Representation of Technological Change: Some Economic Approaches

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Representation of Technological Change Some
Economic Approaches
Jim Turnure Principal, Energy Group ICF
Consulting ORNL Conference on Estimating the
Benefits of Government-Sponsored Energy RD
Arlington, VA
March 4, 2002
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Outline

• I. Overview
• II. NREL Research Task Process and Methodology
• Purpose of Study
• Scope and Limitations
• Research Methodology
• III. Summary of Approaches to Technological
  Representation
• Capital Investment and Growth Models
• Option Value and Principal-Agent Models
• Spillover Effects and Network Models
• Sidebar Top-Down vs. Bottom-Up Models
• Discussion

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I. Overview
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Baseline Estimation is a Critical Step in RD
Benefit Assessment

• RD investment is intended to advance
  technological change, and to improve indicators
  of technological change
• In order to assess the impact of RD investment,
  it is necessary to understand and measure how
  technological change would develop in the absence
  of specific RD investments
• Baseline estimation cannot occur in a vacuum it
  must be carried out in a robust analytic
  framework. In turn, such analytic frameworks
  need theoretical foundations and specific
  premises regarding how the processes of
  innovation and technological change operate in
  the economy
• The purpose of this presentation is to outline
  major theoretical approaches that have developed
  in the field of economics, partly based on a
  literature survey conducted for the National
  Renewable Energy Laboratory (NREL).

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II. NREL Research Task Process and Methodology
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Purpose of Study

• NREL required a thorough survey of the major
  economics literature in order to develop the
  knowledge base on the role of technological
  change in economic growth.
• The intent of the research task was to conduct a
  literature survey, select key papers from the
  survey results, and summarize them in a readily
  usable format. This allows for rapid access to
  the underlying literature base.
• The study is one of a number of starting points
  for RD benefit estimation, which in being
  reevaluated by many organizations partly in
  response to the requirements of the Governmental
  Performance and Results Act (GPRA).

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Scope and Limitations

• This literature review focused primarily on major
  economics journals
• American Economic Review
• Journal of Economic Perspectives
• Journal of Economic Literature
• Economic Journal
• Journal of Policy Analysis
• Journal of Economic and Environmental Management
• Resource and Energy Economics
• Energy Journal
• Another example of meta-data that can be useful
  in this context is The Modern History of Energy
  Conservation An Overview for information
  Professionals by Donald R. Wulfinghoff. This
  document explains major information sources and
  their relative strengths and weaknesses,
  encompassing dedicated energy efficiency
  journals, trade and advocacy sources.

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Research Methodology

• ICF Consultings professional library and
  research staff carried out the initial phase of
  the literature review.
• The Econolit on-line data service was searched
  using keywords such as Coase Theorem,
  Technology, Research and Development and
  Market Barriers.
• The initial search resulted in a citation list of
  over 300 candidate articles. This initial
  bibliography was narrowed to approximately 90
  relevant cites, and these were then collected
  from university libraries and other sources.
• Relevant articles were sorted into major
  categories and reviewed key articles in each
  category were summarized for the draft report.

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III. Summary of Approaches to Technological
Representation
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Schools of Economics

• Economic theory has advanced along a number of
  fronts, forming a series of theoretical
  approaches that can be termed competing schools
  of thought.
• Understanding these competing schools of thought
  is a useful starting point for developing
  analytic frameworks and how technological change
  should be represented in baselines for RD
  benefits measurement.
• The themes outlined in this presentation are
  meant to be suggestive rather than definitive.
  Other categorizations can be equally useful the
  intent here is to establish a starting point for
  discussion and a guide to more information.

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Capital Investment and Growth Models (I)

• By the 1950s growth theory had assumed a dominant
  role in macroeconomics. Key contributions were
  made by Arrow, Samuelson, and Solow.
• During this period robust quantitative models
  were developed including general equilibrium
  models and optimal growth models. More detailed
  work on economic structure and the availability
  of measured data through national governments
  made more sophisticated arguments about the
  determinants of economic growth possible.
• The dynamic of technology and productivity
  improvement is critical in economic growth.
  Other determinants of growth such as population
  and natural resources depend on physical stocks
  that can increase, but technological advances can
  not only increase in a simple incremental
  fashion, but also multiply in ways that allow for
  much faster growth in the overall economy.

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Capital Investment and Growth Models (II)

• Solow (1956 1957) examined how more flexible
  production functions, including a technical
  change term, worked in theory, while noting that
  he was using technical change as a shorthand
  expression for any kind of shift in the
  production function emphasis in original.
  Solow demonstrated the importance of improvements
  in productivity, including improvements resulting
  from technological change.
• Arrow (1962) posited endogenous technical
  improvement as a function of experience, making
  the observation that it is not simply the passage
  of time that results in technical change.
  Learning by doing had been observed in
  industrial settings and Arrow formalizes this
  relationship. In this model technical change is
  a function of producing new capital equipment.
• Mansfield (1961) introduced an early model for
  the firms technology adoption decision. In this
  model the rate of adoption depends on 1) the
  proportion of related firms already using an
  innovation (because of the reduced risk from
  others experience) 2) the estimated
  profitability of using the innovation 3) the
  cost of adoption and 4) inter-industry variations
  in general propensities for adopting innovations.
  

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Capital Investment and Growth Models (III)

• Using an analytic framework based on the concepts
  advanced in this tradition will generally lead to
  a macroeconomic or industry-level model and to
  very broad, aggregate indicators of technological
  change.
• Most models in this tradition would begin with
  aggregate productivity functions using some
  variant of the capital-labor-materials (KLM) or
  capital-labor-energy-materials (KLEM)
  specification. These production functions define
  the available production possibilities and can be
  used to estimate the optimal mix of inputs to
  production.
• Productivity improvements can be though of as a
  wild card multiplier for components of the
  productivity functions. Some theories treat all
  productivity improvements together as a single
  term while others attempt to distinguish multiple
  sources of productivity improvement such as
  technological change.
• While very large RD benefits (operating through
  the multiplier on production functions) are often
  estimated using this approach, the level of
  aggregation makes program-specific assessments
  difficult.

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Option Value and Principal-Agent Models (I)

• Coase (1960) considered the welfare tradeoffs
  introduced by entities whose economic activities
  cause harm to others, but who would in turn be
  harmed if their activities were limited. When
  transaction costs are present, the legal
  allocation of property rights can affect the
  efficiency outcome as well as the equity outcome.
  In such cases government intervention can raise
  total production and efficiency, particularly if
  large numbers of actors are involved.
• Williamson (1979) introduced more specific
  concepts that apply to transaction costs and
  offered a framework in which the most economical
  structure for a given transaction can be
  evaluated. He defined three relevant attributes
  of transactions uncertainty, frequency of
  exchange, and the degree to which investments are
  transaction-specific.
• Dybvig and Spratt (1983) treated the benefits of
  adopting innovation or standards as a positive
  externality, i.e. a public good, showing that
  improvements in outcomes (Pareto optimality) will
  generally be available if government intervenes
  to encourage innovation. The degree of such
  sub-optimal outcomes depends on the private cost
  of the innovation and the amount of social
  benefit that can be gained.

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Option Value and Principal-Agent Models (II)

• The market for lemons is first identified by
  Akerlof (1970) as an effect of incomplete
  information in the marketplace. The information
  contained in market prices is often an average
  that does not accurately reflect product quality.
  As a result, there is an incentive for producers
  to offer products of lower quality and withhold
  products of higher quality. The impact of this
  type of imperfect information is to restrict the
  availability of consumer products based on an
  insufficiently detailed pricing system.
• Principal-agent information asymmetry was first
  studied by Aumann and Maschler for the US Arms
  Control and Disarmament Agency in the mid-1960s.
  Extensions of this approach include Maskin and
  Tirole (1990), who examined the problem of
  imperfect information and conclude that
  inefficiency will generically result when agents
  do not have the full set of information
  available. The lack of complete information is
  equivalent to a form of irrationality on the part
  of agents which restricts their ability to arrive
  at the efficient (Pareto-optimal) arrangement.

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Option Value and Principal-Agent Models (III)

• Establishing an analytic framework using this
  approach will generally lead to a focus on the
  role of information, especially market pricing
  and consumers ability to evaluate relevant
  product features.
• Quantitative estimation of information asymmetry
  usually occurs on an industry or product-specific
  level, leading to indicators of the rate of
  diffusion of new technologies on a similar basis.
  This is an intermediate level of aggregation
  (relative to more disaggregate firm-level or
  transaction-specific indicators).
• Specific models estimate the benefits of more
  rapid technology diffusion in different ways. In
  general these models require assumptions about
  the value of product quality to consumers.
• RD benefit estimates using these concepts will
  be program-specific, with an emphasis on product
  quality and the deployment of technology. These
  are not always the focus of particular RD
  programs, so these are not always the most useful
  measures. In addition these models can be so
  specific to a single product market that they
  raise compatibility issues vis-à-vis other
  benefit estimates.

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Spillover Effects and Network Models (I)

• Based initially on studies of the
  telecommunications industry, spillovers and
  network effects were more broadly defined by Katz
  and Shapiro (1986). They extend the concept
  (consumer benefits of product use as an
  increasing function of other consumers use of
  compatible products) to industries without
  physical network characteristics. These include
  information technology and certain consumer
  goods, such as video cassettes and durable goods
  requiring specialized services.
• Pepall (1992) developed a model of strategic
  product choice when consumer preferences combine
  both vertical and horizontal product
  differentiation. In such cases, the first mover
  advantage for producers is maximized when product
  differentiation is limited by preferences rather
  than technology (termed niche markets). As
  more consumers participate in the relevant
  market, follower firms offering a range of
  competing products increase consumer choices and
  lead to improved market benefits.
• Godoe (2000) advanced a linkage between
  industries RD intensity and their ability to
  create both incremental innovations and radical
  innovations. In this model institutional
  capacity for coordination, direction and
  leadership can anticipate and internalize the
  producer incentives offered by spillovers.

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Spillover Effects and Network Models (II)

• Analytic frameworks based on spillover effects
  and network characteristics focus on the returns
  to RD and how specific firms react to these
  incentives. The emphasis is on groups of
  competing technologies within a particular
  market.
• Network effects are important for consumers
  because their expectations about future product
  compatibility will influence their decisions
  about adopting current technologies.
• Many models using this approach are concerned
  with strategic behavior and employ techniques
  from game theory, such as Cournot equilibrium, in
  order to specify market structure and strategic
  choices. Externalities arise when potential
  first mover firms lack the incentive to conduct
  RD due to risks from follower firms. Public RD
  investment can alter the incentives to private
  RD investment.
• RD benefits estimated using this approach will
  focus on the effect of specific innovations on
  the full range of compatible products, including
  the chances for spillovers that improve the
  diffusion of compatible technologies. Such
  measures will be program-specific but are only
  useful when network characteristics apply.

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Sidebar Top-Down vs. Bottom-Up Models

• Baseline estimation of technological change using
  computer simulation modeling has been an
  important element of research into the costs of
  policy responses to climate change. Some key
  references include Weyant et al (1990) and the
  IPCC Technical Assessment of 1995. These sources
  consider the top-down vs. bottom-up debate
  explicitly.
• Top-down models are associated with
  macroeconomics and share the characteristics of
  growth theory approaches as discussed earlier in
  this presentation. Bottom-up modeling draws on
  optimization techniques largely drawn from
  operations research, placing most of the
  literature outside the research developed in this
  study.
• Optimization modeling is often used for electric
  power systems, because of the interconnected
  nature of the transmission grid, prevalence of
  centralized dispatch for generation, relatively
  small number of decision agents, and high quality
  of data.
• Integration of both approaches may be appropriate
  for thorough and consistent RD benefit
  assessment, but is resource-intensive for
  individual programs.