發(fā)布時間：2018-01-29 03:13

  本文關(guān)鍵詞： 消費模型 貝葉斯估計 面板數(shù)據(jù) 絕對與相對收入假說 分區(qū)域　出處：《首都經(jīng)濟(jì)貿(mào)易大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：消費作為生產(chǎn)的起點和終點,在經(jīng)濟(jì)活動過程中占有十分重要的地位。消費能夠刺激生產(chǎn),創(chuàng)造就業(yè)崗位,促進(jìn)經(jīng)濟(jì)的可持續(xù)發(fā)展。在整個國民經(jīng)濟(jì)發(fā)展的過程中,居民消費對經(jīng)濟(jì)增長發(fā)揮著極為重要的作用。近幾年來,我國居民消費增長率呈現(xiàn)出下降趨勢,而且出現(xiàn)了居民消費率過低、居民有效需求不足的狀況,經(jīng)濟(jì)增長也受到了一定的影響。同時,不同區(qū)域的居民消費規(guī)律也各有不同。因此,需要分區(qū)域?qū)用裣M規(guī)律進(jìn)行研究和分析,為制定合理可行的消費政策提供依據(jù)。在研讀了國內(nèi)外相關(guān)文獻(xiàn)之后,決定選用貝葉斯估計方法,引入了參數(shù)的先驗信息,使統(tǒng)計推斷的質(zhì)量獲得一定的提高,而且將參數(shù)設(shè)為隨機(jī)變量,與經(jīng)濟(jì)事實更為符合。同時,選用面板數(shù)據(jù),增加了模型的觀測值數(shù)據(jù)和自由度,囊括了更多信息,使模型得到更為有效和可靠的參數(shù)估計量。在此基礎(chǔ)之上,分別進(jìn)行了靜態(tài)面板數(shù)據(jù)模型的貝葉斯分析和動態(tài)面板數(shù)據(jù)模型的貝葉斯分析,通過貝葉斯估計與面板數(shù)據(jù)相結(jié)合的方法盡可能地提高參數(shù)估計的有效性與精準(zhǔn)性。在實證研究中,將我國劃分為華北、東北、華東、中南、西南和西北六個地區(qū),選擇各區(qū)域居民的人均收入和人均消費作為數(shù)據(jù),以絕對收入假說為理論依據(jù)構(gòu)建貝葉斯靜態(tài)面板數(shù)據(jù)居民消費模型,以相對收入假說為理論依據(jù)構(gòu)建貝葉斯動態(tài)面板數(shù)據(jù)居民消費模型,來研究我國分區(qū)域居民消費規(guī)律。研究發(fā)現(xiàn):貝葉斯靜態(tài)面板數(shù)據(jù)居民消費模型和貝葉斯動態(tài)面板數(shù)據(jù)居民消費模型都是十分有效的,說明利用貝葉斯靜態(tài)面板數(shù)據(jù)模型和貝葉斯動態(tài)面板數(shù)據(jù)模型都能有效地刻畫我國分區(qū)域居民消費規(guī)律,且絕對收入假說和相對收入假說都比較符合我國國情;貝葉斯動態(tài)面板數(shù)據(jù)居民消費模型能夠有效地描述居民的消費慣性,而且與貝葉斯靜態(tài)面板數(shù)據(jù)居民消費模型相比,其得到的結(jié)果更為精準(zhǔn),說明利用貝葉斯動態(tài)面板數(shù)據(jù)模型能夠更好地刻畫我國分區(qū)域居民消費規(guī)律,且相對收入假說比絕對收入假說更為理想;我國西部各地區(qū)相比東部各地區(qū),居民的邊際消費傾向和消費慣性都要大一些;我國居民上期消費對消費支出的影響要大于當(dāng)期收入對消費支出的影響,居民消費慣性是影響消費支出的主要因素之一。
[Abstract]:Consumption, as the starting point and end point of production, occupies a very important position in the process of economic activities. Consumption can stimulate production and create jobs. Promote the sustainable development of economy. In the whole process of national economic development, resident consumption plays an extremely important role in economic growth. In recent years, the growth rate of resident consumption in China has shown a downward trend. Moreover, the consumption rate of the residents is too low, the effective demand of the residents is insufficient, and the economic growth is also affected to a certain extent. At the same time, the law of residents' consumption is different in different regions. It is necessary to study and analyze the law of residents' consumption in different regions to provide the basis for making reasonable and feasible consumption policies. After studying the relevant literature at home and abroad, we decide to choose Bayesian estimation method. The priori information of the parameters is introduced to improve the quality of statistical inference, and the parameters are set as random variables, which is more consistent with the economic facts. At the same time, the panel data is selected. The observational data and the degree of freedom of the model are increased, and more information is included, so that the model can get more effective and reliable parameter estimation. Bayesian analysis of static panel data model and Bayesian analysis of dynamic panel data model are carried out respectively. By combining Bayesian estimation with panel data, the validity and accuracy of parameter estimation are improved as much as possible. In the empirical study, China is divided into North, Northeast, East and South China. In the southwest and northwest of the six regions, the per capita income and per capita consumption of residents in each region are selected as data, and the absolute income hypothesis is used as the theoretical basis to construct Bayesian static panel data consumption model. Based on the relative income hypothesis, a Bayesian dynamic panel data resident consumption model is constructed. The study found that: Bayesian static panel data resident consumption model and Bayesian dynamic panel data resident consumption model are very effective. It is shown that both Bayesian static panel data model and Bayesian dynamic panel data model can effectively depict the consumption law of residents in different regions of China, and the absolute income hypothesis and the relative income hypothesis are both in line with the situation of our country. Bayesian dynamic panel data resident consumption model can effectively describe residents' consumption inertia, and compared with Bayesian static panel data resident consumption model, the results obtained are more accurate. It shows that using Bayesian dynamic panel data model can better depict the consumption law of Chinese sub-region residents, and the relative income hypothesis is more ideal than the absolute income hypothesis. Compared with the eastern regions, the marginal consumption tendency and the consumption inertia of the residents in the western regions of China are larger than those in the eastern regions. The influence of residents' consumption on consumption expenditure is greater than that of current income, and the resident's consumption inertia is one of the main factors that affect the consumption expenditure.
【學(xué)位授予單位】：首都經(jīng)濟(jì)貿(mào)易大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F224;F126.1

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