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This paper serves as another complementary link in a chain of a rather limited number of investigations in the R&D-innovation-productivity relationship within service industries. Innovation has been found to be a major contributor to productivity growth in manufacturing. In this paper, the importance of innovation is explored by comparing manufacturing and service firms in a sample of knowledge intensive industries. In particular, we intend to find evidence on the following two issues. First, is there any evidence that the reported weak rate of productivity growth in knowledge intensive services can be explained by a low propensity to be innovative? Second, is it possible that knowledge-intensive service firms are less efficient in deriving benefits from innovation than knowledge-intensive manufacturing firms? Empirical results based on innovation survey data indicate a surprising similarity in innovation performance between the two categories of firms.

Schumpeterian development is characterized by the simultaneous interplay of growth and qualitative transformations of the economic system. At the sectoral level, such qualitative transformations become manifest as variations in the sectoral composition of production. Following the implementation of Harberger’s method of visualizing the impact of differential productivity growth, dynamic panel estimations are applied to a standard growth model modified to include specific structural variables for both the manufacturing and the services sectors. Covering 28 countries over the period between 1990 and 2000, the results give empirical substance to the evolutionary emphasis on Schumpeterian development as opposed to mere aggregate growth.

In this paper, we present an agent-based, evolutionary, model which formalizes from the bottom up individual behaviors and interactions in both product and labor markets. We describe vacancy and wage setting, matching and bargaining, demand and price formation as endogenous processes. Firms enjoy labor productivity improvements and are selected in the product market. Simulations show that: (i) the model is able robustly to reproduce Beveridge, Wage and Okun curves; (ii) Okun coefficients greater than one emerge even if individual firms employ linear technologies; (iii) changes in institutional, behavioral, and technological parameters induce statistically detectable shifts in Okun and Beveridge curves.

The aim of this paper is to investigate cross-country patterns of economic divergence in an evolutionary perspective. We propose a simple open economy evolutionary model of growth where the growth variables of each country are microfounded on the dynamics of national firms. The model finds its antecedents in some of the evolutionary models of economic growth developed over the past years. We claim that evolutionary models are able to account for persistent differentiation in the growth performances of countries as a generic property. In fact, the model proposed here does so despite its quite simplified structure.

This contribution starts from today’s definitions of innovation indicators and traces their evolution back over the past 150 years. It is divided into a descriptive and an econometric part. The German innovation system has generally been very stable, even though it witnessed several political changes over the past century. This allows a comparison of the period 1850–1913 with 1951–1999. In the first period, the overall empirical results indicate a linear innovation relation between student numbers as well as public science expenditure, the number of patents granted, and economic demand. However, the second period suggests a different logic in the innovation process: demand drives total R&D expenditure, while patent output does not follow demand. The real domestic product does not seem to depend strongly on innovation activities.

The aim of this paper is to describe the nonlinear dynamism of innovation and to clarify the role of innovation for economic development in terms of Kondratiev business cycles, especially the causal relation of the bubble economy and depressions with innovations. Any paradigm of technological innovation develops within a definite time span reaching maturity. This nonlinear nature clarifies many characteristic features of innovation. Schumpeter’s innovation theory on business cycles is examined through this dynamism. Trunk innovation is defined as that which plays a decisive role in building infrastructures and inducing subsequent innovations. Every innovation has its own technological development period just before the innovation diffusion. The emergence of new markets can be estimated by chasing the ongoing technologies.

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 -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 -shaped path during the diffusion process of the new GPT. Finally, the model generates transitional growth cycles of per capita GNP.