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The physical limits to economic growth by R&D funded innovation Bernard C. Beaudreau a, H. Douglas Lightfoot b Cite https://doi.org/10.1016/j.energy.2015.01.118Get rights and content Abstract For over three decades, worldwide R&D expenditure has risen steadily, reaching $1.3 trillion in 2011. Underlying this unprecedented growth is a deeply-held belief that R&D is a prime mover of economic growth. Ironically, despite three decades of massive R&D expenditure, growth levels have remained substantially lower than that of the immediate post World War II period. This raises important theoretical questions regarding R&D and its impact on growth per se. For example, R&D-growth has been modeled and continues to be modeled as an unbounded set. This has not been inconsequential because it has introduced an upward bias in growth projections as evidenced in the literature. More importantly, are there physically-determined upper limits to R&D-based growth and, if so, what are they? This paper uses the physical sciences to map the physical limits to R&D-based innovation. A consilient model of economic growth is presented and upper bounds for energy efficiency-based growth rates are provided, both for individual energy sectors and globally. We find that with economic growth by innovation limited by physical conditions, increasing the rate of economic growth can only come through increasing the rate of energy consumption. Introduction Virtually ignored in economics for most of the 20th century, research and development (R&D) literally took off in the 1980s. R&D and innovation took center stage in the debate over economic growth; theoretically, empirically and policy-wise. Building on the pioneering work of Denison 1
and Griliches [1], [2] and the writings of Moses Abramovitz1 the growth literature virtually exploded with articles about the myriad aspects of innovation. Governments heeded the call and re-examined incentives, industry structure and corporate taxation. Now, some three decades later, massive spending on R&D (Table 1) growth has not returned GDP2 growth to the levels in the 1950–1970s. Why have record levels of R&D failed to jump-start growth [3]? This paper is an attempt to provide answers to this and other R&D-growth related questions. Our starting point is the physical R&D-growth boundary, defined as the upper limits of R&D derived economic growth based on the underlying physics. By the latter, it should be understood as the fundamental laws of classical mechanics and thermodynamics as applied to material processes. Among the problems associated with the R&D growth model is its unbounded nature. For example, the technology scalar in the Solow-Swan growth model [4], [5] is theoretically unbounded from above, which is in clear violation of the first and second laws of thermodynamics and of matter. In other words, R&D cannot create matter or energy and cannot violate the laws of physics [6], [7], [8]. We re-examine the physical R&D-growth boundary using the energyorganization (EO) approach to modeling material processes. According to this approach, wealth is defined as an increasing function of broadlydefined energy and organization. Included in organization are machinery and equipment, supervision, information, and management. Linking the two is the concept of second-law efficiency, or simply put, energy efficiency. Wealth, or output, growth is bounded from above by 100% efficiency because work output cannot exceed energy input. This is followed by estimated sector-specific and aggregate levels of energy efficiency, as well as projections for future growth over extended time horizons. For purposes of this paper we assume maximum energy efficiency is achieved by 2100. In fact, today, many processes and industries are already very close to maximum energy efficiency. We use increases in energy efficiency because it is a well-known and understood terminology. However, we immediately convert an energy efficiency increase to a decrease in energy intensity. This is because energy efficiency has no defined units whereas energy intensity is measured as energy per unit of output, which can be compared to initial energy intensity.3 For example, in this paper the maximum reduction in energy intensity is used to compare world energy intensities in 1900 and 2100.
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Section snippets The productivity slowdown, policy responses and R&D expenditure The mid-1970s witnessed a marked decline in GDP gross domestic product growth rates in Western industrialized economies as well as in the world economy. For most of the post-World War II (WWII) period up to the mid1970s, economic growth was not only high, but robust. G6 countries could expect growth in the 4–6% range. After the mid-1970s, growth plummeted to just over one percent [9]. These lower growth rates altered the social fabric, a fabric that had been based on rising per-capita wealth. Residual growth and R&D Capital and labor had been front and center in the science of wealth formation throughout the 19th century and information, knowledge and R&D were absent from economic theory [10]. This changed in the postWWII period with the creation of government statistical agencies. If Keynesian-style governments were to fine-tune the economy, they would need detailed knowledge and information about GDP, employment and investment. Typically, in growth accounting exercises today, capital and labor growth The evidence As evidenced by the empirical literature, researchers focused on the relationship between measures of research activity and either TFP or long run patterns of economic growth [12], [13]. TFP is the growth of output that cannot be explained by the growth of traditional inputs such as labor and capital and is termed a “residual”, and often referred to as the Solow residual. Typically, research activity is measured by the level of technical knowledge as by Eqn. (1) where qt is the measure of new Wealth: the underlying physics This section presents an alternative approach to understanding wealth as measured by GDP, one that imposes more structure and limits on the relationship between inputs and outputs. In doing so, we can shed new light on the role of innovation and R&D on material processes and hence aggregate economic growth. We use the E-O (energy-organization) approach to modeling material processes [2]. It models wealth in terms of two universal inputs, namely broadly-defined energy and broadly-defined 3
Estimates of potential increases in energy efficiency, η(t) Currently, there is much interest in improving energy efficiency in applications such as industries [20], specific products [21], [22] and energy security [23]. We examine the aggregate energy efficiency increase from of all sources of energy efficiency increase [24]. We present estimates of η(t) levels and potential rates of growth by sector and for the world economy as a whole. These are based on industry and sector engineering data, and represent “best estimates” of the potential gains in Conclusions In this paper, we examined the question of the physical R&D-Energy Efficiency-Growth boundary. Until now, there were no physical constraints on economic growth based on R&D because R&D growth was, for the most part, assumed to be unbounded. Using basic physics, we examined the physical limits to non-energy consumption-based growth, i.e., the physical limits to energy efficiency. Our conclusions are: 1.
The output of current R&D models of economic growth is not unbounded, but is bounded by the
References (53) R. Ayres et al. Energy efficiency, sustainability and economic growth Energy (2007) L. Guerrini The Solow–Swan model with a bounded population growth rate J Math Econ (Feb. 2006) M. Ladu et al. Is there any relationship between energy and TFP (total factor productivity)? A panel cointegration approach for Italian regions Energy
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(2014) B.-C. Xie et al. Dynamic environmental efficiency evaluation of electric power industries: evidence from OECD (Organization for economic cooperation and Development) and BRIC (Brazil, Russia, India and China) countries Energy (2014) P. Armstrong et al. Improving the energy storage capability of hot water tanks through wall material specification Energy (2014) E. Burman et al. Towards measurement and verification of energy performance under the framework of the European directive for energy performance of buildings Energy (2014) B. Johansson A broadened typology on energy and security Energy (2013) E. Giacone et al. Energy efficiency measurement in industrial processes Energy (2012) M.-C. Chang Energy intensity, target level of energy intensity, and room for improvement in energy intensity: an application to the study of 5
regions in the EU Energy (2014) H.D. Lightfoot Understand the three scales for measuring primary energy and avoid errors Energy (2007) View more references Cited by (12) Multi-objective development path evolution of new energy vehicle policy driven by big data: From the perspective of economic-ecologicalsocial 2023, Applied Energy Show abstract A novel approach for analyzing the effectiveness of the R&D capital for resource conservation: Comparative study on Germany and UK electricity sectors 2020, Energy Policy Citation Excerpt : Table 1 presents the assumed conversion factors of the energy contents to the NREC for different types of energy sources. Considering the non-renewable energy sources (NREC) (Beaudreau and Lightfoot, 2015) avoids the misleading issue of the declining pattern of the overall exergetic efficiency due to the development of renewable capacities in previous studies (such as (Warr and Ayres, 2010)). The temporal fluctuations in the level of the production factors (labor, capital investment, NREC, and R&D investment) and the produced electricity in both countries are presented in Fig. 3 and Fig. 4. Show abstract Technical limits for energy conversion efficiency 2020, Energy Citation Excerpt : 6
Scholars from several fields of energy science and economics have contributed to the discussion on efficiency limits, and these studies can be used to estimate ESP for national and regional energy systems. For example, Beaudreau and Lightfoot [11] estimated the physical limits to energy efficiency growth in the next century that can be achieved through R&D. While, Letchert et al. [12] use a bottom-up model to estimate the maximum possible efficiency gains that could be achieved in major global economies if best available technologies were adopted in all end-use sectors. Show abstract Exploring the potentialities of emergy accounting in studying the limits to growth of urban systems 2018, Ecological Indicators Citation Excerpt : These authors shed doubts about the possibility of environmental sustainability going hand in hand with economic growth, because the later leads to more consumption and thereby to more pressure on natural environment. Trying to answer why increasing and massive spending on research and development (R&D) has not returned a global GDP growth to the levels of 1950–1970, Beaudreau and Lightfoot (2015) stated that R&D alone is not able to restore growth rates to 4–6% per year, because innovation is limited by physical conditions and energy availability. Moreover, in the same way as maximum energy efficiency is limited according to thermodynamic conditions, the area used by a system is also limited. Show abstract What will drive global economic growth in the digital age? 2023, Studies in Nonlinear Dynamics and Econometrics Neural Network Modeling of the Social and Economic, Investment and Innovation Policy of the State 2022, CEUR Workshop Proceedings
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