more data becomes available.
{"title":"Indirect Effects - A Formal Definition and Degrees of Dependency as an Alternative to Technical Coefficients","authors":"F. Coppens","doi":"10.2139/ssrn.1691468","DOIUrl":"https://doi.org/10.2139/ssrn.1691468","url":null,"abstract":"The use of input-output analysis for the computation of secondary effects of final demand changes is well-known. These 'final demand effects' can be calculated using technical coefficients and the inverse of the Leontief matrix. This paper offers an alternative to the use of technical coefficients. Its goal is threefold. First of all degrees of dependency are defined and it is shown how they can be used to compute secondary effects. Their definition is based on an input-output table. Secondly the concept of secondary effects is extended to what is called indirect effects. These indirect effects are not only related to final demand but to total industry output. It is shown how these indirect effects can be calculated using technical coefficients or degrees of dependency. The method used is a variant of the so-called Hypothetical Extraction Methods. Double counting is avoided, as such the resulting multipliers are 'net multipliers'. It is formally demonstrated that technical coefficients and degrees of dependency give the same results when a recent input-output table is available. If this is not the case then the results are different. It is impossible to say which of the two estimates is better. Since technical coefficients are already broadly accepted, some examples are given to justify the use of degrees of dependency. Finally it is explained how the unavailability of an input-output table can be solved. Starting from the supply-use tables a 'quick and dirty method' to infer an input-output table is provided. This topic is justified by the fact that for Belgium input-output tables are only published for those years that are divisible by five, with a three year lag. A short empirical analysis, based on currently available data, shows that technical coefficients and degrees of dependency have comparable performance, with a slight advantage for the technical coefficients. This performance is measured relative to a 'right' result, being the indirect effects for the year 2000 computed using the now available input-output table for the year 2000. This result is called 'right' because it does not make any assumptions on stability of technical coefficients nor of degrees of dependency. The empirical analysis also compares the use of a recent supply-use table to the use of an old input-output table. Supply-use tables on average overestimate the 'right' result. They are however often closest to the 'right' result at the first level. Since these conclusions are based on limited data further analysis is required as more data becomes available.","PeriodicalId":129620,"journal":{"name":"ERN: Input-Output Models (Topic)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125507883","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 use of constant price Input-Output (I-O) models is based on a widely accepted ex-ante notion without a strong empirical analysis. The present paper contributes by filling the research gap with regards to a comparison of nominal and real technology coefficients of India for the latest year 2007-08. In addition, the paper recognizes use of separate price indices for sectoral output and domestic supply. The deflation methodology makes use of specific deflators for inter-industry transactions.The results show structural changes for exports and imports in real terms, as compared with the corresponding nominal shares. Comparison of the nominal and real technology coefficients for individual sectors is revealing, particularly for the energy commodities. The paper validates the hypothesis that nominal and real I-O flows show significantly different production technologies with wide variations across sectors of the economy. Lower input coefficients, in real terms, can be resource saving for the downstream industries. At the same time, higher input coefficients indicate stronger backward linkages from the input providing upstream industries. This can have significant implications on energy requirements of the economy.
{"title":"Technology Coefficients in the Indian Economy: A Comparative Input-Output Analysis between Nominal and Real Coefficients","authors":"A. Tandon, Shahid Ahmed","doi":"10.2139/ssrn.2705329","DOIUrl":"https://doi.org/10.2139/ssrn.2705329","url":null,"abstract":"The use of constant price Input-Output (I-O) models is based on a widely accepted ex-ante notion without a strong empirical analysis. The present paper contributes by filling the research gap with regards to a comparison of nominal and real technology coefficients of India for the latest year 2007-08. In addition, the paper recognizes use of separate price indices for sectoral output and domestic supply. The deflation methodology makes use of specific deflators for inter-industry transactions.The results show structural changes for exports and imports in real terms, as compared with the corresponding nominal shares. Comparison of the nominal and real technology coefficients for individual sectors is revealing, particularly for the energy commodities. The paper validates the hypothesis that nominal and real I-O flows show significantly different production technologies with wide variations across sectors of the economy. Lower input coefficients, in real terms, can be resource saving for the downstream industries. At the same time, higher input coefficients indicate stronger backward linkages from the input providing upstream industries. This can have significant implications on energy requirements of the economy.","PeriodicalId":129620,"journal":{"name":"ERN: Input-Output Models (Topic)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134058223","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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