Input-occupancy-output models of the non-competitive type and their application - an examination of the China-US trade surplus

In this paper we construct an extended non-competitive input-occupancy-output model that captures China＇s processing trade and also develop a methodology to estimate the domestic value-added and employment generated by each unit of total exports, of exports by sector, and of exports by commodity, respectively. We also prove mathematically that the gross value of exports is equal to the sum of total value added and total imports. Based on the methodology proposed here, we compile the 2002 extended Chinese non-competitive input-occupancy-output table and the United States non-competitive input-occupancy- output table, and then estimate and analyze the effects of China＇s exports and US exports on their respective domestic value added and employment.

Does the Domestic Value Added Induced by China's Exports Really Belong to China?

Since 2001, the exports of foreign-invested enterprises （FIEs） have accounted for more than 50percent of China＇s total exports. As foreign capital occupies a high proportion of the total capital of FIEs, most FIEs ＇ capital gains are foreign factor income. Although these gains are calculated as apart of China＇s GDP, they do not belong to China＇s national income. To determine the real contribution of exports to China ＂s welfare, the present paper analyses the impact of exports on China ＂s national income using a non-competitive input output model capturing processing trade. The results show that every US$1000 of China＇s exports generates US$506.8 of national income. The real contribution of exports to China ＂s welfare is much smaller than what we expected. This suggests that China should endeavor to improve the gains from international markets orfind another engine to maintain its economic growth.

STRUCTURAL DECOMPOSITION ANALYSIS ON CHINA'S ENERGY INTENSITY CHANGE FOR 1987-2005

There has been considerable debate about the major factors responsible for the dramatic decline of China＇s energy intensity in the 1980s and 1990s. However, few detailed analysis has been done to explain the fluctuation in energy intensity during 2002-005. In this paper, we use the structural decomposition analysis （SDA） to decompose energy intensity into five determining factors： Energy input coefficient, technology coefficient （Leontief inverse coefficient）, final demands structure by product, final demands by category and final energy consumption coefficient. We then further decompose two coefficients, energy input coefficient and technology coefficient, into structure and real coefficient. Empirical study is carried out based on the energy-input-output tables from 1987 to 2005 in 2000 constant price. The results show that between 1987 and 2002, energy input structure accounts for most of the decline in energy intensity. However, the input structure and final demands structure by product explain the increase of the energy intensity between 2002 and 2005.

A MULTIYEAR LAGS INPUT-HOLDING-OUTPUT MODEL ON EDUCATION WITH EXCLUDING IDLE CAPITAL

This paper develops a multi-year lag Input-Holding-Output （I-H-O） Model on education with exclusion of the idle capital to address the reasonable education structure in support of a sustainable development strategy in China. First, the model considers the multiyear lag of human capital because the lag time of human capital is even longer and more important than that of fixed capital. Second, it considers the idle capital resulting from the output decline in education, for example, student decrease in primary school. The new generalized Leonitief dynamic inverse is deduced to obtain a positive solution on education when output declines as well as expands. After compiling the 2000 I-H-O table on education, the authors adopt modifications-by-step method to treat nonlinear coefficients, and calculate education scale, the requirement of human 2020. It is found that structural imbalance of human development. capital, and education expenditure from 2005 to capital is a serious problem for Chinese economic

A DYNAMIC APPROACH TO CALCULATE SHADOW PRICES OF WATER RESOURCES FOR NINE MAJOR RIVERS IN CHINA

China is experienciug from serious water issues. There are many differences among the Nine Major Rivers basins of China in the construction of dikes, reservoirs, floodgates, flood discharge projects, flood diversion projects, water ecological constructions, water conservancy management, etc. The shadow prices of water resources for Nine Major Rivers can provide suggestions to the Chinese goverument. This article develops a dynamic shadow prices approach based on a multipeziod input-output optimizing model. Unlike previous approaches, the new model is based on the dynamic computable general equilibrium （DCGE） model to solve the problem of marginal long-term prices of water resources. First, definitions and algorithms of DCGE are elaborated. Second, the results of shadow prices of water resources for Nine Major Rivers in 1949-2050 in China using the National Water Conservancy input-holdiug-out in table for Nine Major Rivers in 1999 are listed. A conclusion of this article is that the shadow prices of water resources for Nine Major Rivers are largely based on the extent of scarcity. Selling prices of water resources should be revised via the usage of parameters representing shadow prices.