Socio-demographics,political attitudes and informal sector employment: A cross-country analysis

In this paper, we empirically investigate the relationship between informal sector employment and micro-level socio-demographic characteristics, political acts and attitudes, and individual norms. Using self-reported individual micro-level data from the World Values Survey for seven developing countries (China, Ecuador, Egypt, Mexico, Peru, South Africa and Yemen), our cross-country regressions and principal component analysis reveal that socio-demographic characteristics of individuals are strong predictors of their informal sector employment. Our estimations further document that individual preferences for an economically strong, interventionist and egalitarian state and confidence in state and political institutions are positively and significantly correlated with informal sector employment, whereas variables associated with confidence in free market institutions and support for competition are negatively and significantly correlated with informal sector employment. We also show that individuals who participate either actively or inactively in peaceful and lawful political processes are significantly less likely to work in the informal sector. Finally, we document that individual norms, such as religiosity and tax morale, are negatively correlated with informal sector employment. Throughout our analysis, instead of having to rely on ad-hoc informality categorizations of third parties, we base our measurement of informal sector employment directly on the self-evaluation of individuals, who have the best information on the degree of their informality.     

Inequality and entrepreneurial thresholds

We explore the relationship between inequality and entrepreneurial activity. Drawing on cross-sectional data from a largescale survey of the economic conditions of individuals across India, we develop a number of dimensions of inequality to explore empirically how inequality interacts with entrepreneurship, operationalized as self-employment or as employing other people. We find compelling evidence that there are thresholds to becoming self-employed, and even more so to assembling the combinations of resources and personal attributes required to become an employer. Greater inequality leaves more people unable to make the transition to self-employment, leaving casual laboring as the occupation of necessity. At the same time, inequality increases the number of employers in a society, by concentrating resources - particularly land and finance - enough for significant numbers of people to be able to cross this higher threshold. Lastly, greater differentiation into social or religious groups curtails the ability to cross either entrepreneurial threshold, presumably by limiting the extent and benefits of social networks of value for entrepreneurship.     

When age does not harm innovative behavior and perceptions of competence: Testing interdepartmental collaboration as a social buffer

Can older managers overcome stereotypes relating age to low competence? We integrate the literature on age and cognitive ability with research on innovation to explore whether—and if so, when—employees' age harms performance and promotability appraisals made by their supervisors. Multisource, time‐lag data from 305 project managers indicate that the negative stereotypes can be explained through decreased innovative behavior. However, older employees are not always seen as poorer performers with less potential to be promoted due to their reduced innovative behavior. Rather, interdepartmental collaboration moderates these effects. Specifically, older employees with low interdepartmental collaboration are less innovative and receive worse performance and promotability appraisals than younger employees, but the “age handicap” vanishes when older employees collaborate with members of other departments. Organizations should foster formal or informal collaboration among units to prevent negative consequences of an aging workforce.     

Effect of mobile teaching on students who need special education

The purpose of this study is to test the mobile application designed for the teaching purposes of students who need special education. Many mobile applications and software are available for teaching, thus this study will point the effect of using such technologies in teaching activities as an assistive method to the teacher. The tests are done using our previously designed mobile application that is designed to teach the basic concepts. As it is indicated in the design, the process starts with the testing of the basic abilities of the children, therefore, our tests include these kind of pretests and after that testing phases that will measure the effect of the application to learning. Students who need special education are the focus of the study. The tests are carried out in a special education centre, in Nicosia, Northern Cyprus on two students. Test results show that the mobile application developed in its current form, is a good tool to assist the teachers to enhance and speed up the learning process.

     

Who do you care about? Scientists’ personality traits and perceived impact on beneficiaries

We investigate the roots of scientists' perceptions of the impact of their work by examining stable psychological characteristics such as personality traits. An analysis of personality traits highlights the effects of policies related to gender equality, allocation of research time and skills acquisition. It improves our understanding of the conflicts related to scientists’ perceptions of the impact of their research on beneficiaries. For example, conscientiousness increases the perceived impact on clinical beneficiaries, but reduces the perceived impact on industrial beneficiaries. Organizational scientific freedom increases the effects of personality traits on perceived impact on beneficiaries such that scientists affiliated to a university are less likely than colleagues working in other research settings to perceive the simultaneous impact of their work on both industrial and clinical beneficiaries.     

Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.     

The impact of purchasing strategy-structure (mis)fit on purchasing cost and innovation performance

The organizational design literature strongly supports the notion of “structure follows strategy”, and suggests that a misfit between the two has a negative effect on performance. Building on this line of argument, we examine to what extent the (mis)fit between purchasing strategy and purchasing structure impacts purchasing performance. We focus on cost and innovation purchase category strategies, and examine how the deviation from an ideal purchasing structure defined along three dimensions (centralization, formalization, and cross-functionality) impacts purchasing performance. Analysing data collected from 469 firms in ten countries, we demonstrate that a strategy-structure misfit negatively impacts purchasing performance in both cost and innovation strategies. We also find that purchasing proficiency is a mediator in this relationship between misfit and performance. Our findings aid managerial decision making by empirically validating the necessity of having the right purchasing structure for successfully executing different purchasing strategies.     

Inflation,real economic growth and unemployment expectations: an empirical analysis based on the ECB survey of professional forecasters

Expectations are at the centre of modern macroeconomic theory and policymakers. In this article, we examine the predictive ability and the consistency properties of macroeconomic expectations using data of the European Central Bank (ECB) Survey of Professional Forecasters (SPF). In particular, we provide evidence on the properties of forecasts for three key macroeconomic variables: the inflation rate, the growth rate of real gross domestic product and the unemployment rate.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.