Shall we keep the highly skilled at home? The optimal income tax perspective

We examine how allowing individuals to emigrate to pay lower taxes abroad changes the optimal non-linear income tax scheme in a Mirrleesian economy. An individual emigrates if his domestic utility is less than his utility abroad net of migration costs, utilities and costs both depending on productivity. Three average social criteria are distinguished—national, citizen and resident—according to the agents whose welfare matters. A curse of the middle-skilled occurs in the first-best, and it may be optimal to let some highly skilled leave the country under the resident criterion. In the second-best, under the Citizen and Resident criteria, preventing emigration of the highly skilled is not necessarily optimal because the interaction between the incentive-compatibility and participations constraints may cause countervailing incentives. In important cases, a Rawlsian policymaker should decrease top marginal tax rates to keep everyone at home.     

Recognizing experiential knowledge in the process of qualification of peer helpers: an analysis of an educational program for service users in France

ABSTRACT

This article analyzes an innovative training program enabling the qualification of peer carers, working within the sector of ‘social inclusion’. Since the French national debate on social work conducted within the ‘Estates General’ of 2015, peer workers have become key players in training programs in virtue of their experiential knowledge and their understanding of issues related to the process of social exclusion. This article addresses the role of peer helpers’ experiential knowledge in the training process. Because of their ‘experiential’ and ‘empirical’ knowledge about questions linked to the process of exclusion, peer helpers have become key players in social work teams and within social institutions, thus contributing to new methods of socio-educational intervention. What impact will this recognition of peer helpers’ and service users’ experiential knowledge have on education in social work? This article gives an account of an 8-month training program for peer helpers examined on the methodological level through a process of Participant observation, and based on data from comprehensive interviews carried out with a panel of peer helpers.     

On the Use of Paradox for Generating Theoretical Contributions in Management and Organization Research

Although research relating to paradox has burgeoned throughout the past decades, how paradox has been used in generating theoretical contributions remains largely tacit. Hinging on the systematic analysis of 476 publications, this literature review uncovers how scholars have leveraged paradox in demarcating theoretical contributions in the area of management and organization research. First, scholars can make use of paradox as a means to theorize, adding to the core conceptual conversation on paradox. Second, scholars can make use of paradox as a means to understand or advance insight on particular phenomena, drawing from paradox's conceptual knowledge to push forth discussions or debates in other strands of the management and organization field. Finally, scholars can make use of paradox as a way to verbalize something puzzling or surprising, supporting how readers are to appreciate or make sense of theoretical contributions advanced. Denoting approaches identified as highly complementary, this paper offers explicit handholds for academics to develop theoretical contributions through paradox, supporting the consolidation and further elevation of scholarly impact for the paradox community as such.     

Test of Normality Against Generalized Exponential Power Alternatives

The family of symmetric generalized exponential power (GEP) densities offers a wide range of tail behaviors, which may be exponential, polynomial, and/or logarithmic. In this article, a test of normality based on Rao's score statistic and this family of GEP alternatives is proposed. This test is tailored to detect departures from normality in the tails of the distribution. The main interest of this approach is that it provides a test with a large family of symmetric alternatives having non-normal tails. In addition, the test's statistic consists of a combination of three quantities that can be interpreted as new measures of tail thickness. In a Monte-Carlo simulation study, the proposed test is shown to perform well in terms of power when compared to its competitors.     

Using large data sets to forecast sectoral employment

We use several models using classical and Bayesian methods to forecast employment for eight sectors of the US economy. In addition to using standard vector-autoregressive and Bayesian vector autoregressive models, we also augment these models to include the information content of 143 additional monthly series in some models. Several approaches exist for incorporating information from a large number of series. We consider two multivariate approaches—extracting common factors (principal components) and Bayesian shrinkage. After extracting the common factors, we use Bayesian factor-augmented vector autoregressive and vector error-correction models, as well as Bayesian shrinkage in a large-scale Bayesian vector autoregressive models. For an in-sample period of January 1972 to December 1989 and an out-of-sample period of January 1990 to March 2010, we compare the forecast performance of the alternative models. More specifically, we perform ex-post and ex-ante out-of-sample forecasts from January 1990 through March 2009 and from April 2009 through March 2010, respectively. We find that factor augmented models, especially error-correction versions, generally prove the best in out-of-sample forecast performance, implying that in addition to macroeconomic variables, incorporating long-run relationships along with short-run dynamics play an important role in forecasting employment. Forecast combination models, however, based on the simple average forecasts of the various models used, outperform the best performing individual models for six of the eight sectoral employment series.     

Revealed versus hidden attributes as determinants of percieved product quality

Consumers' quality perception being interpreted as an overall product evaluation process, attribute importance is introduced as a mediating variable between the quality judgment and informational value of cues. Furthermore, all product attribute being classified into two different categories, revealed vs. hidden attributes, it is hypothesized that extrinsic cues can influence consumers' product evaluation only on the hidden quality attributes but not on the revealed quality attributes.     

The impossibility of a Paretian egalitarian

In a one-good world, there is a nice correspondence between the Pigou-Dalton principle of transfer and social welfare dominance. In this paper we study the case of multiple goods (without using prices as a means to come back to one dimension), and show that many results of the one-dimensional setting carry over to the multidimensional case when individuals are assumed to have identical preferences. But the nice correspondence breaks down as soon as individual preferences display minimal differences, and multidimensional versions of the transfer principle clash with the Pareto principle. This analysis reveals an interesting connection with the theory of fair allocation, since multidimensional transfer principles are closely related to the no-domination criterion, a weak version of the no-envy criterion.For helpful comments, we thank J. L. Castillo, M. Le Breton, Y. Sprumont, K. Suzumura and participants at a workshop in Osnabrück, a LivinTax conference in Bordeaux and a seminar in Hitotsubashi University, as well as two referees. Financial support from TMR project Living Standards, Inequality and Taxation Contract no ERBFMXCT 980248 of the European Commission is gratefully acknowledged. We thank Michel Le Breton for giving us the permission to state a result contained in his unpublished Ph D thesis.     

Segmentation of the mean of heteroscedastic data via cross-validation

This paper tackles the problem of detecting abrupt changes in the mean of a heteroscedastic signal by model selection, without knowledge on the variations of the noise. A new family of change-point detection procedures is proposed, showing that cross-validation methods can be successful in the heteroscedastic framework, whereas most existing procedures are not robust to heteroscedasticity. The robustness to heteroscedasticity of the proposed procedures is supported by an extensive simulation study, together with recent partial theoretical results. An application to Comparative Genomic Hybridization (CGH) data is provided, showing that robustness to heteroscedasticity can indeed be required for their analysis.