ECMT 674作业代做、代写Economic Forecasting作业、代写R/RStudio课程作业、代做R程序作业帮做Haskell程序|代做SPSS

ECMT 674: Economic ForecastingFinal Research Paper; Due Date: April 29, 2019 (end of the day, i.e. 11:59pm)This is a team assignment that could be conducted in teams of at most two. Please mark every person’sname on the document that is being returned. I would also like to get the signatures of every team memberunder a statement: “I have contributed to this assignment to a sufficient degree to get equal credit withmy teammates, and all other collaborations are properly acknowledged.” Please submit the files througheCampus. Everyone in the team will receive the same grade.You will need R/RStudio to complete this assignment. You could also use Excel to do the data work forthe assignment. I would like you to turn in one file containing the content of the report as well as figures andtables. Throughout the semester you have used R Markdown to generate the reports, and you should do thesame in this assignment as well. Please name your files in an informative manner: an example would be thecourse name/number + the first initials of the team members + the assignment number + a file identifier.In this assignment you will be looking at GDP growth forecasts and recession probabilities using theinformation in the US yield curve. Some useful references for the project are below. The list is not limitedto the references below, there are many papers about this topic. Some of the references within these linkscould be useful as well (some of the articles below are available for reading only if you are connected to theuniversity network): the Cleveland Fed athttps://www.clevelandfed.org/our-research/indicators-and-data/yield-curve-and-gdpgrowth.aspx the San Francisco Fed athttps://www.frbsf.org/economic-research/publications/economic-letter/2018/august/information-in-yield-curve-about-future-recessions/ the Journal of Finance athttp://www.jstor.org/stable/pdf/2328836.pdf?refreqid=excelsior:5a689814d6f94399d93ac94641339695 the Journal of Applied Econometrics athttps://onlinelibrary.wiley.com/doi/full/10.1002/jae.2485There are also various news media articles on the flattening of the yield curve and its implications for arecession in the US. Consider recent articles in Bloomberg and Forbes: (i) https://www.bloomberg.com/news/articles/2018-04-09/yield-curve-entering-danger-zone-as-inversion-reappears-on-radar;(ii) https://www.forbes.com/sites/simonmoore/2019/03/23/the-yield-curve-just-inverted-putting-the-chance-of-a-recession-at-30/#312c122413ab, among others.The overall objective of this project is to evaluate how well the slope of the yield curve predicts changesin real output growth, and consequently, how well it forecasts recessions. The literature has taken differentapproaches to it: (i) you can forecast the GDP growth and its forecast distribution, figure out the probabilityassociated with negative GDP growth. Ideally, you would like to figure out the probability associated withtwo consecutive quarter negative GDP growth. (ii) You can model the probabilities directly, by defining therecessions consistent with the definition used by the National Bureau of Economic Research (NBER, for areference see https://www.nber.org/cycles/main.html). The idea here is that the recession probabilitiesare directly predicted by the spread. Either approach would be acceptable.1Your analysis should touch on model selection, proper transformation of the variables, include some discussionon how the proper transformation is selected. It should include an out-of-sample forecast evaluationexercise. You can experiment with various spreads as well as various estimation schemes, i.e. fixed, rolling,recursive forecasting. Given the references for the assignment and what you have learned from the currentproject (and perhaps homework 4), you should provide your insights on how good the yield curve is forpredicting recessions.The paper should not be more than 15 pages long and should use reasonable font size, spacing andmargins. The text should be at most 5 pages, the rest can be allocated to figures and tables.2本团队核心人员组成主要包括BAT一线工程师，精通德英语！我们主要业务范围是代做编程大作业、课程设计等等。我们的方向领域：window编程 数值算法 AI人工智能 金融统计 计量分析 大数据 网络编程 WEB编程 通讯编程 游戏编程多媒体linux 外挂编程 程序API图像处理 嵌入式/单片机 数据库编程 控制台 进程与线程 网络安全 汇编语言 硬件编程 软件设计 工程标准规等。其中代写编程、代写程序、代写留学生程序作业语言或工具包括但不限于以下范围:C/C++/C#代写Java代写IT代写Python代写辅导编程作业Matlab代写Haskell代写Processing代写Linux环境搭建Rust代写Data Structure Assginment 数据结构代写MIPS代写Machine Learning 作业 代写Oracle/SQL/PostgreSQL/Pig 数据库代写/代做/辅导Web开发、网站开发、网站作业ASP.NET网站开发Finance Insurace Statistics统计、回归、迭代Prolog代写Computer Computational method代做因为专业，所以值得信赖。如有需要，请加QQ：99515681 或邮箱：[email protected] 微信：codehelp QQ：99515681 或邮箱：[email protected] 微信：codehelp