A Fast Literature Search Engine based on top-quality journals, by Dr. Mingze Gao.
- Topic classification is ongoing.
- Please kindly let me know [mingze.gao@mq.edu.au] in case of any errors.
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Results 10,990 resources
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Automobile manufacturers frequently use promotions involving cash incentives.While payments are nominally directed to either customers or dealers, the ultimatebeneficiary of the promotion depends on the outcome of price negotiation. We useprogram evaluation methods to compare the incidence of these two types ofpromotions. Customers obtain 70 to 90 percent of a customer rebate, but only 30 to40 percent of a dealer discount promotion, a $500 difference for a typical promotion.Our leading hypothesis is that pass-through rates differ because of information asymmetries: customer rebates are well-publicized to customers, while dealerdiscount promotions are not. (JEL D82, L11, L15, L62, L81, M31)
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This paper presents a list of the top 20 articles published in the <em>American Economic Review</em> during its first 100 years. This list was assembled in honor of the <em>AER</em>'s one-hundredth anniversary by a group of distinguished economists at the request of <em>AER</em>'s editor. A brief description accompanies the citations of each article.
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This paper aims to improve the practical applicability of the classic theory of incentive contracts under moral hazard. We establish conditions under which the information provided by an A/B test of incentive contracts is sufficient for answering the question of how best to improve a status quo incentive contract, given a priori knowledge of the agent's monetary preferences. We assess the empirical relevance of this result using data from DellaVigna and Pope's (2018) study of a variety of incentive contracts. Finally, we discuss how our framework can be extended to incorporate additional considerations beyond those in the classic theory.
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Many of the facts about the extensive margin of trade—which firms export, and how many products are sent to how many destinations—are consistent with a surprisingly large class of trade models because of the sparse nature of trade data. We propose a statistical model to account for sparsity, formalizing the assignment of trade shipments to country, product, and firm categories as balls falling into bins. The balls-and-bins model quantitatively reproduces the pattern of zero product- and firm-level trade flows across export destinations, and the frequency of multiproduct, multidestination exporters. In contrast, balls-and-bins overpredicts the fraction of exporting firms.
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We show that the Armenter and Koren model's firm-product-countryresults rely on the assumption that export shipment size is independent of firm size, and this assumption is contradicted by the data.When actual shipment sizes are used in the balls-and-bins model, itcannot reproduce the data on single product/single country exporters.Beyond just showing that the shipment size assumption mattersto balls-and-bins outcomes, our results highlight the important factthat shipment size is an economic decision, co-determined with otherexport choices. For this reason, we argue that a balls-and-bins modelcannot be a purely statistical benchmark model. (JEL F11, F14, O13,O19, Q37)
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Blum, Claro, and Horstmann (2016) make two statements about theballs-and-bins model of Armenter and Koren (2014). First, that usingfirm-level shipment data changes some of our results. Second, thatthe balls-and-bins model is not an appropriate statistical method.We respond to the first statement and argue that the second statementis unfounded and unrelated to the first. Indeed, the work ofBlum, Claro, and Horstmann (2016) is a perfect example of how touse balls-and-bins in a rich dataset to spot interesting data patterns.(JEL F11, F14)
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We have developed Bayesian Markov chain Monte Carlo (MCMC) methods for inferences of continuous-time models with stochastic volatility and infinite-activity Lévy jumps using discretely sampled data. Simulation studies show that (i) our methods provide accurate joint identification of diffusion, stochastic volatility, and Lévy jumps, and (ii) the affine jump-diffusion (AJD) models fail to adequately approximate the behavior of infinite-activity jumps. In particular, the AJD models fail to capture the "infinitely many" small Lévy jumps, which are too big for Brownian motion to model and too small for compound Poisson process to capture. Empirical studies show that infinite-activity Lévy jumps are essential for modeling the S&P 500 index returns.
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- American Economic Review (4,617)
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