Results 21 to 29 of about 72,848 (29)
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Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics
The American Economic Review, 2020The credibility revolution in economics has promoted causal identification using randomized control trials (RCT), difference-in-differences (DID), instrumental variables (IV) and regression discontinuity design (RDD). Applying multiple approaches to over
A. Brodeur, Nikolai Cook, A. Heyes
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Methods Matter: p-Hacking and Publication Bias in Causal Analysis in Economics: Comment
The American Economic Review, 2022Brodeur, Cook, and Heyes (2020) study hypothesis tests from economic articles and find evidence for p-hacking and publication bias, in particular for instrumental variable and difference-in-difference studies.
Sebastian Kranz, Peter Pütz
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What is Missing in Asset-Pricing Factor Models?
Social Science Research Network, 2022Our objective is to develop a methodology to price the cross section of asset returns. Despite the hundreds of systematic risk factors considered in the literature (“factor zoo”), there is still a sizable pricing error.
Massimo Dello Preite +3 more
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Foreign Trade Review, 2022
The imposition of restrictive trade policies and consequent fabrication of foreign trade statistics acts as hindrance for effective policy formulations in the developing countries.
Samir Das, A. Biswas
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The imposition of restrictive trade policies and consequent fabrication of foreign trade statistics acts as hindrance for effective policy formulations in the developing countries.
Samir Das, A. Biswas
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South Asian Journal of Macroeconomics and Public Finance, 2021
Determinism and non-linear behaviour in log-return and conditional volatility time series of the stock market index is examined for twenty-six countries.
Zouhaier Dhifaoui
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Determinism and non-linear behaviour in log-return and conditional volatility time series of the stock market index is examined for twenty-six countries.
Zouhaier Dhifaoui
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Alpha Go Everywhere: Machine Learning and International Stock Returns
Social Science Research Network, 2020We apply machine learning techniques to predict international stock returns using firm characteristics. Market-specific training is important, as neural network models (NNs) achieve stronger results when they are trained in each market separately than ...
Darwin Choi, Wenxi Jiang, Chao Zhang
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Greek GDP Forecasting Using Bayesian Multivariate Models
Social Science Research NetworkBuilding on a proper selection of macroeconomic variables for constructing a Gross Domestic Product (GDP) forecasting multivariate model (Kazanas, 2017), this paper evaluates whether alternative Bayesian model specifications can provide greater ...
Zacharias G. Bragoudakis +1 more
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Unconventional Monetary Policy and the Anchoring of Inflation Expectations
Social Science Research Network, 2017The effects of the unconventional monetary policy (UMP) measures undertaken by the U.S. Federal Reserve (and other major central banks) remain a crucial topic for research.
Matteo Ciccarelli +2 more
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American Economic Review: Insights, 2018
A statistician takes an action on behalf of an agent, based on the agent’s self-reported personal data and a sample involving other people. The action that he takes is an estimated function of the agent’s report.
K. Eliaz, R. Spiegler
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A statistician takes an action on behalf of an agent, based on the agent’s self-reported personal data and a sample involving other people. The action that he takes is an estimated function of the agent’s report.
K. Eliaz, R. Spiegler
semanticscholar +1 more source