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Projekt

Technological Change, Training and Employment of Older Workers

Projektlaufzeit: 01.05.2015 bis 30.04.2017

Kurzbeschreibung

The introduction of new technologies in the workplace often requires changes in workforce skills. As a result, technological change can increase the rate at which human capital depreciates if it is not paired with training. Empirical evidence indicates that older workers are generally less likely to participate in training activities, which puts their skills at an increased risk of obsolescence. Therefore, technological change might reduce the employability of older workers, increasing their probability of job loss and earlier retirement. Unfortunately, little is known about the extent to which older workers are affected by technological change and if training helps them to overcome skill depreciation. We propose to investigate how technological change affects wage growth, employment status and labor market exit among older workers. We also propose to study whether older workers are less likely than younger workers to receive training after a technological change, and whether training can reduce or even reverse the potential negative effects of technological change on the employment outcomes of older workers. Finally, we study how technological change and training affects older workers’ job satisfaction and job perspectives, which can also influence their decision to exit the labor market. While no systematic data on training activities exists in the United States, let alone data that provide a window on the interplay of employer and employee training activity, such data do exist in Germany. The study of Germany can yield many valid insights for the U.S. labor market, particularly its older workers. By 2035, the mean age of the population in the United States, where older workers are currently the fastest-growing segment of the work force, will be about the same as it was in Germany in the mid-2000s (see Exhibit 1 below). In other words, Germany has already experienced the degree of workforce aging the United States is beginning to experience. Job training is also more salient in Germany than in the United States. Altogether, German workers may expect to have 1,017 hours in job-related non-formal education over their careers, while U.S. workers may expect only 551 hours (OECD, 2011) This is because both the German government and employers sponsor training, while U.S. sponsorship of training activities is more limited. By studying technological change and training of older workers in Germany, we can derive insights about challenges that the United States will face in the near future as its labor force ages and how training may help address some of these challenges. Germany offers rich and accessible data sources that combine social-security records with survey data. The datasets we will use include an establishment survey, a survey of training histories of workers employed at these establishments, social-security earning records of these workers, and still other administrative data on the surveyed establishments, all of which can be linked. The resulting linked data will allow us to study the relationship between technological change, training, and the employment prospects of older workers in a more comprehensive and rigorous way than has been done previously.
This project seeks to answer three questions: i) How does technological change affect older workers’ employment and how does training influence this relationship?; ii) Are older workers less likely than younger ones to get training after technological change?; iii) How do technological change and training affect workers’ job satisfaction and job perspectives? We describe below our empirical approach to each of these questions, but first review previous research regarding technological change, training, and employment of older workers.

Ziel

Wir beantworten die Frage ob Training von älteren Erwerbspersonen helfen kann diese länger im Erwerbsleben zu halten.

Methoden

Regression Analyses, correclated random effects approach

Leitung

Daniela Hochfellner
01.05.2015 - 30.04.2017
Nicole Maestas
01.05.2015 - 30.04.2017