distributed lag

简明释义

已分摊差滞

英英释义

例句

1.When estimating the distributed lag 分布滞后 model, it is crucial to select the appropriate number of lags.

在估计 distributed lag 分布滞后 模型时，选择合适的滞后期数至关重要。

2.The distributed lag 分布滞后 approach allows for a more nuanced understanding of time series data.

使用 distributed lag 分布滞后 方法能够更细致地理解时间序列数据。

3.The distributed lag 分布滞后 effect of interest rates on consumer spending can be significant over time.

利率对消费支出的 distributed lag 分布滞后 效应可能会随着时间显著增加。

4.In econometrics, the concept of distributed lag 分布滞后 models helps in understanding how past values of a variable influence its current value.

在计量经济学中，distributed lag 分布滞后 模型有助于理解一个变量的过去值如何影响其当前值。

5.Researchers often use distributed lag 分布滞后 models to analyze the impact of policy changes over several periods.

研究人员经常使用 distributed lag 分布滞后 模型来分析政策变化在几个时期内的影响。

作文

In the field of economics and statistics, the concept of distributed lag plays a crucial role in understanding how current events influence future outcomes. The term distributed lag refers to the phenomenon where the effects of a variable do not occur immediately but are spread over time. This is particularly relevant when analyzing time series data, where one might want to understand how past values of an independent variable impact a dependent variable over various periods. For instance, consider the impact of monetary policy on inflation rates. When a central bank adjusts interest rates, the immediate effect on inflation may be minimal. However, over time, as businesses and consumers adjust their behavior based on these changes, the effects can become significant. Thus, the relationship between interest rates and inflation is not instantaneous; rather, it is characterized by a distributed lag that can last several months or even years.Understanding distributed lag is essential for economists and policymakers. It allows them to create more accurate models that take into account the delayed effects of policy decisions. For example, if a government increases its spending to stimulate the economy, the immediate boost in economic activity may not fully materialize until later due to various factors such as consumer confidence and business investment decisions. By incorporating the concept of distributed lag into their analyses, economists can better predict the timing and magnitude of economic responses to policy changes.Moreover, the distributed lag model is not limited to economics. It is also applicable in fields such as environmental science, where researchers study the long-term effects of pollutants on ecosystems. In this context, the impact of a pollutant may not be seen right away; instead, it may take years for the full consequences to manifest. By recognizing the distributed lag, scientists can develop more effective strategies for mitigating environmental damage and protecting biodiversity.The application of distributed lag models involves statistical techniques that help in estimating the delayed effects of variables. These models often use lagged variables, which are simply past values of the independent variable, to capture the time-dependent relationships. For instance, a researcher might include the values of a particular variable from the previous year, two years ago, and so forth, to see how they relate to the current value of the dependent variable. This approach enables a more nuanced understanding of the data and helps in making informed predictions.In conclusion, the concept of distributed lag is vital in various disciplines, providing insights into the delayed effects of actions and policies. By acknowledging that not all impacts are immediate, analysts can create more robust models that reflect the complexities of real-world dynamics. Whether in economics, environmental studies, or other fields, recognizing the significance of distributed lag allows for a deeper comprehension of cause-and-effect relationships over time. As we continue to navigate complex systems, the ability to understand and apply the principles of distributed lag will remain a valuable asset for researchers and decision-makers alike.

在经济学和统计学领域，distributed lag的概念在理解当前事件如何影响未来结果方面发挥着至关重要的作用。术语distributed lag指的是一个变量的影响不会立即发生，而是随着时间的推移而分散。这在分析时间序列数据时尤为相关，因为人们可能希望了解独立变量的过去值如何在各个时期影响依赖变量。例如，考虑货币政策对通货膨胀率的影响。当中央银行调整利率时，对通货膨胀的即时影响可能微乎其微。然而，随着时间的推移，企业和消费者根据这些变化调整其行为，影响可能会变得显著。因此，利率与通货膨胀之间的关系不是瞬时的；相反，它的特点是一个可以持续几个月甚至几年的distributed lag。理解distributed lag对经济学家和政策制定者至关重要。它使他们能够创建更准确的模型，考虑到政策决策的延迟效应。例如，如果政府增加支出以刺激经济，经济活动的即时提升可能不会完全实现，直到后来才会由于消费者信心和商业投资决策等各种因素而体现出来。通过将distributed lag的概念纳入分析，经济学家可以更好地预测政策变化对经济反应的时机和幅度。此外，distributed lag模型并不限于经济学。它也适用于环境科学等领域，研究人员研究污染物对生态系统的长期影响。在这种情况下，污染物的影响可能不会立即显现；相反，可能需要数年时间才能全面显现后果。通过认识到distributed lag，科学家可以制定更有效的减轻环境损害和保护生物多样性的策略。应用distributed lag模型涉及统计技术，这些技术有助于估计变量的延迟效应。这些模型通常使用滞后变量，即独立变量的过去值，以捕捉时间依赖关系。例如，研究人员可能会包括某一特定变量的前一年、两年前等的值，以查看它们与依赖变量当前值的关系。这种方法使对数据的理解更加细致，并有助于做出明智的预测。总之，distributed lag的概念在各个学科中都是至关重要的，提供了对行动和政策延迟效应的深入洞察。通过承认并非所有影响都是即时的，分析师可以创建更强健的模型，反映现实世界动态的复杂性。无论是在经济学、环境研究还是其他领域，认识到distributed lag的重要性都使我们能够更深入地理解时间上的因果关系。随着我们继续驾驭复杂系统，理解和应用distributed lag原理的能力将仍然是研究人员和决策者宝贵的资产。