Inga Freund

The changing face of cognitive gender differences in Europe

Significance Results showing that gender differences in mathematics and science are smaller in countries with higher gender equality have led researchers to conclude that cognitive gender differences are decreasing as a function of increased gender equality. Instead, we find that improved living conditions and less gender-restricted educational opportunities are associated with increased gender differences favoring women in some cognitive functions and decreases or elimination of gender differences in other cognitive abilities. Our results suggest that these changes take place as a result of women gaining more than men from societal improvements over time, thereby increasing their general cognitive ability more than men. Cognitive gender differences and the reasons for their origins have fascinated researchers for decades. Using nationally representative data to investigate gender differences in cognitive performance in middle-aged and older populations across Europe, we show that the magnitude of these differences varies systematically across cognitive tasks, birth cohorts, and regions, but also that the living conditions and educational opportunities individuals are exposed to during their formative years are related to their later cognitive performance. Specifically, we demonstrate that improved living conditions and less gender-restricted educational opportunities are associated with increased gender differences favoring women in some cognitive functions (i.e., episodic memory) and decreases (i.e., numeracy) or elimination of differences in other cognitive abilities (i.e., category fluency). Our results suggest that these changes take place due to a general increase in women’s cognitive performance over time, associated with societal improvements in living conditions and educational opportunities.

A Matched Employer-Employee Panel Data Set for Austria: 2002-2005

Matched employer-employee (panel) data sets are gaining increasing importance in the analysis of labour markets. In collaboration with Statistics Austria we recently initiated the set up of a matched employer-employee panel data set for Austria, which covers the years 2002-2005. The aim of the paper is to introduce the data set to a broader audience. We first present the set up of the panel data, indicating in more detail the data sources and matching procedure underlying the matched employer-employee data set for Austria. In a second step we show descriptive statistics of the main variables included in our data set. These various statistics encompass three levels of analysis: the aggregate level (i.e. the entire sample), firm level and individual (employee) level.

Firm Productivity, Workforce Age, and Vocational Training in Austria

Controlling for training effort at the firm level as well as for firm-specific characteristics we assess the relation between the firm’s productivity level and the age composition of its employees using a matched employer-employee data set for Austria. Our aim is to test whether the hump-shaped age profile of the employees’ age structure on labour productivity that we found in previous studies is robust once we control for training intensity. We find a simultaneous, negative productivity effect of the share of young workers and old workers on labour productivity in sample of small as well as in sample of large firms. Furthermore it turns out that training intensity is an important variable for labour productivity.

Ageing, Productivity and Wages in Austria: Evidence from a Matched Employer-Employee Data Set at the Sector Level

In this paper we analyse the link between the age structure of the labour force and average labour productivity at the intermediate level of economic sectors. The analysis is based on a panel data set ranging over six years (2002-2007) and covers the sectors of mining, manufacturing and market oriented services in the Austrian economy. Our results exhibit a positive correlation of the share of older employees and productivity, while we cannot find any evidence for a significant relationship of the share of younger employees and productivity. Moreover, the estimated age-wage pattern does not hint at an over-payment of older employees.