经济代写| Good theories and the demand for dat 宏观经济学代写
经济代写
Economically relevant data does not present itself automatically. They need to be collected via the regular government machinery and/or through surveys by the government, private research organisations or individual researchers. Irrespective of who collects the data, the ‘which data?’ question depends on the particular research question or, in the case of the government, on the relevant ministry. Our tax data is with the Ministry of Income Tax. And the collection of agricultural statistics is done by the Ministry of Agriculture and Farmers Welfare.
Often, with research organisations and individual researchers, the ‘which data?’ question depends on the theoretical framework directly or indirectly underpinning their research (and survey). Let me use an anecdote to illustrate the point. After listening to Werner Heisenberg’s talk on quantum mechanics in 1926, Albert Einstein presciently told him, “Whether you can observe a thing or not depends on the theory which you use. It is the theory which decides what can be observed” (p. 40); this conversation was reported by Heisenberg in his in a 1989 volume titled From a Life of Physics. In other words, a good theory can drive the quest for better policies by demanding more relevant data. Of course, the conceptual clarity and coherence provided by good theories must necessarily be supplemented with contextual information.
Although the measurement of GDP is now commonplace, there are still debates on what ought to be included and excluded in it, and rightly so (recall, as noted in Section $2.2$, the demand for time-use surveys to obtain an estimate of women’s unpaid labour). The following passage from Richard Stone’s 1951 in empirical measurement.
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These empirical constructs are well illustrated by the example of the income of an individual or a nation. No amount of searching in primary records, that is the originating entries, actual or imputed, in the books of a firm or individual, will enable us to detect the income that has been made. To ascertain income, it is necessary to set up a theory from which income is derived as a concept by postulation and then associate this concept with a certain set of primary facts. To be sure the theory must take into account possible primary facts if it is to be of any practical use since if it does not the theoretical concept of income will be left hanging in the air, with no empirical correlate. But some theory as do the individuals and pieces of equipment which are largely responsible for generating it. (p. 9)
Similarly, in the next few paragraphs, it will be argued that, given the Indian realities, we need better empirical measures for the Indian macroeconomy.
In Section 3.3, we posed the question ‘What is money?’ The answer given by the RBI is that money refers to the stock of currency in circulation, demand deposits with banks and savings deposits with post office banks. However, now that you have learnt about the presence of informal money in the previous section (Section 6.4), how can a definition of money for the Indian macroeconomy not include informal money?
And although an explanation for the presence of unemployment in a competitive economy was provided in Section 4.2, you now know about the extent of informal employment in India from the previous section (Section $6.4$ ). specific to the nature of employment-self-employed, contract, regular salaried-which will be published at more frequent intervals?
Table $2.1$ captured the inter-sectoral relations of the Indian economy Such a meso approach to understanding an economy, as pointed out already, is especially found in the theories of Quesnay, Marx and Sraffa, and in the applied work of Leontief. The macro approach to understanding an economy gives rise to concepts such as aggregate output and employment. While the wide acceptance of the macro approach has led to the generation of frequent GDP data, the relative neglect of the meso approach, particularly in India, has meant a decline in the demand for inter-sectoral data and, consequently, its supply. Moreover, as Stone writes in The Role of Measurement in Economics (1951), “it is necessary to collect information which will reflect theoretical variables defined in advance, rather than to rely on the manipulation of existing
经济相关数据不会自动呈现。它们需要通过常规的政府机制和/或通过政府、私人研究组织或个人研究人员的调查来收集。无论谁收集数据,“哪些数据?”问题取决于特定的研究问题,或者就政府而言,取决于相关部委。我们的税务数据来自所得税部。农业统计数据的收集由农业和农民福利部完成。
通常,对于研究组织和个人研究人员来说,“哪些数据?”问题取决于直接或间接支持他们的研究(和调查)的理论框架。让我用一个轶事来说明这一点。在 1926 年听完维尔纳·海森堡关于量子力学的演讲后,阿尔伯特·爱因斯坦有先见之明地告诉他:“你能不能观察到一个东西,取决于你使用的理论。理论决定了能观察到的东西”(第 40 页) );海森堡在他 1989 年的一本书《从物理学的一生》中报道了这段对话。换句话说,一个好的理论可以通过要求更多相关数据来推动对更好政策的追求。当然,好的理论所提供的概念清晰性和连贯性必须辅以上下文信息。
尽管 GDP 的测量现在已经司空见惯,但仍然存在关于应该包含和排除哪些内容的争论,这是正确的(回想一下,如第 2.2 节所述,对时间使用调查的需求来获得女性的估计值)无偿劳动)。以下段落来自 Richard Stone 1951 年的经验测量。
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宏观经济
个人或国家收入的例子很好地说明了这些经验结构。在原始记录中的任何搜索,即在公司或个人的账簿中实际或推算的原始条目,都无法使我们检测到已获得的收入。为了确定收入,必须建立一个理论,将收入作为一个概念推导出来,然后将这个概念与一组基本事实联系起来。可以肯定的是,如果该理论要具有任何实际用途,则必须考虑可能的主要事实,因为如果不这样做,则收入的理论概念将悬而未决,没有经验相关性。但是一些理论,以及主要负责产生它的个人和设备。 (第 9 页)
同样,在接下来的几段中,将论证,鉴于印度的现实,我们需要对印度宏观经济采取更好的实证措施。
在第 3.3 节中,我们提出了“金钱是什么?”这个问题。印度储备银行给出的答案是,货币是指流通中的货币存量、银行活期存款和邮局银行的储蓄存款。但是,既然您已经在上一节(第 6.4 节)中了解了非正式货币的存在,那么印度宏观经济的货币定义怎么能不包括非正式货币呢?
尽管在第 4.2 节中提供了对竞争经济中存在失业的解释,但您现在从上一节(第 6.4 美元)中了解了印度非正规就业的程度。具体到就业性质——自雇、合同、固定工资——哪个会更频繁地发布?
表 2.1 美元记录了印度经济的跨部门关系 正如已经指出的那样,这种理解经济的中观方法在 Quesnay、Marx 和 Sraffa 的理论以及 Leontief 的应用著作中尤为常见。理解经济的宏观方法产生了诸如总产出和就业等概念。虽然宏观方法的广泛接受导致 GDP 数据频繁生成,但相对忽视中观方法,尤其是在印度,这意味着对跨部门数据的需求下降,从而导致其供应下降。此外,正如斯通在经济学测量的作用(1951)中所写,“有必要收集能够反映预先定义的理论变量的信息,而不是依赖于对现有的
经济代考
宏观经济学,是以国民经济总过程的活动为研究对象,主要考察就业总水平、国民总收入等经济总量,因此,宏观经济学也被称做就业理论或收入理论。 宏观经济学研究的是经济资源的利用问题,包括国民收入决定理论、就业理论、通货膨胀理论、经济周期理论、经济增长理论、财政与货币政策。
其他相关科目课程代写:组合学Combinatorics集合论Set Theory概率论Probability组合生物学Combinatorial Biology组合化学Combinatorial Chemistry组合数据分析Combinatorial Data Analysis
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宏观经济学是经济学的一个分支,它研究的是一个整体经济,即市场或其他大规模运作的系统是如何运作的。宏观经济学研究经济范围内的现象,如通货膨胀价格水平经济增长,国民收入,国内生产总值,以及失业 .
计量经济学代考
计量经济学是以一定的经济理论和统计资料为基础,运用数学、统计学方法与电脑技术,以建立经济计量模型为主要手段,定量分析研究具有随机性特性的经济变量关系的一门经济学学科。 主要内容包括理论计量经济学和应用经济计量学。 理论经济计量学主要研究如何运用、改造和发展数理统计的方法,使之成为经济关系测定的特殊方法。
相对论代考
相对论(英語:Theory of relativity)是关于时空和引力的理论,主要由愛因斯坦创立,依其研究对象的不同可分为狭义相对论和广义相对论。 相对论和量子力学的提出给物理学带来了革命性的变化,它们共同奠定了现代物理学的基础。
编码理论代写
编码理论(英语:Coding theory)是研究编码的性质以及它们在具体应用中的性能的理论。编码用于数据压缩、加密、纠错,最近也用于网络编码中。不同学科(如信息论、电机工程学、数学、语言学以及计算机科学)都研究编码是为了设计出高效、可靠的数据传输方法。这通常需要去除冗余并校正(或检测)数据传输中的错误。
编码共分四类:[1]
数据压缩和前向错误更正可以一起考虑。
复分析代考
学习易分析也已经很冬年了,七七八人的也续了圧少的书籍和论文。略作总结工作,方便后来人学 Đ参考。
复分析是一门历史悠久的学科,主要是研究解析函数,亚纯函数在复球面的性质。下面一昭这 些基本内容。
(1) 提到复变函数 ,首先需要了解复数的基本性左和四则运算规则。怎么样计算复数的平方根, 极坐标与 $x y$ 坐标的转换,复数的模之类的。这些在高中的时候囸本上都会学过。
(2) 复变函数自然是在复平面上来研究问题,此时数学分析里面的求导数之尖的运算就会很自然的 引入到复平面里面,从而引出解析函数的定义。那/研究解析函数的性贡就是关楗所在。最关键的 地方就是所谓的Cauchy一Riemann公式,这个是判断一个函数是否是解析函数的关键所在。
(3) 明白解析函数的定义以及性质之后,就会把数学分析里面的曲线积分 $a$ 的概念引入复分析中, 定义几乎是一致的。在引入了闭曲线和曲线积分之后,就会有出现复分析中的重要的定理: Cauchy 积分公式。 这个是易分析的第一个重要定理。