Does Premature Deindustrialization Matter? The Role of Manufacturing versus Services in Development

“Premature deindustrialization” typically reflects the fact that the services sector has grown faster than manufacturing at lower levels of per capita income compared to the past. This paper, based on cross-country data, shows that the rising share of services is largely not driven by a statistical artifact whereby what was earlier subsumed in manufacturing value added is now accounted for as service sector contributions. Yet, this matters less for development opportunities because features of manufacturing that were thought of as uniquely special for productivity growth are also shared by some services. And the growth of these high-productivity services is not closely linked to a manufacturing base as it draws on both intermediate demand from other sectors as well as final demand from home and abroad. The prospect of services-led development in lower-income countries however, is limited by the fact that a given service subsector is unlikely to provide opportunities for productivity growth and job creation for unskilled labor simultaneously.

Australia

This chapter examines speeches in the Australian House of Representatives from 1990-2019. Our findings are primarily determined by the nature of Australia’s Westminster-style system, where the government tends to dominate proceedings. We find strong party effects, government versus opposition effects, and strong ministerial effects on the amount and duration of speeches. The descriptive statistics demonstrate that women and less experienced parliamentarians speak less than male and experienced ones. The gender effect also holds when controlling for ministerial selection. The latter is likely to be explained by men being given more important and prestigious ministerial portfolios. We also find that opposition MPs speak more on average than non-ministers on the government side. However, that is mostly a statistical artifact of their necessarily being fewer opposition MPs, but the rules give both sides of the House approximately equal time to speak. While both gender and seniority are predictive of how much people speak, this is mediated by the fact ministers speak more.

Is the DLOQ learning-oriented leadership isomorphic? Learning-oriented leadership mediates hierarchical teams’ learning dimensions

Purpose Learning organizations are often theorized at a team level, yet there is a lack of team-level studies. This study aims to evaluate if team-level dimensions of a learning organizational questionnaire (DLOQ) measures are reliable and reflect real team properties and if both individual-level and team-level DLOQ leadership mediates the effect of rank on other DLOQ measures. Design/methodology/approach An empirical analysis evaluated if team-level DLOQ measures are reliable and reflected real team properties and if DLOQ learning-oriented leadership mediates the effect of rank or team hierarchy on all other DLOQ measures. A novel approach (random group resampling) was used to evaluate if team level measures reflected either a real team property or a statistical artifact. Next, a series of mediation models evaluated if learning-oriented leadership was isomorphic, namely, displays a similar pattern at both individual and team levels. Findings The analysis found team-level DLOQ measures reflected real properties of the teams and were reliable and learning-oriented leadership mediates between rank and team hierarchy and the other six dimensions at both individual and team-levels (i.e. DLOQ team and individual level were isomorphic). Practical implications The results show that hierarchical teams’ learning capacities can be improved by focusing on the learning-oriented leadership, which overcomes the typically negative effect of hierarchical differences within teams. Originality/value This study provides a significant step forward by applying an innovative analysis that shows that the DLOQ team level measures reflect real team properties and DLOQ leadership displays isomorphic characteristics.

REGRESSION TO THE MEAN: METHODOLOGICAL ISSUES FOR EVALUATION OF HEART RATE VARIABILITY VARIABLES FOR STRESS ASSESSMENT

There is now a substantial body of evidence linking the baseline level of heart rate variability (HRV) with the magnitude of stress-induced reduction in respiratory sinus arrhythmia. However, it remains to be proved to what extent these interindividual differences in stress responses may be attributed to the statistical phenomenon of regression to the mean (RTM). We sought to test the hypothesis that the statistical artifact RTM explains pan of the baseline effect. Heart rate recording was carried out in 1156 volunteers. To obtain an estimate of the stress response. 148 persons were randomly selected. Participants were monitored on a rest day and just before an academic examination for state anxiety and HRV. Participants were divided into quartiles according to baseline HRV levels and were compared for response to academic stress. We observed a significant reduction in HRV in subjects with a high baseline HRV (> 75th percentile), while a significant increase was found in the group with low baseline HRV. Regression analysis demonstrated that the value of baseline HRV correlated with the magnitude of stress reaction consistent with the RTM model. Baseline-adjusted ANCOVA does not reveal significant intergroup differences in the changes hi heart rate (HR) and HRV from rest to exam. RTM-adjusted estimates confirmed an exam effect for HR and HRV. The results of our study strongly support RTM as the source of variability of stress-related changes in HRV.

WORKING CLASS IN THE CURRENT SOCIOLOGICAL STUDIES: RUSSIAN CONTEXT

For many years, the working class has been an object of interest for Russian sociology. In Soviet sociology, a lot of research has been devoted to workers and industrial sociology. The point of attention of sociologists moved towards the study of labor relations and the protest movement in enterprises in the 1990s. Then the workers stopped being in the center of attention of sociology, but now interest in the working class is returning. This article is a form of analytical reflection on the research agenda for the study of workers by Russian sociologists. The analysis is based on publications on the research of Russian workers in the leading Russian sociological journals. Workers are considered as a social and professional group that is in a status crisis as an archaic social class that lost in the course of market reforms and represents an obstacle to modernization. Russian authors point to the return of the significant role of industrial workers against the background of a focus on the technological breakthrough of the Russian economy. An analysis of publications also shows that in recent years, researchers have found it difficult to access enterprises to study workers in their work environment, which affects the understanding of the situation of industrial workers in Russia. Workers have become a popular and convenient object of study as a statistical artifact present in sociological data bases, but sometimes this data speaks little of the real situation of the industrial working class. The article emphasizes the growing interest of Russian sociologists to workers and new approaches to their study, including the biographical method and the included observation.

Arrested Development? Puerto Rico in an American Century

Puerto Rico became an American colony in 1898, achieving self-rule after the Great Depression. The standard view is that Puerto Rican living standards stagnated before the policy changes of the New Deal and it has lost ground on the mainland since the early 1970s. I show these claims are mistaken. Using a new GDP index for 1900 to 1940, I show that income per capita grew at impressive rates during direct American rule and Puerto Rico escaped the worst ravages of the Great Depression. In addition, I find the recent growth slowdown is partly a statistical artifact.

Not Restricted to Selection Research: Accounting for Indirect Range Restriction in Organizational Research

Range restriction is a common problem in organizational research and is an important statistical artifact to correct for in meta-analysis. Historically, researchers have had to rely on range-restriction corrections that only make use of range-restriction information for one variable, but it is not uncommon for researchers to have such information for both variables in a correlation (e.g., when studying the correlation between two predictor variables). Existing meta-analytic methods incorporating bivariate range-restriction corrections overlook their unique implications for estimating the sampling variance of corrected correlations and for accurately assigning weights to studies in individual-correction meta-analyses. We introduce new methods for computing individual-correction and artifact-distribution meta-analyses using the bivariate indirect range restriction (BVIRR; “Case V”) correction and describe improved methods for applying BVIRR corrections that substantially reduce bias in parameter estimation. We illustrate the effectiveness of these methods in a large-scale simulation and in meta-analyses of expatriate data. We provide R code to implement the methods described in this article; more comprehensive and robust functions for applying these methods are available in the psychmeta package for R.

Not restricted to selection research: Accounting for indirect range restriction in organizational research

Range restriction is a common problem in organizational research and is an important statistical artifact to correct for in meta-analysis. Historically, researchers have had to rely on range-restriction correc-tions that only make use of range-restriction information for one variable, but it is not uncommon for researchers to have such information for both variables in a correlation (e.g., when studying the cor-relation between two predictor variables). However, existing meta-analytic methods incorporating these corrections overlook their unique implications for estimating the sampling variance of corrected correlations and for accurately assigning weights to studies in individual-correction meta-analyses. We introduce new methods for computing individual-correction and artifact-distribution meta-analyses us-ing the bivariate indirect range-restriction (BVIRR; “Case V”) correction and describe improved meth-ods for applying BVIRR corrections that substantially reduce bias in parameter estimation. We illustrate the effectiveness of these methods in a large-scale simulation and in meta-analyses of expatriate data. We provide R code to implement the methods described in this article; more comprehensive and robust functions for applying these methods are available in the psychmeta package for R (Dahlke & Wiernik, 2018, 2017/2019).