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Temporally Consistent Present Population from Mobile Network Signaling Data for Official Statistics Journal of Official Statistics (IF 1.1) Pub Date : 2023-12-10 Milena Suarez Castillo, Francois Sémécurbe, Cezary Ziemlicki, Haixuan Xavier Tao, Tom Seimandi
Mobile network data records are promising for measuring temporal changes in present populations. This promise has been boosted since high-frequency passively-collected signaling data became available. Its temporal event rate is considerably higher than that of Call Detail Records – on which most of the previous literature is based. Yet, we show it remains a challenge to produce statistics consistent
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Block Weighted Least Squares Estimation for Nonlinear Cost-based Split Questionnaire Design Journal of Official Statistics (IF 1.1) Pub Date : 2023-12-10 Yang Li, Le Qi, Yichen Qin, Cunjie Lin, Yuhong Yang
In this study, we advocate a two-stage framework to deal with the issues encountered in surveys with long questionnaires. In Stage I, we propose a split questionnaire design (SQD) developed by minimizing a quadratic cost function while achieving reliability constraints on estimates of means, which effectively reduces the survey cost, alleviates the burden on the respondents, and potentially improves
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Answering Current Challenges of and Changes in Producing Official Time Use Statistics Using the Data Collection Platform MOTUS Journal of Official Statistics (IF 1.1) Pub Date : 2023-12-10 Joeri Minnen, Sven Rymenants, Ignace Glorieux, Theun Pieter van Tienoven
The modernization of the production of official statistics faces challenges related to technological developments, budget cuts, and growing privacy concerns. At the same time, there is a need for shareable and scalable platforms to support comparable data, leading to several online data collection strategies being rolled out. Time Use Surveys (TUS) are particularly affected by these challenges and
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Small Area Estimates of Poverty Incidence in Costa Rica under a Structure Preserving Estimation (SPREE) Approach Journal of Official Statistics (IF 1.1) Pub Date : 2023-12-10 Alejandra Arias-Salazar
Obtaining reliable estimates in small areas is a challenge because of the coverage and periodicity of data collection. Several techniques of small area estimation have been proposed to produce quality measures in small areas, but few of them are focused on updating these estimates. By combining the attributes of the most recent versions of the structure-preserving estimation methods, this article proposes
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Small Area with Multiply Imputed Survey Data Journal of Official Statistics (IF 1.1) Pub Date : 2023-12-10 Marina Runge, Timo Schmid
In this article, we propose a framework for small area estimation with multiply imputed survey data. Many statistical surveys suffer from (a) high nonresponse rates due to sensitive questions and response burden and (b) too small sample sizes to allow for reliable estimates on (unplanned) disaggregated levels due to budget constraints. One way to deal with missing values is to replace them by several
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Application of Sampling Variance Smoothing Methods for Small Area Proportion Estimation Journal of Official Statistics (IF 1.1) Pub Date : 2023-12-10 Yong You, Mike Hidiroglou
Sampling variance smoothing is an important topic in small area estimation. In this article, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed
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Letter to Editor Quality of 2017 Population Census of Pakistan by Age and Sex Journal of Official Statistics (IF 1.1) Pub Date : 2023-09-07 Asif Wazir, Anne Goujon
This Letter to Editor is a supplement to the previously published article in the Journal of Official Statistics (Wazir and Goujon 2021). In 2021, a reconstruction method using demographic analysis for assessing the quality and validity of the 2017 census data has been applied, by critically investigating the demographic changes in the intercensal period at national and provincial levels. However, at
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A Rejoinder to Garfinkel (2023) – Legacy Statistical Disclosure Limitation Techniques for Protecting 2020 Decennial US Census: Still a Viable Option Journal of Official Statistics (IF 1.1) Pub Date : 2023-09-07 Krishnamurty Muralidhar, Josep Domingo-Ferrer
In our article “Database Reconstruction Is Not So Easy and Is Different from Reidentification”, we show that reconstruction can be averted by properly using traditional statistical disclosure control (SDC) techniques, also sometimes called legacy statistical disclosure limitation (SDL) techniques. Furthermore, we also point out that, even if reconstruction can be performed, it does not imply reidentification
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Database Reconstruction Is Not So Easy and Is Different from Reidentification Journal of Official Statistics (IF 1.1) Pub Date : 2023-09-07 Krishnamurty Muralidhar, Josep Domingo-Ferrer
In recent years, it has been claimed that releasing accurate statistical information on a database is likely to allow its complete reconstruction. Differential privacy has been suggested as the appropriate methodology to prevent these attacks. These claims have recently been taken very seriously by the U.S. Census Bureau and led them to adopt differential privacy for releasing U.S. Census data. This
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Comment to Mulalidhar and Domingo-Ferrer (2023) – Legacy Statistical Disclosure Limitation Techniques Were Not An Option for the 2020 US Census of Population And Housing Journal of Official Statistics (IF 1.1) Pub Date : 2023-09-07 Simson Garfinkel
The Article Database Reconstruction is Not So Easy and Is Different from Reidentification, by Krish Muralidhar and Josep Domingo-Ferrer, is an extended attack on the decision of the U.S. Census Bureau to turn its back on legacy statistical disclosure limitation techniques and instead use a bespoke algorithm based on differential privacy to protect the published data products of the Census Bureau’s
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Looking for a New Approach to Measuring the Spatial Concentration of the Human Population Journal of Official Statistics (IF 1.1) Pub Date : 2023-09-07 Federico Benassi, Massimo Mucciardi, Giovanni Pirrotta
In the article a new approach for measuring the spatial concentration of human population is presented and tested. The new procedure is based on the concept of concentration introduced by Gini and, at the same time, on its spatial extension (i.e., taking into account the concept of spatial autocorrelation, polarization). The proposed indicator, the Spatial Gini Index, is then computed by using two
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A Note on the Optimum Allocation of Resources to Follow up Unit Nonrespondents in Probability Surveys Journal of Official Statistics (IF 1.1) Pub Date : 2023-09-07 Siu-Ming Tam, Anders Holmberg, Summer Wang
Common practice to address nonresponse in probability surveys in National Statistical Offices is to follow up every non respondent with a view to lifting response rates. As response rate is an insufficient indicator of data quality, it is argued that one should follow up non respondents with a view to reducing the mean squared error (MSE) of the estimator of the variable of interest. In this article
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Predicting Days to Respondent Contact in Cross-Sectional Surveys Using a Bayesian Approach Journal of Official Statistics (IF 1.1) Pub Date : 2023-09-07 Stephanie Coffey, Michael R. Elliott
Surveys estimate and monitor a variety of data collection parameters, including response propensity, number of contacts, and data collection costs. These parameters can be used as inputs to a responsive/adaptive design or to monitor the progression of a data collection period against predefined expectations. Recently, Bayesian methods have emerged as a method for combining historical information or
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Towards Demand-Driven On-The-Fly Statistics Journal of Official Statistics (IF 1.1) Pub Date : 2023-09-07 Tjalling Gelsema, Guido van den Heuvel
A prototype of a question answering (QA) system, called Farseer, for the real-time calculation and dissemination of aggregate statistics is introduced. Using techniques from natural language processing (NLP), machine learning (ML), artificial intelligence (AI) and formal semantics, this framework is capable of correctly interpreting a written request for (aggregate) statistics and subsequently generating
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Effects of Changing Modes on Item Nonresponse in Panel Surveys Journal of Official Statistics (IF 1.1) Pub Date : 2023-06-09 Oliver Lipps, Marieke Voorpostel, Gian-Andrea Monsch
To investigate the effect of a change from the telephone to the web mode on item nonresponse in panel surveys, we use experimental data from a two-wave panel survey. The treatment group changed from the telephone to the web mode after the first wave, while the control group continued in the telephone mode. We find that when changing to the web, “don’t know” answers increase moderately from a low level
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Adjusting for Selection Bias in Nonprobability Samples by Empirical Likelihood Approach Journal of Official Statistics (IF 1.1) Pub Date : 2023-06-09 Daniela Marella
Large amount of data are today available, that are easier and faster to collect than survey data, bringing new challenges. One of them is the nonprobability nature of these big data that may not represent the target population properly and hence result in highly biased estimators. In this article two approaches for dealing with selection bias when the selection process is nonignorable are discussed
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Estimating Intra-Regional Inequality with an Application to German Spatial Planning Regions Journal of Official Statistics (IF 1.1) Pub Date : 2023-06-09 Marina Runge
Income inequality is a persistent topic of public and political debate. In this context, the focus often shifts from the national level to a more detailed geographical level. In particular, inequality between or within local communities can be assessed. In this article, the estimation of inequality within regions, that is, between households, is considered at a regionally disaggregated level. From
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Design and Sample Size Determination for Experiments on Nonresponse Followup using a Sequential Regression Model Journal of Official Statistics (IF 1.1) Pub Date : 2023-06-09 Andrew M. Raim, Thomas Mathew, Kimberly F. Sellers, Renee Ellis, Mikelyn Meyers
Statistical agencies depend on responses to inquiries made to the public, and occasionally conduct experiments to improve contact procedures. Agencies may wish to assess whether there is significant change in response rates due to an operational refinement. This work considers the assessment of response rates when up to L attempts are made to contact each subject, and subjects receive one of J possible
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Constructing Building Price Index Using Administrative Data Journal of Official Statistics (IF 1.1) Pub Date : 2023-06-09 Masahiro Higo, Yumi Saita, Chihiro Shimizu, Yuta Tachi
Improving the accuracy of deflators is crucial for measuring real GDP and growth rates. However, construction prices are often difficult to measure. This study uses the stratification and hedonic methods to estimate price indices. The estimated indices are based on the actual transaction prices of buildings (contract prices) obtained from the Statistics on Building Starts survey information from the
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From Quarterly to Monthly Turnover Figures Using Nowcasting Methods Journal of Official Statistics (IF 1.1) Pub Date : 2023-06-09 Daan Zult, Sabine Krieg, Bernd Schouten, Pim Ouwehand, Jan van den Brakel
Short-term business statistics at Statistics Netherlands are largely based on Value Added Tax (VAT) administrations. Companies may decide to file their tax return on a monthly, quarterly, or annual basis. Most companies file their tax return quarterly. So far, these VAT based short-term business statistics are published with a quarterly frequency as well. In this article we compare different methods
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Using Eye-Tracking Methodology to Study Grid Question Designs in Web Surveys Journal of Official Statistics (IF 1.1) Pub Date : 2023-03-16 Cornelia E. Neuert, Joss Roßmann, Henning Silber
Grid questions are frequently employed in web surveys due to their assumed response efficiency. In line with this, many previous studies have found shorter response times for grid questions compared to item-by-item formats. Our contribution to this literature is to investigate how altering the question format affects response behavior and the depth of cognitive processing when answering both grid question
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Characteristics of Respondents to Web-Based or Traditional Interviews in Mixed-Mode Surveys. Evidence from the Italian Permanent Population Census Journal of Official Statistics (IF 1.1) Pub Date : 2023-03-16 Elena Grimaccia, Alessia Naccarato, Gerardo Gallo, Novella Cecconi, Alessandro Fratoni
In order to provide useful tools for researchers in the design of actions to promote participation in web surveys, it is key to study the characteristics that define the profile of a “web respondent”, so that specific interventions can be planned. In this contribution, which draws on data collected during the 2019 housing population census in Italy, we define the set of familial and geographical characteristics
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A Two-Stage Bennet Decomposition of the Change in the Weighted Arithmetic Mean Journal of Official Statistics (IF 1.1) Pub Date : 2023-03-16 Thomas von Brasch, Håkon Grini, Magnus Berglund Johnsen, Trond Christian Vigtel
The weighted arithmetic mean is used in a wide variety of applications. An infinite number of possible decompositions of the change in the weighted mean are available, and it is therefore an open question which of the possible decompositions should be applied. In this article, we derive a decomposition of the change in the weighted mean based on a two-stage Bennet decomposition. Our proposed decomposition
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Investigating an Alternative for Estimation from a Nonprobability Sample: Matching plus Calibration Journal of Official Statistics (IF 1.1) Pub Date : 2023-03-16 Zhan Liu, Richard Valliant
Matching a nonprobability sample to a probability sample is one strategy both for selecting the nonprobability units and for weighting them. This approach has been employed in the past to select subsamples of persons from a large panel of volunteers. One method of weighting, introduced here, is to assign a unit in the nonprobability sample the weight from its matched case in the probability sample
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A Multivariate Regression Estimator of Levels and Change for Surveys Over Time Journal of Official Statistics (IF 1.1) Pub Date : 2023-03-16 Anne Konrad, Yves Berger
Rotations are often used for panel surveys, where the observations remain in the sample for a predefined number of periods and then rotate out. The information of previous waves can be exploited to improve current estimates. We propose a multivariate regression estimator which captures all information available from both waves. By adding additional auxiliary variables describing the information of
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A Statistical Comparison of Call Volume Uniformity Due to Mailing Strategy Journal of Official Statistics (IF 1.1) Pub Date : 2023-03-16 Andrew M. Raim, Elizabeth Nichols, Thomas Mathew
For operations such as a decennial census, the U.S. Census Bureau sends mail to potential respondents inviting a self-response. It is suspected that the mailing strategy affects the distribution of call volumes to the U.S. Census Bureau's telephone helplines. For staffing purposes, more uniform call volumes throughout the week are desirable. In this work, we formulate tests and confidence intervals
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Analyzing the Association of Objective Burden Measures to Perceived Burden with Regression Trees Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Daniel K. Yang, Daniell S. Toth
Higher levels of perceived burden by respondents can lead to ambiguous responses to a questionnaire, item nonresponse, or refusals to continue participation in the survey which can introduce bias and downgrade the quality of the data. Therefore, it is important to understand what might influence the perception of burden in respondents. In this article, we demonstrate, using U.S. Consumer Expenditure
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Relationship Between Past Survey Burden and Response Probability to a New Survey in a Probability-Based Online Panel Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Haomiao Jin, Arie Kapteyn
We conducted an idiographic analysis to examine the effect of survey burden, measured by the length of the most recent questionnaire, or number of survey invitations (survey frequency) in a one-year period preceding a new survey, on the response probability to a new survey in a probability-based Internet panel. The individual response process was modeled by a latent Markov chain with questionnaire
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Your Best Estimate is Fine. Or is It? Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Jerry Timbrook, Kristen Olson, Jolene D. Smyth
Providing an exact answer to open-ended numeric questions can be a burdensome task for respondents. Researchers often assume that adding an invitation to estimate (e.g., “Your best estimate is fine”) to these questions reduces cognitive burden, and in turn, reduces rates of undesirable response behaviors like item nonresponse, nonsubstantive answers, and answers that must be processed into a final
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Response Burden – Review and Conceptual Framework Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Ting Yan, Douglas Williams
Concerns about the burden that surveys place on respondents have a long history in the survey field. This article reviews existing conceptualizations and measurements of response burden in the survey literature. Instead of conceptualizing response burden as a one-time overall outcome, we expand the conceptual framework of response burden by positing response burden as reflecting a continuous evaluation
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A User-Driven Method for Using Research Products to Empirically Assess Item Importance in National Surveys Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Ai Rene Ong, Robert Schultz, Sofi Sinozich, Jennifer Sinibaldi, Brady T West, James Wagner, John Finamore
Large-scale, nationally representative surveys serve many vital functions, but these surveys can be long and burdensome for respondents. Cutting survey length can help to reduce respondent burden and may improve data quality but removing items from these surveys is not a trivial matter. We propose a method to empirically assess item importance and associated burden in national surveys and guide this
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The Effect of Burdensome Survey Questions on Data Quality in an Omnibus Survey Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Angelica Phillips, Rachel Stenger
In interviewer-administered omnibus surveys, burdensome questions asked early in a survey may result in lower quality responses to questions asked later in a survey. Two examples of these burdensome questions are social network questions, wherein respondents are asked about members of their personal network, and knowledge questions, wherein respondents are asked to provide a factually correct response
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Exploring Burden Perceptions of Household Survey Respondents in the American Community Survey Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Jessica Holzberg, Jonathan Katz
Minimizing respondent survey burden may help decrease nonresponse and increase data quality, but the measurement of burden has varied widely. Recent efforts have paid more attention to respondents’ subjective perceptions of burden, measured through the addition of questions to a survey. Despite reliance on these questions as key measures, little qualitative research has been conducted for household
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Determination of the Threshold in Cutoff Sampling Using Response Burden with an Application to Intrastat Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Sašo Polanec, Paul A. Smith, Mojca Bavdaž
Statistical offices frequently use cutoff sampling to determine which businesses in a population should be surveyed. Examples include business surveys about international trade, production, innovation, ICT usage and so on. Cutoff thresholds are typically set in terms of key variables of interest and aim to satisfy a minimum coverage ratio–the share of aggregate values of reporting units. In this article
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Modeling the Relationship between Proxy Measures of Respondent Burden and Survey Response Rates in a Household Panel Survey Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Morgan Earp, Robin Kaplan, Daniell Toth
Respondent burden has important implications for survey outcomes, including response rates and attrition in panel surveys. Despite this, respondent burden remains an understudied topic in the field of survey methodology, with few researchers systematically measuring objective and subjective burden factors in surveys used to produce official statistics. This research was designed to assess the impact
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Testing a Planned Missing Design to Reduce Respondent Burden in Web and SMS Administrations of the CAHPS Clinician and Group Survey (CG-CAHPS) Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Philip S. Brenner, J. Lee Hargraves, Carol Cosenza
We test a planned missing design to reduce respondent burden in Web and SMS administrations of the CAHPS Clinician and Group Survey (CG-CAHPS), a survey of patient experiences widely used by health care providers. Members of an online nonprobability panel were randomly assigned to one of three invitation and data collection mode protocols: email invitation to a Web survey, SMS invitation to a Web survey
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The Effects of Response Burden – Collecting Life History Data in a Self-Administered Mixed-Device Survey Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Johann Carstensen, Sebastian Lang, Fine Cordua
Collecting life history data is highly demanding and therefore prone to error since respondents must retrieve and provide extensive complex information. Research has shown that response burden is an important factor influencing data quality. We examine whether increases in different measures of response burden in a (mixed-device) online survey lead to adverse effects on the data quality and whether
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Response Burden and Dropout in a Probability-Based Online Panel Study – A Comparison between an App and Browser-Based Design Journal of Official Statistics (IF 1.1) Pub Date : 2022-12-06 Caroline Roberts, Jessica M.E. Herzing, Marc Asensio Manjon, Philip Abbet, Daniel Gatica-Perez
Survey respondents can complete web surveys using different Internet-enabled devices (PCs versus mobile phones and tablets) and using different software (web browser versus a mobile software application, “app”). Previous research has found that completing questionnaires via a browser on mobile devices can lead to higher breakoff rates and reduced measurement quality compared to using PCs, especially
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Measuring and Mapping Micro Level Earning Inequality towards Addressing the Sustainable Development Goals – A Multivariate Small Area Modelling Approach Journal of Official Statistics (IF 1.1) Pub Date : 2022-09-13 Saurav Guha, Hukum Chandra
The earning inequality in India has unfavorably obstructed underprivileged in accessing elementary needs like health and education. Periodic labour force survey conducted by National Statistical Office of India generates estimates on earning status at national and state level for both rural and urban sectors separately. However, due to small sample size problem, these surveys cannot generate reliable
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Pseudo Bayesian Mixed Models under Informative Sampling Journal of Official Statistics (IF 1.1) Pub Date : 2022-09-13 Terrance D. Savitsky, Matthew R. Williams
When random effects are correlated with survey sample design variables, the usual approach of employing individual survey weights (constructed to be inversely proportional to the unit survey inclusion probabilities) to form a pseudo-likelihood no longer produces asymptotically unbiased inference. We construct a weight-exponentiated formulation for the random effects distribution that achieves approximately
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Timely Estimates of the Monthly Mexican Economic Activity Journal of Official Statistics (IF 1.1) Pub Date : 2022-09-13 Francisco Corona, Graciela González-Farías, Jesús López-Pérez
In this article, we present a new approach based on dynamic factor models (DFMs) to perform accurate nowcasts for the percentage annual variation of the Mexican Global Economic Activity Indicator (IGAE), the commonly used variable as an approximation of monthly GDP. The procedure exploits the contemporaneous relationship of the timely traditional macroeconomic time series and nontraditional variables
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Economic Nowcasting with Long Short-Term Memory Artificial Neural Networks (LSTM) Journal of Official Statistics (IF 1.1) Pub Date : 2022-09-13 Daniel Hopp
Artificial neural networks (ANNs) have been the catalyst to numerous advances in a variety of fields and disciplines in recent years. Their impact on economics, however, has been comparatively muted. One type of ANN, the long short-term memory network (LSTM), is particularly well-suited to deal with economic time-series. Here, the architecture’s performance and characteristics are evaluated in comparison
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Identifying Data Quality Challenges in Online Opt-In Panels Using Cognitive Interviews in English and Spanish Journal of Official Statistics (IF 1.1) Pub Date : 2022-09-13 Yazmín García Trejo, Mikelyn Meyers, Mandi Martinez, Angela O’Brien, Patricia Goerman, Betsarí Otero Class
In this article, we evaluate how the analysis of open-ended probes in an online cognitive interview can serve as a metric to identify cases that should be excluded due to disingenuous responses by ineligible respondents. We analyze data collected in 2019 via an online opt-in panel in English and Spanish to pretest a public opinion questionnaire (n = 265 in English and 199 in Spanish). We find that
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Variable Inclusion Strategies through Directed Acyclic Graphs to adjust Health Surveys subject to Selection Bias for Producing National Estimates Journal of Official Statistics (IF 1.1) Pub Date : 2022-09-13 Yan Li, Katherine E. Irimata, Yulei He, Jennifer Parker
Along with the rapid emergence of web surveys to address time-sensitive priority topics, various propensity score (PS)-based adjustment methods have been developed to improve population representativeness for nonprobability- or probability-sampled web surveys subject to selection bias. Conventional PS-based methods construct pseudo-weights for web samples using a higher-quality reference probability
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Small Domain Estimation of Census Coverage – A Case Study in Bayesian Analysis of Complex Survey Data Journal of Official Statistics (IF 1.1) Pub Date : 2022-09-13 Joane S. Elleouet, Patrick Graham, Nikolai Kondratev, Abby K. Morgan, Rebecca M. Green
Many countries conduct a full census survey to report official population statistics. As no census survey ever achieves 100% response rate, a post-enumeration survey (PES) is usually conducted and analysed to assess census coverage and produce official population estimates by geographic area and demographic attributes. Considering the usually small size of PES, direct estimation at the desired level
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Hierarchical Bayesian Model with Inequality Constraints for US County Estimates Journal of Official Statistics (IF 1.1) Pub Date : 2022-09-13 Lu Chen, Balgobin Nandram, Nathan B. Cruze
In the production of US agricultural official statistics, certain inequality and benchmarking constraints must be satisfied. For example, available administrative data provide an accurate lower bound for the county-level estimates of planted acres, produced by the U.S. Department of Agriculture’s (USDA) National Agricultural statistics Services (NASS). In addition, the county-level estimates within
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Construction of Databases for Small Area Estimation Journal of Official Statistics (IF 1.1) Pub Date : 2022-09-13 Emily Berg
The demand for small area estimates can conflict with the objective of producing a multi-purpose data set. We use donor imputation to construct a database that supports small area estimation. Appropriately weighted sums of observed and imputed values produce model-based small area estimates. We develop imputation procedures for both unit-level and area-level models. For area-level models, we restrict
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A simulation study of diagnostics for selection bias. Journal of Official Statistics (IF 1.1) Pub Date : 2021-09-12 Philip S Boonstra,Roderick J A Little,Brady T West,Rebecca R Andridge,Fernanda Alvarado-Leiton
A non-probability sampling mechanism arising from non-response or non-selection is likely to bias estimates of parameters with respect to a target population of interest. This bias poses a unique challenge when selection is 'non-ignorable', i.e. dependent upon the unobserved outcome of interest, since it is then undetectable and thus cannot be ameliorated. We extend a simulation study by Nishimura
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Weighted Dirichlet Process Mixture Models to Accommodate Complex Sample Designs for Linear and Quantile Regression. Journal of Official Statistics (IF 1.1) Pub Date : 2021-03-12 Michael R Elliott,Xi Xia
Standard randomization-based inference conditions on the data in the population and makes inference with respect to the repeating sampling properties of the sampling indicators. In some settings these estimators can be quite unstable; Bayesian model-based approaches focus on the posterior predictive distribution of population quantities, potentially providing a better balance between bias correction
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Comparing the Ability of Regression Modeling and Bayesian Additive Regression Trees to Predict Costs in a Responsive Survey Design Context. Journal of Official Statistics (IF 1.1) Pub Date : 2020-12-09 James Wagner,Brady T West,Michael R Elliott,Stephanie Coffey
Responsive survey designs rely upon incoming data from the field data collection to optimize cost and quality tradeoffs. In order to make these decisions in real-time, survey managers rely upon monitoring tools that generate proxy indicators for cost and quality. There is a developing literature on proxy indicators for the risk of nonresponse bias. However, there is very little research on proxy indicators
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Implementing Adaptive Survey Design With an Application to the Dutch Health Survey Journal of Official Statistics (IF 1.1) Pub Date : 2020-09-01 Kees van Berkel, Suzanne van der Doef, Barry Schouten
Abstract Adaptive survey design has attracted great interest in recent years, but the number of case studies describing actual implementation is still thin. Reasons for this may be the gap between survey methodology and data collection, practical complications in differentiating effort across sample units and lack of flexibility of survey case management systems. Currently, adaptive survey design is
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Survey Nonresponse Trends and Fieldwork Effort in the 21st Century: Results of an International Study across Countries and Surveys Journal of Official Statistics (IF 1.1) Pub Date : 2020-09-01 Annemieke Luiten, Joop Hox, Edith de Leeuw
Abstract For more than three decades, declining response rates have been of concern to both survey methodologists and practitioners. Still, international comparative studies have been scarce. In one of the first international trend analyses for the period 1980–1997, De Leeuw and De Heer (2002) describe that response rates declined over the years and that countries differed in response rates and nonresponse
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Working with Response Probabilities Journal of Official Statistics (IF 1.1) Pub Date : 2020-09-01 Jelke Bethlehem
Abstract Sample surveys are often affected by nonresponse. These surveys have in common that their outcomes depend at least partly on a human decision whether or not to participate. If it would be completely clear how this decision mechanism works, estimates could be corrected. An often used approach is to introduce the concept of the response probability. Of course, these probabilities are a theoretical
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Measurement of Interviewer Workload within the Survey and an Exploration of Workload Effects on Interviewers’ Field Efforts and Performance Journal of Official Statistics (IF 1.1) Pub Date : 2020-09-01 Celine Wuyts, Geert Loosveldt
Abstract Interviewer characteristics are usually assumed fixed over the fieldwork period. The number of sample units that require the interviewers’ attention, however, can vary strongly over the fieldwork period. Different workload levels produce different constraints on the time interviewers have available to contact, recruit and interview each target respondent, and may also induce different motivational
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The Effects of Nonresponse and Sampling Omissions on Estimates on Various Topics in Federal Surveys: Telephone and IVR Surveys of Address-Based Samples Journal of Official Statistics (IF 1.1) Pub Date : 2020-09-01 Floyd J. Fowler, Philip Brenner, Anthony M. Roman, J. Lee Hargraves
Abstract With declining response rates and challenges of using RDD sampling for telephone surveys, collecting data from address-based samples has become more attractive. Two approaches are doing telephone interviews at telephone numbers matched to addresses and asking those at sampled addresses to call into an Interactive Voice Response (IVR) system to answer questions. This study used in-person interviewing
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Preface Journal of Official Statistics (IF 1.1) Pub Date : 2020-09-01 Edith de Leeuw, Annemieke Luiten, Ineke Stoop
The response rate is frequently seen as the most important criterion for assessing the quality of a survey. Every survey methodologist, however, knows that the response rate of a survey tells only part of the story. There is more than meets the eye and both response rates and the composition of survey nonresponse should be evaluated critically. There are multiple reasons for this. First, response rates
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Continuing to Explore the Relation between Economic and Political Factors and Government Survey Refusal Rates: 1960–2015 Journal of Official Statistics (IF 1.1) Pub Date : 2020-09-01 Luke J. Larsen, Joanna Fane Lineback, Benjamin M. Reist
Abstract In the United States, government surveys’ refusal rates have been increasing at an alarming rate, despite traditional measures for mitigating nonresponse. Given this phenomenon, now is a good time to revisit the work of Harris-Kojetin and Tucker (1999). In that study, the authors explored the relation between economic and political conditions on Current Population Survey (CPS) refusal rates
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A Validation of R-Indicators as a Measure of the Risk of Bias using Data from a Nonresponse Follow-Up Survey Journal of Official Statistics (IF 1.1) Pub Date : 2020-09-01 Caroline Roberts, Caroline Vandenplas, Jessica M.E. Herzing
Abstract R-indicators are increasingly used as nonresponse bias indicators. However, their effectiveness depends on the auxiliary data used in their estimation. Because of this, it is not always clear for practitioners what the magnitude of the R-indicator implies for bias in other survey variables, or how adjustment on auxiliary variables will affect it. In this article, we investigate these potential
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Evolution of the Initially Recruited SHARE Panel Sample Over the First Six Waves Journal of Official Statistics (IF 1.1) Pub Date : 2020-09-01 Sabine Friedel, Tim Birkenbach
Abstract Attrition is a frequently observed phenomenon in panel studies. The loss of panel members over time can hamper the analysis of panel survey data. Based on data from the Survey of Health, Ageing and Retirement in Europe (SHARE), this study investigates changes in the composition of the initially recruited first-wave sample in a multi-national face-to-face panel survey of an older population
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Assessing Interviewer Performance in Approaching Reissued Initial Nonrespondents Journal of Official Statistics (IF 1.1) Pub Date : 2020-09-01 Laurie Peeters, David De Coninck, Celine Wuyts, Geert Loosveldt
Abstract Nonresponse is a repeatedly reported concern in survey research. In this article, we investigate the technique of reissuing nonrespondents to another interviewer and attempting to convert them into respondents, using data of Rounds 7 and 8 of the European Social Survey (ESS) in Belgium. The results show no marked differences between respondents interviewed by the more and the less successful