On The Cross-Provincial Consumption Convergence Of Chinese Rural Residents

Welfare assessment lays the foundations of public policy analysis. If something went wrong in this process, a government would not be able to measure the effects of current public policies effectively, nor would it be able to give an accurate prediction to a policy it is going to launch. As a result, public resources would be painfully wasted, and, moreover, right and wrong would be confused, leading to a serious social security problem.Unfortunately, two important things do usually go wrong in this process, especially when the measurement of welfare inequality is concerned:(1) Inappropriate measurement base. In the tradition of classic economics welfare was measured mainly based upon income. But in recent years more and more economists have pinpointed the defects of this type of measurement. They believed that welfare condition would be measured more direct by consumption than by income, and argued that income-based measurement should be replaced by consumption-based measurement. (2) Improper measurement indicators. In current economic literature, mean, variance (or standard deviation), Gini coefficient, Theil index and Atkinson index have been commonly used to indicate welfare inequality. But researches based upon these indicators tend to lead to confusing conclusions. In view of these defects, effective welfare measurement necessitates modification of measurement base as well as improvement in methodology. As a logical way of thinking, it would be more effective to study consumption convergence direct, since it can provide richer information than traditional way of measurement based upon discrepancy or inequality indicators, and thus represents a more general alternative to current procedures. This precisely constitutes the starting point of this dissertation.Meanwhile, in the past two decades, many new methods have found their way in the studies of income convergence. As a logical step forward, after interweaving practical problems and methodologies, it would be natural to apply these methodologies to the study of consumption convergence. But even in the field of income convergence study, there are still many limitations in terms of methodology. In view of this, based upon current methodology, this dissertation tries to apply some new methods to consumption convergence study in a comprehensive methodological framework composed by kernel conditional distribution, infinite mixture distribution model, and quantile regression.In the past two decades, with the rapid development of mass media and mobility of people between regions, inter-regional relationships have become increasingly closer, therefore, the interaction of consumption behavior should have to be taken into consideration in studying consumption convergence of rural residents across 31 provinces in China. And this is just the central idea of Tobler's First Law of Geography. In fact, from an econometric perspective, even in the absence of substantive influence across regions, as long as spatial autocorrelation or spatial heteroscedasticity exists, it should have to be taken into consideration or else the results would be biased. Therefore, to avoid misleading results, this dissertation studies consumption convergence across 31 provinces from a spatial perspective, in order to uncover the rule behind the dynamics of consumption distribution and thus to provide some reference to related policy-making departments in China.The whole dissertation is composed of 7 chapters. Chapter 1 is the preface. In Chapter 2, literature in closely related fields is concisely reviewed. In Chapter 3, spatial autocorrelation is tested in terms of spatial cross-sectional data and spatial econometric models to determine whether there exists spatial effect in various expenditures. Chapter 4 represents an exploratory study in which, based upon kernel conditional density, consumption convergence is studied by means of stochastic kernel in terms of per capita total expenditure and classified expenditures respectively, and spatial and income effect are explored. Chapter 5 serves as a confirmatory study in which consumption convergence is tested by means of infinite mixture models in terms of per capita total expenditure and classified expenditures respectively, and spatial and income effect are explored. Chapter 6 is as an explanatory study in which consumption convergence is explained by means of quantile regression models in terms of per capita total expenditure and classified expenditures respectively, and spatial effect is also explored. Chapter 7 constituteis the conclusion in which a summary is made and limitations of this paper are pointed out.Results show that:(1)The various cross-provincial per capita expenditures are all distributed as two locked modes, indicating a bi-modal club convergence; (2)The various cross-provincial per capita expenditures and per capita net income of the 31 Chinese provinces show significant spatial autocorrelation; (3)Spatial autocorrelation influences consumption convergence in some degree, but is not strong enough to change the whole nature; (4)The per capita net income is the first important cause of consumption convergence, and can explain consumption convergence fairly well. But even though, it is not the sole cause.Spatial effect and income combined together can almost explain all the information about consumption convergence; (5)In contrast to the traditional assumption of decreasing MPC(marginal propensity to consume), the MPC of the Chinese rural residents is increasing. Interestingly, this seemingly unusual result explains the special bi-modal converging consumption pattern of the rural residents across the 31 Chinese provinces; (6)The income elasticities of various expenditures display a non-linear pattern, which is also different from traditional assumption.Research conclusions derived from this dissertation are of some value to both policy-makers and industrial practitioners at various levels:(1) At the macro level, they can provide reference to policy-making in terms of transfer programs, regional development as well as domestic demand expansion; (2)At the medium level, they can help governments at various levels in designing industrial development and adjustment plans; (3)At the micro level, they can aid companies of various size in designing business portfolio, predicting sales volumes, segmenting and targeting customers as well launching new products and expanding market coverage.