IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/112440.html

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
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/112440/1/MPRA_paper_112440.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    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.
    2. repec:ebl:ecbull:v:6:y:2008:i:16:p:1-7 is not listed on IDEAS
    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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ditimi Amassoma & O. Adeleke, 2018. "Testing for the Causality between Interest Rate and Stock Market Performance in Nigeria," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 109-124.
    2. Bhuiyan, Erfan M. & Chowdhury, Murshed, 2020. "Macroeconomic variables and stock market indices: Asymmetric dynamics in the US and Canada," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 62-74.
    3. Onneetse L Sikalao-Lekobane, 2014. "Do Macroeconomic Variables Influence Domestic Stock Market Price Behaviour in Emerging Markets? A Johansen Cointegration Approach to the Botswana Stock Market," Journal of Economics and Behavioral Studies, AMH International, vol. 6(5), pages 363-372.
    4. Wilton Bernardino & João B. Amaral & Nelson L. Paes & Raydonal Ospina & José L. Távora, 2022. "A statistical investigation of a stock valuation model," SN Business & Economics, Springer, vol. 2(8), pages 1-25, August.
    5. Barja, Gover, 2014. "Time Series Analysis of Macroeconomic Conditions in Open Economies," EconStor Theses, ZBW - Leibniz Information Centre for Economics, number 333582.
    6. repec:ipg:wpaper:2014-442 is not listed on IDEAS
    7. Fredj Jawadi & Catherine Bruneau & Nadia Sghaier, 2009. "Nonlinear Cointegration Relationships Between Non‐Life Insurance Premiums and Financial Markets," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 753-783, September.
    8. Boucekkine, R. & Laksaci, M. & Touati-Tliba, M., 2021. "Long-run stability of money demand and monetary policy: The case of Algeria," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).
    9. Dimpfl, Thomas, 2014. "A note on cointegration of international stock market indices," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 10-16.
    10. Chakraborty, Chandana & Nunnenkamp, Peter, 2006. "Economic reforms, foreign direct investment and its economic effects in India," Kiel Working Papers 1272, Kiel Institute for the World Economy.
    11. Adamopoulos Antonios, 2010. "Credit Market Development and Economic Growth: An Empirical Analysis for Ireland," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 3-18.
    12. Lee, Chingnun & Shie, Fu Shuen & Chang, Chiao Yi, 2012. "How close a relationship does a capital market have with other such markets? The case of Taiwan from the Asian financial crisis," Pacific-Basin Finance Journal, Elsevier, vol. 20(3), pages 349-362.
    13. Oleg Deev & Martin Hodula, 2016. "Sovereign default risk and state-owned bank fragility in emerging markets: evidence from China and Russia," Post-Communist Economies, Taylor & Francis Journals, vol. 28(2), pages 232-248, April.
    14. Paqué, Karl-Heinz, 1991. "Structural wage rigidity in West Germany 1950-1989: Some new econometric evidence," Kiel Working Papers 489, Kiel Institute for the World Economy.
    15. Mustafa Serdar Basoglu & Turhan Korkmaz & Emrah Ismail Cevik, 2014. "London Metal Exchange: Causality Relationship between the Price Series of Non-Ferrous Metal Contracts," International Journal of Economics and Financial Issues, Econjournals, vol. 4(4), pages 726-734.
    16. Heejoon Kang, 2004. "Inappropriate Detrending and Spurious Cointegration," Econometric Society 2004 Far Eastern Meetings 624, Econometric Society.
    17. Eleni Constantinou & Avo Kazandjian & Georgios P. Kouretas & Vera Tahmazian, 2008. "Common Stochastic Trends Among The Cyprus Stock Exchange And The Ase, Lse And Nyse," Bulletin of Economic Research, Wiley Blackwell, vol. 60(4), pages 327-349, October.
    18. Panagiotis Petris & George Dotsis & Panayotis Alexakis, 2022. "Bubble tests in the London housing market: A borough level analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1044-1063, January.
    19. Rangan Gupta & Stephen Miller, 2012. "“Ripple effects” and forecasting home prices in Los Angeles, Las Vegas, and Phoenix," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 48(3), pages 763-782, June.
    20. Ali, Sharafat, 2014. "Inflation, Income Inequality and Economic Growth in Pakistan: A Cointegration Analysis," MPRA Paper 53706, University Library of Munich, Germany.
    21. Pedro Hugo Clavijo Cortes, 2017. "Balance comercial y volatilidad del tipo de cambio nominal: Un estudio de series de tiempo para Colombia," Revista Economía y Región, Universidad Tecnológica de Bolívar, vol. 11(1), pages 37-58.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:112440. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.