Causal forecasting

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  • This short text is the output of a desire to produce a helpful additional source for my students and from that, perhaps be of use to other similar students and managers of this subject area. After several years of working with classes on Management Decision Making, the need for a short and focused integrative text was clear to me. There are many excellent texts on both the qualitative and quantitative aspects of decision making, but few which address both.

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  • Technological innovations are key causal agents of surprise and disruption. These innovations, and the disruption they produce, have the potential to affect people and societies and therefore government policy, especially policy related to national security. Because the innovations can come from many sectors, they are difficult to predict and prepare for. The purpose of predicting technology is to minimize or eliminate this surprise.

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  • Relatedly, controlling for the forecast error of the change in fiscal policy does not, in our application, provide a way of estimating the causal effect of fiscal policy on growth. Over the two-year intervals that we consider, changes in fiscal policy are unlikely to be orthogonal to economic developments. Thus, the forecast error of fiscal consolidation over our two-year intervals cannot be interpreted as an identified fiscal shock and cannot yield estimates of actual fiscal multipliers. A large literature seeks to identify such exogenous shifts in government spending and revenues.

    pdf48p trinhcaidat 19-04-2013 18 3   Download

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