Browsing by Subject "Automation"

Now showing 1 - 11 of 11
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    Automation and demographic change
    (2017) Abeliansky, Ana; Prettner, Klaus
    We analyze the effects of declining population growth on the adoption of automation technology. A standard theoretical framework of the accumulation of traditional physical capital and of automation capital predicts that countries with a lower population growth rate are the ones that innovate and/or adopt new automation technologies faster. We test the theoretical prediction by means of panel data for 60 countries over the time span from 1993 to 2013. Regression estimates provide empirical support for the theoretical prediction and suggest that a 1% increase in population growth is associated with approximately a 2% reduction in the growth rate of robot density. Our results are robust to the inclusion of standard control variables, the use of different estimation methods, the consideration of a dynamic framework with the lagged dependent variable as regressor, and changing the measurement of the stock of robots.
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    Automation, robots and wage inequality in Germany : a decomposition analysis
    (2020) Schmid, Ramona; Brall, Franziska
    We analyze how and through which channels wage inequality is affected by the rise in automation and robotization in the manufacturing sector in Germany from 1996 to 2017. Combining rich linked employer-employee data accounting for a variety of different individual, firm and industry characteristics with data on industrial robots and automation probabilities of occupations, we are able to disentangle different potential causes behind changes in wage inequality in Germany. We apply the recentered influence function (RIF) regression based Oaxaca-Blinder (OB) decomposition on several inequality indices and find evidence that besides personal characteristics like age and education the rise in automation and robotization contributes significantly to wage inequality in Germany. Structural shifts in the workforce composition towards occupations with lower or medium automation threat lead to higher wage inequality, which is observable over the whole considered time period. The effect of automation on the wage structure results in higher inequality in the 1990s and 2000s, while it has a significant decreasing inequality effect for the upper part of the wage distribution in the more recent time period.
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    Automatisierung, Wachstum und Ungleichheit
    (2018) Schwarzer, Johannes; Prettner, Klaus; Geiger, Niels
    Die Automatisierung stellt eines der wichtigsten Phänomene dar, welche aktuell innerhalb der Wirtschaftswissenschaften und der breiteren Öffentlichkeit diskutiert werden. Dabei finden sich in Bezug auf die Frage, wie sich die Automatisierung gesamtwirtschaftlich auswirkt, sehr unterschiedliche Positionen: Am einen Ende wird auf die negativen Beschäftigungseffekte verwiesen, wenn Menschen mehr und mehr durch Maschinen ersetzt werden und ihre am Markt angebotene Arbeitsleistung nicht mehr nachgefragt somit obsolet wird. Gleichzeitig wird die Automatisierung auch für einen Anstieg der wirtschaftlichen Ungleichheit verantwortlich gemacht. Optimistischere Stimmen verweisen andererseits auf die Entwicklung seit der Industriellen Revolution, die durch fortlaufende technologische Veränderungen mit hohem Produktivitätswachstum und damit starken Wohlfahrtssteigerungen einherging, ohne dass es langfristig zu Massenarbeitslosigkeit gekommen ist. Der vorliegende Aufsatz diskutiert einige allgemein relevante empirische Daten und skizziert ein einfaches theoretisches Wachstumsmodell zur Analyse der Automatisierung. Die hierbei festgehaltenen Ergebnisse werden unter Bezugnahme auf die aktuelle wirtschaftswissenschaftliche Literatur zu den bisherigen und für die Zukunft zu erwartenden ökonomischen Effekten der Automatisierung vertieft und erweitert. Aus den verschiedenen Ansatzpunkten und Überlegungen werden schließlich wirtschaftspolitische Handlungsmöglichkeiten abgeleitet, wobei auch jeweils diskutiert wird, welchen Einschränkungen diese Maßnahmen unterliegen.
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    Four essays on the impact of institutions, technological change, and globalization on labor market outcomes
    (2019) Cords, Dario; Beißinger, Thomas
    The thesis picks up some modern labor market phenomena and contributes to the literature by developing four theoretical models to analyze the effects on labor market outcomes. In particular, it 1) examines how the decision of labor unions to merge or to stay independent depends on the degree of product differentiation, 2) investigates the macroeconomic effects of the deregulation of temporary agency employment, 3) discusses if low-skilled workers will be substituted by automation, and 4) studies how the technological choice of firms in an economy changes due to low-skilled immigration. The first model focuses on the question of the optimal economic behavior of labor unions under multi-unionism. Developing a right-to-manage model, it analyzes how the decision of labor unions to merge or to stay independent depends on the degree of product differentiation. The model predicts that labor unions have strict incentives to merge if the products are substitutable in consumption, while they want to stay separated for complementary products. The second model studies the effects of the deregulation of temporary agency employment on labor market outcomes such as wages, unemployment, and the employment structure. It develops a search and matching model with large firms that produce differentiated goods using regularly employed workers that are organized in labor unions and, in addition, temporary agency workers that may search on-the-job for regular employment. The model shows that the legal deregulation of temporary agency employment increases overall employment and the rate of regular employment. The rate of regular employment increases, since labor unions reduce their wage claims in response to the deregulation of temporary agency employment. As the most surprising result, the model predicts a hump-shaped relationship between the degree of legal deregulation of temporary agency employment and its employment rate. This is explained by voluntary, non-institutional firm-level agreements that restrict the use of temporary agency employment in the production and get more important, the more deregulated temporary agency employment is. The third model incorporates automation in the search and matching framework to reveal if automation creates technological, skill-specific unemployment. The model assumes one-worker firms that operate in a low- or high-skill intensive intermediate sector and employ low- or high-skilled workers, respectively. The two intermediate goods, traditional capital and automation capital in form of industrial robots, 3D printer etc. are used for the production of a final good. Automation capital serves as a perfect substitute for low-skilled labor and an imperfect substitute for high-skilled labor. The model shows that the accumulation of automation capital leads to the creation of technological unemployment. While the unemployment rate of high-skilled workers decreases, low-skilled workers suffer and get replaced by automation capital. Further, the model predicts that wage inequality between high- and low-skilled workers rises as the wage rate of low-skilled workers declines, while the wage rate of high-skilled workers increases. The fourth model examines how the technological choice of firms in a host country change due to an exogenous inflow of low-skilled immigrants. It uses a search and matching model that considers two type of firms that either use a basic technology or a more advanced technology. Workers match with vacancies randomly and consist of three groups: low- and high-skilled natives and low-skilled immigrants. While the skill distribution of workers is exogenous, firms may endogenously adjust their skill requirements. Another feature of the model is that it captures educational mismatch of high-skilled natives. The model rather intuitively suggests that an increase in low-skilled immigration causes firms to change their behavior and to shift their production towards the basic technology. As a consequence, low-skilled natives benefit from the influx of low-skilled immigrants, while the wage rate of high-skilled natives decreases, whereas their employment rate goes up.
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    On the possibility of automation-induced stagnation
    (2017) Gasteiger, Emanuel; Prettner, Klaus
    We analyze the long-run growth effects of automation in the standard overlapping generations framework. We show that, in contrast to other neoclassical models of capital accumulation, automation does not promote growth but induces economic stagnation. The reason is that automation suppresses wages, which are the only source of investment in the overlapping generations framework.
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    Robots and the skill premium : an automation-based explanation of wage inequality
    (2017) Lankisch, Clemens; Prettner, Klaus; Prskawetz, Alexia
    We analyze the effects of automation on the wages of high-skilled and low- skilled workers and thereby on the evolution of wage inequality. Our model explains the simultaneous presence of i) increasing per capita GDP, ii) de-clining real wages of low-skilled workers, and iii) an increasing skill-premium. These developments are consistent with the experience in the United States over the past decades and have the potential to contribute to the explanation of the rise in overall incomeinequality that we have observed since the 1980s.
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    Technological unemployment revisited : automation in a searchand matching framework
    (2018) Prettner, Klaus; Cords, Dario
    Will low-skilled workers be replaced by automation? To answer this question, we set up a search and matching model that features two skill types of workers and includes automation capital as an additional production factor. Automation capital is a perfect substitute for low-skilled workers and an imperfect substitute for high-skilled workers. Using this type of model, we show that the accumulation of automation capital decreases the labor market tightness in the low-skilled labor market and increases the labor market tightness in the high-skilled labor market. This leads to a rising unemployment rate of low-skilled workers and a falling un- employment rate of high-skilled workers. In addition, automation leads to falling wages of low-skilled workers and rising wages of high-skilled workers.
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    The implications of automation for economic growth and the labor share
    (2016) Prettner, Klaus
    We introduce automation into a standard model of capital accumulation and show that (i) there is the possibility of perpetual growth, even in the absence of technological progress; (ii) the long-run economic growth rate declines with population growth, which is consistent with the available empirical evidence; (iii)there is a unique share of savings diverted to automation that maximizes long-run growth; (iv) the labor share declines with automation to an extent that fits to the observed pattern over the last decades.
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    The lost race against the machine : automation, education and inequality in an R&D-based growth model
    (2017) Prettner, Klaus; Strulik, Holger
    We analyze the effect of automation on economic growth and inequality in an R&D-based growth model with two types of labor: highskilled labor that is complementary to machines and low-skilled labor that is a substitute for machines. The model predicts that innovationdriven growth leads to increasing automation, an increasing skill premium, an increasing population share of graduates, increasing income and wealth inequality, a declining labor share, and (in an extension of the basic model) increasing unemployment. In contrast to Pikettys famous claim that faster economic growth reduces inequality, our theory predicts that faster economic growth promotes inequality.
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    Three essays on wage inequality in Germany : the impact of automation, migration and the minimum wage
    (2023) Schmid, Ramona Elisabeth; Beißinger, Thomas
    Economic inequality has increased in the majority of countries worldwide over the last three decades and is highly present in public discussion, political debate and scientific research. Due to the large number and complexity of driving forces behind changes in wage inequality, this cumulative dissertation focuses on three challenges of the German labour market. The first paper addresses the question to which extent automation and robotization impact wage inequality in the manufacturing sector in Germany between 1996 and 2017. Applying decomposition analyses along the entire wage distribution, driving factors behind changes in wage inequality are identified. On the basis of administrative data and a new introduced measure of automation threat, which combines occupation- and requirement-specific scores of automation risk with yearly sector-specific robot densities, the study provides new evidence to existing literature. Besides the traditional factors education and age, the detailed decomposition analysis provides evidence that automation threat contributes significantly to rising wage inequality. On the one hand, changes in the composition of the workforce that is exposed to automation and robotization led to significant increases in wage inequality in the German manufacturing sector during the last two decades. On the other hand, evidence of a growing wage dispersion between occupations with low automation threat (especially associated with non-routine tasks) and occupations with high automation threat (especially associated with routine tasks) is revealed. This trend contributes to rising wage inequality as predicted by routine-biased technological change. The second research study presents new evidence on immigrant-native wage differentials in consideration of regional differences between metropolitan and non-metropolitan areas between 2000 and 2019 in Germany. Since gaps in remuneration provide information on the effectiveness of immigration and labour market policies as well as identify the degree of economic integration of foreign workers, the analysis is currently of great importance. Using administrative data, aggregate decomposition results support the hypothesis that the majority of wage differentials can be explained by differences in observed characteristics. However, overall wage differentials at the median exhibit an increasing trend, and on average higher gaps in remuneration are revealed in urban areas. Detailed decomposition analyses show that the effects of explanatory factors not only change over time but the sources of gaps also vary along the wage distribution. Decisive explanatory variables in this context are the practised profession, the economic sector affiliation and labour market experience. Distinguishing between metropolitan and non-metropolitan areas provides evidence that especially differences in educational attainment impact immigrant-native wage gaps in urban areas. The third paper evaluates the effects of the introduced national minimum wage in 2015 on the gender wage gap in Germany. Being confronted with a low-wage sector of considerable extent and comparably high wage differentials between men and women, this study on Germany provides necessary new insights in this area of research. On the basis of administrative data and counterfactual difference-in-differences analyses significant decreases of wage gaps between men and women that can be traced back to the introduced statutory wage floor are revealed. Especially at the lowest observed wage level and in the East of Germany the highest decreases are observable. The analysis, differentiated by educational level, age and occupational activity, provides detailed information on the effectiveness of the wage floor for different target groups. In particular, at lower wage levels for the least educated and middle aged workers the introduction of the minimum wage is the driving factor that significantly lowers group-specific gender wage gaps. Counterfactual decomposition analyses finally provide first evidence that in the West of Germany possible discrimination against women at the lowest wages is restricted by the wage floor.
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    Die wirtschaftlichen Folgen der Automatisierung
    (2018) Prettner, Klaus; Geiger, Niels; Schwarzer, Johannes
    Der technologische Wandel der letzten 200 Jahre ermöglichte es den heutigen Industrieländern, ein historisch einzigartiges Wohlstandsniveau zu erreichen. Nichtsdestotrotz haben technologische Veränderungen zu jeder Zeit Befürchtungen dahingehend ausgelöst, dass sie zu hoher Arbeitslosigkeit und zur Verarmung ganzer Bevölkerungsschichten führen könnten. Aus zwei Gründen ist dies bisher nicht geschehen: Erstens lösten die technologischen Entwicklungen ein starkes Wirtschaftswachstum aus, wodurch sich die Nachfrage so stark erhöhte, dass trotz der gestiegenen Arbeitsproduktivität durch technologischen Fortschritt das Arbeitsvolumen in den jeweiligen Tätigkeitsbereichen nicht in gleichem Maße abnahm. Zweitens kam es zu einem tiefgreifenden Strukturwandel, durch den das Schrumpfen des Beschäftigungsanteils mancher Sektoren (zuerst vor allem der Landwirtschaft, später auch der Industrie) mit der Entstehung völlig neuer Tätigkeitsbereiche (vor allem im Bereich der personalintensiven Dienstleistungen) einherging. Durch den starken Anstieg der Anzahl der Arbeitskräfte im Dienstleistungssektor wurde der Wegfall an Arbeit in schrumpfenden Sektoren (über- )kompensiert. Nun stellt die aktuelle Welle der Automatisierung eine Form der technologischen Entwicklung dar, welche definitionsgemäß Arbeit für gewisse Aufgaben nicht nur teilweise, sondern vollständig ersetzt und somit obsolet werden lässt. Eine Erhöhung der Nachfrage nach automatisiert hergestellten Gütern oder Dienstleistungen kann somit zu keinen direkten positiven Beschäftigungseffekten führen. Wenngleich beschäftigungssteigernde indirekte Sekundäreffekte weiterhin wirksam sind, so sind die neuen Tätigkeitsbereiche, welche im Zuge der Automatisierung entstehen, oftmals weniger arbeitsintensiv als es die Dienstleistungen in der Vergangenheit waren. Dadurch fallen auch die indirekten Kompensationsmechanismen der negativen Beschäftigungseffekte der Automatisierung tendenziell schwächer aus. In diesem Beitrag gehen wir der Frage nach, wie sich die Automatisierung auf das Wirtschaftswachstum, die Beschäftigung und die Ungleichheit auswirkt und zeigen mögliche Handlungsperspektiven für die Wirtschaftspolitik auf, um ungewünschten Auswirkungen vorzubeugen und entgegenzuwirken.