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  • Statistical Inference 统计推断
  • Statistical Computing 统计计算
  • Advanced Probability Theory 高等概率论
  • Advanced Mathematical Statistics 高等数理统计学
  • (Generalized) Linear Models 广义线性模型
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  • Longitudinal Data Analysis 纵向数据分析
  • Foundations of Data Science 数据科学基础

经济代写|宏观经济学代写Macroeconomics代考|Asset bubbles

We’ve discussed how price inflation can break out in the overall economy when the demand for goods exceeds supply. However, perhaps a more dangerous problem is that of asset inflation that is not the result of an excess of overall demand, rather excess dollars being funneled into a certain category of assets. Why? Because when prices for a particular asset, such as housing or gold, are continuously bid upward based on expectations of future growth, borrowers are able to borrow more and more on that artificially inflated collateral. Whether due to a flight to the perceived safety of a certain asset category, such as bonds, or investment opportunity, such as rental real estate, sudden spikes in demand for a particular asset category can result in quickly inflating prices. The artificially created values are unsustainable in the long-term and prices are bound to correct. At a certain point, borrowers cannot support the higher loan payments and the falling collateral values are insufficient to meet bank loan to value ratios, causing banks to call many of those loans.

This is exactly what happened in the 2008 housing crisis. Of course, riskier lending products such as subprime mortgages and the use of mortgage-backed securities to fund much of the expansion of housingrelated debt compounded the problem. But at the core of the crisis was a build-up in housing values which was fueled by loose lending standards and low interest rates, allowing more and more borrowers to qualify for loans. The dream of home ownership became accessible for more people, but the quality of much of the new lending made for an unstable foundation. It wasn’t a problem while the housing market was booming, but things changed quickly when the market corrected.

What led to the fallout? When a few houses in a neighborhood may be in distress or foreclosure at any given time, it will not affect the values of all the other homes. However, when too many houses are distressed at any one time, a tipping point is reached. Market values are determined largely by comparable sale prices. So, too many foreclosures or short sales will drop the average, resulting in lower market values for all of the remaining houses in the neighborhood. This may upset the required loan to collateral ratio of lending institutions who hold mortgages on the affected homes. Suddenly, loans are under water, meaning that the amounts owed on the properties exceed the values of the underlying collateral. Under pressure by regulators, lenders begin calling those loans, accelerating payment of the entire balance, even if the payments are current, possibly pushing more homes into foreclosure. As banks’ income streams taper and balance sheet ratios become unhealthy, the systems freeze up and a widespread deflating spiral in value begins.

经济代写|宏观经济学代写Macroeconomics代考|Looking forward

With so many opinions and conflicting reports circulating about the economy, it is no wonder that so many people find it confusing. Traditional relationships of the money supply to some of the often-used economic indicators have become skewed in recent years, leading some to question their applicability as tools. Indeed, many who are well-versed and educated in economics often have the story wrong. In trying to make sense of it all, the experts will track the multitude of economic indicators and attempt to predict what the economy is going to do next. But things change quickly, and it is difficult to hit a moving target.

Sometimes measures undertaken do not play out as expected. At the end of the day, it all really comes down to confidence. Many economists and others believe that when citizens, including employers, fear that fiscal policy and monetary policy are not conducted in a sensible manner and are not perceived to be pro-growth for the economy, those citizens simply lose confidence in the future.

The resulting fallout can be widespread, from decreases in spending to rising unemployment. Until confidence is regained, spending will remain sluggish. Rather than hire and invest in productive activities, which would entail much risk in times of uncertainty, business owners may tighten up their spending for fear of an uncertain future. When they are seeking safer alternatives for their money than growing their businesses, they tend to invest (speculate) in financial assets (stock, bonds, etc.). Of course, as there may be more and more buyers interested in certain asset classes, those assets’ values are pushed higher and higher, giving rise to the belief that the wealthy are getting wealthier, even though it’s really just rampant speculation driving the values upward.

These build-ups in value can be very fragile and the difficulty is to predict when they are going to peak and move out of some markets. Corrections can happen gradually, but it is more likely to happen with a short period of steep decline. A little hiccup may occur, causing buyers to panic and prices will plummet drastically. The speculative build-up in value is truly fragile and could burst at a moment’s notice. That is why we use the very fitting term, asset bubble.



经济代写|宏观经济学代写Macroeconomics代考|Asset bubbles


这正是 2008 年住房危机中发生的情况。当然,次级抵押贷款等风险较高的贷款产品以及使用抵押贷款支持证券来为大部分住房相关债务的扩张提供资金使问题更加复杂。但危机的核心是住房价值的上涨,这是由宽松的贷款标准和低利率推动的,这使得越来越多的借款人有资格获得贷款。拥有房屋的梦想为更多人所接受,但大部分新贷款的质量却造成了不稳定的基础。房地产市场繁荣时这不是问题,但当市场调整时情况很快发生了变化。


经济代写|宏观经济学代写Macroeconomics代考|Looking forward





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术语 广义线性模型(GLM)通常是指给定连续和/或分类预测因素的连续响应变量的常规线性回归模型。它包括多元线性回归,以及方差分析和方差分析(仅含固定效应)。



有限元是一种通用的数值方法,用于解决两个或三个空间变量的偏微分方程(即一些边界值问题)。为了解决一个问题,有限元将一个大系统细分为更小、更简单的部分,称为有限元。这是通过在空间维度上的特定空间离散化来实现的,它是通过构建对象的网格来实现的:用于求解的数值域,它有有限数量的点。边界值问题的有限元方法表述最终导致一个代数方程组。该方法在域上对未知函数进行逼近。[1] 然后将模拟这些有限元的简单方程组合成一个更大的方程系统,以模拟整个问题。然后,有限元通过变化微积分使相关的误差函数最小化来逼近一个解决方案。





随机过程,是依赖于参数的一组随机变量的全体,参数通常是时间。 随机变量是随机现象的数量表现,其时间序列是一组按照时间发生先后顺序进行排列的数据点序列。通常一组时间序列的时间间隔为一恒定值(如1秒,5分钟,12小时,7天,1年),因此时间序列可以作为离散时间数据进行分析处理。研究时间序列数据的意义在于现实中,往往需要研究某个事物其随时间发展变化的规律。这就需要通过研究该事物过去发展的历史记录,以得到其自身发展的规律。


多元回归分析渐进(Multiple Regression Analysis Asymptotics)属于计量经济学领域,主要是一种数学上的统计分析方法,可以分析复杂情况下各影响因素的数学关系,在自然科学、社会和经济学等多个领域内应用广泛。


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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