bluuebunny/crossref_metadata_2025 huggingface dataset:
Ethnic Differences in the Labour Market: A Comparison of the Samples of Anonymized Records and Labour Force Survey
Authors: Heath Anthony , McMahon Dorren , Roberts Jane
Published: March 2003

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.
Bayesian Analysis of Mortality Data
Authors: Dellaportas Petros , Smith Adrian F. M. , Stavropoulos Photis
Published: March 2003

Congdon argued that the use of parametric modelling of mortality data is necessary in many practical demographical problems. In this paper, we focus on a form of model introduced by Heligman and Pollard in 1980, and we adopt a Bayesian analysis, using Markov chain Monte Carlo simulation, to produce the posterior summaries required. This opens the way to richer, more flexible inference summaries and avoids the numerical problems that are encountered with classical methods. Particular methodologies to cope with incomplete life-tables and a derivation of joint lifetimes, median times to death and related quantities of interest are also presented.
Commissioned Analysis of Surgical Performance Using Routine Data: Lessons from the Bristol Inquiry
Authors: Spiegelhalter David J. , Aylin Paul , Best Nicola G. , Evans Stephen J. W. , Murray Gordon D.
Published: March 2003

The public inquiry into paediatric cardiac surgery at the Bristol Royal Infirmary commissioned the authors to design and conduct analyses of routine data sources to compare surgical outcomes between centres. Such analyses are necessarily complex in this context but were further hampered by the inherent inconsistencies and mediocre quality of the various sources of data. Three levels of analysis of increasing sophistication were carried out. The reasonable consistency of the results arising from different sources of data, together with a number of sensitivity analyses, led us to conclude that there had been excess mortality in Bristol in open heart operations on children under 1 year of age. We consider criticisms of our analysis and discuss the role of statisticians in this inquiry and their contribution to the final report of the inquiry. The potential statistical role in future programmes for monitoring clinical performance is highlighted.
Bayesian Multivariate Spatial Interpolation with Data Missing by Design
Authors: Le Nhu D. , Sun Weimin , Zidek James V.
Published: March 2003

In a network of s  g sites, responses like levels of airborne pollutant concentrations may be monitored over time. The sites need not all measure the same set of response items and unmeasured items are considered as data missing by design. We propose a hierarchical Bayesian approach to interpolate the levels of, say, k responses at s  u other locations called ungauged sites and also the unmeasured levels of the k responses at the gauged sites. Our method involves two steps. First, when all hyperparameters are assumed to be known, a predictive distribution is derived. In turn, an interpolator, its variance and a simultaneous interpolation region are obtained. In step two, we propose the use of an empirical Bayesian approach to estimate the hyperparameters through an EM algorithm. We base our theory on a linear Gaussian model and the relationship between a multivariate normal and matrix T-distribution. Our theory allows us to pool data from several existing networks that measure different subsets of response items for interpolation.
Latent Variable Models for Mixed Discrete and Continuous Outcomes
Authors: Sammel Mary Dupuis , Ryan Louise M. , Legler Julie M.
Published: March 2003

We propose a latent variable model for mixed discrete and continuous outcomes. The model accommodates any mixture of outcomes from an exponential family and allows for arbitrary covariate effects, as well as direct modelling of covariates on the latent variable. An EM algorithm is proposed for parameter estimation and estimates of the latent variables are produced as a by-product of the analysis. A generalized likelihood ratio test can be used to test the significance of covariates affecting the latent outcomes. This method is applied to birth defects data, where the outcomes of interest are continuous measures of size and binary indicators of minor physical anomalies. Infants who were exposed in utero to anticonvulsant medications are compared with controls.
Second-derivative Functional Regression with Applications to Near Infra-red Spectroscopy
Authors: Goutis Constantinos
Published: March 2003

A linear regression method to predict a scalar from a discretized smooth function is presented. The method takes into account the functional nature of the predictors and the importance of the second derivative in spectroscopic applications. This motivates a functional inner product that can be used as a roughness penalty. Using this inner product, we derive a linear prediction method that is similar to ridge regression but with different shrinkage characteristics. We describe its practical implementation and we address the problem of computing the second derivatives nonparametrically. We apply the method to a calibration example using near infra-red spectra. We conclude with a discussion comparing our approach with other regression algorithms.
Curve Registration
Authors: Ramsay J. O. , Li Xiaochun
Published: March 2003

Functional data analysis involves the extension of familiar statistical procedures such as principal components analysis, linear modelling, and canonical correlation analysis to data where the raw observation xi is a function. An essential preliminary to a functional data analysis is often the registration or alignment of salient curve features by suitable monotone transformations hi of the argument t, so that the actual analyses are carried out on the values xi{hi(t)}. This is referred to as dynamic time warping in the engineering literature. In effect, this conceptualizes variation among functions as being composed of two aspects: horizontal and vertical, or domain and range. A nonparametric function estimation technique is described for identifying the smooth monotone transformations hi, and is illustrated by data analyses. A second-order linear stochastic differential equation is proposed to model these components of variation.
Triple-goal Estimates in Two-stage Hierarchical Models
Authors: Shen Wei , Louis Thomas A.
Published: March 2003

The beauty of the Bayesian approach is its ability to structure complicated models, inferential goals and analyses. To take full advantage of it, methods should be linked to an inferential goal via a loss function. For example, in the two-stage, compound sampling model the posterior means are optimal under squared error loss. However, they can perform poorly in estimating the histogram of the parameters or in ranking them. ‘Triple-goal’ estimates are motivated by the desire to have a set of estimates that produce good ranks, a good parameter histogram and good co-ordinate-specific estimates. No set of estimates can simultaneously optimize these three goals and we seek a set that strikes an effective trade-off. We evaluate and compare three candidate approaches: the posterior means, the constrained Bayes estimates of Louis and Ghosh, and a new approach that optimizes estimation of the histogram and the ranks. Mathematical and simulation-based analyses support the superiority of the new approach and document its excellent performance for the three inferential goals.
Local Maximum Likelihood Estimation and Inference
Authors: Fan Jianqing , Farmen Mark , Gijbels Irene
Published: March 2003

Local maximum likelihood estimation is a nonparametric counterpart of the widely used parametric maximum likelihood technique. It extends the scope of the parametric maximum likelihood method to a much wider class of parametric spaces. Associated with this nonparametric estimation scheme is the issue of bandwidth selection and bias and variance assessment. This paper provides a unified approach to selecting a bandwidth and constructing confidence intervals in local maximum likelihood estimation. The approach is then applied to least squares nonparametric regression and to nonparametric logistic regression. Our experiences in these two settings show that the general idea outlined here is powerful and encouraging.
On the Effect of Overdispersion On Exact Conditional Tests
Authors: Severini Thomas A.
Published: March 2003

Let Y  1, . . ., Yn denote independent random variables such that Yj has a one-parameter exponential family distribution with canonical parameter θj=λ+ψXj; here X  1, . . ., Xn are known constants. Consider a test of the null hypothesis ψ=0. Under the null hypothesis, A=ΣYj is sufficient for λ and, hence, a test of ψ=0 may be based on the conditional distribution of T=ΣXj  Yj given A, which is independent of λ. In this paper, the effects of overdispersion due to a mixture model on the conditional distribution of T given A are considered.
Direct Calculation of the Information Matrix via the EM Algorithm
Authors: Oakes D.
Published: March 2003

A simple explicit formula is provided for the matrix of second derivatives of the observed data log-likelihood in terms of derivatives of the criterion function (conditional expectation of the complete data log-likelihood given the observed data) invoked by the EM algorithm.
Inference in Molecular Population Genetics
Authors: Stephens Matthew , Donnelly Peter
Published: March 2003

Full likelihood-based inference for modern population genetics data presents methodological and computational challenges. The problem is of considerable practical importance and has attracted recent attention, with the development of algorithms based on importance sampling (IS) and Markov chain Monte Carlo (MCMC) sampling. Here we introduce a new IS algorithm. The optimal proposal distribution for these problems can be characterized, and we exploit a detailed analysis of genealogical processes to develop a practicable approximation to it. We compare the new method with existing algorithms on a variety of genetic examples. Our approach substantially outperforms existing IS algorithms, with efficiency typically improved by several orders of magnitude. The new method also compares favourably with existing MCMC methods in some problems, and less favourably in others, suggesting that both IS and MCMC methods have a continuing role to play in this area. We offer insights into the relative advantages of each approach, and we discuss diagnostics in the IS framework.
Improved Small Sample Inference in the Mixed Linear Model: Bartlett Correction and Adjusted Likelihood
Authors: Zucker David M. , Lieberman Offer , Manor Orly
Published: March 2003

The mixed linear model is a popular method for analysing unbalanced repeated measurement data. The classical statistical tests for parameters in this model are based on asymptotic theory that is unreliable in the small samples that are often encountered in practice. For testing a given fixed effect parameter with a small sample, we develop and investigate refined likelihood ratio (LR) tests. The refinements considered are the Bartlett correction and use of the Cox–Reid adjusted likelihood; these are examined separately and in combination. We illustrate the various LR tests on an actual data set and compare them in two simulation studies. The conventional LR test yields type I error rates that are higher than nominal. The adjusted LR test yields rates that are lower than nominal, with absolute accuracy similar to that of the conventional LR test in the first simulation study and better in the second. The Bartlett correction substantially improves the accuracy of the type I error rates with either the conventional or the adjusted LR test. In many cases, error rates that are very close to nominal are achieved with the refined methods.
Epidemics in Heterogeneous Communities: Estimation of R0 and Secure Vaccination Coverage
Authors: Britton Tom
Published: March 2003

A stochastic multitype model for the spread of an infectious disease in a community of heterogeneous individuals is analysed. In particular, estimates of R  0 (the basic reproduction number) and the critical vaccination coverage are derived, where estimation is based on final size data of an outbreak in the community. It is shown that these key parameters cannot be estimated consistently from data; only upper and lower bounds can be estimated. Confidence regions for the upper bounds are derived, thus giving conservative estimates of R  0 and the fractions necessary to vaccinate.
Graphical Techniques for Selecting Explanatory Variables for Time Series Data
Authors: Marriott J. M. , Pettitt A. N.
Published: March 2003

Bayesian model building techniques are developed for data with a strong time series structure and possibly exogenous explanatory variables that have strong explanatory and predictive power. The emphasis is on finding whether there are any explanatory variables that might be used for modelling if the data have a strong time series structure that should also be included. We use a time series model that is linear in past observations and that can capture both stochastic and deterministic trend, seasonality and serial correlation. We propose the plotting of absolute predictive error against predictive standard deviation. A series of such plots is utilized to determine which of several nested and non-nested models is optimal in terms of minimizing the dispersion of the predictive distribution and restricting predictive outliers. We apply the techniques to modelling monthly counts of fatal road crashes in Australia where economic, consumption and weather variables are available and we find that three such variables should be included in addition to the time series filter. The approach leads to graphical techniques to determine strengths of relationships between the dependent variable and covariates and to detect model inadequacy as well as determining useful numerical summaries.
Bayesian Analysis of Two-Component Mixture Distributions Applied to Estimating Malaria Attributable Fractions
Authors: Vounatsou P. , Smith T. , Smith A. F. M.
Published: March 2003

Malaria illness can be diagnosed by the presence of fever and parasitaemia. However, in highly endemic areas the diagnosis of clinical malaria can be difficult since children may tolerate parasites without fever and may have fever due to other causes. We propose a novel, simulation-based Bayesian approach for obtaining precise estimates of the probabilities of children with different levels of parasitaemia having fever due to malaria, by formulating the problem as a mixture of distributions. The methodology suggested is a general methodology for decomposing any two-component mixture distribution nonparametrically, when an independent training sample is available from one of the components. It is based on the assumption that one of the component distributions lies on the left of the other but there is some overlap between the distributions.
Analysis of Distance for Structured Multivariate Data and Extensions to Multivariate Analysis of Variance
Authors: Gower J. C. , Krzanowski W. J.
Published: March 2003

Many data sets in practice fit a multivariate analysis of variance (MANOVA) structure but are not consonant with MANOVA assumptions. One particular such data set from economics is described. This set has a 24 factorial design with eight variables measured on each individual, but the application of MANOVA seems inadvisable given the highly skewed nature of the data. To establish a basis for analysis, we examine the structure of distance matrices in the presence of a priori grouping of units and show how the total squared distance among the units of a multivariate data set can be partitioned according to the factors of an external classification. The partitioning is exactly analogous to that in the univariate analysis of variance. It therefore provides a framework for the analysis of any data set whose structure conforms to that of MANOVA, but which for various reasons cannot be analysed by this technique. Descriptive aspects of the technique are considered in detail, and inferential questions are tackled via randomization tests. This approach provides a satisfactory analysis of the economics data.
Multichannel Electroencephalographic Analyses via Dynamic Regression Models with Time-Varying Lag–Lead Structure
Authors: Prado Raquel , West Mike , Krystal Andrew D.
Published: March 2003

Multiple time series of scalp electrical potential activity are generated routinely in electroencephalographic (EEG) studies. Such recordings provide important non-invasive data about brain function in human neuropsychiatric disorders. Analyses of EEG traces aim to isolate characteristics of their spatiotemporal dynamics that may be useful in diagnosis, or may improve the understanding of the underlying neurophysiology or may improve treatment through identifying predictors and indicators of clinical outcomes. We discuss the development and application of non-stationary time series models for multiple EEG series generated from individual subjects in a clinical neuropsychiatric setting. The subjects are depressed patients experiencing generalized tonic–clonic seizures elicited by electroconvulsive therapy (ECT) as antidepressant treatment. Two varieties of models—dynamic latent factor models and dynamic regression models—are introduced and studied. We discuss model motivation and form, and aspects of statistical analysis including parameter identifiability, posterior inference and implementation of these models via Markov chain Monte Carlo techniques. In an application to the analysis of a typical set of 19 EEG series recorded during an ECT seizure at different locations over a patient’s scalp, these models reveal time-varying features across the series that are strongly related to the placement of the electrodes. We illustrate various model outputs, the exploration of such time-varying spatial structure and its relevance in the ECT study, and in basic EEG research in general.
Choice of thresholds for wavelet shrinkage estimate of the spectrum
Authors: Gao Hong‐Ye
Published: March 2003

We study the problem of estimating the log‐spectrum of a stationary Gaussian time series by thresholding the empirical wavelet coefficients. We propose the use of thresholds tj,n depending on sample size n, wavelet basis ψ and resolution level j. At fine resolution levels (j = 1, 2, ...) we propose

t

j,n = αj log n

where {αj} are level‐dependent constants and at coarse levels (j≫ 1)

t

j,n = (π/√3)(log n)1/2.

The purpose of this thresholding level is to make the reconstructed log‐spectrum as nearly noise‐free as possible. In addition to being pleasant from a visual point of view, the noise‐free character leads to attractive theoretical properties over a wide range of smoothness assumptions. Previous proposals set much smaller thresholds and did not enjoy these properties.
A Proposal for Estimation of the Parameters of Multivariate Moving‐average Models
Authors: Monti Anna Clara
Published: March 2003

A method is proposed for the preliminary estimation of the parameters of multivariate moving‐average processes. Initially,m independent white‐noise series are generated. Then the parameters are estimated through an iterative procedure. The algorithm is fast and simple since it does not require specialized software for time series but a least squares routine. The estimators are consistent and a simulation experiment shows good performance in finite samples. An applicati on to real data is also illustrated
Least‐squares Estimation of an Unknown Number of Shifts in a Time Series
Authors: Lavielle Marc , Moulines Eric
Published: March 2003

In this contribution, general results on the off‐line least‐squares estimate of changes in the mean of a random process are presented. First, a generalisation of the Hajek‐Renyi inequality, dealing with the fluctuations of the normalized partial sums, is given. This preliminary result is then used to derive the consistency and the rate of convergence of the change‐points estimate, in the situation where the number of changes is known. Strong consistency is obtained under some mixing conditions. The limiting distribution is also computed under an invariance principle. The case where the number of changes is unknown is then addressed. All these results apply to a large class of dependent processes, including strongly mixing and also long‐range dependent processes.
Trend Adjustment Prior to Testing for the Cointegrating Rank of a Vector Autoregressive Process
Authors: Saikkonen Pentti , Lutkepohl Helmut
Published: March 2003

Testing the cointegrating rank of a vector autoregressive process that may have a deterministic linear trend is considered. Previous proposals for dealing with such a situation are either to allow for a deterministic trend term in computing a suitable test statistic or else to remove the linear trend first and then derive the test statistic from the trend‐adjusted data. In this study the latter approach is considered and a new method for trend removal is proposed that is based on estimating the trend parameters under the null hypothesis. Likelihood ratio and Lagrange multiplier type test statistics are derived on the basis of the trend‐adjusted data and their asymptotic distributions are considered under the null hypothesis and under local alternatives. A simulation comparison with other proposals is performed.
Residual‐Based Tests For Fractional Cointegration: A Monte Carlo Study
Authors: Dittmann Ingolf
Published: March 2003

This paper reports an extensive Monte Carlo study of six residual‐based tests of the hypothesis of no cointegration against the alternative of fractional cointegration. Critical values, power and size are simulated and compared. It turns out that the Lobato–Robinson LM test, the Geweke–Porter‐Hudak test and the two Phillips–Perron tests exhibit severe size distortions. On the other hand, the augmented Dickey–Fuller test and the modified rescaled range test show only moderate size distortions but are generally less powerful. In addition, the impact and possible treatment of trends in the individual series, and in the cointegration equilibrium, are discussed.
Highly Robust Estimation of the Autocovariance Function
Authors: Ma Yanyuan , Genton Marc G.
Published: March 2003

In this paper, the problem of the robustness of the sample autocovariance function is addressed. We propose a new autocovariance estimator, based on a highly robust estimator of scale. Its robustness properties are studied by means of the influence function, and a new concept of temporal breakdown point. As the theoretical variance of the estimator does not have a closed form, we perform a simulation study. Situations with various size of outliers are tested. They confirm the robustness properties of the new estimator. An S‐Plus function for the highly robust autocovariance estimator is made available on the Web at http://www‐math.mit.edu/~yanyuan/Genton/Time/time.html. At the end, we analyze a time series of monthly interest rates of an Austrian bank.
Properties of Predictors in Overdifferenced Nearly Nonstationary Autoregression
Authors: Sanchez Ismael , Pena Daniel
Published: March 2003

We analyze the effect of overdifferencing a stationary AR(p+1) process whose largest root is near unity. It is found that, if the process is nearly nonstationary, the estimators of the overdifferenced model ARIMA(p,1,0) are root‐T consistent. It is also found that this misspecified ARIMA(p,1,0) has lower predictive mean squared error, to terms of small order, than the properly specified AR(p+1) model due to its parsimony. The advantage of the overdifferenced predictor depends on the remaining roots, the prediction horizon and the mean of the process.
Conditional Heteroskedasticity Driven by Hidden Markov Chains
Authors: Francq Christian , Roussignol Michel , Zakoian Jean‐Michel
Published: March 2003

We consider a generalized autoregressive conditionally heteroskedastic (GARCH) equation where the coefficients depend on the state of a nonobserved Markov chain. Necessary and sufficient conditions ensuring the existence of a stationary solution are given. In the case of ARCH regimes, the maximum likelihood estimates are shown to be consistent. The identification problem is also considered. This is illustrated by means of real and simulated data sets.
A Hierarchical Approach to Covariance Function Estimation for Time Series
Authors: Daniels Michael J. , Cressie Noel
Published: March 2003

The covariance function in time series models is typically modelled via a parametric family. This ensures straightforward best linear prediction while maintaining positive‐definiteness of the covariance function. We suggest an alternative approach, which will result in data‐determined shrinkage towards this parametric model. Positive‐definiteness is maintained by carrying out the shrinkage in the spectral domain. We offer both a fully Bayesian hierarchical approach and an approximate hierarchical approach that will be much simpler computationally. These are implemented on the frequently analysed Canadian lynx data and compared to other models that have been fitted to these data.
An algorithm for the exact likelihood of a stationary vector autoregressive‐moving average model
Authors: MAURICIO JOSÉ ALBERTO
Published: March 2003

The so‐called innovations form of the likelihood function implied by a stationary vector autoregressive‐moving average model is considered without directly using a state–space representation. Specifically, it is shown in detail how to compute the exact likelihood by an adaptation to the multivariate case of the innovations algorithm of Ansley (1979) for univariate models. Comparisons with other existing methods are also provided, showing that the algorithm described here is computationally more efficient than the fastest methods currently available in many cases of practical interest.
Nonlinear error correction models
Authors: ESCRIBANO ALVARO , MIRA SANTIAGO
Published: March 2003

The relationship between cointegration and error correction (EC) models is well characterized in a linear context, but the extension to the nonlinear context is still a challenge. Few extensions of the linear framework have been done in the context of nonlinear error correction (NEC) or asymmetric and time varying error correction models. In this paper, we propose a theoretical framework based on the concept of near epoch dependence (NED) that allows us to formally address these issues. In particular, we partially extend the Granger Representation Theorem to the nonlinear case.
Properties of the nonparametric autoregressive bootstrap
Authors: FRANKE J. , KREISS J.‐P. , MAMMEN E. , NEUMANN M. H.
Published: March 2003

For nonparametric autoregression, we investigate a model based bootstrap procedure (`autoregressive bootstrap') that mimics the complete dependence structure of the original time series. We give consistency results for uniform bootstrap confidence bands of the autoregression function based on kernel estimates of the autoregression function. This result is achieved by global strong approximations of the kernel estimates for the resample and for the original sample. Furthermore, it is obtained that the autoregressive bootstrap also yields asymptotically correct approximations for distributions of parametric statistics, for which regression‐type bootstrap‐techniques like the wild bootstrap do not work. For this purpose, we prove geometric ergodicity and absolute regularity of the nonparametric autoregressive bootstrap process. We propose some particular estimators of the autoregression function and of the density of the innovations such that the mixing coefficients of the autoregressive bootstrap process can be bounded uniformly by some exponentially decaying sequence. This is achieved by using well‐established coupling techniques. Moreover, by using some `decoupling' argument, we show that the stationary density of the bootstrap process converges to that of the original process. The paper may serve as a template for proving similar consistency results for other bootstrap techniques such as the Markov bootstrap.
Internal Migration in Sweden: The Effects of Mobility Grants and Regional Labour Market Conditions
Authors: Westerlund Olle
Published: March 2003

The main purpose of this study is to investigate whether variations in mobility grants have affected internal migration in Sweden. The paper also contains an exploration of how changing labour market conditions influence the migratory behaviour of the unemployed in comparison with other individuals. The results indicate that total migration flows respond to changes in labour market conditions in accordance with predictions from economic theory. This finding seems mainly to stem from the migratory behaviour of the unemployed. Furthermore, non‐matching migration subsidies at the levels employed are not found to be migration enhancing.
Poverty Dynamics: Analysis of Household Incomes in Italy
Authors: Addabbo Tindara
Published: March 2003

Poverty increased in Italy during 1993, both in incidence and intensity. This study focuses on the changes which have taken place after the crisis. The data set used is the Bank of Italy Survey on Household Income and Wealth (SHIW), and poverty is defined in terms of disposable income. A descriptive analysis which uses intensity and incidence indices is provided and probit models are estimated on the poverty probability faced by households of the 1993–95 SHIW panel. The latter microeconometric analysis shows that households living in the South of Italy, with an unemployed husband and whose income was further below the poverty line in 1993, are more likely to have remained poor in 1995. Households whose head has a higher level of education and where the number of employed members is higher were more likely to escape from poverty in 1995. On the whole, it can be stated that poverty did not decrease after the 1993 recession and the poverty status of households living in the South of Italy did worsen after the crisis.
Italian Families Under Economic Stress: The Impact of Social Policies
Authors: Saraceno Chiara
Published: March 2003

The author argues that the persistent and growing inequality in income distribution and relative social immobility of households in Italy depend not only on the specific, dualistic, features of its economy but on its social (particularly family) and welfare arrangements: in terms of the behaviours they encourage within households and by specific household members (along gender and generational lines).
A Simple Model of Severance Pay Determination: The Case of Individual Dismissals in Spain
Authors: Malo Miguel Á.
Published: March 2003

In this article we model the determinants of severance pay for individual dismissals in Spain, following an idea proposed by Jimeno and Toharia (Economistas 55: 243–255, 1993). We point out the importance of severance pay settled before judgment, since the legal framework creates a bargaining space to determine the amount paid by firms in cases of individual dismissal. The model is a simple pre‐trial bargaining game between the firm and the worker. It predicts a higher settled severance pay for dismissals on economic grounds than on disciplinary ones, which could explain the perceptions held about the wide use of disciplinary dismissals in Spain. In addition, this approach could be useful in designing labour market reforms aimed at changing dismissal costs, because it allows us to determine the key variables affecting settled severance pay. Our simple model predicts that the key variables for Spain are the severance pay for unfair dismissal and the probability of unfair dismissal.
The Effect of Trade on Employment and Wages in Italian Industry
Authors: Bella Mariano , Quintieri Beniamino
Published: March 2003

The paper analyses the labour market impact of international trade on the Italian manufacturing sector. Using data for a panel of manufacturing industries the effects of trade‐induced changes in sales on employment and wages are investigated. The evidence suggests that the industry adjustment to demand shocks took place mainly through employment changes. However, increased exposure to foreign competition had a small effect on the Italian labour market, while technological change seems to have a major role in explaining the increase in unemployment.
Trade and Labour Markets: Vertical and Regional Differentiation in Italy
Authors: Celi Giuseppe , Segnana Maria Luigia
Published: March 2003

The labour market misfortunes of the less skilled and rapid growth of international trade in manufactured goods with less advanced countries are linked by the paradoxical observation that trade theorists are in the forefront of those denying the importance of trade in income distribution. This paper analyses this conclusion by stressing the importance of vertical differentiation of trade flows and regional differentiation of skills in order to identify labour market effects of trade integration. Vertical and regional differentiation in trade and labour markets are analysed for a country, Italy, where these two elements seem to play a crucial role. The results show a likely displacement effect on unskilled labour due to trade flows with less advanced countries. Given the characteristics of Italian trade and labour markets, a stronger trade‐induced displacement effect on demand for unskilled labour takes place in the North of the country. Thus the vertical differentiation in Italian intra‐industry trade is a warning against understating the effect of trade on labour markets if product heterogeneity is not adequately considered. The regional differentiation of skill intensity is another warning against understating the effect of trade on labour markets whenever cross‐sectoral effects and the change in relative specialization are not adequately considered.
Sibling Rivalry in Educational Attainment: The German Case
Authors: Bauer Thomas , Gang Ira
Published: March 2003

Recent studies exploring sibling rivalry in the allocation of household resources in the USA produce conflicting results. We contribute to this discussion by addressing the role of sibling rivalry in educational attainment in Germany. Using the German Socioeconomic Panel (GSOEP) we are able to distinguish how the effects of sibling rivalry vary by cultural affiliation, i.e. among families of West German, East German and foreign origin. We also point out and correct for a reference group problem in earlier papers analyzing sibling rivalry.
Labour Flows as Determinants of the Wage–Price Spiral: An Empirical Analysis for The Netherlands
Authors: Broersma Lourens , Den Butter Frank A. G.
Published: March 2003

This study presents an empirical analysis of the influence of labour market flows on wage and price formation. A system of wage, price and employment equations after Nickell (Oxford Bulletin of Economics and Statistics 49: 103–128, 1987) is estimated, including labour flows as indicators of labour market tightness in the wage equation. An impulse response analysis using this system shows how changes in the flow of layoffs (flow from employment to unemployment) may be the basis of short‐run Phillips curve effects in The Netherlands
The Dynamics of Occupational Choice: Theory and Evidence
Authors: Drost André
Published: March 2003

In this paper we provide new empirical and theoretical insights into the dynamics of occupational choice. In the empirical part of the paper we analyse West German time series data on the number of first‐year students in more than 50 fields. We show that this number is cyclical in many fields so that occupational choice is cyclical in many professions. In the theoretical part we develop a model that explains cycles in occupational choice. Unlike other models, it is not based on the unrealistic assumption that occupational choice is independent of the risk of unemployment associated with each occupation.
Assessing the Effects of the ‘Mobility Lists’ Programme by Flexible Duration Models
Authors: Paggiaro Adriano , Trivellato Ugo
Published: March 2003

The ‘Mobility Lists’ programme handles collective redundancies, and combines income support to eligible dismissed employees with benefits to employers who hire them. Benefits vary according to dismissing firm size and are greater for older workers. We focus on the differential effects of programme treatments on the probability of moving from unemployment into permanent jobs. We specify flexible duration models in order to estimate the profile of differential effects over time. Older workers, enjoying longer packages of benefits, have significantly lower chances of moving to employment. Differential effects vary with time and are higher when younger workers approach the expiry of benefits.
Firm‐sponsored Apprenticeship Training in Germany: Empirical Evidence from Establishment Data
Authors: Beckmann Michael
Published: March 2003

This paper investigates the determinants of firm‐sponsored apprenticeship training empirically using German firm‐level data. The hypotheses for this study are based mostly on recent theoretical models about the financing of apprenticeship training which take labour market imperfections (e.g. mobility costs, asymmetric information, and wage floors) into account. Applying the usual probit, tobit, and truncated regression models, some empirical evidence is found supporting the relevance of active or passive poaching. Moreover, the results reveal some differences in the training behaviour of West and East German firms.
Main Verb Versus Reduced Relative Clause Ambiguity Resolution in L2 Sentence Processing
Authors: Juffs Alan
Published: March 2003

This study investigated how adult learners of English as a second language (ESL) process sentences containing verbs that are temporarily ambiguous in interpretation between a main verb and a reduced relative clause. Seventeen Chinese, 17 Korean or Japanese, and 17 Romance learners with advanced ESL proficiency and a comparison group of 17 monolingual native speakers (NSs) of English provided word‐by‐word reading times for 6 sentence types. The evidence showed that they used both verb subcategorization information and post‐ambiguity cues to resolve main verb/reduced relative clause ambiguity. The data also indicated that bad post‐ambiguity cues misled some ESL users more than others, differences that can be attributed to their first languages (L1s). These results suggest that (a) like native speakers, ESL speakers are sensitive to the complex interaction of information sources when parsing a sentence; (b) adult ESL learners are influenced by typological properties of their L1s that are linked to L1 parsing strategies when processing ESL.
Phonological Processing of Second Language Phonemes: A Selective Deficit in a Bilingual Aphasic
Authors: Eviatar Zohar , Leikin Mark , Ibrahim Raphiq
Published: March 2003

We present a case study of a Russian‐Hebrew bilingual transcortical sensory aphasic. In general, aphasic symptoms are similar in the 2 languages, with Hebrew being somewhat more impaired. However, the patient reveals a difference in her ability to perceive phonemes in the context of Hebrew words that is dependent on whether they are presented in a Russian or a native accent. This finding is interpreted as showing that a mediating mechanism that assimilates second language phonemes to native language phonological categories is differentially damaged. Implications for models of speech perception in general and second language phonetic perception in particular are discussed.
The Emergence of Linguistic Person in Spanish–Speaking Children
Authors: Mueller Gathercole Virginia C. , Sebastián Eugenia , Soto Pilar
Published: March 2003

Data from 3 children (2 male, 1 female) acquiring Spanish are explored for the development of linguistic person in an inflectional language. Contrastive use of person, tense, and number and the presence of overt subjects and overt objects are examined. Recent claims that person emerges before tense and number and that the latter license overt subjects are not supported. Each of the 3 children follows a different route in the development of person, tense, and number. The data challenge any theory positing uniformity across children, proposing a maturational sequence of innately endowed categories for person, tense, and number, or claiming that Universal Grammar links the emergence of any of these with the presence of overt subjects.
Procedural Justice and Dutch Victim Policy
Authors: Wemmers Jo‐Anne
Published: March 2003

This paper opens with a brief discussion of the traditional role of the victim in the criminal justice system and the changes which have been made in the Netherlands in order to improve the position of victims of crime. In addition, the author discusses the arguments put forward by policymakers and examines the implementation of victim policy. Next, procedural justice is introduced as a theory from which one could consider the possible impact of victims’ experiences in the criminal justice system on their relationship with the justice system. The author goes on to present research which examines the impact of procedural justice on victims’ attitudes towards legal authorities. The paper closes with a discussion of the importance of procedural justice issues for criminal justice policymakers and legal practitioners.
How to Win Hearts and Minds: Corporate Compliance Policies for Sexual Harassment
Authors: Parker Christine
Published: March 2003

Australian law provides incentives and encouragement for companies to develop their own sexual harassment policies. This paper reports on interviews with equal opportunity officers in Australia’s financial services industry responsible for best practice sexual harassment policies. Their experiences evoke three scholarly critiques of corporate compliance as a regulatory strategy: (1) that corporate compliance programs are a means by which employees’ lives are regimented and controlled by corporate governmentality, (2) or, even worse, that private management priorities subvert the principles of public‐regarding law while appearing to implement them, and (3) that even where law has some effect, regulatory strategies aimed at producing self‐regulatory compliance will provide insufficient deterrence to effect real change. The data however also show that the best of these best practice officers have themselves created complex strategies to resolve tensions between law and management, corporate goals, and normative pressures. In doing so, they have had to combine their personal, professional, and corporate commitments to “win hearts and minds” to antiharassment values by co‐opting management resources to compliance goals through strategic appeals to both “business case” arguments and the specter of public sanctions. This project of cooption depends on their own position and “clout” within the corporation.
Juries and Unpredictability in Products Liability Damage Awards
Authors: Graddy Elizabeth
Published: March 2003

The size and variability of jury damage awards in tort cases has been a contentious issue for over a decade. Nevertheless, there has been little empirical work addressing the relationship between the size of jury awards to products liability victims and their compensable losses. This paper examines this relationship using a sample of California cases. A compensatory model of damages based on plaintiff, injury, and case characteristics explains a large proportion of the variance in damage awards suggesting that juries rely heavily on monetary and non‐monetary loss estimates in determining damages. The evidence argues against charges of unpredictability, and indicates undercompensation on average.
Redundancy Pay, Unions and Employment
Authors: Booth Alison L. , McCulloch Andrew
Published: March 2003

In this paper we estimate the determinants of bargaining over redundancy pay, and its impact on employment variation and financial performance, using the 1990 Workplace Industrial Relations Survey. The estimates indicate that bargaining over redundancy pay is more prevalent in plants with a strong union presence. However, voluntary negotiation of redundancy pay does not appear to reduce employment variability in the face of small demand shocks. Bargaining over manual redundancy pay has an insignificant impact on plants’ financial performance, while bargaining over non‐manual redundancy pay has a large significant positive effect. Our findings may explain the positive attitudes to redundancy pay reported by some employers, and reinforce the general conclusion of cross‐country studies that firing constraints in Britain may be relatively unimportant in preventing labour market flexibility.
Responding to Economic Crises: Policy Alternatives for Equitable Recovery and Development
Authors: Stiglitz Joseph
Published: March 2003

While economic crises are becoming more frequent and severe, our experience in East Asia has demonstrated how the international response to these crises remains inadequate. Appropriate policy responses to economic crises entail three essential dimensions: first, the maintenance of full employment and economic stability through macroeconomic policy; second, complementary structural policy aimed at restoring confidence; and finally, a robust social safety net to mitigate the adverse and potentially long‐term effects of economic downturns. A suitable crisis response requires that policy‐makers recognize the critical role of financial markets and the existence of time lags. Suitable policy responses should consider not only an individual economy’s ability to absorb shocks, but also the asymmetries and nonlinearities of alternative policies. As we thus seek to improve our macroeconomic and structural policies for the future prevention and mitigation of crises, it is critical that we bear in mind the protection of the most vulnerable segments of society from the crises that will inevitably occur.