Booming Index Research Articles

Unveiling the enigma: Exploring how uncertain crude oil prices shape investment expenditure and efficiency in Chinese enterprises

As a crucial energy resource, crude oil plays a vital role in propelling global economic progress. China's energy consumption is extensive due to its position as the second-largest global economy and leading importer of crude oil. A stable crude oil supply can support China's steady economic growth. The China Crude Oil Futures (INE) launch in 2018 has enriched the WTI and Brent crude oil market systems, further consolidating the critical position of crude oil in China's economic and financial development. Therefore, this paper first examines the impact of crude oil price uncertainty on the investment activities of Chinese micro-enterprises by selecting three crude oil futures: WTI, Brent, and INE. Based on the quarterly (half-year) report of Shanghai and Shenzhen A-share listed enterprises from 2008 to 2023, this study examines the effects of uncertainty in crude oil prices on investment spending and efficiency inside enterprises and the underlying mechanisms that drive these effects. This study provides evidence that the fluctuation in crude oil prices has a detrimental impact on investment expenditure, while concurrently improving the investment efficiency of enterprises. The mechanism test also demonstrates that the volatility of crude oil prices has the potential to diminish investment expenditure and enhance the investment efficiency of enterprises. On the macro level, it mainly depends on reducing the macroeconomic boom index, enterprise boom index, and entrepreneur confidence index. At the micro level, it relies on increasing enterprise cash flow, lowering enterprise investment expectations and consumer product demand. Further heterogeneous analysis indicates that during significant events such as the global COVID-19 pandemic and the Russia-Ukraine conflict, there is a substantial increase in crude oil price uncertainty, leading to reduced enterprise investment expenditure and improved enterprise investment efficiency. Furthermore, the volatility associated with the increase in oil prices has a more pronounced effect on investment outlays and operational effectiveness. Moreover, the volatility of crude oil prices significantly influences the investment expenditure and investment efficiency of enterprises in the secondary industry and non-state-owned sectors. This empirical study examined the causal relationship between crude oil price, investment spending, and investment efficiency. The results of this investigation enhance the current scholarly knowledge on the relationship between crude oil prices and investment, so contributing to the advancement and refinement of this particular field of inquiry. This paper makes a valuable exploration and attempt to explain the mechanism of the impact of crude oil price on the investment activities of micro-enterprises.

The impact of transparency stage and overseas refund investment inflows on the human improvement index

This paper examines the impact of the transparency stage and overseas refund investment inflows at the human improvement index. This paper aims to explore the mediating effect of the economic boom at the impact of transparency ranges and foreign direct funding inflows at the human improvement index. This research was carried out in 9 countries in Southeast Asia with a research length from 2012 to 2019. The facts analysis system changed into done the usage of course evaluation. The outcomes indicate that the transparency stage and overseas direct investment have a tremendous influence on economic growth and the human improvement index. Economic growth turned into additionally located to impact the human development index significantly. Therefore, monetary expansion is verified to mediate the transparency stage effect on the human development index. But the economic increase isn't always proven to have a mediating effect on the impact of foreign direct funding at the human improvement index. Therefore, based totally on the outcomes of this examination, the authorities of each use in Southeast Asia need to create a transparent government to increase economic increase and human improvement index. Further, outside investment needs to be recommended to make an excellent monetary boom and human development index.

Application status and optimization prospect of China’s electricity prosperity index

Electric power data can more realistically and objectively reflect the development trend of the national economy. The application of the boom index based on electric power data is an effective way for macroeconomic monitoring and early warning. This paper combs the application of the power prosperity index of the power industry, especially power grid companies, and finds that There are problems such as insufficient application of power data, traditional synthesis methods, irregular data processing, unscientific selection of benchmark indicators, and incomplete evaluation of index validity. Finally, the paper proposes the future direction of the research and application of power boom index optimization.

辽宁省电力景气先行指数与用电需求相关性研究

辽宁省电力景气先行指数与用电需求相关性研究

Investigation of the Linkage among China’s Macroeconomy, Stock Market and Real Estate Market

As two important constituents of China’s macro economy, there are a variety of relationships among China’s stock market, real estate market and its macro economy. In order to investigate these relationships, in this paper, especially with the Macroeconomic Boom Index reflecting China’s macro economy, we use cointegration theory and Granger analysis to demonstrate that there are long-term equilibrium relationship and bidirectional causality between the macro economy and the securities business, also between the macro economy and the real estate market, however, this kind of long-term Equilibrium relationship and bidirectional causality appears very weak.

Early Warning and Monitoring System of the Economic Situation in Real Estate Market

Currently, many scholars have theoretically studied the early warning index of real estate market, but few have focused on the implementation of the system. Our study provides a system for early warning and monitoring the economic situation in real estate market. We construct a boom index for China's real estate market based on the state space model. In particular, we provide users with intuitive graphical interface, which helps regulators distinguish the economic situation of real estate market in a scientific and convenient way. In addition, the system implementation includes some key technologies, such as model-solving, conversion and fusion among multi-data sources, cross-language invoking and hybrid programming.

Identification of vehicle booming sound and its objective evaluation using psychoacoustic parameters

Previous work revealed that booming sound quality is related to loudness and sharpness and that the booming index is developed by using the loudness and sharpness for a signal within the whole frequency range between 20 Hz and 20 kHz. In the present paper, the booming sound quality was found to be effectively related to the loudness at frequencies below 200 Hz; thus the booming index is updated by using the loudness of the signal filtered by the low pass filter at frequencies. The relationship between the booming index and sound metric is identified by an Artificial Neural Network (ANN).

Objective evaluation of interior noise booming in a passenger car based on sound metrics and artificial neural networks

Booming sound is one of the important sounds in a passenger car. The aim of the paper is to develop the objective evaluation method of interior booming sound. The development method is based on the sound metrics and ANN (artificial neural network). The developed method is called the booming index. Previous work maintained that booming sound quality is related to loudness and sharpness – the sound metrics used in psychoacoustics – and that the booming index is developed by using the loudness and sharpness for a signal within whole frequency between 20 Hz and 20 kHz. In the present paper, the booming sound quality was found to be effectively related to the loudness at frequencies below 200 Hz; thus the booming index is updated by using the loudness of the signal filtered by the low pass filter at frequency under 200 Hz. The relationship between the booming index and sound metric is identified by an ANN. The updated booming index has been successfully applied to the objective evaluation of the booming sound quality of mass-produced passenger cars.

Objective evaluation of interior sound quality in passenger cars during acceleration

While driving a passenger car, a driver can hear many sorts of sounds inside the car. Among them, the booming and rumbling sounds are classified as the dominant sound characteristics of passenger cars. A sound quality index evaluating the quality of these two sounds objectively is therefore required and is developed by using an artificial neural network (ANN) in the present paper. Throughout this research, the booming sound and rumbling sound were found to be effectively related to the loudness, sharpness and roughness, while the fluctuation strength is not related to these sounds. These subjective parameters are sound metrics in psychoacoustics and are used as the input of ANN. For the training process of the ANN, 150 interior sounds with booming sound quality and 150 interior sounds with rumbling sound quality of various subjective rates have been synthesized, referring to the sound characteristics of passenger cars. The other 16 interior sounds of passenger cars were obtained by measurement. The booming sound qualities and rumbling sound qualities for these interior sounds were subjectively evaluated by 21 persons for the target of the ANN. After the ANN was trained, the two outputs of this ANN were used for the booming index and rumbling index, respectively. These outputs were tested in the evaluation of the sound quality of the interior sounds which were measured inside of the 16 passenger cars. The preference rate for the 30 passenger cars was evaluated by using these two developed sound indexes. These indexes were also successfully applied to the enhancement of the interior sound quality for a developmental passenger car.

The application of artificial neural networks to the characterization of interior noise booming in passenger cars

The booming index has been developed recently to evaluate the sound characteristics of passenger cars. Previous work maintained that booming sound quality is related to loudness and sharpness -the sound metrics used in psychoacoustics-and that the booming index is developed by using the loudness and sharpness for a signal within whole frequencies between 20 Hz and 20 kHz. In the present paper, the booming sound quality was found to be effectively related to the loudness at frequencies below 200 Hz; thus the booming index is updated by using the loudness of the signal filtered by the low pass filter at frequencies under 200 Hz. The relationship between the booming index and the sound metric is identified by an artificial neural network (ANN). Interior sounds of 10 passenger cars were measured, and 21 persons subjectively evaluated the booming sound qualities for these interior sounds. Throughout this research, it was found that there is a high correlation between the results of these evaluations and the output of a neural network. The updated booming index has been successfully applied to the objective evaluation of the booming sound quality of massproduced passenger cars.