Agustín Maravall

Agustín Maravall Herrero (born in 1944 in Madrid) is a Spanish economist. He is known for his contributions to the analysis of statistics and econometrics, particularly in seasonal adjustment and the estimation of signals in economic time series.^[1] He created a methodology and several computer programs for such analysis that are used throughout the world by analysts, researchers, and data producers. Maravall retired in December 2014 from the Bank of Spain.^[2]

Agustín Maravall
Born	1944 (age 79–80) Madrid
Nationality	Spanish
Awards	Julius Shiskin Award for Economic Statistics 2004 Premio Rey Jaime I de Economia 2005 Premio Galicia de Estadística 2006 King Juan Carlos Prize in Economics 2014
Scientific career
Fields	Economics

Biography

Maravall spent his childhood in Paris, then moved to Madrid and finished secondary school at the Colegio Estudio. He completed a doctorate in agricultural engineering at the Technical University of Madrid, and worked for several years at the Spanish Ministry of Agriculture. With a Fulbright-Ford fellowship he came to the United States and completed a Ph.D. in Economics at the University of Wisconsin–Madison. In 1975, he moved to Washington, D.C. to work as a staff economist in the Research Division of the Federal Reserve Board of Governors. In 1979, he returned to Madrid as a senior economist in the Research Department of the Bank of Spain, and in 1989 he moved to Italy as Full Professor in the Department of Economics of the European University Institute in Florence. In 1996, he returned to the Bank of Spain as Chief Economist and Head of the Time Series Analysis Unit.

Maravall has been on the editorial board of multiple professional journals, including the Journal of Business and Economic Statistics and the Journal of Econometrics. He served on the Program and Scientific Committees of many international meetings and conferences. His teaching experience includes teaching courses in more than 30 countries to participants from more than 60 countries. He was Special Advisor to the European Central Bank and Eurostat, a member of the Board of Directors of the former Institute for Advanced Studies in the Social Sciences of Madrid, and a member of the High Advisory Council for R & D of the Generalitat Valenciana.

Research

Maravall's research focused on time series analysis, time series modeling, and time series applications to economic data. His key contribution, in collaboration with Victor Gómez was the creation of a model-based approach for jointly solving many statistical time series difficulties that affect the analysis and interpretation of economic time series. In the presence of potentially missing observations^[3] the typical (default) technique first performs automatic identification and forecasting of regression-ARIMA models (including adjustment for outliers and calendar effects). The model is then split into models for unobserved components (such as seasonal, trend, transient, and cyclical components), from which filters are generated to estimate and forecast the unobserved components.^[4][5][6] The model-based structure generates the estimators' joint distribution, from which parametric tests and inferences (such as the standard errors of all estimators and forecasts) can be obtained.^[7][8]

Two relevant features of the procedure are first, that all estimators for a given series are derived from the same (well-defined) model and will thus be internally consistent. Second, the automated procedure can be efficiently and reliably applied to very large sets of time series.^[9][10]

His research has been published in academic journals (with some reprinted in books), the Springer-Verlag monograph series Lecture Notes in Statistics and Lecture Notes in Economics and Mathematical Systems, the Bank of Spain monograph series, and in multiple book chapters.^[11]

Software development and seasonal adjustment

With the collaboration of Víctor Gómez (1987–1999) and Gianluca Caporello (1990–2015), the research was incorporated into several computer programs: TRAMO (“Time series Regression with ARIMA noise, Missing values, and Outliers”), SEATS (“Signal Extraction in ARIMA Time Series”), and TSW (“Tramo and Seats for Windows”). An extension of TRAMO, TERROR (“TRAMO for errors”), contains an application of Maravall's research to data editing (the program detects possible errors in incoming data that is part of large time-series data sets).

The programs are used throughout the world in a variety of applications. An important use is the official production of seasonally adjusted data, which has been recommended by working groups at many institutions.^[12] The recent X13-ARIMA-SEATS program of the United States Census Bureau offers two options: their program X12-ARIMA (which adopted and modified the automatic model identification procedure of TRAMO), and SEATS.^[13] The European Statistical System (consisting of central banks and statistical agencies) has developed JDEMETRA+, which is a Java interface with X12-ARIMA and TRAMO-SEATS that is recommended for European countries.^[14] TRAMO and SEATS are also included in statistics and econometrics packages, and are freely available from the Bank of Spain.^[15]

Awards and honors

Former Wisconsin Alumni Research Foundation Fellow (1973–75); Fulbright-Ford Fellow (1971–73); Phi Kappa Phi Honor Society Fellow (1975); Oficial de la Orden Civil del Mérito Agrario (1971). Elected member of the International Statistical Institute (1988).

Fellow of the Journal of Econometrics, 1995; Fellow of the American Statistical Association, 2000.

2004 Julius Shiskin Award for Economic Statistics, sponsored by the Washington Statistical Society, the National Association for Business Economics, and the American Statistical Association, Business and Economics Section. Rey Jaime I Prize in Economics, 2005, sponsored by the Spanish Royal House, the "Fundación Premios Rey Jaime I,” and the Generalitat Valenciana. First Galicia Prize in Statistics, 2006, sponsored by the Caixa Galicia Foundation and the Galicia Statistical Institute. Rey Juan Carlos Prize in Economics, 2014, sponsored by the Celma Foundation and presented by the King of Spain.

Homage “Celebrating 25 years of TRAMO-SEATS and the 70th birthday of Agustín Maravall,” hosted by the Bank of Spain, March 2014, with the participation of researchers from universities, central banks and statistical agencies in Belgium, France, Germany, Italy, The Netherlands, Spain, Sweden, the UK, and the USA.^[16]

References

1. Peña, Daniel (2020-10-01). "Agustín Maravall: An interview with the International Journal of Forecasting". International Journal of Forecasting. 36 (4): 1241–1251. doi:10.1016/j.ijforecast.2019.12.005. ISSN 0169-2070. S2CID 214203153.
2. Peña, Daniel (October 2020). "Agustín Maravall: An interview with the International Journal of Forecasting". International Journal of Forecasting. 36 (4): 1241–1251. doi:10.1016/j.ijforecast.2019.12.005. Retrieved 19 May 2023.
3. GÓMEZ, V. and MARAVALL, A. (1994), "Estimation, Prediction and Interpolation for Nonstationary Series with the Kalman Filter", Journal of the American Statistical Association 89, 611-624.
4. BURMAN, J.P. (1980), "Seasonal Adjustment by Signal Extraction", Journal of the Royal Statistical Society A, 143, 321-337.
5. HILLMER, S.C. and TIAO, G.C. (1982), "An ARIMA‑Model Based Approach to Seasonal Adjustment", Journal of the American Statistical Association 77, 63-70.
6. MARAVALL, A. (1995), "Unobserved Components in Economic Time Series", in Pesaran, H. and Wickens, M. (eds.), The Handbook of Applied Econometrics, chap. 1, 12-72. Oxford: Basil Blackwell.
7. GÓMEZ, V. and MARAVALL, A. (2001b), "Seasonal Adjustment and Signal Extraction in Economic Time Series", Ch.8 in Peña D., Tiao G.C. and Tsay, R.S. (eds.) A Course in Time Series Analysis, New York: J. Wiley and Sons.
8. GÓMEZ, V. and MARAVALL, A. (2001a), "Automatic Modeling Methods for Univariate Series", Ch.7 in Peña D., Tiao G.C. and Tsay, R.S. (eds.), A Course in Time Series Analysis, New York: J. Wiley and Sons.
9. MARAVALL, A., LÓPEZ, R., and PÉREZ, D., (2016) “Reg-ARIMA Model Identification: Empirical Evidence”, special Issue on Frontiers of Statistics and Forecasting, Statistica Sinica, 26, 1365-1388.
10. MARAVALL, A., LOPEZ, R., and PÉREZ, D., (2015), “Reliability of the Automatic Identification of ARIMA Models in Program TRAMO”, in Beran, J., Feng, Y., and Hebbel, H. (eds.) Empirical Economic and Financial Research. Theory, Methods and Practice, Springer series in Advanced Studies in Theoretical and Applied Econometrics, International Publishing, Switzerland, 105-122.
11. Many of the papers and additional documents are available at the Bank of Spain web site and in RESEARCH GATE and GOOGLE.
12. Some examples (available in GOOGLE) are: UNECE (2011), “Practical Guide to Seasonal Adjustment”, United Nations, New York and Geneva, ECE/CES/15; EUROPEAN CENTRAL BANK (2000), “Task Force on Seasonal Adjustment: Final Report”, European Central Bank, Frankfurt. TFSA/0100/FINRP; EUROSTAT (2009), “ESS Guidelines on Seasonal Adjustment”, Methodologies and Working Papers, Eurostat, European Commission, Office for Official Publications of the European Communities; EUROSTAT (1998), “Seasonal Adjustment Methods: A Comparison”, Statistical Document, Eurostat, Office for Official Publications of the European Communities; INTERNATIONAL MONETARY FUND (2014), “Update of ‘Quarterly National Accounts Manual: Concepts, Data Sources and Compilation’”, International Monetary Fund, Statistics Department; OECD (2002), “Harmonizing Seasonal Adjustment Methods in European Union and OECD countries”, OECD Statistics Directorate, STD/STESE G (2002) 22; USBLS (20016), “Methodology for Seasonally Adjusting National Household Survey Labor Force Series”, Tiller, R.B., and Evans, R.D., Current Population Survey, Technical Documentation, US Bureau of Labor Statistics.
13. See U.S. CENSUS BUREAU (2016), X-13-ARIMA-SEATS Seasonal Adjustment Program, Center for Statistical Research and Methodology, US Census Bureau, and U.S. CENSUS BUREAU (2011), "X12-ARIMA Reference Manual; Version 0.3" Statistics Research Division, US Census Bureau. The two programs have been developed by a team led by David Findley and Brian Monsell.
14. See GRUDKOWSKA, S. (2015), “JDemetra+ Reference Manual. Version 1.1”, Department of Statistics, National Bank of Poland. The interface has been mostly developed by J. Palate and his team at the Bank of Belgium with support from Eurostat.
15. BANK of SPAIN It contains, besides the DOS and WINDOWS versions of the programs, interfaces with C++, Java, Python, R, SAS, Matlab, C#, Fame and Linux, papers and documentation, and about 80000 time series.
16. “Celebrating 25 years of TRAMO-SEATS and the 70th birthdate of Agustín Maravall” and “Introduction to the special issue in honor of Agustín Maravall – Springer”.