ECON1001｜Introductory Microeconomics微观经济学入门 悉尼大学
statistics-labTM为您悉尼大学（英语：The University of Sydney）Introductory Microeconomics微观经济学入门澳洲代写代考和辅导服务！
课程介绍：
Introductory Microeconomics addresses the economic decisions of individual firms and households and how these interact in markets. Economic issues are pervasive in contemporary Australian society. Introductory Microeconomics introduces students to the language and analytical framework adopted in Economics for the examination of social phenomena and public policy issues. Whatever one’s career intentions, coming to grips with economic ideas is essential for understanding society, business and government. Students are given a comprehensive introduction to these ideas and are prepared for the advanced study of microeconomics in subsequent years. Prior knowledge of mathematics is assumed.
Introductory Microeconomics微观经济学入门案例
The NE is $a_1=\frac{32}{15}, a_2=\frac{38}{15}$ (found by solving the two best response functions simultaneously).
(h) Find the Nash equilibrium of the simultaneous move game where player 1 chooses $a_1 \in \Re$, player 2 chooses $a_2 \in \Re$, and the payoffs are
$$
u_1\left(a_1, a_2\right)=-\left(a_1-1\right)^2-\left(a_1-\frac{a_2+2}{2}\right)^2
$$
and
$$
u_2\left(a_1, a_2\right)=-\left(a_2-3\right)^2-\left(a_2-\frac{a_1+2}{2}\right)^2 .
$$
(i) Suppose that in class I presented the following slight variant on Spence’s job market signalling model. Nature first chooses the ability $\theta \in{2,3}$ of player 1 (with both choices being equally likely). Player 1 observes $\theta$ and chooses $e \in{0,1}$. Player 2 then observes $e$ and chooses $w \in \Re$. The players’ utility functions are $u_1(e, w ; \theta)=w-c e / \theta^2$ and $u_2(e, w ; \theta)=-(w-\theta)^2$. For $c=4.25$ this model has both a pooling equilibrium:
$$
\begin{array}{ll}
s_1^(\theta=2)=0 & s_2^(e=0)=2.5 \
s_1^(\theta=3)=0 & s_2^(e=1)=2
\end{array}
$$
$$
\mu_2(\theta=2 \mid e=0)=0.5
$$
$$
\mu_2(\theta=2 \mid e=1)=1
$$
and a separating equilibrium:
$$
\begin{array}{lll}
s_1^(\theta=2)=0 & s_2^(e=0)=2 & \mu_2(\theta=2 \mid e=0)=1 \
s_1^(\theta=3)=1 & s_2^(e=1)=3 & \mu_2(\theta=2 \mid e=1)=0
\end{array}
$$
Suppose that after class two students come up to you in the hallway and ask you to settle an argument they are having about whether the equilibria fail the Cho-Kreps Intuitive Criterion. Assume that Irving argues
The pooling equilibrium violates the intuitive criterion. The $\theta=3$ type could make a speech saying ‘I am choosing $e=1$. I know you are supposed to believe that anyone who gets an education is the low type, but this is crazy. The $\theta=2$ type would be worse off switching to $e=1$ even if you did choose $w=3$. I, on the other hand, being the $\theta=3$ type will be better from having switched to $e=1$ if you choose $w=3$. Hence you should believe that I am the high type and give me a high wage.’
Freddy argues
The separating equilibrium violates the intuitive criterion. It is inefficient. Before he learns his type player 1 could make a speech saying. ‘This equilibrium is crazy. Education is of no value, yet with some probability I am going to have to incur substantial education costs. This is entirely due to your arbitrary belief that if I get no education I am the low type. If you instead believed that I was the low type with probability one-half in this case, then the return to education would be sufficiently low so as to allow the inefficiency to be avoided. Moreover, this more reasonable belief would turn out to be correct as I would then choose $e=0$ regardless of my type.’
1) As part of an irrigation project, you need to install several thousand feet of irrigation pipe in ditches dug in land you are improving. You have $\$ 2,000$ to spend and you have to both hire labor and rent shovels to do the job (you already have the pipe). You are given the following information.
- A ditch digger is paid a wage of $\$ 60$ a day. A ditch digger can dig 300 feet of ditch in a day.
- A shovel rents for $\$ 5.00$ per day.
- A pipe layer is paid a wage of $\$ 70$ per day. A pipe layer can lay 600 feet of pipe in a day.
- $\quad$ Each ditch digger needs to work with one shovel but pipe layers bring their own tools.
a) Construct an efficient allocation of the $\$ 2,000$ – that is, an allocation that allows you to maximize the amount of pipe you can lay with $\$ 2,000$. Explain your reasoning.
Answer: The key idea is that you don’t want to purchase resources that cannot be used.
- You don’t want ditch diggers standing around because they don’t have shovels. This means you have to rent one shovel for every ditch digger you hire.
- Similarly, you don’t want pipe layers standing around because there are no ditches into which they can lay pipe. This means you have to hire one pipe layer for every two ditch diggers (who, together, can dig 600 feet of ditch in a day – the same amount of ditch a pipe layer can fill).
Putting these together, an efficient “unit of input” is two ditch diggers, two shovels and one pipe layer for a total cost of $\$ 65+\$ 65+\$ 70$ or $\$ 200$. So an efficient allocation of $\$ 2,000$ would be 10 of these “units” – i.e. 20 ditch diggers, 20 shovels and 10 pipe layers.
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金融工程代写
金融工程是使用数学技术来解决金融问题。金融工程使用计算机科学、统计学、经济学和应用数学领域的工具和知识来解决当前的金融问题，以及设计新的和创新的金融产品。
非参数统计代写
非参数统计指的是一种统计方法，其中不假设数据来自于由少数参数决定的规定模型；这种模型的例子包括正态分布模型和线性回归模型。
广义线性模型代考
广义线性模型（GLM）归属统计学领域，是一种应用灵活的线性回归模型。该模型允许因变量的偏差分布有除了正态分布之外的其它分布。
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）。
有限元方法代写
有限元方法（FEM）是一种流行的方法，用于数值解决工程和数学建模中出现的微分方程。典型的问题领域包括结构分析、传热、流体流动、质量运输和电磁势等传统领域。
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。
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随机分析代写
随机微积分是数学的一个分支，对随机过程进行操作。它允许为随机过程的积分定义一个关于随机过程的一致的积分理论。这个领域是由日本数学家伊藤清在第二次世界大战期间创建并开始的。
时间序列分析代写
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。
回归分析代写
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，工具箱允许您学习和应用专业技术。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。
