Tracking the Domestic Carbon Emission Intensity of China’s Construction Industry: A Global Value Chain Perspective

China is the largest producer of carbon in the world. China’s construction industry has received widespread attention in recent years due to its environmental issues. However, little research has been conducted to investigate the environmental efficiency of the domestic part of this industry. As the foreign contribution is beyond China’s control, identification of domestic carbon emissions is necessary to formulate effective policy interventions. Based on a multi-regional input‐output model, this study attempts to reduce the statistical bias associated with international trade, thereby obtaining a more accurate indicator of domestic carbon emission intensity. This study aims to reveal the change in the domestic carbon emission intensity of China’s construction industry during 2000–2014 and analyze the reason behind it. The results show that, first, both the constructed intensity indicator and commonly used measures of carbon emission intensity have exhibited a decreasing trend over the study period. However, the former has been consistently larger than the latter. Moreover, this difference first increased and then suddenly decreased after a particular year. Second, although the domestic carbon emission intensity shows a gradually declining trend, it has moved from second to first in global rankings, implying that China’s domestic construction industry’s carbon emission efficiency, while falling, lags behind other major economies. Third, the structural decomposition results reveal that changes in direct production emission intensity are the leading causes of the decline in domestic carbon emission intensity. In contrast, a change in the intermediate input structure led to an increase in the emission intensity in China’s construction industry. In addition, the enormous gaps of domestic carbon emission intensity in the construction industry between China and the selected countries are mainly attributable to the difference in the intermediate input structure. The study suggests that China’s construction industry needs to promote high value-added output, optimize intermediate input structure, and improve energy and emission efficiency.

Mathematical Discussion on the Relationship Between SUTs and SIOTs

Since the 1993 System of National Accounts (SNA) and especially the 2008 SNA, traditional input-output table (IOT) of Leontief has been modified quite a lot with many variations. The supply and use tables (SUTs) seem to be substituted for the IOT, although there has not been a complete guiding to SUTs to IOT conversion.Originally in 1968 SNA, SUTs was called make and use matrices as an intermediate step to compile IOT. However, 1993 and 2008 SNA seem to replace IOT with SUTs, of which regulations make it difficult to convert from SUTs to IOT such as regulation on the size of supply and use tables and regulation on the prices of the intermediate input matrix.Some countries use computable general equilibrium (CGE) model, while others use both the CGE model and input-output analysis, so they need to convert SUTs into symmetric input-output tables (SIOTs). The construction of SIOTs is a controversial issue as regards the choice of model to construct both product-by-product and industry-by-industry SIOTs. This paper discusses the SUTs given in 1968, 1993, 2008 SNA, and the method for converting SUTs to SIOTs.Although there have been several articles on how to convert SUTs into SIOTs, this article is an effort to provide an easier, more understandable way to convert SUTs to SIOTs based on the arrangement of supply and use matrices.

EQUILIBRIUM INDETERMINACY, ENDOGENOUS ENTRY AND EXIT, AND INCREASING RETURNS TO SPECIALIZATION

This paper systematically examines the interrelations between equilibrium indeterminacy, endogenous entry and exit of intermediate input firms, and increasing returns to specialization within two versions of a parsimonious one-sector monopolistically competitive RBC model. The technology for producing an intermediate good is postulated to display internal increasing returns to scale in our benchmark framework, whereas positive productive externalities are considered in the alternative setting. We analytically show that either formulation will exhibit belief-driven cyclical fluctuations provided the equilibrium wage-hours locus is positively sloped and steeper than the household’s labor supply curve. We also find that ceteris paribus our alternative macroeconomy is more susceptible to indeterminacy and sunspots than the baseline counterpart.

Services value added in exports: a comparative analysis between Brazil and the United Kingdom from 2000 to 2014

In the last few years, it is observed a rise in the service sector in countries and an increase in international services transactions has accompanied this expansion. Thus, the main objective of this work is to measure the services value added in exports from Brazil and the United Kingdom, from 2000 to 2014, and do a comparative analysis to identify the role of services systemically. The results indicate a clear difference among the countries analysed with regard to exports in the service sector, while for Brazil the sector can be considered as an intermediate input for exports from the non-service sectors; to the United Kingdom, as final exported product. Also, it is concluded that the service sector has been gaining space and importance for the Brazilian economy, indicating a latent potential of the sector in promoting the country's economic growth and, therefore, cannot be treated as a secondary player by public policies of development.

POSISI GVC INDONESIA DI WILAYAH ASEAN-KANADA

Abstrak Rantai Nilai Global atau Global Value Chain (GVC) adalah alat yang berguna untuk melacak pola pergeseran dari produksi global. Kontribusi Indonesia dalam GVC di wilayah ASEAN-Kanada masih rendah, hal ini dapat dilihat dari nilai intermediate input yang lebih rendah dibandingkan dengan nilai final input. Penelitian ini bertujuan untuk menganalisis posisi GVC Indonesia di wilayah ASEAN-Kanada. Penelitian ini menggunakan analisis input-output dengan berdasar pada data World Input Output Databases (WIOD). Hasil studi ini menunjukkan bahwa dalam lingkup ASEAN, kontribusi Indonesia dalam GVC masih rendah, dapat dilihat dari nilai intermediate input yang lebih rendah dari nilai final input. Bila dibandingkan dengan negara-negara lain ASEAN (yang memiliki ekspor terbesar ke Kanada) yaitu Vietnam, Thailand, dan Malaysia, persentase ekspor barang intermediate Indonesia hanya sebesar 48,3%, lebih rendah dibandingkan negara-negara lainnya. Indonesia harus terus mengambil peran aktif di GVC. Di masa depan, Indonesia harus lebih aktif untuk dapat meningkatkan nilai tambah pada ekspor sebagai intermediate input, sehingga akan berdampak pada positif perekonomian Indonesia secara berkelanjutan. Kata Kunci: ASEAN-Kanada FTA, GVC, Nilai Tambah Abstract Global Value Chain (GVC) is a useful tool to track shifting patterns of global production. Indonesia's contribution in GVC is still low, this can be seen from the lower intermediate input value compared to the final input value. The result of this study aims to analyze the position of Indonesia in the GVC in ASEAN-Canada region. The study used input-output analysis based on World Input Output Databases (WIOD). The study shows that within ASEAN, Indonesia’s contribution in GVC is low, it can be seen from the input intermediate value which is lower than the final input value. When compared with other ASEAN countries (which have the largest exports to Canada), as Vietnam, Thailand, and Malaysia, the percentage of Indonesia’s intermediate exports is only 48.3%, which is lower than those of these countries. Indonesia should continue to take active role on GVC. In the future, Indonesia should be proactive to be able to increase added value on export as intermediate input. To indeed it will positively impact Indonesia's economy in a sustainable manner. Keywords: ASEAN-Canada FTA, GVC, Added Value JEL Classification: A11, B17, B22, B41

Prediction and comparison of the impact of COVID-19 epidemic on the financial industry of major countries based on neural intelligent algorithm

The global economy appears the trend of anti-globalization under the influence of COVID-19. Based on the input-output table of lead database from 2006 to 2020, this paper divides the factors that affect the development of financial industry in China, the United States and Russia into six aspects: price, intermediate input, household consumption, government consumption, export and import. ADGA-BP neural network model is proposed in this paper, which is based on six aspects of price, intermediate input, consumer, government consumption, export and import. The intermediate input is decomposed from the perspective of industrial structure to study the interrelationship between financial industry and other industries in the three countries. The results show that the intermediate input is the main factor in the development of financial industry in the three countries, but the source industries of the intermediate input are not the same; the two factors of household consumption and price are closely related to the development of financial industry in the three countries, and they all play a role in promoting China, while the relationship between household consumption and the United States and between price and Russia is reverse; Government consumption only has a significant impact on Russia; from the perspective of mutual influence, the mutual investment between the financial industry of China and the United States is relatively large, while the relationship between the Russian financial industry and the two countries is relatively weak. It shows that under the background of covid-19, the development of financial industry is affected.

Exploring the Effects of Industrial Structure, Technology, and Energy Efficiency on China’s Carbon Intensity and Their Contributions to Carbon Intensity Target

To achieve the national carbon intensity (NCI) target, China should adopt effective mitigation measures. This paper aims to examine the effects of key mitigation measures on NCI. Using the input-output table in 2017, this paper establishes the elasticity model of NCI to investigate the effects of industrial development, intermediate input coefficients, energy efficiency, and residential energy saving on NCI, and further evaluates the contributions of key measures on achieving NCI target. The results are shown as follows. First, the development of seven sectors will promote the increase of NCI while that of 21 sectors will reduce NCI. Second, NCI will decrease significantly with the descending of intermediate input coefficients of sectors, especially electricity production and supply. Third, improving energy efficiency and residential energy saving degree could reduce NCI, but the latter has limited contribution. Fourth, the development of all sectors will reduce NCI by 10.11% in 2017–2022 if sectors could continue the historical development trends. Fifth, assuming that sectors with rising intermediate input coefficients would keep their coefficients unchanged in the predicting period and sectors with descending coefficients would continue the historical descending trend, the improvement of technology and management of all sectors will reduce NCI by 14.02% in 2017–2022.