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作者：Atakan, Alp E.; Ekmekci, Mehmet
作者单位：Koc University; University of London; Queen Mary University London; Boston College
摘要：We study information aggregation when n bidders choose, based on their private information, between two concurrent common-value auctions. There are k(s) identical objects on sale through a uniform-price auction in market s and there are an additional k(r) objects on auction in market r, which is identical to market s except for a positive reserve price. The reserve price in market r implies that information is not aggregated in this market. Moreover, if the object-to-bidder ratio in market s e...
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作者：Fang, Zheng; Seo, Juwon
作者单位：Texas A&M University System; Texas A&M University College Station; National University of Singapore
摘要：This paper develops a uniformly valid and asymptotically nonconservative test based on projection for a class of shape restrictions. The key insight we exploit is that these restrictions form convex cones, a simple and yet elegant structure that has been barely harnessed in the literature. Based on a monotonicity property afforded by such a geometric structure, we construct a bootstrap procedure that, unlike many studies in nonstandard settings, dispenses with estimation of local parameter spa...
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作者：Gul, Faruk; Natenzon, Paulo; Pesendorfer, Wolfgang
作者单位：Princeton University; Washington University (WUSTL)
摘要：We introduce random evolving lotteries to study preference for non-instrumental information. Each period, the agent enjoys a flow payoff from holding a lottery that will resolve at the terminal date. We provide a representation theorem for non-separable risk consumption preferences and use it to characterize agents' attitude to non-instrumental information. To address applications, we characterize peak-trough utilities that aggregate trajectories of flow utilities linearly but, in addition, pu...
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作者：Dou, Liyu; Mueller, Ulrich K.
作者单位：The Chinese University of Hong Kong, Shenzhen; The Chinese University of Hong Kong, Shenzhen; Princeton University
摘要：We introduce a generalization of the popular local-to-unity model of time series persistence by allowing for p autoregressive (AR) roots and p - 1 moving average (MA) roots close to unity. This generalized local-to-unity model, GLTU(p), induces convergence of the suitably scaled time series to a continuous time Gaussian ARMA(p,p - 1) process on the unit interval. Our main theoretical result establishes the richness of this model class, in the sense that it can well approximate a large class of...
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作者：Burzoni, Matteo; Riedel, Frank; Soner, H. Mete
作者单位：University of Milan; University of Bielefeld; University of Johannesburg; Princeton University
摘要：We reconsider the microeconomic foundations of financial economics. Motivated by the importance of Knightian uncertainty in markets, we present a model that does not carry any probabilistic structure ex ante, yet is based on a common order. We derive the fundamental equivalence of economic viability of asset prices and absence of arbitrage. We also obtain a modified version of the fundamental theorem of asset pricing using the notion of sublinear pricing measures. Different versions of the eff...
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作者：Hansen, Bruce E.; Lee, Seojeong
作者单位：University of Wisconsin System; University of Wisconsin Madison; University of New South Wales Sydney
摘要：This paper develops inference methods for the iterated overidentified Generalized Method of Moments (GMM) estimator. We provide conditions for the existence of the iterated estimator and an asymptotic distribution theory, which allows for mild misspecification. Moment misspecification causes bias in conventional GMM variance estimators, which can lead to severely oversized hypothesis tests. We show how to consistently estimate the correct asymptotic variance matrix. Our simulation results show...
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作者：Menzel, Konrad
作者单位：New York University
摘要：We propose a bootstrap procedure for data that may exhibit cluster-dependence in two or more dimensions. The asymptotic distribution of the sample mean or other statistics may be non-Gaussian if observations are dependent but uncorrelated within clusters. We show that there exists no procedure for estimating the limiting distribution of the sample mean under two-way clustering that achieves uniform consistency. However, we propose bootstrap procedures that achieve adaptivity with respect to di...
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作者：Bhattacharya, Debopam
作者单位：University of Cambridge
摘要：An important goal of empirical demand analysis is choice and welfare prediction on counterfactual budget sets arising from potential policy interventions. Such predictions are more credible when made without arbitrary functional-form/distributional assumptions, and instead based solely on economic rationality, that is, that choice is consistent with utility maximization by a heterogeneous population. This paper investigates nonparametric economic rationality in the empirically important contex...
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作者：Giacomini, Raffaella; Kitagawa, Toru
作者单位：University of London; University College London
摘要：This paper reconciles the asymptotic disagreement between Bayesian and frequentist inference in set-identified models by adopting a multiple-prior (robust) Bayesian approach. We propose new tools for Bayesian inference in set-identified models and show that they have a well-defined posterior interpretation in finite samples and are asymptotically valid from the frequentist perspective. The main idea is to construct a prior class that removes the source of the disagreement: the need to specify ...
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作者：Shapiro, Bradley T.; Hitsch, Guenter J.; Tuchman, Anna E.
作者单位：University of Chicago; Northwestern University
摘要：We estimate the distribution of television advertising elasticities and the distribution of the advertising return on investment (ROI) for a large number of products in many categories. Our results reveal substantially smaller advertising elasticities compared to the results documented in the literature, as well as a sizable percentage of statistically insignificant or negative estimates. The results are robust to functional form assumptions and are not driven by insufficient statistical power...
