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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.

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.

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.

International audience

In 2020, firms expected their innovation expenditures to decrease by about 2% in 2020 compared to 2019. This decline is much smaller than that in 2009 following the financial crisis, when innovation expenditures fell by 11%. However, smaller firms with 5 to 99 employees planned to cut their innovation expenditures by 7% to 17 % in 2020. For 2021, firms planned a slight increase in innovation expenditure by 1%. The number of employees in short-time work in Germany peaked at 2.9 million in April 2020, corresponding to a share of 8.7% of all employees. The situation relaxed by October 2020, when the share of short-time workers fell to 2.3%. The most R&D-insensitive industries showed the highest share of short-time work in April 2020 (16.6%), but the lowest in October 2020 (2.0%), indicating that the impact of the crisis on R&D intensive industries weakened in the second half of 2020. This development was strongly driven by the drop of short-time workers in the automobile industry. The recovery of some export-intensive industries, such as the automobile industry, also reflects that firms are starting to adopt and overcome the initially severe disturbances and challenges Covid-19 imposed on international value chains. The global R&D expenditures of large R&D performing German firms declined on average by 1% between 2019 and 2020. However, there are major differences between individual industries. The pharmaceutical and ICT service industries significantly increased their global R&D expenditures, whereas mechanical engineering experienced the sharpest decline in 2020. Firms' average R&D intensity increased in most industries, except for the electronics/instruments industry and ICT services. Firms with R&D or other innovation activities prior to the crisis more often reported negative impacts of the Covid-19 crisis on their general business activities than firms that do not conduct any R&D or innovation activities. This result may be linked to the fact that the crisis had a more severe impact on firms with a more complex internal organisation and more international activities, both of which are typical for R&D and innovation performing firms. The most common strategic responses of firms to the Covid-19 crisis were i) to enhance the digitalisation of their internal processes and ii) to extend their digital offers and sales channels. Both responses were mostly of permanent nature. Reorganising sales towards domestic customers and removing products or services from their portfolio were less common responses. The most frequent crisis-related changes in firms' innovation activities include i) the extension of innovation projects and ii) a reduction in the number of innovation projects due to a lack of impulses for innovation. Reducing collaborations and withdrawing from all innovation activities were less frequent changes.

This paper analyses the impact of intangible capital on firm-level productivity for Germany using panel data from the Community Innovation Survey for the time period 2006 to 2018. Our paper presents three novel results. First, we find a highly significant positive relationship between intangible capital and firm-level productivity with elasticities overall in line with previous findings reported for other large EU economies. Second, our results show that both manufacturing and services are highly intangible-capital intensive, and that intangibles have a greater impact on firm-level productivity in services - particular in the business services sector. Third, our results show that intangible capital investments in German firms are equal to investments in tangible capital since the early 2000s. Overall, the evidence presented in our paper indicates that Germany - in line with other advanced economies - has undergone a structural transition into a knowledge economy in which intangibles act as an important driver of firm-level productivity.

We study the cyclicality of public R&D in 28 OECD countries (1995 – 2017). While procyclical on average, public R&D reacts asymmetrically over different phases of the business cycle and becomes acyclical during recessions. It is also heterogeneous across countries: Innovation leaders and followers behave countercyclically during recessions while moderate innovators behave procyclically. Furthermore, the share of public R&D allocated to the business sector is countercyclical, but the thematic composition remains stable. These results, not driven by countries’ financial constraints, imply that countries behind the innovation frontier might strengthen their resilience to economic crises by adopting countercyclical R&D strategies.

We analyse the geographic proximity of innovative firms to different types of knowledge sources in an urban environment on a microgeographic scale. Based on a comprehensive panel data set of manufacturing and service firms in the German capital city Berlin, we investigate the characteristics of firms' knowledge environment while differentiating by the type of innovation. Geocoded firm locations at the level of individual addresses allows us to describe the knowledge environment of firms on a very fine microgeographic scale. We find that innovative firms are located in places with higher numbers of same-sector firms, more start-ups and a higher inflow of other firms. They also locate in closer proximity to universities and research institutes. These differences decay rapidly within a few metres (50-250 m), indicating a truly microgeographic scope of knowledge sources in urban environments.

Knowledge-based capital is a key factor for productivity growth. Over the past 15 years, it has been increasingly recognised that knowledge-based capital comprises much more than technological knowledge and that these other components are essentia for understanding productivity developments and competitiveness of both firms and economies. We develop selected indicators for knowledge-based capital,often denoted as intangible capital, on the basis of publicly available data from online platforms.These indicators based on data from Facebook and the employer branding and review platform Kununu are compared by OLS regressions with firm-level survey data from the Mannheim Innovation Panel (MIP). All regressions show a positive and significant relationship between survey-based firm-level expenditures for marketing and on-the-job training and the respective information stemming from the online platforms. We therefore explore the possibility of predicting brand equity and firm-specific human capital with machine learning methods.

Hidden Champions (HCs) are firms unknown to the wider public, but global leaders in the niche markets they serve. This paper looks at distinctive features of these firms, focusing on their dynamic capabilities. Employing a unique data base on German firms, we identify a representative sample of German HCs. Based on a matching technique, we examine differences to other firms in terms of the firms' processes, position, and path. We find that HCs' competitive strategy rests on technology leadership and customisation. HCs are more open in their knowledge management, but without compromising control over the new product development process. HCs do not invest more into innovation, but achieve higher innovation success. The higher efficiency can be linked to their superior technological capabilities and to higher investment in human capital and HR management practices that mobilise the creative potential of their employees.

On behalf of the Federal Ministry for Economic Affairs and Energy, the Centre for European Economic Research (ZEW) in Mannheim and the Fraunhofer Institute for Systems and Innovation Research ISI in Karlsruhe undertake continual research into the cultural and creative industries (CCI) in Germany. The results of this work appear in an annual monitoring report that presents key economic indicators on the cultural and creative industries. The analyses contained in the report are based on data from publicly available sources, data held by ZEW, and from a survey on the cultural and creative industries sector in Germany conducted by ZEW specifically for this project. This summary of the report presents the key results for the project year 2019. [...]