General purpose technologies in theory,application and controversy: a review

Distinguishing characteristics of General Purpose Technologies (GPTs) are identified and definitions discussed. Our definition includes multipurpose and single-purpose technologies, defining them according to their micro-technological characteristics, not their macro-economic effects. Identifying technologies as GPTs requires recognizing their evolutionary nature, and accepting possible uncertainties concerning marginal cases. Many of the existing ‘tests’ of whether particular technologies are GPTs are based on misunderstandings either of what GPT theory predicts or what such tests can establish. The development of formal GPT theories is outlined, showing that only the early theories predicted the inevitability of GPT-induced showdown and surges. More recent GPT theories, designed to model the characteristics of GPTs, do not imply the necessity of specific macro effects. We show that GPTs can rejuvenate the growth process without causing slowdowns or surges. We conclude that existing criticisms of GPT theory can be resolved and that the concept remains useful for economic theory.     

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.     

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.     

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.     

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.     

ENDOGENOUS CYCLICAL GROWTH WITH A SIGMOIDAL DIFFUSION OF INNOVATIONS

The model we propose in this paper is an extension of the one described in Freeman et al. [Freeman, S., Hong, D. and Peled, D. (1999) Endogenous Cycles and Growth with Indivisible Technological Developments. Review of Economics Dynamics, 2, 403–432]. In our model, we incorporate the process of diffusion of major innovations and analyze macroeconomic effects on consumption, capital and aggregate output. Following Bresnahan and Trajtenberg [Bresnahan, T. and Trajtenberg, M. (1995) General Purpose Technologies: Engines of Growth?. Journal of Econometrics, 65, 83–108.], Helpman [Helpman, E. (ed.) (1998) General Purpose Technologies and Economic Growth. MIT Press] and Lipsey et al. [Lipsey, R.G., Carlaw, K. and Bekar, C. (2005) Economic Transformations: General Purpose Technologies and Long Term Economic Growth. Oxford University Press.] we assimilate major innovations with the emergence of certain GPTs, and we suggest that the diffusion process for these technologies, at a large scale, might follow an S-shaped pattern. The proposed model presents optimum stationary solutions which are cyclical and have a wave dynamic within each cycle. The cycles are characterized by certain co-movements in consumption, R&D investment, capital accumulation and output. Consideration of the innovation diffusion process highlights new aspects of endogenous cycles and long-run growth.     

Learning about match quality and the use of referrals

The firm?s decision to use referrals as a hiring method is studied in a theoretical model of the labor market. The labor market is characterized by search frictions and uncertain quality of the match between a worker and a job. Using referrals increases the arrival rate of applicants and provides more accurate signals regarding a worker?s suitability for the job. Consistent with the data, referred workers are predicted to have higher wage, higher productivity and lower separation rates and these differentials decline with tenure. The model is extended by introducing heterogeneity in firm productivity and allowing the endogenous determination of signal accuracy. High productivity firms are predicted to invest more in increasing signal accuracy and use referrals to a lesser extent.     

ESTIMATING THE IMPACT OF IMMIGRANTS ON THE HOST COUNTRY SOCIAL SECURITY SYSTEM WHEN RETURN MIGRATION IS AN ENDOGENOUS CHOICE*

This article estimates immigrants’ fiscal impact on the German pension insurance and unemployment insurance systems when return migration is an endogenous choice. For this purpose, it develops a dynamic stochastic model of joint return migration and saving decisions and estimates it using longitudinal data on immigrants from five countries. The results indicate that exogenous return migration—which has been the practice of the literature so far—underestimates the state coffers’ net gain substantially; e.g., the unemployment insurance system’s net gain from Turks arriving after age 30 falls by an amount that is roughly equal to their annual earnings at arrival.     

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.     

Stochastic technical change,non-renewable resource and optimal sustainable growth

We develop a stochastic endogenous growth model involving a non-renewable resource, in which innovation arrivals are governed by a non-stationary Poisson process. Using a CRRA analytical example, we characterize the optimal trajectories of the model and analyze the effects of uncertainty in the sense of Rothschild and Stiglitz by computing a mean-preserving spread. We show that increased variability in the innovation process always implies a smaller optimal R&D effort, since this leads to a reduced marginal rate of return. Effects on the other variables of the model may also be unambiguously identified depending upon the relative risk aversion of agents, the social discount rate and the marginal arrival rate of innovations. Finally, we investigate the conditions under which, on average, the economy reaches a sustainable growth path.     

Institutions,human capital,and growth: The institutional mechanism

This paper contributes to the debate on the relationship between human capital, institutions, and economic growth. The paper first develops a micro-foundation model linking institutions to human capital. The advantage of our modeling strategy is that the human capital accumulation function is derived from an endogenous process. The theoretical model shows that improvements in the quality of institutions foster human capital accumulation, decrease income inequality and change the historical development path. The paper uses cross-country panel data from 1965 to 2005 to test some of the model's propositions and finds that deep structures or structural institutions – which are very persistent and rooted on the historical development path of an economy – affect long-term economic performance, while political institutions are uncorrelated with productivity and long-term economic growth. The empirical estimates also show that growth of physical and human capital – instead of levels – determines long-run economic growth.     

The Role of a Firm’s Net Cash Payouts in Leland’s (1994) Model

We study the effects of introducing payouts on corporate debt and optimal capital structure in a structural credit risk model à la Leland (1994) . We find that increasing the payout parameter not only affects the endogenous bankruptcy level, which is decreased, but modifies the magnitude of a change on the endogenous failure level as a consequence of an increase in risk‐free rate, corporate tax rate, riskiness of the firm and coupon payments. This simple analytical framework is able to capture realistic insights about optimal leverage, spreads and default probabilities more in line with historical norms (if compared to Leland’s results) and closer to predictions obtained through more sophisticated models.     

Joining a Queue or Staying Out: Effects of Information Structure and Service Time on Arrival and Staying Out Decisions

We study a class of single-server queueing systems with a finite population size, FIFO queue discipline, and no balking or reneging. In contrast to the predominant assumptions of queueing theory of exogenously determined arrivals and steady state behavior, we investigate queueing systems with endogenously determined arrival times and focus on transient rather than steady state behavior. When arrival times are endogenous, the resulting interactive decision process is modeled as a non-cooperative n-person game with complete information. Assuming discrete strategy spaces, the mixed-strategy equilibrium solution for groups of n = 20 agents is computed using a Markov chain method. Using a 2 × 2 between-subject design (private vs. public information by short vs. long service time), arrival and staying out decisions are presented and compared to the equilibrium predictions. The results indicate that players generate replicable patterns of behavior that are accounted for remarkably well on the aggregate, but not individual, level by the mixed-strategy equilibrium solution unless congestion is unavoidable and information about group behavior is not provided.JEL Classification: C71, C92, D81     

Efficiency, depth and growth: Quantitative implications of finance and growth theory

We develop a parsimonious finance and endogenous growth model with microeconomic frictions in entrepreneurship and a role for credit constraints. We demonstrate that though an efficiency–growth relation will always exist, the efficiency–depth–growth relation may not. This has implications for the connection between the theory and empirics of finance and growth. We go on to ask whether the model can account for some historical trends in growth, financial depth and financial efficiency for the UK over the period 1850–1913. The best model of finance and growth is one that departs from the standard depth–growth link.     

Path Dependence,Endogenous Innovation,and Growth*

The article presents a model of endogenous innovation and growth, in which technological change is path dependent. The historical pattern of technological development plays a central role in determining the pace of future technological change. Path dependence is explained using a distinction between fundamental and secondary knowledge. The economy moves endogenously between periods of drastic and nondrastic innovation. Technological lock‐in is shown to be a special case of path dependence. The model provides a rationale for cycles in technological leadership. This rationale exists in equilibria with positive levels of fundamental research and in a world with no imitation.     

Poverty traps in a frictionless world: The effects of learning and technology assimilation

We study an endogenous growth model of technology assimilation through an adaptive learning process defining the accumulation of technological knowledge among both workers and industrial clusters. The assimilation of new technology and the arrival rate of innovations are both based on the distance from the technological frontier to the current technological development level of the country. We illustrate how, even if technological innovations become immediately available to all countries, and absent educational and institutional frictions among countries, differences in technological development levels allow for the existence of poverty traps leading to the economic stagnation of technological laggards.     

The empirical application of a small open economy model: Greece 1954–81

A small macroeconometric model designed to analyse the major macroeconomic aggregates in the open economy of Greece is presented. The specification of the model is based on the assumptions of the ‘Monetary Approach to the Balance of Payments and Exchange Rate determination’. Also, it contains an Expectations Augmented Phillips Curve and consists of seven equations. The empirical findings suggest that for the period 1954–81, the Greek economy did not behave consisently with the particular theoretical or other persuasion model. However, the empirical model tracks reasonbly well the historical values of the endogenous variables and it captures the cyclical behaviour of the economy. The evidence suggests that monetary policy had no significant influence on output growth with its role being confined on determining the balance of payments. On the contrary, fiscal policy played a dominant role in output determination and prices variation.     

Patience and prosperity

This paper introduces wealth-dependent time preference into a simple model of endogenous growth. The model generates adjustment dynamics in line with the historical facts on savings and economic growth in Europe from the High Middle Ages to today. Along a virtuous cycle of development more wealth leads to more patience, which leads to more savings and further increasing wealth. Savings rates and income growth rates are thus jointly increasing during the process of development until they converge towards constants along a balanced growth path. During the transition to modern growth an economy in which the association of wealth and patience is stronger overtakes an otherwise identical economy and generates temporarily diverging growth rates.     

Forecasting technology costs via the experience curve — Myth or magic?

To further understand the effectiveness of experience curves to forecast technology costs, a statistical analysis using historical data is carried out. Three hypotheses are tested using available datasets that together shed light on the historical ability of experience curves to forecast technology costs. The results indicate that the Single Factor Experience Curve is a useful forecasting model when errors are viewed in their log format. Practitioners should note that due to the convexity of the log curve a mean overestimation of potential cost reductions can arise as values are converted into monetary units. Time is also tested as an explanatory variable, however forecasts made with endogenous learning based on cumulative capacity as used in traditional experience curves are shown to be vastly superior. Furthermore the effectiveness of increasing weights for more recent data is tested using Weighted Least Squares with exponentially increasing weights. This results in forecasts that are less biased, though have increased spread when compared to Ordinary Least Squares.     

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.