金融部门发展和实体部门增长:疫情前和疫情期间的关联、溢出效应和因果关系

T. Chaudhuri, Indranil Ghosh
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引用次数: 0

摘要

在本文中,我们提出了另一种方法来理解印度金融部门发展与实体部门增长之间的关系。我们使用国家证券交易所(NSE)提供的股票市场行业指数,如资本货物指数、快速消费品指数、能源指数、基础设施指数、金属指数、房地产指数和汽车指数来代表实体行业。为了代表金融行业,我们分别考虑银行指数和金融服务指数。建议的框架在颗粒级上检查关系,以了解关联,溢出和因果关系的程度。我们还分别分析了新冠疫情前和新冠疫情期间金融部门与实体部门之间的关系。我们的研究方法包括使用去趋势相互关联分析(DCCA)、小波多重相关(WMC)、小波多重相互相关(WMCC)、Diebold-Yilmaz溢出框架和非线性因果检验。我们的细粒度方法使我们能够检查不同时期的关系,我们观察到结果是变化的。在COVID期间,与COVID前期间相比,这种关系的强度也不同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FINANCIAL SECTOR DEVELOPMENT AND REAL SECTOR GROWTH – ASSOCIATION, SPILLOVER AND CAUSALITY DURING PRE COVID AND COVID REGIMES
In this paper, we propose an alternative approach to understanding the relationship between financial sector development and real sector growth in India. We use stock market sectoral indices available on National Stock Exchange (NSE) like Capital Goods Index, FMCG Index, Energy Index, Infra Index, Metal Index, Realty Index, and Auto Index to represent the real sector. To represent the financial sector, we consider Bank Index and Financial Services Index separately. The proposed framework examines the relationships at a granular level to understand the extent of association, spillover, and causality. We also analyze the relationship between the financial sector and the real sector in Pre COVID and COVID periods separately. Our research methodology includes the use of Detrended Cross-Correlation Analysis (DCCA), Wavelet Multiple Correlation (WMC), Wavelet Multiple Cross Correlation (WMCC), Diebold-Yilmaz spillover Framework, and Non-Linear Causality Test. Our granular approach has enabled us to examine the relationships in different periods and we observe that the results change. The intensity of the relationships also is different during the COVID period as compared to Pre COVID period.
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