Industrial and innovation policy
Photo by @Victor_g on Unsplash
Team Leaders: Anna Valero and Richard Davies
In recent years, many governments have begun to pursue more activist industrial policies. Most recently, these have been linked to a "green" recovery from the pandemic.
POID researchers documented the strongest evidence for a potentially positive impact of UK industrial policy in: "Some causal effects of an industrial policy". And we have been heavily involved in the policy debate surrounding UK industrial and innovation policy.
In the 2017 LSE Growth Commission report, and a series of articles since, we have highlighted how the longevity of frameworks and strength of institutions governing industrial policy fall short compared with other areas of UK economic policy.
The case for industrial policies that are protected from political cycles is even stronger in the context of the recovery from the COVID-19 crisis, the legal commitment to meeting net-zero greenhouse gas emissions by 2050, and the need to "level up" economic performance and opportunity in the UK.
In a series of recent papers we highlight policies for a strong, sustainable and inclusive recovery, highlighting the importance of a well-designed, long-term and coordinated industrial strategy as a key component for stimulating the investment and innovation required to achieve this.
- Strategy, investment and policy for a strong and sustainable recovery: an action plan
- Jobs for a strong and sustainable recovery from Covid-19
- Innovation for a strong and sustainable recovery from Covid-19
We set out the evidence on policies to promote innovation in a recent paper, providing a "toolkit" for policymakers.
What is needed is to link across the various levers to have a coherent industrial policy for the 21st century. This requires thinking about incentives through tax, regulation, trade (e.g. supply chain), competition policy and those created by government investments in infrastructure and innovation. The work of POID researchers has influenced the creation of the new National Infrastructure Bank and we will work with this to look at how to maximize crowd-in effects of government involvement.
Central to policy evaluation is whether it requires public intervention. The presence of spillovers will often mean that the private sector will not deliver what social efficiency demands.
Undertaken work
Spillovers (Ralf Martin, John Van Reenen)
Some of the practical questions we will address, for example, are the criteria that BEIS and other agencies should use in allocating Innovation Grants. At the moment, spillovers are not given the central position that they should have.
How can we change this to give more focus on the social returns? We have done much work on measuring these spillovers and developing innovation policy. For example: "Have R&D spillovers declined in the 21st century?"
A critical thing for tax policy (such as R&D tax credits) is whether or not these create spillovers.
"Do Fiscal Incentives increase innovation? An RD Design for R&D"
Declining Dynamism? (Richard Davies)
Has dynamism stalled in the UK, as it seems to have done in the US? In the US, the fraction of employees working in young firms has fallen since the 1980s, the entrepreneurship rate is down, there is less job creation and destruction and firms are slower to respond to shocks. Is this true in the UK, and if so, why?
Supply Chains (Amiti, Atkin, Khandelwal, Konings, Haldane)
One important mechanism for spillovers is along the supply chain. The positive effect of multinationals is often thought to be because primes work to improve the quality of their tier 1 suppliers through better management and technologies.
Using B2B firm panel data we will investigate the importance of "superstar" firms as purchases of services. Does forming a new relationship with a major new business improve an SME's productivity, for example?
We will also develop a Supply Chain Management survey tool to mirror the WMS. Working with the Bank of England, consultants like McKinsey, EY and Deloitte we will use qualitative surveys to help develop quantitative data. We are interested in the variation of practices, what drives the changes and ultimately how these supply chains affect micro and macro-economic performance.
We will use these data to investigate how supply chains have been disrupted by the major recent events: Trump's trade wars, COVID-19 and Brexit. How resilient are supply chains to these events? Alternatively, are we experiencing an era of de-globalization?
Human Capital (Anna Valero, John Van Reenen)
Another important theme is the role of Higher and Further Education in economic development.
"The Economic Impact of Universities: Evidence from Across the Globe" (with Anna Valero), Economics of Education Review (2019), 68 53-67. Read also the Vox article.
A paper in the CEP's industrial strategy series set out the importance of universities in the UK's industrial strategy. And more recent work highlights the importance of work-related training for building future skills:
We will investigate how human capital built in the education system and via work-related training affects innovation and diffusion.
Innovation and National Security (Howell, Moretti, Steinwender)
Industrial policy is often linked with strategic defense issues. This is because technological innovation has been linked to military activity since ancient times. More recently, many of the major innovations in the last 100 years have been linked to investment by the (mainly US) military such as Jet Engines, radar, GPS and the Internet.
However, mostly this enthusiasm is based on anecdotes rather than econometrics. We have been working on two sets of projects to assess the importance of defense innovation. First, we are looking at cross industry data since 1980 in all OECD countries, to see to what extent public defense R&D has positive economic pay-offs. Secondly, we are evaluating a specific new way the US Airforce is procuring innovation through its SBIR program. This is focusing on a bottom up, decentralized approach, rather than the traditional top-down approach. With access to administrative data over the last two decades, we can look at Regression Discontinuity Designs to assess the causal effect of these changing competitions.
The role of China looms large in discussions over military technology. Noam Yuchtman is leading a project (with Martin Beraja and David Y. Yang) on Data-intensive Innovation and the State: Evidence from AI Firms in China". Artificial intelligence (AI) innovation is data-intensive. States have historically collected large amounts of data, which is now being used by AI firms. Gathering comprehensive information on firms and government procurement contracts in China’s facial recognition AI industry, we first study how government data shapes AI innovation. We find evidence of a precise mechanism: because data is sharable across uses, economies of scope arise. Firms awarded public security AI contracts providing access to more government data produce more software for both government and commercial purposes. In a directed technical change model incorporating this mechanism, we then study the trade-offs presented by states' AI procurement and data provision policies. Surveillance states' demand for AI may incidentally promote growth, but distort innovation, crowd-out resources, and infringe on civil liberties. Government data provision may be justified when economies of scope are strong and citizens' privacy concerns are limited
Example papers:
"The Intellectual Spoils of War: Defense R&D, Productivity and Spillovers" (Van Reenen, Moretti and Steinwender).
Opening up Military Innovation: An Evaluation of Reforms to the U.S. Air Force SBIR Program" (Van Reenen, Howell, Rathje and Wong).
Diffusion Policies (Anna Valero)
The spillover argument is less clear for diffusion than innovation. Are the benefits from adopting a new technology (or managerial practice) not fully internalized by a firm? If so, why should there be government intervention?
There are many possible answers. One set is around financial frictions which may be felt in particular by SMEs. Another is behavioral biases. A third is that there are informational frictions, so that a firm may not know the full set of benefits from adopting, as these are highly uncertain. After all, we do not know what we do not know.
A way of investigating these issues is through running experiments. We have been engaged in a randomized control trial with the GLA which was focused on the adoption of tried and tested AI technologies by SMEs in London's retail and hospitality sectors. Ongoing work will investigate the barriers to adoption of productivity-enhancing technologies, and the types of intervention that are likely to address these.