IDEAS home Printed from https://ideas.repec.org/p/adv/wpaper/202408.html
   My bibliography  Save this paper

Rastreando la trayectoria de los precios de la quinua en Bolivia: Quiebres estructurales y persistencia de choques

Author

Listed:
  • Javier Aliaga Lordemann

    (Investigador Asociado de INESAD)

  • Ignacio Garrón Vedia

    (Investigador invitado de INESAD)

  • María Cecilia Lenis Abastoflor

    (Investigadora Junior de INESAD)

Abstract

La quinua ha experimentado una notable transformación en las últimas décadas, consolidándose como un pilar fundamental para las comunidades agrícolas andinas y emergiendo como un actor prominente en el mercado global de los súper alimentos. Sin embargo, los precios de este grano han mostrado una dinámica compleja, con grandes fluctuaciones que han impactado directamente sobre los ingresos de los pequeños productores. Esta investigación tiene como objetivo analizar la dinámica del precio de la quinua en Bolivia identificando los principales eventos y factores que han generado quiebres estructurales en su tendencia, así como también identificando la persistencia de los choques a lo largo del tiempo. Se empleó un enfoque que combina, por un lado, el análisis de quiebres estructurales por medio del contraste de Bai y Perron, y también está la estimación de la memoria larga a través del estimador 2ELW. Adicionalmente, se evaluó la influencia de variables exógenas que afectan sobre los precios. Para ello se contempló el índice de actividad mundial de materias primas, el índice oceánico de El Niño y la producción mundial de la quinua. Los hallazgos revelan múltiples quiebres estructurales en la serie de precios de la quinua que se relacionan con ciertos eventos clave. Por ejemplo, están los cambios en la investigación y el desarrollo, el auge de la producción y la comercialización, y el impulso de las iniciativas gubernamentales y de la cooperación internacional. Estos quiebres también se asocian a distintos grados de persistencia de los choques en cada régimen identificado. Si bien las variables exógenas no muestran efectos significativos a corto plazo, se reconoce que podrían tener una influencia relevante en diferentes periodos. Este estudio demuestra la complejidad en la dinámica de los precios de la quinua en Bolivia, que está caracterizada por múltiples quiebres estructurales. Para aprovechar las oportunidades en este mercado, los productores y formuladores de políticas deben implementar estrategias flexibles y de monitoreo constante de la evolución del sector, tomando en cuenta los factores clave que han impulsado los cambios en la tendencia de precios a lo largo del tiempo.

Suggested Citation

  • Javier Aliaga Lordemann & Ignacio Garrón Vedia & María Cecilia Lenis Abastoflor, 2024. "Rastreando la trayectoria de los precios de la quinua en Bolivia: Quiebres estructurales y persistencia de choques," Development Research Working Paper Series 08/2024, Institute for Advanced Development Studies.
  • Handle: RePEc:adv:wpaper:202408
    as

    Download full text from publisher

    File URL: http://www.inesad.edu.bo/pdf/wp2024/wp08_2024.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    2. Shimotsu, Katsumi, 2010. "Exact Local Whittle Estimation Of Fractional Integration With Unknown Mean And Time Trend," Econometric Theory, Cambridge University Press, vol. 26(2), pages 501-540, April.
    3. Zeileis, Achim & Leisch, Friedrich & Hornik, Kurt & Kleiber, Christian, 2002. "strucchange: An R Package for Testing for Structural Change in Linear Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i02).
    4. Bellemare, Marc F. & Fajardo-Gonzalez, Johanna & Gitter, Seth R., 2018. "Foods and fads: The welfare impacts of rising quinoa prices in Peru," World Development, Elsevier, vol. 112(C), pages 163-179.
    5. Jushan Bai & Pierre Perron, 2003. "Critical values for multiple structural change tests," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 72-78, June.
    6. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    7. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    8. Stevens, Andrew W., 2017. "Quinoa quandary: Cultural tastes and nutrition in Peru," Food Policy, Elsevier, vol. 71(C), pages 132-142.
    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. Javier Aliaga Lordemann & Ignacio Garrón Vedia & María Cecilia Lenis Abastoflor, 2024. "Tracking the trend of quinoa price in Bolivia: Structural breaks and persistence of shoks," Development Research Working Paper Series 10/2024, Institute for Advanced Development Studies.
    2. Al-Shboul, Mohammad & Alsharari, Nizar, 2019. "The dynamic behavior of evolving efficiency: Evidence from the UAE stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 119-135.
    3. Gatfaoui, Hayette, 2016. "Linking the gas and oil markets with the stock market: Investigating the U.S. relationship," Energy Economics, Elsevier, vol. 53(C), pages 5-16.
    4. Yannick Le Pen & Benoît Sévi, 2013. "Futures Trading and the Excess Comovement of Commodity Prices," Working Papers halshs-00793724, HAL.
    5. Yazgan, M. Ege & Özkan, Harun, 2015. "Detecting structural changes using wavelets," Finance Research Letters, Elsevier, vol. 12(C), pages 23-37.
    6. repec:ipg:wpaper:19 is not listed on IDEAS
    7. Chevallier, Julien, 2011. "Evaluating the carbon-macroeconomy relationship: Evidence from threshold vector error-correction and Markov-switching VAR models," Economic Modelling, Elsevier, vol. 28(6), pages 2634-2656.
    8. Jerry Coakley & Jian Dollery & Neil Kellard, 2011. "Long memory and structural breaks in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(11), pages 1076-1113, November.
    9. Fantazzini, Dean & Shangina, Tamara, 2019. "The importance of being informed: forecasting market risk measures for the Russian RTS index future using online data and implied volatility over two decades," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 5-31.
    10. repec:dau:papers:123456789/11382 is not listed on IDEAS
    11. repec:ipg:wpaper:2013-019 is not listed on IDEAS
    12. Erdenebat Bataa & Denise R. Osborn & Marianne Sensier & Dick van Dijk, 2014. "Identifying Changes in Mean, Seasonality, Persistence and Volatility for G7 and Euro Area Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(3), pages 360-388, June.
    13. Camilo Alberto Cárdenas-Hurtado & María Alejandra Hernández-Montes, 2019. "Understanding the Consumer Confidence Index in Colombia: A structural FAVAR analysis," Borradores de Economia 1063, Banco de la Republica de Colombia.
    14. Kumar, Nikeel Nishkar & Patel, Arvind, 2023. "Nonlinear effect of air travel tourism demand on economic growth in Fiji," Journal of Air Transport Management, Elsevier, vol. 109(C).
    15. Peter Lildholdt & Anne Vila-Wetherilt, 2004. "Anticipation Of Monetary Policy In UK Financial Markets," Royal Economic Society Annual Conference 2004 20, Royal Economic Society.
    16. Karakotsios, Achillefs & Katrakilidis, Constantinos & Kroupis, Nikolaos, 2021. "The dynamic linkages between food prices and oil prices. Does asymmetry matter?," The Journal of Economic Asymmetries, Elsevier, vol. 23(C).
    17. Umar, Muhammad & Su, Chi-Wei & Rizvi, Syed Kumail Abbas & Lobonţ, Oana-Ramona, 2021. "Driven by fundamentals or exploded by emotions: Detecting bubbles in oil prices," Energy, Elsevier, vol. 231(C).
    18. Bertrand Groslambert & Raphaël Chiappini & Olivier Bruno, 2015. "Bank Output Calculation in the Case of France: What Do New Methods Tell About the Financial Intermediation Services in the Aftermath of the Crisis?," GREDEG Working Papers 2015-32, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    19. Mishra, Brajesh & Ghosh, Sajal & Kanjilal, Kakali, 2020. "Evaluation of import substitution strategy in Indian telecom sector: Empirical evidence of non-linear dynamics," Telecommunications Policy, Elsevier, vol. 44(7).
    20. Oscar Bajo-Rubio, 2022. "Exports and long-run growth: The case of Spain, 1850-2020," Journal of Applied Economics, Taylor & Francis Journals, vol. 25(1), pages 1314-1337, December.
    21. Bajo-Rubio, Oscar & Diaz-Roldan, Carmen & Esteve, Vicente, 2007. "Change of regime and Phillips curve stability: The case of Spain, 1964-2002," Journal of Policy Modeling, Elsevier, vol. 29(3), pages 453-462.
    22. Vicente Esteve, 2004. "Política fiscal y productividad del trabajo en la economía española: un análisis de series temporales," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 19(1), pages 3-29, June.
    23. WenShwo Fang & Stephen M. Miller & ChunShen Lee, 2008. "The Great Moderation Flattens Fat Tails: Disappearing Leptokurtosis," Working papers 2008-48, University of Connecticut, Department of Economics.

    More about this item

    Keywords

    Quinua; precios; quiebres estructurales; memoria larga; dinámica de mercado; región andina.;
    All these keywords.

    JEL classification:

    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q17 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agriculture in International Trade
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:adv:wpaper:202408. 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: Lykke Andersen (email available below). General contact details of provider: https://edirc.repec.org/data/inesabo.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.