IDEAS home Printed from https://ideas.repec.org/a/spr/jqecon/v14y2016i1d10.1007_s40953-015-0019-y.html
   My bibliography  Save this article

Determinants and Forecast of Price Level in India: a VAR Framework

Author

Listed:
  • Cindrella Shah
  • Nilesh Ghonasgi

Abstract

The theoretical association of money supply and exchange rates with prices has been empirically established and shown to be dominant in explaining changes in price levels in India. However, post liberalisation, studies have shown price levels to be impacted by several other factors as also, weakened influence of the traditional factors established by theories. This study aims to find the determinants of price level for the period 1994–2008 using a Vector Autoregression model and test the predictive ability of the model. Our results show shorter and smaller impact of change in money supply and nominal effective exchange rate on price levels. Both money supply and nominal effective exchange rates are found to Granger-cause Consumer Price Index. But, impulse response functions show that the impact of shocks from money supply and nominal effective exchange rates on consumer prices peaks after two lags and is short-lived. Forecast error variance decomposition shows that these demand side factors contribute only 6 % of the forecast error variation in Consumer Price Index.

Suggested Citation

  • Cindrella Shah & Nilesh Ghonasgi, 2016. "Determinants and Forecast of Price Level in India: a VAR Framework," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 57-86, June.
  • Handle: RePEc:spr:jqecon:v:14:y:2016:i:1:d:10.1007_s40953-015-0019-y
    DOI: 10.1007/s40953-015-0019-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40953-015-0019-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s40953-015-0019-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Anuradha Patnaik, 2010. "Study of Inflation in India: A Cointegrated Vector Autoregression Approach," Journal of Quantitative Economics, The Indian Econometric Society, vol. 8(1), pages 118-129, January.
    2. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    3. Mr. Tim Callen & Dongkoo Chang, 1999. "Modeling and Forecasting Inflation in India," IMF Working Papers 1999/119, International Monetary Fund.
    4. repec:zbw:bofitp:2008_002 is not listed on IDEAS
    5. Anca Tanasie & Cosmin Fratostiteanu, 2008. "Forecasting inflation and its determinants," Revista Tinerilor Economisti (The Young Economists Journal), University of Craiova, Faculty of Economics and Business Administration, vol. 1(10), pages 110-116, April.
    6. N. Kundan Kishor, 2012. "Modeling Inflation In India: The Role Of Money," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 57(04), pages 1-19.
    7. Caesar Lack, 2006. "Forecasting Swiss inflation using VAR models," Economic Studies 2006-02, Swiss National Bank.
    8. Partha Ray & Jorge Somnath Chatterjee, 2001. "The role of asset prices in Indian inflation in recent years: some conjectures," BIS Papers chapters, in: Bank for International Settlements (ed.), Modelling aspects of the inflation process and the monetary transmission mechanism in emerging market countries, volume 8, pages 131-150, Bank for International Settlements.
    9. James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
    10. Kenny, Geoff & Meyler, Aidan & Quinn, Terry, 1998. "Bayesian VAR Models for Forecasting Irish Inflation," MPRA Paper 11360, University Library of Munich, Germany.
    11. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    12. Michael Debabrata Patra & Partha Ray, 2010. "Inflation Expectations and Monetary Policy in India: An Empirical Exploration," IMF Working Papers 2010/084, International Monetary Fund.
    13. Pankaj SINHA & Sushant GUPTA & Nakul RANDEV, 2011. "Modeling & Forecasting Of Macro-Economic Variables Of India: Before, During & After Recession," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 6(1(15)/ Sp), pages 43-60.
    14. Ankita Mishra & Vinod Mishra, 2010. "A VAR Model of Monetary Policy and Hypothetical Case of Inflation Targeting in India," Monash Economics Working Papers 15-10, Monash University, Department of Economics.
    15. P., Srinivasan & M., Kalaivani, 2013. "On the Temporal Causal Relationship between Macroeconomic Variables: Empirical Evidence from India," MPRA Paper 46803, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Weida Kuang & Changyu Chen & Qilin Wang, 2020. "Home purchase restriction, real estate investment, and corporate innovation," Frontiers of Business Research in China, Springer, vol. 14(1), pages 1-21, December.
    2. Xiaopeng Guo & Jiaxing Shi & Dongfang Ren, 2016. "Coal Price Forecasting and Structural Analysis in China," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-7, October.
    3. Ciarreta, Aitor & Martinez, Blanca & Nasirov, Shahriyar, 2023. "Forecasting electricity prices using bid data," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1253-1271.

    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. Cimadomo, Jacopo & Giannone, Domenico & Lenza, Michele & Monti, Francesca & Sokol, Andrej, 2022. "Nowcasting with large Bayesian vector autoregressions," Journal of Econometrics, Elsevier, vol. 231(2), pages 500-519.
    2. Nikola N. Nenovsky, 2023. "Are Monetary Aggregates Good Predictors for the Bulgarian Inflation Rate?," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 483-506.
    3. Yiru Wang & Barbara Rossi, 2019. "VAR-based Granger-causality test in the presence of instabilities," Economics Working Papers 1642, Department of Economics and Business, Universitat Pompeu Fabra.
    4. Friedrich Fritzer & Gabriel Moser & Johann Scharler, 2002. "Forecasting Austrian HICP and its Components using VAR and ARIMA Models," Working Papers 73, Oesterreichische Nationalbank (Austrian Central Bank).
    5. Biswajit Maitra, 2016. "Inflation Dynamics in India: Relative Role of Structural and Monetary Factors," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(2), pages 237-255, December.
    6. Barbara Rossi & Yiru Wang, 2019. "Vector autoregressive-based Granger causality test in the presence of instabilities," Stata Journal, StataCorp LP, vol. 19(4), pages 883-899, December.
    7. Biswajit Maitra & Tafajul Hossain, 2020. "Inflation in India: causes and anti-inflationary policy perception," International Journal of Economic Policy Studies, Springer, vol. 14(2), pages 363-387, August.
    8. Biqing Cai & Jiti Gao & Dag Tjøstheim, 2017. "A New Class of Bivariate Threshold Cointegration Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 288-305, April.
    9. Gossé, Jean-Baptiste & Guillaumin, Cyriac, 2013. "L’apport de la représentation VAR de Christopher A. Sims à la science économique," L'Actualité Economique, Société Canadienne de Science Economique, vol. 89(4), pages 309-319, Décembre.
    10. Faust, Jon & Gupta, Abhishek, 2010. "Posterior Predictive Analysis for Evaluating DSGE Models," MPRA Paper 26721, University Library of Munich, Germany.
    11. Liuan Wang & Lu (Lucy) Yan & Tongxin Zhou & Xitong Guo & Gregory R. Heim, 2020. "Understanding Physicians’ Online-Offline Behavior Dynamics: An Empirical Study," Information Systems Research, INFORMS, vol. 31(2), pages 537-555, June.
    12. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    13. Ramona Dumitriu & Razvan Stefanescu, 2015. "The Relationship Between Romanian Exports And Economic Growth After The Adhesion To European Union," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 17-26.
    14. Gediminas Adomavicius & Jesse Bockstedt & Alok Gupta, 2012. "Modeling Supply-Side Dynamics of IT Components, Products, and Infrastructure: An Empirical Analysis Using Vector Autoregression," Information Systems Research, INFORMS, vol. 23(2), pages 397-417, June.
    15. Blazsek, Szabolcs & Licht, Adrian, 2018. "Seasonal quasi-vector autoregressive models for macroeconomic data," UC3M Working papers. Economics 26316, Universidad Carlos III de Madrid. Departamento de Economía.
    16. Kritika Mathur & Nidhi Kaicker & Raghav Gaiha & Katsushi S. Imai & Ganesh Thapa, 2014. "Financialisation of food commodity markets, price surge and volatility: new evidence," Chapters, in: Raghbendra Jha & Raghav Gaiha & Anil B. Deolalikar (ed.), Handbook on Food, chapter 7, pages 149-176, Edward Elgar Publishing.
    17. Marek Rusnak & Tomas Havranek & Roman Horvath, 2013. "How to Solve the Price Puzzle? A Meta-Analysis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(1), pages 37-70, February.
    18. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    19. Alessio Moneta & Peter Spirtes, 2005. "Graph-Based Search Procedure for Vector Autoregressive Models," LEM Papers Series 2005/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    20. Barros, Geraldo Sant’Ana de Camargo & Carrara, Aniela Fagundes & Castro, Nicole Rennó & Silva, Adriana Ferreira, 2022. "Agriculture and inflation: Expected and unexpected shocks," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 178-188.

    More about this item

    Keywords

    Forecasting; Inflation; VAR;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    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:spr:jqecon:v:14:y:2016:i:1:d:10.1007_s40953-015-0019-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.