IDEAS home Printed from https://ideas.repec.org/a/fau/fauart/v67y2017i1p2-14.html
   My bibliography  Save this article

What Determines the Current Account: Intratemporal versus Intertemporal Factors

Author

Listed:
  • Piotr Dybka

    (Warsaw School of Economics)

  • Michal Rubaszek

    (Warsaw School of Economics
    Narodowy Bank Polski)

Abstract

This paper adds to the discussion on the determinants of the current account balance. In particular, we construct a large balanced panel of data for 101 countries and 15 years covering observations for the current account and 18 explanatory variables. Next, we apply static and dynamic Bayesian Model Averaging techniques to verify whether intratemporal (i.e. relative demand and real exchange rates) or intertemporal factors (i.e. stage of development, fiscal balance, demographics) are crucial to understand current account developments. Our results indicate that the latter are key drivers of the external balance, which provides support for the intertemporal model of the current account.

Suggested Citation

  • Piotr Dybka & Michal Rubaszek, 2017. "What Determines the Current Account: Intratemporal versus Intertemporal Factors," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(1), pages 2-14, March.
    • Handle: RePEc:fau:fauart:v:67:y:2017:i:1:p:2-14
    as

    Download full text from publisher

    File URL: http://journal.fsv.cuni.cz/storage/1376_dybka_final_issue_01_2017.pdf
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Piotr Dybka & Bartosz Olesiński & Marek Rozkrut & Andrzej Torój, 2020. "Measuring the uncertainty of shadow economy estimates using Bayesian and frequentist model averaging," KAE Working Papers 2020-046, Warsaw School of Economics, Collegium of Economic Analysis.
    2. Piotr Dybka & Bartosz Olesiński & Marek Rozkrut & Andrzej Torój, 2023. "Measuring the model uncertainty of shadow economy estimates," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(4), pages 1069-1106, August.
    3. Beata Bierut & Piotr Dybka, 2019. "Institutional determinants of export competitiveness among the EU countries: evidence from Bayesian model averaging," NBP Working Papers 306, Narodowy Bank Polski.
    4. Dąbrowski, Marek A., 2021. "A novel approach to the estimation of an actively managed component of foreign exchange reserves," Economic Modelling, Elsevier, vol. 96(C), pages 83-95.
    5. Bierut, Beata K. & Dybka, Piotr, 2021. "Increase versus transformation of exports through technological and institutional innovation: Evidence from Bayesian model averaging," Economic Modelling, Elsevier, vol. 99(C).
    6. Karol Szafranek & Marek Kwas & Grzegorz Szafrański & Zuzanna Wośko, 2020. "Common Determinants of Credit Default Swap Premia in the North American Oil and Gas Industry. A Panel BMA Approach," Energies, MDPI, vol. 13(23), pages 1-23, November.
    7. Piotr Dybka, 2020. "One model or many? Exchange rates determinants and their predictive capabilities," KAE Working Papers 2020-053, Warsaw School of Economics, Collegium of Economic Analysis.

    More about this item

    Keywords

    current account; panel data; bayesian model averaging; intertemporal model;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • F32 - International Economics - - International Finance - - - Current Account Adjustment; Short-term Capital Movements
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics

    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:fau:fauart:v:67:y:2017:i:1:p:2-14. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Natalie Svarcova (email available below). General contact details of provider: https://edirc.repec.org/data/icunicz.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.