IDEAS home Printed from https://ideas.repec.org/a/vls/finstu/v18y2014i3p8-24.html
   My bibliography  Save this article

Assessing The Forecasts Accuracy Of The Weight Of Fiscal Revenues In Gdp For Romania

Author

Listed:
  • SIMIONESCU, Mihaela

    (Institute for Economic Forecasting, Romanian Academy)

Abstract

The main aim of this research is to construct different forecasts for the weight of fiscal revenues in the GDP for Romania on short horizon (2011-2013) by using different types of econometric models. Using annual data from 1995, according to Granger causality test, there is a unidirectional relationship between weight of fiscal revenues (an indicator of fiscal pressure) and real GDP rate in first difference. 74.48% of the fiscal revenues weights is due to this variable, the influence very slowly decreasing till 72.56% at the 10th lag. In the first period, the variation in transformed GDP rate explains 19.25% of the variation in fiscal pressure indicator. The predictions based on a vector-autoregressive model of order 1 (VAR(1)) outperformed the forecasts based on a Bayesian VAR model, moving average process (MA(2)) and dynamic factor model. The static and stochastic simulations based on VAR(1) generated the best predictions of the fiscal pressure indicator on the horizon 2011-2013, according to absolute and relative accuracy measures, excepting the mean error. In terms of sign and directional accuracy, all the types of forecasts performed the same.

Suggested Citation

  • SIMIONESCU, Mihaela, 2014. "Assessing The Forecasts Accuracy Of The Weight Of Fiscal Revenues In Gdp For Romania," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 18(3), pages 8-24.
  • Handle: RePEc:vls:finstu:v:18:y:2014:i:3:p:8-24
    as

    Download full text from publisher

    File URL: ftp://www.eadr.ro/RePEc/vls/vls_pdf/vol18i3p8-24.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christophe Kamps, 2005. "The Dynamic Effects of Public Capital: VAR Evidence for 22 OECD Countries," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 12(4), pages 533-558, August.
    2. E. Paul Durrenberger, 2005. "Labour," Chapters, in: James G. Carrier (ed.), A Handbook of Economic Anthropology, chapter 8, Edward Elgar Publishing.
    3. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    4. Kesten Green & Len Tashman, 2008. "Should We Define Forecast Error as E = F - A Or E = A - F?," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 10, pages 38-40, Summer.
    5. Roberto Perotti, 2004. "Public investment: another (different) look," Working Papers 277, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    6. Camba-Mendez, Gonzalo, 2012. "Conditional forecasts on SVAR models using the Kalman filter," Economics Letters, Elsevier, vol. 115(3), pages 376-378.
    7. A. Melander & G. Sismanidis & D. Grenouilleau, 2007. "The track record of the Commission's forecasts - an update," European Economy - Economic Papers 2008 - 2015 291, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    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. António Afonso & Miguel St. Aubyn, 2009. "Macroeconomic Rates Of Return Of Public And Private Investment: Crowding‐In And Crowding‐Out Effects," Manchester School, University of Manchester, vol. 77(s1), pages 21-39, September.
    2. Alfredo Marvão Pereira & Oriol Roca-Sagalés, 2011. "Long-term effects of fiscal policies in Portugal," Journal of Economic Studies, Emerald Group Publishing, vol. 38(1), pages 114-127, January.
    3. João Sousa Andrade & António Portugal Duarte, 2016. "Crowding-in and crowding-out effects of public investments in the Portuguese economy," International Review of Applied Economics, Taylor & Francis Journals, vol. 30(4), pages 488-506, July.
    4. Tong, Tingting & Yu, Edward & Roberts, Roland K., 2014. "Dynamics of Transport Infrastructure, Exports and Economic Growth in the United States," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 53(1), pages 1-18.
    5. Miguel A. Márquez & Julián Ramajo & Geoffrey JD. Hewings, 2015. "Regional growth and spatial spillovers: Evidence from an SpVAR for the Spanish regions," Papers in Regional Science, Wiley Blackwell, vol. 94, pages 1-18, November.
    6. Buchheim, Lukas & Watzinger, Martin, 2017. "The Employment Effects of Countercyclical Infrastructure Investments," Discussion Papers in Economics 34877, University of Munich, Department of Economics.
    7. Federici, Andrea, 2018. "Il rapporto tra capitale pubblico e altre variabili macroeconomiche: un'applicazione empirica [The relationship between public capital and other macroeconomic variables: an empirical application]," MPRA Paper 88516, University Library of Munich, Germany.
    8. António Afonso & Peter Claeys, 2006. "The dynamic behaviour of budget components and output – the cases of France, Germany, Portugal, and Spain," Working Papers Department of Economics 2006/26, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    9. Emeka Nkoro & Aham Kelvin Uko, 2016. "Exchange Rate and Inflation Volatility and Stock Prices Volatility: Evidence from Nigeria, 1986-2012," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 6(6), pages 1-4.
    10. Nikolay Hristov & Markus Roth, 2019. "Uncertainty Shocks and Financial Crisis Indicators," CESifo Working Paper Series 7839, CESifo.
    11. Loperfido, Nicola, 2010. "A note on marginal and conditional independence," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1695-1699, December.
    12. Kerstin Enflo & Per Hjertstrand, 2009. "Relative Sources of European Regional Productivity Convergence: A Bootstrap Frontier Approach," Regional Studies, Taylor & Francis Journals, vol. 43(5), pages 643-659.
    13. Zamani, Mehrzad, 2007. "Energy consumption and economic activities in Iran," Energy Economics, Elsevier, vol. 29(6), pages 1135-1140, November.
    14. Muhammad Shafiullah & Ravinthirakumaran Navaratnam, 2016. "Do Bangladesh and Sri Lanka Enjoy Export-Led Growth? A Comparison of Two Small South Asian Economies," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 17(1), pages 114-132, March.
    15. Alberto Fuertes & Simón Sosvilla-Rivero, 2019. "“Forecasting emerging market currencies: Are inflation expectations useful?”," IREA Working Papers 201918, University of Barcelona, Research Institute of Applied Economics, revised Oct 2019.
    16. Wesam Salah Alaloul & Muhammad Ali Musarat & Muhammad Babar Ali Rabbani & Qaiser Iqbal & Ahsen Maqsoom & Waqas Farooq, 2021. "Construction Sector Contribution to Economic Stability: Malaysian GDP Distribution," Sustainability, MDPI, Open Access Journal, vol. 13(9), pages 1-26, April.
    17. Hany Eldemerdash & Hugh Metcalf & Sara Maioli, 2014. "Twin deficits: new evidence from a developing (oil vs. non-oil) countries’ perspective," Empirical Economics, Springer, vol. 47(3), pages 825-851, November.
    18. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
    19. Omaima A.G. Hassan & Peter Romilly, 2018. "Relations between corporate economic performance, environmental disclosure and greenhouse gas emissions: New insights," Business Strategy and the Environment, Wiley Blackwell, vol. 27(7), pages 893-909, November.
    20. Claire G.Gilmore & Brian Lucey & Ginette M.McManus, 2005. "The Dynamics of Central European Equity Market Integration," The Institute for International Integration Studies Discussion Paper Series iiisdp069, IIIS.

    More about this item

    Keywords

    forecasts accuracy; fiscal revenues; VAR model; impulse-response function; forecast error;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions

    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:vls:finstu:v:18:y:2014:i:3:p:8-24. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/cfiarro.html .

    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: Daniel Mateescu (email available below). General contact details of provider: https://edirc.repec.org/data/cfiarro.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.