Abstract Following the Asian Financial Crisis, South Korea, Hong Kong, and Taiwan experienced card debt crisis in 2001, 2002 and 2005, respectively. Various countries have studied and tried to find the factors that lead to the card debt crisis, hoping that the proposed countermeasures can effectively solve the problem. However, these are only practical operations and observations. Therefore, through information asymmetry, this article constructs a model of card debt crisis from adverse selection and moral hazard, and theoretically provides the government or competent authority with a policy basis. This article employs document analysis, combined with qualitative and quantitative data, to test the research hypotheses. The verification result is supported regardless of hypotheses tests for adverse selection, or moral hazard and confirms that information asymmetry and market failure do exist in the Taiwan credit card market. The policy implication of the article is that the government or competent authority should stop the illusion of free market mechanism and have to be responsible for employing countermeasures to face the crisis. JEL classification numbers: G01,G21,G28. Keywords: Card debt crisis, Information asymmetry, Adverse selection, Moral hazard , Document analysis, Market failure.
{"title":"Information Asymmetry and Card Debt Crisis in Taiwan","authors":"Chih-Hsiung Chang","doi":"10.47260/bae/927","DOIUrl":"https://doi.org/10.47260/bae/927","url":null,"abstract":"Abstract\u0000Following the Asian Financial Crisis, South Korea, Hong Kong, and Taiwan experienced card debt crisis in 2001, 2002 and 2005, respectively. Various countries have studied and tried to find the factors that lead to the card debt crisis, hoping that the proposed countermeasures can effectively solve the problem. However, these are only practical operations and observations. Therefore, through information asymmetry, this article constructs a model of card debt crisis from adverse selection and moral hazard, and theoretically provides the government or competent authority with a policy basis. This article employs document analysis, combined with qualitative and quantitative data, to test the research hypotheses. The verification result is supported regardless of hypotheses tests for adverse selection, or moral hazard and confirms that information asymmetry and market failure do exist in the Taiwan credit card market. The policy implication of the article is that the government or competent authority should stop the illusion of free market mechanism and have to be responsible for employing countermeasures to face the crisis.\u0000\u0000JEL classification numbers: G01,G21,G28.\u0000Keywords: Card debt crisis, Information asymmetry, Adverse selection, Moral hazard , Document analysis, Market failure.","PeriodicalId":344946,"journal":{"name":"Bulletin of Applied Economics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132809265","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}
Abstract Previous studies on co-integration focused on whether there is co-integration between variables, and might not explore which variables are caused when co-integration exists. This study is based on a multivariate factor model and apply Quah’s decomposition theorem to derive common factors affecting long-run equilibrium, and use this common factor to explain which variables affect the formation of co-integration. Empirically, five stock markets in the Asian-Pacific Chinese region (Hong Kong, Singapore, Taiwan and China including Shanghai and Shenzhen stock markets) are the objects of analysis. According to the estimated common factor, the existence of the co-integration among the five stock markets is caused by the stock markets in Taiwan and Hong Kong. Therefore, when investing in these five stock markets, investors must incorporate and use the information of the two stock markets as a decisive factor in order to promote correct decision-making. That is, the policy authorities of these countries should promote the effective interaction and operation of the stock market. The decisive influence of stock market information in the two countries cannot be ignored. JEL classification numbers: F30, F65, G10, G15. Keywords: Co-integration, Error Correction Model (ECM), Common Component, Quah’s Decomposition Theorem.
{"title":"Common Components in Co-integrated System and Its Estimation and Application: Evidence from Five Stock Markets in Asia-Pacific Chinese Region","authors":"Hsiang-Hsi Liu, Chien-Kuo Tseng","doi":"10.47260/bae/926","DOIUrl":"https://doi.org/10.47260/bae/926","url":null,"abstract":"Abstract Previous studies on co-integration focused on whether there is co-integration between variables, and might not explore which variables are caused when co-integration exists. This study is based on a multivariate factor model and apply Quah’s decomposition theorem to derive common factors affecting long-run equilibrium, and use this common factor to explain which variables affect the formation of co-integration. Empirically, five stock markets in the Asian-Pacific Chinese region (Hong Kong, Singapore, Taiwan and China including Shanghai and Shenzhen stock markets) are the objects of analysis. According to the estimated common factor, the existence of the co-integration among the five stock markets is caused by the stock markets in Taiwan and Hong Kong. Therefore, when investing in these five stock markets, investors must incorporate and use the information of the two stock markets as a decisive factor in order to promote correct decision-making. That is, the policy authorities of these countries should promote the effective interaction and operation of the stock market. The decisive influence of stock market information in the two countries cannot be ignored. JEL classification numbers: F30, F65, G10, G15. Keywords: Co-integration, Error Correction Model (ECM), Common Component, Quah’s Decomposition Theorem.","PeriodicalId":344946,"journal":{"name":"Bulletin of Applied Economics","volume":"405 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125300038","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}
Abstract The рurрose of this research was to examine cointegration relationships among the stock market indices before and after the global financial crisis. The cointegration effects were analysed also in the context of the COVID-19 pandemic. The sample included 20 years of data at daily, weekly, and monthly frequencies for stock рrice indices in the United States (S&Р 500), Europe (STXE 600), Japan (Nikkei 225), China (SSE composite), Australia (S&P/ASX 200), and Brazil (IBOVESPA). Two interesting empirical facts were documented. First, the global financial crisis does not seem to have played a significant and uniform role in influencing the cointegration relationship, as only for the monthly sample the number of cointegrating relationships changed after the crisis. Second, the daily sample allowed to explore the period during the COVID-19 pandemic. The findings suggest that this event increased the number of cointegrating relationships, perhaps due to the global nature of such phenomenon which affects both developed and emerging economies contemporaneously. On the other hand, the financial crisis affected mainly developed economies, and the spillovers to emerging markets took place at a later stage as a second-round effect. In line with the previous findings in the existing literature, the results of the study have shown that cointegration stock market indices is dependent on the period of analysis and the frequency of the data. JEL classification numbers: C0, C4, G1, F6. Keywords: Cointegration analysis, stock markets, financial crisis, COVID-19.
{"title":"Cointegration Analysis of Financial Market Indices During Financial Shocks\u0000\u0000Focus on Global Financial Crisis and COVID-19 Рandemic Crisis","authors":"Roko Pedisic","doi":"10.47260/bae/924","DOIUrl":"https://doi.org/10.47260/bae/924","url":null,"abstract":"Abstract\u0000The рurрose of this research was to examine cointegration relationships among the stock market indices before and after the global financial crisis. The cointegration effects were analysed also in the context of the COVID-19 pandemic. The sample included 20 years of data at daily, weekly, and monthly frequencies for stock рrice indices in the United States (S&Р 500), Europe (STXE 600), Japan (Nikkei 225), China (SSE composite), Australia (S&P/ASX 200), and Brazil (IBOVESPA). \u0000Two interesting empirical facts were documented. First, the global financial crisis does not seem to have played a significant and uniform role in influencing the cointegration relationship, as only for the monthly sample the number of cointegrating relationships changed after the crisis. Second, the daily sample allowed to explore the period during the COVID-19 pandemic. The findings suggest that this event increased the number of cointegrating relationships, perhaps due to the global nature of such phenomenon which affects both developed and emerging economies contemporaneously. On the other hand, the financial crisis affected mainly developed economies, and the spillovers to emerging markets took place at a later stage as a second-round effect. \u0000In line with the previous findings in the existing literature, the results of the study have shown that cointegration stock market indices is dependent on the period of analysis and the frequency of the data.\u0000\u0000JEL classification numbers: C0, C4, G1, F6.\u0000Keywords: Cointegration analysis, stock markets, financial crisis, COVID-19.","PeriodicalId":344946,"journal":{"name":"Bulletin of Applied Economics","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115697547","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}
Abstract Thanks to the deregulation of financial regulations since the 1990s, the domestic financial institutions had ever been in excessive amounts for a long time. In order to expand their business scope and market share, they often adopted a looser or simple review mechanism, which led to a decline in the asset quality of financial institutions and an upward trend in overdue loans. As a result, the credit card debt crisis caused by the information asymmetry and the derived serious social problems ensued . Under the pressure of public opinion, the financial authority was forced to promote the debt negotiation mechanism in 2005 and even led passing the Consumer Debt Clearance Regulations in 2007. This article analyzed the statistics of consumer finance related to public and private banks, trying to explain whether the problems related to information asymmetry was reduced and whether financial institution management was effective. The result revealed that the number of valid cards, revolving interest rates, and overdue ratios fell in tandem after the financial authority intervened in the market. Especially when the credit card debt crisis and the social problem were showed under control, it was proven that financial institution management is essential and effective to reduce problems related to information asymmetry in Taiwan. JEL classification numbers: G01,G21,G28. Keywords: Financial Institution Management, Credit Cards, Card Debt Crisis, Information Asymmetry, Adverse Selection, Moral Hazard.
{"title":"Is Financial Institution Management Effective to Reduce Problems Related to Information Asymmetry in Taiwan?","authors":"Chih-Hsiung Chang, Wu Chang, Yi-Yu Shih","doi":"10.47260/bae/923","DOIUrl":"https://doi.org/10.47260/bae/923","url":null,"abstract":"Abstract\u0000Thanks to the deregulation of financial regulations since the 1990s, the domestic financial institutions had ever been in excessive amounts for a long time. In order to expand their business scope and market share, they often adopted a looser or simple review mechanism, which led to a decline in the asset quality of financial institutions and an upward trend in overdue loans. As a result, the credit card debt crisis caused by the information asymmetry and the derived serious social problems ensued . Under the pressure of public opinion, the financial authority was forced to promote the debt negotiation mechanism in 2005 and even led passing the Consumer Debt Clearance Regulations in 2007. \u0000This article analyzed the statistics of consumer finance related to public and private banks, trying to explain whether the problems related to information asymmetry was reduced and whether financial institution management was effective. The result revealed that the number of valid cards, revolving interest rates, and overdue ratios fell in tandem after the financial authority intervened in the market. Especially when the credit card debt crisis and the social problem were showed under control, it was proven that financial institution management is essential and effective to reduce problems related to information asymmetry in Taiwan.\u0000\u0000JEL classification numbers: G01,G21,G28.\u0000Keywords: Financial Institution Management, Credit Cards, Card Debt Crisis, Information Asymmetry, Adverse Selection, Moral Hazard.","PeriodicalId":344946,"journal":{"name":"Bulletin of Applied Economics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133796742","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}
Abstract The paper sought to assess the taxes and economic growth nexus in Ghana. The study used annual time-series data collected from 1972 to 2019. The study used the Johansen Co-integration technique, vector error correction model, and Granger causality test to assess the causal relationship between tax revenue and economic growth in Ghana. The Co-integration test was used to establish the long-run relationship. In contrast, the Granger Causality test was used to establish the short-run relationship between the variables used in the model. The study revealed that the model has a speed of adjustment of 61.4% to restore the short-run relationship to the long-run equilibrium path. Furthermore, the study found a unidirectional relationship between tax revenue variables and economic growth. Again, the study found support for a positive and significant nexus between direct tax revenue and economic growth and a significant and negative nexus between indirect tax revenue and economic growth. Based on the results, the study recommends that the government tax policy move gradually from indirect tax revenue concentration to direct tax revenue to finance development programs to sustain economic growth. Keywords: Direct tax; Economic growth; Granger Causality; Indirect tax.
{"title":"Tax Revenue and Economic Growth Nexus in Ghana: Co-integration and Granger causality Test","authors":"J. MacCarthy, Paul Muda, Prince Sunu","doi":"10.47260/bae/922","DOIUrl":"https://doi.org/10.47260/bae/922","url":null,"abstract":"Abstract\u0000The paper sought to assess the taxes and economic growth nexus in Ghana. The study used annual time-series data collected from 1972 to 2019. The study used the Johansen Co-integration technique, vector error correction model, and Granger causality test to assess the causal relationship between tax revenue and economic growth in Ghana. The Co-integration test was used to establish the long-run relationship. In contrast, the Granger Causality test was used to establish the short-run relationship between the variables used in the model. The study revealed that the model has a speed of adjustment of 61.4% to restore the short-run relationship to the long-run equilibrium path.\u0000Furthermore, the study found a unidirectional relationship between tax revenue variables and economic growth. Again, the study found support for a positive and significant nexus between direct tax revenue and economic growth and a significant and negative nexus between indirect tax revenue and economic growth. Based on the results, the study recommends that the government tax policy move gradually from indirect tax revenue concentration to direct tax revenue to finance development programs to sustain economic growth.\u0000\u0000Keywords: Direct tax; Economic growth; Granger Causality; Indirect tax.","PeriodicalId":344946,"journal":{"name":"Bulletin of Applied Economics","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134564316","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}
{"title":"On the Heteroskedastic-Autoregressive Specification of the Linear Regression Model","authors":"E. Lola, S. Symeonides","doi":"10.47260/bae/921","DOIUrl":"https://doi.org/10.47260/bae/921","url":null,"abstract":"","PeriodicalId":344946,"journal":{"name":"Bulletin of Applied Economics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126493168","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}
Olesea Speian, V. Ganea, Constantinos Kyriakopoulos
{"title":"Yield Curve Construction: A Note on the Moldovan bond market","authors":"Olesea Speian, V. Ganea, Constantinos Kyriakopoulos","doi":"10.47260/bae/919","DOIUrl":"https://doi.org/10.47260/bae/919","url":null,"abstract":"","PeriodicalId":344946,"journal":{"name":"Bulletin of Applied Economics","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128252457","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}
Abstract By setting the market capitalization as the frame of patent value reference, twenty-two quarter’s market capitalization from 2016Q1 to 2021Q2 of China listed companies (A-shares) were collected. All valid patent data of three patent species including the invention grant, the utility model grant and the design grant, were retrieved for calculating the average patent life of each A-share. The variances of the market capitalization via different patent life groups were analyzed via ANOVA. The A-shares having invention grant’s patent lives above the general level usually showed higher market capitalization means than the A-shares having invention grant’s patent lives below the general level. The invention grants with longer patent life might be regarded as the patents of higher value. The utility model grants with longer patent life might not be regarded as the patents of higher value because of poor significance. The design grant’s patent life was a significant indicator for discriminating China A-share’s market capitalization, however, the optimal patent life were close to but not longer than four years. The longer patent life of the design grants was not regarded as higher value. JEL classification numbers: C38, C46, G11, G12. Keywords: patent, market capitalization, China A-share, patent life, ANOVA.
{"title":"Longer Patent Life Representing Higher Value? A Study on China Stock Market and China Patents","authors":"Hong-Wen Tsai, Hui-Chung Che, Bo Bai","doi":"10.47260/bae/918","DOIUrl":"https://doi.org/10.47260/bae/918","url":null,"abstract":"Abstract\u0000By setting the market capitalization as the frame of patent value reference, twenty-two quarter’s market capitalization from 2016Q1 to 2021Q2 of China listed companies (A-shares) were collected. All valid patent data of three patent species including the invention grant, the utility model grant and the design grant, were retrieved for calculating the average patent life of each A-share. The variances of the market capitalization via different patent life groups were analyzed via ANOVA. The A-shares having invention grant’s patent lives above the general level usually showed higher market capitalization means than the A-shares having invention grant’s patent lives below the general level. The invention grants with longer patent life might be regarded as the patents of higher value. The utility model grants with longer patent life might not be regarded as the patents of higher value because of poor significance. The design grant’s patent life was a significant indicator for discriminating China A-share’s market capitalization, however, the optimal patent life were close to but not longer than four years. The longer patent life of the design grants was not regarded as higher value.\u0000\u0000JEL classification numbers: C38, C46, G11, G12.\u0000Keywords: patent, market capitalization, China A-share, patent life, ANOVA.","PeriodicalId":344946,"journal":{"name":"Bulletin of Applied Economics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133364752","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}
Abstract The functionality of a region depends on its people. Yet for some regions within Australia, attracting and retaining varied skilled people continues to be a challenge. What influences people to want to stay, move away from or move into a region? Before we can answer this question, we firstly need to understand ‘who’ is making this decision. Much of past research assumes the decision is made at the individual head of household level or must assume the decision is made at the individual as opposed to the household level as a result of data availability. This paper highlights the limitations of making such an assumption and offers an alternative method transforming secondary microdata to reflect the collective household unit as the decision making unit. We find that our migration models are statistically robust with results consistent with conventional studies that show smaller, younger households are more mobile. Most importantly, however, we find evidence that our proxies which represent characteristics of the collective unit, termed “Decision Making Unit”, are also statistically significant. Thus, justifying the need for migration models to reflect the collective unit and not just the individual, should we seek to better understand motives. JEL classification numbers: J61, R23, R58 Keywords: interregional migration, migration, decision-making, households, regions
{"title":"Interregional Migration: Who Decides to Move?","authors":"Diana Castorina, R. Welters","doi":"10.47260/bae/917","DOIUrl":"https://doi.org/10.47260/bae/917","url":null,"abstract":"Abstract\u0000\u0000The functionality of a region depends on its people. Yet for some regions within Australia, attracting and retaining varied skilled people continues to be a challenge. What influences people to want to stay, move away from or move into a region? Before we can answer this question, we firstly need to understand ‘who’ is making this decision. Much of past research assumes the decision is made at the individual head of household level or must assume the decision is made at the individual as opposed to the household level as a result of data availability. This paper highlights the limitations of making such an assumption and offers an alternative method transforming secondary microdata to reflect the collective household unit as the decision making unit. We find that our migration models are statistically robust with results consistent with conventional studies that show smaller, younger households are more mobile. Most importantly, however, we find evidence that our proxies which represent characteristics of the collective unit, termed “Decision Making Unit”, are also statistically significant. Thus, justifying the need for migration models to reflect the collective unit and not just the individual, should we seek to better understand motives. \u0000\u0000JEL classification numbers: J61, R23, R58\u0000Keywords: interregional migration, migration, decision-making, households, regions","PeriodicalId":344946,"journal":{"name":"Bulletin of Applied Economics","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130955940","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 briefly survey the literature which uses data for Gini coefficients of education. We update the Gini coefficients of education to include the year 2015, added to the Barro-Lee data set recently, and compare them to those of the earlier data set based on older Barro-Lee data. A panel analysis shows that every five years education inequality falls by 2.8 percentage points. A stable average value is predicted to be 0.22. Kernel density world distributions for education Ginis loose their twin peaks when going from 1955 to later years, and the right tail of the distribution with high inequality is losing mass over time.
{"title":"Global Dynamics of Gini Coefficients of Education for 146 Countries: Update to 1950-2015 and a Compact Guide to the Literature","authors":"T. Ziesemer","doi":"10.47260/bae/916","DOIUrl":"https://doi.org/10.47260/bae/916","url":null,"abstract":"We briefly survey the literature which uses data for Gini coefficients of education. We update the Gini coefficients of education to include the year 2015, added to the Barro-Lee data set recently, and compare them to those of the earlier data set based on older Barro-Lee data. A panel analysis shows that every five years education inequality falls by 2.8 percentage points. A stable average value is predicted to be 0.22. Kernel density world distributions for education Ginis loose their twin peaks when going from 1955 to later years, and the right tail of the distribution with high inequality is losing mass over time.","PeriodicalId":344946,"journal":{"name":"Bulletin of Applied Economics","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132816576","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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