Relationship between the consumer price index and the producer price index for six south american countries
1 recurso en línea (páginas 39-74).
- Autores:
-
Cerquera Losada, Oscar Hernán
Murcia Arias, Juan Pablo
Conde Guzmán, Jonás
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2018
- Institución:
- Universidad Pedagógica y Tecnológica de Colombia
- Repositorio:
- RiUPTC: Repositorio Institucional UPTC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uptc.edu.co:001/2359
- Acceso en línea:
- http://repositorio.uptc.edu.co/handle/001/2359
- Palabra clave:
- Indice de precios
Números índices (Economía)
Análisis de regresión
Análisis de covarianza
Modelo de vectores autorregresivos.
Modelo de vectores de corrección de error.
Raíz unitaria.
Cointegración.
Causalidad.
- Rights
- openAccess
- License
- Copyright (c) 2018 Universidad Pedagógica y Tecnológica de Colombia
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Relationship between the consumer price index and the producer price index for six south american countries |
| dc.title.alternative.eng.fl_str_mv |
Relação entre o índice de preços ao consumidor e índice de preços ao produtor por seis países sul-americanos |
| title |
Relationship between the consumer price index and the producer price index for six south american countries |
| spellingShingle |
Relationship between the consumer price index and the producer price index for six south american countries Indice de precios Números índices (Economía) Análisis de regresión Análisis de covarianza Modelo de vectores autorregresivos. Modelo de vectores de corrección de error. Raíz unitaria. Cointegración. Causalidad. |
| title_short |
Relationship between the consumer price index and the producer price index for six south american countries |
| title_full |
Relationship between the consumer price index and the producer price index for six south american countries |
| title_fullStr |
Relationship between the consumer price index and the producer price index for six south american countries |
| title_full_unstemmed |
Relationship between the consumer price index and the producer price index for six south american countries |
| title_sort |
Relationship between the consumer price index and the producer price index for six south american countries |
| dc.creator.fl_str_mv |
Cerquera Losada, Oscar Hernán Murcia Arias, Juan Pablo Conde Guzmán, Jonás |
| dc.contributor.author.none.fl_str_mv |
Cerquera Losada, Oscar Hernán Murcia Arias, Juan Pablo Conde Guzmán, Jonás |
| dc.subject.armarc.none.fl_str_mv |
Indice de precios Números índices (Economía) Análisis de regresión Análisis de covarianza |
| topic |
Indice de precios Números índices (Economía) Análisis de regresión Análisis de covarianza Modelo de vectores autorregresivos. Modelo de vectores de corrección de error. Raíz unitaria. Cointegración. Causalidad. |
| dc.subject.proposal.spa.fl_str_mv |
Modelo de vectores autorregresivos. Modelo de vectores de corrección de error. Raíz unitaria. Cointegración. Causalidad. |
| description |
1 recurso en línea (páginas 39-74). |
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2018 |
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2018-06-25 |
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2019-01-31T15:43:10Z |
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2019-01-31T15:43:10Z |
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Cerquera Losada, O. H., Murcia Arias, J. P. & Conde Guzmán, J. (2018). Relationship between the consumer price index and the producer price index for six south american countries. Apuntes del CENES, 37(66), 39-74. DOI: https://doi.org/10.19053/01203053.v37.n66.2019.6601. http://repositorio.uptc.edu.co/handle/001/2359 |
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Electrónico 2256-5779 |
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http://repositorio.uptc.edu.co/handle/001/2359 |
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10.19053/01203053.v37.n66.2019.6601 |
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Cerquera Losada, O. H., Murcia Arias, J. P. & Conde Guzmán, J. (2018). Relationship between the consumer price index and the producer price index for six south american countries. Apuntes del CENES, 37(66), 39-74. DOI: https://doi.org/10.19053/01203053.v37.n66.2019.6601. http://repositorio.uptc.edu.co/handle/001/2359 Electrónico 2256-5779 10.19053/01203053.v37.n66.2019.6601 |
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eng |
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eng |
| dc.relation.references.spa.fl_str_mv |
Banco Central do Brasil. (2016). Relatório de Inflação, 8(4). Bonilla, C. (2011). Economic Structure and Unemployment in Colombia: A VEC Analysis. Sociedad y Economía, (20), 99-124. Bryan, F., Cecchetti, S. G. & Wiggins, R. (2011). Efficient Inflation Estimation. NBER Working Paper, (6183). Campos, C. & Jalil, M. (2000). Relación entre el índice de precios del productor (IPP) y el índice de precios al consumidor (IPC). Bogotá: Subgerencia de Estudios Económicos, Banco de la República. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of the American Statistical Association, 74(366), 427-431. https://doi.org/10.1080/01621459.1979.10482531 https://doi.org/10.1080/01621459.1979.10482531 Espinosa, O. A. & Vaca, P. A. (2015). The Influence of Financial, Fiscal and External Sectors in the Colombian Economy: A Bayesian VAR Approach. Desarrollo y Sociedad, (75), 11-49. Frimpong, J. M. & Oteng-Abayie, E. F. (2008). Bivariate Causality Analysis between FDI Inflows and Economic Growth in Ghana. International Research Journal of Finance & Economics, 15, 1-20 Granger, C. W. (1969). Investigaring Causal Relations by Econometric Model and Cross-spectral Method. Econometrica, 37(3), 424-438. https://doi. org/10.2307/1912791 https://doi.org/10.2307/1912791 Hakimipoor, N. (2016). Investigation on Causality Relationship between Consumer Price Index and Producer Price Index in Iran. Iran: Hikari. Johansen, S., & Juselius, K., (1990). Maximum Likelihood Estimation and Inference on Cointegration– with Applications to the Demand for Money. Oxford Bulletin of Economics and Statistics, 52(2), 169–210. Loría, D. (2007). Econometría con aplicaciones. México: Pearson Addison-Wesley Editor Lütkepohl, H. (2004). Forecasting with VARMA Models. Economics Working Papers ECO2004/25. Florence, Italy: European University Institute. Martínez, W., Caicedo, E. & Tique, E. (2012). Explorando la relación entre el IPC e IPP: el caso colombiano. Bogotá: Borradores de Economía, Banco de la República Mel, L. T. (2011). The Relationship Between Consumer Price Index (CPI) and Producer Price Index (PPI) in Malaysia. Masters thesis. Universiti Malaysia Sarawak, UNIMAS. OECD. (2017, April). Data.OECD. Retrieved from https://data.oecd.org/price/producer-price-indices-ppi.htm Schwarz, G. (1978). Estimating the Dimension of a Model. The Annals of Statistics, 6(2), 461-464. Selçuk A. (2011). The Causal Relationship between Producer Price Index and Consumer Price Index: Empirical Evidence from Selected European Countries. International Journal of Economics and Finance, 3(6), 227-232. Sims, C. (1972). Money, Income, and Causality. American Economic Review, 62(4), 540-552. Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48. https:// doi.org/10.2307/1912017 https://doi.org/10.2307/1912017 Toda, H. Y. & Tamamoto, T. (1995). Statistical Inference in Vector Autoregressions with Possibly Integrated Processes. Journal of Econometrics, 66, 225-250. |
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Apuntes del CENES;Volumen 37, número 66 (Julio-Diciembre 2018) |
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Copyright (c) 2018 Universidad Pedagógica y Tecnológica de Colombia |
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Cerquera Losada, Oscar HernánMurcia Arias, Juan PabloConde Guzmán, Jonás2019-01-31T15:43:10Z2019-01-31T15:43:10Z2018-06-25Cerquera Losada, O. H., Murcia Arias, J. P. & Conde Guzmán, J. (2018). Relationship between the consumer price index and the producer price index for six south american countries. Apuntes del CENES, 37(66), 39-74. DOI: https://doi.org/10.19053/01203053.v37.n66.2019.6601. http://repositorio.uptc.edu.co/handle/001/2359Electrónico 2256-5779http://repositorio.uptc.edu.co/handle/001/235910.19053/01203053.v37.n66.2019.66011 recurso en línea (páginas 39-74).Este trabajo analiza la relación entre el índice de precios al consumidor y el índice de precios al productor para seis países de Suramérica: Brasil, Colombia, Ecuador, Perú, Paraguay y Uruguay. Para determinar esta relación se estimaron modelos de vectores autorregresivos y modelos de vectores de corrección de error. Además se hizo el análisis de impulso respuesta, y se desarrolló la prueba de causalidad de Toda y Yamamoto. La periodicidad de los datos es anual, y el periodo de tiempo varía para cada país, debido a la disponibilidad de la información. De acuerdo con las características de las variables, se estimaron tres modelos VAR y tres modelos VEC. A pesar de esto, se observa que ambos indicadores muestran sensibilidad a los shocks repentinos, tanto en sí mismos como en la otra variable, efecto que varía según las características de cada país. En Brasil, Colombia, Ecuador y Uruguay no se presenta causalidad entre las dos variables, caso contrario al de Perú y Paraguay.This paper analyzes the relationship between the consumer price index and the producer price index for six countries in South America: Brazil, Colombia, Ecuador, Peru, Paraguay and Uruguay. To determine this relationship autoregressive vector models and error correction vector models were estimated. In addition, the impulse response analysis was performed, and the Toda and Yamamoto causality test was applied. The data’s periodicity is annual, and the period of time varies for each country, due to the availability of information. According to the characteristics of the variables, three VAR models and three VEC models were estimated. Despite this, it is observed that both indicators show sensitivity to sudden shocks both in themselves as in the other variable, effect that varies according to the characteristics of each country. In Brazil, Colombia, Ecuador and Uruguay, there is no causality between the two variables, contrary to Peru and Paraguay.Este artigo analisa a relação entre o índice de preços índice de preços ao consumidor e produtor por seis países da América do Sul, Brasil, Colômbia, Equador, Peru, Paraguai e Uruguai. Para determinar esse vetor relacionamento modelos Autorregressivos e modelos vetores de correção de erros foram estimados. Além disso, a análise de resposta de impulso foi realizado, e teste de causalidade Toda e Yamamoto desenvolvido. A periodicidade dos dados é anual, e o período de tempo varia para cada país, devido à disponibilidade das informações. De acordo com as características das variáveis, foram estimados três modelos VAR e três modelos VEC. Apesar disso, observa-se que ambos os indicadores apresentam sensibilidade a choques repentinos tanto em si quanto na outra variável, efeito que varia de acordo com as características de cada país. No Brasil, Colômbia, Equador e Uruguai não há causalidade entre as duas variáveis, ao contrário do Peru e do Paraguai.Bibliografía y webgrafía: páginas 67-68.Artículo de investigaciónCódigo de clasificación de Journal of Economic Literature (JEL): B23, C01, C3, C52, E31.application/pdfengUniversidad Pedagógica y Tecnológica de ColombiaCopyright (c) 2018 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/6601/7252Relationship between the consumer price index and the producer price index for six south american countriesRelação entre o índice de preços ao consumidor e índice de preços ao produtor por seis países sul-americanosArtículo 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_970fb48d4fbd8a85Banco Central do Brasil. (2016). Relatório de Inflação, 8(4).Bonilla, C. (2011). Economic Structure and Unemployment in Colombia: A VEC Analysis. Sociedad y Economía, (20), 99-124.Bryan, F., Cecchetti, S. G. & Wiggins, R. (2011). Efficient Inflation Estimation. NBER Working Paper, (6183).Campos, C. & Jalil, M. (2000). Relación entre el índice de precios del productor (IPP) y el índice de precios al consumidor (IPC). Bogotá: Subgerencia de Estudios Económicos, Banco de la República.Dickey, D. A., & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of the American Statistical Association, 74(366), 427-431. https://doi.org/10.1080/01621459.1979.10482531 https://doi.org/10.1080/01621459.1979.10482531Espinosa, O. A. & Vaca, P. A. (2015). The Influence of Financial, Fiscal and External Sectors in the Colombian Economy: A Bayesian VAR Approach. Desarrollo y Sociedad, (75), 11-49.Frimpong, J. M. & Oteng-Abayie, E. F. (2008). Bivariate Causality Analysis between FDI Inflows and Economic Growth in Ghana. International Research Journal of Finance & Economics, 15, 1-20Granger, C. W. (1969). Investigaring Causal Relations by Econometric Model and Cross-spectral Method. Econometrica, 37(3), 424-438. https://doi. org/10.2307/1912791 https://doi.org/10.2307/1912791Hakimipoor, N. (2016). Investigation on Causality Relationship between Consumer Price Index and Producer Price Index in Iran. Iran: Hikari.Johansen, S., & Juselius, K., (1990). Maximum Likelihood Estimation and Inference on Cointegration– with Applications to the Demand for Money. Oxford Bulletin of Economics and Statistics, 52(2), 169–210.Loría, D. (2007). Econometría con aplicaciones. México: Pearson Addison-Wesley EditorLütkepohl, H. (2004). Forecasting with VARMA Models. Economics Working Papers ECO2004/25. Florence, Italy: European University Institute.Martínez, W., Caicedo, E. & Tique, E. (2012). Explorando la relación entre el IPC e IPP: el caso colombiano. Bogotá: Borradores de Economía, Banco de la RepúblicaMel, L. T. (2011). The Relationship Between Consumer Price Index (CPI) and Producer Price Index (PPI) in Malaysia. Masters thesis. Universiti Malaysia Sarawak, UNIMAS.OECD. (2017, April). Data.OECD. Retrieved from https://data.oecd.org/price/producer-price-indices-ppi.htmSchwarz, G. (1978). Estimating the Dimension of a Model. The Annals of Statistics, 6(2), 461-464.Selçuk A. (2011). The Causal Relationship between Producer Price Index and Consumer Price Index: Empirical Evidence from Selected European Countries. International Journal of Economics and Finance, 3(6), 227-232.Sims, C. (1972). Money, Income, and Causality. American Economic Review, 62(4), 540-552.Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1-48. https:// doi.org/10.2307/1912017 https://doi.org/10.2307/1912017Toda, H. Y. & Tamamoto, T. (1995). Statistical Inference in Vector Autoregressions with Possibly Integrated Processes. Journal of Econometrics, 66, 225-250.Apuntes del CENES;Volumen 37, número 66 (Julio-Diciembre 2018)Indice de preciosNúmeros índices (Economía)Análisis de regresiónAnálisis de covarianzaModelo de vectores autorregresivos.Modelo de vectores de corrección de error.Raíz unitaria.Cointegración.Causalidad.ORIGINALPPS_982_Relationship_between_consumer.pdfPPS_982_Relationship_between_consumer.pdfArchivo principalapplication/pdf1522017https://repositorio.uptc.edu.co/bitstreams/2a8ccd02-a90a-4842-91d4-dc1a17266583/downloaddd173b4266a14c90e735bf2b3df22e38MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-814798https://repositorio.uptc.edu.co/bitstreams/b45cfb8f-fa00-43dc-ac9e-1c5a4d3067bf/download88794144ff048353b359a3174871b0d5MD52TEXTPPS-982.pdf.txtPPS-982.pdf.txtExtracted 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BlbCBub21icmUgZGUgbGEgcGFydGUgbyBsYXMgcGFydGVzIHF1ZSBlbCBBdXRvciBPcmlnaW5hbCB5L28gZWwgTGljZW5jaWFudGUgaHViaWVyZW4gZGVzaWduYWRvIHBhcmEgbGEgYXRyaWJ1Y2nDs24gKHYuZy4sIHVuIGluc3RpdHV0byBwYXRyb2NpbmFkb3IsIGVkaXRvcmlhbCwgcHVibGljYWNpw7NuKSBlbiBsYSBpbmZvcm1hY2nDs24gZGUgbG9zIGRlcmVjaG9zIGRlIGF1dG9yIGRlbCBMaWNlbmNpYW50ZSwgdMOpcm1pbm9zIGRlIHNlcnZpY2lvcyBvIGRlIG90cmFzIGZvcm1hcyByYXpvbmFibGVzOyBlbCB0w610dWxvIGRlIGxhIE9icmEgc2kgZXN0w6EgcHJvdmlzdG87IGVuIGxhIG1lZGlkYSBkZSBsbyByYXpvbmFibGVtZW50ZSBmYWN0aWJsZSB5LCBzaSBlc3TDoSBwcm92aXN0bywgZWwgSWRlbnRpZmljYWRvciBVbmlmb3JtZSBkZSBSZWN1cnNvcyAoVW5pZm9ybSBSZXNvdXJjZSBJZGVudGlmaWVyKSBxdWUgZWwgTGljZW5jaWFudGUgZXNwZWNpZmljYSBwYXJhIHNlciBhc29jaWFkbyBjb24gbGEgT2JyYSwgc2Fsdm8gcXVlIHRhbCBVUkkgbm8gc2UgcmVmaWVyYSBhIGxhIG5vdGEgc29icmUgbG9zIGRlcmVjaG9zIGRlIGF1dG9yIG8gYSBsYSBpbmZvcm1hY2nDs24gc29icmUgZWwgbGljZW5jaWFtaWVudG8gZGUgbGEgT2JyYTsgeSBlbiBlbCBjYXNvIGRlIHVuYSBPYnJhIERlcml2YWRhLCBhdHJpYnVpciBlbCBjcsOpZGl0byBpZGVudGlmaWNhbmRvIGVsIHVzbyBkZSBsYSBPYnJhIGVuIGxhIE9icmEgRGVyaXZhZGEgKHYuZy4sICJUcmFkdWNjacOzbiBGcmFuY2VzYSBkZSBsYSBPYnJhIGRlbCBBdXRvciBPcmlnaW5hbCwiIG8gIkd1acOzbiBDaW5lbWF0b2dyw6FmaWNvIGJhc2FkbyBlbiBsYSBPYnJhIG9yaWdpbmFsIGRlbCBBdXRvciBPcmlnaW5hbCIpLiBUYWwgY3LDqWRpdG8gcHVlZGUgc2VyIGltcGxlbWVudGFkbyBkZSBjdWFscXVpZXIgZm9ybWEgcmF6b25hYmxlOyBlbiBlbCBjYXNvLCBzaW4gZW1iYXJnbywgZGUgT2JyYXMgRGVyaXZhZGFzIHUgT2JyYXMgQ29sZWN0aXZhcywgdGFsIGNyw6lkaXRvIGFwYXJlY2Vyw6EsIGNvbW8gbcOtbmltbywgZG9uZGUgYXBhcmVjZSBlbCBjcsOpZGl0byBkZSBjdWFscXVpZXIgb3RybyBhdXRvciBjb21wYXJhYmxlIHkgZGUgdW5hIG1hbmVyYSwgYWwgbWVub3MsIHRhbiBkZXN0YWNhZGEgY29tbyBlbCBjcsOpZGl0byBkZSBvdHJvIGF1dG9yIGNvbXBhcmFibGUuCmQuCVBhcmEgZXZpdGFyIHRvZGEgY29uZnVzacOzbiwgZWwgTGljZW5jaWFudGUgYWNsYXJhIHF1ZSwgY3VhbmRvIGxhIG9icmEgZXMgdW5hIGNvbXBvc2ljacOzbiBtdXNpY2FsOgppLglSZWdhbMOtYXMgcG9yIGludGVycHJldGFjacOzbiB5IGVqZWN1Y2nDs24gYmFqbyBsaWNlbmNpYXMgZ2VuZXJhbGVzLiBFbCBMaWNlbmNpYW50ZSBzZSByZXNlcnZhIGVsIGRlcmVjaG8gZXhjbHVzaXZvIGRlIGF1dG9yaXphciBsYSBlamVjdWNpw7NuIHDDumJsaWNhIG8gbGEgZWplY3VjacOzbiBww7pibGljYSBkaWdpdGFsIGRlIGxhIG9icmEgeSBkZSByZWNvbGVjdGFyLCBzZWEgaW5kaXZpZHVhbG1lbnRlIG8gYSB0cmF2w6lzIGRlIHVuYSBzb2NpZWRhZCBkZSBnZXN0acOzbiBjb2xlY3RpdmEgZGUgZGVyZWNob3MgZGUgYXV0b3IgeSBkZXJlY2hvcyBjb25leG9zIChwb3IgZWplbXBsbywgU0FZQ08pLCBsYXMgcmVnYWzDrWFzIHBvciBsYSBlamVjdWNpw7NuIHDDumJsaWNhIG8gcG9yIGxhIGVqZWN1Y2nDs24gcMO6YmxpY2EgZGlnaXRhbCBkZSBsYSBvYnJhIChwb3IgZWplbXBsbyBXZWJjYXN0KSBsaWNlbmNpYWRhIGJham8gbGljZW5jaWFzIGdlbmVyYWxlcywgc2kgbGEgaW50ZXJwcmV0YWNpw7NuIG8gZWplY3VjacOzbiBkZSBsYSBvYnJhIGVzdMOhIHByaW1vcmRpYWxtZW50ZSBvcmllbnRhZGEgcG9yIG8gZGlyaWdpZGEgYSBsYSBvYnRlbmNpw7NuIGRlIHVuYSB2ZW50YWphIGNvbWVyY2lhbCBvIHVuYSBjb21wZW5zYWNpw7NuIG1vbmV0YXJpYSBwcml2YWRhLgppaS4JUmVnYWzDrWFzIHBvciBGb25vZ3JhbWFzLiBFbCBMaWNlbmNpYW50ZSBzZSByZXNlcnZhIGVsIGRlcmVjaG8gZXhjbHVzaXZvIGRlIHJlY29sZWN0YXIsIGluZGl2aWR1YWxtZW50ZSBvIGEgdHJhdsOpcyBkZSB1bmEgc29jaWVkYWQgZGUgZ2VzdGnDs24gY29sZWN0aXZhIGRlIGRlcmVjaG9zIGRlIGF1dG9yIHkgZGVyZWNob3MgY29uZXhvcyAocG9yIGVqZW1wbG8sIGxvcyBjb25zYWdyYWRvcyBwb3IgbGEgU0FZQ08pLCB1bmEgYWdlbmNpYSBkZSBkZXJlY2hvcyBtdXNpY2FsZXMgbyBhbGfDum4gYWdlbnRlIGRlc2lnbmFkbywgbGFzIHJlZ2Fsw61hcyBwb3IgY3VhbHF1aWVyIGZvbm9ncmFtYSBxdWUgVXN0ZWQgY3JlZSBhIHBhcnRpciBkZSBsYSBvYnJhICjigJx2ZXJzacOzbiBjb3ZlcuKAnSkgeSBkaXN0cmlidXlhLCBlbiBsb3MgdMOpcm1pbm9zIGRlbCByw6lnaW1lbiBkZSBkZXJlY2hvcyBkZSBhdXRvciwgc2kgbGEgY3JlYWNpw7NuIG8gZGlzdHJpYnVjacOzbiBkZSBlc2EgdmVyc2nDs24gY292ZXIgZXN0w6EgcHJpbW9yZGlhbG1lbnRlIGRlc3RpbmFkYSBvIGRpcmlnaWRhIGEgb2J0ZW5lciB1bmEgdmVudGFqYSBjb21lcmNpYWwgbyB1bmEgY29tcGVuc2FjacOzbiBtb25ldGFyaWEgcHJpdmFkYS4KZS4JR2VzdGnDs24gZGUgRGVyZWNob3MgZGUgQXV0b3Igc29icmUgSW50ZXJwcmV0YWNpb25lcyB5IEVqZWN1Y2lvbmVzIERpZ2l0YWxlcyAoV2ViQ2FzdGluZykuIFBhcmEgZXZpdGFyIHRvZGEgY29uZnVzacOzbiwgZWwgTGljZW5jaWFudGUgYWNsYXJhIHF1ZSwgY3VhbmRvIGxhIG9icmEgc2VhIHVuIGZvbm9ncmFtYSwgZWwgTGljZW5jaWFudGUgc2UgcmVzZXJ2YSBlbCBkZXJlY2hvIGV4Y2x1c2l2byBkZSBhdXRvcml6YXIgbGEgZWplY3VjacOzbiBww7pibGljYSBkaWdpdGFsIGRlIGxhIG9icmEgKHBvciBlamVtcGxvLCB3ZWJjYXN0KSB5IGRlIHJlY29sZWN0YXIsIGluZGl2aWR1YWxtZW50ZSBvIGEgdHJhdsOpcyBkZSB1bmEgc29jaWVkYWQgZGUgZ2VzdGnDs24gY29sZWN0aXZhIGRlIGRlcmVjaG9zIGRlIGF1dG9yIHkgZGVyZWNob3MgY29uZXhvcyAocG9yIGVqZW1wbG8sIEFDSU5QUk8pLCBsYXMgcmVnYWzDrWFzIHBvciBsYSBlamVjdWNpw7NuIHDDumJsaWNhIGRpZ2l0YWwgZGUgbGEgb2JyYSAocG9yIGVqZW1wbG8sIHdlYmNhc3QpLCBzdWpldGEgYSBsYXMgZGlzcG9zaWNpb25lcyBhcGxpY2FibGVzIGRlbCByw6lnaW1lbiBkZSBEZXJlY2hvIGRlIEF1dG9yLCBzaSBlc3RhIGVqZWN1Y2nDs24gcMO6YmxpY2EgZGlnaXRhbCBlc3TDoSBwcmltb3JkaWFsbWVudGUgZGlyaWdpZGEgYSBvYnRlbmVyIHVuYSB2ZW50YWphIGNvbWVyY2lhbCBvIHVuYSBjb21wZW5zYWNpw7NuIG1vbmV0YXJpYSBwcml2YWRhLgo1LiBSZXByZXNlbnRhY2lvbmVzLCBHYXJhbnTDrWFzIHkgTGltaXRhY2lvbmVzIGRlIFJlc3BvbnNhYmlsaWRhZC4KQSBNRU5PUyBRVUUgTEFTIFBBUlRFUyBMTyBBQ09SREFSQU4gREUgT1RSQSBGT1JNQSBQT1IgRVNDUklUTywgRUwgTElDRU5DSUFOVEUgT0ZSRUNFIExBIE9CUkEgKEVOIEVMIEVTVEFETyBFTiBFTCBRVUUgU0UgRU5DVUVOVFJBKSDigJxUQUwgQ1VBTOKAnSwgU0lOIEJSSU5EQVIgR0FSQU5Uw41BUyBERSBDTEFTRSBBTEdVTkEgUkVTUEVDVE8gREUgTEEgT0JSQSwgWUEgU0VBIEVYUFJFU0EsIElNUEzDjUNJVEEsIExFR0FMIE8gQ1VBTFFVSUVSQSBPVFJBLCBJTkNMVVlFTkRPLCBTSU4gTElNSVRBUlNFIEEgRUxMQVMsIEdBUkFOVMONQVMgREUgVElUVUxBUklEQUQsIENPTUVSQ0lBQklMSURBRCwgQURBUFRBQklMSURBRCBPIEFERUNVQUNJw5NOIEEgUFJPUMOTU0lUTyBERVRFUk1JTkFETywgQVVTRU5DSUEgREUgSU5GUkFDQ0nDk04sIERFIEFVU0VOQ0lBIERFIERFRkVDVE9TIExBVEVOVEVTIE8gREUgT1RSTyBUSVBPLCBPIExBIFBSRVNFTkNJQSBPIEFVU0VOQ0lBIERFIEVSUk9SRVMsIFNFQU4gTyBOTyBERVNDVUJSSUJMRVMgKFBVRURBTiBPIE5PIFNFUiBFU1RPUyBERVNDVUJJRVJUT1MpLiBBTEdVTkFTIEpVUklTRElDQ0lPTkVTIE5PIFBFUk1JVEVOIExBIEVYQ0xVU0nDk04gREUgR0FSQU5Uw41BUyBJTVBMw41DSVRBUywgRU4gQ1VZTyBDQVNPIEVTVEEgRVhDTFVTScOTTiBQVUVERSBOTyBBUExJQ0FSU0UgQSBVU1RFRC4KNi4gTGltaXRhY2nDs24gZGUgcmVzcG9uc2FiaWxpZGFkLgpBIE1FTk9TIFFVRSBMTyBFWElKQSBFWFBSRVNBTUVOVEUgTEEgTEVZIEFQTElDQUJMRSwgRUwgTElDRU5DSUFOVEUgTk8gU0VSw4EgUkVTUE9OU0FCTEUgQU5URSBVU1RFRCBQT1IgREHDkU8gQUxHVU5PLCBTRUEgUE9SIFJFU1BPTlNBQklMSURBRCBFWFRSQUNPTlRSQUNUVUFMLCBQUkVDT05UUkFDVFVBTCBPIENPTlRSQUNUVUFMLCBPQkpFVElWQSBPIFNVQkpFVElWQSwgU0UgVFJBVEUgREUgREHDkU9TIE1PUkFMRVMgTyBQQVRSSU1PTklBTEVTLCBESVJFQ1RPUyBPIElORElSRUNUT1MsIFBSRVZJU1RPUyBPIElNUFJFVklTVE9TIFBST0RVQ0lET1MgUE9SIEVMIFVTTyBERSBFU1RBIExJQ0VOQ0lBIE8gREUgTEEgT0JSQSwgQVVOIENVQU5ETyBFTCBMSUNFTkNJQU5URSBIQVlBIFNJRE8gQURWRVJUSURPIERFIExBIFBPU0lCSUxJREFEIERFIERJQ0hPUyBEQcORT1MuIEFMR1VOQVMgTEVZRVMgTk8gUEVSTUlURU4gTEEgRVhDTFVTScOTTiBERSBDSUVSVEEgUkVTUE9OU0FCSUxJREFELCBFTiBDVVlPIENBU08gRVNUQSBFWENMVVNJw5NOIFBVRURFIE5PIEFQTElDQVJTRSBBIFVTVEVELgo3LiBUw6lybWluby4KYS4JRXN0YSBMaWNlbmNpYSB5IGxvcyBkZXJlY2hvcyBvdG9yZ2Fkb3MgZW4gdmlydHVkIGRlIGVsbGEgdGVybWluYXLDoW4gYXV0b23DoXRpY2FtZW50ZSBzaSBVc3RlZCBpbmZyaW5nZSBhbGd1bmEgY29uZGljacOzbiBlc3RhYmxlY2lkYSBlbiBlbGxhLiBTaW4gZW1iYXJnbywgbG9zIGluZGl2aWR1b3MgbyBlbnRpZGFkZXMgcXVlIGhhbiByZWNpYmlkbyBPYnJhcyBEZXJpdmFkYXMgbyBDb2xlY3RpdmFzIGRlIFVzdGVkIGRlIGNvbmZvcm1pZGFkIGNvbiBlc3RhIExpY2VuY2lhLCBubyB2ZXLDoW4gdGVybWluYWRhcyBzdXMgbGljZW5jaWFzLCBzaWVtcHJlIHF1ZSBlc3RvcyBpbmRpdmlkdW9zIG8gZW50aWRhZGVzIHNpZ2FuIGN1bXBsaWVuZG8gw61udGVncmFtZW50ZSBsYXMgY29uZGljaW9uZXMgZGUgZXN0YXMgbGljZW5jaWFzLiBMYXMgU2VjY2lvbmVzIDEsIDIsIDUsIDYsIDcsIHkgOCBzdWJzaXN0aXLDoW4gYSBjdWFscXVpZXIgdGVybWluYWNpw7NuIGRlIGVzdGEgTGljZW5jaWEuCmIuCVN1amV0YSBhIGxhcyBjb25kaWNpb25lcyB5IHTDqXJtaW5vcyBhbnRlcmlvcmVzLCBsYSBsaWNlbmNpYSBvdG9yZ2FkYSBhcXXDrSBlcyBwZXJwZXR1YSAoZHVyYW50ZSBlbCBwZXLDrW9kbyBkZSB2aWdlbmNpYSBkZSBsb3MgZGVyZWNob3MgZGUgYXV0b3IgZGUgbGEgb2JyYSkuIE5vIG9ic3RhbnRlIGxvIGFudGVyaW9yLCBlbCBMaWNlbmNpYW50ZSBzZSByZXNlcnZhIGVsIGRlcmVjaG8gYSBwdWJsaWNhciB5L28gZXN0cmVuYXIgbGEgT2JyYSBiYWpvIGNvbmRpY2lvbmVzIGRlIGxpY2VuY2lhIGRpZmVyZW50ZXMgbyBhIGRlamFyIGRlIGRpc3RyaWJ1aXJsYSBlbiBsb3MgdMOpcm1pbm9zIGRlIGVzdGEgTGljZW5jaWEgZW4gY3VhbHF1aWVyIG1vbWVudG87IGVuIGVsIGVudGVuZGlkbywgc2luIGVtYmFyZ28sIHF1ZSBlc2EgZWxlY2Npw7NuIG5vIHNlcnZpcsOhIHBhcmEgcmV2b2NhciBlc3RhIGxpY2VuY2lhIG8gcXVlIGRlYmEgc2VyIG90b3JnYWRhICwgYmFqbyBsb3MgdMOpcm1pbm9zIGRlIGVzdGEgbGljZW5jaWEpLCB5IGVzdGEgbGljZW5jaWEgY29udGludWFyw6EgZW4gcGxlbm8gdmlnb3IgeSBlZmVjdG8gYSBtZW5vcyBxdWUgc2VhIHRlcm1pbmFkYSBjb21vIHNlIGV4cHJlc2EgYXRyw6FzLiBMYSBMaWNlbmNpYSByZXZvY2FkYSBjb250aW51YXLDoSBzaWVuZG8gcGxlbmFtZW50ZSB2aWdlbnRlIHkgZWZlY3RpdmEgc2kgbm8gc2UgbGUgZGEgdMOpcm1pbm8gZW4gbGFzIGNvbmRpY2lvbmVzIGluZGljYWRhcyBhbnRlcmlvcm1lbnRlLgo4LiBWYXJpb3MuCmEuCUNhZGEgdmV6IHF1ZSBVc3RlZCBkaXN0cmlidXlhIG8gcG9uZ2EgYSBkaXNwb3NpY2nDs24gcMO6YmxpY2EgbGEgT2JyYSBvIHVuYSBPYnJhIENvbGVjdGl2YSwgZWwgTGljZW5jaWFudGUgb2ZyZWNlcsOhIGFsIGRlc3RpbmF0YXJpbyB1bmEgbGljZW5jaWEgZW4gbG9zIG1pc21vcyB0w6lybWlub3MgeSBjb25kaWNpb25lcyBxdWUgbGEgbGljZW5jaWEgb3RvcmdhZGEgYSBVc3RlZCBiYWpvIGVzdGEgTGljZW5jaWEuCmIuCVNpIGFsZ3VuYSBkaXNwb3NpY2nDs24gZGUgZXN0YSBMaWNlbmNpYSByZXN1bHRhIGludmFsaWRhZGEgbyBubyBleGlnaWJsZSwgc2Vnw7puIGxhIGxlZ2lzbGFjacOzbiB2aWdlbnRlLCBlc3RvIG5vIGFmZWN0YXLDoSBuaSBsYSB2YWxpZGV6IG5pIGxhIGFwbGljYWJpbGlkYWQgZGVsIHJlc3RvIGRlIGNvbmRpY2lvbmVzIGRlIGVzdGEgTGljZW5jaWEgeSwgc2luIGFjY2nDs24gYWRpY2lvbmFsIHBvciBwYXJ0ZSBkZSBsb3Mgc3VqZXRvcyBkZSBlc3RlIGFjdWVyZG8sIGFxdcOpbGxhIHNlIGVudGVuZGVyw6EgcmVmb3JtYWRhIGxvIG3DrW5pbW8gbmVjZXNhcmlvIHBhcmEgaGFjZXIgcXVlIGRpY2hhIGRpc3Bvc2ljacOzbiBzZWEgdsOhbGlkYSB5IGV4aWdpYmxlLgpjLglOaW5nw7puIHTDqXJtaW5vIG8gZGlzcG9zaWNpw7NuIGRlIGVzdGEgTGljZW5jaWEgc2UgZXN0aW1hcsOhIHJlbnVuY2lhZGEgeSBuaW5ndW5hIHZpb2xhY2nDs24gZGUgZWxsYSBzZXLDoSBjb25zZW50aWRhIGEgbWVub3MgcXVlIGVzYSByZW51bmNpYSBvIGNvbnNlbnRpbWllbnRvIHNlYSBvdG9yZ2FkbyBwb3IgZXNjcml0byB5IGZpcm1hZG8gcG9yIGxhIHBhcnRlIHF1ZSByZW51bmNpZSBvIGNvbnNpZW50YS4KZC4JRXN0YSBMaWNlbmNpYSByZWZsZWphIGVsIGFjdWVyZG8gcGxlbm8gZW50cmUgbGFzIHBhcnRlcyByZXNwZWN0byBhIGxhIE9icmEgYXF1w60gbGljZW5jaWFkYS4gTm8gaGF5IGFycmVnbG9zLCBhY3VlcmRvcyBvIGRlY2xhcmFjaW9uZXMgcmVzcGVjdG8gYSBsYSBPYnJhIHF1ZSBubyBlc3TDqW4gZXNwZWNpZmljYWRvcyBlbiBlc3RlIGRvY3VtZW50by4gRWwgTGljZW5jaWFudGUgbm8gc2UgdmVyw6EgbGltaXRhZG8gcG9yIG5pbmd1bmEgZGlzcG9zaWNpw7NuIGFkaWNpb25hbCBxdWUgcHVlZGEgc3VyZ2lyIGVuIGFsZ3VuYSBjb211bmljYWNpw7NuIGVtYW5hZGEgZGUgVXN0ZWQuIEVzdGEgTGljZW5jaWEgbm8gcHVlZGUgc2VyIG1vZGlmaWNhZGEgc2luIGVsIGNvbnNlbnRpbWllbnRvIG11dHVvIHBvciBlc2NyaXRvIGRlbCBMaWNlbmNpYW50ZSB5IFVzdGVkLgo= 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