Many areas of the natural and social sciences involve complex systems that link together multiple sectors. Integrated assessment models (IAMs) are approaches that integrate knowledge from two or more domains into a single framework, and these are particularly important for climate change. One of the earliest IAMs for climate change was the DICE/RICE family of models, first published in Nordhaus (1992), with the latest version in Nordhaus (2017, 2017a). A difficulty in assessing IAMs is the inability to use standard statistical tests because of the lack of a probabilistic structure. In the absence of statistical tests, the present study examines the extent of revisions of the DICE model over its quarter-century history. The study find that the major revisions have come primarily from the economic aspects of the model, whereas the environmental changes have been much smaller. Particularly sharp revisions have occurred for global output, damages, and the social cost of carbon. These results indicate that the economic projections are the least precise parts of IAMs and deserve much greater study than has been the case up to now, especially careful studies of long-run economic growth (to 2100 and beyond).
During his period at the LSE from the early 1960s to the mid 1980s, John Denis Sargan rose to international prominence and the LSE emerged as the world’s leading centre for econometrics. Within this context, we examine the life of Denis Sargan, describe his major research accomplishments, recount the work of his many doctoral students, and track this remarkable period that constitutes the Sargan era of econometrics at the LSE.
Professor T.W. Anderson passed away on September 17, 2016 at the age of 98 years after an astonishing career that spanned more than seven decades. Standing at the nexus of the statistics and economics professions, Ted Anderson made enormous contributions to both disciplines, playing a significant role in the birth of modern econometrics with his work on structural estimation and testing in the Cowles Commission during the 1940s, and educating successive generations through his brilliant textbook expositions of time series and multivariate analysis. This article is a tribute to his many accomplishments.
A growing number of school districts use centralized assignment mechanisms to allocate school seats in a manner that reflects student preferences and school priorities. Many of these assignment schemes use lotteries to ration seats when schools are oversubscribed. The resulting random assignment opens the door to credible quasi-experimental research designs for the evaluation of school effectiveness. Yet the question of how best to separate the lottery-generated variation integral to such designs from non-random preferences and priorities remains open. This paper develops easily-implemented empirical strategies that fully exploit the random assignment embedded in a wide class of mechanisms, while also revealing why seats are randomized at one school but not another. We use these methods to evaluate charter schools in Denver, one of a growing number of districts that combine charter and traditional public schools in a unified assignment system. The resulting estimates show large achievement gains from charter school attendance. Our approach generates efficiency gains over ad hoc methods, such as those that focus on schools ranked first, while also identifying a more representative average causal effect. We also show how to use centralized assignment mechanisms to identify causal effects in models with multiple school sectors.
We study the classic sequential screening problem in the presence of ex-post participation constraints. We establish necessary and sufficient conditions that determine when the optimal selling mechanism is either static or sequential. In the static contract, the buyers are not screened with respect to their interim type and the object is sold at a posted price. In the sequential contract, the buyers are screened with respect to their interim type and a menu of quantities is offered.
We completely characterize the optimal sequential contract with binary interim types and a continuum of ex-post values. Importantly, the optimal sequential contract randomizes the allocation of the low-type buyer and awards a deterministic allocation to the high type buyer. Finally, we provide additional results for the case of multiple interim types.
We study the classic sequential screening problem in the presence of ex-post participation constraints. We establish necessary and sufficient conditions that determine exhaustively when the optimal selling mechanism is either static or sequential. In the static contract, the buyers are not screened with respect to their interim type and the object is sold at a posted price. In the sequential contract, the buyers are screened with respect to their interim type and a menu of quantities is offered.
We completely characterize the optimal sequential contract with binary interim types and a continuum of ex-post values. Importantly, the optimal sequential contract randomizes the allocation of the low type buyer while giving a deterministic allocation to the high type. Finally, we provide additional results for the case of multiple interim types.
We study the classic sequential screening problem in the presence of buyers’ ex-post participation constraints. A leading example is the online display advertising market, in which publishers frequently do not use up-front fees and instead use transaction-contingent fees. We establish conditions under which the optimal selling mechanism is static and buyers are not screened with respect to their interim type, or sequential and the buyers are screened with respect to their interim type. In particular, we provide an intuitive necessary and sufficient condition under which the static contract is optimal for general distributions of ex-post values. Further, we completely characterize the optimal sequential contract with binary interim types and continuum of ex-post values when this condition fails. Importantly, the latter contract randomizes the allocation of the low type buyer while giving a deterministic allocation to the high type. We also provide partial results for the case of multiple interim types.
We quantify the welfare effects of zone pricing, or setting common prices across distinct markets, in retail oligopoly. Although monopolists can only increase profits by price discriminating, this need not be true when firms face competition. With novel data covering the retail home improvement industry, we find that Home Depot would benefit from finer pricing but that Lowe’s would prefer coarser pricing. Zone pricing softens competition in markets where firms compete, but it shields consumers from higher prices in rural markets, where firms might otherwise exercise market power. Overall, zone pricing produces higher consumer surplus than finer price discrimination does.