Abstract In this thesis, an attempt is made to evaluate the effects on growth of the National Plan Industria 4.0, the government set of policy measures articulated in two main policy frames known as Skill Achievements and Innovative Investments. The quantitative evaluation is performed through the simulation of policy scenarios within a modified version of the model QUEST III-Italy. Model changes have been implemented for enabling a more satisfactory treatment of the “Skill Biased Technical Change” (SBTC) and “Process Innovation”. The first aim is reached through the endogenization of the skill-shares of employed workers. In the relationship introduced the production of new ideas influences the share of superstar workers and the share of non-routinized skilled workers according a logistic relationship; while routinized skilled workers are allocated in a residual category that reduces as new technologies increase. This mechanism allows for the consideration of the substitutability between routinized skilled workers and technologies. The second aim has been reached modeling the spillover of the physical capital productivity. The share of new ideas not covered by patents is not included in the acquisition cost of physical capital, but provides, through spillovers, a total physical capital productivity higher than the acquisition cost of physical capital itself. This productivity affects investment in the physical capital accumulation equation, making the value of physical capital higher than its acquisition cost. The main results put in evidence a positive trend for the Italian economy so to move Italy out of the zero growth threat. The endogenous growth process entirely explicates its effect only in the long run when human capital has completed the education process and is really effective in R&D sector and when all the effects of government measures have been put in operation. From the employment point of view economic growth is reduced mainly by the lack of infrastructures to support the workers education process forecasted by the plan. New technologies can find their way both through the skills and through the infrastructures, with the result that this empowerment of skills leads to an increase in high skilled workers only in the very long run. In the short run new technologies will bring a limited set of other low skilled jobs, complementary to them, which induce to an increase in low skilled employment, which decreases when these skills will be digitalized.
Nella tesi si vogliono quantificare gli effetti dei provvedimenti governativi che vanno sotto il nome di “Piano Nazionale Industria 4.0:Acquisizione di Competenze e Investimenti Innovativi” sulla crescita economica attraverso la simulazione degli scenari di politica sul modello QUEST III-Italia modificato con la introduzione di equazioni che consentano di trattare il fenomeno dello “Skilled Biased Technical Change” (SBTC) e “innovazione di processo.” Il primo obiettivo viene raggiunto endogenizzando le quote di lavoratori occupati. La relazione ipotizzata è tale per cui la quota dei superstar workers e la quota dei non routinized skilled workers dipenda con una relazione logistica, e quindi crescente, dalle nuove idee. Al contrario, i routinized skilled workers costituiranno la categoria residuale e che quindi diminuisce all’aumentare delle nuove tecnologie. Questa categoria residuale è stata introdotta al fine di modellare la sostituibilità tra routinized skilled workers e tecnologie. Il secondo obiettivo viene raggiunto modellizzando la produttività del capitale fisico legata agli spillover delle nuove idee. La quota di nuove idee non coperta da brevetto, porta, attraverso gli spillover, ad una produttività totale del capitale fisico, maggiore del costo di acquisto del capitale fisico stesso. Tale produttività, influenza gli investimenti nell’equazione di accumulazione del capitale fisico, facendo sì che il valore del capitale fisico sia maggiore del suo costo d’acquisto. I principali risultati tratteggiano un contesto economico italiano di crescita seppur non sostenuta, e tale da allontanare l’Italia dal rischio di crescita zero. Il processo di crescita endogena esplica interamente il suo effetto solo nel lungo periodo, quando il capitale umano ha completato l’intero processo di formazione ed è effettivamente allocato nel settore di R&D e quando tutti gli effetti delle riforme governative hanno trovato attuazione. Dal lato dell’occupazione la crescita economica è frenata principalmente dalla mancanza di infrastrutture tali da sostenere il processo di formazione dei lavoratori previsto dal piano. Le nuove tecnologie non trovano terreno fertile dal lato delle competenze, e dal lato delle infrastrutture, con il risultato che questo potenziamento delle competenze porta solo nel lunghissimo periodo ad un aumento dell’occupazione altamente qualificata. Nel breve periodo le nuove tecnologie portano un insieme limitato di lavori low skilled complementari ad esse, che induce un aumento dell’occupazione low skilled, che decrementa a sua volta man mano che queste mansioni vengono automatizzate.
Skill biased technological change and process innovation in QUEST III with R&D: Policy Simulations for "Industria 4.0" / Ciaschini, Clio. - (2018 Mar 22).
Skill biased technological change and process innovation in QUEST III with R&D: Policy Simulations for "Industria 4.0"
CIASCHINI, CLIO
2018-03-22
Abstract
Abstract In this thesis, an attempt is made to evaluate the effects on growth of the National Plan Industria 4.0, the government set of policy measures articulated in two main policy frames known as Skill Achievements and Innovative Investments. The quantitative evaluation is performed through the simulation of policy scenarios within a modified version of the model QUEST III-Italy. Model changes have been implemented for enabling a more satisfactory treatment of the “Skill Biased Technical Change” (SBTC) and “Process Innovation”. The first aim is reached through the endogenization of the skill-shares of employed workers. In the relationship introduced the production of new ideas influences the share of superstar workers and the share of non-routinized skilled workers according a logistic relationship; while routinized skilled workers are allocated in a residual category that reduces as new technologies increase. This mechanism allows for the consideration of the substitutability between routinized skilled workers and technologies. The second aim has been reached modeling the spillover of the physical capital productivity. The share of new ideas not covered by patents is not included in the acquisition cost of physical capital, but provides, through spillovers, a total physical capital productivity higher than the acquisition cost of physical capital itself. This productivity affects investment in the physical capital accumulation equation, making the value of physical capital higher than its acquisition cost. The main results put in evidence a positive trend for the Italian economy so to move Italy out of the zero growth threat. The endogenous growth process entirely explicates its effect only in the long run when human capital has completed the education process and is really effective in R&D sector and when all the effects of government measures have been put in operation. From the employment point of view economic growth is reduced mainly by the lack of infrastructures to support the workers education process forecasted by the plan. New technologies can find their way both through the skills and through the infrastructures, with the result that this empowerment of skills leads to an increase in high skilled workers only in the very long run. In the short run new technologies will bring a limited set of other low skilled jobs, complementary to them, which induce to an increase in low skilled employment, which decreases when these skills will be digitalized.File | Dimensione | Formato | |
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