Project

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Post-Pandemic Economic Outlook: Automation, Reshoring, Education, and Growth

English title Post-Pandemic Economic Outlook: Automation, Reshoring, Education, and Growth
Applicant Cozzi Guido
Number 200914
Funding scheme Project funding (Div. I-III)
Research institution School of Economics and Political Science University of St. Gallen
Institution of higher education University of St.Gallen - SG
Main discipline Economics
Start/End 01.04.2021 - 31.03.2025
Approved amount 223'050.00
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Keywords (7)

automation; endogenous growth; education; offshoring; unemployment; reshoring; business cycles

Lay Summary (Italian)

Lead
Major economic crises are rare events and often differ in terms of nature, context, size, duration, consequences, and speed of recovery. For this reason, it is hard to gauge the prospects of the world economy following a particular large crisis such as the current Covid-19 pandemic. Against this background, our project has the ambitious aim to investigate the post-pandemic economic outlook, with special emphasis on automation, reshoring, education, and growth. The results of our project will offer a comprehensive view of the potential consequences of the acceleration of automation due to the Covid-19 pandemic and chosen strategies of future-proofing supply chains on national and world economies. They will also equip policy makers with tools that may help them find solutions that spur economic recovery and foster long-term growth.
Lay summary

Obiettivi

L'obiettivo principale del progetto è quello di affrontare le questioni relative al modo in cui le strategie di approvvigionamento future, in seguito alla pandemia del Covid-19, avranno un impatto sulle economie nazionali e mondiali. In particolare, attraverso questo progetto vorremmo: 

  1.  Fornire un quadro per studiare le interdipendenze tra le fluttuazioni economiche, le decisioni di reshoring e l’ automazione. 
  2.  Discutere il ruolo dei governi nel dotare le persone delle giuste competenze per soddisfare le richieste di lavoro nell'era dell'automazione.
  3.   Costruire un quadro per indagare quanto ampi possano essere gli effetti negativi di una diminuzione dell’offshoring per il paese di destinazione e se gli interventi politici attraverso l'istruzione, la R&S e i sussidi di automazione, possano ridurre almeno l'impatto a lungo termine. 
  4.  Proporre un nuovo set di strumenti che può servire ad analizzare come varie politiche aziendali o governative possono influenzare le decisioni di approvvigionamento e quindi la crescita economica in Svizzera. 

Contesto socio-scientifico

Il reshoring è stato un tema in evoluzione negli ultimi anni perché i progressi nell'automazione rendono possibile ai robot di sostituire alcuni dei lavori che sono stati precedentemente delocalizzati in paesi con manodopera a basso costo. L'argomento ha guadagnato slancio recentemente a causa delle interruzioni della catena di approvvigionamento globale innescate dalla pandemia del Covid-19. Tuttavia, ci sono poche ricerche che discutono le implicazioni del reshoring. Il nostro progetto colmerà la lacuna nella letteratura e, in ultima analisi, fornirà un set di strumenti di modellazione politica per investigare come quest’ultima possa influenzare le decisioni di approvvigionamento.

Direct link to Lay Summary Last update: 31.03.2021

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Abstract

The common theme of this project is the post-pandemic economic outlook, with special emphasis on automation, reshoring, education, and growth. Its main objective is to provide frameworks that combine cutting edge theories and methodologies stemming from various strands of macroeconomics to address questions related to how the strategies of future-proofing supply chains following the Covid-19 pandemic impact national and world economies.Reshoring, the relocation of offshore production back to the home economy, has been an evolving theme over the past couple of years. The reason is that the advances in automation make it possible for robots to replace some of the jobs that were previously offshored to lower labor-cost countries. The topic gained momentum recently due to the increased trade frictions between the United States (US) and China and the global supply chain disruptions triggered by the Covid-19 pandemic. However, there is little and mostly empirical research discussing the implications of reshoring for the source country, only some of these analyses being also motivated theoretically by deterministic models of production. In contrast to this literature, we will set up a dynamic stochastic general equilibrium (DSGE) model with endogenized growth that incorporates reshoring decisions, automation and technology adoption activities, unemployment, and public institutions. We will use this framework to analyze the impact of various policies taken in different countries in response to the Covid-19 pandemic. Further, we aim to make a horse race of automation, adoption, employee retention, and reshoring subsidies to investigate which has the best implications for employment and growth.Given its aim, this model allows for skill heterogeneity but assumes that the levels for the different skill groups of workers are exogenously provided. However, the occurrence of unemployment with technological change has been shown to depend on the extent to which workers can educate themselves (e.g. Mortensen and Pissarides, 1994; Carré and Drouot, 2004; Moreno-Galbis, 2012). For this reason, in a second paper, we relax this exogeneity assumption and allow for human capital accumulation. The purpose is to investigate the role of governments in equipping people with the right skills to meet the labor requirements in the age of automation. We will thus construct a model that facilitates the analysis of whether education and skill-upgrading subsidies can mitigate the negative consequences of automation and reshoring on low-skilled labor employment.In a third paper, we will switch focus to the offshore destination countries, for which the offshoring of business processes from developed countries has been a boon. The reason is that it brought significant economic benefits stemming from increased job creation and consequently from enlarged demand for goods and services. However, empirical research indicates that the acceleration of automation in developed countries leads to a decrease in offshoring and has a negative impact on employment in countries that are offshoring destination. We thus propose a framework to investigate how large the negative effects of a decrease in offshoring can be for the destination country and whether policy interventions through education, R&D, and automation subsidies in an offshoring destination country might reduce at least the long-term impact.Lastly, we will combine and extend the above-mentioned models to provide a workable modeling toolkit to analyze how the various business or government policies can influence offshoring, backshoring or nearshoring decisions and ultimately economic growth in Switzerland. In the past years, Swiss companies have mainly offshored, with some of them afterwards nearshoring their activities from Asia to Europe and only a few of them backshoring to Switzerland. The vulnerabilities of the global value chain exposed by the Covid-19 disruptions might encourage Swiss firms to reduce their offshoring and even choose to backshore. For this reason, it is important to investigate how several policy actions to improve technology absorption and top talent availability could influence these decisions and what will be their implications for the Swiss economy. Inspired by the success of the MONROE Toolkit (2019), to whose realization I also contributed, the policy modeling toolkit for Switzerland, while undoubtedly containing more complex models than those included in MONROE, will have a user-friendly interface which will make it accessible even to users without advanced modeling skills.
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