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La trimestralización de variables flujo. Un estudio de simulación de los métodos de desagregación temporal con indicador

  • Alejandro Rodríguez Caro


  • Santiago Rodríguez Feijoo


  • Delia Dávila Quintana


En el presente trabajo se estudian las propiedades de seis métodos de desagregación temporal con información auxiliar basados en el propuesto por Chow y Lin (1971), a través de una simulación de Montecarlo. El objetivo del trabjo es determinar el método correcto a utilizar en función de las condiciones de la información auxiliar.

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Paper provided by Facultad de Ciencias Económicas de la ULPGC in its series Documentos de trabajo conjunto ULL-ULPGC with number 2003-01.

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Length: 15 pages
Date of creation: 2003
Date of revision:
Handle: RePEc:can:series:2003-01
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  1. Nijman, T.E. & Palm, F.C., 1986. "Efficiency gains due to using missing data procedures in regression models," Research Memorandum FEW 240, Tilburg University, School of Economics and Management.
  2. Palm, F.C. & Nijman, Th., 1982. "Missing observations in the dynamic regression model," Serie Research Memoranda 0018, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  3. Fernandez, Roque B, 1981. "A Methodological Note on the Estimation of Time Series," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 471-76, August.
  4. Lutkepohl, Helmut, 1984. "Linear transformations of vector ARMA processes," Journal of Econometrics, Elsevier, vol. 26(3), pages 283-293, December.
  5. Nijman, T.E. & Palm, F.C., 1990. "Predictive accuracy gain from disaggregate sampling in ARIMA models," Other publications TiSEM 50a68aea-1b30-497d-b111-6, Tilburg University, School of Economics and Management.
  6. Chow, Gregory C & Lin, An-loh, 1971. "Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series," The Review of Economics and Statistics, MIT Press, vol. 53(4), pages 372-75, November.
  7. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-73, April.
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