城镇居民收入分布变迁的消费市场效应研究
|
摘要
自1978年改革开放以来，我国进入一个有史以来最好的发展阶段，经济高速增长带来居民收入水平的快速提高及其分配结构的剧烈演变，而且快速发展过程中出现问题及在问题解决中呈现出的反复和震荡，必然比发达国家来的明显和剧烈。中国这一特定的经济环境决定了其在整个发展过程中的理论创新和政策实践必将遇到许多不同于西方传统理论的新挑战和新课题。于是，从收入分布变迁出发，重新审视我国收入和消费间的作用机制，对寻求激发和释放居民需求的突破口来说，具有重要的理论和现实意义。
本文以“经济增长→居民收入分布变迁→消费行为改变→消费市场效应”为思想主线，以居民收入分布变迁为切入点，且把其作为近年来我国居民消费需求演变的主要动力，提出了收入分布变迁消费市场效应的理论预期，该预期的核心内容是在市场机制主导下由居民收入分布变迁引致而来的居民消费需求偏好和档次的转变和局部多个市场轮番出现供不应求和价格虚高等非均衡现象的结果。为分析其合理性，本文从理论和计量两个展开讨论。
首先通过对西方经典消费理论的简单回顾和评析，在储蓄动机不同的异质群体假设下分析出了收入和储蓄之间的“马鞍形”关系，此为西方收入分布和消费作用的主要理论观点。但通过对我国城镇居民收入分布变迁和需求的演变规律发现，此规律并不符合我国居民特有的间歇性周期波动消费行为及其“整体需求不足、局部需求旺盛”的需求现状，很难实现西方式的由微观到宏观的过度。因此本文转换思路，从收入分布视角，并结合我国居民消费行为规律，提出收入分布变迁消费市场效应的理论预期是很有理论必要的。
要计量检验收入分布变迁消费市场效应的存在性和合理性，前提需完成收入分布变迁的测度及相关计量变量的设计。首先运用非参数核密度估计方法和多种函数形式参数方法相结合的方式，选取8次CHNS数据的大样本调查数据和统计年鉴中2000-2009年城镇居民收入分组数据对收入分布进行了拟合，结果显示我国城镇居民收入水平由低到高向上转移的趋势明显，而这种提高的不同步性又导致了收入差距的扩大。其次采用反事实分析法，分解得到度量收入分布变迁的均值变化、方差变化和残差变化三个动态特征的计量变量，分解结果中均值变化占据主导，方差变化次之，说明在收入分布变迁中经济发展的推动作用为主导，由现阶段的分配制度等导致的不同步次之。
在收入分布变迁计量完成基础上，依据消费的经济逻辑理论，在异质性偏好的前提下，证明了收入分布变迁会对会对总消费产生组群下的水平效应、组内规模效应和组间分配效应三方面影响。而后采用CHIP数据中2002年和2007年的城镇数据，借助内生性门限回归的组群划分，通过对上述结果的实证检验表明，水平效应对总消费变化的影响占主导；规模效应则对总消费有抑制作用，源于组群间由高到低的人口回流；组间分配效应在整体上作用很小，表明组间收入差距对总消费的抑制作用没有想象中那么大，但群体间作用差异大，尤其是低收入组群对总消费的抑制作用最大。
在上一步研究基础上进一步深入，对消费支出分布分位点上居民的收入分布变迁消费效应进行研究。为了保证微观数据间的可比性，对CHIP数据进行了人工面板改造，借助其门限模型的分位数回归，完成了消费分布分位点上收入分布变迁消费效应的度量，结果表明居民收入方差带来的离散效应在各分位点的消费效应中占据主导，而均值变化带来的水平效应表现乏力。因此，水平效应对绝对支出增长贡献的乏力，直接导致了其在现实中对消费率拉低的主导作用。另外，我国收入分布和消费分布间存在矛盾，其根源由对CHIP数据的统计分析表明，在于现阶段我国多数居民，尤其是中等阶层面临的消费结构困境。
至于收入分布变迁对消费结构的影响效应研究，首先构造“反事实收入变量”，对AIDS模型进行动态性扩展，而后基于我国“十五”和“十一五”两期的城镇数据进行了实证检验，结果显示“十五”时期我国城镇居民消费结构整体上由生存型向发展型演变升级，整体收入的提高带来的水平效应是我国消费结构不断升级的主要原因；而“十一五”期间的水平效应不再显著，离散和异质效应占据主导，整体社会需求下滑；但收入差距对个别市场消费有一定积极作用，尤其对耐用品和文化娱乐服务等消费；异质效应作用下高收入阶层已有显著地的服务类消费需求，消费结构存在进一步升级的可能。上述分析说明水平效应决定整体需求，而离散和异质效应影响单个市场需求。
最后进一步以家用车市场为例考察了收入分布变迁对单一市场的影响。基于按收入分组的城镇居民家用车拥有量等数据，采用基于消费函数回归的分解方法，度量了收入分布变迁对家用车市场的影响效应。结果显示收入分布变迁的水平效应几乎均起到了决定性的正向拉动作用，但其效果并未得到充分释放，原因在于离散效应对低收入者的抑制作用，但离散效应对中等以上的高收入人群的需求具有很强的正向促进作用，其现阶段在全国整体来看仍有积极作用；异质效应则由于数据原因略显微弱。
Since the reform and opening up in1978, China has entered a period of rapid development,and the rapid economic growth has brought a rapid increase in the level of income and itsdistribution also evolution drastically in a short time, so problems encountered and solved laterappeared again and again must come more obvious and severe than in developed countries. Chinathis particular economic environment determines the theoretical innovation and policy practicesthroughout the development process is bound to encounter many new challenges and newtheoretical issues which is different from the Western. As a result, from the perspective of theincome distribution evolution, studying the mechanism of income and consumption and seeking abreakthrough of releasing residents’ demand has an important theoretical and practical significance.
In view of the above considerations, this paper follows the research mentality of “EconomicGrowth→Income Distribution Evolution→Changes of Consumer Behavior→Evolution ofthe Level and Structure of Consumer Demand”, puts changes of the income distribution as thestarting point and as the driving force of consumer demand evolution, and then we propose thetheoretical expectation that consumer market effects of income distribution evolution, on which wecarry out the micro-econometric study deeply.
Firstly give a simple review and assessment of the Western classical theory, and then under theassumption of heterogeneous groups that have different motives in savings, we get the "saddle"relationship between income and savings, which can be used as the Western theoretical basis ofeffect analysis between income distribution and consumption. But through statistical analysis ofstatus that our urban residents’ income distribution evolution and demand change, we find that thisrule does not meet our residents unique intermittent cyclical fluctuations of consumer behavior andour status quo demand of "insufficient overall demand, strong local demand", so it is difficult torealize the transition from the micro to the macro by the way as Western. As a result, we convertideas to the income distribution, and propose the theoretical expectation of consumer market effectsof income distribution evolution finally.
In order to characterize income distribution evolution and design income quantitativevariables that follow-up study required. Firstly, base on the large sample survey data of eight year’sCHNS data and2000-2009statistical yearbook urban group data, through a method combination of non-parametric kernel density estimation and several forms of parameter-function, we get theconclusions that the trend of China's urban residents income transfer from low to high upsignificantly, but this increase is not synchronized, which has led to a widening income gap.Secondly, we obtain the mean change, variance change and residual change of income distributionevolution by counterfactual analysis, where the mean change is dominant, followed by the variancechange, last is residual change, by which we know that the promoting role of the economicdevelopment is the most important and the second is the distribution system.
Then from the perspective of income distribution changes, according to economic logic ofconsumption theory, and under the premise of heterogeneity, we establishe a mathematical model tostudy how the evolution of income distribution impacts on the total consumption, whose resultshow that income distribution changes would generate the level effect, scale effect in the group anddistributional effect between the groups. Adopted in2002and2007CHIP urban data, based onthreshold regression, empirical results show that level effect dominates on the impact of changes intotal consumption, scale also reflects a certain inhibitory effect for the high to low populationreflux, and the overall effect of distributional effects between the groups is very small, so impactionof the income gap on total consumption is not so big as imagined, but effects between groups havea big difference, especially low-income groups take the greatest inhibitory effect on totalconsumption.
Based on the research in the previous chapter, takes a further study on the demand effects ofincome evolution on the expenditure quantiles. In order to ensure comparability of data, weconstruct a quasi-panel of CHIP data, and by quantile regression of its threshold model we finshiedthe estimate. The main conclusion is that scatter effect caused by income variance bring dominanteffect on expenditure quantiles, while the level effect play poor performance. Showed that leveleffect contributed weakly to spending, a direct result is that its leading role of consumption ratereduce; while there are significant inconsistencies between the distribution of the income andexpenditure, its roots are likely to be the consumption dilemma of durable goods that majority ofresidents faced.
As for the study about effects of income distribution evolution on the consumption structure.By constructing two "counterfactual income variable", we construct a new model that dynamicexpansion of AIDS. Then based on China urban data of "Tenth Five-Year" and "EleventhFive-Year", we finish the empirical test and results show that in the Tenth Five-Year consumptionstructure of urban resident overally upgrade from subsistence to developmental level, and the mainreason is the level effect brought by the improvement of residents’ average revenue. While during the Eleventh Five-Year period, the horizontal effect is not significant any more, scatter andheterogeneity effects take the dominant role, which cause decline of the whole society demand. Butincome inequality still has some positive effects on individual consumer market, especially for themarket of durable goods and consumer services, culture and entertainment. The high-income grouphas a significant class of service consumer demand, showing that there will be a further escalationof our consumption structure. So level effect major impacts the overall demand, while variance andresidual effects are more inclined to affect the specific market demand.
In the end, we take further study on the effect of income distribution change on the singlemarket with family car market as an example. Income distribution evolution generate three effects,including level effect, scatter effect and heterogeneity effect on consumer demand for family carsand other durable goods. Empirical analysis found that, level effect almost always play a major rolein promoting car’s consumption; scatter effect has a greater inhibition on the families ofmiddle-class and less, but has a positive impact on the higher income groups, especially for thehighest income group, whose scatter effect is greater than the level effect, so it has a smallerpositive effect on the whole; as for heterogeneous effect, it’s very weak. Based on revenue trends,there is a possibility the automotive market shrinking, so income distribution reform and industrialplanning process needs to be more cautious.
本文以“经济增长→居民收入分布变迁→消费行为改变→消费市场效应”为思想主线，以居民收入分布变迁为切入点，且把其作为近年来我国居民消费需求演变的主要动力，提出了收入分布变迁消费市场效应的理论预期，该预期的核心内容是在市场机制主导下由居民收入分布变迁引致而来的居民消费需求偏好和档次的转变和局部多个市场轮番出现供不应求和价格虚高等非均衡现象的结果。为分析其合理性，本文从理论和计量两个展开讨论。
首先通过对西方经典消费理论的简单回顾和评析，在储蓄动机不同的异质群体假设下分析出了收入和储蓄之间的“马鞍形”关系，此为西方收入分布和消费作用的主要理论观点。但通过对我国城镇居民收入分布变迁和需求的演变规律发现，此规律并不符合我国居民特有的间歇性周期波动消费行为及其“整体需求不足、局部需求旺盛”的需求现状，很难实现西方式的由微观到宏观的过度。因此本文转换思路，从收入分布视角，并结合我国居民消费行为规律，提出收入分布变迁消费市场效应的理论预期是很有理论必要的。
要计量检验收入分布变迁消费市场效应的存在性和合理性，前提需完成收入分布变迁的测度及相关计量变量的设计。首先运用非参数核密度估计方法和多种函数形式参数方法相结合的方式，选取8次CHNS数据的大样本调查数据和统计年鉴中2000-2009年城镇居民收入分组数据对收入分布进行了拟合，结果显示我国城镇居民收入水平由低到高向上转移的趋势明显，而这种提高的不同步性又导致了收入差距的扩大。其次采用反事实分析法，分解得到度量收入分布变迁的均值变化、方差变化和残差变化三个动态特征的计量变量，分解结果中均值变化占据主导，方差变化次之，说明在收入分布变迁中经济发展的推动作用为主导，由现阶段的分配制度等导致的不同步次之。
在收入分布变迁计量完成基础上，依据消费的经济逻辑理论，在异质性偏好的前提下，证明了收入分布变迁会对会对总消费产生组群下的水平效应、组内规模效应和组间分配效应三方面影响。而后采用CHIP数据中2002年和2007年的城镇数据，借助内生性门限回归的组群划分，通过对上述结果的实证检验表明，水平效应对总消费变化的影响占主导；规模效应则对总消费有抑制作用，源于组群间由高到低的人口回流；组间分配效应在整体上作用很小，表明组间收入差距对总消费的抑制作用没有想象中那么大，但群体间作用差异大，尤其是低收入组群对总消费的抑制作用最大。
在上一步研究基础上进一步深入，对消费支出分布分位点上居民的收入分布变迁消费效应进行研究。为了保证微观数据间的可比性，对CHIP数据进行了人工面板改造，借助其门限模型的分位数回归，完成了消费分布分位点上收入分布变迁消费效应的度量，结果表明居民收入方差带来的离散效应在各分位点的消费效应中占据主导，而均值变化带来的水平效应表现乏力。因此，水平效应对绝对支出增长贡献的乏力，直接导致了其在现实中对消费率拉低的主导作用。另外，我国收入分布和消费分布间存在矛盾，其根源由对CHIP数据的统计分析表明，在于现阶段我国多数居民，尤其是中等阶层面临的消费结构困境。
至于收入分布变迁对消费结构的影响效应研究，首先构造“反事实收入变量”，对AIDS模型进行动态性扩展，而后基于我国“十五”和“十一五”两期的城镇数据进行了实证检验，结果显示“十五”时期我国城镇居民消费结构整体上由生存型向发展型演变升级，整体收入的提高带来的水平效应是我国消费结构不断升级的主要原因；而“十一五”期间的水平效应不再显著，离散和异质效应占据主导，整体社会需求下滑；但收入差距对个别市场消费有一定积极作用，尤其对耐用品和文化娱乐服务等消费；异质效应作用下高收入阶层已有显著地的服务类消费需求，消费结构存在进一步升级的可能。上述分析说明水平效应决定整体需求，而离散和异质效应影响单个市场需求。
最后进一步以家用车市场为例考察了收入分布变迁对单一市场的影响。基于按收入分组的城镇居民家用车拥有量等数据，采用基于消费函数回归的分解方法，度量了收入分布变迁对家用车市场的影响效应。结果显示收入分布变迁的水平效应几乎均起到了决定性的正向拉动作用，但其效果并未得到充分释放，原因在于离散效应对低收入者的抑制作用，但离散效应对中等以上的高收入人群的需求具有很强的正向促进作用，其现阶段在全国整体来看仍有积极作用；异质效应则由于数据原因略显微弱。
Since the reform and opening up in1978, China has entered a period of rapid development,and the rapid economic growth has brought a rapid increase in the level of income and itsdistribution also evolution drastically in a short time, so problems encountered and solved laterappeared again and again must come more obvious and severe than in developed countries. Chinathis particular economic environment determines the theoretical innovation and policy practicesthroughout the development process is bound to encounter many new challenges and newtheoretical issues which is different from the Western. As a result, from the perspective of theincome distribution evolution, studying the mechanism of income and consumption and seeking abreakthrough of releasing residents’ demand has an important theoretical and practical significance.
In view of the above considerations, this paper follows the research mentality of “EconomicGrowth→Income Distribution Evolution→Changes of Consumer Behavior→Evolution ofthe Level and Structure of Consumer Demand”, puts changes of the income distribution as thestarting point and as the driving force of consumer demand evolution, and then we propose thetheoretical expectation that consumer market effects of income distribution evolution, on which wecarry out the micro-econometric study deeply.
Firstly give a simple review and assessment of the Western classical theory, and then under theassumption of heterogeneous groups that have different motives in savings, we get the "saddle"relationship between income and savings, which can be used as the Western theoretical basis ofeffect analysis between income distribution and consumption. But through statistical analysis ofstatus that our urban residents’ income distribution evolution and demand change, we find that thisrule does not meet our residents unique intermittent cyclical fluctuations of consumer behavior andour status quo demand of "insufficient overall demand, strong local demand", so it is difficult torealize the transition from the micro to the macro by the way as Western. As a result, we convertideas to the income distribution, and propose the theoretical expectation of consumer market effectsof income distribution evolution finally.
In order to characterize income distribution evolution and design income quantitativevariables that follow-up study required. Firstly, base on the large sample survey data of eight year’sCHNS data and2000-2009statistical yearbook urban group data, through a method combination of non-parametric kernel density estimation and several forms of parameter-function, we get theconclusions that the trend of China's urban residents income transfer from low to high upsignificantly, but this increase is not synchronized, which has led to a widening income gap.Secondly, we obtain the mean change, variance change and residual change of income distributionevolution by counterfactual analysis, where the mean change is dominant, followed by the variancechange, last is residual change, by which we know that the promoting role of the economicdevelopment is the most important and the second is the distribution system.
Then from the perspective of income distribution changes, according to economic logic ofconsumption theory, and under the premise of heterogeneity, we establishe a mathematical model tostudy how the evolution of income distribution impacts on the total consumption, whose resultshow that income distribution changes would generate the level effect, scale effect in the group anddistributional effect between the groups. Adopted in2002and2007CHIP urban data, based onthreshold regression, empirical results show that level effect dominates on the impact of changes intotal consumption, scale also reflects a certain inhibitory effect for the high to low populationreflux, and the overall effect of distributional effects between the groups is very small, so impactionof the income gap on total consumption is not so big as imagined, but effects between groups havea big difference, especially low-income groups take the greatest inhibitory effect on totalconsumption.
Based on the research in the previous chapter, takes a further study on the demand effects ofincome evolution on the expenditure quantiles. In order to ensure comparability of data, weconstruct a quasi-panel of CHIP data, and by quantile regression of its threshold model we finshiedthe estimate. The main conclusion is that scatter effect caused by income variance bring dominanteffect on expenditure quantiles, while the level effect play poor performance. Showed that leveleffect contributed weakly to spending, a direct result is that its leading role of consumption ratereduce; while there are significant inconsistencies between the distribution of the income andexpenditure, its roots are likely to be the consumption dilemma of durable goods that majority ofresidents faced.
As for the study about effects of income distribution evolution on the consumption structure.By constructing two "counterfactual income variable", we construct a new model that dynamicexpansion of AIDS. Then based on China urban data of "Tenth Five-Year" and "EleventhFive-Year", we finish the empirical test and results show that in the Tenth Five-Year consumptionstructure of urban resident overally upgrade from subsistence to developmental level, and the mainreason is the level effect brought by the improvement of residents’ average revenue. While during the Eleventh Five-Year period, the horizontal effect is not significant any more, scatter andheterogeneity effects take the dominant role, which cause decline of the whole society demand. Butincome inequality still has some positive effects on individual consumer market, especially for themarket of durable goods and consumer services, culture and entertainment. The high-income grouphas a significant class of service consumer demand, showing that there will be a further escalationof our consumption structure. So level effect major impacts the overall demand, while variance andresidual effects are more inclined to affect the specific market demand.
In the end, we take further study on the effect of income distribution change on the singlemarket with family car market as an example. Income distribution evolution generate three effects,including level effect, scatter effect and heterogeneity effect on consumer demand for family carsand other durable goods. Empirical analysis found that, level effect almost always play a major rolein promoting car’s consumption; scatter effect has a greater inhibition on the families ofmiddle-class and less, but has a positive impact on the higher income groups, especially for thehighest income group, whose scatter effect is greater than the level effect, so it has a smallerpositive effect on the whole; as for heterogeneous effect, it’s very weak. Based on revenue trends,there is a possibility the automotive market shrinking, so income distribution reform and industrialplanning process needs to be more cautious.
引文
①资料来源于2011年《中国老龄事业发展“十二五”规划》。
[1] Ahluwalia M S. Income distribution and development: some stylized facts[J]. AmericanEconomic Review,1976,66(2):128-35.
[2] Ando A, Modigliani F. The life-cycle hypothesis of saving: aggregate implications andtests[J]. The American Economic Review,1963,53(1):55-84.
[3] Atkinson A B. The changing distribution of income: Evidence and explanations[J]. GermanEconomic Review,2000,1(1):3-18.
[4] Beierlein J G, Dunn J W, McConnon J C. The demand for electricity and natural gas in theNortheastern United States[J]. The Review of Economics and Statistics,1981,63(3):403-408.
[5] Blanciforti L, Green R. An almost ideal demand system incorporating habits: an analysis ofexpenditures on food and aggregate commodity groups[J]. The Review of Economics andStatistics,1983,65(3):511-515.
[6] Blinder A S. A Model of Inherited Wealth[J]. The Quarterly Journal of Economics,1973,87(4):608-626.
[7] Blinder A S. Distribution effects and the aggregate consumption function[J]. The Journal ofPolitical Economy,1975:447-475.
[8] Blinder A S. The relationship between distribution effects and the consumption[J]. TheJournal of Political Economy,2002,132(3):447-476.
[9] Blundell R, Pashardes P, Weber G. What do we learn about consumer demand patterns frommicro data?[J]. American Economic Review,1993,83(3):570-597.
[10] Borooah V K, Sharpe D R. Aggregate consumption and the distribution of income in theUnited Kingdom: an econometric analysis[J]. Economic Journal,1986,96(382):449-66.
[11] Brems H. Long-run automobile demand[J]. The Journal of Marketing,1956,20(4):379-384.
[12] Burney N A, Akmal M. Food demand in Pakistan: an application of the extended linearexpenditure system[J]. Journal of Agricultural Economics,1991,42(2):185-195.
[13] Buse A. Aggregation, distribution and dynamics in the linear and quadratic expendituresystems[J]. The Review of Economics and Statistics,1992,(74):45-53.
[14] Buse A. Evaluating the linearized almost ideal demand system[J]. American Journal ofAgricultural Economics,1994,76(4):781-793.
[15] Button K, Ngoe N and Hine J. Modelling vehicle ownership and use in low incomecountries[J]. Journal of Transport Economics and Policy,1993,27(1):51-67.
[16] Caballero R J. Consumption puzzles and precautionary saving[J]. Journal of MonetaryEconomics,1990,25:113-136.
[17] Cambell J Y, Deaton A S. Why is consumption so smooth[J]. Review of Economic Study,1989,56:357-373.
[18] Campbell J Y, Mankiw N G. The response of consumption to income: a cross-countryinvestigation[J]. European economic review,1991,35(4):723-756.
[19] Caner M, Hansen B E. Instrumental variable estimation of a threshold model[J].Econometric Theory,2004,20(5):813-843.
[20] Carroll C D. Buffer-stock saving and the life cycle/permanent income hypothesis[J]. TheQuarterly Journal of Economics,1997,112(1):1-55.
[21] Chakrabarty M, Schmalenbach A, Racine J. On the distributional effects of income in anaggregate consumption relation[J]. Canadian Journal of Economics/Revue canadienned’Economique,2006,39(4):1121-1243.
[22] Chernozhukov V, Hansen C. The effects of401(k) participation on the wealth distribution:an instrumental quantile regression analysis[J]. Review of Economics and Statistics,2004,86(3):735-751.
[23] Chernozhukov V, Hansen C. Instrumental variable quantile regression: A robust inferenceapproach[J]. Journal of Econometrics,2008,142(1):379-398.
[24] Chernozhukov V, Hansen C, Jansson M. Inference approaches for instrumental variablequantile regression[J]. Economics Letters,2007,95(2):272-277.
[25] Collado M D. Estimating dynamic models from time series of independentcross-sections[J]. Journal of Econometrics,1997,82(1):37-62.
[26] Cowell F A. Measuring inequality[M]. London: Prentice Hall/Harvester Wheatsheaf,1995.
[27] Cutler D M, Katz L F. Rising inequality? changes in the distribution of income andconsumption in the1980s[R]. National Bureau of Economic Research,1992.
[28] Dagum C. A new model for personal income distribution: specification and estimation[J].Economie Appliquée,1977,30(3):413-437.
[29] Dagum C. Wealth distribution models: analysis and applications[J]. Statistica,2006,(3):235-268.
[30] Dargay J, Gately D and Sommer M. Vehicle ownership and income growth, worldwide:1960-2030[J]. The Energy Journal,2007,28(4):143-170.
[31] Deaton A, Muellbauer J. An almost ideal demand system[J]. The American EconomicReview,1980,70(3):312-326.
[32] Deaton A. Panel data from time series of cross-sections[J]. Journal of Econometrics,1985,30(1):109-126.
[33] Deaton A. Saving and Liquidity Constraints[J]. Econometrica,1991,59(5):1221-1248.
[34] Deaton A. The analysis of household surveys: a microeconometric approach todevelopment policy[M]. World Bank Publications,1997.
[35] Diewert W E. Exact and superlative index numbers[J]. Journal of econometrics,1976,4(2):115-145.
[36] Dissanayake D, Morikawa T. Investigating household vehicle ownership, mode choice andtrip sharing decisions using a combined revealed preference/stated preference Nested Logitmodel: case study in Bangkok Metropolitan Region[J]. Journal of Transport Geography,2010,18(3):402-410.
[37] Dong D, Capps Jr O. Impacts Of Income Distribution On Market Demand[C]//1998Annualmeeting, August2-5, Salt Lake City, UT. American Agricultural Economics Association(New Name2008: Agricultural and Applied Economics Association),1998(20996).
[38] Duesenberry J S. Income Saving and the Theory[M]. Harvard University Press,1949.
[39] Dynan K E. How prudent are consumers?[J]. Journal of Political Economy,1993,101(6):1104-1113.
[40] Dynan K E. Habit formation in consumer preferences: Evidence from panel data[J].American Economic Review,2000,90(3):391-406.
[41] Firpo S, Fortin N M, Lemieux T. Unconditional quantile regressions[J]. Econometrica,2009,77(3):953-973.
[42] Flavin M A. The excess smoothness of consumption: identification and estimation[J].Review of Economic Studies,1993,60:651-666.
[43] Friedman M. A Theory of the Consumption Function[M]. Princeton: Princeton UniversityPress,1957.
[44] Fr lich M, Melly B. Unconditional quantile treatment effects under endogeneity[R]. IZADiscussion Papers,2008.
[45] Fr lich M, Melly B. Unconditional quantile treatment effects under endogeneity[J]. Journalof Business&Economic Statistics,2013(just-accepted).
[46] Gibrat R. Les inégalités économiques[M]. Recueil Sirey,1931.
[47] Girma S. A quasi-differencing approach to dynamic modelling from a time series ofindependent cross-sections[J]. Journal of Econometrics,2000,98(2):365-383.
[48] Gorman W M. Community preference fields[J]. Econometrica: journal of the EconometricSociety,1953,21:63-80.
[49] Gorman W M. Lecture notes[R]. London School of Economics, Mimeo,1971.
[50] Gorman W M. On a class of preference fields[J]. Metroeconomica,1961,13(2):53-56.
[51] Gorman W M. Separable utility and aggregation[J]. Econometrica: Journal of theEconometric Society,1959,27(3):469-481.
[52] Gosling A, Machin S, Meghir C. What Has Happened to Men's Wages since the Mid‐1960s?[J]. Fiscal Studies,1994,15(4):63-87.
[53] Hall R E. Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theoryand Evidence[J]. The Journal of Political Economy,1978,86(6):971-987.
[54] Hannan E J. Principles of Econometrics[J]. Technometrics,1973,15(1):195-196.
[55] Hansen B E. Inference in TAR models[J]. Studies in Nonlinear Dynamics andEconometrics,1997,2(1):1-14.
[56] Hansen B E. Threshold effects in non-dynamic panels: Estimation, testing, and inference[J].Journal of econometrics,1999,93(2):345-368.
[57] Hansen B E. Sample splitting and threshold estimation[J]. Econometrica,2000,68(3):575-603.
[58] Hansen B E, Seo B. Testing for two-regime threshold cointegration in vectorerror-correction models[J]. Journal of Econometrics,2002,110(2):293-318.
[59] Heien D M. Demographic effects and the multiperiod consumption function[J]. Journal ofPolitical Economy,1972,80(1):125-38.
[60] Hyslop D, Maré D. Understanding changes in the distribution of household incomes inNew Zealand between1983-86and1995-98[R]. New Zealand Treasury,2001.
[61] Ibrahim A Ahmad, Yanqin Fan, Optimal bandwidth for kernel density estimators offunctions of observations[J]. Statistics&Probability Letters,2005,51(3):245-251.
[62] Jenkins S P, Van Kerm P. Accounting for income distribution trends: a density functiondecomposition approach[J]. Journal of Economic Inequality,2005,(3):43-61.
[63] Jones E, Mustiful B W. Purchasing behaviour of higher-and lower-income shoppers: a lookat breakfast cereals[J]. Applied Economics,1996,28(1):131-137.
[64] Keynes J M. The General Theory of Employment, Interest and Money[M]. New York,1936.
[65] Koenker R, Bassett G. Regression quantiles[J]. Econometrica: Journal of the EconometricSociety,1978,46(1):33-50.
[66] Koenker R, Machado J A F. Goodness of fit and related inference processes for quantileregression[J]. Journal of the american statistical association,1999,94(448):1296-1310.
[67] Koenker R. Quantile regression for longitudinal data[J]. Journal of Multivariate Analysis,2004,91(1):74-89.
[68] Koenker R. Quantile regression[M]. Cambridge University Press,2005.
[69] Koenker, R., Kevin F. Hallock, Quantile Regression[J]. The Journal of EconomicPerspectives,2001,15(4):143-156.
[70] Leland H E. Saving and uncertainty: The precautionary demand for saving[J]. TheQuarterly Journal of Economics,1968,82(3):465-473.
[71] Li H, Zou H. Income inequality is not harmful for growth: theory and evidence[J]. Reviewof Development Economics,1998,2(3):318-334.
[72] Lluch C, Williams R. Consumer demand systems and aggregate consumption in the USA:An application of the extended linear expenditure system[J]. Canadian Journal ofEconomics,1975,8(1):49-66.
[73] Lluch C, Williams R. Cross country demand and savings patterns: An application of theextended linear expenditure system[J]. The Review of Economics and Statistics,1975,8:320-328.
[74] Lluch C. The extended linear expenditure system[J]. European Economic Review,1973,4(1):21-32.
[75] Lou F, Li X. An empirical analysis of income disparity and consumption in China[J].Frontiers of Economics in China,2011,6(1):157-170.
[76] Minoiu, C., Poverty Analysis based on kernel density estimates from grouped data [R].Working Paper,2006
[77] Manski C F. Identification problems in the social sciences[M]. Harvard University Press,1995.
[78] McDonald J B. Some generalized functions for the size distribution of income[J].Econometrica: Journal of the Econometric Society,1984,52:647-663.
[79] Melly B. Decomposition of differences in distribution using quantile regression[J]. LabourEconomics,2005,12(4):577-590.
[80] Modigliani F, Ando A. The'Permanent Income'and the'Life Cycle'Hypothesis of SavingBehavior: Comparison and Tests[C]//Proceedings of the Conference on Consumption andSaving.1960,2:49-174.
[81] Modigliani F, Brumberg R. Post Keynesian Economics[M]. New Brunswick N J: RutgersUniversity Press,1954.
[82] Muellbauer J. Community preferences and the representative consumer[J]. Econometrica:Journal of the Econometric Society,1976,44(5):979-999.
[83] Musgrave P. Income distribution and the aggregate consumption function[J]. Journal ofPolitical Economy,1980,88(3):504-525.
[84] O'Dea D. The changes in New Zealand's income distribution[R]. New Zealand Treasury,2000.
[85] Parzen E. On estimation of a probability density function and mode[J]. Annals ofmathematical statistics,1962,33(3):1065-1076.
[86] Pashardes P. Bias in estimating the almost ideal demand system with the stone indexapproximation[J]. The Economic Journal,1993,103:908-915.
[87] Pearce I F. A contribution to demand analysis[M]. Clarendon Press,1964.
[88] Pittau M G, Zelli R. Testing for changing shapes of income distribution: Italian evidence inthe1990s from kernel density estimates[J]. Empirical Economics,2004,29(2):415-430.
[89] Powell D. Unconditional quantile regression for exogenous or endogenous treatmentvariables[R].2011.
[90] Reed W J. On Pareto’s law and the determinants of Pareto exponents[J]. Journal of IncomeDistribution,2004,13:7-17.
[91] Reed W J. The Pareto law of incomes—an explanation and an extension[J]. Physica A:Statistical Mechanics and its Applications,2003,319:469-486.
[92] Rosenblatt M. Remarks on some nonparametric estimates of a density function[J]. TheAnnals of Mathematical Statistics,1956,27(3):832-837.
[93] Rudemo M. Empirical choice of histograms and kernel density estimators[J]. ScandinavianJournal of Statistics,1982,9:65-78.
[94] Salem A B Z, Mount T D. A convenient descriptive model of income distribution: thegamma density[J]. Econometrica,1974,42(6):1115-1127.
[95] Silverman B W. Using kernel density estimates to investigate multimodality[J]. Journal ofthe Royal Statistical Society. Series B (Methodological),1981,43:97-99.
[96] Simmons P. Evidence on the Impact of Income Distribution on Consumer Demand in theUK1955–68[J]. The Review of Economic Studies,1980,47(5):893-906.
[97] Singh S K, Maddala G S. A Function for Size Distribution of Incomes[J]. Econometrica:Journal of the Econometric Society,1976,44:963-970.
[98] Singh S K, Maddala G S. A function for size distribution of incomes[M]//Modeling incomedistributions and Lorenz curves. Springer New York,2008:27-35.
[99] Singh, S. K., G. S. Maddala. A Function for the Size Distribution of Incomes[J].Econometrica,1976,44:963-970.
[100] Stiglitz J E. Distribution of income and wealth among individuals[J]. Econometrica:Journal of the Econometric Society,1969,37(3):382-397.
[101] Stoker T M. Simple tests of distributional effects on macroeconomic equations[J]. TheJournal of Political Economy,1986,94(4):763-795.
[102] Stoker T M. Empirical approaches to the problem of aggregation over individuals[J].Journal of Economic Literature,1993,31:1827-1874.
[103] Stone R. Linear expenditure systems and demand analysis: an application to the pattern ofBritish demand[J]. The Economic Journal,1954,64(9):511-527.
[104] Storchmann K. Long-run gasoline demand for passenger cars: the role of incomedistribution[J]. Energy Economics,2005,27(1):25-58.
[105] Taillie C. Lorenz ordering within the generalized gamma family of income distributions[J].Statistical Distributions in Scientific Work,1981,6:181-192.
[106] Taillie C. Lorenz ordering within the Generalized Gamma Family of IncomeDistributions[M]. in Taillie, C., G. P. Patil and B. Balderssari (eds.). Statistical Distributionsin Scientific Work,1981,6:181–192, Boston.
[107] Theil, H., Principles of Econometrics[M]. New York: North Holland Press,1971.
[108] Wan G. Accounting for income inequality in rural China: a regression-based approach[J].Journal of Comparative Economics,2004,32(2):348-363.
[109] Wilfling B, Kr mer W. The Lorenz-ordering of Singh-Maddala income distributions[J].Economics Letters,1993,43(1):53-57.
[110] Wu C O. Kernel smoothing of the nonparametric maximum likelihood estimation forbiased sampling models[J]. Math Methods Statist,1996,5:275-298.
[111] Yen S T, Chern W S. Flexible demand systems with serially correlated errors：fat and oilconsumption in the United States[J]．American Journal of Agicultural Economics,1992,8:689-697.
[112] Zeldes S P. Consumption and liquidity constraints: an empirical investigation[J]. TheJournal of Political Economy,1989,97(2):305-346.
[113] Zeldes S P. Optimal Consumption with Stochastic Income: Deviations from CertaintyEquivalence[J]. The Quarterly Journal of Economics,1989,104(2):275-298.
[114] Zhihao Zheng, Henneberry, The Impact of Changes in Income Distribution on Current andFuture Food Demand in Urban China[J]. Journal of Agricultural and Resource Economics,2010,35:51–71.
[115] Zhou J, Zhang D. A Research on the Relationship between Urban Households’ Income andExpenditure in Hainan[J]. Technology and Investment,2013,4:12-17.
[116]安格斯迪顿,约翰米尔鲍尔.经济学与消费者行为[M].中国人民大学出版社,2005.
[117]白仲林,赵亮.天津市城镇居民收人流动性的实证分析——伪面板数据门限自回归模型的估计与检验[C].天津市社会科学界第七届学术年会优秀论文集,2011,1029-1040.
[118]白仲林,赵亮.我国通货膨胀率的最优目标区间几何?[J].统计研究,2011,28(6):6-10.
[119]白仲林.面板数据模型的设定,统计检验和新进展[J].统计与信息论坛,2010,25(10):3-12.
[120]陈建宝,杜小敏,董海龙.基于分位数回归的中国居民收入和消费的实证分析[J].统计与信息论坛,2009,24(7):44-50.
[121]陈建宝,李坤明.收入分配,人口结构与消费结构:理论与实证研究[J].上海经济研究,2013(4):74-87.
[122]陈娟,林龙,叶阿忠.基于分位数回归的中国居民消费研究[J].数量经济技术经济研究,2008,25(2):16-27.
[123]陈娟,孙敬水.我国城镇居民收入不平等变动实证研究——基于收入分布变化分解的视角[J].统计研究,2009,26(9):77-81.
[124]陈强.高级计量经济学及Stata应用[M].高等教育出版社,2010.
[125]陈秋玲,曹庆瑾,张阿丽.基于扩展线性支出系统模型的我国城镇居民消费结构分析[J].管理学报,2010,(1):68-72.
[126]陈希孺,柴根象.非参数统计教程[M].华东师范大学出版社,1993.
[127]陈云.居民收入分布及其变迁的统计研究[D].首都经济贸易大学,2009.
[128]陈云.中国居民收入分布专题实证研究——居民收入分布变迁测度及其影响因素分解[J].统计与信息论坛,2013,28(2):3-9.
[129]陈宗胜,周云波.再论改革与发展中的收入分配[M].经济科学出版社,2002.
[130]蔡玉程,金晓彤.关于我国消费需求不足问题的思考[J].江汉论坛,1999,(12):23-24.
[131]程磊.收入差距扩大与中国内需不足：理论机制与实证检验[J].经济科学,2011,(1):11-24.
[132]迟福林.消费主导:中国转型大战略[M].中国经济出版社,2012.
[133]迟巍,黎波,余秋梅.基于收入分布的收入差距扩大成因的分解[J].数量经济技术经济研究,2008,(9):52-64.
[134]段先盛.收入分配对总消费影响的结构分析——兼对中国城镇家庭的实证检验[J].数量经济技术经济研究,2009(2):151-160.
[135]段先盛.收入分配对经济发展方式的影响：理论与实证[M].北京:人民出版社,2011.
[136]樊茂清,任若恩.基于异质性偏好的中国城镇居民消费结构研究[J].中国软科学,2007,10:37-46.
[137]范剑平.我国居民消费率偏低的原因分析与开拓城镇市场的对策选择[J].宏观经济研究,1999,(6):41-46.
[138]范剑平.鼓励消费政策可行性研究[J].经济科学,2001(2):5-14.
[139]范剑平.论投资主导型向居民消费,社会投资双拉动型转换——我国经济增长的需求结构分析[J].经济学动态,2003(2):11-14.
[140]方福前.中国居民消费需求不足原因研究[J].中国社会科学,2009,2:68-82.
[141]封福育.名义利率与通货膨胀:对我国“费雪效应”的再检验——基于门限回归模型分析[J].数量经济技术经济研究,2009(1):89-98.
[142]高铁梅.计量经济分析方法与建模：Eviews应用及实例（第二版）[M].北京：清华大学出版社,2009.
[143]古继宝,荣敏,吴剑琳.中国民用汽车保有量的组合预测[J].工业技术经济,2010,29(4):123-127.
[144]郭其友,芦丽静.经济持续增长动力的转变——消费主导型增长的国际经验与借鉴[J].中山大学学报:社会科学版,2009,49(2):190-197.
[145]杭斌,郭香俊.基于习惯形成的预防性储蓄——中国城镇居民消费行为的实证分析[J].统计研究,2009,(3):38-43.
[146]杭斌,申春兰.潜在流动性约束与预防性储蓄行为——理论框架及实证研究[J].管理世界,2006(9):28-35.
[147]杭斌,闫新华.经济快速增长时期的居民消费行为——基于习惯形成的实证分析[J].经济学（季刊）,2013,12(4):1191-1208.
[148]郝令昕,奈曼.分位数回归模型[M].肖东亮译,上海:格致出版社:上海人民出版社,2012.
[149]贺振华,寇宗来.收入分布,厂商定价与耐用品的消费扩张[J].南方经济,2006,(8):5-16.
[150]洪求枝,高明成,夏莹娇.灰色系统预测方法在我国私人汽车拥有量预测中的应用[J].长江大学学报自然科学版:理工卷,2008,5(1):132-134.
[151]胡祖光.基尼系数理论最佳值及其简易计算公式研究[J].经济研究,2004,9:60-69.
[152]金晓彤,蔡玉程,董直庆.中国城镇居民间歇式周期性波动的消费行为[J].吉林大学社会科学学报,2007,(6):123-127.
[153]金晓彤,董直庆,盛光华.连锁效应导引下的中国城镇居民消费行为:理论假说与实态验证[J].经济科学,2004,(4):74-83.
[154]金晓彤,杨晓东.中国城镇居民消费行为变异论的四个假说及其理论分析[J].管理世界,2004,(11):7-16+30.
[155]李春玲.当代中国社会的消费分层[J].中山大学学报(社会科学版),2007,4:8-13.
[156]李建伟.居民收入分布对耐用消费品及经济增长周期的影响——以城镇居民家庭乘用车为例[J].经济纵横,2013,(6):1-11.
[157]李军.收入差距对消费需求影响的定量分析[J].数量经济技术经济研究,2003,(9):5-11.
[158]李实,罗楚亮.中国城乡收入差距的重新估计[J].北京大学学报(哲学社会科学版),2007,2:12-24.
[159]李实,罗楚亮.中国收入差距究竟有多大?[J].经济研究,2011,4:68-79.
[160]李玉忍,高社生,张学源.核密度的随机加权估计及其应用[J],西北大学学报,2008,3:351-361.
[161]厉以宁.消费经济学[M].北京:人民出版社,1984.
[162]林伯强.中国的经济增长,贫困减少与政策选择[J].经济研究,2003,(12):15-26.
[163]林文芳.区域性偏好与城乡居民消费差异[J].统计研究,2009,26(11):87-92.
[164]林毅夫.潮涌现象与发展中国家宏观经济理论的重新构建[J].经济研究,2007,(1):126-131.
[165]林毅夫,巫和懋,邢亦青.“潮涌现象”与产能过剩的形成机制[J].经济研究,2010,(10):4-l9.
[166]刘华,钟甫宁.食物消费与需求弹性——基于城镇居民微观数据的实证研究[J].南京农业大学学报:社会科学版,2009,9(3):36-43.
[167]刘重力,黄平川.技术进口对我国企业技术创新能力的影响——基于中国省际数据的分位数回归[J].南开经济研究,2012(5):132-141.
[168]罗娟娟.农民收入分布函数的探讨[J].保险职业学院学报,2007,21(1):70-74.
[169]罗娟娟.我国农民收入和消费的相互影响[D].中南大学,2007.
[170]罗军.产能过度增长的成因及影响[J].中国国情国力,2011,(2):23-25.
[171]穆月英.中国城乡居民消费需求系统的AIDS模型分析[J].经济问题,2001(8):25-28.
[172]乔为国,孔欣欣.中国居民收入差距对消费倾向变动趋势的影响[J].当代经济科学,2005,27(5):1-5.
[173]屈小博,霍学喜.农户消费行为两阶段LES-AIDS模型分析——基于陕西省农村住户的微观实证[J].中国人口科学,2007(5):80-87.
[174]任玉珑,陈容,史乐峰.基于Logistic组合模型的中国民用汽车保有量预测[J].工业技术经济,2011,(8):90-97.
[175]史玉伟.消费函数理论主要假说述评[J].经济经纬,2005(3):17-19.
[176]苏铭.我国轿车需求的影响因素、趋势及区域变化——基于居民家用轿车保有量的实证分析[J].山西财经大学学报,2010,(1):43-49.
[177]苏鹏,孙巍.消费需求结构失衡的收入变迁效应说及实证检验[J].现代财经:天津财经学院学报,2013(9):15-23.
[178]苏鹏,孙巍.收入差距与内需不足：消费需求的非线性特征[J].商业研究,2013,(12):47-53.
[179]苏鹏,孙巍,姜博.收入分布变迁对社会总消费的影响[J].当代经济研究,2014,(1):77-83.
[180]孙巍,苏鹏.中国城镇居民收入分布的变迁研究[J].吉林大学社会科学学报,2013,53(3):23-31.
[181]孙巍,苏鹏.引入收入变迁因素的AIDS模型的扩展及实证检验[J].数理统计与管理,2013,32(4):658-668.
[182]孙巍,谢淑萍,朱嫒玲等.收入效应说与现阶段轿车市场需求的规律性——基于2004-2006年21种典型轿车月度数据的实证分析[J].商业研究,2008,(8):16-18.
[183]孙巍,杨程博,谢淑萍.现阶段城镇居民耐用品消费行为特征变化的计量研究[J].学习与探索,2013(1):108-112.
[184]孙巍,张馨月.中国家用车拥有量的饱和点测算——基于Gompertz模型的动态面板估计[J].消费经济,2011(1):46-49.
[185]万定山.中国城市居民收入分布的变化:1988—1999年[J].经济学(季刊),2005,4:45-66.
[186]王海港.我国居民收入分配的格局—帕雷托分布方法[J].南方经济，2006，24(5):73-82.
[187]王海港.中国居民家庭的收入变动及其对长期平等的影响[J].经济研究,2005,(1):56-66.
[188]王兢.拟合的收入分布函数在贫困线,贫困率测算中的应用[J].经济经纬,2005(2):66-68.
[189]王潼.我国城镇居民收入变迁研究[J].数量经济技术经济研究,2000,(8):19-21.
[190]王小鲁,樊纲.收入分配与公共政策[M].经济科学出版社,2005.
[191]王亚芬,肖晓飞,高铁梅.我国城镇居民收入分配差距的实证研究[J].财经问题研究，2007,(6):65-71.
[192]王艳,范金.收入差距与中国城镇居民消费行为的实证研究[J].管理工程学报,2007,21(1):6-11.
[193]沃塞曼著,吴喜之译.现代非参数统计[D].科学出版社,2008.
[194]吴涛,贺汉根,贺明科.核密度的随机加权估计及其应用[J].西北大学学报,2008,3:351-361.
[195]谢中华. MATLAB统计分析与应用:40个案例分析[M].北京:北京航空航天大学出版社,2010.
[196]徐建国.收入分布和耐用消费品的增长方式[J].北京大学中国经济研究中心学刊,2000,(8)：1-21.
[197]徐现祥,王海港.我国初次分配中的两极分化及成因[J].经济研究,2008,(2):106-118.
[198]许建华,张学工,李衍达.一种基于核函数的非线性感知器算法[J].计算机学报,2002,25:689-695.
[199]薛留根,廖靖宇.条件密度近邻核估计的逼近速度[J].应用概率统计,2001,2:163-167.
[200]余永定,李军.中国居民消费函数的理论与验证[J].中国社会科学,2000,1(12):3-1.
[201]袁志刚,宋铮.消费理论的新发展及其在中国的应用[J].上海经济研究,1999(6):2-9.
[202]袁志刚,朱国林.消费理论中的收入分配与总消费[J].中国社会科学,2002,2:69-76.
[203]袁志刚.中国居民消费前沿问题研究[M].复旦大学出版社,2011.
[204]臧旭恒,居民资产与消费选择行为分析[M].上海人民出版社,2001.
[205]臧旭恒,孙文祥.城乡居民消费结构:基于ELES模型和AIDS模型的比较分析[J].山东大学学报:哲学社会科学版,2004(6):122-126.
[206]臧旭恒,转型时期消费需求升级与产业发展研究[M].北京:经济科学出版社,2012.
[207]张帆.中国的粮食消费与需求[J].管理世界,1998(4):186-196.
[208]张广胜.农村市场发育对农户消费行为影响的实证研究[J].中国农村观察,2002(4):43-47.
[209]张启良,张驰.我国居民收入增长公平性研究[J].统计科学与实践,2010(4):7-9.
[210]张世伟,郝东阳.分位数上城镇居民消费支出的决定[J].财经问题研究,2011,(9):119-123.
[211]张馨月.基于收入变迁的城镇居民乘用车需求演化规律研究[D].吉林大学,2011.
[212]张屹山,陈默.泰尔(Theil)指数及其在中国的适用性检验——兼论收入分配与扩大内需[J].经济与管理研究,2012,(12):5-14.
[213]张瑜.我国城乡居民收入分布的核密度估计[J].统计与决策,2006(19):73-74.
[214]张宇. FDI技术外溢的地区差异与吸收能力的门限特征——基于中国省际面板数据的门限回归分析[J].数量经济技术经济研究,2008,25(1):28-39.
[215]张玉梅,喻闻,李志强.中国农村居民食物消费需求弹性研究[J].江西农业大学学报:社会科学版,2012,11(2):7-13.
[216]章上峰,许冰,胡祖光.中国城乡收入分布动态演进及经验检验[J].统计研究,2009,26(12):32-40.
[217]赵人伟,李实.中国居民收入差距的扩大及其原因[J].经济研究,1997,(9):19-28.
[218]赵人伟,李实,卡尔,李思勤.中国居民收入分配再研究[M].中国财政经济出版社,1999.
[219]周绍杰,张俊森,李宏彬.中国城市居民的家庭收入,消费和储蓄行为:一个基于组群的实证研究[J].经济学（季刊）,2009,8(4):1197-1220.
[220]周云波.城市化、城乡差距以及全国居民总体收入差距的变化——收入差距倒U形假说的实证检验[J].经济学（季刊）,2009,8(4):1239-1256.
[221]朱国林,范建勇,严燕.中国的消费不振与收入分配:理论和数据[J].经济研究,2002,5:72-80.
[222]朱国林.消费理论最新发展动态[J].经济学动态,2002,4:62-65.
[223]朱建平,朱万闯.中国居民消费的特征分析——中基于两阶段面板分位回归[J].数理统计与管理,2012,31(4):680-688.
[224]朱平芳,张征宇.无条件分位数回归:文献综述与应用实例[J].统计研究,2012(3):88-96.
[225]邹薇,周浩.经济趋同的计量分析与收入分布动态学研究[J].世界经济,2007,30(6):81-96.
[1] Ahluwalia M S. Income distribution and development: some stylized facts[J]. AmericanEconomic Review,1976,66(2):128-35.
[2] Ando A, Modigliani F. The life-cycle hypothesis of saving: aggregate implications andtests[J]. The American Economic Review,1963,53(1):55-84.
[3] Atkinson A B. The changing distribution of income: Evidence and explanations[J]. GermanEconomic Review,2000,1(1):3-18.
[4] Beierlein J G, Dunn J W, McConnon J C. The demand for electricity and natural gas in theNortheastern United States[J]. The Review of Economics and Statistics,1981,63(3):403-408.
[5] Blanciforti L, Green R. An almost ideal demand system incorporating habits: an analysis ofexpenditures on food and aggregate commodity groups[J]. The Review of Economics andStatistics,1983,65(3):511-515.
[6] Blinder A S. A Model of Inherited Wealth[J]. The Quarterly Journal of Economics,1973,87(4):608-626.
[7] Blinder A S. Distribution effects and the aggregate consumption function[J]. The Journal ofPolitical Economy,1975:447-475.
[8] Blinder A S. The relationship between distribution effects and the consumption[J]. TheJournal of Political Economy,2002,132(3):447-476.
[9] Blundell R, Pashardes P, Weber G. What do we learn about consumer demand patterns frommicro data?[J]. American Economic Review,1993,83(3):570-597.
[10] Borooah V K, Sharpe D R. Aggregate consumption and the distribution of income in theUnited Kingdom: an econometric analysis[J]. Economic Journal,1986,96(382):449-66.
[11] Brems H. Long-run automobile demand[J]. The Journal of Marketing,1956,20(4):379-384.
[12] Burney N A, Akmal M. Food demand in Pakistan: an application of the extended linearexpenditure system[J]. Journal of Agricultural Economics,1991,42(2):185-195.
[13] Buse A. Aggregation, distribution and dynamics in the linear and quadratic expendituresystems[J]. The Review of Economics and Statistics,1992,(74):45-53.
[14] Buse A. Evaluating the linearized almost ideal demand system[J]. American Journal ofAgricultural Economics,1994,76(4):781-793.
[15] Button K, Ngoe N and Hine J. Modelling vehicle ownership and use in low incomecountries[J]. Journal of Transport Economics and Policy,1993,27(1):51-67.
[16] Caballero R J. Consumption puzzles and precautionary saving[J]. Journal of MonetaryEconomics,1990,25:113-136.
[17] Cambell J Y, Deaton A S. Why is consumption so smooth[J]. Review of Economic Study,1989,56:357-373.
[18] Campbell J Y, Mankiw N G. The response of consumption to income: a cross-countryinvestigation[J]. European economic review,1991,35(4):723-756.
[19] Caner M, Hansen B E. Instrumental variable estimation of a threshold model[J].Econometric Theory,2004,20(5):813-843.
[20] Carroll C D. Buffer-stock saving and the life cycle/permanent income hypothesis[J]. TheQuarterly Journal of Economics,1997,112(1):1-55.
[21] Chakrabarty M, Schmalenbach A, Racine J. On the distributional effects of income in anaggregate consumption relation[J]. Canadian Journal of Economics/Revue canadienned’Economique,2006,39(4):1121-1243.
[22] Chernozhukov V, Hansen C. The effects of401(k) participation on the wealth distribution:an instrumental quantile regression analysis[J]. Review of Economics and Statistics,2004,86(3):735-751.
[23] Chernozhukov V, Hansen C. Instrumental variable quantile regression: A robust inferenceapproach[J]. Journal of Econometrics,2008,142(1):379-398.
[24] Chernozhukov V, Hansen C, Jansson M. Inference approaches for instrumental variablequantile regression[J]. Economics Letters,2007,95(2):272-277.
[25] Collado M D. Estimating dynamic models from time series of independentcross-sections[J]. Journal of Econometrics,1997,82(1):37-62.
[26] Cowell F A. Measuring inequality[M]. London: Prentice Hall/Harvester Wheatsheaf,1995.
[27] Cutler D M, Katz L F. Rising inequality? changes in the distribution of income andconsumption in the1980s[R]. National Bureau of Economic Research,1992.
[28] Dagum C. A new model for personal income distribution: specification and estimation[J].Economie Appliquée,1977,30(3):413-437.
[29] Dagum C. Wealth distribution models: analysis and applications[J]. Statistica,2006,(3):235-268.
[30] Dargay J, Gately D and Sommer M. Vehicle ownership and income growth, worldwide:1960-2030[J]. The Energy Journal,2007,28(4):143-170.
[31] Deaton A, Muellbauer J. An almost ideal demand system[J]. The American EconomicReview,1980,70(3):312-326.
[32] Deaton A. Panel data from time series of cross-sections[J]. Journal of Econometrics,1985,30(1):109-126.
[33] Deaton A. Saving and Liquidity Constraints[J]. Econometrica,1991,59(5):1221-1248.
[34] Deaton A. The analysis of household surveys: a microeconometric approach todevelopment policy[M]. World Bank Publications,1997.
[35] Diewert W E. Exact and superlative index numbers[J]. Journal of econometrics,1976,4(2):115-145.
[36] Dissanayake D, Morikawa T. Investigating household vehicle ownership, mode choice andtrip sharing decisions using a combined revealed preference/stated preference Nested Logitmodel: case study in Bangkok Metropolitan Region[J]. Journal of Transport Geography,2010,18(3):402-410.
[37] Dong D, Capps Jr O. Impacts Of Income Distribution On Market Demand[C]//1998Annualmeeting, August2-5, Salt Lake City, UT. American Agricultural Economics Association(New Name2008: Agricultural and Applied Economics Association),1998(20996).
[38] Duesenberry J S. Income Saving and the Theory[M]. Harvard University Press,1949.
[39] Dynan K E. How prudent are consumers?[J]. Journal of Political Economy,1993,101(6):1104-1113.
[40] Dynan K E. Habit formation in consumer preferences: Evidence from panel data[J].American Economic Review,2000,90(3):391-406.
[41] Firpo S, Fortin N M, Lemieux T. Unconditional quantile regressions[J]. Econometrica,2009,77(3):953-973.
[42] Flavin M A. The excess smoothness of consumption: identification and estimation[J].Review of Economic Studies,1993,60:651-666.
[43] Friedman M. A Theory of the Consumption Function[M]. Princeton: Princeton UniversityPress,1957.
[44] Fr lich M, Melly B. Unconditional quantile treatment effects under endogeneity[R]. IZADiscussion Papers,2008.
[45] Fr lich M, Melly B. Unconditional quantile treatment effects under endogeneity[J]. Journalof Business&Economic Statistics,2013(just-accepted).
[46] Gibrat R. Les inégalités économiques[M]. Recueil Sirey,1931.
[47] Girma S. A quasi-differencing approach to dynamic modelling from a time series ofindependent cross-sections[J]. Journal of Econometrics,2000,98(2):365-383.
[48] Gorman W M. Community preference fields[J]. Econometrica: journal of the EconometricSociety,1953,21:63-80.
[49] Gorman W M. Lecture notes[R]. London School of Economics, Mimeo,1971.
[50] Gorman W M. On a class of preference fields[J]. Metroeconomica,1961,13(2):53-56.
[51] Gorman W M. Separable utility and aggregation[J]. Econometrica: Journal of theEconometric Society,1959,27(3):469-481.
[52] Gosling A, Machin S, Meghir C. What Has Happened to Men's Wages since the Mid‐1960s?[J]. Fiscal Studies,1994,15(4):63-87.
[53] Hall R E. Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theoryand Evidence[J]. The Journal of Political Economy,1978,86(6):971-987.
[54] Hannan E J. Principles of Econometrics[J]. Technometrics,1973,15(1):195-196.
[55] Hansen B E. Inference in TAR models[J]. Studies in Nonlinear Dynamics andEconometrics,1997,2(1):1-14.
[56] Hansen B E. Threshold effects in non-dynamic panels: Estimation, testing, and inference[J].Journal of econometrics,1999,93(2):345-368.
[57] Hansen B E. Sample splitting and threshold estimation[J]. Econometrica,2000,68(3):575-603.
[58] Hansen B E, Seo B. Testing for two-regime threshold cointegration in vectorerror-correction models[J]. Journal of Econometrics,2002,110(2):293-318.
[59] Heien D M. Demographic effects and the multiperiod consumption function[J]. Journal ofPolitical Economy,1972,80(1):125-38.
[60] Hyslop D, Maré D. Understanding changes in the distribution of household incomes inNew Zealand between1983-86and1995-98[R]. New Zealand Treasury,2001.
[61] Ibrahim A Ahmad, Yanqin Fan, Optimal bandwidth for kernel density estimators offunctions of observations[J]. Statistics&Probability Letters,2005,51(3):245-251.
[62] Jenkins S P, Van Kerm P. Accounting for income distribution trends: a density functiondecomposition approach[J]. Journal of Economic Inequality,2005,(3):43-61.
[63] Jones E, Mustiful B W. Purchasing behaviour of higher-and lower-income shoppers: a lookat breakfast cereals[J]. Applied Economics,1996,28(1):131-137.
[64] Keynes J M. The General Theory of Employment, Interest and Money[M]. New York,1936.
[65] Koenker R, Bassett G. Regression quantiles[J]. Econometrica: Journal of the EconometricSociety,1978,46(1):33-50.
[66] Koenker R, Machado J A F. Goodness of fit and related inference processes for quantileregression[J]. Journal of the american statistical association,1999,94(448):1296-1310.
[67] Koenker R. Quantile regression for longitudinal data[J]. Journal of Multivariate Analysis,2004,91(1):74-89.
[68] Koenker R. Quantile regression[M]. Cambridge University Press,2005.
[69] Koenker, R., Kevin F. Hallock, Quantile Regression[J]. The Journal of EconomicPerspectives,2001,15(4):143-156.
[70] Leland H E. Saving and uncertainty: The precautionary demand for saving[J]. TheQuarterly Journal of Economics,1968,82(3):465-473.
[71] Li H, Zou H. Income inequality is not harmful for growth: theory and evidence[J]. Reviewof Development Economics,1998,2(3):318-334.
[72] Lluch C, Williams R. Consumer demand systems and aggregate consumption in the USA:An application of the extended linear expenditure system[J]. Canadian Journal ofEconomics,1975,8(1):49-66.
[73] Lluch C, Williams R. Cross country demand and savings patterns: An application of theextended linear expenditure system[J]. The Review of Economics and Statistics,1975,8:320-328.
[74] Lluch C. The extended linear expenditure system[J]. European Economic Review,1973,4(1):21-32.
[75] Lou F, Li X. An empirical analysis of income disparity and consumption in China[J].Frontiers of Economics in China,2011,6(1):157-170.
[76] Minoiu, C., Poverty Analysis based on kernel density estimates from grouped data [R].Working Paper,2006
[77] Manski C F. Identification problems in the social sciences[M]. Harvard University Press,1995.
[78] McDonald J B. Some generalized functions for the size distribution of income[J].Econometrica: Journal of the Econometric Society,1984,52:647-663.
[79] Melly B. Decomposition of differences in distribution using quantile regression[J]. LabourEconomics,2005,12(4):577-590.
[80] Modigliani F, Ando A. The'Permanent Income'and the'Life Cycle'Hypothesis of SavingBehavior: Comparison and Tests[C]//Proceedings of the Conference on Consumption andSaving.1960,2:49-174.
[81] Modigliani F, Brumberg R. Post Keynesian Economics[M]. New Brunswick N J: RutgersUniversity Press,1954.
[82] Muellbauer J. Community preferences and the representative consumer[J]. Econometrica:Journal of the Econometric Society,1976,44(5):979-999.
[83] Musgrave P. Income distribution and the aggregate consumption function[J]. Journal ofPolitical Economy,1980,88(3):504-525.
[84] O'Dea D. The changes in New Zealand's income distribution[R]. New Zealand Treasury,2000.
[85] Parzen E. On estimation of a probability density function and mode[J]. Annals ofmathematical statistics,1962,33(3):1065-1076.
[86] Pashardes P. Bias in estimating the almost ideal demand system with the stone indexapproximation[J]. The Economic Journal,1993,103:908-915.
[87] Pearce I F. A contribution to demand analysis[M]. Clarendon Press,1964.
[88] Pittau M G, Zelli R. Testing for changing shapes of income distribution: Italian evidence inthe1990s from kernel density estimates[J]. Empirical Economics,2004,29(2):415-430.
[89] Powell D. Unconditional quantile regression for exogenous or endogenous treatmentvariables[R].2011.
[90] Reed W J. On Pareto’s law and the determinants of Pareto exponents[J]. Journal of IncomeDistribution,2004,13:7-17.
[91] Reed W J. The Pareto law of incomes—an explanation and an extension[J]. Physica A:Statistical Mechanics and its Applications,2003,319:469-486.
[92] Rosenblatt M. Remarks on some nonparametric estimates of a density function[J]. TheAnnals of Mathematical Statistics,1956,27(3):832-837.
[93] Rudemo M. Empirical choice of histograms and kernel density estimators[J]. ScandinavianJournal of Statistics,1982,9:65-78.
[94] Salem A B Z, Mount T D. A convenient descriptive model of income distribution: thegamma density[J]. Econometrica,1974,42(6):1115-1127.
[95] Silverman B W. Using kernel density estimates to investigate multimodality[J]. Journal ofthe Royal Statistical Society. Series B (Methodological),1981,43:97-99.
[96] Simmons P. Evidence on the Impact of Income Distribution on Consumer Demand in theUK1955–68[J]. The Review of Economic Studies,1980,47(5):893-906.
[97] Singh S K, Maddala G S. A Function for Size Distribution of Incomes[J]. Econometrica:Journal of the Econometric Society,1976,44:963-970.
[98] Singh S K, Maddala G S. A function for size distribution of incomes[M]//Modeling incomedistributions and Lorenz curves. Springer New York,2008:27-35.
[99] Singh, S. K., G. S. Maddala. A Function for the Size Distribution of Incomes[J].Econometrica,1976,44:963-970.
[100] Stiglitz J E. Distribution of income and wealth among individuals[J]. Econometrica:Journal of the Econometric Society,1969,37(3):382-397.
[101] Stoker T M. Simple tests of distributional effects on macroeconomic equations[J]. TheJournal of Political Economy,1986,94(4):763-795.
[102] Stoker T M. Empirical approaches to the problem of aggregation over individuals[J].Journal of Economic Literature,1993,31:1827-1874.
[103] Stone R. Linear expenditure systems and demand analysis: an application to the pattern ofBritish demand[J]. The Economic Journal,1954,64(9):511-527.
[104] Storchmann K. Long-run gasoline demand for passenger cars: the role of incomedistribution[J]. Energy Economics,2005,27(1):25-58.
[105] Taillie C. Lorenz ordering within the generalized gamma family of income distributions[J].Statistical Distributions in Scientific Work,1981,6:181-192.
[106] Taillie C. Lorenz ordering within the Generalized Gamma Family of IncomeDistributions[M]. in Taillie, C., G. P. Patil and B. Balderssari (eds.). Statistical Distributionsin Scientific Work,1981,6:181–192, Boston.
[107] Theil, H., Principles of Econometrics[M]. New York: North Holland Press,1971.
[108] Wan G. Accounting for income inequality in rural China: a regression-based approach[J].Journal of Comparative Economics,2004,32(2):348-363.
[109] Wilfling B, Kr mer W. The Lorenz-ordering of Singh-Maddala income distributions[J].Economics Letters,1993,43(1):53-57.
[110] Wu C O. Kernel smoothing of the nonparametric maximum likelihood estimation forbiased sampling models[J]. Math Methods Statist,1996,5:275-298.
[111] Yen S T, Chern W S. Flexible demand systems with serially correlated errors：fat and oilconsumption in the United States[J]．American Journal of Agicultural Economics,1992,8:689-697.
[112] Zeldes S P. Consumption and liquidity constraints: an empirical investigation[J]. TheJournal of Political Economy,1989,97(2):305-346.
[113] Zeldes S P. Optimal Consumption with Stochastic Income: Deviations from CertaintyEquivalence[J]. The Quarterly Journal of Economics,1989,104(2):275-298.
[114] Zhihao Zheng, Henneberry, The Impact of Changes in Income Distribution on Current andFuture Food Demand in Urban China[J]. Journal of Agricultural and Resource Economics,2010,35:51–71.
[115] Zhou J, Zhang D. A Research on the Relationship between Urban Households’ Income andExpenditure in Hainan[J]. Technology and Investment,2013,4:12-17.
[116]安格斯迪顿,约翰米尔鲍尔.经济学与消费者行为[M].中国人民大学出版社,2005.
[117]白仲林,赵亮.天津市城镇居民收人流动性的实证分析——伪面板数据门限自回归模型的估计与检验[C].天津市社会科学界第七届学术年会优秀论文集,2011,1029-1040.
[118]白仲林,赵亮.我国通货膨胀率的最优目标区间几何?[J].统计研究,2011,28(6):6-10.
[119]白仲林.面板数据模型的设定,统计检验和新进展[J].统计与信息论坛,2010,25(10):3-12.
[120]陈建宝,杜小敏,董海龙.基于分位数回归的中国居民收入和消费的实证分析[J].统计与信息论坛,2009,24(7):44-50.
[121]陈建宝,李坤明.收入分配,人口结构与消费结构:理论与实证研究[J].上海经济研究,2013(4):74-87.
[122]陈娟,林龙,叶阿忠.基于分位数回归的中国居民消费研究[J].数量经济技术经济研究,2008,25(2):16-27.
[123]陈娟,孙敬水.我国城镇居民收入不平等变动实证研究——基于收入分布变化分解的视角[J].统计研究,2009,26(9):77-81.
[124]陈强.高级计量经济学及Stata应用[M].高等教育出版社,2010.
[125]陈秋玲,曹庆瑾,张阿丽.基于扩展线性支出系统模型的我国城镇居民消费结构分析[J].管理学报,2010,(1):68-72.
[126]陈希孺,柴根象.非参数统计教程[M].华东师范大学出版社,1993.
[127]陈云.居民收入分布及其变迁的统计研究[D].首都经济贸易大学,2009.
[128]陈云.中国居民收入分布专题实证研究——居民收入分布变迁测度及其影响因素分解[J].统计与信息论坛,2013,28(2):3-9.
[129]陈宗胜,周云波.再论改革与发展中的收入分配[M].经济科学出版社,2002.
[130]蔡玉程,金晓彤.关于我国消费需求不足问题的思考[J].江汉论坛,1999,(12):23-24.
[131]程磊.收入差距扩大与中国内需不足：理论机制与实证检验[J].经济科学,2011,(1):11-24.
[132]迟福林.消费主导:中国转型大战略[M].中国经济出版社,2012.
[133]迟巍,黎波,余秋梅.基于收入分布的收入差距扩大成因的分解[J].数量经济技术经济研究,2008,(9):52-64.
[134]段先盛.收入分配对总消费影响的结构分析——兼对中国城镇家庭的实证检验[J].数量经济技术经济研究,2009(2):151-160.
[135]段先盛.收入分配对经济发展方式的影响：理论与实证[M].北京:人民出版社,2011.
[136]樊茂清,任若恩.基于异质性偏好的中国城镇居民消费结构研究[J].中国软科学,2007,10:37-46.
[137]范剑平.我国居民消费率偏低的原因分析与开拓城镇市场的对策选择[J].宏观经济研究,1999,(6):41-46.
[138]范剑平.鼓励消费政策可行性研究[J].经济科学,2001(2):5-14.
[139]范剑平.论投资主导型向居民消费,社会投资双拉动型转换——我国经济增长的需求结构分析[J].经济学动态,2003(2):11-14.
[140]方福前.中国居民消费需求不足原因研究[J].中国社会科学,2009,2:68-82.
[141]封福育.名义利率与通货膨胀:对我国“费雪效应”的再检验——基于门限回归模型分析[J].数量经济技术经济研究,2009(1):89-98.
[142]高铁梅.计量经济分析方法与建模：Eviews应用及实例（第二版）[M].北京：清华大学出版社,2009.
[143]古继宝,荣敏,吴剑琳.中国民用汽车保有量的组合预测[J].工业技术经济,2010,29(4):123-127.
[144]郭其友,芦丽静.经济持续增长动力的转变——消费主导型增长的国际经验与借鉴[J].中山大学学报:社会科学版,2009,49(2):190-197.
[145]杭斌,郭香俊.基于习惯形成的预防性储蓄——中国城镇居民消费行为的实证分析[J].统计研究,2009,(3):38-43.
[146]杭斌,申春兰.潜在流动性约束与预防性储蓄行为——理论框架及实证研究[J].管理世界,2006(9):28-35.
[147]杭斌,闫新华.经济快速增长时期的居民消费行为——基于习惯形成的实证分析[J].经济学（季刊）,2013,12(4):1191-1208.
[148]郝令昕,奈曼.分位数回归模型[M].肖东亮译,上海:格致出版社:上海人民出版社,2012.
[149]贺振华,寇宗来.收入分布,厂商定价与耐用品的消费扩张[J].南方经济,2006,(8):5-16.
[150]洪求枝,高明成,夏莹娇.灰色系统预测方法在我国私人汽车拥有量预测中的应用[J].长江大学学报自然科学版:理工卷,2008,5(1):132-134.
[151]胡祖光.基尼系数理论最佳值及其简易计算公式研究[J].经济研究,2004,9:60-69.
[152]金晓彤,蔡玉程,董直庆.中国城镇居民间歇式周期性波动的消费行为[J].吉林大学社会科学学报,2007,(6):123-127.
[153]金晓彤,董直庆,盛光华.连锁效应导引下的中国城镇居民消费行为:理论假说与实态验证[J].经济科学,2004,(4):74-83.
[154]金晓彤,杨晓东.中国城镇居民消费行为变异论的四个假说及其理论分析[J].管理世界,2004,(11):7-16+30.
[155]李春玲.当代中国社会的消费分层[J].中山大学学报(社会科学版),2007,4:8-13.
[156]李建伟.居民收入分布对耐用消费品及经济增长周期的影响——以城镇居民家庭乘用车为例[J].经济纵横,2013,(6):1-11.
[157]李军.收入差距对消费需求影响的定量分析[J].数量经济技术经济研究,2003,(9):5-11.
[158]李实,罗楚亮.中国城乡收入差距的重新估计[J].北京大学学报(哲学社会科学版),2007,2:12-24.
[159]李实,罗楚亮.中国收入差距究竟有多大?[J].经济研究,2011,4:68-79.
[160]李玉忍,高社生,张学源.核密度的随机加权估计及其应用[J],西北大学学报,2008,3:351-361.
[161]厉以宁.消费经济学[M].北京:人民出版社,1984.
[162]林伯强.中国的经济增长,贫困减少与政策选择[J].经济研究,2003,(12):15-26.
[163]林文芳.区域性偏好与城乡居民消费差异[J].统计研究,2009,26(11):87-92.
[164]林毅夫.潮涌现象与发展中国家宏观经济理论的重新构建[J].经济研究,2007,(1):126-131.
[165]林毅夫,巫和懋,邢亦青.“潮涌现象”与产能过剩的形成机制[J].经济研究,2010,(10):4-l9.
[166]刘华,钟甫宁.食物消费与需求弹性——基于城镇居民微观数据的实证研究[J].南京农业大学学报:社会科学版,2009,9(3):36-43.
[167]刘重力,黄平川.技术进口对我国企业技术创新能力的影响——基于中国省际数据的分位数回归[J].南开经济研究,2012(5):132-141.
[168]罗娟娟.农民收入分布函数的探讨[J].保险职业学院学报,2007,21(1):70-74.
[169]罗娟娟.我国农民收入和消费的相互影响[D].中南大学,2007.
[170]罗军.产能过度增长的成因及影响[J].中国国情国力,2011,(2):23-25.
[171]穆月英.中国城乡居民消费需求系统的AIDS模型分析[J].经济问题,2001(8):25-28.
[172]乔为国,孔欣欣.中国居民收入差距对消费倾向变动趋势的影响[J].当代经济科学,2005,27(5):1-5.
[173]屈小博,霍学喜.农户消费行为两阶段LES-AIDS模型分析——基于陕西省农村住户的微观实证[J].中国人口科学,2007(5):80-87.
[174]任玉珑,陈容,史乐峰.基于Logistic组合模型的中国民用汽车保有量预测[J].工业技术经济,2011,(8):90-97.
[175]史玉伟.消费函数理论主要假说述评[J].经济经纬,2005(3):17-19.
[176]苏铭.我国轿车需求的影响因素、趋势及区域变化——基于居民家用轿车保有量的实证分析[J].山西财经大学学报,2010,(1):43-49.
[177]苏鹏,孙巍.消费需求结构失衡的收入变迁效应说及实证检验[J].现代财经:天津财经学院学报,2013(9):15-23.
[178]苏鹏,孙巍.收入差距与内需不足：消费需求的非线性特征[J].商业研究,2013,(12):47-53.
[179]苏鹏,孙巍,姜博.收入分布变迁对社会总消费的影响[J].当代经济研究,2014,(1):77-83.
[180]孙巍,苏鹏.中国城镇居民收入分布的变迁研究[J].吉林大学社会科学学报,2013,53(3):23-31.
[181]孙巍,苏鹏.引入收入变迁因素的AIDS模型的扩展及实证检验[J].数理统计与管理,2013,32(4):658-668.
[182]孙巍,谢淑萍,朱嫒玲等.收入效应说与现阶段轿车市场需求的规律性——基于2004-2006年21种典型轿车月度数据的实证分析[J].商业研究,2008,(8):16-18.
[183]孙巍,杨程博,谢淑萍.现阶段城镇居民耐用品消费行为特征变化的计量研究[J].学习与探索,2013(1):108-112.
[184]孙巍,张馨月.中国家用车拥有量的饱和点测算——基于Gompertz模型的动态面板估计[J].消费经济,2011(1):46-49.
[185]万定山.中国城市居民收入分布的变化:1988—1999年[J].经济学(季刊),2005,4:45-66.
[186]王海港.我国居民收入分配的格局—帕雷托分布方法[J].南方经济，2006，24(5):73-82.
[187]王海港.中国居民家庭的收入变动及其对长期平等的影响[J].经济研究,2005,(1):56-66.
[188]王兢.拟合的收入分布函数在贫困线,贫困率测算中的应用[J].经济经纬,2005(2):66-68.
[189]王潼.我国城镇居民收入变迁研究[J].数量经济技术经济研究,2000,(8):19-21.
[190]王小鲁,樊纲.收入分配与公共政策[M].经济科学出版社,2005.
[191]王亚芬,肖晓飞,高铁梅.我国城镇居民收入分配差距的实证研究[J].财经问题研究，2007,(6):65-71.
[192]王艳,范金.收入差距与中国城镇居民消费行为的实证研究[J].管理工程学报,2007,21(1):6-11.
[193]沃塞曼著,吴喜之译.现代非参数统计[D].科学出版社,2008.
[194]吴涛,贺汉根,贺明科.核密度的随机加权估计及其应用[J].西北大学学报,2008,3:351-361.
[195]谢中华. MATLAB统计分析与应用:40个案例分析[M].北京:北京航空航天大学出版社,2010.
[196]徐建国.收入分布和耐用消费品的增长方式[J].北京大学中国经济研究中心学刊,2000,(8)：1-21.
[197]徐现祥,王海港.我国初次分配中的两极分化及成因[J].经济研究,2008,(2):106-118.
[198]许建华,张学工,李衍达.一种基于核函数的非线性感知器算法[J].计算机学报,2002,25:689-695.
[199]薛留根,廖靖宇.条件密度近邻核估计的逼近速度[J].应用概率统计,2001,2:163-167.
[200]余永定,李军.中国居民消费函数的理论与验证[J].中国社会科学,2000,1(12):3-1.
[201]袁志刚,宋铮.消费理论的新发展及其在中国的应用[J].上海经济研究,1999(6):2-9.
[202]袁志刚,朱国林.消费理论中的收入分配与总消费[J].中国社会科学,2002,2:69-76.
[203]袁志刚.中国居民消费前沿问题研究[M].复旦大学出版社,2011.
[204]臧旭恒,居民资产与消费选择行为分析[M].上海人民出版社,2001.
[205]臧旭恒,孙文祥.城乡居民消费结构:基于ELES模型和AIDS模型的比较分析[J].山东大学学报:哲学社会科学版,2004(6):122-126.
[206]臧旭恒,转型时期消费需求升级与产业发展研究[M].北京:经济科学出版社,2012.
[207]张帆.中国的粮食消费与需求[J].管理世界,1998(4):186-196.
[208]张广胜.农村市场发育对农户消费行为影响的实证研究[J].中国农村观察,2002(4):43-47.
[209]张启良,张驰.我国居民收入增长公平性研究[J].统计科学与实践,2010(4):7-9.
[210]张世伟,郝东阳.分位数上城镇居民消费支出的决定[J].财经问题研究,2011,(9):119-123.
[211]张馨月.基于收入变迁的城镇居民乘用车需求演化规律研究[D].吉林大学,2011.
[212]张屹山,陈默.泰尔(Theil)指数及其在中国的适用性检验——兼论收入分配与扩大内需[J].经济与管理研究,2012,(12):5-14.
[213]张瑜.我国城乡居民收入分布的核密度估计[J].统计与决策,2006(19):73-74.
[214]张宇. FDI技术外溢的地区差异与吸收能力的门限特征——基于中国省际面板数据的门限回归分析[J].数量经济技术经济研究,2008,25(1):28-39.
[215]张玉梅,喻闻,李志强.中国农村居民食物消费需求弹性研究[J].江西农业大学学报:社会科学版,2012,11(2):7-13.
[216]章上峰,许冰,胡祖光.中国城乡收入分布动态演进及经验检验[J].统计研究,2009,26(12):32-40.
[217]赵人伟,李实.中国居民收入差距的扩大及其原因[J].经济研究,1997,(9):19-28.
[218]赵人伟,李实,卡尔,李思勤.中国居民收入分配再研究[M].中国财政经济出版社,1999.
[219]周绍杰,张俊森,李宏彬.中国城市居民的家庭收入,消费和储蓄行为:一个基于组群的实证研究[J].经济学（季刊）,2009,8(4):1197-1220.
[220]周云波.城市化、城乡差距以及全国居民总体收入差距的变化——收入差距倒U形假说的实证检验[J].经济学（季刊）,2009,8(4):1239-1256.
[221]朱国林,范建勇,严燕.中国的消费不振与收入分配:理论和数据[J].经济研究,2002,5:72-80.
[222]朱国林.消费理论最新发展动态[J].经济学动态,2002,4:62-65.
[223]朱建平,朱万闯.中国居民消费的特征分析——中基于两阶段面板分位回归[J].数理统计与管理,2012,31(4):680-688.
[224]朱平芳,张征宇.无条件分位数回归:文献综述与应用实例[J].统计研究,2012(3):88-96.
[225]邹薇,周浩.经济趋同的计量分析与收入分布动态学研究[J].世界经济,2007,30(6):81-96.