Pub Date : 2022-09-01DOI: 10.1177/00194662221118312
Farah Farooq Shah, D. Joshi
The research uses data from a multi-stage survey performed in 2019 to evaluate short-term migrants’ characteristics and sectoral transitions in Kashmir. After locating in-migrants in the selected clusters, we randomly selected 253 samples in a 70:30 urban–rural ratio. The IV-Probit is used to identify the features of short-term migration to the valley. Results reveal that short-term migrants are primarily absorbed in construction. In addition, most in-migrants are unskilled and come from marginalised communities. This study contributes to the knowledge on migration in a developing nation like India, particularly in Kashmir. In addition to temporarily increasing the urban inflow, short-term labour migration may assist the family left behind by remitting revenue. Hence, these results are critical for policymaking regarding mobility, urban development and the expanding construction sector. JEL Codes: J6; C2
{"title":"Determining the Attributes of Short-Term Migration to Kashmir, India","authors":"Farah Farooq Shah, D. Joshi","doi":"10.1177/00194662221118312","DOIUrl":"https://doi.org/10.1177/00194662221118312","url":null,"abstract":"The research uses data from a multi-stage survey performed in 2019 to evaluate short-term migrants’ characteristics and sectoral transitions in Kashmir. After locating in-migrants in the selected clusters, we randomly selected 253 samples in a 70:30 urban–rural ratio. The IV-Probit is used to identify the features of short-term migration to the valley. Results reveal that short-term migrants are primarily absorbed in construction. In addition, most in-migrants are unskilled and come from marginalised communities. This study contributes to the knowledge on migration in a developing nation like India, particularly in Kashmir. In addition to temporarily increasing the urban inflow, short-term labour migration may assist the family left behind by remitting revenue. Hence, these results are critical for policymaking regarding mobility, urban development and the expanding construction sector. JEL Codes: J6; C2","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"70 1","pages":"707 - 712"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43720543","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 : 2022-09-01DOI: 10.1177/00194662221118320
Haroon Rasool, Masudul Hasan Adil, Md.Ali Tarique
The call for inclusive growth has been unanimously declared by policymakers across the world. With India’s rapid economic growth rate, Indian policymakers also set its economy on the track of inclusive growth while formulating the 11th Five Year Plan. Despite, India’s fast-growing and vibrant economy, it fails poorly in Human Development Index ranked 131 in 2016. An unfortunate aspect of the current phase of high growth of the Indian economy has been its ‘non-inclusive’ nature. The distribution of income has been highly iniquitous. The richest 1% in India cornered 73% of the wealth generated in 2017, presenting a worrying picture of rising income inequality. In this regard, the study attempts to identify the determinants of inclusive growth in India by using annual data from 1981 to 2015. The study employs the autoregressive distributed lag (ARDL) model and the error correction method (ECM) to investigate the long-run and short-run relationship between inclusive growth and its determinants. The bounds test findings confirm the cointegrating relationship among variables. The ARDL estimates suggest that growth in initial income, government expenditure, human development, investment and financial development fosters inclusive growth; while inflation and population growth dampens it. The results also imply that increasing trade openness and foreign direct investment would not be beneficial for India in terms of growth inclusiveness. Based on these findings, the study recommends that the Government of India should take appropriate steps to increase per capita income and social spending with particular attention to macroeconomic stability while they work at improving the quality of population in order to achieve sustainable and robust inclusive growth. JEL Codes: Q4, F1, H7, D31, O43
{"title":"ARDL Approach to Drivers of Inclusive Growth In India","authors":"Haroon Rasool, Masudul Hasan Adil, Md.Ali Tarique","doi":"10.1177/00194662221118320","DOIUrl":"https://doi.org/10.1177/00194662221118320","url":null,"abstract":"The call for inclusive growth has been unanimously declared by policymakers across the world. With India’s rapid economic growth rate, Indian policymakers also set its economy on the track of inclusive growth while formulating the 11th Five Year Plan. Despite, India’s fast-growing and vibrant economy, it fails poorly in Human Development Index ranked 131 in 2016. An unfortunate aspect of the current phase of high growth of the Indian economy has been its ‘non-inclusive’ nature. The distribution of income has been highly iniquitous. The richest 1% in India cornered 73% of the wealth generated in 2017, presenting a worrying picture of rising income inequality. In this regard, the study attempts to identify the determinants of inclusive growth in India by using annual data from 1981 to 2015. The study employs the autoregressive distributed lag (ARDL) model and the error correction method (ECM) to investigate the long-run and short-run relationship between inclusive growth and its determinants. The bounds test findings confirm the cointegrating relationship among variables. The ARDL estimates suggest that growth in initial income, government expenditure, human development, investment and financial development fosters inclusive growth; while inflation and population growth dampens it. The results also imply that increasing trade openness and foreign direct investment would not be beneficial for India in terms of growth inclusiveness. Based on these findings, the study recommends that the Government of India should take appropriate steps to increase per capita income and social spending with particular attention to macroeconomic stability while they work at improving the quality of population in order to achieve sustainable and robust inclusive growth. JEL Codes: Q4, F1, H7, D31, O43","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"70 1","pages":"615 - 634"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42156997","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 : 2022-08-31DOI: 10.1177/00194662221118318
Sonia Chawla, S. Rani
The present article draws on the banker’s perspective and extracts some practical insights about the factors behind specific NPAs resolution strategies. Based on the thorough review of the perspective, conceptual and empirical literature, and using exploratory factor analysis (EFA), the study has identified 21 dimensions for ‘management of NPAs’. The empirical analysis of these dimensions has extracted 7 factors for management to be significant. A structured questionnaire has been developed and data has been collected from officers in different banks in India, especially working in the credit department. The questionnaire has been empirically tested for reliability and validity using confirmatory factor analysis (CFA) and also Z-test for checking the significance of the explored and confirmed factors. The present research work offers pragmatic suggestions for banking regulators, on improving the asset quality of banks in India and also throws new insights on effective credit management in banks. JEL Codes: G01, G21, G32, E44
{"title":"Resolution of Non-performing Assets of Commercial Banks: The Evidence from Banker’s Perspective in Indian Banking Sector","authors":"Sonia Chawla, S. Rani","doi":"10.1177/00194662221118318","DOIUrl":"https://doi.org/10.1177/00194662221118318","url":null,"abstract":"The present article draws on the banker’s perspective and extracts some practical insights about the factors behind specific NPAs resolution strategies. Based on the thorough review of the perspective, conceptual and empirical literature, and using exploratory factor analysis (EFA), the study has identified 21 dimensions for ‘management of NPAs’. The empirical analysis of these dimensions has extracted 7 factors for management to be significant. A structured questionnaire has been developed and data has been collected from officers in different banks in India, especially working in the credit department. The questionnaire has been empirically tested for reliability and validity using confirmatory factor analysis (CFA) and also Z-test for checking the significance of the explored and confirmed factors. The present research work offers pragmatic suggestions for banking regulators, on improving the asset quality of banks in India and also throws new insights on effective credit management in banks. JEL Codes: G01, G21, G32, E44","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"70 1","pages":"635 - 654"},"PeriodicalIF":0.0,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47943821","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 : 2022-08-29DOI: 10.1177/00194662221113931
S. Bhushan
{"title":"Editorial","authors":"S. Bhushan","doi":"10.1177/00194662221113931","DOIUrl":"https://doi.org/10.1177/00194662221113931","url":null,"abstract":"","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"70 1","pages":"383 - 384"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44529861","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 : 2022-08-29DOI: 10.1177/00194662221104756
G. P.
{"title":"Olivier Blanchard and Dani Rodrik (Ed.), Combating Inequality: Rethinking Government’s Role. Cambridge, Massachusetts, London, England: The MIT Press, 2021, pp. 312, $34.95. ISBN: 9780262045612.","authors":"G. P.","doi":"10.1177/00194662221104756","DOIUrl":"https://doi.org/10.1177/00194662221104756","url":null,"abstract":"","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"70 1","pages":"546 - 548"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48895363","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 : 2022-08-23DOI: 10.1177/00194662221118313
Abdhut Deheri
This article investigates the relationship between remittance inflows and financial development in India from 1980 to 2018. The study employed Autoregressive Distributed Lag (ARDL) and Vector Error Correction (VEC) models to capture the short and long-run dynamics. In addition, the impulse response function (IRF) and forecast error variance decomposition (FEVD) analysis were utilised to understand the dynamic reaction of financial development to a given shock to remittance inflows and other variables. The results of the ARDL model reveal that remittances negatively influence financial development in the short run, while they positively influence it in the long run. The IRF analysis shows that financial development responds positively to one standard positive shock to remittance inflows. The FEVD analysis further reveals that shocks to remittance inflows explain around 30% to 32% of the total variation in financial development. From a policy standpoint, the findings suggest that well-framed policies should be formulated and implemented to encourage more remittance flows through formal channels. It will boost financial development, economic growth and also increase the other developmental effects of remittances on the economy. JEL Codes: C32, F22, F37
{"title":"The Nexus Between Remittance Inflows and Financial Development in India: Substitutes or Complements?","authors":"Abdhut Deheri","doi":"10.1177/00194662221118313","DOIUrl":"https://doi.org/10.1177/00194662221118313","url":null,"abstract":"This article investigates the relationship between remittance inflows and financial development in India from 1980 to 2018. The study employed Autoregressive Distributed Lag (ARDL) and Vector Error Correction (VEC) models to capture the short and long-run dynamics. In addition, the impulse response function (IRF) and forecast error variance decomposition (FEVD) analysis were utilised to understand the dynamic reaction of financial development to a given shock to remittance inflows and other variables. The results of the ARDL model reveal that remittances negatively influence financial development in the short run, while they positively influence it in the long run. The IRF analysis shows that financial development responds positively to one standard positive shock to remittance inflows. The FEVD analysis further reveals that shocks to remittance inflows explain around 30% to 32% of the total variation in financial development. From a policy standpoint, the findings suggest that well-framed policies should be formulated and implemented to encourage more remittance flows through formal channels. It will boost financial development, economic growth and also increase the other developmental effects of remittances on the economy. JEL Codes: C32, F22, F37","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"70 1","pages":"597 - 614"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43665590","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 : 2022-07-07DOI: 10.1177/00194662221105552
Nagesh Kumar
One of the largest and richest economies of the world in much of the human history, India emerged from the colonial rule in 1947, as one of the poorest countries. Much has been achieved over the past 75 years in both economic and social terms. However, many challenges remain that need to be addressed over the next quarter century. In this essay, an overview of the key achievements and the gaps in India’s socio-economic development is presented, in the context ‘Azadi ka Amrit Mahotsav’, celebrating India’s 75th year of Independence. It also summarises aspirations for the Indian Centenary that will be celebrated in 2047 and a vision of India’s global leadership, not only in economic terms but also in terms of prosperity that is more inclusive, more sustainable and more resilient to enable her to celebrate the Centenary with a greater sense of national pride, achievement and fulfilment, becoming a role model for the developing world! JEL Codes: O53, O14, O11, O12
印度是人类历史上最大、最富有的经济体之一，1947年摆脱殖民统治，成为最贫穷的国家之一。过去75年来，在经济和社会方面都取得了很大成就。然而，仍有许多挑战需要在未来25年解决。在这篇文章中，概述了印度社会经济发展的主要成就和差距，在“Azadi ka Amrit Mahotsav”的背景下，庆祝印度独立75周年。它还总结了将于2047年庆祝的印度百年纪念的愿望，以及印度在全球领导地位的愿景，不仅在经济方面，而且在更包容、更可持续、更有弹性的繁荣方面，使她能够以更大的民族自豪感、成就和满足感庆祝百年纪念，成为发展中国家的榜样!JEL代码:O53, O14, O11, O12
{"title":"Indian Economy@75: Achievements, Gaps and Aspirations for the Indian Centenary","authors":"Nagesh Kumar","doi":"10.1177/00194662221105552","DOIUrl":"https://doi.org/10.1177/00194662221105552","url":null,"abstract":"One of the largest and richest economies of the world in much of the human history, India emerged from the colonial rule in 1947, as one of the poorest countries. Much has been achieved over the past 75 years in both economic and social terms. However, many challenges remain that need to be addressed over the next quarter century. In this essay, an overview of the key achievements and the gaps in India’s socio-economic development is presented, in the context ‘Azadi ka Amrit Mahotsav’, celebrating India’s 75th year of Independence. It also summarises aspirations for the Indian Centenary that will be celebrated in 2047 and a vision of India’s global leadership, not only in economic terms but also in terms of prosperity that is more inclusive, more sustainable and more resilient to enable her to celebrate the Centenary with a greater sense of national pride, achievement and fulfilment, becoming a role model for the developing world! JEL Codes: O53, O14, O11, O12","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"70 1","pages":"385 - 405"},"PeriodicalIF":0.0,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48266649","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 : 2022-06-27DOI: 10.1177/00194662221104786
Sreyash Sarkar, A. Chaudhury, Madhabendra Sinha
This study desires to look at the impact of family background on cognitive skills of the children. On the basis of primary survey of two districts of West Bengal—namely Bankura and Nadia—and using the fathers’ education, occupation and per capita household income as the proxies for family background we have employed multinomial probit and ordered logit regression model for this analysis. The findings reveal that there exists a significant positive association between family background and cognitive skills of the child indicating the existence of poor intergenerational mobility in education in the surveyed region. JEL Codes: I20, I24, I28
{"title":"Impact of Family Background on Cognitive Skills: An Empirical Investigation","authors":"Sreyash Sarkar, A. Chaudhury, Madhabendra Sinha","doi":"10.1177/00194662221104786","DOIUrl":"https://doi.org/10.1177/00194662221104786","url":null,"abstract":"This study desires to look at the impact of family background on cognitive skills of the children. On the basis of primary survey of two districts of West Bengal—namely Bankura and Nadia—and using the fathers’ education, occupation and per capita household income as the proxies for family background we have employed multinomial probit and ordered logit regression model for this analysis. The findings reveal that there exists a significant positive association between family background and cognitive skills of the child indicating the existence of poor intergenerational mobility in education in the surveyed region. JEL Codes: I20, I24, I28","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"70 1","pages":"533 - 545"},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43605724","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 : 2022-06-22DOI: 10.1177/00194662221105554
Pallavi Gupta, S. Kothe
Caste-based wage discrimination can counteract the development process. This article uses two distinct estimation methods to examine earning gaps between forward castes also referred to as ‘general category’ workers and traditionally disadvantaged or ‘backward caste’ workers in the Indian labour market. First, we interpret the inequality indicator of the Theil index and decompose Theil to show within and between-group inequalities. Second, a Threefold Oaxaca Decomposition is employed to break earnings differentials into components of endowment, coefficient and interaction. Earning gaps are examined separately in urban and rural divisions. Within-group inequalities are found larger than between groups across variables, with a higher overall inequality for forward castes. Wage differentials are substantially greater for urban areas and favour FC. A high endowment implies pre-market discrimination in human capital investments such as nutrition and education. Policymakers should first invest in basic quality education and simultaneously expand postgraduate diploma opportunities, subsequently increasing participation in the labour force for traditionally disadvantaged in disciplines and occupations where forward castes have long dominated. JEL Codes: J01, J08, J15, J30, J31, J71
{"title":"What Explains Caste-based Wage Inequalities and Earning Gaps in the Indian Labour Market? Theil and Oaxaca Decomposition Analysis","authors":"Pallavi Gupta, S. Kothe","doi":"10.1177/00194662221105554","DOIUrl":"https://doi.org/10.1177/00194662221105554","url":null,"abstract":"Caste-based wage discrimination can counteract the development process. This article uses two distinct estimation methods to examine earning gaps between forward castes also referred to as ‘general category’ workers and traditionally disadvantaged or ‘backward caste’ workers in the Indian labour market. First, we interpret the inequality indicator of the Theil index and decompose Theil to show within and between-group inequalities. Second, a Threefold Oaxaca Decomposition is employed to break earnings differentials into components of endowment, coefficient and interaction. Earning gaps are examined separately in urban and rural divisions. Within-group inequalities are found larger than between groups across variables, with a higher overall inequality for forward castes. Wage differentials are substantially greater for urban areas and favour FC. A high endowment implies pre-market discrimination in human capital investments such as nutrition and education. Policymakers should first invest in basic quality education and simultaneously expand postgraduate diploma opportunities, subsequently increasing participation in the labour force for traditionally disadvantaged in disciplines and occupations where forward castes have long dominated. JEL Codes: J01, J08, J15, J30, J31, J71","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"70 1","pages":"514 - 532"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43419694","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 : 2022-06-20DOI: 10.1177/00194662221104755
K. Nagi, G. Sridevi
This paper aims to answer if there is a gender-based disparity in educational performances due to the children’s background characteristics. What are the factors that cause a gender gap and the extent to which these factors contribute to the gap in educational performance? The study attempts to approach these questions using the fourth round of Young Lives survey data for the older cohort. Based on the results of a simple linear regression model and gender-based means of the explanatory variables, we adopted the Oaxaca–Blinder decomposition technique. Regression results show gender, time to study, social background, mother’s education, expenditure on education and years of education significantly influence the children’s mathematics performance and ceteris paribus. The majority of the performance difference, using the Oaxaca–Blinder technique, was explained by the differences in the variation of the mean outcome of male and female children, applied to the impact of female children. The entirety of the coefficient effect is explained by the body mass index and years of schooling a child has received. JEL Codes: I21, I22, I24, I25, I26, I29
{"title":"Unveiling Gender Gap in Educational Performance: Evidence from India","authors":"K. Nagi, G. Sridevi","doi":"10.1177/00194662221104755","DOIUrl":"https://doi.org/10.1177/00194662221104755","url":null,"abstract":"This paper aims to answer if there is a gender-based disparity in educational performances due to the children’s background characteristics. What are the factors that cause a gender gap and the extent to which these factors contribute to the gap in educational performance? The study attempts to approach these questions using the fourth round of Young Lives survey data for the older cohort. Based on the results of a simple linear regression model and gender-based means of the explanatory variables, we adopted the Oaxaca–Blinder decomposition technique. Regression results show gender, time to study, social background, mother’s education, expenditure on education and years of education significantly influence the children’s mathematics performance and ceteris paribus. The majority of the performance difference, using the Oaxaca–Blinder technique, was explained by the differences in the variation of the mean outcome of male and female children, applied to the impact of female children. The entirety of the coefficient effect is explained by the body mass index and years of schooling a child has received. JEL Codes: I21, I22, I24, I25, I26, I29","PeriodicalId":85705,"journal":{"name":"The Indian economic journal : the quarterly journal of the Indian Economic Association","volume":"70 1","pages":"472 - 489"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45642573","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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