Periodic Reporting for period 4 - TechChange (Technological Change: New Sources, Consequences, and Impact Mitigation)
Periodo di rendicontazione: 2023-09-01 al 2024-04-30
This project focusses on technological change at the firm level, how it propagates to workers, and how to deal with possible negative consequences. It has been structured around several major parts.
1. The first part considers how technological change might affect the size of firms. If information and communication technology allow firms to operate on a larger scale, this means that more productive firms can absorb a larger part of the workforce. When workers are heterogeneous, this alters their wage differences. We outline this new idea, and quantify it a calibrated macro model that also accommodates traditional views of technological change such as skill-biased change.
2. The second part considered the mitigation of detrimental effects on the workforce and inference of the effects of future technological change from the past.
- 2.1 In one subpart we investigated if national changes to industry employment can be used to predict regional changes, which is essential to understand and predict regional inequality.
- 2.2 For regions that are negatively affected by technological change we investigate how subsidy spending on different industries can help or hurt such regions. In particular, subsidizing industries that generate quick employment gains might not help long-run growth.
- 2.3 We also investigated the forecastability of future technological change and its consequences for occupational employment. We also added a part to consider whether firms could self-report which worker level they need and whether this could aid in bringing workers of different skills to the right employment, thereby allowing workers to better navigate changing work requirements through better sorting.
3. A final component that was added to this project concerns the implications of Covid-19 and future pandemic diseases, and the role of technology in it. We build a model where individuals can protect themselves but the government can also intervene, to study how much old and young individuals will privately protect themselves and in which way the government should intervene on each of these groups.
1. The first part considers how technological change might affect the size of firms. If information and communication technology allow firms to operate on a larger scale, this means that more productive firms can absorb a larger part of the workforce. When workers are heterogeneous, this alters their wage differences. We outline this new idea, and quantify it a calibrated macro model that also accommodates traditional views of technological change such as skill-biased change.
2. The second part considered the mitigation of detrimental effects on the workforce and inference of the effects of future technological change from the past.
- 2.1 In one subpart we investigated if national changes to industry employment can be used to predict regional changes, which is essential to understand and predict regional inequality.
- 2.2 For regions that are negatively affected by technological change we investigate how subsidy spending on different industries can help or hurt such regions. In particular, subsidizing industries that generate quick employment gains might not help long-run growth.
- 2.3 We also investigated the forecastability of future technological change and its consequences for occupational employment. We also added a part to consider whether firms could self-report which worker level they need and whether this could aid in bringing workers of different skills to the right employment, thereby allowing workers to better navigate changing work requirements through better sorting.
3. A final component that was added to this project concerns the implications of Covid-19 and future pandemic diseases, and the role of technology in it. We build a model where individuals can protect themselves but the government can also intervene, to study how much old and young individuals will privately protect themselves and in which way the government should intervene on each of these groups.
For part 1 we set up an assignment model where firms of different productivity choose both the ability and quantity of their workers in each occupation (blue and white collar). We provide a simple micro-foundation and provide conditions for more productive firms to hire more able workers, which is important to match German employer-employee micro-data. We focus on decade 2005 to 2015 where we can abstract from market power since we show that measured mark-ups are remarkably constant on average and display little dispersion (though we theoretically show how to embed it).
We characterize the equilibrium via a system of differential equations coupled with boundary-value-constraints that represent market-clearing. We considered many computational approaches, as the boundary problems render this difficult. Through iteration on a shooting algorithm we managed to calibrate both time periods. We fit the data quite well, and use the model as a laboratory: Quantity-bias increases the spread of firm sizes, increases average wages, but decreases wage dispersion. The latter is especially pronounced for quantity-bias for white collar workers. We presented this at the final grant conference and in a working paper.
For part 2a we completed a working paper which shows that the distribution of employment matters both for aggregate employment and especially for regional inequality, with aggregation forces amplifying large predicted positive gains.
For part 2b we searched for a setting where the amount of subsidies remains constant but the industries that receive subsidies change. We settled on regulatory changes in France that provide local municipalities with more discretion on subsidies. Using an arguably exogeneous component, we show in matched employer-employee data that this increases subsidies to manufacturing and low-skilled services at the cost of research and development. This has lasting positive employment effects. These are concentrated at the lower end of the skill spectrum, while the very high-skill sector deteriorates. The effects seem quite persistent. We presented this at the final grant conference and in a working paper.
In part 2c) we investigated predictability of occupational change based on industry leaders and followers, with some success presented at the end-of-grant conference. Also, we analyzed how one might be able to bring the right level of experience into jobs that need such experience. We expanded insights from two-sided matching with search frictions to allow firms to post their skill requirements to allow workers to adjust their search to different skill postings. We managed to capture them in a tight theoretical model that explains the large positive findings in novel field-experimental data. This was presented in many seminars, a podcast and in a working paper.
Third, for project 3 we worked on the role of technology (e.g. teleworking) during a pandemic, with Covid-19 as lead example. Since the old protect themselves more, we show that any additional lockdowns should target predominantly the young. This is especially so for ageing, industrialized countries where some teleworking is feasible. Testing is powerful in reducing the need for lockdowns. We provide general insight for other pandemics that are yet to come. We presented this to practitioners, at interdisciplinary conferences, in non-refereed general-interest columns, and the paper has a 2nd-round revision at the Review of Economic Studies.
We characterize the equilibrium via a system of differential equations coupled with boundary-value-constraints that represent market-clearing. We considered many computational approaches, as the boundary problems render this difficult. Through iteration on a shooting algorithm we managed to calibrate both time periods. We fit the data quite well, and use the model as a laboratory: Quantity-bias increases the spread of firm sizes, increases average wages, but decreases wage dispersion. The latter is especially pronounced for quantity-bias for white collar workers. We presented this at the final grant conference and in a working paper.
For part 2a we completed a working paper which shows that the distribution of employment matters both for aggregate employment and especially for regional inequality, with aggregation forces amplifying large predicted positive gains.
For part 2b we searched for a setting where the amount of subsidies remains constant but the industries that receive subsidies change. We settled on regulatory changes in France that provide local municipalities with more discretion on subsidies. Using an arguably exogeneous component, we show in matched employer-employee data that this increases subsidies to manufacturing and low-skilled services at the cost of research and development. This has lasting positive employment effects. These are concentrated at the lower end of the skill spectrum, while the very high-skill sector deteriorates. The effects seem quite persistent. We presented this at the final grant conference and in a working paper.
In part 2c) we investigated predictability of occupational change based on industry leaders and followers, with some success presented at the end-of-grant conference. Also, we analyzed how one might be able to bring the right level of experience into jobs that need such experience. We expanded insights from two-sided matching with search frictions to allow firms to post their skill requirements to allow workers to adjust their search to different skill postings. We managed to capture them in a tight theoretical model that explains the large positive findings in novel field-experimental data. This was presented in many seminars, a podcast and in a working paper.
Third, for project 3 we worked on the role of technology (e.g. teleworking) during a pandemic, with Covid-19 as lead example. Since the old protect themselves more, we show that any additional lockdowns should target predominantly the young. This is especially so for ageing, industrialized countries where some teleworking is feasible. Testing is powerful in reducing the need for lockdowns. We provide general insight for other pandemics that are yet to come. We presented this to practitioners, at interdisciplinary conferences, in non-refereed general-interest columns, and the paper has a 2nd-round revision at the Review of Economic Studies.
For project 3, choice about social distancing exceeds standard epidemiological models, and externalities between generations exceeds work on this in economics. It provides a general framework (including teleworking, testing and incomplete information…) and we manage to provide insights regarding how heterogeneity of the population matters not only for the unregulated economy, but also for optimal policy, for Covid-19 and beyond.
For project 1 we introducing a novel form of technological change (“quantity-biased change”: firms being able to grow larger) while nesting older ones (skill-biased change), and the feedback on workers. We extend sorting conditions to the new framework, overcame computational difficulties of having three-sided heterogeneity and size of firms, and managed to fit the data quite well and to use it as a laboratory to understand sources of change.
For project 2a the main novelty is to assess more carefully the breakdown of shocks to the regional level, to show new insights on how inequalities between regions are amplified by local effects and dispersion is relevant for the aggregate level of economic activity.
For project 2b we show that how subsidies are allocated matters. More local discretion (at same subsidy level) favors manufacturing at the costs of other R&D, increases employment, favors the low-skill sector, and had long-term impact. Previous work considered mainly the level of subsidies, or considered short durations.
For project 2c we could empirically and theoretically show that clearly structured cheap-talk communication of firms can substantially reduce the mismatch in the labor market between job demands and worker experience. This had neither been studied in field-experiments nor in theory before, but has the potential to help workers deal with the changing nature of jobs.
For project 1 we introducing a novel form of technological change (“quantity-biased change”: firms being able to grow larger) while nesting older ones (skill-biased change), and the feedback on workers. We extend sorting conditions to the new framework, overcame computational difficulties of having three-sided heterogeneity and size of firms, and managed to fit the data quite well and to use it as a laboratory to understand sources of change.
For project 2a the main novelty is to assess more carefully the breakdown of shocks to the regional level, to show new insights on how inequalities between regions are amplified by local effects and dispersion is relevant for the aggregate level of economic activity.
For project 2b we show that how subsidies are allocated matters. More local discretion (at same subsidy level) favors manufacturing at the costs of other R&D, increases employment, favors the low-skill sector, and had long-term impact. Previous work considered mainly the level of subsidies, or considered short durations.
For project 2c we could empirically and theoretically show that clearly structured cheap-talk communication of firms can substantially reduce the mismatch in the labor market between job demands and worker experience. This had neither been studied in field-experiments nor in theory before, but has the potential to help workers deal with the changing nature of jobs.