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This paper presents a new statistical methodology for the small area estimation of the proportion of employed, unemployed and inactive people, and of unemployment rates. The novel empirical best and plug-in predictors are based on a multinomial mixed model that is fitted to unit-level data. Model parameters are estimated by maximum-likelihood and mean-squared errors by parametric bootstrap. Several simulation experiments are carried out to empirically investigate the properties of these estimators and predictors. Finally, a detailed application to real data from the first Spanish Labour Force Survey of 2021 is included, where the target is to map labour force indicators by province, sex, and age group. [ABSTRACT FROM AUTHOR]

In line with the existing literature, the primary focus of the present paper is on understanding the multifaceted factors contributing to unequal employment opportunities for women and the potential implications for both individuals and society. Specifically, the objective is to identify meaningful risk factors that affect the probability of being employed for women in the 20–49 age group, exploring possible demographic, educational, social, and family factors, as well as territorial context factors. The analysis is conducted on the three most populous European countries (Italy, France, and Germany) as representatives of different welfare regimes. The analysis exploits the rich information available in the micro-data of the Labour Force Survey (2021) as well as Eurostat regional statistics considering individuals nested in regions (NUTS 2). A deep analysis of empirical findings sheds light on employment determinants and motivations for not working, which appear to be essentially related to family and demographic factors. These results reveal the country-specific profiles that indicate greater risk of non-employment and also provide a basis for suggesting different policy implications. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has brought about a significant impact on people's lives, both in terms of health and socioeconomic aspects. The pandemic has led to a shift in the work environment, with a massive increase in the number of people working from home due to movement restrictions. In this study, we analyse data from two waves (2019 and 2020) of the Swiss Labour Force Survey to investigate the prevalence of working from home in Switzerland before and during the pandemic. The study has two aims: to identify the characteristics of Swiss teleworkers during the pandemic and to determine if there is a gender gap in working from home. The findings reveal that highly educated workers with children in high-level occupations are more likely to telework. However, there is a gender gap in teleworking in some sectors, since part-time workers, who are mostly women (74 percent), are less likely to work from home than full-time workers. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has brought about a significant impact on people's lives, both in terms of health and socioeconomic aspects. The pandemic has led to a shift in the work environment, with a massive increase in the number of people working from home due to movement restrictions. In this study, we analyse data from two waves (2019 and 2020) of the Swiss Labour Force Survey to investigate the prevalence of working from home in Switzerland before and during the pandemic. The study has two aims: to identify the characteristics of Swiss teleworkers during the pandemic and to determine if there is a gender gap in working from home. The findings reveal that highly educated workers with children in high-level occupations are more likely to telework. However, there is a gender gap in teleworking in some sectors, since part-time workers, who are mostly women (74 percent), are less likely to work from home than full-time workers.

According to the standards set by the International Labour Office, people of working age who have performed some remunerated work during a specified short reference period are classified as employed, regardless of how many hours they have worked, while those who have not been able to work at all (despite wanting to) are classified as unemployed. As observed by many experts in the field, this rigid division between employed and unemployed can conceal labour markets with deeply different characteristics. In particular, the average number of hours worked and, more importantly, their distribution across employees may vary significantly across countries. The aim of this paper is to define fuzzy indicators of employment and unemployment by using the available information on the number of hours worked and the satisfaction or dissatisfaction of workers with this. In this approach, each person in the labour force is assigned a degree of employment between 0 and 1, where 0 means full non-membership in the fuzzy set of employed (and full membership in the fuzzy set of unemployed) and 1 means full membership in the fuzzy set of employed. To show the potentiality of the proposed method, we apply fuzzy measures to Labour Force Survey data from 29 European countries and compare the results with the official employment and unemployment statistics published by Eurostat. [ABSTRACT FROM AUTHOR]

This article develops model-based predictors for area-level proportions of employed men and women by occupation sectors and for entropies and divergence indexes (DIs) within and between sex groups. Since the direct estimators of the proportions add up to one in the occupational sections, they are compositions that can be imprecise if the sample sizes are small. We fit a multivariate Fay–Herriot model to logratio transformations of the direct estimators of the proportions. Small area estimators of the proportions, entropies, and DIs are derived from the fitted model and the corresponding mean squared errors are estimated by parametric bootstrap. Several simulation experiments designed to analyze the behavior of the introduced model-based predictors are carried out. We give an application to Spanish Labour Force Survey data from 2022. The target is to investigate the state of sex occupational entropies and divergences in Spanish provinces. [ABSTRACT FROM AUTHOR]

Luxembourg, known for its immigration history, attracts immigrants to work. This study analyses different immigrant groups in the labour market from 2014 to 2022 by using Labor Force Survey (LFS) data, Symbolic Data Analysis (SDA), and the Monitoring the Evolution of Clusters (MEC) framework.Based on the birthplace and length of residence in Luxembourg, in each year, microdata were aggregated into 21 symbolic objects. They were primarily described by 16 modal variables which are multi-valued variables with a frequency attached to each category. Moreover, clustering using complete linkage and the Chernoff’s distance was applied. The Heuristic Identification of Noisy Variables (HINoV) suggested that with just six variables, objects may be grouped homogeneously. The MEC framework traced temporal relations and transitions between the clusters, revealing some movements across the different years.Results indicate that people from the European Union (EU) and Neighbouring countries have similar profiles while the Portuguese have opposite characteristics. The Luxembourgers are somewhere in between. Profiling people from non-EU countries was challenging.The data and methodology used make it easy to replicate the work in other nations, enabling comparison of results and monitoring to continue in the future. [ABSTRACT FROM AUTHOR]

This paper introduces a new statistical methodology for estimating Duncan dissimilarity indexes of occupational segregation by sex in administrative areas and time periods. Given that direct estimators of the proportion of men (or women) in the group of employed people for each occupational sector are not accurate enough in the considered estimation domains, we fit to them a three-fold Fay–Herriot model with random effects at three hierarchical levels. Based on the fitted area-level model, empirical best predictors of the cited proportions and Duncan segregation indexes are derived. A parametric bootstrap algorithm is implemented to estimate the mean squared error. Some simulation studies are included to show how the proposed predictors have a good balance between bias and mean squared error. Data from the Spanish Labour Force Survey are used to illustrate the performance of the new statistical methodology and to give some light about the current state of sex occupational segregation by province in Spain. Research claims that there is a sex gap that persists despite advances in the inclusion of women in the labour market in recent years and that is related to the unequal sharing of family responsabilities and the stigmas still present in modern societies. [ABSTRACT FROM AUTHOR]

The aim of this study is to provide a comprehensive description of the statistical methodology used to produce estimates for various labor market variables at both the City and FUA levels, along with an analysis of the results obtained. To achieve this goal, small area estimates were computed using a unit-level multivariate model. This model was specifically designed to enable coherent estimation of the variables of interest collected by the Labour Force Survey, exploiting information derived from administrative data and statistical Registers. The use of such administrative data at the unit-level represents a novel approach to estimation based on Italian Labour Force Survey data. The estimator used in this work is based on a multivariate model implemented through the Mind R package, which was developed by Istat. The method presented in this study represents an extended multivariate version of the conventional linear mixed model at the unit level. To ensure consistency across different domains, a single cross-classification model was employed, encompassing all relevant domains of interest. The outcomes of this analysis reveal significant improvements in efficiency compared to direct estimates. This is particularly noteworthy in the estimation of unemployed individuals (both total and by gender), where direct estimates are prone to relatively high sampling errors. [ABSTRACT FROM AUTHOR]

Using data from 27 European countries in the academic years 2005/06, 2010/11, and 2015/16, we investigate the association between student funding policies and student labour during term time – a phenomenon often seen as detrimental for higher education outcomes. Income substitution effects between entitlements to different types of financial aid and labour income can vary depending on national context, including prevailing norms with regard to students' transition to independent adulthood. Thus, we use panel regressions with random effects for countries, controlling for relevant factors like average wages in the economy. We could not reject the null hypothesis of no relationship between student funding policy and the share of students in employment. On the other hand, generosity of student funding, in particular of its non-repayable components, was negatively, albeit weakly, associated with the average hours worked by employed students. We found this pattern to be more prevalent among older and female students, but not among students living with parents or from lower educational backgrounds. Overall, student funding policies explain little cross-country variance in student labour. This could be attributed to students' preference to use public funding as a substitute of parental transfers or a mean for increasing their total income. [ABSTRACT FROM AUTHOR]

Copyright of Ruch Prawniczy, Ekonomiczny i Socjologiczny (0035-9629) is the property of Adam Mickiewicz University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The creation of equal opportunities in the labour market for people with disability remains a challenge in many countries around the world. The impact of disability, especially when it comes to work opportunities for disabled people, cannot be properly understood without access to the relevant statistics. Information about working-age disabled people is crucial in the development of labour market policy. Such information should be available not only at the national level but also at lower levels of spatial aggregation. The main aim of this article is to propose a way of producing reliable estimates of key labour market indicators (economic activity rate, employment rate and unemployment rate) for working-age disabled people in Poland at the province level. The authors apply SPREE estimation and use data from the Labour Force Survey 2011–2019 (LFS) and the 2011 Census to produce estimates characterized by better precision and stability over time than what can be achieved by applying direct estimation. While the scale of changes in the labour market situation of working-age disabled people was found to be similar to trends observed in the whole working-age population, there are differences in spatial patterns associated with these two groups.

Copyright of Revista de Derecho de la Seguridad Social, Laborum is the property of Ediciones Laborum S.L. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tijdschrift voor Arbeidsvraagstukken is the property of Amsterdam University Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper applies the concept of hierarchised mobility to study return migration in Slovakia in the context of the country's EU accession. The analysis is based on the national Labour Force Survey dataset, covering a decade of labour migration and return between the 2008/2009 financial crisis and the Covid pandemic, concentrating in particular on the short-term labour market outcomes for less skilled return migrants. It is found that even under improved economic conditions, patterns of labour mobility set in the aftermath of the EU's Eastern enlargement continued to persist, together with structural inequalities in the Slovak labour market. Returnees in Slovakia face a markedly higher unemployment rate relative to stayers, and are less likely to be self-employed shortly after their return to Slovakia, compared to stayers or migrants. Returnees were also more exposed to instability in their jobs than migrants and stayers. From this perspective, return migration itself is a reflection of hierarchised mobility, as returnees clearly occupy the least stable jobs, and are the most exposed to instability in their employment. It appears that migration patterns from and to Slovakia are ingrained within the broader functioning of the European labour market. [ABSTRACT FROM AUTHOR]

Survey data are still contemplated as one of the main sources in official statistics. However, due to the high cost of conducting a survey, as well as the respondent burden, it may not be possible to collect all variables of interest in a data set. To obtain a more comprehensive source of data, one possible way is to integrate available data from different data sets such as already existing data, administrative registers, and official surveys. This helps to minimize the shortcomings of each survey and to maximize their advantages. In this paper, a mixed method at the micro-level has been applied to integrate data sourced from two surveys, involving the 'Iranian Labour Force Survey' and the 'Iranian Time Use Survey' which have been performed in the Fall of 2015. Thereby, besides increasing the coverage of the variables from two sources, we could also study the peculiarities of work and life qualities. For this objective, we develop a statistical matching micro approach by proposing the conditional predictive Dirichlet distribution and conditional predictive multinomial distribution in the regression step of mixed methods. In the end, the quality of matching along with the similarity of marginal distributions of specific variables (variables of interest) pre-and-post the integration are assessed by some similarity measures and the Kolmogorov–Smirnov test. [ABSTRACT FROM AUTHOR]

Copyright of WISTA Wirtschaft und Statistik is the property of Statistisches Bundesamt and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tijdschrift voor Arbeidsvraagstukken is the property of Amsterdam University Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background and objective Disability assessments are crucial for identifying barriers faced by individuals with disabilities, particularly in countries like India, where disability is often underreported. The Labour Force Survey Disability Module (LFS-DM) is a widely used tool for disability assessment. It is available in English, and Indian Hindi-speaking people who are not proficient in English may face difficulties in responding to it. This study aimed to translate and culturally adapt the LFS-DM into Hindi. This will improve its accessibility and relevance for Hindi-speaking populations in India. Methods The LFS-DM was translated into Hindi using a forward and backward translation process involving three bilingual experts. The resulting Hindi version was reviewed for conceptual equivalence (on a 10-point scale) by three healthcare professionals. Pilot testing was conducted with 51 participants with various disabilities who completed the questionnaire and participated in cognitive interviews. The test-retest reliability was assessed using the intraclass correlation coefficient (ICC) with a two-week interval between administrations. Results The linguistic validation process ensured that the Hindi version of the LFS-DM was conceptually equivalent to the original English version with an average score of 9.57 ±0.48. Pilot testing revealed that all participants (27 males, 24 females, mean age: 45.6 ±7.8 years) easily understood the questions, with no major issues reported. Test-retest reliability was good to excellent, with ICC ranging from 0.843 (minimum) to 0.999 (maximum). Conclusions The Hindi-translated LFS-DM was linguistically valid and had similar conceptual equivalence with the original questionnaire. It showed good to excellent test-retest reliability. Hence, it can be used in the assessment of disability among Hindi-speaking populations. This tool can be used in future research, healthcare assessments, and policy development, contributing to more inclusive practices for persons with disabilities in India., Competing Interests: Human subjects: Consent for treatment and open access publication was obtained or waived by all participants in this study. Institutional Ethics Committee, All India Institute of Medical Sciences, Deoghar issued approval 2023-93-EMP-03. The study was conducted in full compliance with the guidelines of the Declaration of Helsinki. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: The study is funded by ICMR. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Kumar et al.)

In multipurpose surveys several interest variables and a very large number of auxiliary variables are collected. Auxiliary variables are usually considered in calibration for improving estimates. But, very often, some of them are included for the sole purpose of increasing consistency. Consistency is an important point for National Statistical Institutes especially as a means for promoting credibility in published statistics. As a direct result, the number of auxiliary variables considered in calibration continue to grow over time. In literature, several methods show how to manage many auxiliary variables in order to prevent some unpleasant consequences on the accuracy of estimates. They consist mainly in variable selection or dimension reduction and they are very useful for deriving calibrated estimates more accurately. However, looking at them, it is not easy to infer how much the contribution of each auxiliary variable is, especially when there are plenty of them. The Shapley decomposition applied in the calibration context could be a useful tool to better understand the net effects of auxiliary variables, and, in addition, it provides further information for supporting researchers in choosing the best calibration system. It provides a direct measure of the change with respect to Horvitz–Thompson estimates and to related sampling variances due to the introduction of each auxiliary variable in the calibration. The method has been applied to real data of the Italian Labour Force Survey that makes an extensive use of auxiliary variables in calibration. [ABSTRACT FROM AUTHOR]

On 1 January 1973, the UK joined the European Economic Community and, in its capacity as a member state, conducted a Labour Force Survey in that year for the first time. The purpose of this article is to contribute to the history of the Labour Force Survey. It begins by outlining the landscape of government statistics in the UK in the post-Second World War period. It then explores the UK's decision in June 1972 to participate in the survey, with a particular focus on the deliberations of the working group of government statisticians tasked with implementing the survey. It identifies the key issues with which the working group grappled. It draws attention to the economic narratives which prevailed and suggests that decisions relating to the collection, analysis, and interpretation of data, and their publication as official statistics, may be influenced by the dominant narratives. In the final section, it describes how the UK implemented the survey, and identifies the ways in which the UK's approach to the implementation of the survey differed from those of other member states. This research is an empirical study based upon the analysis of primary and secondary sources (both published records and unpublished records in archives). [ABSTRACT FROM AUTHOR]

Copyright of Tijdschrift voor Arbeidsvraagstukken is the property of Amsterdam University Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article addresses the issue of socio-demographic attributes of NEET status (dropping out of employment, education or training for young people between 15 and 24 years old) in Russia, and presents an investigation of the impact of education on falling into NEET for the first time. Whilst existing studies on Russian NEETs provide a general descriptive insight into NEET status, little is known about the role of education in NEET-types formation. The empirical analysis was based on the micro-data of the Russian Labour Force Survey (LFS) by the Federal State Statistics Service for 1995–2017, and the Russia Longitudinal Monitoring Survey Higher School of Economics (RLMS-HSE) for 2000–2017. Gender-specific multinomial logit analyses and dynamic multinomial logit panel regressions empirically support the heterogeneous nature of Russian NEETs confirming the human capital framework. They show that higher education does not provide a universal safety net from NEET status in Russia. While risks of NEET-inactivity are mainly concentrated among those who have primary or vocational education, NEET-unemployment in Russia is associated with higher education. Results contribute to the ongoing discussion about the changing rates of return for higher education and the saturation of the Russian labour market with university graduates. [ABSTRACT FROM AUTHOR]

The main aim of the paper is to use the repeated weighting (RW) method on data from the National Census of Population and Housing 2011 (NCPH) and Labour Force Survey (LFS) to ensure consistency between margins of final tables derived from different statistical sources. This technique, based on different data sources, would ensure consistency between estimates in final output tables. This is the first application of the RW approach on data from official statistics in Poland. The results obtained by applying the RW method to data from the NCPH and additional surveys (e.g. LFS) may be used by Statistics Poland for the formulation of conclusions and recommendations for the upcoming census in 2021. The method may be also considered as an important step towards the production of timely and more detailed statistical information in Poland based on multi-source data infrastructure in general4.

Copyright of Sociología del Trabajo is the property of Universidad Complutense de Madrid and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Public opinion has moved towards a more restrictive approach to immigration since 2008, particularly in countries more strongly affected by economic recession. This is generally assumed to be a consequence of economic threat due to greater competition for scarce material resources, such as employment, leading to anti-immigration sentiment. However, not all individuals are affected equally by job losses, nor by the presence of migrants. Using data from the European Social Survey (2008–2016), in conjunction with the Labour Force Survey (2007–2016), this paper examines if individuals within occupations and sectors which face economic decline as measured by job losses, and which have a greater representation of migrants, are more likely to express anti-immigration sentiment. In line with the threat hypothesis the study finds that positive job growth is associated with pro-immigration sentiment while a greater share of migrants within occupations and sectors is linked to greater opposition towards immigration. [ABSTRACT FROM AUTHOR]

Public opinion has moved towards a more restrictive approach to immigration since 2008, particularly in countries more strongly affected by economic recession. This is generally assumed to be a consequence of economic threat due to greater competition for scarce material resources, such as employment, leading to anti-immigration sentiment. However, not all individuals are affected equally by job losses, nor by the presence of migrants. Using data from the European Social Survey (2008–2016), in conjunction with the Labour Force Survey (2007–2016), this paper examines if individuals within occupations and sectors which face economic decline as measured by job losses, and which have a greater representation of migrants, are more likely to express anti-immigration sentiment. In line with the threat hypothesis the study finds that positive job growth is associated with pro-immigration sentiment while a greater share of migrants within occupations and sectors is linked to greater opposition towards immigration. [ABSTRACT FROM AUTHOR]

The aim of this article is to analyse the possibility of applying selected perturbative masking methods of Statistical Disclosure Control to microdata, i.e. unit‑level data from the Labour Force Survey. In the first step, the author assessed to what extent the confidentiality of information was protected in the original dataset. In the second step, after applying selected methods implemented in the sdcMicro package in the R programme, the impact of those methods on the disclosure risk, the loss of information and the quality of estimation of population quantities was assessed. The conclusion highlights some problematic aspects of the use of Statistical Disclosure Control methods which were observed during the conducted analysis.

Copyright of Revue d'Économie Régionale & urbaine is the property of Librairie Armand Colin and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Advanced Mathematical Modeling (JAMM) is the property of Shahid Chamran University of Ahvaz and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Absenteeism is an important feature of the labour market, imposing significant costs on employers and the economy as a whole. This paper is the first to use a large labour force survey sample to investigate how different physical and mental health conditions affect absence rates among prime age workers in the UK. A pooled time series/cross-section analysis reveals that people with a chronic health condition are more likely to be absent from work, and mental health has a significantly larger effect than physical health. From a longitudinal perspective, we find that a change in mental health has an effect on absenteeism more than three times greater than a change in physical health. These findings imply that the prevention and alleviation of chronic health conditions, particularly common mental disorders such as depression and anxiety that are highly prevalent in prime age workers, will deliver significant benefits to the UK economy due to reduced absenteeism. Further, there is significant heterogeneity between different health conditions, with some having no effect at all on absenteeism having controlled for other factors. [ABSTRACT FROM AUTHOR]

Copyright of Ekonomske Ideje i Praksa is the property of Centar za Izdavacku Delatnost Ekonomskog Fakulteta u Beogradu and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An unfavourable position in the labour market relative to that of the local population is one of the specific problems that affect the immigrant population. The aim of this paper is to highlight the position of immigrants in the labour market in Serbia. Special emphasis is placed on discussing the possibilities of the Labour Force Survey (LFS) for studying immigration and the position of immigrants within the labour market in countries with pronounced emigration and a low inflow of foreign labour, as is the case in Serbia. The findings are based on the implementation of a qualitative inquiry and additional processed data from the LFS from 2014 to 2018. Given that the majority of people who immigrated to Serbia were from the former Yugoslav republics, the country of birth criterion was used to separate the immigrant population. The research results show that the age-sex structure of working-age immigrants is not specific to economic migrants. Those born abroad do not have a higher unemployment rate than the domestic population, although they are more affected by the problem of long-term unemployment. Based on the analysis of LFS data, a review of contemporary empirical research, and findings obtained from Serbian experts for the purposes of this paper, both the limitations and the confirmed potentials of the LFS for studying the position of immigrants in the Serbian labour market were discussed. More-over, the need for methodological advancement in terms of the coverage of the immigrant population was emphasised.

We analyse the effect of post-financial crisis unemployment dynamics on the Spanish pension system's financial health using Aggregate Accounting. We compare the basic scenario where the current labour market dynamics persist with a full employment (best-case) scenario. We find that economic risk is the main driver of unsustainability in the short run. However, in the long run, the main driver of expenditures lies in the ageing demographic structure. Our results suggest that future reforms should increase labour market participation but confirm that recent pension reforms do not attain sustainability in the long run, indicating the need of further pension reforms. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic emergency put pressure on the organization of the production and employment system in Italy and required strategies to ensure the safety of workers and consumers from the risks of contagion. Organizational models that exploit the possibility offered by technology to work remotely were used. The aim of the paper is to compare the Italian labour market before the pandemic, when work from home concerns only a negligible percentage of employment, with a hypothetical scenario where all the feasible remotely jobs could be performed from home. The paper analyzes the consistency and the characteristics of workers who worked remotely before the pandemic using the results of the ad hoc module of the Italian Labour force survey. A classification of occupations is proposed on the basis of their potential remote feasibility and an estimate of their extent in the Italian labor market is provided. Finally, the paper focuses on the actual remote working experience during the Covid-19 emergency. [ABSTRACT FROM AUTHOR]