本文關(guān)鍵詞： 消費(fèi)模型 貝葉斯估計(jì) 面板數(shù)據(jù) 絕對(duì)與相對(duì)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(fèi)作為生產(chǎn)的起點(diǎn)和終點(diǎn),在經(jīng)濟(jì)活動(dòng)過程中占有十分重要的地位。消費(fèi)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(gè)國民經(jīng)濟(jì)發(fā)展的過程中,居民消費(fèi)對(duì)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(fèi)增長率呈現(xiàn)出下降趨勢(shì),而且出現(xiàn)了居民消費(fèi)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(shí),不同區(qū)域的居民消費(fèi)規(guī)律也各有不同。因此,需要分區(qū)域?qū)用裣M(fèi)規(guī)律進(jìn)行研究和分析,為制定合理可行的消費(fèi)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(jì)方法,引入了參數(shù)的先驗(yàn)信息,使統(tǒng)計(jì)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(shí)更為符合。同時(shí),選用面板數(shù)據(jù),增加了模型的觀測(cè)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(jì)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(dòng)態(tài)面板數(shù)據(jù)模型的貝葉斯分析,通過貝葉斯估計(jì)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(jì)的有效性與精準(zhǔn)性。在實(shí)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(gè)地區(qū),選擇各區(qū)域居民的人均收入和人均消費(fèi)作為數(shù)據(jù),以絕對(duì)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(fèi)模型,以相對(duì)收入假說為理論依據(jù)構(gòu)建貝葉斯動(dòng)態(tài)面板數(shù)據(jù)居民消費(fèi)模型,來研究我國分區(qū)域居民消費(fèi)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(fèi)模型和貝葉斯動(dòng)態(tài)面板數(shù)據(jù)居民消費(fèi)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(dòng)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(fèi)規(guī)律,且絕對(duì)收入假說和相對(duì)收入假說都比較符合我國國情;貝葉斯動(dòng)態(tài)面板數(shù)據(jù)居民消費(fèi)模型能夠有效地描述居民的消費(fèi)慣性,而且與貝葉斯靜態(tài)面板數(shù)據(jù)居民消費(fèi)模型相比,其得到的結(jié)果更為精準(zhǔn),說明利用貝葉斯動(dòng)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(fèi)規(guī)律,且相對(duì)收入假說比絕對(duì)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(fèi)傾向和消費(fèi)慣性都要大一些;我國居民上期消費(fèi)對(duì)消費(fèi)支出的影響要大于當(dāng)期收入對(duì)消費(fèi)支出的影響,居民消費(fèi)慣性是影響消費(fèi)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(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F224;F126.1

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 徐倩,鄒德新,李曉毅;大學(xué)生消費(fèi)模型的建立與分析[J];沈陽師范大學(xué)學(xué)報(bào)(自然科學(xué)版);2005年03期

2 苑鳳岐;中國消費(fèi)模型和消費(fèi)結(jié)構(gòu)的變化[J];社會(huì)科學(xué);1987年01期

3 臧振春;個(gè)人多期消費(fèi)模型研究[J];河南科學(xué);2002年03期

4 德娜·吐熱汗;陳敬鋒;阿不都熱合曼;;新疆居民消費(fèi)模型的研究與分析[J];新疆農(nóng)業(yè)大學(xué)學(xué)報(bào);2006年01期

5 黃江華;;大學(xué)生消費(fèi)模型的建立[J];科技情報(bào)開發(fā)與經(jīng)濟(jì);2009年13期

6 張滌新;我國居民收入、人口、投資與居民消費(fèi)模型的比較及分析[J];數(shù)量經(jīng)濟(jì)技術(shù)經(jīng)濟(jì)研究;2001年07期

7 陳鈺芬;我國居民收入、人口、教育、財(cái)政政策和貨幣政策與居民消費(fèi)模型的實(shí)證分析[J];數(shù)理統(tǒng)計(jì)與管理;2004年02期

8 勵(lì)怡康;地區(qū)生活消費(fèi)模型的建立與分析[J];財(cái)經(jīng)研究;1988年06期

9 許世蒙,張玉忠;常系數(shù)投資消費(fèi)模型的一些優(yōu)化性質(zhì)[J];運(yùn)籌學(xué)學(xué)報(bào);2002年01期

10 李晗虹,王春峰;動(dòng)態(tài)多目標(biāo)投資消費(fèi)模型[J];系統(tǒng)工程;2005年04期

相關(guān)會(huì)議論文 前2條

1 王安中;王源;;城市數(shù)字文本衍生的消費(fèi)模型與信息化浪潮下“流城市”的模態(tài)建構(gòu)[A];“傳播與中國·復(fù)旦論壇”（2012）——可溝通城市：理論建構(gòu)與中國實(shí)踐論文集[C];2012年

2 晁夕;;DPB-T-S旅游消費(fèi)模型在網(wǎng)站中的應(yīng)用[A];2013中國旅游科學(xué)年會(huì)論文集[C];2013年

相關(guān)碩士學(xué)位論文 前5條

1 王鳳龍;中國分區(qū)域居民消費(fèi)模型的貝葉斯估計(jì)研究[D];首都經(jīng)濟(jì)貿(mào)易大學(xué);2017年

2 范青江;以消費(fèi)模型為基礎(chǔ)的品牌價(jià)值研究[D];對(duì)外經(jīng)濟(jì)貿(mào)易大學(xué);2004年

3 包云飛;我國人壽保險(xiǎn)消費(fèi)模型的構(gòu)建及分析[D];同濟(jì)大學(xué);2007年

4 麻存義;效用受相關(guān)影響的最優(yōu)投資—消費(fèi)模型[D];蘭州大學(xué);2011年

5 毛海棠;金融危機(jī)下的居民消費(fèi)模型及趨勢(shì)預(yù)測(cè)[D];中南大學(xué);2009年

，

本文編號(hào)：1472349