Isabel Molina and J.N.K. Rao, Lauréats du prix de La revue canadienne de statistique 2011

Isabel Molina
J.N.K. Rao
Lauréats du prix de La revue canadienne de statistique
2011
"Small area estimation of poverty indicators", CJS/RCS vol. 38, 2010, pp 369-385
The Canadian Journal of Statistics Award is presented each year by the Statistical Society of Canada to the author(s) of an article published in the journal, in recognition of the outstanding quality of the paper’s methodological innovation and presentation.
 
This year’s winner is the article entitled “Small area estimation of poverty indicators” (vol. 38, no 3, pp. 369-385), by Isabel Molina and J.N.K. Rao.
 
The authors propose to estimate nonlinear small area population parameters by using the empirical Bayes (best) method, based on a nested error model. They focus on poverty indicators as particular nonlinear parameters of interest, but the proposed methodology is applicable to general nonlinear parameters. They use a parametric bootstrap method to estimate the mean squared error of the empirical best estimators. They also establish small sample properties of these estimators by model-based and design-based simulation studies. Results show large reductions in mean squared error relative to direct area-specific estimators and other estimators obtained by simulated censuses. The authors also apply the proposed method to estimate poverty incidences and poverty gaps in Spanish provinces by gender with mean squared errors estimated by the mentioned parametric bootstrap method. For the Spanish data, results show a significant reduction in coefficient of variation of the proposed empirical best estimators over direct estimators for practically all domains. The paper develops a methodology that can provide more accurate results in small area estimation of poverty indicators and poverty gaps. The application and presentation of the results were also outstanding.
Isabel Molina joined the Department of Statistics at Carlos III University-Madrid as an Assistant Professor in 2003, currently she is a Tenured Associate Professor in the same department. Prior to joining Carlos III University-Madrid, Molina earned B.Sc. (statistics, 1999) and PhD (statistics and operations research, 2003) degrees, both from Miguel Hernández University-Elche in the Alicante Province, Spain. On the research front, her interests include small area estimation, linear mixed models, generalised linear mixed models and resampling techniques, in particular the bootstrap. A recipient of the Ramiro Melendreras Prize from the Statistics and Operations Research Society of Spain (2001), Molina also received the Doctoral Prize for Excellence from Miguel Hernández University (2005). Molina is an active member of the Statistics and Operations Research Society of Spain where she currently serves on the Liaison Committee with Companies.

J.N.K. Rao is Distinguished Research Professor at Carleton University. Rao consults regularly for Statistics Canada; he is also a Member of Statistics Canada’s Advisory Committee on Methodology. He received an Honorary Doctor of Mathematics degree from the University of Waterloo in 2008. Rao’s research interests in survey sampling include small area estimation, missing data and imputation, empirical likelihood methods, re-sampling methods for variance estimation, analysis of survey data, multiple frame surveys and inferential issues. In addition to his prolific and distinguished research record, Rao is the author of the 2003 Wiley book Small Area Estimation. A recipient of the Waksberg Award (2004) for survey methodology, he also was awarded the Gold Medal of the Statistical Society of Canada (1993). Rao is listed as ISI Highly Cited Researcher in Mathematical Sciences. He is a Fellow of the American Statistical Association, the Institute of Mathematical Statistics and the Royal Society of Canada.