Cuihong Yang

INPUT–OUTPUT ANALYSIS: THE NEXT 25 YEARS

This year marks the 25th anniversary of the International Input–Output Association and the 25th volume of Economic Systems Research. To celebrate this anniversary, a group of eight experts provide their views on the future of input–output. Looking forward, they foresee progress in terms of data collections, methods, theory testing, and focus and scope.

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 2002–2005. 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.

Accounting for China's import growth: a structural decomposition for 1997-2005

This paper applies structural decomposition analysis to Chinese input–output tables in order to disentangle and quantify the sources of Chinas import growth and Chinas growth in vertical specialization: that is, Chinas incorporation into the global supply chain. Chinas exports and the role of processing trade therein have increased substantially in the last decade. Yet, they account for only one third of Chinas import growth from 1997 to 2005. Instead, the volume growth of Chinas domestic final demand is found to be most important. Moreover, compared with other countries, the structural change in input–output coefficients and in the commodity composition of domestic final demand turns out to be surprisingly important. Looking only at vertical specialization, it is concluded that more than half of its growth, from 21% in 1997 to 30% in 2005, is due to the growth of Chinas import ratios.

PROCESSING TRADE BIASES THE MEASUREMENT OF VERTICAL SPECIALIZATION IN CHINA

Vertical specialization (VS) is often measured by the import contents of the exports, using an input–output (I–O) framework. Half of Chinas exports are processing exports, which largely depend on imported intermediate inputs and tie up upstream as well as downstream trade partners. Thus, one would expect to find strong VS for China. Using the ‘ordinary’ I–O tables, however, this is not the case. Because the production of processing exports is only a small part of total production, the average input structure in the I–O table hides the typical features of processing exports. Using adapted, tripartite I–O tables (for 2002 and 2007) in which the processing exports have been singled out, indeed reveals the expected strong VS in China.

Revisiting the Global Net Carbon Dioxide Emission Transfers by International Trade: The Impact of Trade Heterogeneity of China

To revisit global net carbon dioxide (CO2) emissions transfers by international trade for year 2007, this study employs a new world-wide, multiregional input-output (MRIO) table in which Chinas production is separated into domestic use, processing exports, and nonprocessing exports. The results show that processing exports in China involves relatively lower CO2 emissions than other production types for the same output levels. Therefore, if processing exports are not appropriately distinguished, net CO2 emission exports from China to other regions will be distorted; the relative bias occasionally reaches 15%. Net emission exports from regions other than China are also distorted, particularly for regions that use considerable Chinese processing exports as intermediates, such as the United States, European Union (EU), and East Asia. Given that processing exports prevail in a large number of developing countries, such as Mexico and Vietnam, one should carefully interpret measurements of net emission transfers by international trade by utilizing the ordinary world-wide MRIO model.

A Method to Optimize Gross Fixed Capital Investments for Water Conservancy in China

Abstract A major concern of policymakers and researchers in China is finding an appropriate size of the gross fixed capital investments for water conservancy (GFCIWC). This paper determines the optimal proportion of GFCIWC to GDP. Unlike engineering economics, we investigate the benefits of GFCIWC at a macro-economic level, using the 1999 input–output table extended for water conservancy. Different kinds of impacts are induced by GFCIWC. These include forward benefits (flood control, water supply, irrigation, hydroelectric power, soil and water conservation, environmental protection) and backward benefits for GDP; negative social effects; and opportunity costs of GFCIWC. The results are put into a set of regression equations between total benefits of GFCIWC and the proportion of GFCIWC to GDP, from which the optimal proportion – or a desirable range – can be determined. The results may provide policymakers with guidelines for allocating investments.

Optimizing China’s export structure combining goal programming and non-competitive input-output model

Based on a non-competitive input-output model capturing China’s processing exports, this paper establishes a goal programming model to optimize China’s export structure. In this model, China’s domestic production is divided into three parts: Production for domestic use, processing exports, and non-processing exports and production for other foreign invested enterprises. This division enables differentiation of the effects of various trade patterns, on the basis of which the authors conduct an empirical analysis using 2002 data, to obtain a Pareto optimality.

A COMPARISON OF PRODUCER, CONSUMER AND SHARED RESPONSIBILITY BASED ON A NEW INTER-COUNTRY INPUT-OUTPUT TABLE CAPTURING TRADE HETEROGENEITY

In this paper, we employed a new inter-country input-output table where China’s productions are differentiated into domestic use, processing exports and non-processing exports (WIOD-DPN table), to compare the CO2 emissions responsibilities of 13 major regions under producer, consumer and shared accounting systems. The results show that the CO2 emissions responsibility of advanced countries would become less when the accounting system is changed from a consumer system to a shared system, while that of emerging countries are on the contrary. The degree of these changes depends on the value-added received by the production countries from the global value chain.

Yearly Grain Output Predictions in China 1980-2004

China has a population of 1.3 billion and grain accordingly plays a crucial role in the Chinese economy. In this paper we suggest predicting grain output mainly by factor inputs and asset holding, and present a Systematic Integrated Prediction Approach (SIPA). The key elements of SIPA are an extended input–output model with assets, nonlinear variable coefficient forecasting equations, and using the minimum sum of the absolute values. Since 1980 we have used the approach to predict the yearly national grain output of China. The prediction lead time is more than half a year. The bumper, average, and poor harvests are accurately predicted every year. The average error rate over the period 1980–2004 is 1.9%.

Why has China's vertical specialization declined?

ABSTRACT Vertical specialization (VS) is quantified by the VS share, which measures the average import content per dollar of exports. A characteristic of China’s export trade is its strong dependence on assembly and processing activities. To take proper account of this, China’s VS shares should explicitly distinguish processing export production from other production. We estimate China’s annual VS shares from 2000 to 2012—the latest year for which a special input–output table is available that makes such an explicit distinction. We find that VS shares increased from 2000 to 2004 and subsequently started to decrease. To explore why it has declined, we introduce a new structural decomposition approach. We find that the decrease of the VS share appears to have been driven mainly by the substitution of imported intermediates by domestic products. This occurred in particular in the production of exports, which implies an upgrading of China’s position in global value chains.