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Analyzing Interlinkages between Financial and Real Estate Sector in the aftermath of COVID-19's Second wave: An Econometric Approach using VECM model

Author

Listed:
  • G.K., Chetan Kumar
  • K.B., Rangappa
  • S., Suchitra

Abstract

Entire global economy has been adversely affected by the demand and supply shocks which have been created due to consequent waves of Covid-19 pandemic. Indian Economy was none the better amidst the second wave. Due to the demand and supply shocks at both national and international level, Indian Economy witnessed an unprecedented contraction of its Gross Domestic Product by around twenty four percent. In this context one of the few prominent sectors which could assist in the recovery of Indian Economy is expected to be Real Estate. Due to its inherent forward and backward linkages with infrastructure, it could assist in faster recovery of economy through multiplier effect. In addition to that, Credit Policy is going to play a vital role in assisting the recovery of any prominent sector. In this backdrop, our study is an attempt to analyze as to whether Real Estate, Infrastructure and Financial sector are co-integrated or not. Further, provided they are co-integrated, our study tries to find out the speed of correction. Our paper through its empirical approach aims to suggest relevant credit policy measures.

Suggested Citation

  • G.K., Chetan Kumar & K.B., Rangappa & S., Suchitra, 2021. "Analyzing Interlinkages between Financial and Real Estate Sector in the aftermath of COVID-19's Second wave: An Econometric Approach using VECM model," MPRA Paper 112440, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:112440
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    References listed on IDEAS

    as
    1. S. Mahendra Dev & Rajeswari Sengupta, 2020. "Covid-19: Impact on the Indian economy," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2020-013, Indira Gandhi Institute of Development Research, Mumbai, India.
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    3. Orawan Ratanapakorn & Subhash Sharma, 2007. "Dynamic analysis between the US stock returns and the macroeconomic variables," Applied Financial Economics, Taylor & Francis Journals, vol. 17(5), pages 369-377.
    4. Robert Engle & Clive Granger, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    5. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-228, August.
    Full references (including those not matched with items on IDEAS)

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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G2 - Financial Economics - - Financial Institutions and Services
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • M2 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

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