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MEXICAN MAQUILA INDUSTRY OUTLOOK. A Quantitative Space-Time Analysis

Author

Listed:
  • F. Javier TRIVEZ
  • Angel Mauricio REYES
  • F. Javier ALIAGA

Abstract

The aim of this article is to analyse the current situation and the short and mid term outlook of the maquila export industry in Mexico. The purpose is to carry out an analysis of quantitative economic conjuncture, by conveniently combining the necessary elements. Therefore, we have used an empiric base- relevant information expressed in monthly statistical time series of the Mexican value added of export income charged by maquila service (VAECMS) in national and state levels- and quantitative methods (statistical-econometrics techniques). Under this framework, we present a methodological proposal in order to analyse ARIMA models with outliers and calendar effects, then we use a reduced model for the signal extraction. The trend-cycle component is the most suitable way to consider the underlying evolution. From this component and from the growth rate and inertial behaviour we are able to extract the major conclusions of the current Mexican export maquila situation in general as well as in detail in the principal states of the country.

Suggested Citation

  • F. Javier TRIVEZ & Angel Mauricio REYES & F. Javier ALIAGA, 2009. "MEXICAN MAQUILA INDUSTRY OUTLOOK. A Quantitative Space-Time Analysis," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 9(1).
    • Handle: RePEc:eaa:eerese:v:9:y2009:i:9_2
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    References listed on IDEAS

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    1. F. Javier Trivez & Javier Nievas, 1998. "Analyzing the effects of level shifts and temporary changes on the identification of ARIMA models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(3), pages 409-424.
    2. Maravall, Agustin & Pierce, David A, 1986. "The Transmission of Data Noise into Policy Noise in U.S. Monetary Control," Econometrica, Econometric Society, vol. 54(4), pages 961-979, July.
    3. Ledolter, Johannes, 1989. "The effect of additive outliers on the forecasts from ARIMA models," International Journal of Forecasting, Elsevier, vol. 5(2), pages 231-240.
    4. Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Time Series: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 343-349, October.
    5. Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 291-320, October.
    6. Agustin Maravall & David A. Pierce, 1987. "A Prototypical Seasonal Adjustment Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 8(2), pages 177-193, March.
    7. Wai-Sum Chan, 1995. "Understanding the effect of time series outliers on sample autocorrelations," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 4(1), pages 179-186, June.
    8. Mendoza, Jorge Eduardo, 2002. "Educación, experiencia y especialización manufacturera en la frontera norte de México [Schooling, experience and manufacturing specialization along the northern border of Mexico]," MPRA Paper 2811, University Library of Munich, Germany, revised 04 Apr 2002.
    9. Chen, Chung & Tiao, George C, 1990. "Random Level-Shift Time Series Models, ARIMA Approximations, and Level-Shift Detection," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 83-97, January.
    10. F. Javier Trivez & Javier Nievas, 1996. "Comportamiento en muestras pequeñas de los atípicos innovacionales: Un ejercicio de simulación," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 5, pages 161-175, Junio.
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    More about this item

    Keywords

    Conjunctural Analysis; Signal Extraction; Underlying; Evolution; Underlying Growth; ARIMA Models; Outliers; Forecast.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • L69 - Industrial Organization - - Industry Studies: Manufacturing - - - Other

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