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The COVID-19 pandemic has affected firms in many economies. Exploiting treatment heterogeneity, we use a difference-in-differences design to causally identify the short-run impact of COVID-19 on innovation spending in 2020 and expected innovation spending in subsequent years. Based on a representative sample of German firms, we find that negatively affected firms substantially reduced innovation expenditure not only in the first year of the pandemic (2020) but also in the two subsequent years, indicating ’Long–Covid’ effects on innovation. In 2020, innovation expenditure fell by 4.7 % due to the pandemic. In 2022, innovation spending was even 5.4 % lower compared to the counterfactual scenario without the pandemic. Firms with higher pre-treatment digital capabilities show higher innovation resilience during the pandemic. Moreover, COVID-19 leads to a decrease in innovation spending not only in firms that were strongly negatively affected by the pandemic, but also in those firms that experienced a positive demand shock from the pandemic, presumably to increase production capacity.

The R&D policy instrument mix concept has become increasingly important for understanding how public R&D support drives firm-level R&D. To-date, empirical studies have conceptualised the instrument mix as a static unit, whereby firms receive multiple policy instruments at one point in time. However, firms can also receive multiple instruments in a sequence, over time. While sequencing is well rehearsed theoretically, this remains a major gap in the empirical literature. Our study evaluates, for the first time, how R&D policy instrument mix sequencing impacts firm-level R&D. We construct a unique dataset, containing almost 25,000 firm-year observations over a 17-year period for Ireland. Our analysis focuses on R&D grants, R&D tax credits, and publicly-supported academic-industry collaborations, and develops two novel approaches to measure R&D policy instrument mix sequencing. Our results suggest that R&D policy instrument mix sequencing is highly effective at driving firmlevel R&D, but that some sequences are more effective than others. These findings highlight opportunities to realise superior policy outcomes through targeted sequencing.

Die deutsche Wirtschaft hat die Ausgaben für Innovationen im Jahr 2021 deutlich um 4,7 Prozent auf 178,6 Milliarden Euro gesteigert. Damit wurde der Rückgang aus dem Jahr 2020 - damals sanken die Innovationsausgaben pandemiebedingt um 3,6 Prozent auf 170,5 Milliarden Euro - wettgemacht. Das Vor-Pandemie-Niveau aus dem Jahr 2019 (176,9 Milliarden Euro) wurde allerdings nur leicht übertroffen. Gleichzeitig erhöhte sich die Anzahl der kontinuierlich forschenden Unternehmen um knapp 8 Prozent auf einen neuen Höchststand von etwa 42.000. Zu diesen Ergebnissen kommt die aktuelle Innovationserhebung 2022, die das ZEW Mannheim im Auftrag des Bundesministeriums für Bildung und Forschung (BMBF) jährlich durchführt. German companies increased their innovation spending in 2021 by 4.7 per cent to 178.6 billion euros. This significant increase has made up for the decline in 2020, when innovation expenditure fell by 3.6 per cent to 170.5 billion euros due to the pandemic. However, the pre-pandemic level from 2019 (176.9 billion euros) was only slightly exceeded. At the same time, the number of companies continuously conducting R&D rose by almost eight per cent and reached a new high of around 42,000. These are the findings of the Innovation Survey 2022 (in German only), which ZEW Mannheim conducts annually on behalf of the German Federal Ministry of Education and Research.

Artificial Intelligence (AI) is often regarded as the next general-purpose technology with a rapid, penetrating, and far-reaching use over a broad number of industrial sectors. A main feature of new general-purpose technology is to enable new ways of production that may increase productivity. So far, however, only very few studies investigated likely productivity effects of AI at the firm-level; presumably because of lacking data. We exploit unique survey data on firms’ adoption of AI technology and estimate its productivity effects with a sample of German firms. We employ both a cross-sectional dataset and a panel database. To address the potential endogeneity of AI adoption, we also implement IV estimators. We find positive and significant effects of the use of AI on firm productivity. This finding holds for different measures of AI usage, i.e., an indicator variable of AI adoption, and the intensity with which firms use AI methods in their business processes. ispartof: FEB Research Report MSI_2203 pages:1-36 status: published

Artificial Intelligence (AI) is often regarded as the next general-purpose technology with a rapid, penetrating, and far-reaching use over a broad number of industrial sectors. A main feature of new general-purpose technology is to enable new ways of production that may increase productivity. So far, however, only very few studies investigated likely productivity effects of AI at the firm-level; presumably because of lacking data. We exploit unique survey data on firms’ adoption of AI technology and estimate its productivity effects with a sample of German firms. We employ both a cross-sectional dataset and a panel database. To address the potential endogeneity of AI adoption, we also implement an IV approach. We find positive and significant effects of the use of AI on firm productivity. This finding holds for different measures of AI usage, i.e., an indicator variable of AI adoption, and the intensity with which firms use AI methods in their business processes.

Eco-innovations are crucial for the mitigation of climate change effects. It is therefore important to know if the existing climate change regulations and carbon pricing are appropriate and sufficient to trigger such innovations. Besides government measures, the demand for carbon neutral products or the impacts of climate change such as extreme weather conditions leading to higher costs for the affected firms may also promote eco-innovation activities. For the first time, the new wave of the Community Innovation Survey 2020 in Germany allows an analysis of the effects of climate change policy and costs, demand for climate friendly goods and extreme weather conditions on (eco-)innovation. The results of probit and treatment effect models show that innovative firms seem to be significantly more affected by climate change measures and consequences compared to other firms. All climate change indicators are positively correlated to eco-innovations. Interestingly, other innovation activities also profit from the extent to which a firm is affected by climate change albeit the marginal effects are lower compared to eco-innovations. Demand for climate neutral products is significantly important for all eco-product-innovations.

Foreign-owned subsidiaries make significant contributions to national Research and Development (R&D) in many host countries. Policymakers often support subsidiaries through R&D grants and R&D tax credits. A key objective of this funding is to leverage R&D-driven firm performance benefits for the host economy. However, the subsidiary's parent firm may decide not to exploit the results from publicly-funded R&D projects in the host country. Therefore, supporting subsidiaries' R&D presents a risk that significant amounts of public funding may translate into little, or no payoffs for the host economy. Our study provides the first evaluation of 1) whether public R&D funding stimulates additional R&D investment in subsidiaries, 2) whether policy-induced R&D drives subsidiary performance, and 3) the differential effects of R&D grants and R&D tax credits. Drawing on a unique panel dataset for Ireland (2007-2016), we find that both R&D supports drive subsidiary R&D, resulting in substantial host country firm performance benefits.

Mit dieser Studie wird die Liste forschungsintensiver Industrien - die sogenannte "Hochtechnologie-Liste" - auf Basis der aktuellen Klassifikation der Wirtschaftszweige (WZ 2008) in aktualisierter Form vorgelegt. Die neue "ISI/ZEW/SV-Liste" deckt, in tief gegliederter Ebene, sowohl den Industrie- als auch den Dienstleistungssektor ab. Neben der Liste forschungsintensiver Wirtschaftszweige enthält die Studie auch eine Liste für das aktuelle internationale Warenverzeichnis für den Außenhandel (SITC Rev. 4) sowie eine Liste wissensintensiver Wirtschaftszweige, die auf Basis von Daten zum Qualifikationsniveau der Beschäftigten sowie der Art der Beschäftigung erstellt wurde. Zudem wurden weitere Indikatoren der Wissensintensität betrachtet, die verschiedene Investitionen in Wissenskapital abbilden, nämlich Humankapitalinvestitionen, Investitionen in Software und Datenbanken, in Markenwerte und Reputation, sowie in sonstiges nicht-technisches Wissen.

Studie im Auftrag des Verbands der Chemischen Industrie e.V.

Process innovation is an important part of firms’ innovation activities and supposed to significantly contribute to positive returns from innovation. Measuring process innovation output at the firm level is still in its infancy, however. This paper reports empirical evidence on measures of process innovation output that have been collected in the German part of the Community Innovation Survey (CIS) over the past 25 years. Distinguishing between cost reduction and quality improvement, the paper finds low item non-response for the qualitative (yes/no) part of both indicators. Item non-response is much higher for quantitative information and does not decrease with questionnaire experience of firms. For both cost reduction and quality improvement, response to quantitative indicators is categorical in nature, and firms tend to report the same set of values when participating frequently in the survey. The determinants of realising the two types of process innovation output are very similar. The observed variance in the quantitative part is difficult to explain for both measures. The impact of process innovation output on firm performance is limited. While cost reduction seems to spur the export share, sales increase due to quality improvement is associated with higher profitability.

Obtaining indicators on innovation activities of firms has been a challenge in economic research for a long time. The most frequently used indicators - R&D expenditure and patents - provide an incomplete picture as they represent inputs and throughputs in the innovation process. Output measurement of innovation has strongly been relying on survey data such as the Community Innovation Survey (CIS), but suffers from several short-comings typical to sample surveys, including incomplete coverage of the firm sector, low timeliness and limited comparability across industries and firms. The availability of big data sources has initiated new efforts to collect innovation data at the firm level. This paper discusses recent attempts of using digital big data sources on firms for generating firm-level innovation indicators, including Websites and social media. It summarises main challenges when using big data and proposes avenues for future research.

Corona-Pandemie wirkt als Hemmnis und als Impulsgeber für Innovationen - Die deutsche Wirtschaft hat im ersten Jahr der Corona-Krise ihre Innovationsausgaben um 3,6 Prozent auf 170,5 Milliarden Euro reduziert. Zwölf Prozent der Unternehmen haben aufgrund der Pandemie gänzlich auf die Durchführung von Innovationsaktivitäten verzichtet. Gleichzeitig haben elf Prozent der Unternehmen aufgrund der Pandemie-Situation in zusätzliche Produktinnovationen investiert, zwölf Prozent haben zusätzliche Prozessinnovationen vorangetrieben. Das sind zentrale Ergebnisse der Innovationserhebung 2021, für die das ZEW Mannheim im Auftrag des Bundesministeriums für Bildung und Forschung (BMBF) im Jahr 2021 die Unternehmen in Deutschland befragt hat. COVID-19 Pandemic Is Both an Obstacle and an Impetus for Innovation - German companies reduced their innovation spending by 3.6 per cent to 170.5 billion euros in the first year of the COVID-19 crisis. Twelve per cent of companies did not undertake any innovation activities at all due to the pandemic. At the same time, eleven per cent of the companies invested in additional product innovations in response to the pandemic situation and twelve per cent pushed ahead with additional process innovations. These are key findings of the Innovation Survey 2021, which ZEW Mannheim conducted among German companies on behalf of the German Federal Ministry of Education and Research.