IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v132y2015icp129-132.html
   My bibliography  Save this article

Toward a more reliable picture of the economic activity: An application to Argentina

Author

Listed:
  • Camacho, Maximo
  • Dal Bianco, Marcos
  • Martinez-Martin, Jaime

Abstract

We advocate a dynamic factor model to provide alternative measures of output data using indirect information from economic indicators. We apply the method to show evidence of a significant gap between estimated and official measures of Argentine GDP since 2007.

Suggested Citation

  • Camacho, Maximo & Dal Bianco, Marcos & Martinez-Martin, Jaime, 2015. "Toward a more reliable picture of the economic activity: An application to Argentina," Economics Letters, Elsevier, vol. 132(C), pages 129-132.
    • Handle: RePEc:eee:ecolet:v:132:y:2015:i:c:p:129-132
    DOI: 10.1016/j.econlet.2015.03.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176515001330
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2015.03.032?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. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    2. Marcos Dal Bianco & Jaime Martinez-Martín & Maximo Camacho, 2013. "Short-Run Forecasting of Argentine GDP Growth," Working Papers 1314, BBVA Bank, Economic Research Department.
    3. Tomasz Kamil Michalski & Guillaume Stoltz, 2010. "Do countries falsify economic data strategically? Some evidence that they do," Post-Print hal-00543492, HAL.
    4. Rawski, Tom, 1993. "How fast has Chinese industry grown?," Policy Research Working Paper Series 1194, The World Bank.
    5. Tomasz Michalski & Gilles Stoltz, 2013. "Do Countries Falsify Economic Data Strategically? Some Evidence That They Might," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 591-616, May.
    6. Janet Koech & Jian Wang, 2012. "China's slowdown may be worse than official data suggest," Economic Letter, Federal Reserve Bank of Dallas, vol. 7(8), August.
    7. John G. Fernald & Israel Malkin & Mark M. Spiegel, 2013. "On the reliability of Chinese output figures," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue mar25.
    8. Ariel Coremberg, 2014. "Measuring Argentina’s GDP Growth," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 15(1), pages 1-32, January.
    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. Christian Glocker & Philipp Wegmueller, 2020. "Business cycle dating and forecasting with real-time Swiss GDP data," Empirical Economics, Springer, vol. 58(1), pages 73-105, January.
    2. Luciano Campos & Danilo Leiva-León & Steven Zapata- Álvarez, 2022. "Latin American Falls, Rebounds and Tail Risks," Borradores de Economia 1201, Banco de la Republica de Colombia.
    3. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    4. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2016. "Learning from Potentially-Biased Statistics: Household Inflation Perceptions and Expectations in Argentina," NBER Working Papers 22103, National Bureau of Economic Research, Inc.
    5. Wegmüller, Philipp & Glocker, Christian & Guggia, Valentino, 2023. "Weekly economic activity: Measurement and informational content," International Journal of Forecasting, Elsevier, vol. 39(1), pages 228-243.

    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. Holz, Carsten A., 2014. "The quality of China's GDP statistics," China Economic Review, Elsevier, vol. 30(C), pages 309-338.
    2. Zhang, Jin & Li, Pujiang & Zhao, Guochang, 2018. "Is power generation really the gold measure of the Chinese economy? A conceptual and empirical assessment," Energy Policy, Elsevier, vol. 121(C), pages 211-216.
    3. Banu Demir Pakel & Beata Smarzynska Javorcik & Beata Smarzynska Javorcik, 2018. "Forensics, Elasticities and Benford's Law," CESifo Working Paper Series 7266, CESifo.
    4. Dang, Canh Thien & Owens, Trudy, 2020. "Does transparency come at the cost of charitable services? Evidence from investigating British charities," Journal of Economic Behavior & Organization, Elsevier, vol. 172(C), pages 314-343.
    5. Thomas Stoerk, 2015. "Statistical corruption in Beijing’s air quality data has likely ended in 2012," GRI Working Papers 194, Grantham Research Institute on Climate Change and the Environment.
    6. Mukherjee, Abhiroop & Panayotov, George & Shon, Janghoon, 2021. "Eye in the sky: Private satellites and government macro data," Journal of Financial Economics, Elsevier, vol. 141(1), pages 234-254.
    7. Abel Rodríguez Tirado & Marcelo Delajara & Federico Hernández Álvarez, 2016. "Nowcasting Mexico’s Short-Term GDP Growth in Real-Time: A Factor Model versus Professional Forecasters," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Fall 2016), pages 167-182, October.
    8. Koch, Christoffer & Okamura, Ken, 2020. "Benford’s Law and COVID-19 reporting," Economics Letters, Elsevier, vol. 196(C).
    9. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2016. "Learning from Potentially Biased Statistics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(1 (Spring), pages 59-108.
    10. Ausloos, Marcel & Cerqueti, Roy & Mir, Tariq A., 2017. "Data science for assessing possible tax income manipulation: The case of Italy," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 238-256.
    11. Mir, T.A., 2014. "The Benford law behavior of the religious activity data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 1-9.
    12. Yi Chen & Ziying Fan & Xiaomin Gu & Li-An Zhou, 2020. "Arrival of Young Talent: The Send-Down Movement and Rural Education in China," American Economic Review, American Economic Association, vol. 110(11), pages 3393-3430, November.
    13. Vadim S. Balashov & Yuxing Yan & Xiaodi Zhu, 2020. "Who Manipulates Data During Pandemics? Evidence from Newcomb-Benford Law," Papers 2007.14841, arXiv.org, revised Jan 2021.
    14. Tomasz Michalski & Gilles Stoltz, 2013. "Do Countries Falsify Economic Data Strategically? Some Evidence That They Might," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 591-616, May.
    15. Abhiroop Mukherjee & George Panayotov & Janghoon Shon, 2019. "Eye in the sky: private satellites and government macro data," HKUST IEMS Working Paper Series 2019-68, HKUST Institute for Emerging Market Studies, revised Oct 2019.
    16. McDonald, Bruce D. III & Goodman, Christopher B, 2020. "The Truth about Honesty in the Nonprofit Sector," SocArXiv 48g5c, Center for Open Science.
    17. Riccioni, Jessica & Cerqueti, Roy, 2018. "Regular paths in financial markets: Investigating the Benford's law," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 186-194.
    18. Ronelle Burger & Canh Thien Dang & Trudy Owens, 2017. "Better performing NGOs do report more accurately: Evidence from investigating Ugandan NGO financial accounts," Discussion Papers 2017-10, University of Nottingham, CREDIT.
    19. Biswas, Amit K. & von Hagen, Jürgen & Sarkar, Sandip, 2022. "FDI Mismatch, trade Mis-reporting, and hidden capital Movements: The USA - China case," Journal of International Money and Finance, Elsevier, vol. 120(C).
    20. T. Mir, 2016. "The leading digit distribution of the worldwide illicit financial flows," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 271-281, January.

    More about this item

    Keywords

    Business cycles; Output growth; Dynamic factor models; Argentina;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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:eee:ecolet:v:132:y:2015:i:c:p:129-132. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.