Producing Monthly Estimates of Unemployment and Employment According to the International Labour Office Definition

Monthly unemployment statistics are available in Britain from a monthly count of the number of people claiming unemployment-related benefits. There has been considerable debate on the appropriateness of this measure. Unemployment and employment statistics are available quarterly from the Labour Force Survey (LFS), using International Labour Office (ILO) definitions. In this paper various options for producing monthly unemployment estimates according to the ILO definition are examined. Methods considered are a monthly LFS, calculating rolling averages from the quarterly LFS, and methods which combine LFS and claimant count data. It is proposed that a monthly LFS of 60 000 households be introduced which can produce monthly estimates of total unemployment and more detailed estimates quarterly. Such a survey would also fill an important gap by providing monthly employment statistics which are needed to provide a complete picture of the labour market.     

Missing data and small area estimation in the UK Labour Force Survey

Summary.  We apply multivariate shrinkage to estimate local area rates of unemployment and economic inactivity by using UK Labour Force Survey data. The method exploits the similarity of the rates of claiming unemployment benefit and the unemployment rates as defined by the International Labour Organisation. This is done without any distributional assumptions, merely relying on the high correlation of the two rates. The estimation is integrated with a multiple-imputation procedure for missing employment status of subjects in the database (item non-response). The hot deck method that is used in the imputations is adapted to reflect the uncertainty in the model for non-response. The method is motivated as a development (improvement) of the current operational procedure in which the imputed value is a non-stochastic function of the data. An extension of the procedure to subjects who are absent from the database (unit non-response) is proposed.     

Unemployment, life satisfaction and retrospective error

Summary.  The paper compares current and 1-year retrospective data on unemployment in the German Socio-Economic Panel study. 13% of all unemployment spells are not reported 1 year later, and another 7% are misreported. The ratio of retrospective to current unemployment has increased in recent years and is related to salience of unemployment measures such as the loss of life satisfaction that is associated with unemployment. Individuals with weak labour force attachment, e.g. women with children or individuals who are close to retirement, have the greatest propensity to under-report unemployment retrospectively. The data are consistent with evidence on retrospective bias found by cognitive psychologists and survey methodologists.     

我国失业统计的改革

目前我国失业和就业不足的现象已普通存在,并已引起政府和社会各界的高度重视。近年来,我国公布的失业率数字一直在3%以内,同世界大多数国家相比,我国是低失业率的国家。但是,我国的失业率与国际通行标准在统计概念、指标定义、调查方法方面存在着诸多差异。全面分析这些差异、改进我国的失业统计,对我国宏观经济政策的指导和社会主义市场经济体制的发展具有重要意义。     

Model-Based Estimation of Unemployment Rates in Small Areas of Portugal

The high level of unemployment is a major problem in most European countries nowadays. Hence, the demand for small area labor market statistics has rapidly increased over the past few years. The Portuguese Labour Force Survey is the main source of official statistics at the macro level. However, it was not designed to produce reliable design-based statistics at the micro level due to small sample sizes. The goal of this article is to analyze the performance of model-based small area estimators to estimate the unemployment rate at micro level. Our results showed that the temporal estimator is the most suitable.     

Small area estimates of labour force participation under a multinomial logit mixed model

Summary.  A new methodology is developed for estimating unemployment or employment characteristics in small areas, based on the assumption that the sample totals of unemployed and employed individuals follow a multinomial logit model with random area effects. The method is illustrated with UK labour force data aggregated by sex–age groups. For these data, the accuracy of direct estimates is poor in comparison with estimates that are derived from the multinomial logit model. Furthermore, two different estimators of the mean-squared errors are given: an analytical approximation obtained by Taylor linearization and an estimator based on bootstrapping. A simulation study for comparison of the two estimators shows the good performance of the bootstrap estimator.     

A spatial analysis on Italian unemployment differences

Using spatial econometric models, this paper focuses attention on the spatial structure of provincial unemployment disparities of Italian provinces for the year 2003. On the basis of findings from the economic literature and of the available socio-economic data, various model specifications including supply- and demand-side variables are tested. Further we use ESDA analysis as equivalent to integration analysis on time series; therefore it is applied on each variable, dependent and independent, involved in the statistical model. The suggestions of ESDA lead us to the most adequate statistical model, which estimates indicate that there is a significant degree of neighbouring effect (i.e. positive spatial correlation) among labour markets at the provincial level in Italy; this effect is present notwithstanding we controlled for local characteristics. The unemployment shows a polarized spatial pattern that is strongly connected to labour demand and to a much lesser extent to the share of young population and economic structural composition.     

Ethnic differences in the labour market: a comparison of the samples of anonymized records and Labour Force Survey

The public use sample from the 1991 UK census makes it possible to conduct individual level analyses of ethnic minorities' educational and occupational attainments. Unfortunately, however, the census asked only about higher level qualifications obtained after reaching 18 years of age. A comparison with the Labour Force Surveys (LFSs) shows that the census gives in some respects a misleading impression of qualifications among the first-generation members of ethnic minorities: the LFS data show that ethnic minorities tend to be more polarized in their qualifications than the British-born whites, with relatively large proportions at the two extremes, either with degrees or with no qualifications at all. It follows that the census's treatment of qualifications may tend to exaggerate the scale of disadvantage of ethnic minorities in the labour market, and particularly in access to the salariat where qualifications play a particularly large role in recruitment. Regression analyses of sample of anonymized records and LFS data confirm these expectations although they indicate that the results of the census are not seriously misleading as regards the pattern of ethnic disadvantages in the competition to avoid unemployment. The LFS data also confirm earlier findings that the ethnic penalties are in general of similar magnitude among the second generation to those among the first generation, despite the substantial equalization of educational experience that has taken place. There is some evidence that disadvantages in access to the salariat may have been reduced, but this is counterbalanced by the evidence that disadvantages in the avoidance of unemployment may have deteriorated.     

Outlier Robust Small‐Area Estimation Under Spatial Correlation

Modern systems of official statistics require the estimation and publication of business statistics for disaggregated domains, for example, industry domains and geographical regions. Outlier robust methods have proven to be useful for small‐area estimation. Recently proposed outlier robust model‐based small‐area methods assume, however, uncorrelated random effects. Spatial dependencies, resulting from similar industry domains or geographic regions, often occur. In this paper, we propose an outlier robust small‐area methodology that allows for the presence of spatial correlation in the data. In particular, we present a robust predictive methodology that incorporates the potential spatial impact from other areas (domains) on the small area (domain) of interest. We further propose two parametric bootstrap methods for estimating the mean‐squared error. Simulations indicate that the proposed methodology may lead to efficiency gains. The paper concludes with an illustrative application by using business data for estimating average labour costs in Italian provinces.     

A maximum estimability criterion for design classification and selection

A maximum estimability (maxest) criterion is proposed for design classification and selection. It is an extension and refinement of Webb's resolution criterion for general factorial designs. By using the estimability vector associated with the maxest criterion, projective properties of nonregular designs are studied from the estimability perspective. Comparisons with other criteria are also discussed.     

Monte Carlo integration: An application to labour market states and transitions

This paper is concerned with the application of simulation estimation methods to micro-econometric labour market models. Based on a multi-period probit model for direct job changes and unemployment, estimators for the likelihood of individual employment histories are obtained by Monte Carlo integration and employed in a standard ML-procedure. The results for West German panel data suggest that dynamic effects are largely prevalent on labour markets and that in particular, past unemployment has drastic negative effects on future employment chances. Further, there are no indications that foreigners have a different labour market performance, nor that they are crowding natives out into unemployment.     

Unemployment duration and the length of entitlement periods for unemployment benefits: do the IAB employment subsample and the German Socio-Economic Panel yield the same results?*

Summary: We compare information on the length of unemployment spells contained in the IAB employment subsample (IABS) and in the German Socio-Economic Panel (GSOEP). Due to the lack of information on registered unemployment in the IABS, we use two proxies of unemployment in the IABS as introduced by Fitzenberger/Wilke (2004). The first proxy comprises all periods of nonemployment after an employment spell which contain at least one period with unemployment compensation transfers. The second proxy includes all episodes between two employment spells during which an individual continuously received unemployment benefits. Estimation of standard duration models indicates that conclusions drawn from the IABS and the GSOEP differ in many cases. While the GSOEP suggests that the hazard rate has a maximum at about 12 months of unemployment, the IABS results suggest that this maximum is at about 20 months. Contrary to our GSOEP results and contrary to many results based on the GSOEP found in the literature, we find a statistically significant association between longer maximum entitlement periods of unemployment benefits (‘Arbeitslosengeld’) and longer unemployment durations for men in the IABS. The results for women do not show such clear patterns. The large sample size of the IABS also allows to trace out statistically significant effects of characteristics such as regional and industry indicators, which is generally not possible in the relatively small GSOEP. * Acknowledgements: We would like to thank the editors of this special issue, Joachim M?ller and Bernd Fitzenberger, two anonymous referees, the participants of the ‘Statistische Woche 2004’ in Frankfurt (in particular Reinhard Hujer, Olaf Hübler and Gerd Ronning), seminar participants at the ZEW Mannheim (especially Fran?ois Laisney and Alexander Spermann) and Jennifer Hunt for their many helpful comments and suggestions. All remaining errors are our own. Financial support of the Deutsche Forschungsgemeinschaft (DFG) through the research project ‘Microeconometric modelling of unemployment durations under consideration of the macroeconomic situation’ is gratefully acknowledged. The data used in this paper were made available by the Institute for Employment Research (IAB) at the Federal Labour Office of Germany, Nürnberg, and the German Socio Economic Panel Study (GSOEP) at the German Institute for Economic Research (DIW), Berlin.     

On optimality of extremal schemes in progressive type II censoring

In a progressively type II censored life-testing experiment intact units may be removed from the experiment after every failure. If the initial number of units in the experiment and the total number of failures are fixed, the experimenter may choose between different censoring schemes. By specifying an optimality criterion, one may improve the outcome of the experiment by choosing the respective optimal scheme. We establish a simple property of a general optimality criterion that yields optimality of certain extremal schemes. Applications to some criteria that measure the total time of the experiment and its variability illustrate the approach. The results are based on stochastic orderings of generalized order statistics.     

ASSESSING ERROR RATE ESTIMATORS: THE LEAVE-ONE-OUT METHOD RECONSIDERED

Many comparative studies of the estimators of error rates of supervised classification rules are based on inappropriate criteria. In particular, although they fix the Bayes error rate, their summary statistics aggregate a range of true error rates. This means that their conclusions about the performance of classification rules cannot be trusted. This paper discusses the general issues involved, and then focuses attention specifically on the leave-one-out estimator. The estimator is investigated in a simulation study, both in absolute terms and in comparison with a popular bootstrap estimator. An improvement to the leave-one-out estimator is suggested, but the bootstrap estimator appears to maintain superiority even when the criteria are adjusted.     

Estimating Gross Labor-Force Flows

We present and apply an adjustment procedure for the Bureau of the Census and Bureau of Labor Statistics gross labor-force flows data that addresses two major defects in the data. First, an adjustment procedure is developed to take account of individuals with missing labor-force classifications who are not missing at random. Second, we provide a procedure for adjustment for individuals with spurious labor-force transitions arising because of classification errors in either the current or the previous Current Population Survey. Our procedures are applied to compute adjusted monthly gross change data for the period January 1977–December 1982. The average adjustment for nonrandom missing classifications ranges from –12% to 15% of the unadjusted gross change data. The average adjustment for spurious labor-force transitions reduces estimated movements by 8%–49%. The classification adjustment also increases estimated consecutive periods of unemployment by 18%. We apply several internal and external consistency checks to our procedure. In general, the adjustments appear reasonable. We also suggest some modifications of Current Population Survey procedures that could reduce the use of ex post adjustment procedures in the future.     

Estimation under length-bias and right-censoring: an application to unemployment duration analysis for married women

In this work we analyse unemployment duration for married women in Spain, using the Labour Force Survey (LFS) of the Spanish Institute for Statistics, 1987-1997. Consistent non-parametric estimation of the unemployment survival function is provided. Since the available data are length- biased, a suitable correction of the Kaplan-Meier product-limit estimator is motivated and used for the referred analysis. The accuracy of parametric models is checked by means of goodness-of-fit plots--a graphical tool that requires preliminary estimation of the survival. Structural features of the associated hazard (as monotonicity and unimodality) are explored.     

D‐optimal minimax fractional factorial designs

The D‐optimal minimax criterion is proposed to construct fractional factorial designs. The resulting designs are very efficient, and robust against misspecification of the effects in the linear model. The criterion was first proposed by Wilmut & Zhou (2011); their work is limited to two‐level factorial designs, however. In this paper we extend this criterion to designs with factors having any levels (including mixed levels) and explore several important properties of this criterion. Theoretical results are obtained for construction of fractional factorial designs in general. This minimax criterion is not only scale invariant, but also invariant under level permutations. Moreover, it can be applied to any run size. This is an advantage over some other existing criteria. The Canadian Journal of Statistics 41: 325–340; 2013 © 2013 Statistical Society of Canada     

Measuring the Influence of Unemployment Insurance on Unemployment Experiences

This article investigates the comprehensive effects of unemployment insurance (UI) policies on the amount of time and unemployment that individuals report between jobs. The econometric model jointly determines the effects of UI on the lengths of nonemployment spells, the classification of these spells as unemployment, and the likelihood of collecting program benefits. The model carefully attempts to isolate variation in UI benefits attributable to differences in generosity across programs to avoid biases in estimating policy effects induced by other contaminating sources of benefit variation. Using data on men from the National Longitudinal Survey of Youth, the empirical results find (a) UI recipients typically experience longer spells between jobs, at least up to the exhaustion of UI benefits, and report substantially larger fractions of these spells as unemployment; (b) weekly benefit amounts exert no significant influence on the likelihood of UI recipiency, on the length of spells between jobs, or on the fraction of these spells classified as unemployment; and (c) increases in weeks of UI eligibility raise the likelihood of UI collection and lengthen the number of weeks of unemployment between jobs by inducing long spells to become longer and not by altering short-duration behavior.     

Hierarchical Bayes estimation of spatial statistics for rates

The U.S. Bureau of Labour Statistics publishes monthly unemployment rate estimates for its 50 states, the District of Columbia, and all counties, under Current Population Survey. However, the unemployment rate estimates for some states are unreliable due to low sample sizes in these states. Datta et al. (1999) proposed a hierarchical Bayes (HB) method using a time series generalization of a widely used cross-sectional model in small-area estimation. However, the geographical variation is also likely to be important. To have an efficient model, a comprehensive mixed normal model that accounts for the spatial and temporal effects is considered. A HB approach using Markov chain Monte Carlo is used for the analysis of the U.S. state-level unemployment rate estimates for January 2004-December 2007. The sensitivity of such type of analysis to prior assumptions in the Gaussian context is also studied.     

The Covariance Inflation Criterion for Adaptive Model Selection

We propose a new criterion for model selection in prediction problems. The covariance inflation criterion adjusts the training error by the average covariance of the predictions and responses, when the prediction rule is applied to permuted versions of the data set. This criterion can be applied to general prediction problems (e.g. regression or classification) and to general prediction rules (e.g. stepwise regression, tree-based models and neural nets). As a by-product we obtain a measure of the effective number of parameters used by an adaptive procedure. We relate the covariance inflation criterion to other model selection procedures and illustrate its use in some regression and classification problems. We also revisit the conditional bootstrap approach to model selection.