Nonparametric estimation when data on derivatives are available

We consider settings where data are available on a nonparametric function and various partial derivatives. Such circumstances arise in practice, for example in the joint estimation of cost and input functions in economics. We show that when derivative data are available, local averages can be replaced in certain dimensions by nonlocal averages, thus reducing the nonparametric dimension of the problem. We derive optimal rates of convergence and conditions under which dimension reduction is achieved. Kernel estimators and their properties are analyzed, although other estimators, such as local polynomial, spline and nonparametric least squares, may also be used. Simulations and an application to the estimation of electricity distribution costs are included.Comment: Published at http://dx.doi.org/10.1214/009053606000001127 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Nonparametric Least Squares Regression and Testing in Economic Models

nonparametric regression, semiparametric regression, partial linear model, least squares, empirical processes, hypothesis testing, conditional moment tests, U-statistics, bootstrap, specification test, significance test, additive separability, multiplicative separability, homogeneity, monotonicity, concavity, demand theory, maximization hypothesis

Energy Projects, Social Licence, Public Acceptance and Regulatory Systems in Canada: A White Paper

It has become increasingly difficult in Canada to gain and sustain public acceptance of energy projects. Increased levels of protest, combined with traditional media and social media coverage of opposition, combine to suggest decreased public acceptance of energy projects. Decision-makers have responded accordingly, and a variety of energy projects have either been delayed or put on hold indefinitely. This is true for both conventional and renewable energy projects and in many different regions across the country. A number of proposed energy projects have recently faced opposition from various stakeholder groups. For instance, the decision of the Joint Review Panel for the Northern Gateway Pipeline is being challenged in Canada’s court system. First Nations groups have issued an ultimatum to the Federal Government that it must choose between Site C (a proposed hydro dam) and liquefied natural gas development in B.C. Rapid expansion of wind energy projects in Ontario has engendered lengthy and costly appeals and the rise of an anti-wind social movement. In Nova Scotia, tidal energy development is being positioned as a new renewable energy option; gaining public acceptance is critical in light of recent opposition to wind energy development. As these experiences suggest, not only has the regulatory process become more contentious, but also an apparently new concept — social licence — has had popular appeal. This white paper reports on the results of a year-long interdisciplinary collaboration aimed at identifying and summarizing extant research regarding social licence and related concepts, with a particular emphasis on understanding its implications for public acceptance of energy projects in Canada, and their related regulatory processes. In particular, this research addressed the following questions: 1. What is the history and scope of the term ‘social licence’, both in the context of energy project development and more generally? What are the strengths and limitations of this term? How does it help or hinder energy policy, regulatory debates and decision-making? 2. What are the similarities and differences between the notion of social licence and established concepts and other concepts or frameworks? 3. From the standpoint of public acceptance of energy projects, is Canada’s regulatory system broken? From whose perspective? And what alternatives might be considered? 4. What are barriers to, and enablers of a licence within the regulatory process — legal, social or otherwise? 5. What role does social licence play in the larger picture: How valid is the concept of social licence? Can social licence actually stop a project, or determine the outcome of an election? Does it create a valuable dialogue about a project? When opposition to projects leads to the arrest of people breaching an injunction or violent confrontations, what role can social licence play in promoting an alternative approach? In addition to a comprehensive look at the concepts of public acceptance and social licence and their applications to Canada, this white paper arrives at certain conclusions (Section 5) and makes recommendations (Section 6) for improving Canada’s regulatory systems and improving public confidence in Canada’s various energy-related regulatory agencies. For instance, as the federal government embarks on its agenda to amend the regulatory process, the research presented here can inform how the government can best carry out its mandate of reform while balancing the economic, environmental, political, social, and security-related issues pertinent to regulators, federal and provincial governments, industry, First Nations, environmental groups and the general public. The appeal of the term “social licence” derives from the inclusivity and equitability that it seems to imply. But populist pressure for increased voice and regulatory or judicial intervention, arising out of a sense of disaffection or disenfranchisement, is hardly a novel phenomenon: historical context and the lessons learned therefrom are essential in evaluating the idea and situating the debate within a meaningful framework. Social licence entails an additional layer of ‘regulation’, albeit an amorphous one. A central lesson of the 20th century experience is that regulation comes at a cost, and that excessive regulation and intervention can lead to paralysis and ‘government failure’. The implication is that regulation should be relied upon where it is necessary, and should be implemented in sensible ways. One of the conclusions of this report is that public trust and confidence can be enhanced by rationalizing existing regulatory vehicles to reduce the common perception that decisions are sometimes politically motivated and ensuring that decisions are made at the right levels of government. The institutionalization of social licence also has identifiable risks. It is likely to increase incentives for “rent-seeking behaviour.” The threat of veto, or even obstruction, endows the affected group with leverage that can result in extraction of rents that are disproportionate to impacts. It also increases regulatory and political uncertainty associated with a given project, discouraging investment, or requiring returns higher than are merited by the inherent riskiness of the proposed undertaking. The term “social licence” needs to be further analyzed, and, if used, used with care. The concept originated in the mining sector as the “social licence to operate,” and as the concept has migrated to the energy sector, it appears to have broadened in scope so that its meaning has become unclear, amorphous and confusing. Other terms such as “acceptance,” “support” or “public confidence” may be more appropriate in the energy sphere. Regulators, policy-makers and politicians should refrain from the use of these terms without a clear understanding of their implications. Our specific recommendations include: 1. Governmental Coordination. Greater coordination of regulatory processes between the federal and provincial governments is required and should be directed towards enhancing beneficial outcomes for all affected stakeholders (Section 6.1). 2. Stakeholder Engagement. A consistent, transparent and rigorous system for identifying and reaching out to stakeholders is essential to regulatory efficiency and efficacy (Section 6.2). 3. Social Licence as a Concept. When it comes to energy development, the term “social licence” needs to be further analyzed, and, if used, used with care (Section 6.3). 4. First Nations. The federal and provincial governments should take ownership of this duty to consult and ensure that it is done in a comprehensive manner that has been set out by both domestic and international law (Section 6.4). 5. Changes to the NEB Act. An independent review of the changes to the NEB Act regarding time to consult and the list of those who can be consulted should be undertaken to ensure the NEB is unconstrained in its ability to regulate appropriately and has public confidence in its mandate and decisions (Section 6.5). 6. Make Broader Use of Information Gained during Assessment Processes. Energy regulators should consider mechanisms to report recurring concerns that are outside of the scope of their mandate (Section 6.6). 7. Compliance after Project Approval. There is a need for publicly available, timely and relevant data relating to the compliance and post-approval status of projects. Data should be placed on a government portal to increase accessibility to stakeholders (Section 6.7). 8. Cross-Examination in Regulatory Hearings. The extensiveness of permitted cross-examination, and indeed the entire regulatory proceeding, needs to be proportionate to the magnitude of the impacts of the ultimate decision (Section 6.8)

Dynamic Nonparametric State Price Density EstimationUsing Constrained Least Squares and the Bootstrap

The economic theory of option pricing imposes constraints on the structure of call functions and state price densities (SPDs). Except in a few polar cases, it does not prescribe functional forms. This paper proposes a nonparametric estimator of option pricing models which incorporates various restrictions within a single least squares procedure thus permitting investigation of a wide variety of model specifications and constraints. Among these we consider monotonicity and convexity of the call function and integration to one of the state price density. The procedure easily accommodates heteroskedasticity of the residuals. Static and dynamic properties can be tested using both asymptotic and bootstrap methods. Our monte carlo simulations suggest that bootstrap confidence intervals are far superior to aymptotic ones particularly when estimating derivatives of the call function. We apply the techniques to option pricing data on the DAX

Perspectives on nonparametric and Semiparametric Modeling

Nonparametric regression techniques hold out the promise of more flexible modeling of data in many areas of physical, biological and social sciences. However, their use is hampered by the Òcurse of dimensionalityÓ which imposes enormous data requirements as the number of explanatory variables increases. After summarizing two of the most commonly used methods for mitigating the ÒcurseÓ, this paper outlines a new approach which exploits data on derivatives. In economics, such circumstances arise in the joint estimation of cost and factor demand functions, or when production function data are combined with data on factor prices. The ideas are illustrated using empirical examples from energy economics.

Nonparametric Regression Techniques in Economics

This introduction to nonparametric regression emphasizes techniques that might be most accessible and useful to the applied economist. The paper begins with a brief overview of the class of models under study and central theoretical issues such as the curse of dimensionality, the bias-variance trade-off and rates of convergence. The paper then focuses on kernel and nonparametric least squares estimation of the nonparametric regression model, and optimal differencing estimation of the partial linear model. Constrained estimation and hypothesis testing is also discussed. Empirical examples include returns to scale in electricity distribution and hedonic pricing of housing attributes.