scholarly journals An Appraisal of Common Reweighting Methods for Nonresponse in Household Surveys Based on the Norwegian Labour Force Survey and the Statistics on Income and Living Conditions Survey

2020 ◽  
Vol 36 (1) ◽  
pp. 151-172
Author(s):  
Nancy Duong Nguyen ◽  
Li-Chun Zhang
Keyword(s):  
Data Collection ◽  
Labour Force ◽  
Real Data ◽  
Household Surveys ◽  
Labour Force Survey ◽  
Simulation Studies ◽  
Statistical System ◽  
Auxiliary Variables ◽  
Statistical Adjustment ◽  
Design Weights

AbstractDespite increasing efforts during data collection, nonresponse remains sizeable in many household surveys. Statistical adjustment is hence unavoidable. By reweighting the design, weights of the respondents are adjusted to compensate for nonresponse. However, there is no consensus on how this should be carried out in general. Theoretical comparisons are inconclusive in the literature, and the associated simulation studies involve hypothetical situations not all equally relevant to reality. In this article we evaluate the three most common reweighting approaches in practice, based on real data in Norway from the two largest household surveys in the European Statistical System. We demonstrate how cross- examination of various reweighting estimators can help inform the effectiveness of the available auxiliary variables and the choice of the weight adjustment method.

Estimation of the scale of inactive unemployment in Poland

2020 ◽  
Vol 65 (6) ◽  
pp. 11-38
Author(s):  
Kamil Wilak
Keyword(s):  
Labour Force ◽  
Significant Proportion ◽  
Labour Force Survey ◽  
Auxiliary Variables ◽  
Upward Trend ◽  
Unit Level ◽  
Demographic Indicators ◽  
Level Data ◽  
Calibration Approach

The aim of the study described in the paper is to estimate the level of inactive unemployment in Poland. This required the estimation of the number of inactive unemployed and their percentage in the total number of persons registered as unemployed. The estimation was based on unit-level data from the Polish Labour Force Survey (2010–2018). A calibration approach was applied that involved auxiliary variables relating to registered unemployment. The results indicate that a significant proportion of persons registered as unemployed are economically inactive. The percentage of inactive unemployed ranged from 29.8 to 53.3 percent over the studied period, with an upward trend observed since 2014. It was also demonstrated that the level of inactive unemployment varies among groups defined by basic demographic indicators, i.e. sex, age and education. The most pronounced differences can be observed between groups determined by sex – women registered as unemployed are economically inactive much more often than men.

scholarly journals Duality of Female Employment in Pakistan

1991 ◽  
Vol 30 (4II) ◽  
pp. 733-743 ◽  
Author(s):  
Shahnaz Kazi ◽  
Bilquees Raza
Keyword(s):  
Data Collection ◽  
Labour Force ◽  
Female Employment ◽  
Population Census ◽  
Labour Force Survey ◽  
Formal Sector ◽  
Agricultural Census ◽  
Employment Of Women ◽  
Changes Over Time ◽  
Official Data

Before proceeding to the main fmdings of the study it is necessary to briefly mention the problems of data collection on women's employment in Pakistan. The shortcomings of official data sources such as the Labour Force Survey and the Population Census have been pointed out in detail elsewhere [Afzal and Nasir (1987); Government of Pakistan (1986)] here it will suffice to state that women's economic participation is greatly underestimated in official statistics mainly due to unsuitable methods of data collection, inappropriate definitions of activities and stress on recording only one activity, and the cultural inhibition to admitting to women working. Given these problems the present study relies primarily on data from intensive micro-level surveys and the Agricultural Census in the case of informal ,sector employment of women since the limitations of official data are particularly " acute in these occupations, while estimates of changes over time in women's share of formal sector jobs (professionals, clerical, administrative and organized industry) are mainly based on Labour Force Survey data.

scholarly journals Estimation of employed persons in the case of sample rotation

2008 ◽  
Vol 48 ◽  
Author(s):  
Viktoras Chadyšas ◽  
Danutė Krapavickaitė
Keyword(s):  
Random Sampling ◽  
Sampling Design ◽  
Labour Force ◽  
Auxiliary Information ◽  
Real Data ◽  
Simple Random Sampling ◽  
Ratio Estimator ◽  
Labour Force Survey ◽  
The Real ◽  
Sample Rotation

The aim of the paper – to investigate effectiveness of the ratio estimator in the labour force survey in the case of the simple random sampling with rotation. For each quarter of the year one fourth of the previousquarter sample is changed with the new one, and three fourth’s are remaining the same. After simplification of the sampling design the estimator using auxiliary information and its approximate variance is constructed. The accuracy of the estimator obtained is studied by modelling with the real data.

scholarly journals Exploring the Combined Effects of Rater Misfit and Differential Rater Functioning in Performance Assessments

2019 ◽  
Vol 79 (5) ◽  
pp. 962-987 ◽  
Author(s):  
Stefanie A. Wind ◽  
Wenjing Guo
Keyword(s):  
Data Collection ◽  
Simulation Study ◽  
Real Data ◽  
Performance Assessments ◽  
Combined Effects ◽  
Simulation Studies ◽  
Rater Effects ◽  
Research And Practice ◽  
Systematic Biases ◽  
Sensitivity Changes

Rater effects, or raters’ tendencies to assign ratings to performances that are different from the ratings that the performances warranted, are well documented in rater-mediated assessments across a variety of disciplines. In many real-data studies of rater effects, researchers have reported that raters exhibit more than one effect, such as a combination of misfit and systematic biases related to student subgroups (i.e., differential rater functioning [DRF]). However, researchers who conduct simulation studies of rater effects usually focus on the effects in isolation. The purpose of this study was to explore the degree to which rater effect indicators are sensitive to rater effects when raters exhibit more than one type of effect, and to explore the degree to which this sensitivity changes under different data collection designs. We used a simulation study to explore combinations of DRF and rater misfit. Overall, our findings suggested that it is possible to use common numeric and graphical indicators of DRF and rater misfit when raters exhibit both these effects, but that these effects may be difficult to distinguish using only numeric indicators. We also observed that combinations of rater effects are easier to identify when complete rating designs are used. We discuss implications of our findings as they result to research and practice.

scholarly journals Self-employment as a stepping stone to better labor market matching: a comparison between immigrants and natives

2020 ◽  
Vol 86 (4) ◽  
pp. 479-501
Author(s):  
Magdalena Ulceluse
Keyword(s):  
Labor Market ◽  
Comparative Analysis ◽  
Labour Force ◽  
Demographic Characteristics ◽  
Labour Force Survey ◽  
Self Employment ◽  
Barriers To Employment ◽  
Labor Market Matching ◽  
Shed Light ◽  
The Eu

AbstractThe paper investigates the relation between overeducation and self-employment, in a comparative analysis between immigrants and natives. Using the EU Labour Force Survey for the year 2012 and controlling for a list of demographic characteristics and general characteristics of 30 destination countries, it finds that the likelihood of being overeducated decreases for self-employed immigrants, with inconclusive results for self-employed natives. The results shed light on the extent to which immigrants adjust to labor market imperfections and barriers to employment and might help explain the higher incidence of self-employment that immigrants exhibit, when compared to natives. This is the first study to systematically study the nexus between overeducation and self-employment in a comparative framework. Moreover, the paper tests the robustness of the results by employing two different measures of overeducation, contributing to the literature of the measurement of overeducation.

scholarly journals A comprehensive evaluation of methods for Mendelian randomization using realistic simulations and an analysis of 38 biomarkers for risk of type 2 diabetes

2021 ◽  
Author(s):  
Guanghao Qi ◽  
Nilanjan Chatterjee
Keyword(s):  
Type 2 Diabetes ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Real Data ◽  
Causal Effects ◽  
Type I ◽  
Genome Wide Association Studies ◽  
Simulation Studies ◽  
Sample Sizes

Abstract Background Previous studies have often evaluated methods for Mendelian randomization (MR) analysis based on simulations that do not adequately reflect the data-generating mechanisms in genome-wide association studies (GWAS) and there are often discrepancies in the performance of MR methods in simulations and real data sets. Methods We use a simulation framework that generates data on full GWAS for two traits under a realistic model for effect-size distribution coherent with the heritability, co-heritability and polygenicity typically observed for complex traits. We further use recent data generated from GWAS of 38 biomarkers in the UK Biobank and performed down sampling to investigate trends in estimates of causal effects of these biomarkers on the risk of type 2 diabetes (T2D). Results Simulation studies show that weighted mode and MRMix are the only two methods that maintain the correct type I error rate in a diverse set of scenarios. Between the two methods, MRMix tends to be more powerful for larger GWAS whereas the opposite is true for smaller sample sizes. Among the other methods, random-effect IVW (inverse-variance weighted method), MR-Robust and MR-RAPS (robust adjust profile score) tend to perform best in maintaining a low mean-squared error when the InSIDE assumption is satisfied, but can produce large bias when InSIDE is violated. In real-data analysis, some biomarkers showed major heterogeneity in estimates of their causal effects on the risk of T2D across the different methods and estimates from many methods trended in one direction with increasing sample size with patterns similar to those observed in simulation studies. Conclusion The relative performance of different MR methods depends heavily on the sample sizes of the underlying GWAS, the proportion of valid instruments and the validity of the InSIDE assumption. Down-sampling analysis can be used in large GWAS for the possible detection of bias in the MR methods.

Brazilian National Household Health Survey and PCAT: the case of Mato Grosso do Sul, Brazil

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
L F Pinto ◽  
D Soranz ◽  
L J Santos ◽  
M S Paranhos ◽  
L S Malta ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Primary Health Care ◽  
Data Collection ◽  
Health Survey ◽  
Household Surveys ◽  
Mato Grosso ◽  
Primary Health ◽  
The World ◽  
Mato Grosso Do Sul

Abstract Brazil is divided into five administrative regions, 27 federation units and 5,570 municipalities. Mato Grosso do Sul is one of the states located in the Midwest region and has 1.6 million km2 and a resident population of 2.8 million inhabitants, that is, it has an even lower demographic density than its region - only 7.8 inhabitants/km2. Mato Grosso do Sul has part of the Pantanal, a biome considered the largest continuous floodplain in the world, rich in biodiversity. For this reason, displacements for data collection in household surveys combine roads and rivers. In 2019, the Brazilian National Institute of Geography and Statistics (Istituto Nazionale di Statistica del Brasile) in partnership with the Ministry of Health launched the world's largest household sample survey, the National Health Survey (PNS-2019), in which part of its questions included the use of Primary Care Assessment Tool (PCAT, adult version), created by professors Barbara Starfield and Leiyu Shi in the 2000s. IBGE interviewers visited more than 100,000 households across the country. In Mato Grosso do Sul, more than 3,000 households were surveyed. In this work, we present the data collection instrument used by IBGE and its multiple analysis possibilities in the scope of primary health care, crossing the variables from other questionnaire modules in order to compare the results from Brazil with the state of Mato Grosso do Sul and its capital, Campo Grande. Developing a baseline and measuring the attributes of primary health care in each of the Brazilian states is another step towards giving health policy accountability, towards strong primary care. IBGE's experience in household surveys and innovation in data collection in primary care is an example for the world that yes, it is possible to develop statistically representative national sample surveys and make them perennial in their regular household surveys, by the time World Health Organization (WHO) discusses universal health coverage. Key messages Evaluation of primary care using an internationally validated instrument is possible on national bases with random household sample surveys. A questionnaire elaborated academically can be used as an instrument of public policy to evaluate nationwide health services.

scholarly journals Covid-19 and The Gender Gap in Employment Among Parents of Young Children in Canada

2021 ◽  
pp. 089124322110012
Author(s):  
Sylvia Fuller ◽  
Yue Qian
Keyword(s):  
Gender Equity ◽  
Gender Gap ◽  
Labour Force ◽  
Work Hours ◽  
Labour Force Survey ◽  
Educational Inequalities ◽  
Class Inequality ◽  
Employment Barriers ◽  
Employment Gap ◽  
Structural Shifts

Economic and social disruptions of the COVID-19 pandemic have important implications for gender and class inequality. Drawing on Statistics Canada’s monthly Labour Force Survey, we document trends in gender gaps in employment and work hours over the pandemic (February–October 2020). Our findings highlight the importance of care provisions for gender equity, with gaps larger among parents than people without children, and most pronounced when care and employment were more difficult to reconcile. When employment barriers eased, so did the gender–employment gap. The pandemic could not undo longer-standing cultural and structural shifts motivating contemporary mothers’ employment. The pandemic also exacerbated educational inequalities among women, highlighting the importance of assessing gendered impacts through an intersectional lens.

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