1. bookVolume 38 (2022): Edition 2 (June 2022)
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2001-7367
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01 Oct 2013
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Assessing Residual Seasonality in the U.S. National Income and Product Accounts Aggregates

Publié en ligne: 14 Jun 2022
Volume & Edition: Volume 38 (2022) - Edition 2 (June 2022)
Pages: 399 - 428
Reçu: 01 Dec 2020
Accepté: 01 Jun 2021
Détails du magazine
License
Format
Magazine
eISSN
2001-7367
Première parution
01 Oct 2013
Périodicité
4 fois par an
Langues
Anglais
Abstract

There is an ongoing debate on whether residual seasonality is present in the estimates of real Gross Domestic Product (GDP) in U.S. national accounts and whether it explains the slower quarter-one GDP growth rate in the recent years. This article aims to bring clarity to this topic by (1) summarizing the techniques and methodologies used in these studies; (2) arguing for a sound methodological framework for evaluating claims of residual seasonality; and (3) proposing three diagnostic tests for detecting residual seasonality, applying them to different vintages and different sample spans of data on real GDP and its major components from the U.S. national accounts and making comparisons with results from the previous studies.

Keywords

Blakely, C., and T.S. McElroy. 2017. “Signal Extraction Goodness-of-fit Diagnostic Tests Under Model Parameter Uncertainty: Formulations and Empirical Evaluation.” Econometric Reviews 36: 447–467. DOI: https://doi.org/10.1080/07474938.2016.1140277.10.1080/07474938.2016.1140277 Search in Google Scholar

Canova, F., and B.E. Hansen. 1995. “Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability.” Journal of Business and Economic Statistics 13: 237–252. DOI: https://doi.org/10.1080/07350015.1995.10524598.10.1080/07350015.1995.10524598 Search in Google Scholar

Cowan, B., S. Smith, and S. Thompson. 2018. “Seasonal Adjustment in the National Income and Product Accounts.” Survey of Current Business 98(8). Available at: https://apps.bea.gov/scb/2018/08-august/pdf/0818-gdp-seasonality.pdf (accessed April 2022). Search in Google Scholar

Findley, D.F., D.P. Lytras, and T.S. McElroy. 2017. Detecting Seasonality in Seasonally Adjusted Monthly Time Series. U.S. Census Bureau research report, 2017(3). Available at: https://www.census.gov/content/dam/Census/library/working-papers/2017/adrm/rrs2017-03.pdf (accessed April 2022). Search in Google Scholar

Findley, D.F., B.C. Monsell, W.R. Bell, M.C. Otto, and B.C. Chen. 1998. “New Capabilities and Methods of the X-12-ARIMA Seasonal Adjustment Program.” Journal of Business and Economic Statistics 16: 127–177. DOI: https://doi.org/10.1080/07350015.1998.10524743.10.1080/07350015.1998.10524743 Search in Google Scholar

Franses, P.H. 1994. “A Multivariate Approach to Modeling Univariate Seasonal Time Series.” Journal of Econometrics 63(1): 133–151. DOI: https://doi.org/10.1016/0304-4076(93)01563-2.10.1016/0304-4076(93)01563-2 Search in Google Scholar

Friedman, M. 1937. “The Use of Ranks to Avoid the Assumption of Normality Implicit in the Analysis of Variance.” Journal of the American Statistical Association 32: 675–701. DOI: https://doi.org/10.1080/01621459.1937.10503522.10.1080/01621459.1937.10503522 Search in Google Scholar

Furman, J. 2015. “Second Estimate of GDP for the First Quarter of 2015.” Council of Economic Advisers Blog. Available at: https://obamawhitehouse.archives.gov/blog/2015/05/29/second-estimate-gdp-first-quarter-2015 (accessed May 2021). Search in Google Scholar

Gilbert, C.E., N.J. Morin, A.O. Paciorek, and C.R. Sahm. 2015. “Residual Seasonality in GDP.” FED Notes. DOI: https://doi.org/10.17016/2380-7172.1538.10.17016/2380-7172.1538 Search in Google Scholar

Gómez, V., and A. Maravall. 1996. Programs TRAMO and SEATS: Instructions for the User. Working Paper: 9628. Servicio de Estudios, Banco de España. Available at: https://www.researchgate.net/publication/247274792_Programs_TRAMO_and_SEATS_instructions_for_the_user (accessed May 2021). Search in Google Scholar

Groen, J., and P. Russo. 2015. “The Myth of First-Quarter Residual Seasonality.” Liberty Street Economics. Available at: https://libertystreeteconomics.newyorkfed.org/2015/06/the-myth-of-first-quarter-residual-seasonality.html (accessed May 2021). Search in Google Scholar

Hylleberg, S., R.F. Engle, C.W.J. Granger, and B.S. Yoo. 1990. “Seasonal Integration and Cointegration.” Journal of Econometrics 44: 215–238. DOI: https://doi.org/10.1016/0304-4076(90)90080-D.10.1016/0304-4076(90)90080-D Search in Google Scholar

Kruskal, W.H., and W.A. Wallis. 1952. “Use of Ranks in One-Criterion Variance Analysis.” Journal of the American Statistical Association 47: 583–621. DOI: https://doi.org/10.1080/01621459.1952.10483441.10.1080/01621459.1952.10483441 Search in Google Scholar

Lengermann, P., E. Morin, A. Paciorek, E. Pinto, and C. Sahm. 2017. Another Look at Residual Seasonality in GDP. FEDS Notes. Washington: Board of Governors of the Federal Reserve System. DOI: https://doi.org/10.17016/2380-7172.2031.10.17016/2380-7172.2031 Search in Google Scholar

Lothian, J., and M. Morry. 1978. A Set of Quality Control Statistics for the X-11 ARIMA Seasonal Adjustment Method. Statistics Canada Working Paper: 78-10-005E. Available at: https://www.census.gov/content/dam/Census/library/working-papers/1978/adrm/lothianmorry1978.pdf (accessed May 2021). Search in Google Scholar

Lunsford, K.G. 2017. “Lingering Residual Seasonality in GDP Growth.” Economic Commentary, Federal Reserve Bank of Cleveland. DOI: https://doi.org/10.26509/FRBC-EC-201706.10.26509/frbc-ec-201706 Search in Google Scholar

Lytras, D.P., R.M. Feldpausch, and W.R. Bell. 2007. “Determining Seasonality: A Comparison of Diagnostics from X-12-ARlMA.” In Proceedings of the Third International Conference on Establishment Surveys (ICES-III), June 18–21, Montreal, Canada. Available at: https://www.census.gov/content/dam/Census/library/working-papers/2007/adrm/ices2007dpl.pdf (accessed May 2021). Search in Google Scholar

Maravall, A. 2012. Update of Seasonality Tests and Automatic Model Identification in TRAMO-SEATS. Banco de España. Search in Google Scholar

McCulla, S.H., and S. Smith. 2015. “Preview of the 2015 Annual Revision of the National Income and Product Accounts.”, Survey of Current Business 95(6). Available at: https://apps.bea.gov/scb/pdf/2015/06%20June/0615_preview_of_2015_annual_revision_of_national_income_and_product_accounts.pdf (accessed May 2021). Search in Google Scholar

McElroy, T.S. 2012. “An Alternative Model-Based Seasonal Adjustment that Reduces Residual Seasonal Autocorrelation.”, Taiwan Economic Forecast and Policy 43: 33–70. Available at: https://www.census.gov/content/dam/Census/library/working-papers/2012/adrm/mcelroytefp.pdf (accessed May 2021). Search in Google Scholar

McElroy, T.S. 2018. “Seasonal Adjustment Subject to Accounting Constraints.” Statistica Neerlandica 72: 574–589. DOI: https://doi.org/10.1111/stan.12161.10.1111/stan.12161 Search in Google Scholar

McElroy, T.S. 2021. “A Diagnostic for Seasonality Based Upon Polynomial Roots of ARMA Models.” Journal of Official Statistics 37(2): 1–28. DOI: https://doi.org/10.2478/jos-2021-0016.10.2478/jos-2021-0016 Search in Google Scholar

McElroy, T.S., and S. Holan. 2009. “A Nonparametric Test for Residual Seasonality.”, Survey Methodology 35: 67–83., Available at: https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2009001/article/10885-eng.pdf?st=gTYxvTH5 (accessed May 2021). Search in Google Scholar

McElroy, T.S., O. Pang, and B. Monsell. 2019. “Seasonal Adjustment Subject to Lower Frequency Benchmarks.” In the 2019 Proceedings of American Statistical Association July 27 August 1, Alexandria, VA. Search in Google Scholar

McElroy, T.S. and D.N. Politis. 2020. Time Series: A First Course with Bootstrap Sampler. Boca Raton: CRC Press.10.1201/9780429109553 Search in Google Scholar

McElroy, T.S., and A. Roy. 2021. “Testing for Adequacy of Seasonal Adjustment in the Frequency Domain.” Journal of Statistical Planning and Inference 221: 241–255. DOI: https://doi.org/10.1016/j.jspi.2020.06.012.10.1016/j.jspi.2020.06.012 Search in Google Scholar

Moulton, B.R., and B.D. Cowan. 2016. “Residual Seasonality in GDP and GDI: Findings and Next Steps.” Survey of Current Business 96(7)., Available at: https://apps.bea.-gov/scb/pdf/2016/07%20July/0716_residual_seasonality_in_gdp_and_gdi.pdf (accessed May 2021). Search in Google Scholar

Müller, U.K., and M.W. Watson 2008. “Testing Models of Low-Frequency Variability.” Econometrica 76: 979–1016. DOI: https://doi.org/10.3982/ECTA6814.10.3982/ECTA6814 Search in Google Scholar

Müller, U.K., and M.W. Watson. 2015. Low-Frequency Econometrics. NBER Working Paper 21564: 1–45. DOI: https://doi.org/10.3386/w21564.10.3386/w21564 Search in Google Scholar

Nyblom, J. 1989. “Testing for the Constancy of Parameters Over Time.” Journal of the American Statistical Association 84: 223–230. DOI: https://doi.org/10.1080/01621459.1989.10478759.10.1080/01621459.1989.10478759 Search in Google Scholar

Phillips, K., and J. Wang. 2016. Residual Seasonality in U.S. GDP Data. FRB of Dallas Working Paper 1608. DOI: https://doi.org/10.24149/wp1608.10.24149/wp1608 Search in Google Scholar

Priestley, M.B. 1981. Spectral Analysis and Time Series. New York: Academic Press. Search in Google Scholar

Rudebusch, G.D., D. Wilson, and T. Mahedy. 2015. “The Puzzle of Weak First-Quarter GDP Growth.” FRBSF Economic Letter, Available at: https://www.frbsf.org/economic-research/publications/economic-letter/2015/may/weak-first-quarter-gdp-residual-seasonality-adjustment/ (accessed May 2021). Search in Google Scholar

St. Louis Fed. 2019. “Taking a Closer Look at Residual Seasonality and U.S. GDP Growth.” On the Economy. Federal Reserve Bank of St. Louis. Available at: https://www.stlouisfed.org/on-the-economy/2019/january/closer-look-residual-seasonalitygdp-growth (accessed May 2021). Search in Google Scholar

Soukup, R., and D. Findley. 1999. “On the spectrum diagnostics used by X-12-ARIMA to indicate the presence of trading day effects after modeling or adjustment.” In the 1999 Proceedings of American Statistical Association, August 8–12, Alexandria, VA. Available at https://www.census.gov/content/dam/Census/library/working-papers/1999/adrm/rr9903s.pdf. Search in Google Scholar

Stark, T. 2015. “First Quarters in the National Income and Product Accounts.” Research Rap, Federal Reserve Bank of Philadelphia. Available at: https://www.philadelphia-fed.org/the-economy/macroeconomics/first-quarters-in-the-national-income-and-product-accounts (accessed May 2021). Search in Google Scholar

U.S. Bureau of Economic Analysis. 2018a. Available at: https://www.bea.gov/data/gdp/-gross-domestic-product. Search in Google Scholar

U.S. Bureau of Economic Analysis. 2018b. Available at: https://apps.bea.gov/iTable. Search in Google Scholar

U.S. Census Bureau. 2020. X-13ARIMA-SEATS Reference Manual. U.S. Census Bureau. Washington D.C. USA, Available at https://www2.census.gov/software/x-13arima-seats/x13as/windows/documentation/docx13ashtml.pdf (accessed April 2022). Search in Google Scholar

Wright, J.H. 2018. Seasonal Adjustment of NIPA Data. NBER working paper: 24895. DOI: https://doi.org/10.3386/w24895.10.3386/w24895 Search in Google Scholar

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