The American Economic Review

最新文章

• Does foreign direct investment increase the productivity of domestic firms? In search of spillovers through backward linkages AI翻译
  作者：Javorcik, BS
  作者单位：The World Bank
  摘要：Many countries strive to attract foreign direct investment (FDI) hoping that knowledge brought by multinationals will spill over to domestic industries and increase their productivity. In contrast with earlier literature that failed to find positive intraindustry spillovers from FDI, this study focuses on effects operating across industries. The analysis, based on firm-level data from Lithuania, produces evidence consistent with positive productivity spillovers from FDI taking place through co...
• Estimating the value of a statistical life: The importance of omitted variables and publication bias AI翻译
  作者：Ashenfelter, O; Greenstone, M
  作者单位：Princeton University; National Bureau of Economic Research; Massachusetts Institute of Technology (MIT)
• Toward a consumption tax, and beyond AI翻译
  作者：Gordon, R; Kalambokidis, L; Rohaly, J; Slemrod, J
  作者单位：University of California System; University of California San Diego; University of Minnesota System; University of Minnesota Twin Cities; Urban Institute; University of Michigan System; University of Michigan
• Verifying the solution from a nonlinear solver: A case study: Comment AI翻译
  作者：Shachar, R; Nalebuff, B
  作者单位：Tel Aviv University; Yale University
• Effects of technology on incentive design of share contracts AI翻译
  作者：Pandey, P
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
• Distinguishing informational cascades from herd behavior in the laboratory AI翻译
  作者：Çelen, B; Kariv, S
  作者单位：Columbia University; University of California System; University of California Berkeley
  摘要：This paper reports an experimental test of how individuals learn from the behavior of others. By using techniques only available in the laboratory, we elicit subjects' beliefs. This allows us to distinguish informational cascades from herd behavior. By adding a setup with continuous signal and discrete action, we enrich the ball-and-urn observational learning experiments paradigm of Lisa R. Anderson and Charles Holt (1997). We attempt to understand subjects' behavior by estimating a model that...
• On a political solution to the NIMBY conflict AI翻译
  作者：Feinerman, E; Finkelshtain, I; Kan, I
  作者单位：Hebrew University of Jerusalem
• When does learning in games generate convergence to nash equilibria? The role of supermodularity in an experimental setting AI翻译
  作者：Chen, Y; Gazzale, R
  作者单位：University of Michigan System; University of Michigan; Williams College
  摘要：This study clarifies the conditions under which learning in games produces convergence to Nash equilibria in practice. We experimentally investigate the role of supermodularity, which is closely related to the more familiar concept of strategic complementarities, in achieving convergence through learning. Using a game from the literature on solutions to externalities, we find that supermodular and near-supermodular games converge significantly better than those far below the threshold of super...
• Partnership firms, reputation, and human capital AI翻译
  作者：Morrison, AD; Wilhelm, WJ Jr
  作者单位：University of Oxford; University of Virginia
• Rationalizing the Penn world table: True multilateral indices for international comparisons of real income AI翻译
  作者：Neary, JP
  作者单位：University College Dublin; Centre for Economic Policy Research - UK
  摘要：Real incomes are routinely compared internationally using methods that correct for deviations from purchasing power parity. The most widely used of these is the Geary method which, though theoretically suspect, underlies the Penn World Table. This paper provides a theoretical foundation for the Geary method which I call the GAIA (Geary-Allen International Accounts) system. I show that the Geary method is exact when preferences are non-homothetic Leontief and, more generally, gives a (possibly ...