FORECASTING ECONOMIC TIME SERIES
经济时间序列预测AI 解读 ↓
本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。
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引用量采用 OpenAlex 单条关联记录,不合计多个记录;关联记录可能包含正式发表版本,不等于此版本单独引用。缺失不视为零,引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配,同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列,再参考通用方法与发表日期。
AI 根据所提供的论文材料归类:题名及摘要直接讨论经济时间序列、宏观总量预测和通胀预测的历史表现。
经济时间序列预测AI 解读 ↓
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The prediction of future events and developments is an exciting and perhaps mysterious task, often associated with the aura of prophets and seers instead of probabilistic models and computer screens. The reality of macroeconomic forecasting, however, is quite mundane. Predictions of macroeconomic aggregates play an important role in the decision making of private enterprises, central banks, and governments. In general, forecasts become less popular if they turn out to be inaccurate ex post, and the postwar history of macroeconomic forecasting has had its share of disappointments. For instance, in the early 1980's, economists tested inflation forecasts taken over the previous 20 years and found that the forecasts were poor, partly as a result of the oil price shocks in the 1970's. A recent study (Croushore, 1998) with data up to 1996 provides a more favorable assessment of the quality of inflation forecasts.