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Retropolating some relevant series of Mexico's System of National Accounts at constant prices: The case of Mexico City's GDP

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  • Víctor M. Guerrero
  • Francisco Corona

Abstract

In Mexico, the System of National Accounts is disaggregated at the State level and expressed at constant prices of the most recent base year, 2008, for the years 2003 to 2015. Another frequently used database related to the National Accounts and disaggregated by State contains a quarterly index of economic activity. Further, a yearly database is also available with State‐level disaggregation and base year 1993, but it only covers the years 1993 to 2006 and employs a different classification system from that of base year 2008. In this work, we are concerned with the problem of retropolating the database of a Mexican State called Mexico City with the maximum level of disaggregation allowed by the publicly available databases. We followed a data‐driven approach and combined the three databases to produce an estimated homogeneous quarterly database with base year 2008, covering the years 1993 to 2015 and disaggregated up to groups of sectors.

Suggested Citation

  • Víctor M. Guerrero & Francisco Corona, 2018. "Retropolating some relevant series of Mexico's System of National Accounts at constant prices: The case of Mexico City's GDP," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 495-519, November.
    • Handle: RePEc:bla:stanee:v:72:y:2018:i:4:p:495-519
    DOI: 10.1111/stan.12162
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    References listed on IDEAS

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    1. Tommaso Fonzo, 2003. "Constrained retropolation of high-frequency data using related series: A simple dynamic model approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 12(1), pages 109-119, February.
    2. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    3. E. Silva & V. M. Guerrero & D. Peña, 2011. "Temporal disaggregation and restricted forecasting of multiple population time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(4), pages 799-815, January.
    4. Baoline Chen, 2012. "A Balanced System of U.S. Industry Accounts and Distribution of the Aggregate Statistical Discrepancy by Industry," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 202-211, February.
    5. Víctor Guerrero & Fabio Nieto, 1999. "Temporal and contemporaneous disaggregation of multiple economic time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 8(2), pages 459-489, December.
    6. Sax, Christoph & Steiner, Peter, 2013. "Temporal Disaggregation of Time Series," MPRA Paper 53389, University Library of Munich, Germany.
    7. Reinier Bikker & Jacco Daalmans & Nino Mushkudiani, 2013. "Benchmarking Large Accounting Frameworks: A Generalized Multivariate Model," Economic Systems Research, Taylor & Francis Journals, vol. 25(4), pages 390-408, December.
    8. Robert E. Yuskavage, 2007. "COnverting Historical Industry Time Series Data from SIC to NAICS," BEA Papers 0085, Bureau of Economic Analysis.
    9. Di Fonzo, Tommaso, 1990. "The Estimation of M Disaggregate Time Series When Contemporaneous and Temporal Aggregates Are Known," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 178-182, February.
    10. Pfaff, Bernhard, 2008. "VAR, SVAR and SVEC Models: Implementation Within R Package vars," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i04).
    11. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    12. Tommaso Proietti, 2011. "Multivariate temporal disaggregation with cross-sectional constraints," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(7), pages 1455-1466, June.
    13. Trabelsi, Abdelwahed & Hillmer, Steven C, 1989. "A Benchmarking Approach to Forecast Combination," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(3), pages 353-362, July.
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