Long-term growth driven by a sequence of general purpose technologies

We present a Schumpterian model of endogenous growth with General Purpose Technologies (GPTs) that captures two important historical stylized facts: First, from the beginning of mankind until today GPTs are arriving at an increasing frequency and, second, all GPTs heavily depended on previous technologies. In our model, the arrival of GPTs is endogenous and arises stochastically depending on the currently available applied knowledge stock. This way of endogenizing the arrival of new GPTs allows for a model which is more in tune with the historical reality than the existing GPT models.     

Modeling the diffusion of general purpose technologies in an evolutionary multi-sector framework

General purpose technologies (GPTs) are characterized by their pervasive use in the economy. The introduction of a new GPT (product innovation) as well as increasing productivity within a GPT-sector (as a consequence of process innovations) affect the economy in several ways. First, a new GPT offers the opportunity to produce goods by means of cheaper processes; secondly, technical change within the GPT sector influences productivity gains in related sectors. Also social consequences such as changing wage share, technical unemployment and transitional wage inequality can be observed. Finally, the emergence of a GPT often coincides with output decline, preceding economic growth. This paper introduces a multi-sector diffusion model to study these effects by combining classical economics and replicator-dynamics. Empirical evidence is given by the information and communication technology sector in Denmark and its impact on the economic structure from 1966 to 2007.     

Sustained endogenous growth driven by structured and evolving general purpose technologies

We address two interrelated issues: structured technology and non-stationary equilibrium growth. We do this by modelling multiple, co-existing, non-identical general purpose technologies (GPTs). Three sectors producing pure and applied research and consumption goods, employ different, evolving, technologies. Agents within each sector operate under conditions of Knightian uncertainty and path dependence, employing technologies that differ in specific parameter values. This behaviour produces a non-stationary (non-ergodic) growth process. Important characteristics of structured technology, previously only described historically, are successfully modelled, including co-existing GPTs some of which compete with each other while others complement each other in varying degrees. Because changes in technology are partial causes of, but not contemporaneous with, GDP changes, their separate evolutions can be studied.     

The improvement trajectory of PCR DNA replication and ERP software as general purpose technologies: an exploratory study of ‘anchor technologies’

As an effort to peek into the black box of large-scale general purpose technologies (GPTs) like biotechnology and information technology, we develop the concept of ‘anchor technologies’. An anchor technology is a core technology of a large-scale GPT (‘mega-GPT’) that opens a new era in the development and diffusion of the mega-GPT. We trace the historical evolution of two process-based, yet otherwise very different, anchor technologies: enterprise resource planning (ERP) software within the mega-GPT of information technology and polymerase chain reaction (PCR) DNA replication within the mega-GPT of biotechnology. The case studies reveal the utility of ‘productisation’ as an important means of commercialising innovations in anchor technologies; more generally, the interplay between improvement in process-based technologies and in complementary product-based technologies provides insight into how ERP and PCR were able to sustain a path of continued improvement within their respective mega-GPT.     

The dynamic effects of general purpose technologies on Schumpeterian growth

General purpose technologies (GPTs) are drastic innovations characterized by pervasiveness in use and innovational complementarities. The dynamic effects of a GPT are analyzed within a quality-ladders model of scale-invariant Schumpeterian growth. The diffusion path of a GPT across a continuum of industries is governed by S-curve dynamics. The model generates a unique, saddle-path long-run equilibrium. Along the transition path, the measure of industries that adopt the new GPT increases, consumption per capita falls, and the interest rate rises. The growth rate of the stock market depends negatively on the rate of GPT diffusion and the magnitude of the GPT-ridden R&D productivity gains; and positively on the rate of population growth. It also follows a U-shaped path during the diffusion process of the new GPT. Finally, the model generates transitional growth cycles of per capita GNP.JEL Classification: E3, O3, O4I would like to thank Elias Dinopoulos for encouragement, and for constructive comments and suggestions. I would also like to thank David Figlio, Douglas Waldo, Steven Slutsky and participants in the 9th Biennial Congress of the International Schumpeter Society for useful discussions and suggestions. Any remaining errors are my own responsibility.     

Exploring outward FDI and the choice of destination: evidence from Swedish firm-level data

Using Swedish firm-level data on all firms and their affiliates abroad, we investigate what observable firm and country characteristics affect the size of an affiliate in a particular destination. We employ the richness of the data to investigate the importance of destination country factors in explaining firm outward FDI activities and distinguish between the factors that affect such activities in manufacturing versus services firms as well as vertical versus horizontal investments. Our results lend support to existing theories of multinational activity of manufacturing but not services firms. We also find observable differences between vertical and horizontal manufacturing firms that are not always explained by theory.     

Adjusting to a New Technology: Experience and Training

How does the economy react to the arrival of a new major technology? The existing literature on general-purpose technologies (GPTs) has studied the role that mechanisms like secondary innovations, diffusion, and learning by firms play in the adjustment process. By contrast, we focus on a new mechanism: the interplay between technological change and two types of human capital—technology-specific experience and education. We show that technological change that requires more education and training, like computerization, necessarily produces an initial slowdown. On the other hand, technological change that lowers the training requirements, like the move from the artisan shop to the factory, can produce either a bust or a boom. We identify three key properties that determine the outcome: (1) the productivity of inexperienced workers, (2) the speed with which experience raises productivity, and (3) the level of general skills required to operate the new technology.     

STRUCTURAL CHANGE AND THE GROWTH OF INDUSTRIAL SECTORS: EMPIRICAL TEST OF A GPT MODEL

This paper investigates the empirical relevance of a model of structural change and the growth of industrial sectors. The model analyzes the process of diffusion of general‐purpose technologies (GPTs) and how this affects the dynamic performance of manufacturing and service industries. The empirical analysis studies the dynamics and the determinants of labor productivity growth for a large number of sectors in 18 OECD countries over the period 1970–2005. The results of dynamic panel data and cross‐sectional analysis provide support for the empirical validity of the model. Industries that are close to the core of ICT‐related GPTs are characterized by greater innovative capabilities and have recently experienced a more dynamic performance. Relatedly, countries that have been able to shift their industrial structure toward these high‐opportunity manufacturing and service industries have grown more rapidly.     

Does a cap on the carbon price have to be a cap on green investments?

Policy makers and economists are discussing a regulatory ceiling for carbon prices, acting as a “safety valve” for the protection of regulated businesses from unexpected price surges. While the pros and cons of such a regulatory feature are widely discussed in the literature, the optimal design of such a cap and the attendant economic and environmental consequences have yet to be subjected to quantitative analyses. We employ a Monte Carlo simulation/dynamic programming approach to investigate the impact of different carbon price cap designs on an individual firm in the energy generation industry. Specifically, we model the firm’s choice between a pulverized coal combustion plant and a combined cycle gas turbine plant, a large hydropower plant, a solid biomass plant and an on-shore wind farm. Our results show that the effects of a maximum carbon price set by the regulator is largely independent of its exact characteristics, albeit not of its level. A higher cap favors low-carbon technologies in general. However, due to differences in their cost structures, a price cap has different impacts on the relative attractiveness of the specific alternative technologies investigated.     

Policy dilemma of innovation: An info-gap approach

New ideas or technologies are often advocated because of their purported improvements on existing methods. However, what is new is usually less well-known and less widely tested than what is old. New methods may entail greater unknown dangers as well as greater potential advantages. The policy maker who must choose between innovation and convention faces a dilemma of innovation. We present a methodology, based on info-gap robustness, to deal with the innovation dilemma. We illustrate the approach by examining the policy decisions for managing the light brown apple moth in California.     

Preference Anomalies,Preference Elicitation and the Discovered Preference Hypothesis

There is wide-ranging evidence, much of it deriving from economics experiments, of ‘anomalies’ in behaviour that challenge standard preference theories. This paper explores the implications of these anomalies for preference elicitation methods. Because methods that are used to inform public policy, such as contingent valuation, are based on standard preference theories, their validity may be called into question by the anomaly data. However, on a new interpretation, these anomalies do not contradict standard theory but are errors in stated preference that can be expected to disappear as people become more experienced in relevant decision environments. We explore the evidence for this interpretation and what implications follow for preference elicitation methodology. JEL classifications: C91, D01, D60, D81, D83, H40     

Financial Contracting Theory Meets the Real World: An Empirical Analysis of Venture Capital Contracts

We compare the characteristics of real-world financial contracts to their counterparts in financial contracting theory. We do so by studying the actual contracts between venture capitalists (VCs) and entrepreneurs. The distinguishing characteristic of VC financings is that they allow VCs to separately allocate cash flow rights, board rights, voting rights, liquidation rights, and other control rights. We describe and measure these rights. We then interpret our results in relation to existing financial contracting theories. We also describe the interrelation and the evolution across financing rounds of the different rights.     

The growth of knowledge: Testing a theory of scientific revolutions with a formal model

Modern theories of science emphasize scientific revolutions rather than the traditional cumulative view of scientific progress. Thomas Kuhn, in particular, has formulated a theory of science based on the lifecycle of paradigms. Though Kuhn's theory is attractive, no calculus is offered by which the theory can be tested. This study tests the dynamic consistency of Kuhn's theory by formalizing the theory and testing it with a computer simulation model. The model plays the roles of the actors, tracing out the consequences of their day-to-day actions. Sensitivity tests are used to explore the importance of various hypotheses. Results show the theory to be dynamically consistent: The lifecycle of paradigms described by Kuhn can be accounted for by Kuhn's theory. Kuhn's theory thus passes a test to which few other theories of science have been subjected. The study shows how modeling can provide a method for testing theories even when those theories are stated entirely in qualitative terms, at a high level of abstraction, and in a context divorced from explicit dynamic analysis.     

Consumers as Co-developers: Learning and Innovation Outside the Firm

This study describes a process in which a firm relies on an external consumer community for innovation. While it has been recognized that users may sometimes innovate, little is known about what commercial firms can do to motivate and capture such innovations and their related benefits. We contribute to strategy literature by suggesting that learning and innovation efforts from which a firm may benefit need not necessarily be located within the organization, but may well reside in the consumer environment. We also contribute to the existing theory on "user- driven innovation' by showing what firms purposively can do to generate consumer innovation efforts. An explorative case study shows that consumer innovation can be structured, motivated, and partly organized by a commercial firm that organizes the infrastructure for consumers' interactive learning in a public online domain.     

平台到底是什么——基于分工与协调视角

以技术管理、战略管理、产业组织和生态系统为代表的研究视角,对平台本质的限制性理解直接导致学术界对平台到底是什么存在异议,将平台本质限制性理解为特定情境的平台功能是导致上述问题的根本原因。突破现有研究视角局限,引入分工与协调视角,对平台本质特征进行阐释是解决这个问题最好方案。在梳理平台本质特征的基础上,认为平台是一个以共享界面和接口为黏合剂的互补性自治主体进行分工与协调的元组织。通过解决平台本质研究中存在的争议与问题,揭示平台到底是什么,进而深化对平台的理解及在现实中的应用。     

Consumers as Co-developers: Learning and Innovation Outside the Firm

This study describes a process in which a firm relies on an external consumer community for innovation. While it has been recognized that users may sometimes innovate, little is known about what commercial firms can do to motivate and capture such innovations and their related benifits. We contribute to strategy literature by suggesting that learning and innovation efforts from which a firm may benifit need not necessarily be located within the organization, but may well reside in the consumer environment. We also contribute to the existing theory on ‘user-driven innovation’ by showing what firms purposively can do to generate consumer innovation efforts. An explorative case study shows that consumer innovation can be structured, motivated, and partly organized by a commercial firm that organizes the infrastructure for consumers’ interactive learning in a public online domain.     

Expected utility theory and prospect theory: one wedding and a decent funeral

Choice behavior is typically evaluated by assuming that the data is generated by one latent decision-making process or another. What if there are two (or more) latent decision-making processes generating the observed choices? Some choices might then be better characterized as being generated by one process, and other choices by the other process. A finite mixture model can be used to estimate the parameters of each decision process while simultaneously estimating the probability that each process applies to the sample. We consider the canonical case of lottery choices in a laboratory experiment and assume that the data is generated by expected utility theory and prospect theory decision rules. We jointly estimate the parameters of each theory as well as the fraction of choices characterized by each. The methodology provides the wedding invitation, and the data consummates the ceremony followed by a decent funeral for the representative agent model that assumes only one type of decision process. The evidence suggests support for each theory, and goes further to identify under what demographic domains one can expect to see one theory perform better than the other. We therefore propose a reconciliation of the debate over two of the dominant theories of choice under risk, at least for the tasks and samples we consider. The methodology is broadly applicable to a range of debates over competing theories generated by experimental and non-experimental data.     

ICTs and time-span in technical efficiency gains. A stochastic frontier approach over a panel of Italian manufacturing firms

In this paper, in contrast to much of the existing literature dealing with the impact of information and communication technologies (ICTs) on labour productivity, we assess the relationship between ICT investments and technical efficiency (TE) using a stochastic frontier approach. We utilize a large panel dataset of Italian manufacturing firms over the period 1995–2006 and confirm the findings of the previous work on ICT and productivity. In addition, we test to what extent ICT investments influence the gap between firms and the production frontier; that is, how adoption of ICT influences the narrowing of the said gap. We also test the duration of the effects of adopting ICT on technical efficiency. Finally, our results indicate that ICT returns on TE are influenced by certain firm characteristics, most of which idiosyncratic, such as management practices, labour organization, research and development.     

Systems of innovation and innovation ecosystems: a literature review in search of complementarities

This paper aims to clarify to what extent the emerging theory of innovation ecosystems (IE) and the theory of systems of innovation (SI) are complementary and then identify how its communities could benefit from cross-fertilization. We performed a critical literature review of both topics using meta-synthesis as method to identify, analyze and compare the two theories. Using a framework, this paper explores the elements belonging to each theory’s domain, in order to identify the key factors necessary to compare the two theories. The results of this analysis show that both theories involve the assessment of three key aspects: the understanding of innovation activities, the role of the agents involved, and the interaction and resulting networks among them. A similarity was found showing that these two different theories are applications of System Thinking approach. Another finding, which has not been mentioned in previous research on the topic, is that the construction of the initial concepts of the IE theory was originally rooted in several SI elements. Finally, we found key factors that may be the cross-fertilization link between the two communities that represent each theory.