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• 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|Evaluating the Estimated State’s Predictive Content

The fact that the CES and ADP-FRB series receive roughly equal weight when extracting the common signal supports the idea that combining the signal from both series can contribute to our understanding of “true” employment growth. It is of interest to know how useful the state estimate is for forecasting applications, so in this section we evaluate the ability of the real-time state estimate to forecast the fully revised CES. Even though CES is only a noisy estimate of true employment growth, it is widely tracked as an indicator of the labor market, and success in forecasting it can help bolster the case that the state estimate is picking up usable signal.

For the forecasting exercises, we employ a framework similar to that found in equation (1), without the additional controls. The dependent variable is the current vintage of the CES estimate. As independent variables we include various combinations of the ADP-FRB employment estimate, the CES employment estimate, the smoothed state as estimated using both ADP-FRB and CES, and the smoothed state as estimated by CES only. This final variable is included to distinguish the time-averaging effect of the statespace model from the additional information included in ADP-FRB. If the ADP-FRB series has no information, then CES and the smoothed state based on CES alone ought to be the only relevant predictors. Importantly, all the independent variables are real-time estimates, which means that the state-space estimates include no future information.

The results of this exercise can be found in table 5.5. The first two columns include the $t+1$ current vintage CES employment value as its dependent variable. The second column adds the CES state as an additional explanatory variable. The third column contains the average employment growth over $t+1, t+2, t+3$ – i.e., the average growth rate of the next three months of employment. Estimated together, the only variable that is statistically significant across all three specifications is the ADP-CES state. ${ }^{30}$ The horserace results indicate that when comparing employment-based indicators of future CES readings of employment gains, the combination of the ADPFRB series and the past CES gains provides the most information about future employment.

## 统计代写|经济统计代写Economic Statistics代考|Coverage and Representativeness Biases

We now examine bias with respect to coverage and representativeness for the Reed vacancies, as well as describing the steps we take to reduce these biases.

These two types of bias exist at the aggregate level. Vacancies posted online are unlikely to cover 100 percent of vacancies advertised in the economy, and the Reed stock of vacancies, obtained from equation (1), has aggregate coverage of around 40 percent relative to the ONS Vacancy Survey. In addition, the composition of the vacancies that are posted online is likely to be quite different from reality. These problems of bias and coverage exist for all job vacancy data based on job advertisements, including the widely used JobCentre Plus data, and have long existed in the empirical literature on job vacancies. Prior to the advent of national vacancy statistics, most previous empirical work was based on the use of vacancies advertised at job centers, which have the same problems though for different reasons.

Additionally, vacancies as posted online do not have some of the problems that data collected by surveys have. Surveys are likely to have non- or incomplete-response bias, overestimation of the vacancies posted by large firms, underestimation of vacancies from recently created firms and, when comparing vacancies and unemployment, could be biased by frequency mismatch between surveys (Abraham 1983). Nonresponse bias is not relevant for job advertisements posted online; differentials due to firm size may exist but are more likely to be caused by the ability to advertise positions (rather than size itself), and as postings are typically at daily frequency there can be no large role for frequency mismatch. The cost of posting advertisements online with a recruiter means that the problem of phantom vacancies, for which no job ever existed, is likely to be small.

There are many factors that affect the coverage of online job vacancies.Technological diffusion is one; given that no vacancies were posted on the World Wide Web before 1990, and that newspaper circulations have fallen substantially since the 1980 s, there has been a drift in job vacancies from ads in newspapers to ads placed online. Over time, the coverage of online vacancies has improved. Barnichon (2010) shows that this drift in coverage closely follows the S-shape typical of technological diffusion for the US, and that it also closely follows the similarly S-shaped fraction of internet users in that country. At the start of the period we study, 78 percent of the UK population were internet users, suggesting that the equivalent transition in the UK was already well under way by $2008 . .^7$ Another reason why there are coverage differences for online ads posted with a recruiter versus surveys is the cost of posting vacancies online. Cajner and Ratner (2016) find that changes in the cost of posting vacancies online had a significant influence on the aggregate stock of vacancies as represented by online sources versus other sources. The (time-dependent) reweighting we will use will correct for both of these biases. ${ }^8$

# 经济统计代考

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## 有限元方法代写

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## 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。

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