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\"Information Fantasies focuses on the cultural practices and media imaginations around information technologies, cybernetics, and systems theory in late 1970s and 1980s China. Xiao Liu explores China's rise to prominence in the global economy through revisiting these earlier 'information fantasies' present in science fiction, modernist writing, films, scientific treatises, historical monographs, and key intellectual debates\"-- Provided by publisher.

Few observers are unimpressed by the economic ambition of China or by the nation's remarkable rate of growth. But what does the future hold? This meticulously researched book closely examines the strengths and weaknesses of the Chinese economic system to discover where the nation may be headed and what the Chinese experience reveals about emerging market economies. The authors find that contrary to popular belief, cutting edge innovation is not a prerequisite for sustained economic vitality-and that China is a perfect case in point.

Economic development has brought about global greenhouse gas emissions and, thus, global climate change, a common challenge worldwide and urgently needs to be addressed. Accurate carbon price forecasting plays a pivotal role in providing a reasonable basis for carbon pricing and ensuring the healthy development of carbon markets. Therefore, this paper proposes a two-stage interval-valued carbon price combination forecasting model based on bivariate empirical mode decomposition (BEMD) and error correction. In Stage I, the raw carbon price and multiple influencing factors are decomposed into several interval sub-modes by BEMD. Then, we select artificial intelligence-based multiple neural network methods such as IMLP, LSTM, GRU, and CNN to conduct combination forecasting for interval sub-modes. In Stage II, the error generated in Stage I is calculated, and LSTM is used to predict the error; then, the error forecasting result is added to the first stage result to obtain the error-corrected forecasting result. Taking the carbon trading prices of Hubei, Guangdong, and the national carbon market, China, as the research object, the empirical analysis proves that the combination forecasting of interval sub-modes of Stage I outperforms the single forecasting method. In addition, the error correction technique in Stage II can further improve the forecasting accuracy and stability, which is an effective model for interval-valued carbon price forecasting. This study can help policymakers formulate regulatory policies to reduce carbon emissions and help investors avoid risks.

We analyze the role of the US–China trade war in forecasting out-of-sample daily realized volatility of Bitcoin returns. We study intraday data spanning from 1st July 2017 to 30th June 2019. We use the heterogeneous autoregressive realized volatility model (HAR-RV) as the benchmark model to capture stylized facts such as heterogeneity and long-memory. We then extend the HAR-RV model to include a metric of US–China trade tensions. This is our primary forecasting variable of interest, and it is based on Google Trends. We also control for jumps, realized skewness, and realized kurtosis. For our empirical analysis, we use a machine-learning technique that is known as random forests. Our findings reveal that US–China trade uncertainty does improve forecast accuracy for various configurations of random forests and forecast horizons.

Purpose - The purpose of this paper is to propose an objective method for technology forecasting (TF). For the construction of the proposed model, the paper aims to consider new approaches to patent mapping and clustering. In addition, the paper aims to introduce a matrix map and K-medoids clustering based on support vector clustering (KM-SVC) for vacant TF.Design methodology approach - TF is an important research and development (R&D) policy issue for both companies and government. Vacant TF is one of the key technological planning methods for improving the competitive power of firms and governments. In general, a forecasting process is facilitated subjectively based on the researcher's knowledge, resulting in unstable TF performance. In this paper, the authors forecast the vacant technology areas in a given technology field by analyzing patent documents and employing the proposed matrix map and KM-SVC to forecast vacant technology areas in the management of technology (MOT).Findings - The paper examines the vacant technology areas for MOT patent documents from the USA, Europe, and China by comparing these countries in terms of technology trends in MOT and identifying the vacant technology areas by country. The matrix map provides broad vacant technology areas, whereas KM-SVC provides more specific vacant technology areas. Thus, the paper identifies the vacant technology areas of a given technology field by using the results for both the matrix map and KM-SVC.Practical implications - The authors use patent documents as objective data to develop a model for vacant TF. The paper attempts to objectively forecast the vacant technology areas in a given technology field. To verify the performance of the matrix map and KM-SVC, the authors conduct an experiment using patent documents related to MOT (the given technology field in this paper). The results suggest that the proposed forecasting model can be applied to diverse technology fields, including R&D management, technology marketing, and intellectual property management.Originality value - Most TF models are based on qualitative and subjective methods such as Delphi. That is, there are few objective models. In this regard, this paper proposes a quantitative and objective TF model that employs patent documents as objective data and a matrix map and KM-SVC as quantitative methods.

In Chinese Firms and Technology in the Reform Era, Yizheng Shi analyses the technological behaviour of state- owned firms. In particular he shows how they have imported, utilised and assimilated foreign technology into their operations. The author argues that despite being granted more autonomy and having to face increased competition, Chinese firms are still not motivated to assimilate properly imported technology because of the absence of well- delineated property rights.

China and India, the world's two most populous countries, will exercise increasing influence in international affairs in the coming decades. This document assesses the relative prospects of China and India through 2025 in four domains: demography, macroeconomics, science and technology, and defense spending and procurement. In each domain, the authors try to answer the following questions: Who is ahead? By how much? and Why?

In the context of China’s strategic push toward high-quality development, the concept of new quality productive forces (NQPF)—which emphasizes technological innovation, green transformation, and digital upgrading—has received a lot of attention. However, the increasing volatility and ambiguity in climate-related policymaking present a serious institutional challenge. This study addresses the underexplored question of how climate policy uncertainty (CPU) affects the regional development of NQPF in China. Unlike traditional productivity, NQPF relies on long-term innovation and sustainable investment, which are highly sensitive to external policy signals. Drawing on panel data from 30 Chinese provinces between 2013 and 2021, this paper uses fixed-effects regressions to empirically assess the influence of CPU on NQPF. The findings reveal that CPU significantly suppresses the development of NQPF, but this effect is mitigated by financial inclusion, carbon market participation, and strong local government sustainability performance. This paper provides new insight into the risks posed by climate uncertainty to economic development and highlights institutional tools that can buffer its negative effects.

This paper presents a forecast and analysis of population, economic development, energy consumption and CO2 emissions variation in China in the short- and long-term steps before 2020 with 2007 as the base year. The widely applied IPAT model, which is the basis for calculations, projections, and scenarios of greenhouse gases (GHGs) reformulated as the Kaya equation, is extended to analyze and predict the relations between human activities and the environment. Four scenarios of CO2 emissions are used including business as usual (BAU), energy efficiency improvement scenario (EEI), low carbon scenario (LC) and enhanced low carbon scenario (ELC). The results show that carbon intensity will be reduced by 40-45% as scheduled and economic growth rate will be 6% in China under LC scenario by 2020. The LC scenario, as the most appropriate and the most feasible scheme for China's low-carbon development in the future, can maximize the harmonious development of economy, society, energy and environmental systems. Assuming China's development follows the LC scenario, the paper further gives four paths of low-carbon transformation in China: technological innovation, industrial structure optimization, energy structure optimization and policy guidance.

In the recent climate change negotiations it was declared that the increase in global temperature should be kept below 2°C by 2100, relative to pre-industrial levels. China's CO ₂ emissions from energy and cement processes already account for nearly 24% of global emissions, a trend that is expected to keep increasing. Thus the role of China in global GHG mitigation is crucial. A scenario analysis of China's CO ₂ emissions is presented here and the feasibility of China reaching a low-carbon scenario is discussed. The results suggest that recent and continued technological progress will make it possible for China to limit its CO ₂ emissions and for these emissions to peak before 2025 and therefore that the global 2°C target can be achieved. Policy relevance In signing the Copenhagen Accord, China agreed to the global 2°C target. Results from this article could be used to justify low-carbon development policies and negotiations. While many still doubt the feasibility of a low-carbon pathway to support the global 2°C target, the results suggest that such a pathway can be realistically achieved. This conclusion should increase confidence and guide the policy framework further to make possible China's low-carbon development. Related policies and measures, such as renewable energy development, energy efficiency, economic structure optimization, technology innovation, low-carbon investment, and carbon capture and storage (CCS) development, should be further enhanced. Furthermore, China can play a larger role in the international negotiations process. In the global context, the 2°C target could be reaffirmed and a global regime on an emissions mitigation protocol could be framed with countries’ emissions target up to 2050.