Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia
1 recurso en línea (páginas 35-62).
- Autores:
-
Talero Sarmiento, Leonardo Hernán
Lamos Díaz, Henry
Garavito Hernández, Edwin Alberto
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2019
- Institución:
- Universidad Pedagógica y Tecnológica de Colombia
- Repositorio:
- RiUPTC: Repositorio Institucional UPTC
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- spa
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- oai:repositorio.uptc.edu.co:001/2576
- Acceso en línea:
- http://repositorio.uptc.edu.co/handle/001/2576
- Palabra clave:
- Centros de acopio - Investigaciones
Mercadeo de productos agrícolas
Producción agropecuaria - Aspectos económicos - Colombia
Indicadores económicos
Precios agrícolas
Agricultura - Aspectos económicos
Prueba de hipótesis
Causalidad de Granger
Microeconomía
Precios agrícolas
- Rights
- openAccess
- License
- Copyright (c) 2019 Universidad Pedagógica y Tecnológica de Colombia
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Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia |
| dc.title.alternative.eng.fl_str_mv |
Testing the weak form of efficient market hypothesis and causality analysis in Colombian food supply centers Avaliação da hipótese da eficiência fraca do mercado e análise de causalidade em centros de abastecimento de comida da Colômbia |
| title |
Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia |
| spellingShingle |
Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia Centros de acopio - Investigaciones Mercadeo de productos agrícolas Producción agropecuaria - Aspectos económicos - Colombia Indicadores económicos Precios agrícolas Agricultura - Aspectos económicos Prueba de hipótesis Causalidad de Granger Microeconomía Precios agrícolas |
| title_short |
Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia |
| title_full |
Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia |
| title_fullStr |
Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia |
| title_full_unstemmed |
Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia |
| title_sort |
Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia |
| dc.creator.fl_str_mv |
Talero Sarmiento, Leonardo Hernán Lamos Díaz, Henry Garavito Hernández, Edwin Alberto |
| dc.contributor.author.none.fl_str_mv |
Talero Sarmiento, Leonardo Hernán Lamos Díaz, Henry Garavito Hernández, Edwin Alberto |
| dc.subject.armarc.none.fl_str_mv |
Centros de acopio - Investigaciones Mercadeo de productos agrícolas Producción agropecuaria - Aspectos económicos - Colombia Indicadores económicos Precios agrícolas Agricultura - Aspectos económicos |
| topic |
Centros de acopio - Investigaciones Mercadeo de productos agrícolas Producción agropecuaria - Aspectos económicos - Colombia Indicadores económicos Precios agrícolas Agricultura - Aspectos económicos Prueba de hipótesis Causalidad de Granger Microeconomía Precios agrícolas |
| dc.subject.proposal.spa.fl_str_mv |
Prueba de hipótesis Causalidad de Granger Microeconomía Precios agrícolas |
| description |
1 recurso en línea (páginas 35-62). |
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2019 |
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2019-05-10T20:05:41Z |
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2019-05-10T20:05:41Z |
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2019-02-07 |
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Artículo de revista |
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Talero Sarmiento, L. H., Lamos Díaz, H. & Garavito Hernández, E. A. (2019). Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia. Apuntes del CENES, 38(67), 35-62. DOI: https://doi.org/10.19053/01203053.v38.n67.2019.8040. http://repositorio.uptc.edu.co/handle/001/2576 |
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Electrónico 2256-5779 |
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0120-3053 |
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http://repositorio.uptc.edu.co/handle/001/2576 |
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10.19053/01203053.v38.n67.2019.8040 |
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Talero Sarmiento, L. H., Lamos Díaz, H. & Garavito Hernández, E. A. (2019). Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia. Apuntes del CENES, 38(67), 35-62. DOI: https://doi.org/10.19053/01203053.v38.n67.2019.8040. http://repositorio.uptc.edu.co/handle/001/2576 Electrónico 2256-5779 0120-3053 10.19053/01203053.v38.n67.2019.8040 |
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Bekkers, E., Brockmeier, M., Francois, J., & Yang, F. (2017). Local Food Prices and International Price Transmission. World Development, 96, 216–230. https://doi. org/10.1016/j.worlddev.2017.03.008 Benavides, G. (2004). Price Volatility Forecasts for Agricultural Commodities: An Application of Historical Volatility Models, Option Implieds and Composite Approaches for Futures Prices of Corn and Wheat. SSRN Electronic Journal, 3(2), 40–59. https://doi.org/10.2139/ssrn.611062 Bouri, E., Chang, T., & Gupta, R. (2017). Testing the Efficiency of the Wine Market Using Unit Root Tests with Sharp and Smooth Breaks. Wine Economics and Policy, 6(2), 80-87. https://doi.org/10.1016/j.wep.2017.06.001 Caeiro, F. & Mateus, A. (2014). Randtests: Testing Randomness in R. R Package Version, 1. Cárdenas, J. I. & Vallejo, L. E. (2016). Agricultura y desarrollo rural en Colombia 2011-2013: una aproximación. Apuntes del Cenes, 35(62), 87. https://doi. org/10.19053/22565779.4411 Coronado, S., Ramírez, M. & Celso, P. L. (2014). Inefficiency in the International Coffee Market: The Case of Colombian Arabica. African Journal of Agricultural Research, 9(5), 556–561. DeJong, D. N., Nankervis, J. C., Savin, N. E. & Whiteman, C. H. (1992). The Power Problems of Unit Root Test in Time Series with Autoregressive Errors. Journal of Econometrics, 53(1–3), 323–343. https://doi.org/10.1016/0304-4076(92)90090-E Departamento Administrativo Nacional de Estadística -DANE-. (2017). Cuentas trimestrales, Colombia. Producto interno bruto (PIB) Boletín técnico cuarto trimestre de 2016. Bogotá: DANE. Departamento Nacional de Planeación -DNP-. (2015). El campo colombiano: un camino hacia el bienestar y la paz. Misión para la transformación del campo. Recuperado de https://www.dnp.gov.co/programas/agricultura/Paginas/Informe-misi%- C3%B3n-FInal.aspx. Duarte-Duarte, J. B. & Mascareñas Pérez-Iñigo, J. M. (2014a). Comprobación de la eficiencia débil en los principales mercados financieros latinoamericanos. Estudios Gerenciales, 30(133), 365–375. https://doi.org/10.1016/j.estger.2014.05.005 Duarte-Duarte, J. B. & Mascareñas Pérez-Iñigo, J. M. M. (2014b). ¿Han sido los mercados bursátiles eficientes informacionalmente? Apuntes del Cenes, 33(57), 117. https://doi.org/10.19053/22565779.2906 Duarte-Duarte, J. B., Talero, L. H. & Sierra, K. J. (2017). Evaluation of the Effect of Investor Psychology on an Artificial Stock Market Through its Degree of Efficiency. Contaduría y Administración, 62(4), 1361–1376. https://doi.org/10.1016/j. cya.2017.06.014 Durbin, J. & Watson, G. S. (1951). Testing for Serial Correlation in Least Squares Regression. II. Biometrika, 38(1/2), 159. https://doi.org/10.2307/2332325 Fama, E. F. (1965). The Behavior of Stock-Market Prices. The Journal of Business, 38(1), 34. https://doi.org/10.1086/294743 Fama, E. F. (1991). Efficient Capital Markets: II. The Journal of Finance, 46(5), 1575– 1617. https://doi.org/10.1111/j.1540-6261.1991.tb04636.x Food and Agriculture Organization of the United Nations FAO. (2011). Food Price Volatility and the Right to Food. Rome: FAO. Geary, R. C. (1935). The Ratio of the Mean Deviation to the Standard Deviation as a Test of Normality. Biometrika, 27(3–4), 310–332. https://doi.org/10.1093/ biomet/27.3-4.310 Gómez, H. J. (2011). Política comercial y de competitividad del sector agrícola en Colombia. En Cuadernos Fedesarrollo (ed.), La política comercial del sector agrícola en Colombia (pp. 6–20). Bogotá: Cuadernos Fedesarrollo. Granger, C. W. J. (1986). Developments in the Study of Cointegrated Economic Variables. Oxford Bulletin of Economics and Statistics, 48(3), 213–228. https://doi. org/10.1111/j.1468-0084.1986.mp48003002.x Grossman, S. J. & Stiglitz, J. E. (1980). On the Impossibility of Informationally Efficient Markets. The American Economic Review, 70(3), 393–408. Retrieved from www. jstor.org/stable/1805228. Gujarati, D. N. & Porter, D. C. (2010). Econometría. México: McGraw-Hill. Hassan, A., Abdullah, M. S. & Shah, Z. A. (2007). Testing of Random Walks and market efficiency in an emerging market: An empirical analysis of Karachi Stock Exchange. The Business Review, Cambridge, 9(1), 271–280. Karali, B., & Power, G. J. (2013). Short- and Long-Run Determinants of Commodity Price Volatility. American Journal of Agricultural Economics, 95(3), 724–738. https://doi.org/10.1093/ajae/aas122 Lachman, J. & Jack, P. (2017). Study of Efficiency and Information Transmission for Agricultural Futures Markets: A Comparative Analysis between Buenos Aires and Chicago Using Monthly and Daily Data. Estudios Economicos, 34(69), 3–23. Levy, R. A. (1967). The Theory of Random Walks: A Survey of Findings. The American Economist, 11(2), 34–48. https://doi.org/10.1177/056943456701100205 Lo, A. W. (1991). Long-Term Memory in Stock Market Prices. Econometrica, 59(5), 1279–1313. https://doi.org/10.2307/2938368 Lo, A. W. (2005). Reconciling Efficient Market with Behavioral Finance: The Adaptative Markets Hypothesis. The Journal of Investment Consulting, 7(2), 1–25. https:// doi.org/10.2139/ssrn.728864 Malkiel, B. G. (2003). The Efficient Market Hypothesis and Its Critics. Journal of Economic Perspectives, 17(1), 59–82. https://doi.org/10.1257/089533003321164958 Minot, N. (2014). Food Price Volatility in Sub-Saharan Africa: Has it Really Increased? Food Policy, 45, 45–56. https://doi.org/10.1016/j.foodpol.2013.12.008 Nisar, S. & Hanif, M. (2012). Testing Weak Form of Efficient Market Hypothesis: Empirical Evidence from South-Asia. World Applied Sciences Journal, 17(4), 414–427. https://doi.org/10.3968/5524 Peters, E. E. (2015). Fractal Market Analysis: Applying Chaos Theory to Investment and Economics. Wiley Finance Editions. Retrieved from https://books.google.com.co/books?hl=es&lr=&id=_bkoySKyc_cC&oi=fnd&pg=PA3&dq=(Fractal+Market+ Analysis:+Applying+Chaos+Theory+to+Investment+and+Economics&ots=s- NzltsZ0IO&sig=cnQpI_4F5zlD5blbhNH9omRATmo%5Cnhttp://www.loc.gov/ catdir/description/wiley037/93028 Pfaff, B. (2008). Analysis of Integrated Series with R and Cointegrated Time. Use R! New York: Springer. Resta, M. (2012). Hurst Exponent and its Applications in Time-series Analysis. Recent Patents on Computer Science, 5(3), 211–219. https://doi. org/10.2174/2213275911205030211 Ruiz-Porras, A. & Ruiz-Robles, B. (2015). La hipótesis de eficiencia y la modelación de series bursátiles mexicanas: un análisis multivariado. Economía Informa, 390, 28–57. https://doi.org/10.1016/S0185-0849(15)30003-7 Savin, N. E. & White, K. J. (1977). The Durbin-Watson Test for Serial Correlation with Extreme Sample Sizes or Many Regressors. Econometrica, 45(8), 1989. https:// doi.org/10.2307/1914122 Talero, L. H., Duarte, J. B. & Garcés, L. D. (2017). La complejidad del mercado bursátil latinoamericano a partir de un modelo autómata celular conductual. Apuntes del Cenes, 36(64), 199–223. https://doi.org/10.19053/01203053.v36.n64.2017.5421 Tansuchat, R., Chang, C. & McAleer, M. (2009). Modelling Long Memory Volatility in Agricultural Commodity Futures Returns. https://doi.org/10.2139/ssrn.1491890 Tejeda, H. A. & Goodwin, B. K. (2009). Price Volatility, Nonlinearity, and Asymmetric Adjustments in Corn, Soybean, and Cattle Markets: Implications of Ethanol-Driven (Market) Shocks. In 2009 Conference, April 20-21, 2009, St. Louis, Missouri. Tillman, J. A. (1975). The Power of the Durbin-Watson Test. Econometrica, 43(5/6), 959. https://doi.org/10.2307/1911337 Toth, A., Rendall, S., & Reitsma, F. (2016). Resilient Food Systems: A Qualitative Tool for Measuring Food Resilience. Urban Ecosystems, 19(1), 19–43. https://doi. org/10.1007/s11252-015-0489-x Velásquez, J. D. & Aldana, M. A. (2007). Modelado del precio del café colombiano en la bolsa de Nueva York usando redes neuronales artificiales. Recuperado de http:// www.scielo.org.co/pdf/rfnam/v60n2/a16v60n2.pdf Zeileis, A., & Hothorn, T. (2002). Diagnostic Checking in Regression Relationships. R. News, 2(3), 7-10. |
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Talero Sarmiento, Leonardo HernánLamos Díaz, HenryGaravito Hernández, Edwin Alberto2019-05-10T20:05:41Z2019-05-10T20:05:41Z2019-02-07Talero Sarmiento, L. H., Lamos Díaz, H. & Garavito Hernández, E. A. (2019). Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de Colombia. Apuntes del CENES, 38(67), 35-62. DOI: https://doi.org/10.19053/01203053.v38.n67.2019.8040. http://repositorio.uptc.edu.co/handle/001/2576Electrónico 2256-57790120-3053http://repositorio.uptc.edu.co/handle/001/257610.19053/01203053.v38.n67.2019.80401 recurso en línea (páginas 35-62).Na Colômbia, existem centros de coleta tradicionais, onde os produtos agrícolas são comercializados e distribuídos, o preço de venda desses produtos é publicado por instituições governamentais em relatórios semanais. Para determinar se as séries de preços seguem um passeio aleatório e se existem relações entre os centros, são aplicados seis testes que avaliam a hipótese de eficiência fraca e o teste de causalidade de Granger. Para tanto, é analizado o preço semanal histórico de vinte e oito produtos agrícolas comercializados em seis mercados, durante a primeira semana de 2013 até a última semana de 2017. Os principais resultados indicam que os mercados tendem para a eficiência, embora não tenham o mesmo nível porquanto a eficiência varia de acordo com o produto que é comercializado. Além disso, os centros de Manizales, Barranquilla e Villavicencio influenciam os preços dos mercados de Bogotá, Bucaramanga e Medellín.In Colombia, there are traditional food supply centers to trade agricultural products. Government institutions publish sale prices of these products in weekly reports. In order to determine the random characteristics of these price series and if there are relationships between the centers, we use a battery of six different tests to examine the weak form of efficient market hypothesis and the Granger causality test. For this, this work collected the historical weekly price of 28 agricultural products, taking into account six markets, during the first week of 2013 to the last week of 2017. The main results indicate that markets tend towards efficiency, however, the efficiency depends on the product traded. In addition, the centers in Manizales, Barranquilla and Villavicencio influence the prices of the Bogotá, Bucaramanga and Medellín markets.En Colombia existen centros tradicionales de acopio donde se comercializan y distribuyen productos agrícolas. El precio de venta de estos productos es publicado por instituciones del Gobierno en informes semanales. Con el objetivo de determinar si las series de precios siguen una caminata aleatoria y si existen relaciones entre los centros, se aplican seis pruebas que evalúan la hipótesis de eficiencia débil y la prueba de causalidad de Granger. Para ello se analiza el precio histórico semanal de 28 productos agrícolas comercializados en seis mercados, durante la primera semana de 2013 a la última de 2017. Los principales resultados indican que los mercados tienden a la eficiencia, aunque no tienen el mismo nivel, ya que esta varía según el producto que se comercialice. Además, los centros en Manizales, Barranquilla y Villavicencio influyen sobre los precios de los mercados de Bogotá, Bucaramanga y Medellín.Bibliografía y webgrafía: páginas 59-62.Código de Clasificación de Journal of Economic Literature (JEL) :C12, D4, D40, G14, Q13.application/pdfspaUniversidad Pedagógica y Tecnológica de ColombiaCopyright (c) 2019 Universidad Pedagógica y Tecnológica de Colombiahttps://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)http://purl.org/coar/access_right/c_abf2https://revistas.uptc.edu.co/index.php/cenes/article/view/8040/7610Evaluación de la hipótesis de eficiencia débil y análisis de causalidad en las centrales de abastos de ColombiaTesting the weak form of efficient market hypothesis and causality analysis in Colombian food supply centersAvaliação da hipótese da eficiência fraca do mercado e análise de causalidade em centros de abastecimento de comida da ColômbiaArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionTexthttps://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85Bekkers, E., Brockmeier, M., Francois, J., & Yang, F. (2017). Local Food Prices and International Price Transmission. World Development, 96, 216–230. https://doi. org/10.1016/j.worlddev.2017.03.008Benavides, G. (2004). Price Volatility Forecasts for Agricultural Commodities: An Application of Historical Volatility Models, Option Implieds and Composite Approaches for Futures Prices of Corn and Wheat. SSRN Electronic Journal, 3(2), 40–59. https://doi.org/10.2139/ssrn.611062Bouri, E., Chang, T., & Gupta, R. (2017). Testing the Efficiency of the Wine Market Using Unit Root Tests with Sharp and Smooth Breaks. Wine Economics and Policy, 6(2), 80-87. https://doi.org/10.1016/j.wep.2017.06.001Caeiro, F. & Mateus, A. (2014). Randtests: Testing Randomness in R. R Package Version, 1.Cárdenas, J. I. & Vallejo, L. E. (2016). Agricultura y desarrollo rural en Colombia 2011-2013: una aproximación. Apuntes del Cenes, 35(62), 87. https://doi. org/10.19053/22565779.4411Coronado, S., Ramírez, M. & Celso, P. L. (2014). 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Modelado del precio del café colombiano en la bolsa de Nueva York usando redes neuronales artificiales. Recuperado de http:// www.scielo.org.co/pdf/rfnam/v60n2/a16v60n2.pdfZeileis, A., & Hothorn, T. (2002). Diagnostic Checking in Regression Relationships. R. 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