Events

Business dynamism, i.e., the process of new efficient firms entering the market, grow and force less efficient competitors to contract and exit, is believed to be key both for productivity and employment growth. A particular role in that take young high growth firms with the potential to fundamentally disrupt the economy. Business dynamism and firm high growth, however, are in decline in many advanced countries, most prominently shown for the US, which has important long term effects on the transformation process of the economy. Based on firm-level data, originating from Germany’s largest credit rating agency (Creditreform), covering the period 2002–2019, we show some new insights in firm high growth dynamics. By that, we look at secular trends, heterogeneity in terms of firm size and age as well as sectoral differences.

Taken this as background information, the presentation will proceed by introducing a larger research project that we are currently setting up jointly with IWH (Halle Institute for Economic Research). Here, a unique new data infrastructure, linking the above treated firm-level data with establishment and employee data from IAB will be developed and exploited. This new data infrastructure will allow to respond to several crucial questions in the literature of entrepreneurship, business dynamism, and firm high-growth. More precisely, the research agenda comprises the analysis of who creates jobs in Germany (small vs. big vs. young), as well as the investigation of the conditions (rural arears vs. economic centres, IT infrastructure, closeness to scientific institutions) spurring firm high growth and regional development. Furthermore, we ask the question of the role of entrepreneur characteristics to high growth firm outcomes, such as age, experience, education and migrant status, and the role of inventors and workers. Lastly, the project also comprises the analysis of the effect of M&A activity on firm growth and the innovativeness of the economy.

Contact person: Albert Roger

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Sophie Quach's work strives to advance our understanding of how users and firms can both benefit from their complementary objectives, roles and resources in joint innovation processes. For firms, adopting, perfecting, producing, and eventually broadly diffusing commercially viable freely revealed user innovations among customers is clearly a great business opportunity. As user innovations originate from different incentives and in different environments than producer innovations, user innovations “generally pioneer functionally new applications and markets prior to producers understanding the opportunity” (von Hippel, 2017). Firms’ commercialization of user innovations is also beneficial from a societal perspective, as it reduces what has been termed the “diffusion shortfall” of user innovations (de Jong et al., 2015, 2018). Many valuable user innovations remain underused because users lack both incentives and resources to produce and popularize them. 

Contact person: Svenja Friess

Social and environmental innovation are important for economic and societal development and to reach the Sustainable Development Goals of the United Nations. However, to date, we lack objective, validated, and non-survey based indicators to measure these two important forms of innovation. To what extent can patent and trademark data be used to construct such measures? Using data from several independent samples, we correlate different survey-based measures of social and environmental innovation with patent and trademark-based measures. Our results show that trademark-based measures can be used to identify social and environmental innovation. The results regarding patent data are mixed.

Contact person: David Heller

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We analyze how the adoption of the California Consumer Privacy Act (CCPA), which limits the acquisition, processing, and trade of consumer personal data, heterogeneously affects firms with and without previously gathered customer data. Exploiting a novel and hand-collected data set of 11,436 conversational-AI firms with rich personal information on U.S. consumers, we find that the CCPA gives a strong protection and advantage to firms with previously accumulated (in-house) data. First, products of these firms generate more customer feedback and exhibit higher product ratings after the adoption of the CCPA. Second, publicly traded firms with in-house data exhibit higher valuations, profitability, asset utilization, and they invest more after the adoption of the CCPA. Third, earnings of such firms can be more accurately predicted by analysts. To rationalize these empirical findings, we build a general equilibrium model where firms produce intermediate goods using labor and data in the form of intangible capital. Data can be traded with other firms subject to a cost representing regulatory and technical challenges. Firms differ in their ability to collect data internally, driven by their business models and/or the size of their customer base, and reliance on data. When the introduction of the CCPA increases the cost of trading data, firms with a low ability to collect in-house data and high reliance on data suffer the most as they cannot adequately substitute the previously externally purchased data.

Contact person: Svenja Friess

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Many established firms have substantially reduced their engagement in upstream scientific research since the 1980s. We examine how two components of public science – scientific knowledge and human capital – affect corporate investment in research and innovation. Empirically, we link firms with public science that is relevant to their innovation and trace funding sources. Identification is based on firm-specific exposure to (i) changes in federal agency R&D budgets and (ii) windfall funding from congressional appropriations. We find that public knowledge crowds out internal research, except for firms at the technology frontier (“frontier firms”), which continue to invest in internal research even when public knowledge relevant to their innovation is abundant. Second, human capital increases internal research and innovation, especially in frontier firms. We conclude that while the rise in public science can partly explain the decline in corporate science, the effect has been uneven across firms, affecting non-frontier firms more than frontier firms, and potentially amplifying the gap between them.

Contact person: Michael Rose 

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The Role of an Open Source Software Compliance Certification in the Software Supply Chain – Insights from a Conjoint Experiment

Presenter: Juliane Wissel (TUM)

Discussant: Ambre Nicolle (ISTO)

First-Party Complements in Platform Markets: The Role of Competition

Presenter: Alexey Rusakov (ISTO)

Discussant: Adrian Göttfried (TUM)

On 19/20 December 2022, the Max Planck Institute for Innovation and Competition will host the 5^th Research on Innovation, Science and Entrepreneurship Workshop, an annual workshop for Ph.D. students and Junior Post-docs in Economics and Management. 

The goal of the RISE5 Workshop is to stimulate an in-depth discussion of a select number of empirical research papers. It offers Ph.D. students and Junior Post-docs an opportunity to present their work and to receive feedback.

Keynote speaker of the RISE5 Workshop is Robert Seamans (NYU Stern).

See the full Program.

For more information see RISE Workshop.

Programme

12/15/2022
 

09:00 a.m.
Opening Remarks: Intro to the MPI project

11:00 a.m.
Panel 1: The role of the SDGs and data sharing to better address climate change

02:00 p.m.
Panel 2: The current data-related legal framework to tackle climate change: what is there and what is missing

04:15 p.m.
Panel 3: Producing from the land: data-related business and technologies to tackle climate change

12/16/2022
 

09:00 a.m.
Panel 4: Consumption in the city: data-related initiatives to foster a sustainable consumption culture

11:15 a.m.
Panel 5: Data-based initiatives to fight climate change: going beyond the market

02:00 p.m.
Closing Remarks

The data economy offers great potential for emerging economies to achieve sustainable development goals (SDGs). However, data-sharing policies must be properly framed to leverage this potential. This is the starting premise of the international research project led by the Max Planck Institute for Innovation and Competition, in collaboration with international partners, called "Data Sharing in Emerging Economies". The project aims to define a holistic normative regulatory theory on promoting data sharing that will help to fulfil SDGs. Furthermore, it aims to develop specific policies for data sharing in emerging economies and, ultimately, provide assistance for possible legal reforms. The partners taking part in the project are Université Virtuelle du Sénégal, BML Munjal University of India, and Mackenzie University of Brazil.

For Brazil, the project’s main focus is on Climate Action (SDG 13) due to its relevance for the country and the world, the limited progress in environmental goals reported so far, and the great potential to advance in this area by fostering the data economy. Given the scope of the topic, the project is narrowed down to address environmental issues from a territorial perspective, taking into account the interrelation between agricultural production, transportation processes, and product consumption in cities. This opens up questions on how agribusiness and (city) consumption impact climate change, a matter related to economic growth (SDG 8) and responsible consumption and production (SDG 12). It also raises questions about the impact of climate change on rural and urban life, which connects to issues of deforestation and life on land (SDG 15), and how to promote sustainable and clean cities (SDG 11). All of these are relevant topics on the Brazilian policy agenda.

In its first stage, the project will be focused on the Amazon and São Paulo regions, each with its own rural/urban dynamics, but also interconnected along the national agribusiness product value chain. As evidence shows, agribusiness is one of Brazil’s main economic sectors, accounting for about 21% of GDP in 2018. It is also one of the sectors with the greatest potential to reduce greenhouse gases (GHG). A major source of pollution is beef herds, whose exploitation also relates to illegal deforestation actions. As noted by the OECD, while combating illegal deforestation is a priority, digital technologies based on big data and machine learning are also key to increasing farming efficiency and thus contributing to climate action. Finding more evidence on how data-sharing initiatives can promote green production and growth, as well as what the policy and technical challenges are to making this happen, are concrete goals of the project.

So is identifying the extent to which data-sharing initiatives may help to foster a greener consumption culture. Evidence shows that cities are responsible for rapid GHG effects. How products are transported to urban areas, what the consumption habits of individuals are, and how waste is disposed of and/or reused, are key questions related to goods’ life cycle and their environmental impact. The project aims to explore data-related initiatives with the potential to mitigate the impact of consumption and waste in São Paulo. So far, indicators and programs related to climate action exist, as well as some initiatives, like platforms for agriculture product traceability that can improve the consumer decision-making process and tax collection. The project aims to identify further data-related initiatives —market and non-market based—  that can benefit from data sharing, such as platforms to collate data on food loss, waste, and surplus, or data sharing for the process of waste-separate collection.

This exploratory research will take the form of a workshop with stakeholders from academia, the public sector, civil society, and industry. It will be held on 15-16 December 2022, at the premises of the Mackenzie University in São Paulo. Stakeholders are kindly invited to contribute by providing insights regarding: (1) business models used and market realities; (2) existing legal and technical impediments to data sharing; and/or (3) the role they foresee of policy- and lawmakers for any future policy or legislative action.