Suchergebnisse

In recent decades right-wing populist parties have experienced increased electoral success in many western democracies. This rise of the far-right, which is strongly built on the support of the working class, coincides with a sharp decline of the manufacturing sector. This paper analyzes the contribution of this manufacturing decline to the rise of the Austrian far-right. Overall the decline in manufacturing employment has strongly contributed to this rightward shift in the political landscape, with the manufacturing decline explaining roughly 43% of the observed increase in far-right vote-shares between 1995 and 2017. This effect is entirely driven by increases in natives unemployment rates, which increased considerably due to the manufacturing decline. Regarding the influences of the forces underlying the manufacturing decline, namely international trade and automation technologies, suggests that both forces contributed in roughly equal parts to this development.

Internal migration flows from rural to urban areas have greatly contributed to population declines in many rural areas across both Europe and the US. At the same time there is mounting evidence for a tight connection between internal migration and shifts in labor demand, with the latter being heavily affected by the rise of automation technologies. Therefore this paper analyzes the effects industrial robotization has had on manufacturing employment and internal migration in Austria during the period 2003-2016, specifically focusing on rural-to-urban migration flows. The results show that robotization has caused significant declines in manufacturing employment to which populations reacted by increased out-migration. This migratory response takes the form of rural-to-urban migration, thereby contributing to population declines in many rural areas in Austria. These rural-to-urban movements are primarily driven by young and medium/low skilled individuals, i.e. those groups that bear the strongest shock incidence.

In a seminal paper Graetz and Michaels (2018) find that robots increase labor productivity and TFP, lower output prices and adversely affect the employment share of low-skilled labor. We show that these effects hold only, when comparing hardly-robotizing with highly-robotizing sectors and collapse, when only the latter are analyzed. Controlling for demographic workforce variables reestablishes the productivity effects, but still rejects positive wage effects and skill-biased technological change. Additionally, we find no effects, when the investigation period is extended to the most recent data (2008-2015) and document non-monotonicity in one of the instruments, which calls the respective results into question.

Monitoring progress towards the fulfillment of the Sustainable Development Goals (SDGs) requires the assessment of potential future trends in poverty. This paper presents an econometric tool that provides a methodological framework to carry out projections of poverty rates worldwide and aims at assessing absolute poverty changes at the global level under different scenarios. The model combines country-specific historical estimates of the distribution of income, using Beta–Lorenz curves, with projections of population changes by age and education attainment level, as well as GDP projections to provide the first set of internally consistent poverty projections for all countries of the world. Making use of demographic and economic projections developed in the context of the Intergovernmental Panel on Climate Change's Shared Socioeconomic Pathways, we create poverty paths by country up to the year 2030. The differences implied by different global scenarios span worldwide poverty rates ranging from 4.5% (around 375 million persons) to almost 6% (over 500 million persons) by the end of our projection period. The largest differences in poverty headcount and poverty rates across scenarios appear for Sub-Saharan Africa, where the projections for the most optimistic scenario imply over 300 million individuals living in extreme poverty in 2030. The results of the comparison of poverty scenarios point towards the difficulty of fulfilling the first goal of the SDGs unless further development policy efforts are enacted.

Monitoring progress towards the fulfillment of the Sustainable Development Goals (SDGs) requires the assessment of potential future trends in poverty. This paper presents an econometric tool that provides a methodological framework to carry out projections of poverty rates worldwide and aims at assessing absolute poverty changes at the global level under different scenarios. The model combines country-specific historical estimates of the distribution of income, using Beta-Lorenz curves, with projections of population changes by age and education attainment level, as well as GDP projections to provide the first set of internally consistent poverty projections for all countries of the world. Making use of demographic and economic projections developed in the context of the Intergovernmental Panel on Climate Change's Shared Socioeconomic Pathways, we create poverty paths by country up to the year 2030. The differences implied by different global scenarios span worldwide poverty rates ranging from 4.5% (around 375 million persons) to almost 6% (over 500 million persons) by the end of our projection period. The largest differences in poverty headcount and poverty rates across scenarios appear for Sub-Saharan Africa, where the projections for the most optimistic scenario imply over 300 million individuals living in extreme poverty in 2030. The results of the comparison of poverty scenarios point towards the difficulty of fulfilling the first goal of the SDGs unless further development policy efforts are enacted.

Monitoring progress towards the fulfillment of the Sustainable Development Goals (SDGs) requires the assessment of potential future trends in poverty. This paper presents an econometric tool that provides a methodological framework to carry out projections of poverty rates worldwide and aims at assessing absolute poverty changes at the global level under different scenarios. The model combines country-specific historical estimates of the distribution of income, using Beta–Lorenz curves, with projections of population changes by age and education attainment level, as well as GDP projections to provide the first set of internally consistent poverty projections for all countries of the world. Making use of demographic and economic projections developed in the context of the Intergovernmental Panel on Climate Change's Shared Socioeconomic Pathways, we create poverty paths by country up to the year 2030. The differences implied by different global scenarios span worldwide poverty rates ranging from 4.5% (around 375 million persons) to almost 6% (over 500 million persons) by the end of our projection period. The largest differences in poverty headcount and poverty rates across scenarios appear for Sub-Saharan Africa, where the projections for the most optimistic scenario imply over 300 million individuals living in extreme poverty in 2030. The results of the comparison of poverty scenarios point towards the difficulty of fulfilling the first goal of the SDGs unless further development policy efforts are enacted.

Monitoring progress towards the fulfillment of the Sustainable Development Goals (SDGs) requires the assessment of potential future trends in poverty. This paper presents an econometric tool that provides a methodological framework to carry out projections of poverty rates worldwide and aims at assessing absolute poverty changes at the global level under different scenarios. The model combines country-specific historical estimates of the distribution of income, using Beta–Lorenz curves, with projections of population changes by age and education attainment level, as well as GDP projections to provide the first set of internally consistent poverty projections for all countries of the world. Making use of demographic and economic projections developed in the context of the Intergovernmental Panel on Climate Change's Shared Socioeconomic Pathways, we create poverty paths by country up to the year 2030. The differences implied by different global scenarios span worldwide poverty rates ranging from 4.5% (around 375 million persons) to almost 6% (over 500 million persons) by the end of our projection period. The largest differences in poverty headcount and poverty rates across scenarios appear for Sub-Saharan Africa, where the projections for the most optimistic scenario imply over 300 million individuals living in extreme poverty in 2030. The results of the comparison of poverty scenarios point towards the difficulty of fulfilling the first goal of the SDGs unless further development policy efforts are enacted.