assignmentutor-lab™ 为您的留学生涯保驾护航 在代写经济统计Economic Statistics方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写经济统计Economic Statistics代写方面经验极为丰富，各种代写经济统计Economic Statistics相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|经济统计代写Economic Statistics代考|Methodological Challenges

Because the CPI is designed to use its own surveyed data, BLS has encountered some challenges related to alternative data congruence with CPI methodology. The primary obstacle to dealing with transaction data in the CPI has been dealing with product lifecycle effects – that is, when products exhibit systematic price trends in their lifecycle. For certain goods such as apparel and new vehicles, a product is typically introduced at a high price on the market and gradually discounted over time. At the point where the good exits, the price has been discounted substantially and may be on clearance. In the CPI, a similar good is selected, and its price is compared with that of the exiting good. The price relative constructed by comparing these two items typically implies a large increase in price from the exiting good to its replacement. This large increase will offset the incremental price declines over the prior product’s lifecycle. While this method works in the CPI’s fixed weight index, Williams and Sager (2019) found that a price comparison between exiting and new goods in a dynamically weighted index may undercorrect in situations where an exiting item is a low-inventory item on clearance, or overcorrect in other situations, and that multilateral price index methods designed to address chain drift, specifically the rolling year Gini Eltetö Köves Szulc (GEKS) index discussed in Ivancic, Diewert, and Fox (2011), did not remedy downward drift associated with product lifecycles. Greenlees and McClelland (2010) found that hedonic price indexes often exhibit the same drift as matched-model indexes. Conventional hedonic methods also do not address product lifecycle effects. Silver and Heravi (2005) found that coefficient estimates from hedonic regressions may be affected by product cycles, which they attributed to pricing strategies, including the dumping of obsolete merchandise. More generally, the implications of product lifecycles have not received much attention in the price index literature, with some exceptions such as Melser and Syed (2016) and Ehrlich et al. (this volume).

## 统计代写|经济统计代写Economic Statistics代考|Operational Challenges

While timeliness is often listed as one of the virtues of Big Data, it can be an issue for both corporate and secondary sources – BLS needs for a monthly index are not always a high priority or even possible for data vendors and corporate headquarters. At times, BLS risks publication delays or must accept truncating observations from the end of the month. In other cases, the data are only available with a lag – this is particularly the case with medical claims data, as described in the Physicians and Hospitals Services case. To the extent that the CPI is making use of data from multiple sources that come in with varying lags, BLS may need to reconsider the CPI as a measure that is published and never revised, taking into consideration the impact that might have on use of the CPI for cost-of-living-adjustments and contract escalation.

BLS has control over all data processing of traditionally collected data and has many procedures and systems in place to control the overall quality of the micro data collected and used in CPI’s outputs. With alternative data, BLS has to rely on others who do not always have the same data quality needs. Data cleanliness can be a risk with vendor data, descriptive data are not always collected, and data comparability over time is not guaranteed. In addition, continuation of any vendor data source is not guaranteed and could disappear without any warning; thus, BLS spends some time looking at these risks and how best to mitigate them. BLS creates fallback plans but recognizes that their implementation-if needed-may not be fast enough or smooth enough to prevent temporary gaps in coverage in the CPI.
In order for an alternative data source to be incorporated into the aggregate CPI measure, the data must be mapped into CPI’s item categorization and geographic structure. This is simple when a dataset’s coverage directly corresponds to a CPI item category. However, in many cases, transaction data cover a broad range of items and BLS must concord these items to the CPI structure based on the company’s categorizations and item descriptions. BLS developed a machine-learning system to assist in the CorpX categorizations, which has greatly improved its ability to handle large datasets with hundreds of thousands of items.

# 经济统计代考

## 统计代写|经济统计代写Economic Statistics代考|Operational Challenges

BLS 控制了传统收集数据的所有数据处理，并制定了许多程序和系统来控制在 CPI 输出中收集和使用的微观数据的整体质量。对于替代数据，BLS 必须依赖于其他人并不总是具有相同的数据质量需求。数据清洁度可能是供应商数据的风险，并不总是收集描述性数据，并且无法保证数据随时间的可比性。此外，不保证任何供应商数据源的继续存在，并且可能会在没有任何警告的情况下消失；因此，BLS 花一些时间研究这些风险以及如何最好地减轻它们。BLS 制定了后备计划，但承认其实施（如果需要）可能不够快或不够顺畅，无法防止 CPI 覆盖范围出现暂时性缺口。

## 有限元方法代写

assignmentutor™作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

assignmentutor™您的专属作业导师
assignmentutor™您的专属作业导师