How well does Learning-by-doing Explain Cost Reductions in a Carbon-free Energy Technology?

The incorporation of experience curves has enhanced the treatment of technological change in models used to evaluate the cost of climate and energy policies. However, the set of activities that experience curves are assumed to capture is much broader than the set that can be characterized by learning-by-doing, the primary connection between experience curves and economic theory. How accurately do experience curves describe observed technological change? This study examines the case of photovoltaics (PV), a potentially important climate stabilization technology with robust technology dynamics. Empirical data are assembled to populate a simple engineering-based model identifying the most important factors affecting the cost of PV over the past three decades. The results indicate that learning from experience only weakly explains change in the most important cost-reducing factors— plant size, module efficiency, and the cost of silicon. They point to other explanatory variables to include in future models. Future work might also evaluate the potential for efficiency gains from policies that rely less on ‘riding down the learning curve’ and more on creating incentives for firms to make investments in the types of cost-reducing activities quantified in this study.Learning-by-doing, Experience Curves, Learning Curves, Climate Policy

Agent-based Social Psychology: from Neurocognitive Processes to Social Data

Moral Foundation Theory states that groups of different observers may rely on partially dissimilar sets of moral foundations, thereby reaching different moral valuations. The use of functional imaging techniques has revealed a spectrum of cognitive styles with respect to the differential handling of novel or corroborating information that is correlated to political affiliation. Here we characterize the collective behavior of an agent-based model whose inter individual interactions due to information exchange in the form of opinions are in qualitative agreement with experimental neuroscience data. The main conclusion derived connects the existence of diversity in the cognitive strategies and statistics of the sets of moral foundations and suggests that this connection arises from interactions between agents. Thus a simple interacting agent model, whose interactions are in accord with empirical data on conformity and learning processes, presents statistical signatures consistent with moral judgment patterns of conservatives and liberals as obtained by survey studies of social psychology.Comment: 11 pages, 4 figures, 2 C codes, to appear in Advances in Complex System

A MERGE Model with Endogenous Technological Change and the Cost of Carbon Stabilization

Two stylized backstop systems with endogenous technological learning formulations (ETL) are introduced in MERGE: one for the electric and the other for the non-electric markets. Then the model is applied to analyze the impacts of ETL on carbon-mitigation policy, contrasting the resulting impacts with the situation without learning. As the model considers endogenous technological change in the energy sector only some exogenous key parameters defining the production function are varied together with the assumed learning rates to check the robustness of our results. Based on model estimations and the sensitivity analyses we conclude that increased commitments for the development of new technologies to advance along their learning curves has a potential for substantial reductions in the cost of climate mitigation helping to reach safe concentrations of carbon in the atmosphere.Climate change stabilization policies, Non-linear optimization, Induced technological change, Energy and macroeconomy

Sequential International Joint-Ventures and the Option to Choose

The purpose of this study is to formalize the optimal choice of market entry strategy for an individual multinational enterprise (MNE) from a dynamic perspective. It is argued that incorporating a suitable treatment of irreversibility, uncertainty and flexibility related to a MNEs investment decision gives further insights to the expansion, dissolvement, and optimal timing of international joint ventures (IJVs). The evolutionary process of the value of the foreign direct investment can be interpreted as a compound complex chooser option. The results suggest that uncertainty, size of equity share and future investment/divestment opportunities play an important role when it comes to transit from export to the first phase of the foreign direct investment commitment. The paper underscores the importance of modeling the dynamics of market entry and helps to refine the application of real options in the alliance context by providing a closed-form solution in continuous time to valueForeign direct investment, multinational enterprise, sequential investments, entry mode, international joint venture, real options

Accounting for Uncertainty Affecting Technical Change in an Economic-Climate Model

The key role of technological change in the decline of energy and carbon intensities of aggregate economic activities is widely recognized. This has focused attention on the issue of developing endogenous models for the evolution of technological change. With a few exceptions this is done using a deterministic framework, even though technological change is a dynamic process which is uncertain by nature. Indeed, the two main vectors through which technological change may be conceptualized, learning through R&D investments and learning-by-doing, both evolve and cumulate in a stochastic manner. How misleading are climate strategies designed without accounting for such uncertainty? The main idea underlying the present piece of research is to assess and discuss the effect of endogenizing this uncertainty on optimal R&D investment trajectories and carbon emission abatement strategies. In order to do so, we use an implicit stochastic programming version of the FEEM-RICE model, first described in Bosetti, Carraro and Galeotti, (2005). The comparative advantage of taking a stochastic programming approach is estimated using as benchmarks the expected-value approach and the worst-case scenario approach. It appears that, accounting for uncertainty and irreversibility would affect both the optimal level of investment in R&D –which should be higher– and emission reductions –which should be contained in the early periods. Indeed, waiting and investing in R&D appears to be the most cost-effective hedging strategy.Stochastic Programming, Uncertainty and Learning, Endogenous Technical Change

Induced Technological Change in a Limited Foresight Optimization Model

The threat of global warming calls for a major transformation of the energy system the coming century. Modeling technological change is an important factor in energy systems modeling. Technological change may be treated as induced by climate policy or as exogenous. We investigate the importance of induced technological change (ITC) in GET-LFL, an iterative optimization model with limited foresight that includes learning-by-doing. Scenarios for stabilization of atmospheric CO2 concentrations at 400, 450, 500 and 550 ppm are studied. We find that the introduction of ITC reduces the total net present value of the abatement cost over this century by 3-9% compared to a case where technological learning is exogenous. Technology specific polices which force the introduction of fuel cell cars and solar PV in combination with ITC reduce the costs further by 4-7% and lead to significantly different technological solutions in different sectors, primarily in the transport sector.Energy system model, Limited foresight, Climate policy, Endougenous learning, Technological lock-in

ILR Research in Progress 2011-12

The production of scholarly research continues to be one of the primary missions of the ILR School. During a typical academic year, ILR faculty members published or had accepted for publication over 25 books, edited volumes, and monographs, 170 articles and chapters in edited volumes, numerous book reviews. In addition, a large number of manuscripts were submitted for publication, presented at professional association meetings, or circulated in working paper form. Our faculty's research continues to find its way into the very best industrial relations, social science and statistics journals.Research_in_Progress_2011_12.pdf: 46 downloads, before Oct. 1, 2020