Estimation of heterogeneous preferences, with an application to demand for internet services

This paper presents a structural econometric framework for discrete and continuous consumer choices in which unobserved intrapersonal and interpersonal preference heterogeneity is modeled explicitly. It outlines a simulation-assisted estimation methodology applicable in this framework. This methodology is illustrated in an application to analyze data from the U.C. Berkeley Internet Demand Experiment

Data-Driven Estimation in Equilibrium Using Inverse Optimization

Equilibrium modeling is common in a variety of fields such as game theory and transportation science. The inputs for these models, however, are often difficult to estimate, while their outputs, i.e., the equilibria they are meant to describe, are often directly observable. By combining ideas from inverse optimization with the theory of variational inequalities, we develop an efficient, data-driven technique for estimating the parameters of these models from observed equilibria. We use this technique to estimate the utility functions of players in a game from their observed actions and to estimate the congestion function on a road network from traffic count data. A distinguishing feature of our approach is that it supports both parametric and \emph{nonparametric} estimation by leveraging ideas from statistical learning (kernel methods and regularization operators). In computational experiments involving Nash and Wardrop equilibria in a nonparametric setting, we find that a) we effectively estimate the unknown demand or congestion function, respectively, and b) our proposed regularization technique substantially improves the out-of-sample performance of our estimators.Comment: 36 pages, 5 figures Additional theorems for generalization guarantees and statistical analysis adde

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

The case for international coordination of electricity regulation : evidence from the measurement of efficiency in South America

A decade long experience shows that monitoring the performance of public and private monopolies in South America is proving to be the hard part of the reform process. The operators who control most of the information needed for regulatory purposes have little interest in volunteering their dissemination unless they have an incentive to do so. The authors argue that, in spite of, and maybe because of, a much weaker information base and governance structure, South America's electricity sector could pursue an approach that relies on performance rankings based on comparative efficiency measures. The authors show that with the rather modest data currently available publicly, such an approach could yield useful results. They provide estimates of efficiency levels in South America's main distribution companies between 1994 and 2000. Moreover, the authors show how relatively simple tests can be used by regulators to check the robustness of their results and strengthen their position at regulatory hearings.Economic Theory&Research,Environmental Economics&Policies,Enterprise Development&Reform,Labor Policies,Health Monitoring&Evaluation,Environmental Economics&Policies,Economic Theory&Research,Geographical Information Systems,Health Monitoring&Evaluation,Educational Technology and Distance Education

Technology frontier, labor productivity and economic growth: Evidence from OECD countries

We use 29 OECD countries data spanning over 1960-2000 to study the growth strategy when countries are close to the technology frontier. Relying on a semi-parametric generalized additive model, we estimate labor productivity equations. We find that the number of agents enrolled in higher education is a determinant of growth. Moreover, when a country is sufficiently near the technology frontier thanks to an increasing R&D expenditure, it becomes optimal to invest in fundamental research, since after a short period of efficiency, business R&D can no longer ensure the transition toward the technology frontier, while higher education presents the opposite shape. These findings support the main assertion of Aghion and Cohen (2004) that countries which are near the technology frontier have to invest in higher education while those far away from the frontier make their technology level growing up by investing in primary and secondary schooling.Education, R&D, Labor Productivity, Economic Growth

ILR Research in Progress 2013-14

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_2013_14.pdf: 54 downloads, before Oct. 1, 2020

The price of anarchy in transportation networks by estimating user cost functions from actual traffic data

We have considered a large-scale road network in Eastern Massachusetts. Using real traffic data in the form of spatial average speeds and the flow capacity for each road segment of the network, we converted the speed data to flow data and estimated the origin-destination flow demand matrices for the network. Assuming that the observed traffic data correspond to user (Wardrop) equilibria for different times-of-the-day and days-of-the-week, we formulated appropriate inverse problems to recover the per-road cost (congestion) functions determining user route selection for each month and time-of-day period. In addition, we analyzed the sensitivity of the total user latency cost to important parameters such as road capacities and minimum travel times. Finally, we formulated a system-optimum problem in order to find socially optimal flows for the network. We investigated the network performance, in terms of the total latency, under a user-optimal policy versus a system-optimal policy. The ratio of these two quantities is defined as the Price of Anarchy (POA) and quantifies the efficiency loss of selfish actions compared to socially optimal ones. Our findings contribute to efforts for a smarter and more efficient city