经济代写|产业经济学代写Industrial Economics代考|ECON3121

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产业经济学是关于公司、行业和市场的研究。它研究各种规模的公司–从当地的角落商店到沃尔玛或乐购这样的跨国巨头。它还考虑了一系列的行业,如发电、汽车生产和餐馆。

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我们提供的产业经济学Industrial Economics及其相关学科的代写,服务范围广, 其中包括但不限于:

  • 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
  • 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
经济代写|产业经济学代写Industrial Economics代考|ECON3121

经济代写|产业经济学代写Industrial Economics代考|Consumer goods industry

The textile and wearing apparel industry remained sluggish. From January to May 2016 , the industrial value added of the textile industry, the Manufacture of Textile, Wearing Apparel and Accessories as well as the leather, fur and feather products and shoemaking industry grew $7.4,5.2$ and $3.7 \%$ year on year respectively, rising by $-0.3,0$ and $0.1$ percentage points respectively as against the first quarter of this

year and by $0.4,0.8$ and $-1.2$ percentage points as against the growth rates in the whole year of $2015 .$

The textile and wearing apparel industry was greeted with a slight pickup in its earnings growth rate. From January to May 2016 , the total profits of the textile industry and the Manufacture of Textile, Wearing Apparel and Accessories grew $6.9$ and $7.3 \%$ respectively, rising by $0.2$ and $0.4$ percentage points respectively over the first quarter of this year and by $1.8$ and $3.3$ percentage points as against the growth rates in the whole year of 2015 . From January to May, the total profits of the leather, fur and feather products and shoemaking industry grew $4.9 \%$, decreasing $2.4$ percentage points as against the first quarter of this year.

The textile and wearing apparel industry first took a turn for the better. From January to May 2016 , the export delivery values of the textile industry and the leather, fur and feather products and shoemaking industry grew $0.7$ and $1.9 \%$ year on year respectively, rising by $0.5$ and $1.3$ percentage points respectively over the first quarter of this year; the Manufacture of Textile, Wearing Apparel and Accessories continued the negative growth trend in its export volume, but the decreasing amplitude tended to narrow (Table $1.7$ and Fig. 1.15).

Differentiation of the food industry: From January to May 2016 , the industrial value added of the farm and sideline food processing industry, the food manufacturing industry and the wine, beverage and refined tea manufacturing industry grew $6.2,8.7$ and $6.1 \%$ respectively year on year, $0.6,0.1$ and $-1.1$ percentage points higher as against the first quarter of this year respectively and rising by $0.7$, $1.2$ and $-1.6$ percentage points respectively as against the whole year of 2015 . Since the beginning of this year, the growth rate of industrial value added of tobacco industry witnessed a sharp decline, but the decreasing amplitude tended to narrow on a monthly basis. From January to May, the value added of tobacco industry dropped $12.0 \%$ year on year, narrowing by $1.4$ percentage points as against the first quarter of this year. In the first quarter of 2016 , the drastic downsizing of cigarette production in China led to severe situation of commercial sales of tobacco products.

经济代写|产业经济学代写Industrial Economics代考|Profits dropped

Profits dropped in tobacco industry and wine, beverage and refined tea manufacturing industries but improved markedly in farm and sideline food processing industry and food manufacturing industry. From January to May, the prime operating revenue and total profit of the farm and sideline food processing industry grew $5.7 \%$ and $11.7 \%$ year on year respectively, $0.6$ and $-0.4$ percentage points respectively higher than the first quarter of this year and $2.2$ and $5.3$ percentage points respectively over the previous year; the prime operating revenue and total profit of the food manufacturing industry grew $7.8$ and $15.1 \%$ year on year respectively, $0.3$ and $-2.4$ percentage points higher than the first quarter of this year and $1.5$ and $6.0$ percentage points respectively higher than the previous year; the prime operating revenue and total profit of the wine, beverage and refined manufacturing industries grew $5.6$ and $3.0 \%$ year on year respectively, $1.1$ and $9.0$ percentage points lower than the first quarter of this year and $0.8$ and $4.5$ percentage points lower than the previous year; and the prime operating revenue and total profit of the tobacco industry declined $11.7$ and $24.0 \%$ year on year respectively, $0.6$ and 7.0 percentage point lower than the first quarter of this year and $17.2$ and $22.6$ percentage points lower than the previous year.

The export volume of the farm and sideline food processing industry and the food manufacturing industry turned for the better while the export growth rate of the tobacco industry and the wine, beverage and refined tea manufacturing industries just reversed. From January to May 2016, the export delivery value of the farm and sideline food processing industries and the food manufacturing industry grew $0.0 \%$ and $10.5 \%$ year on year respectively, $1.9$ and $0.1$ percentage point respectively higher than the first quarter of this year, and $6.8$ and $9.4$ percentage points respectively higher than the previous year; the export delivery value of the tobacco industry and the wine, beverage and refined tea manufacturing industries grew $6.1$ and $9.0 \%$ year on year respectively, descending by $5.6$ and $34.3$ percentage points respectively from the first quarter of this year (Table 1.8).

The pharmaceutical industry maintained a high-level growth. The pharmaceutical industry is typically viewed as an industry against the economic circle, i.e. the more sluggish the economic growth is, the greater the demand for medicines will become and the faster the pharmaceutical industry will grow. From January to May 2016 , the Industrial value added of the pharmaceutical industry grew $10.2 \%$ year on year, $1.0$ percentage point higher than the first quarter of this year and $0.3$ percentage points higher than the previous year (Fig. 1.16).

经济代写|产业经济学代写Industrial Economics代考|Forecast and Prospect of Industrial

Variations in the industrial economics operation may take place in tendency and cycle. Since the year of 2010 , the growth rate of China’s industrial economics seemingly has the tendency towards slowing down. While the tendency variable factors played a leading role in the slowdown of industrial economics operation, the cyclical factors played a key role. Main factors acting on tendency variation included: (i) capital accumulation, (ii) variation in labor force and its qualities, and (iii) technical progress. Cyclical variation was largely subject to short-time simulative monetary and fiscal policy and to variability of requirement space. Currently, due to declining marginal rate of capital return, there would be a downturn in the pace of capital accumulation. Variation in labor force and its qualities took little effect in a short term, but technical progress would hopefully become a supporting factor for this round of industrial economic growths. The drop-offs in global demand and domestic investment constituted a realistic basis for the government to implement a proactive fiscal and monetary policy.

In this report, the time sequence model is used to simulate the growth rates of industrial economics under various circumstances. According to the simulation results, (1) the slowing down tendency will continue; $(2)$ the proactive financial and monetary policy plays a significant role in easing the fluctuations of industrial economics growth; and (3) the technical progress will be the main supporting force for industrial economic growth.

经济代写|产业经济学代写Industrial Economics代考|ECON3121

产业经济学代考

经济代写|产业经济学代写Industrial Economics代考|Consumer goods industry

纺织服装行业持续低迷。2016年1月至2016年5月,纺织工业、纺织服装及辅料制造业以及皮革、毛皮、羽绒制品和制鞋业的工业增加值增长7.4,5.2和3.7%同比分别上升−0.3,0和0.1与第一季度相比分别有几个百分点

年及以后0.4,0.8和−1.2与全年增长率相比的百分点2015.

纺织服装行业盈利增速小幅回升。2016年1-5月,纺织行业和纺织服装辅料制造业利润总额增长6.9和7.3%分别上升0.2和0.4个百分点分别比今年一季度和1.8和3.3与 2015 年全年增长率相比的百分点。1-5月,皮革、毛皮、羽绒制品和制鞋业利润总额增长4.9%, 递减2.4与今年一季度相比。

纺织服装行业先是好转。2016年1-5月,纺织业和皮革、毛皮、羽绒制品、制鞋业出口交货值增长0.7和1.9%同比分别上升0.5和1.3分别比今年一季度高出一个百分点;纺织服装及辅料制造业出口量继续负增长,但降幅趋于收窄(表1.7和图 1.15)。

食品产业分化:2016年1-5月,农副食品加工业、食品制造业和酒、饮料、精制茶制造业工业增加值增长6.2,8.7和6.1%分别同比,0.6,0.1和−1.1分别比今年一季度高出一个百分点,增长了0.7, 1.2和−1.6分别与2015年全年相比。今年以来,烟草行业工业增加值增速大幅回落,但降幅逐月收窄。1-5月烟草业增加值下降12.0%同比缩小1.4与今年一季度相比。2016年第一季度,中国卷烟产量大幅缩减导致烟草制品商业销售形势严峻。

经济代写|产业经济学代写Industrial Economics代考|Profits dropped

烟草业和酒、饮料、精制茶制造业利润下降,农副食品加工业和食品制造业明显好转。1-5月农副食品加工业主营业务收入和利润总额增长5.7%和11.7%分别同比,0.6和−0.4分别高于今年一季度和2.2和5.3分别比上年增加一个百分点;食品制造业主营业务收入和利润总额增长7.8和15.1%分别同比,0.3和−2.4比今年一季度高出几个百分点1.5和6.0分别比上年高出一个百分点;葡萄酒、饮料和精炼制造业主营业务收入和利润总额增长5.6和3.0%分别同比,1.1和9.0比今年一季度低几个百分点,0.8和4.5比上年低个百分点;烟草业主营业务收入和利润总额下降11.7和24.0%分别同比,0.6比今年一季度下降 7.0 个百分点,17.2和22.6比上年低几个百分点。

农副食品加工业和食品制造业出口量向好,烟草业、酒、饮料和精制茶制造业出口增速逆势上扬。2016年1-5月农副食品加工业和食品制造业出口交货值增长0.0%和10.5%分别同比,1.9和0.1分别比今年一季度高出一个百分点,6.8和9.4分别比上年高出一个百分点;烟草业和酒、饮料、精茶制造业出口交货值增长6.1和9.0%同比分别下降5.6和34.3与今年第一季度相比分别有几个百分点(表 1.8)。

医药行业保持高位增长。医药行业通常被视为一个逆经济循环的行业,即经济增长越慢,药品需求量越大,医药行业增长越快。2016年1-5月,医药行业工业增加值增长10.2%比去年同期,1.0比今年一季度高出一个百分点,0.3个百分点高于上年(图 1.16)。

经济代写|产业经济学代写Industrial Economics代考|Forecast and Prospect of Industrial

产业经济运行的变化可能呈趋势性和周期性。2010年以来,中国工业经济增速似乎有放缓的趋势。趋势变量因素在工业经济运行放缓中起主导作用,而周期性因素则起关键作用。影响趋势变化的主要因素包括:(i)资本积累,(ii)劳动力及其素质的变化,以及(iii)技术进步。周期性变化在很大程度上受制于短期模拟货币和财政政策以及需求空间的可变性。目前,由于资本边际收益率的下降,资本积累的步伐将会放缓。劳动力及其素质的变化在短期内影响不大,但技术进步有望成为这一轮工业经济增长的支撑因素。全球需求和国内投资的下降,为政府实施积极的财政和货币政策提供了现实基础。

在本报告中,时间序列模型用于模拟工业经济在各种情况下的增长率。根据模拟结果,(1)减速趋势将继续;(2)积极的金融货币政策对缓解产业经济增长波动具有重要作用;(三)技术进步将成为工业经济增长的主要支撑力量。

经济代写|产业经济学代写Industrial Economics代考 请认准statistics-lab™

统计代写请认准statistics-lab™. statistics-lab™为您的留学生涯保驾护航。

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。

R语言代写问卷设计与分析代写
PYTHON代写回归分析与线性模型代写
MATLAB代写方差分析与试验设计代写
STATA代写机器学习/统计学习代写
SPSS代写计量经济学代写
EVIEWS代写时间序列分析代写
EXCEL代写深度学习代写
SQL代写各种数据建模与可视化代写

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