Experience Curve Model Research Articles

Mills of progress grind slowly? Estimating learning rates for onshore wind energy

Estimated learning rates for onshore wind span a large range of about 40 percentage points. We propose a multi-factor experience curve model with a new economies of scale measure and estimate learning rates for onshore wind using country-level data from seven European countries. We find learning by doing rates of 2%–3% and learning by searching rates of 7%–9% in terms of LCOE. When decomposing LCOE, we find no significant learning in installed costs but significant learning in capacity factors. Accounting for improvements in capacity factors and modeling learning by searching can hence be promising for energy models that endogenize technological change. We confirm our results in several robustness checks, and show that depreciation rates of the knowledge stock have large effects on estimated learning rates.

Mills of Progress Grind Slowly? Estimating Learning Rates for Onshore Wind Energy

Estimated learning rates for onshore wind span a large range of about 40 percentage points. We propose a multi-factor experience curve model with a new economies of scale measure and estimate learning rates for onshore wind using country-level data from seven European countries. We find learning by doing rates of 2%-3% and learning by searching rates of 7%-9% in terms of LCOE. When decomposing LCOE, we find no significant learning in installed costs but significant learning in capacity factors. Accounting for improvements in capacity factors and modelling learning by searching can hence be promising for energy models that endogenize technological change. We confirm our results in several robustness checks, and show that depreciation rates of the knowledge stock have large effects on estimated learning rates.

When will the 2015 millennium development goal of infant mortality rate be finally realised? - Projections for 21 OECD countries through 2050

According to the United Nations Children's Fund (UNICEF), the number of global infant deaths for those under the age of one year was down from 8.4 million in 1990 to 5.4 million in 2010. However, the declining trend of infant mortality rate varies significantly from country to country based on the vastly different environmental elements they face. This paper attempts to predict the future infant mortality rate of 21 OECD countries through 2015 and 2050 by the use of experience curve model and compare the results to the two other well-known projections by the United Nations Population Division and the US Census Bureau in the context of the millennium development goal targets. The results from all three projections indicate that only one or two countries will meet the two-thirds reduction target of the 2015 millennium development goal. By 2050, four to 18 countries will still not be able to meet the target. Therefore, each country may need to undertake a comprehensive review of its policies and programs of infant mortality control to generate many alternative plans for major improvement.

When will the 2015 millennium development goal of infant mortality rate be finally realised? - Projections for 21 OECD countries through 2050

According to the United Nations Children's Fund (UNICEF), the number of global infant deaths for those under the age of one year was down from 8.4 million in 1990 to 5.4 million in 2010. However, the declining trend of infant mortality rate varies significantly from country to country based on the vastly different environmental elements they face. This paper attempts to predict the future infant mortality rate of 21 OECD countries through 2015 and 2050 by the use of experience curve model and compare the results to the two other well-known projections by the United Nations Population Division and the US Census Bureau in the context of the millennium development goal targets. The results from all three projections indicate that only one or two countries will meet the two-thirds reduction target of the 2015 millennium development goal. By 2050, four to 18 countries will still not be able to meet the target. Therefore, each country may need to undertake a comprehensive review of its policies and programs of infant mortality control to generate many alternative plans for major improvement.

Can we predict long-term future crime rates? A projection of crime rates through 2030 for individual states in the USA

Can we predict long-term crime rates? The overall result of many long-term projections has been described as notoriously poor. Therefore, more research efforts are called for by trying out several new and different methodologies. In this paper, we offer the use of simple experience curve models as an alternative forecasting method. We use the experience curve models to project total crime and violent crime rates in 2030 for 50 individual states, including Washington DC, in the USA. The results are encouraging in that the projection models developed from historical data for respective states show, in general, high values of R2 over .85. Our projected crime rates show both increasing trends as well as declining trends compared to 2010. A large variation among individual states is due to highly variable experience curve slopes we estimated across respective states.

Using the experience curve model to project carbon dioxide emissions through 2040

Projections of long-term carbon dioxide (CO2) emissions in the literature vary over a wide range depending on both socio-economic development and mitigation policy. Therefore, any attempt to improve the accuracy of such projections is important. We present a simple aggregate model to project the future carbon intensity of economic output, which is then used to forecast energy-related CO2 emissions through 2040 for seven countries and three regions of the world. Our projection results are compared to those from the International Energy Outlook 2013 report. We find that our projections are significantly higher than those reported in the International Energy Outlook 2013 report.

Alternative Projection of the Carbon Dioxide Emission for 10 Countries and Regions - In Comparison with the 2013 International Energy Outlook

A projection of future carbon emission is a vital input in influencing climate change for the world as well as for individual country and region. We provide alternative projections of future carbon dioxide emission and compare our projections with those from the International Energy Outlook report (2013) for seven countries and three region -- China, U.S., India, Japan, Brazil, South Korea, Canada, Europe and Eurasia, Middle East and Africa. For the projection methodology, we use kinked experience curve model. We find that the EIA’s projections are significantly lower than ours in nine countries and regions with the exception of Japan.

Comparative analysis of long-term road fatality targets for individual states in the US—An application of experience curve models

Both the Federal government and individual state governments in the US establish long-term road fatality targets to plan and evaluate the effectiveness of their respective safety programs. The purpose of this paper is to develop a simple fatality projection model to project future fatality rates and number of fatalities through 2020 and 2030 for individual states. And then, long-term fatality target value established by ten selected states will be compared to our projected values to assess realism of these targets.Based on the results of this study, several policy recommendations to accelerate reduction of road fatality are made.

Predicting the costs of photovoltaic solar modules in 2020 using experience curve models

Except in few locations, photovoltaic generated electricity remains considerably more expensive than conventional sources. It is however expected that innovation and learning-by-doing will lead to drastic cuts in production cost in the near future. The goal of this paper is to predict the cost of PV modules out to 2020 using experience curve models, and to draw implications about the cost of PV electricity. Using annual data on photovoltaic module prices, cumulative production, R&D knowledge stock and input prices for silicon and silver over the period 1990–2011, we identify a experience curve model which minimizes the difference between predicted and actual module prices. This model predicts a 67% decrease of module price from 2011 to 2020. This rate implies that the cost of PV generated electricity will reach that of conventional electricity by 2020 in the sunniest countries with annual solar irradiation of 2000 kWh/year or more, such as California, Italy, and Spain.

Comparative Analysis of Long-Term Road Fatality Targets for Individual States in America - An Application of Experience Curve Models

Comparative Analysis of Long-Term Road Fatality Targets for Individual States in America - An Application of Experience Curve Models

Mergers and Acquisitions in a Business Game

We apply a design-science approach to examine the merger and acquisition features of a business game. These features include an experience-curve model that constitutes the endogenous incentive for horizontal integration, supplemented with a production capacity limit and a business license fee for each firm. Procedures for acquisitions include the ability of firms to found subsidiary firms and to purchase firms by submitting market offers to buy shares, by accepting market offers to sell shares, and by engaging in statutory takeovers. The game was administered to 180 college undergraduates for 200 periods over the duration of one semester. By the end of the exercise, the participants had founded 285 firms across five interdependent industries. About 28% of the firms had acquired other firms. Forward acquisitions exceed backward and conglomerate acquisitions throughout the duration of the exercise, forward acquisitions exceed horizontal acquisitions when the economy is less mature, and horizontal acquisitions increase more than forward, backward, and conglomerate acquisitions when the economy is more mature. On the whole, participants behaved rationally, evidence that the merger and acquisition features function as intended. A follow-up study of hubris in mergers and acquisitions is suggested.

A global and local endogenous experience curve model for projecting future uptake and cost of electricity generation technologies

A global and local learning model (GALLM) has been developed to project the cost and global uptake of different electricity generation technologies to the year 2050. This model features three regions, endogenous technological learning within and across those regions, various government policies to facilitate technological learning and a penalty constraint which is used to mimic the effect market forces play on the capital cost of electricity generation technologies. This constraint has been added as market forces have been a strong factor in technology pricing in recent years. Global, regional and component experience curves have been developed for some technologies. The model, with the inclusion of these features, projects a diverse range of technologies contributing to global electricity generation under a carbon price scenario. The penalty constraint leads to gradual and continual installations of technologies and because the constraint provides a disincentive to install too much of a technology, it reduces the impact of uncertainty in the learning rate. Alternative forms of the penalty constraint were tested for their suitability; it was found that, with a zero and lower-cost version of the constraint, photovoltaics are installed in a boom-and-bust cycle, which is not supported by past experience. When the constraint is set at a high level, there are fewer installations.

Can We Predict Long-Term Future Crime Rates?

Can we predict long-term crime rates? In this paper, we offer the use of simple experience curve models as an alternative forecasting method. We use the experience curve models to project total crime and violent crime rates in 2030 for 50 individual states and Washington D.C. in the United States. Results are encouraging in that projection models developed from historical data for respective states show, in general, high values of R2 over .85. Our projected crime rates show both increasing trends as well as declining trends compared to 2010. A large variation among individual states is due to highly variable experience curve slopes we estimated across respective states.

Kinked Experience Curve

How much productivity improvement or cost reduction would be possible when the number of semiconductor chips fabricated increased from one million to two million? How many more wind farms or photovoltaic farms needed to be installed before their unit cost of producing electricity can become parity with unit cost from the fossil power plant? Can the child mortality rate in the world be reduced by two-thirds between 1990 and 2015? Or, can the prevalence rate from tuberculosis be reduced by 50% between 1990 and 2015? Can experience curve (EC) models provide answers to these questions? We present an extended EC approach known as kinked EC models which are capable of predicting the long-term future performance measures such as accident rate, mortality rate, energy efficiency index, etc. in the context of large learning systems such as nation, region, or even the world.

Next Frontier of Experience Curve Application - Predicting Performance of Large Learning Systems by Kinked Experience Curve

Kinked experience curve model is presented as a major alternative to classical experience curve model. Whenever a sudden shift in the historical pattern of data occurs, the use of kinked model may yield a more accurate and reliable future projection. The purpose of this paper is to present an extended EC approach known as kinked model which appears to be better-suited for application where social or physical performance measurements such as accident, mortality, recovery, energy efficiency, carbon emission, etc., are under analysis. Based on our empirical studies, the use of kinked models will become more dominant when the variables to be analyzed deal with social and developmental issues in the context of expanded learning systems. The kinked models will often yield higher learning rates and higher coefficients of determination.

When Will the Millennium Development Goal on Infant Mortality Rate Be Realized? - Projections for 21 OECD Countries Through 2050 -

Background: Reduction of under-five year mortality rate by two-thirds by 2015 compared to 1990 level has been adopted as Target 4A in the Millennium Development Goals. Since infant deaths account for over seventy percents of under-five year mortality, the same two-thirds reduction Target of infant mortality rate (IMR) will be a prerequisite for achieving the Target 4A. Methods: We develop classical and kinked experience curve equations as our models to project IMR for 21 OECD countries for 2015 and 2050 We also use projected IMR by the UN and by the U.S. Census Bureau for comparison. Findings: Our projection indicates that only two countries will meet the reduction goal by 2015. However, all but four countries will achieve the garget by 205'3 On the other hand, projections by UN and the U.S. Census are more pessimistic in that only seven or four countries are expected to meet the target by 2050. Conclusion: We have demonstrated that the kinked experience curve model may be a useful alternative projection methodology. The results from all three projection methodologies suggest that each country may need a comprehensive review of its policy and programs of infant mortality control for major improvement.

Modeling the Diffusion of Residential Photovoltaic Systems in Italy: An Agent-Based Simulation

We propose an agent-based model to simulate the diffusion of small PV systems among single- or two-family homes in Italy over the 2006-2026 period. To this end,we explicitly model the geographical distribution of the agents in order to account for regional differences across the country. The adoption decision is assumed to be influenced predominantly by (1) the payback period of the investment, (2) its environmental benefit, (3) the household’s income, and (4) the influence of communication with other agents. For the estimation of the payback period, the model considers investment costs, local irradiation levels, governmental support, earnings from using self-produced electricity vs. buying electricity from the grid, as well as various administrative fees and maintenance costs. The environmental benefit is estimated by a proxy for the CO2 emissions saved. The level of the household income is associated with the specific economic conditions of the region where the agent is located, as well as the agent’s socio-economic group (age group, level of education, household type). Finally, the influence of communication is measured by the number of links with other households that have already adopted a PV system. In each simulation step, the program dynamically updates the social system and the communication network, while the evolution of the PV system’s investment costs depend on a one-factor experience curve model that is based on the exogeneous development of the global installed PV capacity. Our results show that Italy’s domestic PV installations are already beyond an initial stage of rapid growth and, though likely to spread further, they will do so at a significantly slower rate of diffusion.

Is Forecasting Future Suicide Rates Possible? Application of the Experience Curve

Many OECD (Organization for Economic Co-operation and Development) countries have implemented national suicide prevention strategies. An accurate forecast of future suicide rate, if available, will be useful for planning and evaluation of a suicide prevention strategy. Therefore, we have developed a simple forecasting model of suicide rate for 15 OECD countries. We use the experience curve model with the data from 1960 to 2005 to forecast suicide rate for each of the 15 countries. In the experience curve analysis, the independent variable is the cumulative population size and the dependent variable is suicide rate for each country. For the 15 countries, the application of the experience curve generates the averaged experience slope of 61.2%, implying a reduction of 38.8% in suicide rate as the cumulative population size is doubled. Using the estimated experienced equation, we forecast both suicide rate and the number of deaths from suicide in years 2010, 2020 and 2030 for each of the 15 countries. The use of the experience curve generates long-term future suicide rate which may be useful input in developing a national prevention strategy.

Renewable electricity production costs—A framework to assist policy-makers' decisions on price support

Despite recent progress, the production costs for renewable electricity remain above those for conventional power. Expectations of continuous reductions in production costs, typically underpin governments' policies for financial support. They often draw on the technology-focused versions of the Experience Curve model. This paper discusses how national-contextual factors also have a strong influence on production costs, such as geographic, infrastructural, institutional, and resource factors. As technologies mature, and as they reach significant levels of diffusion nationally, sustained increases in production costs might be recorded, due to these nationally contextual factors, poorly accounted for in policy-making decisions for price support. The paper suggests an analytical framework for a more comprehensive understanding of production costs. Based on this, it recommends that the evolution of specific cost levels and factors be monitored to locate ‘sources of changes’. The paper also suggests policy instruments that governments may use to facilitate cost decreases, whenever possible. The application of the framework is illustrated for the diffusion of wind power in Spain during the past three decades.

Is Forecasting Future Suicide Rate Possible? - Application of Experience Curve

Many OECD (Organization for Economic Co-operation and Development) countries have implemented national suicide prevention strategies. An accurate forecast of future suicide rate, if available, will be useful for planning and evaluation of a suicide prevention strategy. Therefore, we have developed a simple forecasting model of suicide rate for 15 OECD countries. We use the experience curve model with the data from 1960 to 2005 to forecast suicide rate for each of the 15 countries. In the experience curve analysis, the independent variable is the cumulative population size and the dependent variable is suicide rate for each country. For the 15 countries, the application of the experience curve generates the averaged experience slope of 61.2%, implying a reduction of 38.8% in suicide rate as the cumulative population size is doubled. Using the estimated experienced equation, we forecast both suicide rate and the number of deaths from suicide in years 2010, 2020 and 2030 for each of the 15 countries. The use of the experience curve generates long-term future suicide rate which may be useful input in developing a national prevention strategy.