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 485 resources
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The US Environmental Protection Agency (EPA) uses a dynamic approach to enforcing air pollution regulations, with repeat offenders subject to high fines and designation as high priority violators (HPV). We estimate the value of dynamic enforcement by developing and estimating a dynamic model of a plant and regulator, where plants decide when to invest in pollution abatement technologies. We use a fixed grid approach to estimate random coefficient specifications. Investment, fines, and HPV designation are costly to most plants. Eliminating dynamic enforcement would raise pollution damages by 164 percent with constant fines or raise fines by 519 percent with constant pollution damages.
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Foreign currency debt is considered a source of financial instability in emerging markets. We propose a theory in which liability dollarization arises from an insurance motive of domestic savers. Since financial crises are associated to depreciations, savers ask for a risk premium when saving in local currency. This force makes domestic currency debt expensive, and incentivizes borrowers to issue foreign currency debt. Providing ex post support to borrowers can alleviate the effect of the crisis on savers' income, lowering their demand for insurance, and, surprisingly, it can reduce ex ante incentives to borrow in foreign currency.
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Social network data are often prohibitively expensive to collect, limiting empirical network research. We propose an inexpensive and feasible strategy for network elicitation using Aggregated Relational Data (ARD): responses to questions of the form "how many of your links have trait k?" Our method uses ARD to recover parameters of a network formation model, which permits sampling from a distribution over node- or graph-level statistics. We replicate the results of two field experiments that used network data and draw similar conclusions with ARD alone.
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Using data from a two-year pricing experiment, we study the impact of subsidy policies on weather insurance take-up. Results show that subsidies increase future insurance take-up through their influence on payout experiences. Exploring mechanisms of the payout effect, we find that for households that randomly benefited from financial education, receiving a payout provides a one-time learning experience that improves take-up permanently. In contrast, households with poor insurance knowledge continuously update take-up decisions based on recent experiences with disasters and payouts. Combining subsidy policies with financial education can thus be effective in promoting long-run insurance adoption.
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"Big data" financial technology raises concerns about market inefficiency. A common concern is that the technology might induce traders to extract others' information, rather than to produce information themselves. We allow agents to choose how much they learn about future asset values or about others' demands, and we explore how improvements in data processing shape these information choices, trading strategies and market outcomes. Our main insight is that unbiased technological change can explain a market-wide shift in data collection and trading strategies. However, in the long run, as data processing technology becomes increasingly advanced, both types of data continue to be processed. Two competing forces keep the data economy in balance: data resolve investment risk, but future data create risk. The efficiency results that follow from these competing forces upend two pieces of common wisdom: our results offer a new take on what makes prices informative and whether trades typically deemed liquidity-providing actually make markets more resilient.
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This paper analyzes how bounded rationality affects monetary and fiscal policy via an empirically relevant enrichment of the New Keynesian model. It models agents' partial myopia toward distant atypical events using a new microfounded "cognitive discounting" parameter. Compared to the rational model, (i) there is no forward guidance puzzle; (ii) the Taylor principle changes: with passive monetary policy but enough myopia equilibria are determinate and economies stable; (iii) the zero lower bound is much less costly; (iv) price-level targeting is not optimal; (v) fiscal stimulus is effective; (vi) the model is "neo-Fisherian" in the long run, Keynesian in the short run.
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The Bartik instrument is formed by interacting local industry shares and national industry growth rates. We show that the typical use of a Bartik instrument assumes a pooled exposure research design, where the shares measure differential exposure to common shocks, and identification is based on exogeneity of the shares. Next, we show how the Bartik instrument weights each of the exposure designs. Finally, we discuss how to assess the plausibility of the research design. We illustrate our results through two applications: estimating the elasticity of labor supply, and estimating the elasticity of substitution between immigrants and natives.
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The spatial layout of cities is an important feature of urban form, highlighted by urban planners but overlooked by economists. This paper investigates the causal economic implications of city shape in India. I measure cities' geometric properties over time using satellite imagery and historical maps. I develop an instrument for urban shape based on geographic obstacles encountered by expanding cities. Compact city shape is associated with faster population growth and households display positive willingness to pay for more compact layouts. Transit accessibility is an important channel. Land use regulations can contribute to deteriorating city shape.
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We construct a structural model of on-the-job search in which workers differ in skills along several dimensions and sort themselves into jobs with heterogeneous skill requirements along those same dimensions. Skills are accumulated when used, and depreciate when not used. We estimate the model combining data from O*NET with the NLSY79. We use the model to shed light on the origins and costs of mismatch along heterogeneous skill dimensions. We highlight the deficiencies of relying on a unidimensional model of skill when decomposing the sources of variation in the value of lifetime output between initial conditions and career shocks.
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We propose a criterion of stability for two-sided markets with asymmetric information. A central idea is to formulate off-path beliefs conditional on counterfactual pairwise deviations and on-path beliefs in the absence of such deviations. A matching-belief configuration is stable if the matching is individually rational with respect to the system of on-path beliefs and is not blocked with respect to the system of off-path beliefs. The formulation provides a language for assessing matching outcomes with respect to their supporting beliefs and opens the door to further belief-based refinements. The main refinement analyzed in the paper requires the Bayesian consistency of on-path and off-path beliefs with prior beliefs. We define concepts of Bayesian efficiency, the rational expectations competitive equilibrium, and the core. Their contrast with pairwise stability manifests the role of information asymmetry in matching formation.
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Journals
- American Economic Review (118)
- Journal of Finance (75)
- Journal of Financial Economics (151)
- Review of Financial Studies (141)
Topic
- Bond (36)
- CEO (15)
- Director (7)
- Capital Structure (2)
- Mergers and Acquisitions (2)
Resource type
- Journal Article (485)