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the expected loss of forestry income, self-insurance, uncertainty characterizing the probability of occurrence of natural …
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It is a commonly held view that democracy is better at safeguarding environment while autocracy is predatory in nature, and is thus insensitive towards environment. However, others argue that democracy leads to environmental degradation. We revisit this contentious relationship between regime...
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This paper develops a machine-learning method that allows researchers to estimate heterogeneous treatment effects with panel data in a setting with many covariates. Our method, which we name the dynamic causal forest (DCF) method, extends the causal-forest method of Wager and Athey (2018) by...
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Machine Learning models are often considered to be "black boxes" that provide only little room for the incorporation of theory (cf. e.g. Mukherjee, 2017; Veltri, 2017). This article proposes so-called Dynamic Factor Trees (DFT) and Dynamic Factor Forests (DFF) for macroeconomic forecasting, which...
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