The education pillar of the Europe 2020 strategy: a convergence analysis

Empirica - In March 2010, the European Commission launched the Europe 2020 strategy ‘for smart, sustainable and inclusive growth’ in the EU. Education is a major pillar of the Europe...     

Data-based mechanistic modelling and forecasting globally averaged surface temperature

The main objective of this paper it to model the dynamic relationship between global averaged measures of Total Radiative Forcing (RTF) and surface temperature, measured by the Global Temperature Anomaly (GTA), and then use this model to forecast the GTA. The analysis utilizes the Data-Based Mechanistic (DBM) approach to the modelling and forecasting where, in this application, the unobserved component model includes a novel hybrid Box-Jenkins stochastic model in which the relationship between RTF and GTA is based on a continuous time transfer function (differential equation) model. This model then provides the basis for short term, inter-annual to decadal, forecasting of the GTA, using a transfer function form of the Kalman Filter, which produces a good prediction of the ‘pause’ or ‘levelling’ in the temperature rise over the period 2000 to 2011. This derives in part from the effects of a quasi-periodic component that is modelled and forecast by a Dynamic Harmonic Regression (DHR) relationship and is shown to be correlated with the Atlantic Multidecadal Oscillation (AMO) index.     

The power of positivity? The influence of positive psychological capital language on crowdfunding performance

We extend the entrepreneurship literature to include positive psychological capital — an individual or organization's level of psychological resources consisting of hope, optimism, resilience, and confidence — as a salient signal in crowdfunding. We draw from the costless signaling literature to argue that positive psychological capital language usage enhances crowdfunding performance. We examine 1726 crowdfunding campaigns from Kickstarter, finding that entrepreneurs conveying positive psychological capital experience superior fundraising performance. Human capital moderates this relationship while social capital does not, suggesting that costly signals may, at times, enhance the influence of costless signals. Post hoc analyses suggest findings generalize across crowdfunding types, but not to IPOs.     

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.     

Capital gains lock-in and governance choices

Differences in accrued gains and investors’ tax-sensitivity induce variation in a capital gains lock-in effect across mutual funds even for the same stock at the same time. Exploiting this variation, we show this effect influences funds’ governance decisions: higher capital gains decrease the likelihood a fund exits prior to contentious votes and increase the likelihood a fund votes against management. Consistent with tax motivation, these findings are concentrated among funds with tax-sensitive investors. Further, high aggregate capital gains across funds holding a stock predict a higher likelihood management loses a vote and a lower likelihood a contentious vote is proposed.     

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.     

Using performance-based warranties to influence consumer purchase decisions

Abstract

Traditional warranty analysis focuses on the reliability of a product and offers warranty designs that compensate a consumer if the item fails. We introduce the concept of a performance-based warranty (PBW) that guarantees that a product will operate at or above some baseline level of performance, such as a minimum energy efficiency for an appliance. We illustrate how consumer behavior can change in the presence of a PBW and define the parameters for which a manufacturer may increase revenue. Finally, we present an algorithm to solve for the optimal PBW design given a consumer’s belief about the expected performance of the product.     

COVID-19 and business renewal: Lessons and insights from the global airline industry

The emergence of the COVID-19 pandemic has adversely affected the fortunes of multiple companies around the globe. Accordingly, questions are increasingly being asked about how organizations can revitalize during and after a crisis. Yet, we have limited understanding of how organizations renew themselves during crises over time. We explore this question through the lens and examination of two South-Asian airlines: Pakistan International Airlines and Sri Lankan Airlines. The cases offer important insights into the reasons behind underperformance of state-controlled enterprises and renewal activities. We shed light on strategic renewal (SR) in the wake of increasing liberalization and deregulations in the global airline industry. To this end, we propose a four-stage approach towards renewing such underperforming organizations to respond effectively to black swan events and external shocks.     

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.