Pub Date : 2022-10-02DOI: 10.25071/1874-6322.40544
G. Fields
Pro-poor growth refers to how incomes change for the poor and for otherswhen economic growth occurs. Dualistic development refers to three typesof economic growth patterns in a two-sector economy: 1) modern sectorenrichment, 2) traditional sector enrichment, and 3) modern sectorenlargement. The question asked in this article is, what can we say aboutthe pro-poorness of each of the three types of dualistic development? Themain conclusion I reach is that pro-poor growth works well for the first twodualistic growth types but runs into some difficulties for the third. Toovercome these problems, I posit some axioms for dualistic development –particularly, by treating pro-richness and pro-poorness as distinct orderings.
{"title":"Pro-Poor Growth Meets Dualistic Development","authors":"G. Fields","doi":"10.25071/1874-6322.40544","DOIUrl":"https://doi.org/10.25071/1874-6322.40544","url":null,"abstract":"Pro-poor growth refers to how incomes change for the poor and for otherswhen economic growth occurs. Dualistic development refers to three typesof economic growth patterns in a two-sector economy: 1) modern sectorenrichment, 2) traditional sector enrichment, and 3) modern sectorenlargement. The question asked in this article is, what can we say aboutthe pro-poorness of each of the three types of dualistic development? Themain conclusion I reach is that pro-poor growth works well for the first twodualistic growth types but runs into some difficulties for the third. Toovercome these problems, I posit some axioms for dualistic development –particularly, by treating pro-richness and pro-poorness as distinct orderings.","PeriodicalId":142300,"journal":{"name":"Journal of Income Distribution®","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116658971","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 : 2022-10-02DOI: 10.25071/1874-6322.40548
Ira N. Gang, R. Natarajan, K. Sen, Myeong-Su Yun
We examine the patterns and correlates of the productivity gap betweenmale- and female-owned enterprises in India’s informal sector.Female-owned firms are 45 per cent less productive than male-owned firmson average, with the greatest productivity gaps observed at the lower end ofthe productivity distribution. We measure a firm’s productivity in terms ofits labour productivity. Using decomposition methods, we find thatstructural effects account for approximately 73 per cent of the productivitygap, with the remainder attributable to differences in observablecharacteristics captured by composition effects. We also find that, amongobservable characteristics, the most important set of factors explaining thegender productivity gap are the characteristics of a firm, such as its size,age, receipt of government assistance, registration with state authorities,contract-based work, and accounting records. Male-owned firms have acompetitive advantage over female-owned enterprises with respect to thesecharacteristics.
{"title":"Does the Gender of the Owner Affect the Productivity of Enterprises in India’s Informal Economy?","authors":"Ira N. Gang, R. Natarajan, K. Sen, Myeong-Su Yun","doi":"10.25071/1874-6322.40548","DOIUrl":"https://doi.org/10.25071/1874-6322.40548","url":null,"abstract":"We examine the patterns and correlates of the productivity gap betweenmale- and female-owned enterprises in India’s informal sector.Female-owned firms are 45 per cent less productive than male-owned firmson average, with the greatest productivity gaps observed at the lower end ofthe productivity distribution. We measure a firm’s productivity in terms ofits labour productivity. Using decomposition methods, we find thatstructural effects account for approximately 73 per cent of the productivitygap, with the remainder attributable to differences in observablecharacteristics captured by composition effects. We also find that, amongobservable characteristics, the most important set of factors explaining thegender productivity gap are the characteristics of a firm, such as its size,age, receipt of government assistance, registration with state authorities,contract-based work, and accounting records. Male-owned firms have acompetitive advantage over female-owned enterprises with respect to thesecharacteristics.","PeriodicalId":142300,"journal":{"name":"Journal of Income Distribution®","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130744557","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 : 2022-10-02DOI: 10.25071/1874-6322.40546
Shi Li, Yangyang Shen
This article assesses the pro-poor growth effect in China’s rural populationsover the period 2007–2018 using the strict pro-poor index proposed byNanak Kakwani. The results show that while China’s rural areas did notexperience strictly defined pro-poor growth between 2007–2013, acontemporary pro-poor effect was observed during which Targeted PovertyAlleviation (TPA) policies were implemented. The conclusion is robust inthe dimensions of income and expenditure and non-income well-being.Through a heterogeneity analysis, this article finds differences in pro-poorgrowth among various groups. In particular, poor women, seniors, children,and geographic areas (such as western China) benefited more during thetargeted poverty-alleviation policy period than their counterparts. Finally,we use Kakwani’s shared prosperity index to show that China is activelymaking more positive efforts and preparations towards attaining commonlyshared prosperity.
{"title":"Targeted Poverty Alleviation and Pro-Poor Growth","authors":"Shi Li, Yangyang Shen","doi":"10.25071/1874-6322.40546","DOIUrl":"https://doi.org/10.25071/1874-6322.40546","url":null,"abstract":"This article assesses the pro-poor growth effect in China’s rural populationsover the period 2007–2018 using the strict pro-poor index proposed byNanak Kakwani. The results show that while China’s rural areas did notexperience strictly defined pro-poor growth between 2007–2013, acontemporary pro-poor effect was observed during which Targeted PovertyAlleviation (TPA) policies were implemented. The conclusion is robust inthe dimensions of income and expenditure and non-income well-being.Through a heterogeneity analysis, this article finds differences in pro-poorgrowth among various groups. In particular, poor women, seniors, children,and geographic areas (such as western China) benefited more during thetargeted poverty-alleviation policy period than their counterparts. Finally,we use Kakwani’s shared prosperity index to show that China is activelymaking more positive efforts and preparations towards attaining commonlyshared prosperity.","PeriodicalId":142300,"journal":{"name":"Journal of Income Distribution®","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128261661","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 : 2022-09-04DOI: 10.25071/1874-6322.40477
Xiaoyang Zhu, Ying-Min Kuo
This paper uncovers a new mechanism through which financial development affects in- come inequality. We first revisit the effect of financial development on inequality using a panel of 94 countries from 1980 to 2017. The results show that both credit and equity markets development are positively related to different measurements of inequality, and the results are robust to endogeneity tests and other specifications. We then show empirically that this positive finance-inequality relationship can be explained by finance-induced innova- tion, especially by the finance-induced high-technology innovation. We further find that this mechanism seems to be more important than other innovation-related factors in explaining the finance-inequality relationship in low- and middle-income countries.
{"title":"Finance-induced Innovation: A New Mechanism Explaining Finance-Inequality Relationship","authors":"Xiaoyang Zhu, Ying-Min Kuo","doi":"10.25071/1874-6322.40477","DOIUrl":"https://doi.org/10.25071/1874-6322.40477","url":null,"abstract":"\u0000 \u0000 \u0000This paper uncovers a new mechanism through which financial development affects in- come inequality. We first revisit the effect of financial development on inequality using a panel of 94 countries from 1980 to 2017. The results show that both credit and equity markets development are positively related to different measurements of inequality, and the results are robust to endogeneity tests and other specifications. We then show empirically that this positive finance-inequality relationship can be explained by finance-induced innova- tion, especially by the finance-induced high-technology innovation. We further find that this mechanism seems to be more important than other innovation-related factors in explaining the finance-inequality relationship in low- and middle-income countries. \u0000 \u0000 \u0000","PeriodicalId":142300,"journal":{"name":"Journal of Income Distribution®","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128089595","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 : 2022-07-10DOI: 10.25071/1874-6322.40494
S. Khalifa
This paper argues that the effect of income inequality on economic growth depends on the level of democracy in a country and whether people believe that redistribution is an essential component of the democratic process. The paper uses the World Values Survey to focus on countries where the majority believe that taxing the rich and subsidizing the poor an essential component of democracy, and on countries where the majority believe that the rich do not buy elections in their country. Using the threshold estimation technique introduced by Hansen (1999), the analysis suggests the presence of a statistically significant threshold income inequality level, below which democracy does not have a statistically significant effect on growth, and above which an increase in the dose of democratization has a statistically significant negative effect on economic growth. The interpretation is that in countries where income inequality is high, and the majority believe that taxing the rich and subsidizing the poor is an essential component of democracy, a higher level of democratic governance allows people to support redistribution policies which can deter investment and economic growth.
{"title":"Distributive Justice, Democracy and Growth","authors":"S. Khalifa","doi":"10.25071/1874-6322.40494","DOIUrl":"https://doi.org/10.25071/1874-6322.40494","url":null,"abstract":"This paper argues that the effect of income inequality on economic growth depends on the level of democracy in a country and whether people believe that redistribution is an essential component of the democratic process. The paper uses the World Values Survey to focus on countries where the majority believe that taxing the rich and subsidizing the poor an essential component of democracy, and on countries where the majority believe that the rich do not buy elections in their country. Using the threshold estimation technique introduced by Hansen (1999), the analysis suggests the presence of a statistically significant threshold income inequality level, below which democracy does not have a statistically significant effect on growth, and above which an increase in the dose of democratization has a statistically significant negative effect on economic growth. The interpretation is that in countries where income inequality is high, and the majority believe that taxing the rich and subsidizing the poor is an essential component of democracy, a higher level of democratic governance allows people to support redistribution policies which can deter investment and economic growth.","PeriodicalId":142300,"journal":{"name":"Journal of Income Distribution®","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132640437","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 : 2022-06-12DOI: 10.25071/1874-6322.40474
Jordan Rosenblum, L. Kenworthy, Mikael Nygård
This article contributes to the quantitative analysis of international differences in executive compensation with a novel emphasis on the role of political drivers—specifically, labor power, owner power, and executive power—while controlling for market factors. It leverages nested analysis, pairing a 2016 cross-sectional analysis of 179 firms in 20 countries with case studies of Finland, from 1971 to 2017, and the United States, from 1936 to 2016. The 2016 cross-sectional analysis of the world's largest firms finds market forces are important, but leave a large portion of international differences in top executive compensation unexplained. Also important are labor power and executive power. Similarly, while controlling for market forces, the longitudinal case studies of large firms in the US and Finland each find stronger labor power relative to executive power associated with lower executive pay. The theoretical framework advanced in this paper helps to explain why top CEO pay—and consequent top-end income inequality—are each extreme in certain countries and periods, and modest in others.
{"title":"Power, Policy, and the Compensation of Top Executives","authors":"Jordan Rosenblum, L. Kenworthy, Mikael Nygård","doi":"10.25071/1874-6322.40474","DOIUrl":"https://doi.org/10.25071/1874-6322.40474","url":null,"abstract":"This article contributes to the quantitative analysis of international differences in executive compensation with a novel emphasis on the role of political drivers—specifically, labor power, owner power, and executive power—while controlling for market factors. It leverages nested analysis, pairing a 2016 cross-sectional analysis of 179 firms in 20 countries with case studies of Finland, from 1971 to 2017, and the United States, from 1936 to 2016. The 2016 cross-sectional analysis of the world's largest firms finds market forces are important, but leave a large portion of international differences in top executive compensation unexplained. Also important are labor power and executive power. Similarly, while controlling for market forces, the longitudinal case studies of large firms in the US and Finland each find stronger labor power relative to executive power associated with lower executive pay. The theoretical framework advanced in this paper helps to explain why top CEO pay—and consequent top-end income inequality—are each extreme in certain countries and periods, and modest in others.","PeriodicalId":142300,"journal":{"name":"Journal of Income Distribution®","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114846077","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 : 2022-06-12DOI: 10.25071/1874-6322.40475
Jeffrey Thompson, Jesse Bricker, Michael Parisi
We explore the importance of income fluctuations at the top of the U.S. income distribution in understanding rising income concentration. Very high income families—including the top .001 percent—account for much of the recent top income growth, but are under-studied even in the literature exploring high-income groups. Using 3-year panels of tax records from 1997 to 2013 we document that top-income shares are lower—typically by about 20 percent—when measured by using a three-year income average, and that cyclical income fluctuations are greatest at the very top of the income distribution. Trends toward rising concentration over time, however, cannot be explained by these fluctuations, as growth in top-income shares is comparable for annual and three-year average income, and measured income dispersion has increased only for the very top group. Further, the probability of remaining in the highest income groups over multiple years increased over the sample period.
{"title":"Understanding Rising Concentration at the Extremes of the U.S. Income Distribution","authors":"Jeffrey Thompson, Jesse Bricker, Michael Parisi","doi":"10.25071/1874-6322.40475","DOIUrl":"https://doi.org/10.25071/1874-6322.40475","url":null,"abstract":"We explore the importance of income fluctuations at the top of the U.S. income distribution in understanding rising income concentration. Very high income families—including the top .001 percent—account for much of the recent top income growth, but are under-studied even in the literature exploring high-income groups. Using 3-year panels of tax records from 1997 to 2013 we document that top-income shares are lower—typically by about 20 percent—when measured by using a three-year income average, and that cyclical income fluctuations are greatest at the very top of the income distribution. Trends toward rising concentration over time, however, cannot be explained by these fluctuations, as growth in top-income shares is comparable for annual and three-year average income, and measured income dispersion has increased only for the very top group. Further, the probability of remaining in the highest income groups over multiple years increased over the sample period.","PeriodicalId":142300,"journal":{"name":"Journal of Income Distribution®","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125257399","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 : 2021-12-13DOI: 10.25071/1874-6322.40445
Thomas Hauner
This paper asks if two, otherwise identical, economies were distinguished only by their distributions of wealth, are they equally stable in response to a random shock? A theoretical financial network model is proposed to understand the relationship between wealth inequality and financial crises. In a financial network, financial assets link individual asset and liability holders to form a web of economic connections. The total connectivity of an individual is described by their degree, and the overall distribution of connections in the network is imposed through a degree distribution--equivalent to the wealth distribution as incoming connections represent assets and outgoing connections liabilities. A network's topology varies with the level of wealth inequality and total wealth and together, simulations show, they determine network contagion in the event of a random negative income shock to some individual. Random network simulations, whereby each financial connection is randomly placed, reveal that increasing wealth inequality makes a wealthy network less stable--as measured by the share of individuals failing financially or the decline in financial asset values. These results suggest a unique architectural role for accumulated assets and their distribution in macro-financial stability.
{"title":"Wealth Inequality, Network Topology and Financial Instability","authors":"Thomas Hauner","doi":"10.25071/1874-6322.40445","DOIUrl":"https://doi.org/10.25071/1874-6322.40445","url":null,"abstract":"This paper asks if two, otherwise identical, economies were distinguished only by their distributions of wealth, are they equally stable in response to a random shock? A theoretical financial network model is proposed to understand the relationship between wealth inequality and financial crises. In a financial network, financial assets link individual asset and liability holders to form a web of economic connections. The total connectivity of an individual is described by their degree, and the overall distribution of connections in the network is imposed through a degree distribution--equivalent to the wealth distribution as incoming connections represent assets and outgoing connections liabilities. A network's topology varies with the level of wealth inequality and total wealth and together, simulations show, they determine network contagion in the event of a random negative income shock to some individual. Random network simulations, whereby each financial connection is randomly placed, reveal that increasing wealth inequality makes a wealthy network less stable--as measured by the share of individuals failing financially or the decline in financial asset values. These results suggest a unique architectural role for accumulated assets and their distribution in macro-financial stability.","PeriodicalId":142300,"journal":{"name":"Journal of Income Distribution®","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130638281","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 : 2021-11-05DOI: 10.25071/1874-6322.40462
Yishay D. Maoz, A. Sarid
An intricate dynamic pattern has been commonly observed in many developed countries during the past decades. This pattern contains a simultaneous rise in the following economic variables: (i) total factor productivity, (ii) educated labor supply, (iii) wage-gap between high- and low-skilled workers, and (iv) income inequality. Typical explanations for the different elements of this pattern assume a skill-biased technical change (SBTC) or capital-skill complementarity. In this study we offer a complementing explanation for these phenomena, which is based on sectoral heterogeneity and endogenous factor mobility, rather than on an SBTC. We show that sectoral heterogeneity can amplify the effects of a technical change, whether skill-biased or general, in a manner that generates the four elements of the above described dynamic pattern. Furthermore, inequality can perform also a Kuznets-curve pattern, as was observed in several countries, in contrast to the inequality dynamics in typical SBTC models.
{"title":"Sectoral Heterogeneity, Income Inequality and Productivity Dynamics","authors":"Yishay D. Maoz, A. Sarid","doi":"10.25071/1874-6322.40462","DOIUrl":"https://doi.org/10.25071/1874-6322.40462","url":null,"abstract":"An intricate dynamic pattern has been commonly observed in many developed countries during the past decades. This pattern contains a simultaneous rise in the following economic variables: (i) total factor productivity, (ii) educated labor supply, (iii) wage-gap between high- and low-skilled workers, and (iv) income inequality. Typical explanations for the different elements of this pattern assume a skill-biased technical change (SBTC) or capital-skill complementarity. In this study we offer a complementing explanation for these phenomena, which is based on sectoral heterogeneity and endogenous factor mobility, rather than on an SBTC. We show that sectoral heterogeneity can amplify the effects of a technical change, whether skill-biased or general, in a manner that generates the four elements of the above described dynamic pattern. Furthermore, inequality can perform also a Kuznets-curve pattern, as was observed in several countries, in contrast to the inequality dynamics in typical SBTC models.","PeriodicalId":142300,"journal":{"name":"Journal of Income Distribution®","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128635196","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 : 2021-10-22DOI: 10.25071/1874-6322.40447
Rafael Wildauer, Jakob Kapeller
Taking survey data of household wealth as our major example, this short article discusses some of the issues applied researchers are facing when fitting (Type I) Pareto distributions to complex survey data. The contribution of this article is threefold. First, we show how the ordering of the data vector is related to alternative definitions of the empirical CCDF. Second, we provide an intuitive reinterpretation of the bias-corrected estimator developed by Gabaix and Ibragimov (2011), in terms of the alternative definitions of the empirical CCDF, which allows us to generalize their result to the case of complex survey data. Third, we provide computational formulas for standard Kolmogorov-Smirnov (KS) and Cramer-von Mises (CvM) goodness- of-fit tests for complex survey data. Taken together the article provides a concise and hopefully useful presentation of the fundamentals of Pareto tail- fitting with complex survey data.
{"title":"Fitting Pareto Tails to Wealth Survey Data: A Practioners’ Guide","authors":"Rafael Wildauer, Jakob Kapeller","doi":"10.25071/1874-6322.40447","DOIUrl":"https://doi.org/10.25071/1874-6322.40447","url":null,"abstract":"\u0000\u0000\u0000Taking survey data of household wealth as our major example, this short article discusses some of the issues applied researchers are facing when fitting (Type I) Pareto distributions to complex survey data. The contribution of this article is threefold. First, we show how the ordering of the data vector is related to alternative definitions of the empirical CCDF. Second, we provide an intuitive reinterpretation of the bias-corrected estimator developed by Gabaix and Ibragimov (2011), in terms of the alternative definitions of the empirical CCDF, which allows us to generalize their result to the case of complex survey data. Third, we provide computational formulas for standard Kolmogorov-Smirnov (KS) and Cramer-von Mises (CvM) goodness- of-fit tests for complex survey data. Taken together the article provides a concise and hopefully useful presentation of the fundamentals of Pareto tail- fitting with complex survey data.\u0000\u0000\u0000","PeriodicalId":142300,"journal":{"name":"Journal of Income Distribution®","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124308238","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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