The PNRR and productivity: the cases of the chemical and mechatronics industries

The study evaluates the extent to which public funds for research, innovation, and technological transformation can contribute to the competitiveness of Italian high-tech supply chains. The investigation, which examines 74 chemistry and mechatronics projects funded by the PNRR, shows how results depend on how investments are tailored to the specificities of the supply chains and the degree to which these are investments that the private sector would not have made, or would have made to a lesser extent.

Study objectives  

The objective of the study is to analyze how different supply chains respond to incentives in different ways. Conducting ex-ante studies of policies to be implemented is useful for following the European Union's "better regulation" framework and setting them according to the specificities of the supply chains. Italy is, in fact, one of the few OECD economies where sustained increases in research and development (R&D) and education levels have not translated into growth in Total Factor Productivity, in English Total Factor Productivity (TFP), which measures how well a company or supply chain manages to produce by using labor, capital, and technology—over long horizons, as emerged from a 2018 Bank of Italy study.  

Methodology and construction of estimates

OpenEconomics analyzed 74 PNRR projects related to the chemistry and mechatronics supply chains: 7 projects with 173.4 million euros in PNRR funding in chemistry and 67 projects with 740.3 million in mechatronics.

The analysis of the two supply chains reveals two different channels for productivity transmission. In chemistry, there is a relatively direct link between research and development, process innovation, and productivity. In mechatronics, however, research spending alone is not enough: what matters most is its integration with software, automation, data, machinery, and skills. The comparison therefore shows that different public support measures must be consistent with the way each supply chain produces and adopts innovation.

These are ex-ante estimates: the PNRR cannot yet be evaluated ex-post with a sufficient time series. The study applies the historical econometric results of each supply chain to the projects, assuming that only a portion of the spending is additional—that is, capable of generating investments that otherwise would not have occurred, would have been smaller, or would have been postponed.  

Main results

In the central scenario, the study estimates a possible increase in total factor productivity of +1.77% in chemistry and +0.28% in mechatronics. TFP measures the ability to generate more value by better combining labor, capital, skills, and technology. These values should not be read as a ranking, nor as observed causal effects or fiscal multipliers. They are prospective and conditional estimates: they describe what could happen if the funds activate the correct production channel.

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Chemistry: research enters the processes

For chemistry, the study identifies a crelatively direct channel between research and development and productivity. Resources primarily fund activities comparable to industrial R&D, and since 2010, private research has been positively and significantly associated with TFP. The transition to production is clear: new knowledge can translate into better materials, facilities, and processes, with effects on quality and efficiency.

The estimated +1.77% should be read within this framework: it indicates a potential consistent with the observed channel, not a guaranteed return for every funded project. For the company, the consequence is operational: a solid proposal must link research and industrial transformation, from experimentation to pilot plants, all the way to scaling and certification. It must clarify which technological risk it reduces, which additional investment it enables, and which productive result will be verifiable.

Public selection must follow the same chain. A project gains value when support expands its scope, accelerates its implementation, or addresses a new risk. If it replaces already planned resources, additionality is lost.

Mechatronics: value is created through integration

In mechatronics, the picture changes. The aggregate volume of R&D, considered in isolation, does not robustly explain productivity trends. The supply chain combines mechanics, electronics, software, automation, data, sensors, machinery, and technical skills: value is created by their integration into processes.

The conditional estimate of +0.28% reflects this complexity. It does not indicate less useful funding; it signals that research produces results when it meets digital capital, machinery, skills, and technology transfer. The project must explain how software, data, and machinery will interact, which skills will enable their use, and how the process will change, clarifying whether the benefits will reach suppliers and partners.

For managers and applicants, project quality comes before capital

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For those designing funds, the point is not to distribute more resources, but to select interventions capable of transforming them into productive capacity. Interoperability, automation, data usage, complementary investments, and execution capability matter more than financial size alone. Criteria must therefore verify whether the project triggers additional investments, whether the company has the conditions to implement it, and whether results can be measured beyond the reported expenditure.

For applicants, funding cannot be the end goal of the project. A credible proposal shows what change it produces in processes, which technologies it integrates, which skills it requires, and which private or organizational investments it mobilizes. In chemistry, this means linking research to materials, facilities, and processes; in mechatronics, it means demonstrating the integration of software, automation, data, machinery, and people.  

The consequence is common: design quality comes before capital. Public funds are effective when they make a transformation achievable that a company, on its own, would not have initiated with the same timeline, scale, or technological content. It is on this consistency between the instrument, the project, and the supply chain that design, selection, and evaluation must focus.