Bremen Papers on Economics & Innovation
In the light of anthropogenic climate change, a polarized discussion about the right measures to keep economic activity within the planet’s ecological boundaries has emerged: Advocates of de-growth argue that continuous GDP growth is impossible because of natural limits to growth. They call for measures to change individual consumption patterns, to constrain affluence in wealthy countries, and to reform the economic system in such a way that it can fulfil its functions even without continuously growing GDP. Advocates of green growth argue that GDP growth and ecological impacts are conceptionally independent and call for promoting entrepreneurial activity which facilitates the transition towards a carbon-neutral, circular economy without curtailing economic growth. At first sight, the two views appear in unresolvable conflict. After sketching the two approaches, we point towards their common ground and argue that the conflict may concern ideologies rather than evidence-based policy proposals. Taken seriously, both call e.g. for urgent action; for fundamental reforms to correct faulty price signals; for promoting a circular economy powered by regenerative energy sources; for political measures which enable sufficient life styles; and for evidence-based rather than ideological economic analysis. Focusing on this common ground may accelerate the vital transition to a sustainable economy.
Russian regions display a significant variation in terms of waste management efforts. This is puzzling considering the importance of waste management for all regional governments and the urgency of the problem for the Russian public as reflected in opinion polls. We study whether more authoritarian regional governments in Russia are better able to solve the problem of waste management. Using a regional panel data set for the period of 2012-2019, we find that our measure of the degree of authoritarianism – the share of votes for the United Russia party in parliamentary elections – has a strong positive effect on the share of recycled waste in the Russian regions. This result indicates that more authoritarian regions tend to recycle more household waste than less authoritarian regions. This finding is consistent with the theory of environmental authoritarianism that suggests that authoritarian governments are better able to tackle environmental challenges.
This study explores the regional innovation system characteristics that build the basis for the regional absorptive capacity of entrepreneurial knowledge. Regionalized patent data is combined with firm level and regional information for German regions over the period 1995 until 2015. Network analysis is applied to identify regional innovation system characteristics on three different layers: 1) cooperation between incumbent firms, 2) learning regimes, and 3) the technological knowledge base. Random forest analyses on basis of conditional inference classification trees are used to identify the most important characteristics for the regional absorption of entrepreneurial knowledge in general and on different efficiency levels. It is shown that characteristics on all three layers impact the regional absorption of entrepreneurial knowledge. Further, the direction and magnitude of the effect regional innovation system characteristics have on the regional knowledge absorption vary across different levels of absorption rates. It is concluded that for a successful implementation of policies to increase the impact of entrepreneurial knowledge on regional development, the regional innovation system needs to be monitored and adapted continuously.
The recognition of regional business opportunities is the crucial starting point of the entrepreneurial process that governs the persistence of regional entrepreneurship patterns. This persistence depends on the quantity of perceived opportunities and the quality of opportunities perceived by regional inhabitants. However, it is unclear which region-individual interactions relate to the quantity regional business opportunity perception and how long-standing regional entrepreneurship patterns are reflected in conceptions of entrepreneurship that govern the quality of perceived opportunities. A primary data collection in German regions with distinct long-standing entrepreneurship patterns assessed two main aspects. First, the regional embeddedness of respondents on four levels – actor, network, environmental, and cultural – is set in relation to the likelihood of opportunity perception. Second, an implicit measurement of mental representations of entrepreneurship is examined. The mental representations of entrepreneurship, reflecting the conceptions of entrepreneurship, are investigated to identify differences between the conceptions of entrepreneurship that come along with the long-standing regional entrepreneurship patterns and to detect differences between opportunity-perceivers and non-perceivers. The results suggest that regions reinforce long-standing entrepreneurship patterns with distinct individual-region relations that impact the quantity of perceived regional opportunities and distinct conceptualizations of entrepreneurship that shape the quality of perceived opportunities. Differences are observed for the perception of opportunities that are characterized by innovativeness versus those that are general in nature, showing that innovative opportunity perception is less dependent on the regional context than general opportunity perception
This paper contributes to the discussion on exploration and exploitation by analyzing the innovation behavior of SMEs and large firms during the first year of the COVID-19 pandemic in Germany. It provides a novel way to measure the type of firm innovation behavior in a dynamically changing environment. After collecting news articles about innovation activities conducted by firms, we applied text mining techniques to identify the positioning of each firm on the continuum from exploitation to exploration. The results of our analyses indicate three main dynamics: 1) all studied firms tend to conduct more explorative innovation activities during the COVID-19 crisis, 2) large and “technology-intensive” firms are more prone to perform explorative innovation activities than SMEs and firms that are not “technology-intensive”, and 3) technology intensity is associated with explorative innovation behavior during the crisis. Our results suggest that considering technology intensity and the size of firms is important for designing effective policies during crises.
Technological progress leads to the development of robots that are more error-prone and fragile than their predecessors. As a consequence, the utilization of the existing automation capital stock is associated with higher wear and tear, CPU overload or communication downtime and, as a consequence,an increase of depreciation costs. This in turn affect new investments in the future. Considering a growth model with physical and automation capital utilization, we argue that in a fully automated society, the utilized automation capital is a perfect substitute for labor, not the automation capital stock per se. We show that it is not necessarily the introduction of capital utilization by itself, but the relationship between the elasticities of utilization of automation and physical capital that plays a crucial role in slowing down the convergence speed in a model that reflects an automated society.
This paper investigates how the development of AI-related inventions by Multinational Enterprises (MNEs) affects their technological trajectories and innovative performance. I combine a matched-pair analysis with an extension of the Difference-in-Difference method to analyse these effects over a novel panel dataset of MNEs. This dataset links over 30 thousand MNEs to more than 10 million patents that these companies owned directly or indirectly (i.e., through their subsidiaries) in the period from 2011 to 2019. The results indicate that MNEs introducing AI-related inventions increase the relatedness of subsequent inventions by about 10 per cent compared to a control group. These results are robust when accounting for a self-selection bias. AI is thus being used to reinforce the existing technological trajectories, rather than to disrupt them. The results also suggest that the number of subsequent inventions is about 40 per cent higher for MNEs that introduce AI during the observation period compared to the control group, without significant effects on the intensity of R&D expenditures per invention. It is argued that this increase in innovative performance is linked not only to knowledge dynamics created by learning about AI but also by AI’s technical potential to be used for learning.
State socialism failed due to its inner contradictions. Despite huge investments in R&D-intensive industries, the soviet-type economy collapsed in 1989 in Eastern Germany, and the market-based system in the Western part prevailed. We compare the two parallel existing innovation systems in Germany to shed light on the success and failure of the state-led innovation system. Based on newly created indicators from archive data we show in a natural experiment setting that modernization efforts in relation to GDP was much bigger in the socialist as compared to the market economy in the last decades. These achievements, however, could not fully unfold in favor of economic growth due to obstacles related to the setting of research priorities, innovation incentives, and knowledge flow.
This paper investigates the impact of applicant and inventor team composition on patent commercialization in form of product creation. It outlines the importance of applicant and inventor team characteristics, i.e. specifically, size and internationality, on the speed of market authorization of a patent-related product and on the product quality. The analysis is performed for the European pharmaceutical industry. The product data is taken from the European Medicines Agency website for the period 2010-2019. Manual patent-product concordance is established with the help of the Pat-INFORMED database from the World Intellectual Property Organization and the Health Canada database. The created dataset presents combined data on patent and product characteristics. Results from an accelerated failure time model show that larger applicant teams as well as the presence of international applicants and inventors decelerate the market authorization of patent-related products. Results of the probit analysis show that larger inventor teams lead to patents of higher quality.
It is of key importance to identify innovative business ideas in an early stage, so that funding resources can be adequately allocated according to their economic potential. Traditional indicators do not reliably discriminate business ideas with high degree of innovativeness and high incorporation chances from those with low degree of innovativeness and low incorporation prospects. Therefore, this paper examines the content of business idea descriptions to improve the estimations of the incorporation probability. The paper aims to answer two questions: 1) Are there differences in topic prevalence in innovative and non-innovative business ideas?, and 2) How does the composition of topics related to a business idea influence its incorporation probability? Structural topic modeling and classification tree analysis are applied on business idea descriptions from a competition in Bremen, Germany, from 2003 until 2019. The results show that business idea descriptions are a rich source of information to identify both innovative ideas and those with higher incorporation prospects.
The most important resource to improve technologies in the field of artificial intelligence is data. Two
types of policies are crucial in this respect: privacy and data-sharing regulations, and the use of
surveillance technologies for policing. Both types of policies vary substantially across countries and
political regimes. In this paper, we examine how authoritarian and democratic political institutions can
influence the quality of research in artificial intelligence, and the availability of large-scale datasets to
improve and train deep learning algorithms. We focus mainly on the Chinese case, and find that –
ceteris paribus – authoritarian political institutions continue to have a negative effect on innovation.
They can, however, have a positive effect on research in deep learning, via the availability of large-scale
datasets that have been obtained through government surveillance. We propose a research
agenda to study which of the two effects might dominate in a race for leadership in artificial intelligence
between countries with different political institutions, such as the United States and China.
Environmental innovation (EI) plays an important role in decoupling economic growth and environmental harm. This paper focuses on the environmental innovation behavior of companies in transition countries of Eastern Europe and Central Asia, which have been little studied so far. These countries share the Soviet legacy of environmental mismanagement, and have restructured their innovation systems relatively recently in the course of transition. The EBRD-EIB-WB Enterprise Survey (2018-2020) allows us to examine the determinants of environmental innovation in 29 transition countries. Although the theory places a greater emphasis on external sources of knowledge in EI, the results indicate that collaborative R&D is still quite weak in these countries. Moreover, environmental regulation increases the likelihood of adopting energy efficiency measures, while customers demanding environmental standards increase the likelihood across all innovation activities, indicating an increasing sustainability awareness among consumers.
In economic research about climate change mitigation, there is a tension between the objectives to ensure scientific rigor (focusing on orthodox theory) and to illuminate blind spots of relevance (drawing on different “heterodox” theories). Our aim is to develop an economic perspective on climate change mitigation which considers both objectives.
We conduct a critical literature review, searching for coherent economic theory lattices, which meet the requirements of research programs, i.e. contain a pre-analytic vision, an analytical core including a concept of rationality, and examples of applications in empirical research. We develop a framework structuring these research programs and associated research fields and search for examples illustrating their applicability to climate change mitigation.
We identify several research fields within four major research programs that perceive economic phenomena as (1) individual optimization decisions (neoclassical analysis of efficient and of inefficient equilibria and behavioral economics); (2) a set of institutions (New and Original institutional economics); (3) a complex evolutionary system (Biophysical and Evolutionary economics); and (4) an objective function (which can guide research focusing on the content or the distribution of the normatively defined units of interest). For each research program and its subdivisions, we present theoretical elements and illustrate how they can improve our understanding of how economic activity contributes to climate change and how these impacts can be alleviated.
There is a need for more systematic evidence synthesis to validate the contributions of the different economic research fields and to improve their selection and application to climate change.
We examine the explicit business model preferences and implicit mental representations of entrepreneurship in the early phase of the crisis. We find that the crisis comes with adaptations in both. During crisis, society is open for new business models, even though people increasingly rely on established economic actors instead of opening up towards newly founded firms. We conclude that the early and sudden impact of the crisis influences the entrepreneurial culture onwards and therefore potentially future entrepreneurial activities.
Green technologies are at the very core of endeavors to combine economic and environmental targets to achieve sustainable growth. In this article, we aim to determine the impact of green technology development on total factor productivity of European regions. Our paper contributes to the literature on technological change and regional growth in various ways. i) Our paper is, to the best of our knowledge, the first to assess the specific role of green technologies for regional growth on a broad empirical base. ii) We advance methodologically on the pertinent literature by explicitly accounting for cross-sectional dependence in our empirical approach. iii) By providing a simple theoretical framework, we directly link our results to implications of environmental policies for capital accumulation and composition dynamics, contributing to the ongoing debate revolving around the strong version of the Porter hypothesis. Our results, based on a sample of 270 European NUTS-2 regions over 25 years, imply that general technology development is mostly associated with positive economic returns, but our data is not supportive of positive economic returns to green technologies.
Cognitive, social and geographic distances between collaborators impact the likelihood to succeed together. This paper argues that cultural proximity moderates this impact. While taking Boschma’s (2005) proximity concept as a point of departure, the informal part of institutional distance – cultural distance – is emphasized. Culture is defined following the concept of Hofstede et al. (2010), applying it one of the first times to the regional level. Results reveal that cultural proximity has different layers, all moderating the impact of cognitive, social and geographic distances. Out of the six investigated cultural distance layers, five moderate the impact of geographic distance, another five the one of social distance and four moderate the impact of cognitive distance.
While innovations have been acknowledged as a key factor for economic growth, it appears that they are unique features of central actors. Recently, especially the outstanding opportunities arising from rather radical innovations have been highlighted. These kinds of innovations combine knowledge pieces that have not been combined before and consequently create something radically new. While the influence of firms’ network position on innovativeness in general has already been investigated, it remains to be researched in the context of radical innovations. We address this research gap by empirically investigating the influence of firms’ network position on the emergence and diffusion patterns of radical innovations. By analysing a unique dataset evidence is found that central firms are essential drivers of the emergence and diffusion of radical innovations. However, the results also indicate that under certain conditions (e.g. high knowledge diversity) also peripheral firms can contribute to the emergence of radical innovations.
It is a challenge to empirically investigate rapidly developing situations. An economic crisis is such a situation in which firms exit, enter, and create new business models. The current pandemic has caused a turbulent situation with hardship, but at the same time with creative potential of innovative change. It calls for empirical analyses, but firm level data based on surveys is hard to collect given the high speed of developments. An alternative data source are news articles reporting on innovation issues and assessed by text mining techniques. This is exemplified in this chapter. It shows how topic modeling can be used to scrutinize the shift of innovation topics since the beginning of the COVID-19 crisis. The results apply to a small innovation system in Germany and confirm that innovation priorities change during a crisis and that many different actors are involved.
This preprint has not undergone any post-submission improvements or corrections. The Version of Record of this article is published in Springer Journal Eurasian Business Review and is available online at https://doi.org/10.1007/s40821-021-00192-y
Based on Schumpeterian theoretical considerations, this paper investigates the innovation behavior of firms during the severe economic crisis of the year 2008/2009. It focuses on transition countries of Central and Eastern Europe and Central Asia, which have completely restructured their innovation systems through the course of transformation from planned to market economies a relatively short time ago. As a result of the crisis, we observe a strong decline of innovation activity in all transition economies. In line with the literature, there is, however, empirical evidence for both creative destruction as well as creative accumulation. This underlines two key findings: firstly, the universality and durability of Schumpeterian assumptions, and secondly, a call for anti-cyclical innovation policy.
Although repression against elites is a common occurrence in authoritarian regimes, we know little about which elites are targeted. This paper uses an original dataset on the prosecution of mayors in large Russian cities to examine the factors that make elites more likely to be arrested.We argue that in electoral authoritarian regimes like Russia, regime leaders are reluctant to arrest popular officials. Such officials command political capital that is useful to the regime, and arrests of prominent officials can produce popular backlash. We examine this argument using an original dataset on all arrests of municipal leaders in Russia’s 221 largest cities between 2002 and 2018. We find that mayors who won their elections by large margins are less likely to be arrested. In addition, we demonstrate several other substantively important patterns: 1) a mayor’s professional background is not related to the likelihood of arrest, 2) opposition mayors are four times more likely to be arrested, and 3) arrests are more likely in ethnic republics.
The income inequality hypothesis (IIH) predicts that income inequality itself is the major determinant of population health. A novel continuous wavelet approach allows us to directly estimate the association between health and income inequality for the U.S. between 1941 and 2015 simultaneously, at any frequency and time domain. After controlling for gender, aggregate income, governmental spendings on health and education, the paper finds, first, that the frequency domain is relevant for identifying any relationship between health and income inequality, but, second, the overall evidence for the IIH is weak. Only for the time span 1956-1993 and for long-run frequencies, we find that an increase of income inequality has adverse effects on health. We are not able to confirm the existence of the IIH for any other time periods at different frequencies, even not for the period of the recent financial crisis. Hence, the empirical confirmation of the IIH is the rare exemption rather than the rule and its existence, at least on an aggregate level, clearly depends on the frequency domain.
In this article, we examine how investor motives affect investment behavior in equity crowdfunding. In particular, we compare the investment behavior of sustainability-oriented with ordinary crowd investors on six leading equity crowdfunding platforms in Austria and Germany and investigate whether they suffer from a default shock that was recently identified by Dorfleitner et al. (2019). In general, we find evidence of a default shock in equity crowdfunding that occurs immediately after the event or if investors experience more than two insolvencies. Moreover, we find that sustainability-oriented investors pledge larger amounts of money and invest in more campaigns than ordinary crowd investors. The results also suggest that sustainability-oriented crowd investors care about non-financial returns, as they react more sensitively after experiencing a default in their equity crowdfunding portfolios, which indicates that they suffer beyond the pure financial loss. These findings contribute to recent literature on equity crowdfunding, socially responsible investing, and how individual investment motives and personal experiences affect investment decisions.
Are investors in electoral authoritarian regimes discriminated against for political activism? In this paper, we implement a simple experiment to test whether affiliation with the ruling party or the political opposition affects the probability that investors receive advice from investment promotion agencies in Russian regions. Between December 2016 and June 2017, we sent 1504 emails with a short question and a number of randomized treatments to 188 investment promotion agencies in 70 Russian regions. Although investment promotion agencies are nominally depoliticized in Russia, we find that switching the political affiliation of a potential investor from the opposition party “Yabloko” to the government party “United Russia” on average increases the chances to receive a reply by 30%. The effect strongly depends on regional levels of political competition, with higher levels of discrimination in regions that are less politically competitive.
Radical innovations by definition have a great influence on the future of the existing economic systems. It means that not only radical innovators, but also other stakeholders can experience their impact. The factors, influencing the direction and strength of this impact are far from being understood. Early appropriation of radical innovator’s knowledge may be especially important for small and medium-sized firms (SMEs), serving as the source of competitive advantage. Here different proximity dimensions (geographical, cognitive, institutional, organizational and social), measuring respective distances to a radical innovator, may play a crucial role. Thus, this paper opts at revealing the importance of proximity measures for the case of German biotechnology SMEs. A longitudinal dataset covering the period from 1996 to 2016 for the innovative performance of SMEs, that are citing radical innovators, is used as the base of the analysis. Results only partially confirm the findings of previous research by indicating the negative effect of higher distance and organizational proximity. However, the effect of both cognitive and social dimension could not be confirmed. Reasons for that potentially lie both in unique character of radical innovation and peculiarities of the biotechnology field in Germany.
During the past decade, equity crowdfunding (ECF) has emerged as an alternative funding channel for startup firms. In Germany, the Small Investor Protection Act became binding in July 2015, with the legislative goal to protect investors engaging in this new asset class. Since then, investors pledging more than 1,000 EUR now must self-report their income and wealth. Investing more than 10,000 EUR in a single ECF issuer is only possible through a corporate entity. We examine how the Small Investor Protection Act has affected investor behavior at Companisto, Germany’s largest ECF portal for startup firms. The results show that after the new law became binding, sophisticated investors invest less on average while casual investors invest more. Moreover, the signaling capacity of large investments has disappeared.
This paper relates cultural evolution theory and social learning dynamics to induced preference change in consumption behavior. We argue that the promotion of sustainable consumption via preference change is a cornerstone of future policy and should complement standard regimentations such as regulation for harm reduction in production and the investment in green technologies. The application of cultural evolution mechanisms may act as a key element for implementing future societal acceptance of responsible individual consumption and a trigger for the self-transformation of the economy. We will discuss what kind of policies can be used in future to channel our consumption preferences and build up an economic “presents for the future” scenario that will go beyond existing policy tools. An already established tool in behavioral economics that provides an elegant, cheap and often effective measure to promote green behavior is “green nudging.” However, it comes at the cost of being perceived as paternalistic and non-transparent. In addition, nudging requires the alteration of a very specific choice architecture for every single consumption decision scenario and is therefore limited in its scope of application and – most importantly – long-term effectiveness. Here we offer a more general behavioral approach for future environmental policy. We argue that preference change for consumption can be induced by policy makers using tools drawn from cultural evolution. We develop concrete scenarios for policy makers to induce pro-environmental preferences within consumer populations. We argue that our approach is likely to induce alteration of existing and the establishment of new consumption patterns on a much larger scale than nudging and will be more successful in establishing permanent future effects.
This paper relates cultural distance and governance structures. We suggest a model of cultural evolution that captures the idiosyncratic socialization dynamics taking place in groups of communicating and interacting agents. Based on these processes, cultural distance within and between groups or organizational units develops. Transaction cost theorists associate higher cultural distance with higher transaction costs. Therefore, one problem of economic organization is assessing alternative governance structures in terms of the socialization dynamics they enable that entail di erent intraorganizational transaction costs. We assume that transaction can be organized within governance structures that allow transaction cost economizing socialization processes.
This paper aims to explain the emergence and diffusion of novel combinations in Germany. On the one hand, it scrutinizes on the effect of internal technological diversity. On the other hand, it looks at interactions with other actors and assesses whether relatedness to the overall regional knowledge base or rather being related to specific regional actors improves radical inventive activity in German organisations. It is demonstrated that the emergence of radical novelty is positively influenced by an optimal degree of internal diversity as well as relatedness to actors at the technological frontier. However, for this radical novelty to diffuse, rather diverse actors and cognitive proximity to the regional knowledge base is important. The results call for a more fine-grained picture in the relatedness debate and deliver interesting insights for inventive organisations in terms of partner choice and policy-makers for future initiatives.
Decline and break-up of institutionalized cooperation, at all levels, has occurred frequently. Some of its concomitants, such as international migration, have become topical in the globalized world. Aspects of the phenomenon have also become known as failing states. However, the focus in most social sciences has been on institutional emergence and persistence, not collapse. We develop an endogenous explanation of collapsing institutions. Collapse may be an implication of the very economic success of institutionalized cooperation and of increasing system complexity, when cognitive conditions for effective collective decision-making do not proportionately evolve. Moreover, we show that collapse is not a simple logical reverse of emergence. Rather, institutions break up at different factor constellations than the ones prevailing at emergence. We approach endogenous institutional break-up and its asymmetry from various paradigmatic and disciplinary perspectives, employing psychology, anthropology, network analysis, and institutional economics. These perspectives cover individuals, groups, interaction-arenas, populations, and social networks.
Radical innovations are of key importance from an economic point of view since they bear the potential to trigger the emergence of new technological trends and fuel economic prosperity while simultaneously causing far-reaching structural change processes. In this paper we focus on the transfer channels of radical innovations launched by small and medium-sized firms (SMEs). Based on a unique longitudinal dataset covering the observation period 1996 - 2016, we identify and trace back radical innovations of SMEs in the German Biotech in order to analyze the extent to which SMEs themselves or eventually also other organizations in their direct cooperation surrounding benefit from radical innovations in terms of subsequent innovation performance. Results from panel data count models indicate that direct cooperation partners of “radical innovators” generally seem to show higher innovative performance than partners of the control group, i.e. not radical innovating “statistical twin” firms. A more differentiated picture emerges if one considers the geographical and technological proximity of the cooperation partners.
Nowadays environmental and climate issues have brought the topic of bioeconomy to the political agenda around the world. Plant-based bioeconomy (pBE) has a key role in securing sustainable supplies of energy, food and raw materials for increasingly aging and growing societies. However, the technological roots and development path of pBE are far from being fully understood. Accordingly, we seek to contribute to an in-depth understanding of how biotechnology innovations affected the emergence of bioeconomy by exploring the technological field evolution of plant-based patent applications between 1995 and 2015 in Germany. We employ patent citation data and conduct forward citation analysis to trace technological trajectories within plant-based biotechnology. We extend previous work by combing patent-based citation analysis with text-mining approach. Main path analysis allows the identification of main players within plant-based biotechnology over time. Our explorations reveal dominant and also peripheral technologies within the sphere of plant-based applications and provide us in this way with a more comprehensive understanding of the field´s technological evolution. Our findings suggest a transition from basic biotechnological research towards more sustainability- and medicine-related technological orientation in the field.
This paper focuses on the question whether or not a reduction of the knowledge barrier is good for welfare. Based on a dynamic monopoly setting with simultaneous investment decisions in process as well as in product Research & Development (R&D), we show that a reduction of the knowledge barrier has ambiguous welfare consequences: Due to a lower knowledge barrier, product quality and welfare increase in the short-run. However, this may not necessarily be the case in the long-run. One reason is that a positive long-lasting knowledge barrier shock triggers the monopolist to sub-optimally lower its product R&D investments today and in the future at the cost of future product quality. This in turn may reduce welfare. Accordingly, to realize the first-best level of product quality, the long-run optimal R&D subsidy rate for product innovations increase with a reduction of the knowledge barrier.
The tendency of industries to cluster in some areas and possible effects of this regional clustering have fascinated researchers from multiple disciplines alike. Driven by the success of some clusters, as for example Silicon Valley, the concept has also become quite popular among politicians. Despite the already substantial financial support, a positive cluster effect on the success of the corresponding companies has not been consistently asserted yet. In this context, recently it has been accentuated to further examine the role of contextual influences that might explain the ambiguous effect of clusters on firm´s success. The aim of this paper is therefore to investigate the alleged effect of clusters on firm performance and the moderating influence of the specific context by conducting a meta-analysis of the relevant empirical literature. Therefor four different performance variables from four separate publication databases are considered. After the selection and exclusion process, the final sample of the meta-analysis consists of 168 empirical studies. The statistical integration of the corresponding results of these empirical studies indicate that there exists relatively weak evidence for a pure firm-specific cluster effect. Instead, it can be asserted that several variables from different levels of analysis directly or interactively moderate the relationship between clusters and firm´s success. For example, it is pointed out that the probability for a positive firm-specific cluster effect is significantly higher in high-tech industries as well as for small and medium-sized companies. Depending on the specific conditions, clusters can therefore be blessing and curse at the same time.
This paper deals with the question as to whether technology can lessen the problem of scarce resources. Focusing on fossil and biomass materials as important resources for production and consumption, the paper empirically investigates whether environmental innovations reduce the material usage in European economies. A dynamic panel model is employed to estimate the effect of environmental innovations on the use of fossil and biomass materials. It shows that there is no continuously mitigating effect of green technology. For biomass, no significant technology effects are found. Fossil materials are saved by innovations in recycling as well as by new production and processing technologies, but not by all categories of relevant green technology.
We investigate the question on how to use a non-renewable resources efficiently in the presence of a minimum subsistence level of consumption. In our model, households are characterized by Stone-Geary preferences and output is Cobb-Douglas using physical and human capital as well as resources as input factors. This setup gives rise to a six dimensional dynamic system with three control and three state variables. Despite this complexity, it is shown that a closed form solution exists in terms of the Gaussian hypergeometric function. The closed form solution allows us to calibrate the model to the situation of 108 countries using data from the World Bank on countries’ endowments with physical capital and natural resources. We are able to quantify the implications of observed capital stocks for the growth perspective of each country. In particular, we analyze whether a level of subsistence consumption equivalent to the World Bank’s poverty lines can be accomplished. Our calibration results also shed some light on what has been termed the “resource curse”.
This paper discusses automation embedded into a standard growth model without exogenous growth when investment decisions for physical and automation capital are irreversible. The imposed non-negativity constraints on physical and automation capital induces an imbalance effect between the growth rate of output and the fraction between physical and automation capital. The paper shows that this imbalance effect leads (i) to transitional dynamics off the steady state while (ii) retaining per-petual growth of the AK style in the steady state without exogenous technological progress. We also show that the resulting transition path does not have to be on the saddle path of the system without the nonnegativity constraints.
This paper investigates the response of CO2 emissions to the business cycle for the U.S. on a monthly basis between 1973-2015. Using a rolling-regression approach, we find that the emissions elasticity with respect to GDP is not constant over time, irrespective which filtering method, such as the Hodrick-Prescott, the Baxter-King, the Christiano-Fitzgerald or the Butterworth filter has been employed. In order to check whether or not emissions react differently during normal and recession times, next, we employ a Markov-switching approach. We find, first, that emissions are significantly more elastic during recessions than in normal times. Second, depending on the filtering method, we also obtain parameter estimates of the emissions elasticity above one in recession times and below one in normal times. The results are also robust against including monetary policy also in times of the zero lower bound. Thus, environmental policy instruments not turning out to be sub-optimal should account for this asymmetric response of emissions due to changes in GDP.
Humans are an ecologically extremely successful species. Underlying this achievement is our evolved unique adaptation for culture. Moreover, humans’ cultural capacity initiated a process of gene-culture coevolution that lead to a plethora of behavioral and cognitive dispositions on which cultural adaptation to challenging environments via cultural evolution rests. These characteristics of human cognition are highly relevant to any discipline dealing with human behavior. This article presents these outcomes of human phylogeny and discusses this naturalistic perspective’s implications for (evolutionary) economics. Moreover, some fruitful applications of cultural evolution theory to the explanation of economic phenomena are provided.