The Different Consumption Between Rural and Urban Areas in China

Transcription

1 Spring semester 2009 The Different Consumption Between Rural and Urban Areas in China Thesis in Economics (Bachelor Thesis) Author: Qin Ke ( ) Examinator: Dominique Anxo Advisor: Håkan Locking Mats Hammarstedt 1

2 Abstract Since the reform and opening up in 1978, China s economy began to grow at a high speed for thirty years. In 2007, the GDP of China was billion RMB, which was the fourth one in the world. However, under these achievement, China s economy was still face with some problems, such as the different consumption between rural and urban areas. In this thesis, on the basis of China Statistical Yearbook from 1998 to 2007, I will analyze the differences in the level and pattern of consumption between rural and urban areas. In order to reasch these differernces deeply, I divide consumption to eight items, which are Food, Clothes, Housing, Daily necessities, Transportations & Telecommunications, Culture Education & Recreation, Medical and Health Care, and Others. Then I create a model according to Keynes s theory about consumption. Through the regression I can estimate the different consumption between rural and urban areas in each kind of goods. After the regression of different consumption between rural and urban areas in eight items, I find two important characters. First, the constant basic consumption in rural area is less than urban one. Second, the disposable income elasticity of demand in rural area are more than urban one. So I think the gap of disposable income limits comsuption in rural area and creates the different consumption between rural and urban areas fundamentally. Key words: different consumption rural and urban areas consumption structure 2

3 Content 1. Introduction Main differences in the level and pattern of consumption between rural and urban areas The difference in the level of consumption The difference in consumption structure Methodology The economic knowledge Keynes s general theory The dummy variable The Model Data Results from the regression Conclusion Reference Appendix

4 1. Introduction Since reform and opening up in 1978, China opened the door to the world and started the new development in the economy, up to now, the GDP of China has kept growing at a high speed for 30 years, from billion RMB (1978) to billion (2007) 1. At the same time, the income of Chinese resident also has an obvious improvement, the data from the China State Statistic Bureau ( ) and China statistical Yearbook ( ) reveals that the per capita disposable income of urban resident has increased from RMB (1978) to RMB (2007) and the per capita disposable income of rural resident has grown from RMB (1978) to RMB (2007) 2, of course, all of these data are nominal. In the same way, consumption of Chinese household naturally has improved greatly, too. Absolutely, the achievement of China economy in the past 30 years were great and exciting to all of the world, however, if we research these economic data deeply, we will find that there are still many questions in China, such as the different consumption between rural and urban areas. In 2007, the total consumption of Chinese households reached billion RMB, in which rural consumption was billion RMB, urban consumption was billion RMB. The level of consumption in urban area is almost three times more than rural one. Here we need to notice that the rural population was % in the total population in China. Therefore, the amount of the consumption are much different between rural and urban areas. At the sme time, the differences are not only appeared in the level of consumption, but also revealed clearly in the structure of consumption. 1. The data is in the appendix 1,from China State Statistic Bureau ( ) 2. The data is in the appendix 2, from China statistical Yearbook ( ). 4

5 According to the China Statistical Yearbook, it divide consumption to eight items, which are Food, Clothes, Housing, Daily necessities, Transportations & Telecommunications, Culture Education & Recreation, Medical and Health Care, and Others. In order to know consumption structure deeply, we should analyze consumption of each item between rural and urban areas. In this article, through views of the level and the structure, I choose the data mainly from 1998 to 2007 to research the different consumption between rural and urban residents. About the economic theories and the model, I mainly ues the Keynes s General Theory 3 and some econometrics methods to research more details of the different consuption between rural and urban areas. At the end, I use the software, the Eview 3.1 to get the result of regression, and estimate whether each kind of goods between rural and urban areas is consumed differently? How different is consumption between rural and urban areas? 3. John Maynard Keynes (1936 ) 5

6 consumption(yuan) 2. Main differences in the level and pattern of consumption between rural and urban areas In China, the developments between rural area and urban areas are very different. Therefore, we have to research Chinese consumption through two kinds of households. 2.1 The difference in the level of consumption From 1998 to 2007, the level of the consumption in rural area and urban areas are both increasing a lot. However, the average per capita consumption in the rural area reveals the different character from the urban area. Looking at the following figure 1, the data are shown in the appendix 3. Figure 1: The comparation between the urban and rural areas in the average per capita consumptin urban areas rural areas year Sources: China State Statistic Bureau ( ); China statistical Yearbook ( ). 6

7 In this figure, the blue line where points are the average per capita consumption in urban area grows steeply, but the red one which means the average per capita consumption in rural area is flat. Therefore, it is easy to find that the growing speed of the average per capita consumption in urban area is visibly faster than the speed of increase in rural area. Besides, a very interesting truth is that although the rural population is larger than the urban one 1, its proportion of the gross consumption are becoming less and less. In the figure 2, we can see the rural proportion in the gross consumption has decreased almost 10 % in the past decade. Figure 2: 100% 80% The proportion of gross consumption between rural and urban areas 60% 40% 20% 0% year rural areas urban areas Sources: China State Statistic Bureau ( ); China statistical Yearbook ( ). Added that in 2007, Chinese pupolation is million, in which the rural pupolation is million and occupies %. 1. More informations about the data of Chinese population are in the appendix 4, from China statistical Yearbook ( ) 7

8 To sum up, the difference in the level of consumption is the important and clear character between rural and urban areas. But it is not an only point, the difference in consumption structure is also a main feature. 2.2 The difference in consumption structure In the thesis of Zhu Shie (2007) 2, the Engel s Coefficient 3 is used to analyze different consumption structure between rural and urban areas simply. The Engel s Coefficient is from Engel's law 4, which is an observation in economics stating that, with a given set of tastes and preferences, when income rises, the proportion of income spent on food falls, even if actual expenditure on food rises. In other words, the income elasticity of demand of food is less than 1. The Engel's Coefficient indicating the share of income spent on food and drinks is a major indicator of the people's living standard. According to the measure set by the Food and Agricultural Organization of the United Nations (FAO), an Engel's Coefficient above 59 percent represents absolutely poverty; percent, barely enough food and clothing; percent, a "moderately well-off" standard of living; percent, a "well-to-do" standard of living; and below 30 percent, a "wealthy" life. 5 If the Engel's Coefficient is big, it means people are poor and live in a bad level. In contrast, if the Engle Coefficient is small, it proofs people have more money except their basic cost of eating, they enjoy a good life. Figure 3 shows the Engel's Coefficient in the rural and the urban areas from 1998 to Zhu Shie (2007) 3. Engel's coefficient = consumption on food and drinks total consumption x100% 4.The function of Engel's law = change % of consumpion on food and drinks change % of disposable income x100%

9 tht engel coefficient(%) Figure 3: The comparation of engel coefficient between rural and urban residents The engel coefficient of rural residents The engel coefficient of urban residents year Sources: China statistical Yearbook ( ). In this figure, we know that the Engel's Coefficient of the rural and urban residents both decline in the past 10 years, and the trace of two lines also looks like similar. However, the gap between these lines reveals that consumption of food and drinks are different between rural and urban areas. Then we will analyze the consumption structure deeply through a model later. As the article related before, the structure of consumption could be divided clearly to eight items according to the rule of China Statistical Yearbook. They are Food, Clothes, Housing, Daily necessities, Transportations & Telecommunications, Culture Education & Recreation, Medical and Health Care, and Others. In this essay, I list the proportion of each kind of goods in residents consumption structure between rural and urban areas in Appendix 6 and 7. At the same time, I set an order among these items to help the reader observe all of the information about eight kinds of goods easily. Then we can make a direct and simple comparison about the difference of consumption structure in the past ten year between rural and ruban areas. 9

10 From two tables in Appendix 6 and 7, in consumption structure of the rural and urban residents, the proportion of Food both decrease, but the order still both keep at first; the proportion of Clothes both have a little decline, and the order both decline, too; the proportion of Housing both increase, but the change of order between rural and urban are different; consumption of Daily necessities both decrease in the proportion and order; consumption of Transportations & Telecommunications and Medical & Health care both have a clearly increase in the proportion and order in rural and urban areas; the proportion of Culture & Education & Recreation both increase, but the order both decline between urban and rural residents. All of these results could be observed directly. In a word, through these comparisons, it is easy to find that consumption structure between rural and urban areas looks differently, too. In order to discover the real situation and estimate how different consumption between rural and urban areas is, in the next part, we will use the economic theories and the Eview 3.1 to research some related data from 1998 to

11 3. Methodology In order to analyze the different consumption between rural and urban areas, we need to use the economic theory and set a model. In this article, I will choose Keynes s theory 1 as the foundation. Because Keynes s consuption function is the basic one, and it is the basic theory to other economic theories about consumption. At last, I set a model to estimate the difference in consumption between rural and urban areas. 3.1The economic knowledge In this part, I introduce the Keynes s theory about consumption first and then lead to a econometric concept called dummy variable to create the model Keynes s general theory In Keynes s theory, he conjectures three ideas: The first important idea is the marginal propensity to consume (MPC) which means the amount consumed out of an additional dollar of income, so the marginal propensity to consume should be between 0 and 1. In his article, he thinks that the fundamental psychological law, upon which we are entitled to depend with great confidence,...is that are disposed, as a rule and on the average, to increase their consumption as their disopsable income increases, but not by as much as the increase in their income. in other words, it means if a person earn extra 1 dollar, he will not consume less than 1, and save some money. The second conjecture is the ratio of consumption to the disopsable income, which could be called average propernsity to consume (APC). Keynes thinks the APC will fall when the disopsable income rises, so the rich people will save more wealth than the poor people. 1. Keynes (1936) 11

12 At the last, in Keynes s view, the income is the main determinant of consumption and the interest rate has not an important factor. In his book, he says that the the main conclusion suggested by expenrience, I think, is that the short-period influence of the rate of interest on individual spending out of a given income is secondary and relatively unimportant. According to Keynes s conjectures, the consumption function could be written like this: C = a +βy, a > 0, 0 < β < 1, Where C is the consumption, Y is the disposable income, a is constant, and β is the marginal propensity to consume. This function shows the three ideas of Keynes, and APC = C/ Y= a/y+ β. About Keynes s modal, it is very successful in the early research. However, through more analysis, people find some anomalies with the conjecture of the average propensity to consume. In my essay, I will not explain this topic deeply; I just use above model as the basic function to analyze the relationship between the consumption and the income. Therefore, we can get consumption models of rural and urban areas like these: Urban area: Ln(C) = a 1 + a 2 *Ln(Y) + ε Rural area: Ln(C) = a 3 + a 4 *Ln(Y) + ε The dummy variable In the econometrics, generally the variable could be divided to four different kinds: they are the ratio scale, the interval scale, the ordinal scale and the nominal scale. In this part, the dummy variable belongs to the nominal scale. A dummy variable is a numerical variable used in regression analysis to represent subgroups of the sample in 12

13 your study 6. In research design, a dummy variable is often used to distinguish different treatment groups. In the simplest case, we would use a 0, 1 dummy variable where a person is given a value of 0 if they are in the control group or a 1 if they are in the treated group. Through learning the econometrics, especially the knowledge about the dummy variable, we can use these methods to analyze the different consumption between rural and urban areas. For example, we assume that the value of the dummy variable equals to 1 if consumption is in rural area, the other way round, the value is 0 if consumption is in urban area. 3.2 The Model The above discussion about the different consumption between rural and urban areas in China can be summarized in the following equation as Ln(C) = a 1 + a 2 *Ln(Y) +a 3 *D+ a 4 *D*Ln(Y) + ε Where C means consumption, Y means the disposable income, D equals to 1 if in rural area and D equals to 0 if in urban area. So that a 1 represents an average constant fixed consumption in urban areas, a 2 represents the disposable income elasticity of demand in urban area, a 3 represents a different fixed consumption between urban and rural areas, a 4 represents the different disposable income elasticity of demand between urban and rural areas, ε means the random error which is taken into this model to cover other influences. 3.3 Data The data in this essay are obtained from various sources. The primary data source is

14 the China Statistical Yearbook from 1998 to 2007, where I get the data about GDP, GNP, population status, the disposable income, the average per capita consumption, the Engel s coefficient, and so on. All of these data are separated to rural and urban areas. Beside, please notice that the data I used in this paper do not consider Hong Kong, Macao and Tai Wan, because in the China Statistical Yearbook economic situations of Hong Kong, Macao and Tai Wan are recorded as the individual part. In the process of regression, I have to find per capita consumption of eight different items in rural and urban areas from 1998 to 2007, some exact data are hard to collect, so I have to search them from the network and other essays. I have listed the main data used in my article in Appendix. 14

15 4.Results from the regression According to above model and the data in the past ten years, I will get results of the regression and estimate the different consumption among eight different kinds of goods between rural and urban areas. In the China Statistical Yearbook, goods are divided to eight items, so I define that V1 is consumption of food which includes grain, starch, bean products, lipin, meat, egg, aquatic product, vegetable, condiment, sugar and so on; V2 is consumption of clothes which includs dress, material, shoes and so on; V3 is consumption of housing which includes house, water and electricity, fuel and so on. V4 is consumption of daily necessities which includes durable consumer goods, adornment, bedding, furniture and so on; V5 is consumption of transportations & telecommunications, V6 is consumption of culture education & recreation, V7 is consumption of medical and health care, V8 is consumption of others. So we can get resluts from the regression like these: Food: Dependent Variable: V1 Method: Least Squares Date: 05/30/09 Time: 23:16 Sample: 1 20 Included observations: 20 Variable Coefficient Std. Error t-statistic Prob. C Y D DY R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) In this table, the t-statistic absolute values of D and DY are both more than 2 and the corresponding probability are less than Therefore, D and DY are significant with 95% confidence level in the model. We can know that a 3 = and a 4 = 15

16 , which reveals the constant consumption of Food in rural area is less than urban one, at the same time, the disposable income elasticity of demand in rural area is bigger than urban one, in other words, if the disposable income of people in rural area increase 1%, their consumption in Food will increase more 0.13% than urban one, when D=1 the slope is steeper. So consumption of Food could be different between rural and urban areas. Clothes: Dependent Variable: V2 Method: Least Squares Date: 05/30/09 Time: 23:22 Sample: 1 20 Included observations: 20 Variable Coefficient Std. Error t-statistic Prob. C Y D DY R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) In this table, the t-statistic absolute values of D and DY are both more than 3 and the P-values are less than Therefore, D and DY are significant in the model at 99% confidence level. We can know that a 3 = and a 4 = , which means the constant consumption of Clothes in rural area is less than urban one. At the same time, the disposable income elasticity of demand in rural area is bigger than urban one, in other words, if the disposable income of people in rural area increase 1%, their consumption in Clothes will increase more 0.29% than urban one, when D=1 the slope is steeper. So consumption of Clothes could be different between rural and urban areas. Housing: Dependent Variable: V3 Method: Least Squares Date: 05/30/09 Time: 23:24 16

17 Sample: 1 20 Included observations: 20 Variable Coefficient Std. Error t-statistic Prob. C Y D DY R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) In this table, the t-statistic absolute values of D and DY are both more than 3 and the P-values are less than Therefore, D and DY are significant in the model at 99% confidence level. We know that a 3 = and a 4 = , which means the constant consumption of Housing in rural area is less than urban one. At the same time, the disposable income elasticity of demand in rural area is bigger than urban one, in other words, if the disposable income of people in rural area increase 1%, their consumption in Housing will increase more 0.34% than urban one. When D=1 the slope is steeper. So consumption of Housing could be different between rural and urban areas. Daily necessities: Dependent Variable: V4 Method: Least Squares Date: 05/30/09 Time: 23:25 Sample: 1 20 Included observations: 20 Variable Coefficient Std. Error t-statistic Prob. C Y D DY R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) In this table, the t-statistic absolute values of D and DY are both more than 3 and the P-values are less than Therefore, D and DY are significant in the model at 99% 17

18 confidence level.we know that a 3 = and a 4 = , which means the constant consumption of Daily necessities in rural area is less than urban one. At the same time, the disposable income elasticity of demand in rural area is bigger than urban one, in other words, if the disposable income of people in rural area increase 1%, their consumption in Daily necessities will increase more 0.63% than urban one. When D=1 the slope is steeper. So consumption of Daily necessities could be different between rural and urban areas. Transportations & Telecommunications: Dependent Variable: V5 Method: Least Squares Date: 05/30/09 Time: 23:25 Sample: 1 20 Included observations: 20 Variable Coefficient Std. Error t-statistic Prob. C Y D DY R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) In this table, the t-statistic absolute values of D and DY are both more than 2 and the P-values are less than Therefore, D and DY are significant with 95% confidence level in the model. We can know that a 3 = and a 4 = , which means the constant consumption of Transportations & Telecommunications in rural area is less than urban one. At the same time, the disposable income elasticity of demand in rural area is bigger than urban one, in other words, if the disposable income of people in rural area increase 1%, their consumption in Transportations & Telecommunications will increase more 0.71% than urban one. When D=1 the slope is steeper. So consumption of Transportations & Telecommunications could be different between rural and urban areas. Culture Education & Recreation: 18

19 Dependent Variable: V6 Method: Least Squares Date: 05/30/09 Time: 23:27 Sample: 1 20 Included observations: 20 Variable Coefficient Std. Error t-statistic Prob. C Y D DY R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) In this table, the t-statistic absolute values of D and DY are both less than 2 and the P- values are more than Therefore, D and DY are not significant in the model. We cannot assess whether an increase of Y will affect different consumption of V6 between rural and urban areas. Medical and Health Care: Dependent Variable: V7 Method: Least Squares Date: 05/30/09 Time: 23:27 Sample: 1 20 Included observations: 20 Variable Coefficient Std. Error t-statistic Prob. C Y D DY R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) In this table, the t-statistic absolute values of D and DY are both more than 2 and the P-values are less than Therefore, D and DY are significant with 95% confidence level in the model. We can know that a 3 = and a 4 = , which means the constant consumption of Medical and Health Care in rural area is less than urban one. At the same time, the disposable income elasticity of demand in rural area is bigger than urban one, in other words, if the disposable income of people in rural area 19

20 increase 1%, their consumption in Medical and Health Care will increase more 0.44% than urban one. When D=1 the slope is steeper. So consumption of Medical and Health Care could be different between rural and urban areas. Others: Dependent Variable: V8 Method: Least Squares Date: 05/30/09 Time: 23:27 Sample: 1 20 Included observations: 20 Variable Coefficient Std. Error t-statistic Prob. C Y D DY R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) In this table, the t-statistic absolute value of DY is less than 2 and the P-values more than Therefore, D and DY are not significant in the model. We cannot assess whether an increase of Y will affect different consumption of V6 between rural and urban areas. In this item, it includes lots of different kinds of goods except above seven kinds of goods. Therefore, we would not need to consider more about this item. 20

21 5.Conclusion In this article, we focus on the different consumption between rural and urban areas in China from 1998 to 2007, and estimate different consumption among eight kinds of items between rural and urban areas by using a simple model based on the time series data of the mainland in China. About the different consumption between rural and urban areas in China, we can find lots of articles related to this topic, but these academic essays research through different ways. Such as Zhu Shie 1 analyzes the different consumption between rural and urban areas by using the Engel's Coefficient, Shi Wen 2 only estimates the difference in the level of consumption, Du Ting 3 and Ying Ling 4 proof that the different disposable income between rural and urban areas is the main reason leading to the different consumption, Jiang Tao 5 uses the Extend Linear Expenditure System (ELES) to analyze the different consumption structure, Peng Haiyan 6 find the margial propensity to consume in rural area is larger than it in urban area, and so on. I must acknowledge these articles and writors, becasue they help me understand the different consumption between rural and urban areas in China deeply from different points of view. According to results of the regression in the last part, we have estimated that consumption between rural and urban areas are much different on the Food, Clothes, Housing, Daily necessities,transportations & Telecommunications, Medical and Health Care. For culture education & recreation, we can not make sure 1. Zhu Shie (2007) 2. Shi Wen (2005) 3. Du Ting (2006) 4. Ying Lin (2007) 5. Jiang Tao (2008) 6. Peng Haiyan (2006) 21

22 that consumption of them is different between rural and urban areas. Through the regression, we find two same characters in consumption of Food, Clothes, Housing, Daily necessities,transportations & Telecommunications, Medical and Health Care. First is the constant basic consumption of Food, Clothes, Housing, Daily necessities,transportations & Telecommunications, Medical and Health Care in rural area are less than urban ones. Second, the disposable income elasticity of demand for these five items in rural area are bigger than urban ones, in other words, when D=1 the slope is steeper. I think that there are many reasons to explain why the different consumption between rural and urban areas exist, for example the different custom between rural and urban areas. In rural area, people think the owner of the house must be themselves, they do not like to rent house, so they likely spend more money on housing. However, in urban area, people have many choices to living, it is easy for people to rent a house, especially young people in urban area often rent house at the beginning of their career. Another reason could be the different price of goods, in rural area, the price of daily necessities is obviously lower than its price in urban area. However, in my view, the basic reason is different disposable income, which influences the price of goods. Looking at this table: Sources: China statistical Yearbook ( ). 22

23 In this figure, we will find the disposable income gap is so large between rural and urban areas. The per capita disposable income in urban is almost 2.5 times more than rural one. As we know in the result of regression, the disposable income elasticity of demand for Food, Clothes, Housing, Daily necessities,transportations & Telecommunications, Medical and Health Care in rural area is larger than the urban one, rural people want to consume but they have not enough disposable income. So the gap of disposable income limits consumption in rural area and creates the different consumption between rural and urban areas fundamentally. 23

24 Reference John Maynard Keynes (1936). The General Theory of Employment, Interest and Money. Constantino Lluch (1973). The extended linear expenditure system. European Economic Review,Volume 4, Issue 1, April 1973, Pages N. Gregory Mankiw ( 2007). Macroeconomics, Sixth Edition, Pages Damodar N.Gujarati (1978). Basic Econometrics. Third Edition Campbell John Y, N.Gregory Mankiw (1989). Consumption,Income,and InterestRates: Reinterpreting the Time Series Evidence. In Olivier Blanchard and Stanley Fischer(eds.), NBER Macroeconomics Annual19 89, Cambridge, Mass. MIT Press,1989. Pages Campbell John Y, N.Gregory Mankiw (1991). The response of Consumption to Income: A Cross Country Investigation. European Economic Review,1991, Pages Deaton, A (1997). A Micm econometric AppIoach to Development Policy. The Analysis of Household surveys, Stéphane Dées (2001). The opening policy in China Simulations of a macro econometric model. Journal of Policy Modeling, 2001, Pages Zang Xuheng (1997). The analysis of the consumption function in China. Pages , Zhu Shie (2007). A Contrast between the Consumptions of Rural and Urban Residents in China. Consumer economics, Issue 4, 2007, Pages

25 Du Ting, Pang dong (2006). Study on the Characteristics of Resident's Consumption Behavior in China's Business Cycle. Journal of Zhongnan University of Economics and Law, Issue 3, 2006, Pages Peng Haiyan, Wu Xiaorong (2006). Empirical Study on Consumption Differences between China's Urban and Rural Residents. Shang Hai Management Science, Issue 2, 2006, Pages Yin Ling (2007). An Empirical Analysis on China's Residential Consumption Behavior. Productivity Research, Issue 13, 2007, Pages Shi Wen (2005). Trend of Our Residents' Consumption Propensity and Its Reasons. Academic Exchange, Issue 9, 2005, Page Jiang Tao (2008). Analysis to the Transition of consumption in China. Journal of Yan Shan University, Issue 4, Wu Kelie, Li Huijian (2004). The Marginal Propensity of Consume in the Consumptive Function. Social Science Research, Issue 2,2004 Zhu Tianxing, Guo Tianzuo and Cen Anhong (2004). Empirical analysis to marginal propensity of consumption of Chinese town resident. Journal of Shenyang University of Technology, Issue 4, Xiao Yanhua (2001). Positive Analysis of Chinese Urban Households' Consumption Patterns. Journal of Xiangtan University (Philosophy and Social Sciences), Issue 3,2001. Wang Liang(2005). Appraisals of the Methods of Marginal Propensity to Consume. Statistics & Information Forum, Issue 5, Guo Yajun, Zheng Shaofeng (2006). A Panel Date Analysis of the Consumption Structure of China's Urban Citizens. Journal of Northwest Sci-Tech University of Agriculture and Forestry, Issue 2,

26 Zhu Wei, Li Yuansheng (2006). Panel Data Analysis of China Urban Residents' Consumption Structure. Application of Statistics and Management, Issue 6, Li Haitao, Jin Yu (2003). The Influence of Income Difference on Consumption Structure in Urban Areas. Statistics & Information Forum, Issue 3, 2003, Pages Fan Maoqing, Ren Ruoen (2006). The Experimental Analysis of Consumption Structure of Urban Residents of China. Statistical Research, Issue 12, Chen Fei (2005). The Effect of Income Gap upon the Consumption Structure of the Urban Residents of Our Country. Economic Survey, Issue 6, Yan Guoxiang (2005). The Development Trend of Chinese Urban Residents' Consumption Structure and Analysis of Its Influence to Domestic Demand. Journal of Taiyuan University of Technology(Social Sciences Edition), Issue 4, 2005, Pages Li Dongshen (1995). Using the Expand Linear Expenditure System to Analysis the Consumption in Rural Area. Finance and Trade Research, April 1995, Pages Shangguan Jinzhi, Zhang Huixian (2008). Study on the Track of Inhabitant Consumption Changes in China. East China Economic Management, Issue 12, 2008, Pages Zhang Zhimin (2003). The Analysis of Factors Influencing Chinese Inlabitants Consumption Since Commercial Research, Issue 24,

27 Appendix Appendix 1: The basic data of Chinese economy from 1978 to 2007 *The amounts are calculated according to the nominal price (current price) *Unit: 100 million RMB YEAR GNP GDP PRIMARY INDUSTRY SECONDARY INDUSTRY TERTIARY INDUSTRY Sources: China State Statistic Bureau ( ). 27

28 Appendix 2: The data about the average per capita disposable income in urban and rural areas from 1978 to 2007 *Unit: 1RMB DISPOSABLE INCOME PER DISPOSABLE INCOME PER URBAN RESIDENT RURAL RESIDENT YEAR NOMINAL NOMINAL INDEX(1978=100) INDEX(1978=100) RMB RMB Sources: China statistical Yearbook ( ). Appendix 3: The data about the average per capita consumption in the urban and the rural areas from 1978 to 2007 *Unit: 1 RMB YEAR NATION RURAL URBAN 28

29 Sources: China State Statistic Bureau ( ); China statistical Yearbook ( ). Appendix 4: The data about the population in the urban and the rural areas from 1978 to *Unit: 10 THOUSAND PEOPLE YEAR TOTAL PUPOLATIO N PUPOLATIO N URBAN AREA PROPORTIO N (%) PUPOLATIO N RURAL AREA PROPORTIO N (%)

30 Sources: China statistical Yearbook ( ). Appendix 5: The data about the Engel s coefficient of urban and rural households from 1978 to 2007 *Unit: 1percent (1%) YEAR ENGEL'S COEFFICIENT OF URBAN RESIDENTS (%) ENGEL'S COEFFICIENT OF RURAL RESIDENTS (%)

31 Sources: China State Statistic Bureau ( ); China statistical Yearbook ( ). Appendix 6: The proportion of the urban residents consumption structure, and the order from 1998 to 2007 Items Food Clothes Housing Daily necessiti es Transportations &Telecommunicatio ns Sources: China statistical Yearbook ( ). Culture Education &Recreation Medical &health care Others Year (1) 11.1(3) 9.4(4) 8.2(5) 5.9(6) 11.5(2) 4.7(7) 4.7(8) (1) 10.5(3) 9.8(4) 8.6(5) 6.7(6) 12.3(2) 5.3(7) 4.9(8) (1) 10.0(4) 11.3(3) 7.5(6) 8.5(5) 13.4(2) 6.4(7) 3.5(8) (1) 10.1(4) 10.3(3) 8.3(6) 8.6(5) 13.0(2) 6.5(7) 5.3(8) (1) 9.1(5) 10.4(4) 6.5(7) 10.4(3) 14.9(2) 7.1(6) 3.9(8) (1) 9.8(5) 10.7(4) 6.3(7) 11.1(3) 14.4(2) 7.3(6) 3.3(8) (1) 9.6(5) 10.1(4) 6.0(7) 11.8(3) 14.4(2) 7.2(6) 3.2(8) (1) 10.1(5) 10.2(4) 5.6(7) 12.6(3) 13.8(2) 7.6(6) 3.4(8) (1) 10.4(5) 10.4(4) 5.7(7) 13.2(3) 13.8(2) 7.1(6) 3.6(8) (1) 10.4(4) 9.8(5) 6.0(7) 13.6(2) 13.3(3) 7.0(6) 3.6(8) Note: the order is shown in the parentheses. 31

32 Appendix 7: The proportion of the rural residents consumption structure, and the order from 1998 to 2007 Iterms Year Food Clothes Housing Daily necessit ies Transportations &Telecommunicatio ns Culture Education &Recreation Medical &health care Others (1) 6.2(4) 15.1(2) 5.2(5) 3.8(7) 10.0(3) 4.3(6) 2.0(8) (1) 5.8(4) 14.8(2) 5.2(5) 4.4(7) 10.7(3) 4.4(6) 2.1(8) (1) 5.8(4) 15.5(2) 4.5(7) 5.6(5) 11.2(3) 5.2(6) 3.1(8) (1) 5.7(5) 16.0(2) 4.4(7) 6.3(4) 11.1(3) 5.6(6) 3.2(8) (1) 5.7(5) 16.4(2) 4.4(7) 7.0(4) 11.5(3) 5.7(6) 3.0(8) (1) 5.7(6) 15.9(2) 4.2(7) 8.4(4) 12.1(3) 5.9(5) 2.2(8) (1) 5.5(6) 14.8(2) 4.1(7) 8.8(4) 11.3(3) 6.0(5) 2.3(8) (1) 5.8(6) 14.5(2) 4.4(7) 9.6(4) 11.6(3) 6.6(5) 2.0(8) (1) 5.8(6) 16.6(2) 4.5(7) 10.2(4) 10.8(3) 6.8(5) 2.2(8) (1) 6.0(6) 16.8(2) 4.6(7) 10.9(3) 10.8(4) 6.5(5) 2.3(8) Sources: China statistical Yearbook ( ). Note: the order is shown in the parentheses. Appendix 8: The data about the per capita consumption structure in urban area from 1998 to YEAR FOOD CLOTHES HOUSING Daily necessities Transportations Telecommunications Culture Education *Unit: 1 RMB Sources: China State Statistic Bureau ( ); China statistical Yearbook ( Medical care Others

33 Appendix 9: The data about the per capita consumption structure in rural area from 1998 to *Unit: 1 RMB YEAR Sources: China State Statistic Bureau ( ); China statistical Yearbook ( ). FOOD CLOTH ES HOUSI NG Daily necessiti es Transportatio ns Telecommunic ations Culture Educati on Medic al care Others