Agricultural Trade Liberalization and Poverty in China: A Dynamic CGE Model Analysis

Transcription

1 Agricultural Trade Liberalization and Poverty in China: A Dynamic CGE Model Analysis Xiaohe Liu, Lan Fang & Hongye You Institute of Agricultural Economics & Development Chinese Academy of Agricultural Sciences 12 Zhongguancun South St. Beijing , CHINA xliu17@hotmail.com The 6th PEP Network General Meeting Lima, Peru June 14-16th,

2 Outline Introduction Contribution of the Research Policy Relevance Methodology Data Requirements and Sources 2

3 1. Introduction The trade reform in China has progressed smoothly since the late 1980s. The gains and losses from trade liberalization are often unevenly distributed in sectors. It could consequently hurt the farmers, who are categorized as being in the poorest group in rural areas. But until now, the impact of agricultural trade liberalization on the poor is still not quite clear. 3

4 Main questions: Is the trade liberalization in agriculture favorable or harmful to the poor? What alternative policies can be used to ensure a more equitable distribution of the gains from trade reform? The results from this study could be of great value for policy makers to identify courses of action for enhancing the positive outcomes of income distribution and reducing any unfavorable effects from further policy changes. 4

5 2. Contribution of the Research In the previous studies, a static CGE model with single representative household was usually used (Wang, 1999; Martin et al., 1999; Walmsley et al., 2000; Lejour, 2000) to examine the impacts of the Chinese membership of the WTO on its economy some positive conclusions on welfare were made at the national level or even at the regional level (Yang and Huang 1997; Fan and Zheng 2000; Diao et al. 2002, 2003; Jiang 2003). 5

6 However, this does not imply that different income groups of households in China would benefit equally. Some households may seriously suffer due to the uneven distributions of income among different sectors (agriculture, manufacture and service), regions (urban or rural), or labors (skilled or unskilled). Moreover, very few attempts had been made to investigate the impacts of agricultural trade liberalization on poverty in China. 6

7 In this project, we intend to extend a framework of a dynamic CGE model to simulate the effects of tariff reduction on agriculture, manufacture and service sectors; to identify the inequality between urban and rural areas; to specify the disparity of lower-income and higher-income households; and to trace the labors movement from rural to urban areas. 7

8 3. Policy Relevance After China s accession to the WTO, one of the most striking issues on China s economic development has been a large disparity of income between the rural and urban households; This is largely due to limited factor mobility, especially of labor and capital; Surplus farm labor and low labor productivity have resulted in low agricultural income and hidden unemployment in rural areas; 8

9 The rural-urban gap in living standards is further accentuated by disparities in access to education, health care, and other social services; Meanwhile, the tariff reduction and the nontariff-barriers abolition would benefit manufacturing sectors, but hurt agricultural producers, and consequently increase ruralurban disparity; and thus influence the pattern of income distribution in different sectors and the poverty incidence in different income groups of households. 9

10 4. Methodology Reason for using a dynamic model The structure of the Chinese economy has changed significantly since the reform undertaken in It is inappropriate for us to use a standard static model describing the dramatic changes in economy structure for a mid or long period. To fulfill this task, a dynamic CGE model with multi-household and different types of labors is developed to examine the effects of changes in policies, such as tariff reduction and domestic support, on poverty in China. 10

11 Structure of the model A dynamic CGE model of MC-HUGE is based on the Monash model and designed for forecasting and policy analysis. Like its predecessor ORANI, MONASH not only has a high level of microeconomic detail, but also a strong forecasting capability. 11

12 This is due to: a more detailed specification of intertemporal (i.e. dynamic) relationships; a greater use of up-to-date data; and the enhancements which allow the model to make use of information from a specialized forecasting mechanism and recent historic trends. 12

13 Moreover, the Monash model incorporates three types of intertemporal links: physical capital accumulation; financial asset/liability accumulation; and lagged adjustment process. For more detail, see Dixion, P.B. and M.T. Rimmer (2002). 13

14 Extension of the basic model The basic model of MC-HUGE only possesses one type of labor and one representative household. We will extend the basic model by disaggregating the factor of labor to six types and the consumption of households to ten groups: 14

15 Six types of labors include urban skilled, urban unskilled, urban self-employed, rural skilled, rural unskilled and rural selfemployment. Ten groups of households are classified by their income. There are five classes in both urban and rural regions. Moreover, there are some linkages between different labors and households. With the detailed income and expenditure sections, the poverty and distribution study can be carried out. 15

16 5. Data Requirements and Sources Source of the Social Accounting Matrix (SAM) MC-HUGE database, Version 1.0; The baseline for the period of 1977 to 2015 is prepared along with the base model; In this project, non-agricultural sectors will be aggregated. 16

17 Source of the household disaggregation From Yearbook of Rural Household Survey and Yearbook of Urban Household Survey (various editions), we will obtain the expenditure details, by different income groups of households, in rural and urban areas; understand the changes in expenditure structure; and achieve a more accurate historical forecast. 17

18 Source of the labor disaggregation According to GTAP database Version 6 and China Economic Census Yearbook, we will disaggregate labors into six categories. Moreover, by using the data of China Labor Statistical Yearbook, we can find out the changes in labor structure during a long period and import it into the dynamic model baseline so as to gain a more accurate historical forecast. 18

19 6. Short list of key References Diao, X., Fan, S. and Zhang, X. (2002) How China s WTO Accession Affects Rural Economy in the Less-developed Regions: A Multi-region, General Equilibrium Analysis, TMD Discussion Paper No. 87, International Food Policy Research Institute, Washington DC. Diao, X., Somwaru, A. and Tuan, F. (2003) Regional and National Perspectives of China s Integration into the WTO: A CGE Inquiry with Emphasis on the Agricultural Sector, Review of Urban & Regional Development Studies, 15: Jiang, T. (2003) The Impact of China s WTO Accession on Its Regional Economies, Australian Agribusiness Review, 11. Lejour, A. (2000) China and the WTO: The Impact on China and the World Economy, mimeo, Netherlands Bureau for Economic Policy Analysis, and paper presented at the third annual conference of Global Economic Analysis, Melbourne. Peter B. Dixon and Maureen T. Rimmer (2002) Dynamic General Equilibrium Modelling for Forecasting and Policy, North-Holland. Wang, Z. and Zhai, F. (1998) Tariff Reduction, Tax Replacement, and Implications for Income Distribution in China, Journal of Comparative Economics, 26: Yang, Y. and Huang, Y. (1997) The Impact of Trade Liberalization on Income Distribution in China, Economics Division China Economy Working Paper 87/1, Research School of Pacific and Asian Studies, ANU. Zheng, Yuxin and Fan, Mingtai (1999) A Chinese CGE Model and Its Application to Policy Analysis, Social Sciences Documentation Publishing House, Beijing. 19