Constructing sociodemographic indicators for national statistical institutes by using mobile phone data: estimating literacy rates in Senegal
Modern systems of official statistics require the accurate and timely estimation of sociodemographic indicators for disaggregated geographical regions. Traditional data collection methods such as censuses or household surveys impose great financial and organizational burdens on national statistical...
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| Published in | Journal of the Royal Statistical Society. Series A, Statistics in society Vol. 180; no. 4; pp. 1163 - 1190 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford
John Wiley & Sons Ltd
01.10.2017
Oxford University Press |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Modern systems of official statistics require the accurate and timely estimation of sociodemographic indicators for disaggregated geographical regions. Traditional data collection methods such as censuses or household surveys impose great financial and organizational burdens on national statistical institutes. The rise of new information and communication technologies offers promising sources to mitigate these shortcomings. We propose a unified approach for national statistical institutes in developing countries based on small area estimation that allows for the estimation of sociodemographic indicators by using mobile phone data. In particular, the methodology is applied to mobile phone data from Senegal for deriving subnational estimates of the share of illiterates disaggregated by gender. The estimates are used to identify hotspots of illiterates with a need for additional infrastructure or policy adjustments. Although we focus on literacy as a particular sociodemographic indicator, the approach proposed is applicable to indicators from national statistics in general. |
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| AbstractList | Summary
Modern systems of official statistics require the accurate and timely estimation of sociodemographic indicators for disaggregated geographical regions. Traditional data collection methods such as censuses or household surveys impose great financial and organizational burdens on national statistical institutes. The rise of new information and communication technologies offers promising sources to mitigate these shortcomings. We propose a unified approach for national statistical institutes in developing countries based on small area estimation that allows for the estimation of sociodemographic indicators by using mobile phone data. In particular, the methodology is applied to mobile phone data from Senegal for deriving subnational estimates of the share of illiterates disaggregated by gender. The estimates are used to identify hotspots of illiterates with a need for additional infrastructure or policy adjustments. Although we focus on literacy as a particular sociodemographic indicator, the approach proposed is applicable to indicators from national statistics in general. Modern systems of official statistics require the accurate and timely estimation of sociodemographic indicators for disaggregated geographical regions. Traditional data collection methods such as censuses or household surveys impose great financial and organizational burdens on national statistical institutes. The rise of new information and communication technologies offers promising sources to mitigate these shortcomings. We propose a unified approach for national statistical institutes in developing countries based on small area estimation that allows for the estimation of sociodemographic indicators by using mobile phone data. In particular, the methodology is applied to mobile phone data from Senegal for deriving subnational estimates of the share of illiterates disaggregated by gender. The estimates are used to identify hotspots of illiterates with a need for additional infrastructure or policy adjustments. Although we focus on literacy as a particular sociodemographic indicator, the approach proposed is applicable to indicators from national statistics in general. |
| Author | Zbiranski, Till Bruckschen, Fabian Schmid, Timo Salvati, Nicola |
| Author_xml | – sequence: 1 givenname: Timo surname: Schmid fullname: Schmid, Timo – sequence: 2 givenname: Fabian surname: Bruckschen fullname: Bruckschen, Fabian – sequence: 3 givenname: Nicola surname: Salvati fullname: Salvati, Nicola – sequence: 4 givenname: Till surname: Zbiranski fullname: Zbiranski, Till |
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| Cites_doi | 10.1126/science.1186605 10.1002/sim.6219 10.1111/j.1467-9469.2011.00773.x 10.1214/07-AOS512 10.1093/jssam/smu026 10.1111/1468-0262.00399 10.1007/978-3-642-37210-0_6 10.1002/9781118814963.ch20 10.1023/A:1012410420337 10.1111/j.1467-9868.2006.00542.x 10.1080/01621459.1979.10482505 10.1016/j.jmva.2013.10.012 10.1198/016214506000001293 10.1080/01621459.1974.10480222 10.1080/01621459.1990.10475320 10.1111/rssa.12085 10.1002/cjs.10051 10.1111/rssa.12123 10.1016/j.spasta.2014.07.001 10.1016/j.csda.2013.09.016 10.1007/s13571-015-0096-0 10.1093/biomet/92.1.183 10.1016/j.jmva.2009.10.009 10.1126/science.aac4420 10.1002/9781118735855 10.1177/1367549413510420 10.1007/s11749-010-0218-y 10.1214/12-STS395 10.1515/jos-2015-0017 10.1073/pnas.1408439111 10.1002/9781118814963 |
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| References | 2009; 25 2007; 102 2014; 70 2010; 38 2015; 16 2013; 28 2015; 3 2012 2010; 328 1950; 21 2015; 31 2015; 77 2010; 101 2008; 36 2007 2012; 39 1971 2003 2003; 71 2014; 111 1979; 74 2014; 40 2015; 350 1994; 9 1990; 85 1974; 69 2010; 20 2001 2006; 68 2000; 10 2015; 178 2016; 179 2017 2016 2005; 92 2015 2014 2014; 17 2013 2012; 66 2014; 33 2001; 53 2014; 10 2014; 124 Molina (2023030410250208700_rssa12305-cit-0032) 2010; 38 Searle (2023030410250208700_rssa12305-cit-0044) 1971 Chandra (2023030410250208700_rssa12305-cit-0007) 2015; 3 United Nations Educational, Scientific and Cultural Organization (2023030410250208700_rssa12305-cit-0047) 2015 Montjoye (2023030410250208700_rssa12305-cit-0034) 2014 Ford (2023030410250208700_rssa12305-cit-0017) 2007 Henderson (2023030410250208700_rssa12305-cit-0023) 1950; 21 Schelle (2023030410250208700_rssa12305-cit-0043) 2013 Ha (2023030410250208700_rssa12305-cit-0021) 2014; 33 Giusti (2023030410250208700_rssa12305-cit-0019) 2012; 66 Yoshimori (2023030410250208700_rssa12305-cit-0049) 2014; 124 Datta (2023030410250208700_rssa12305-cit-0011) 2005; 92 Lahiri (2023030410250208700_rssa12305-cit-0026) 2015; 77 Montjoye (2023030410250208700_rssa12305-cit-0033) 2013 Jiang (2023030410250208700_rssa12305-cit-0024) 2001; 53 Liu (2023030410250208700_rssa12305-cit-0028) 2014; 40 Heil (2023030410250208700_rssa12305-cit-0022) 2014; 17 López-Vizcaíno (2023030410250208700_rssa12305-cit-0029) 2015; 178 Marhuenda (2023030410250208700_rssa12305-cit-0031) 2014; 70 Chatterjee (2023030410250208700_rssa12305-cit-0008) 2008; 36 Casas-Cordero (2023030410250208700_rssa12305-cit-0005) 2016 Chambers (2023030410250208700_rssa12305-cit-0006) 2016; 179 Fay (2023030410250208700_rssa12305-cit-0016) 1979; 74 Carter (2023030410250208700_rssa12305-cit-0004) 1974; 69 Datta (2023030410250208700_rssa12305-cit-0010) 2000; 10 Elbers (2023030410250208700_rssa12305-cit-0015) 2003; 71 Li (2023030410250208700_rssa12305-cit-0027) 2010; 101 Pratesi (2023030410250208700_rssa12305-cit-0040) 2009; 25 Eagle (2023030410250208700_rssa12305-cit-0014) 2010; 328 Dowle (2023030410250208700_rssa12305-cit-0013) 2017 Blumenstock (2023030410250208700_rssa12305-cit-0003) 2015; 350 Ghosh (2023030410250208700_rssa12305-cit-0018) 1994; 9 Jiang (2023030410250208700_rssa12305-cit-0025) 2001 Rao (2023030410250208700_rssa12305-cit-0042) 2015 Villalon (2023030410250208700_rssa12305-cit-0048) 2012 Bell (2023030410250208700_rssa12305-cit-0002) 2015; 16 Groupe Speciale Mobile Association (2023030410250208700_rssa12305-cit-0020) 2015 Porter (2023030410250208700_rssa12305-cit-0037) 2014; 10 Raghunathan (2023030410250208700_rssa12305-cit-0041) 2007; 102 United Nations Educational, Scientific and Cultural Organization (2023030410250208700_rssa12305-cit-0046) 2012 Pratesi (2023030410250208700_rssa12305-cit-0039) 2016 Deville (2023030410250208700_rssa12305-cit-0012) 2014; 111 Opsomer (2023030410250208700_rssa12305-cit-0035) 2012; 39 Slud (2023030410250208700_rssa12305-cit-0045) 2006; 68 Marchetti (2023030410250208700_rssa12305-cit-0030) 2015; 31 Datta (2023030410250208700_rssa12305-cit-0009) 2010; 20 R Core Team (2023030410250208700_rssa12305-cit-0502) 2017 Pfeffermann (2023030410250208700_rssa12305-cit-0036) 2013; 28 Plummer (2023030410250208700_rssa12305-cit-0501) 2003 Prasad (2023030410250208700_rssa12305-cit-0038) 1990; 85 Agence Nationale de la Statistique et de la Demographie (2023030410250208700_rssa12305-cit-0001) 2012 |
| References_xml | – volume: 85 start-page: 163 year: 1990 end-page: 171 article-title: The estimation of the mean squared error of small area estimators publication-title: J. Am. Statist. Ass. – volume: 68 start-page: 239 year: 2006 end-page: 257 article-title: Mean‐squared error estimation in transformed Fay–Herriot models publication-title: J. R. Statist. Soc. – volume: 16 start-page: 563 year: 2015 end-page: 584 article-title: Borrowing information over time in binomial/logit normal models for small area estimation publication-title: Statist. Transn New Ser. – start-page: 48 year: 2013 end-page: 55 – volume: 28 start-page: 40 year: 2013 end-page: 68 article-title: New important developments in small area estimation publication-title: Statist. Sci. – volume: 71 start-page: 355 year: 2003 end-page: 364 article-title: Micro‐level estimation of poverty and inequality publication-title: Econometrica – start-page: 75 year: 2001 end-page: 97 – volume: 178 start-page: 535 year: 2015 end-page: 565 article-title: Small area estimation of labour force indicators under a multinomial model with correlated time and area effects publication-title: J. R. Statist. Soc. – volume: 101 start-page: 882 year: 2010 end-page: 892 article-title: An adjusted maximum likelihood method for solving small area estimation problems publication-title: J. Multiv. Anal. – start-page: 379 year: 2016 end-page: 403 – volume: 21 start-page: 309 year: 1950 end-page: 310 article-title: Estimation of genetic parameters publication-title: Ann. Math. Statist. – year: 2007 – volume: 20 start-page: 574 year: 2010 end-page: 588 article-title: Bayesian benchmarking with applications to small area estimation publication-title: Test – year: 2003 – volume: 69 start-page: 880 year: 1974 end-page: 885 article-title: Empirical bayes methods applied to estimating fire alarm probabilities publication-title: J. Am. Statist. Ass. – volume: 25 start-page: 37 year: 2009 end-page: 53 article-title: Small area estimation in the presence of correlated random area effects publication-title: J. Off. Statist. – volume: 328 start-page: 1029 year: 2010 end-page: 1031 article-title: Network diversity and economic development publication-title: Science – year: 1971 – volume: 111 start-page: 15888 year: 2014 end-page: 15893 article-title: Dynamic population mapping using mobile phone data publication-title: Proc. Natn. Acad. Sci. USA – volume: 74 start-page: 269 year: 1979 end-page: 277 article-title: Estimation of income for small places: an application of James‐Stein procedures to census data publication-title: J. Am. Statist. Ass. – year: 2016 – year: 2014 – volume: 102 start-page: 474 year: 2007 end-page: 486 article-title: Combining information from two surveys to estimate county‐level prevalence rates of cancer risk factors and screening publication-title: J. Am. Statist. Ass. – year: 2012 – volume: 40 start-page: 1 year: 2014 end-page: 13 article-title: Hierarchical bayes modeling of survey‐weighted small area proportions publication-title: Surv. Methodol. – volume: 10 start-page: 27 year: 2014 end-page: 42 article-title: Spatial Fay‐Herriot models for small area estimation with functional covariates publication-title: Spatl Statist. – volume: 10 start-page: 613 year: 2000 end-page: 627 article-title: A unified measure of uncertainty of estimated best linear unbiased predictors in small area estimation problems publication-title: Statist. Sin. – volume: 53 start-page: 217 year: 2001 end-page: 243 article-title: Empirical best prediction for small area inference with binary data publication-title: Ann. Inst. Statist. Math. – volume: 38 start-page: 369 year: 2010 end-page: 385 article-title: Small area estimation of poverty indicators publication-title: Can. J. Statist. – volume: 17 start-page: 452 year: 2014 end-page: 470 article-title: Are neighbours alike?: Practices of conviviality in Catalonia and Casamance publication-title: Eur. J. Cult. Stud. – volume: 33 start-page: 3932 year: 2014 end-page: 3945 article-title: Methods and results for small area estimation using smoking data from the 2008 national health interview survey publication-title: Statist. Med. – volume: 31 start-page: 263 year: 2015 end-page: 281 article-title: Small area model‐based estimators using big data sources publication-title: J. Off. Statist. – volume: 124 start-page: 281 year: 2014 end-page: 294 article-title: A new adjusted maximum likelihood method for the Fay‐Herriot small area model publication-title: J. Multiv. Anal. – volume: 92 start-page: 183 year: 2005 end-page: 196 article-title: On measuring the variability of small area estimators under a basic area level model publication-title: Biometrika – volume: 77 start-page: 312 year: 2015 end-page: 320 article-title: Variable selection for linear mixed models with applications in small area estimation publication-title: Sankhya – volume: 70 start-page: 268 year: 2014 end-page: 280 article-title: Information criteria for Fay‐Herriot model selection publication-title: Computnl Statist. Data Anal. – volume: 39 start-page: 528 year: 2012 end-page: 542 article-title: Model‐based non‐parametric variance estimation for systematic sampling publication-title: Scand. J. Statist. – volume: 179 start-page: 453 year: 2016 end-page: 479 article-title: Semiparametric small area estimation for binary outcomes with application to unemployment estimation for local authorities in the UK publication-title: J. R. Statist. Soc. – year: 2017 – volume: 350 start-page: 1073 year: 2015 end-page: 1076 article-title: Predicting poverty and wealth from mobile phone metadata publication-title: Science – volume: 66 start-page: 1 year: 2012 end-page: 14 article-title: Semiparametric Fay‐Herriot model using penalized splines publication-title: J. Ind. Soc. Agric. Statist. – volume: 36 start-page: 1221 year: 2008 end-page: 1245 article-title: Parametric bootstrap approximation to the distribution of eblup and related prediction intervals in linear mixed models publication-title: Ann. Statist. – volume: 9 start-page: 55 year: 1994 end-page: 93 article-title: Small area estimation: an appraisal publication-title: Statist. Sci. – volume: 3 start-page: 109 year: 2015 end-page: 135 article-title: A spatially nonstationary Fay‐Herriot model for small area estimation publication-title: J. Surv. Statist. Methodol. – year: 2015 – year: 2013 – volume: 328 start-page: 1029 year: 2010 ident: 2023030410250208700_rssa12305-cit-0014 article-title: Network diversity and economic development publication-title: Science doi: 10.1126/science.1186605 contributor: fullname: Eagle – volume: 33 start-page: 3932 year: 2014 ident: 2023030410250208700_rssa12305-cit-0021 article-title: Methods and results for small area estimation using smoking data from the 2008 national health interview survey publication-title: Statist. Med. doi: 10.1002/sim.6219 contributor: fullname: Ha – volume: 39 start-page: 528 year: 2012 ident: 2023030410250208700_rssa12305-cit-0035 article-title: Model-based non-parametric variance estimation for systematic sampling publication-title: Scand. J. Statist. doi: 10.1111/j.1467-9469.2011.00773.x contributor: fullname: Opsomer – volume: 36 start-page: 1221 year: 2008 ident: 2023030410250208700_rssa12305-cit-0008 article-title: Parametric bootstrap approximation to the distribution of eblup and related prediction intervals in linear mixed models publication-title: Ann. Statist. doi: 10.1214/07-AOS512 contributor: fullname: Chatterjee – volume: 21 start-page: 309 year: 1950 ident: 2023030410250208700_rssa12305-cit-0023 article-title: Estimation of genetic parameters publication-title: Ann. Math. Statist. contributor: fullname: Henderson – volume: 3 start-page: 109 year: 2015 ident: 2023030410250208700_rssa12305-cit-0007 article-title: A spatially nonstationary Fay-Herriot model for small area estimation publication-title: J. Surv. Statist. Methodol. doi: 10.1093/jssam/smu026 contributor: fullname: Chandra – volume: 71 start-page: 355 year: 2003 ident: 2023030410250208700_rssa12305-cit-0015 article-title: Micro-level estimation of poverty and inequality publication-title: Econometrica doi: 10.1111/1468-0262.00399 contributor: fullname: Elbers – volume-title: Religion, social demand, and educational reforms in Senegal year: 2012 ident: 2023030410250208700_rssa12305-cit-0048 contributor: fullname: Villalon – start-page: 48 volume-title: Social Computing, Behavioral–Cultural Modeling and Prediction year: 2013 ident: 2023030410250208700_rssa12305-cit-0033 doi: 10.1007/978-3-642-37210-0_6 contributor: fullname: Montjoye – start-page: 379 volume-title: Analysis of Poverty Data by Small Area Estimation year: 2016 ident: 2023030410250208700_rssa12305-cit-0005 doi: 10.1002/9781118814963.ch20 contributor: fullname: Casas-Cordero – volume: 53 start-page: 217 year: 2001 ident: 2023030410250208700_rssa12305-cit-0024 article-title: Empirical best prediction for small area inference with binary data publication-title: Ann. Inst. Statist. Math. doi: 10.1023/A:1012410420337 contributor: fullname: Jiang – volume: 68 start-page: 239 year: 2006 ident: 2023030410250208700_rssa12305-cit-0045 article-title: Mean-squared error estimation in transformed Fay–Herriot models publication-title: J. R. Statist. Soc. doi: 10.1111/j.1467-9868.2006.00542.x contributor: fullname: Slud – volume: 74 start-page: 269 year: 1979 ident: 2023030410250208700_rssa12305-cit-0016 article-title: Estimation of income for small places: an application of James-Stein procedures to census data publication-title: J. Am. Statist. Ass. doi: 10.1080/01621459.1979.10482505 contributor: fullname: Fay – volume-title: Literacy project for girls and women in Senegal year: 2015 ident: 2023030410250208700_rssa12305-cit-0047 contributor: fullname: United Nations Educational, Scientific and Cultural Organization – volume: 124 start-page: 281 year: 2014 ident: 2023030410250208700_rssa12305-cit-0049 article-title: A new adjusted maximum likelihood method for the Fay-Herriot small area model publication-title: J. Multiv. Anal. doi: 10.1016/j.jmva.2013.10.012 contributor: fullname: Yoshimori – volume-title: People treat you as if you are nothing: what good is free education when poverty means children are forced into work? year: 2007 ident: 2023030410250208700_rssa12305-cit-0017 contributor: fullname: Ford – volume-title: Demographic and Health Survey—multiple indicator cluster survey (2010–2011) year: 2012 ident: 2023030410250208700_rssa12305-cit-0001 contributor: fullname: Agence Nationale de la Statistique et de la Demographie – volume: 102 start-page: 474 year: 2007 ident: 2023030410250208700_rssa12305-cit-0041 article-title: Combining information from two surveys to estimate county-level prevalence rates of cancer risk factors and screening publication-title: J. Am. Statist. Ass. doi: 10.1198/016214506000001293 contributor: fullname: Raghunathan – volume: 69 start-page: 880 year: 1974 ident: 2023030410250208700_rssa12305-cit-0004 article-title: Empirical bayes methods applied to estimating fire alarm probabilities publication-title: J. Am. Statist. Ass. doi: 10.1080/01621459.1974.10480222 contributor: fullname: Carter – volume-title: data.table: extension of data.frame year: 2017 ident: 2023030410250208700_rssa12305-cit-0013 contributor: fullname: Dowle – volume: 40 start-page: 1 year: 2014 ident: 2023030410250208700_rssa12305-cit-0028 article-title: Hierarchical bayes modeling of survey-weighted small area proportions publication-title: Surv. Methodol. contributor: fullname: Liu – volume-title: D4d-senegal: the second mobile phone data for development challenge year: 2014 ident: 2023030410250208700_rssa12305-cit-0034 contributor: fullname: Montjoye – volume: 85 start-page: 163 year: 1990 ident: 2023030410250208700_rssa12305-cit-0038 article-title: The estimation of the mean squared error of small area estimators publication-title: J. Am. Statist. Ass. doi: 10.1080/01621459.1990.10475320 contributor: fullname: Prasad – volume: 178 start-page: 535 year: 2015 ident: 2023030410250208700_rssa12305-cit-0029 article-title: Small area estimation of labour force indicators under a multinomial model with correlated time and area effects publication-title: J. R. Statist. Soc. doi: 10.1111/rssa.12085 contributor: fullname: López-Vizcaíno – volume: 38 start-page: 369 year: 2010 ident: 2023030410250208700_rssa12305-cit-0032 article-title: Small area estimation of poverty indicators publication-title: Can. J. Statist. doi: 10.1002/cjs.10051 contributor: fullname: Molina – volume-title: JAGS: a program for analysis of Bayesian graphical models using Gibbs sampling. year: 2003 ident: 2023030410250208700_rssa12305-cit-0501 contributor: fullname: Plummer – volume: 179 start-page: 453 year: 2016 ident: 2023030410250208700_rssa12305-cit-0006 article-title: Semiparametric small area estimation for binary outcomes with application to unemployment estimation for local authorities in the UK publication-title: J. R. Statist. Soc. doi: 10.1111/rssa.12123 contributor: fullname: Chambers – volume: 10 start-page: 27 year: 2014 ident: 2023030410250208700_rssa12305-cit-0037 article-title: Spatial Fay-Herriot models for small area estimation with functional covariates publication-title: Spatl Statist. doi: 10.1016/j.spasta.2014.07.001 contributor: fullname: Porter – volume: 25 start-page: 37 year: 2009 ident: 2023030410250208700_rssa12305-cit-0040 article-title: Small area estimation in the presence of correlated random area effects publication-title: J. Off. Statist. contributor: fullname: Pratesi – volume: 70 start-page: 268 year: 2014 ident: 2023030410250208700_rssa12305-cit-0031 article-title: Information criteria for Fay-Herriot model selection publication-title: Computnl Statist. Data Anal. doi: 10.1016/j.csda.2013.09.016 contributor: fullname: Marhuenda – volume: 77 start-page: 312 year: 2015 ident: 2023030410250208700_rssa12305-cit-0026 article-title: Variable selection for linear mixed models with applications in small area estimation publication-title: Sankhya doi: 10.1007/s13571-015-0096-0 contributor: fullname: Lahiri – start-page: 75 volume-title: Proc. Sem. Funding Opportunity in Survey Research year: 2001 ident: 2023030410250208700_rssa12305-cit-0025 contributor: fullname: Jiang – volume: 92 start-page: 183 year: 2005 ident: 2023030410250208700_rssa12305-cit-0011 article-title: On measuring the variability of small area estimators under a basic area level model publication-title: Biometrika doi: 10.1093/biomet/92.1.183 contributor: fullname: Datta – volume: 16 start-page: 563 year: 2015 ident: 2023030410250208700_rssa12305-cit-0002 article-title: Borrowing information over time in binomial/logit normal models for small area estimation publication-title: Statist. Transn New Ser. contributor: fullname: Bell – volume-title: R: a Language and Environment for Statistical Computing year: 2017 ident: 2023030410250208700_rssa12305-cit-0502 contributor: fullname: R Core Team – volume: 101 start-page: 882 year: 2010 ident: 2023030410250208700_rssa12305-cit-0027 article-title: An adjusted maximum likelihood method for solving small area estimation problems publication-title: J. Multiv. Anal. doi: 10.1016/j.jmva.2009.10.009 contributor: fullname: Li – volume-title: Schulsysteme, Unterricht und Bildung im Mehrsprachigen Frankophonen Westen und Norden Afrikas year: 2013 ident: 2023030410250208700_rssa12305-cit-0043 contributor: fullname: Schelle – volume: 9 start-page: 55 year: 1994 ident: 2023030410250208700_rssa12305-cit-0018 article-title: Small area estimation: an appraisal publication-title: Statist. Sci. contributor: fullname: Ghosh – volume: 66 start-page: 1 year: 2012 ident: 2023030410250208700_rssa12305-cit-0019 article-title: Semiparametric Fay-Herriot model using penalized splines publication-title: J. Ind. Soc. Agric. Statist. contributor: fullname: Giusti – volume: 350 start-page: 1073 year: 2015 ident: 2023030410250208700_rssa12305-cit-0003 article-title: Predicting poverty and wealth from mobile phone metadata publication-title: Science doi: 10.1126/science.aac4420 contributor: fullname: Blumenstock – volume-title: The mobile economy 2015. Groupe Speciale Mobile Association year: 2015 ident: 2023030410250208700_rssa12305-cit-0020 contributor: fullname: Groupe Speciale Mobile Association – volume-title: Linear Models year: 1971 ident: 2023030410250208700_rssa12305-cit-0044 contributor: fullname: Searle – volume: 10 start-page: 613 year: 2000 ident: 2023030410250208700_rssa12305-cit-0010 article-title: A unified measure of uncertainty of estimated best linear unbiased predictors in small area estimation problems publication-title: Statist. Sin. contributor: fullname: Datta – volume-title: Small Area Estimation year: 2015 ident: 2023030410250208700_rssa12305-cit-0042 doi: 10.1002/9781118735855 contributor: fullname: Rao – volume: 17 start-page: 452 year: 2014 ident: 2023030410250208700_rssa12305-cit-0022 article-title: Are neighbours alike?: Practices of conviviality in Catalonia and Casamance publication-title: Eur. J. Cult. Stud. doi: 10.1177/1367549413510420 contributor: fullname: Heil – volume-title: Global partnership for girls’ and women's education year: 2012 ident: 2023030410250208700_rssa12305-cit-0046 contributor: fullname: United Nations Educational, Scientific and Cultural Organization – volume: 20 start-page: 574 year: 2010 ident: 2023030410250208700_rssa12305-cit-0009 article-title: Bayesian benchmarking with applications to small area estimation publication-title: Test doi: 10.1007/s11749-010-0218-y contributor: fullname: Datta – volume: 28 start-page: 40 year: 2013 ident: 2023030410250208700_rssa12305-cit-0036 article-title: New important developments in small area estimation publication-title: Statist. Sci. doi: 10.1214/12-STS395 contributor: fullname: Pfeffermann – volume: 31 start-page: 263 year: 2015 ident: 2023030410250208700_rssa12305-cit-0030 article-title: Small area model-based estimators using big data sources publication-title: J. Off. Statist. doi: 10.1515/jos-2015-0017 contributor: fullname: Marchetti – volume: 111 start-page: 15888 year: 2014 ident: 2023030410250208700_rssa12305-cit-0012 article-title: Dynamic population mapping using mobile phone data publication-title: Proc. Natn. Acad. Sci. USA doi: 10.1073/pnas.1408439111 contributor: fullname: Deville – volume-title: Analysis of Poverty Data by Small Area Estimation year: 2016 ident: 2023030410250208700_rssa12305-cit-0039 doi: 10.1002/9781118814963 contributor: fullname: Pratesi |
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| SubjectTerms | Cell phones Cellular telephones Censuses Communications technology Data collection Developing countries Indicators Information technology Infrastructure LDCs Literacy Mobile phones Model‐based estimation Official statistics Small area estimation Sociodemographics |
| Title | Constructing sociodemographic indicators for national statistical institutes by using mobile phone data: estimating literacy rates in Senegal |
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