National Bureau Of Statistics Of China Research Articles

Ensemble Learning Applications in Multiple Industries: A Review

This study proposes a systematic review of the application of Ensemble learning (EL) in multiple industries. This study aims to review prevailing application in multiple industries to guide for the future landing application. This study also proposes a research method based on Systematic Literature Review (SLR) to address EL literature and help advance our understanding of EL for future optimization. The literature is divided three categories by the National Bureau of Statistics of China (NBSC): the primary industry, the secondary industry and the tertiary industry. Among existing problems in industrial management systems, the frequently discussed are quality control, prediction, detection, efficiency and satisfaction. In addition, given the huge potential in various fields, the gap and further directions are also suggested. This study is essential to industry managers and cross-disciplinary scholars to lead a guideline to solve the issues in practical work, as it provided a panorama of application domains and current problems. This is the first review of the application of EL in multiple industries in the literature. The paper has potential values to broaden the application area of EL, and to proposed a novel research method based SLR to sort out literature.

The Application of Exponential Smoothing in GDP Forecasting

GDP forecasting is the estimation of gross domestic product (GDP) over a period of time in the future, which is important for national governments, businesses, and investors respectively. The exponential smoothing method, also known as an exponentially weighted average method, is a forecasting method with the advantages of a clear process and convenient calculation. In this paper, the literature method is used, and "gross domestic product", "GDP", and "exponential smoothing method" are used in various databases and literature review websites, "Macroeconomics" and "forecasting" as the keywords to search, comb the literature, categorize and summarize the application of exponential smoothing method in GDP forecasting, and at the same time, the experimental method is used to design an experiment to forecast the future growth of GDP in the next three years by using the data published by the National Bureau of Statistics of China (NBSC). The results of the experiment are that the value-added of the primary industry is expected to continue to grow from about 9227.246 billion Yuan in 2023 to about 100139.20 billion Yuan in 2025. The value added of the secondary industry is projected to continue to grow from about 510,795,800,000,000 Yuan in 2023 to about 563,968,676,000,000 Yuan in 2025. The value added to the tertiary sector is projected to continue to grow from about 679,630.84 billion yuan in 2023 to about 753,204.88 billion yuan in 2025. Correspondingly, the Gross Domestic Product (GDP) will continue to grow, from about 1,281,982,888 million yuan in 2023 to about 1,417,312,284 million yuan in 2025. By analyzing the forecast results, it can be seen that all three major industries in China will maintain growth in the next three years. Depending on the different attributes of the three major industries, the government or enterprises will take appropriate measures to ensure the growth of the industries as well as to cope with various risks. This forecast is based on past data, but the actual economic situation may be affected by many external factors such as the international trade environment and the global economic situation. Governments and businesses will therefore need to pay close attention to these factors in order to adjust their strategies in a timely manner.

Corporate Innovation Incentive Policy During Business Cycles: Fiscal Subsidies or Tax Incentives?

ABSTRACT This paper empirically tests the incentive effect of fiscal policy on corporate innovation from 2007 to 2019 in China. With data from A-share-listed companies in the China Stock Market & Accounting Research (CSMAR) and Wind databases and GDP data from the National Bureau of Statistics of China (NBSC), the paper uses the Hodrick – Prescott (HP) filter method and a panel fixed effects model to empirically test the incentive effect of fiscal and tax policies on corporate innovation, compares the incentive differences between tax incentives and fiscal subsidies across different business cycles, and conducts heterogeneity analysis. The study finds that although fiscal subsidies and tax incentives promote enterprise innovation, the innovation incentive effect of fiscal subsidies is greater during an economic downturn than during an upturn. In contrast, tax incentives are stronger during an economic upturn than during a downturn. The results of this research may help to develop economic policies and to guide the precise implementation of tax and fee reductions.

The Impact of the Digital Economy on Innovation: New Evidence from Panel Threshold Model

The digital economy has aroused widespread concern. This paper studies the impact of the digital economy on innovation using a panel threshold model. Taking 30 provinces, municipalities, and autonomous regions in China as the research object, the time span is from 2013 to 2019. The data are from the National Bureau of Statistics of China (NBSC), China National Intellectual Property Administration (CAIPA), the China Stock Market and Accounting Research (CSMAR), and the Ministry of Industry and Information Technology (MIIT)of China. Data analysis is performed with ArcGIS 10.2 and STATA 16 software. The influence mechanism of digital economy on innovation is innovatively analyzed from the aspects of innovation elements, innovation tools, innovation subjects, and innovation environment. A digital economy development level index system is constructed using the entropy method, and the development level of China’s digital economy in time and space is analyzed. On this basis, the nonlinear impact of digital economy on innovation, i.e., the threshold effect, is innovatively studied using the panel threshold model. It is found that China’s digital economy develops rapidly, but there is a serious spatial imbalance, and there are great differences in the different dimensions of the digital economy. At the same time, the impact of digital economy on innovation has a double threshold effect with industrial structure as the threshold variable and a single threshold effect with urbanization level as the threshold variable. Specifically, the promoting effect of digital economy on innovation increases with the optimization of industrial structure or the improvement of urbanization level. This study enriches the theoretical research on the impact of digital economy on innovation, and it has important support and reference value for China’s development of digital economy and improvement of innovation capacity.

Impact Measurement of COVID-19 Lockdown on China's Electricity-Carbon Nexus.

Lockdown measures to prevent the spread of coronavirus disease 2019 (COVID-19) resulted in the plummeting of China’s overall electric-power demand and production. To date, power generation remains one of the largest carbon dioxide (CO2) emitting sectors of China on account of its high carbon intensity. Within this context, our study seeks to measure the impacts of COVID-19 lockdown on the electricity-power related carbon footprints on both generation and consumption sides. Built on statistical data of electricity generation and consumption released by the National Bureau of Statistics of China (NBSC), we calculate he nationwide electricity related CO2 emission changes in regional, economic-sectoral and technological dimensions during January–April 2020, when the strictest lock-down measures were taken in China and compare the results with the same months of the year prior. Our results show that both east and central China power grids witnessed drastic reduction (15.0% and 13.8%) in electricity-generation caused CO2 emissions; and the biggest falls of provincial-scale electricity-generation CO2 emission took place in Hubei (27.3%). Among China’s electricity production mix, coal remains the biggest CO2 emitter and contributed 95.7% of the overall nationwide reduction. The most significant decline of the nationwide consumptive-electricity carbon footprint was by 10.1% in February, with the secondary economic sector the biggest contributor.

Research and application of real-time monitoring and early warning thresholds for multi-temporal agricultural products information

Monitoring and early warning is an important means to effectively prevent risks in agricultural production, consumption and price. In particular, with the change of modes of national administration against the background of big data, improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making. Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning. How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning. Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society, this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions. Based on the data of the National Bureau of Statistics of China (NBSC) and survey data, this paper used a variety of statistical methods to determine the early warning thresholds of the production, consumption and prices of agricultural products. Combined with Delphi expert judgment correction method, it finally determined the early warning thresholds of agricultural product information in multiple time, and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018. The results show that: (1) the daily, weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products; (2) the multi-temporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information, provide a benchmarking standard for China's agricultural production, consumption and price monitoring and early warning at the national macro level, and further improve the application of China's agricultural product monitoring and early warning.

The Effects of Compliance Timing on Multinational Enterprises’ Corporate Performance in China: An Application of Institutional Perspectives

Purpose – Multi-National Enterprises (MNEs) tend to face a high level of institutional pressures in regions with high institutional development level. When complying with institutional pressures, firms try to make decisions to maximize profit while minimizing the risks to them. The purpose of this study is to investigate the influence of the institutional development level on institutional compliance timing by MNEs and the relationship between compliance speed and corporate performance. Design/methodology – The research focuses on three main variables, which are the institutional development level (as a determination of the institutional pressure level), the firm’s compliance speed (as a determination of the compliance timing), and the firm’s financial performance (as a determination of the corporate performance). We collected 19,869 firm-level data from CSMAR (the China Stock Market and Accounting Research), 6,922 CSR data from RKS (the Rankins CSR Ratings), and province and city-level data from the NERIM (National Economic Research Institute Index of Marketization) and NBSC (National Bureau of Statistics of China). The firms in China were chosen for analysis, and the analysis period was from 2008 to 2017. Random Effects GLS Regression was used to test the relationships among the variables. Findings – This study examined the effect of the institutional development level on the firm’s compliance speed, together with the effect of compliance speed on the firm’s financial performance of the MNEs in China. We found that the institutional development level positively influenced firms’ financial performances, which means the firms’ financial performances are better in the region with a high institutional development level. The compliance speed of institutional practice by firms was faster in the higher level of institutional development. However, the firm’s delayed compliance led to better financial performance. Originality/value – Studies in the resource dependence view of Institutional Theory often fall short in understanding the theory by overlooking the firm’s active decision-making. Thus, the findings do not present a full scope of corporate performance in this regard. This study not only found a way to test the role of a firm’s independent decision-making (i.e., compliance timing) when facing the institutional pressure but also prove the significant role of the compliance timing on corporate performance. Also, we were able to test the effect of institutional development level, controlling location-specific variables because we used CSR performance data for MNEs operating in China. Lastly, by doing the above, the findings of this study suggest practical implications to the industry practitioners in MNEs.

Modeling and dynamic analysis of tuberculosis in mainland China from 1998 to 2017: the effect of DOTS strategy and further control

BackgroundTuberculosis (TB) is one of the most important health topics in the world. Directly observed treatment and short course chemotherapy (DOTS) strategy combines medicine care and modern health system firmly, and it has been carried out by World Health Organization (WHO) since 1997. In the struggle with TB, China has promoted the process of controlling the disease actively, and the full coverage of DOTS strategy has been reached around 2004. Mathematical modeling is a very useful tool to study the transmission of diseases. Understanding the impact of DOTS strategy on the control of TB is important for designing further prevention strategy.MethodsWe investigate the impact of control strategy on the transmission of TB in China by dynamic model. Then we discuss further control for TB aiming at developing new vaccine and improving treatment. The optimal control problem, minimizing the total number of infectious individuals with the lowest cost, is proposed and analyzed by Pontryagin’s maximum principle. Numerical simulations are provided to illustrate the theoretical results.ResultsTheoretical analysis for the epidemic model is given. Based on the data reported by National Bureau of Statistics of China (NBSC), the basic reproduction number of each stage is estimated and compared, and they are mathcal {R}_{0}^{1}=1.7885 and mathcal {R}_{0}^{2}=1.0741, respectively. Optimal control strategy for further control is designed and proved well. An intuitionistic comparison between the optimal control strategy and the current control strategy is given.ConclusionsThe diagnosis and treatment of TB in China have been promoted a lot and the mathcal {R}_{0} is reduced by the full coverage of DOTS strategy. However, the mathcal {R}_{0} in China is still greater than 1 now. The relationship between mathcal {R}_{0} and vaccination strategy is shown. Optimal strategy aiming at exposed and infected population is suggested for further control.

Trade Liberalization, Markup and Resource Allocation

In recent years, the research on Chinese multi-product firms has aroused wide attention. As an important part of Chinese trade, data show that about 75% of the total export enterprises are multi-product firms in China, and the exports of MFNs take up more than 95% of the total export values between 2000 and 2005. Additionally, based on the product classification by BEC (Broad Economic Categories), the imports of intermediate goods account for more than 70% of Chinese total import values. Therefore, it is more in line with China’s national conditions and significant to explore the effect of intermediate trade liberalization on Chinese multi-product firms. Especially, with the rising events of de-globalization, the study on how to face the shock of intermediate liberalization by adjusting the markups of different products, and to optimize the resource allocation within enterprises and improve the competitiveness of Chinese MFNs, becomes of much greater importance for China nowadays. In this paper, based on Melitz and Ottaviano (2008), we first theoretically construct a heterogeneous firm model with the variable markup, and then estimate the firm-product level markup of Chinese manufacturing firms by modifying the augmented approach proposed by De Loecker, et al. (2016). Using highly disaggregated Chinese firm-level data from the National Bureau of Statistics of China (NBSC) and Chinese Custom data, this paper empirically uncovers the patterns of how Chinese multi-product exporters adjust the markups of their core and non-core products, during the intermediate trade liberalization. We find that core products enjoy the highest markup in a multi-product firm and the firm tends to adjust its non-core products’ markups more after the reduction of intermediate input tariff. To be more specific, the closer a product situates to the core product in the product rank ladder, the greater extent that the firm would adjust its markup to. This indicates that the intermediate input liberalization would help to narrow the gap between the core and the non-core products within the multi-product firms, and thus optimize the resource allocation. In addition, we do a series of robustness checks, which further support our aforementioned main findings. On the one hand, our research contributes to the traditional literature by examining whether and how input tariff reduction would help to adjust the markups between the core and non-core products within MFNs. On the other hand, this paper is complementary to a large body of studies on the impact of trade liberalization on market power and resource allocation. Our results suggest that China should further promote the process of trade liberalization, especially the intermediate trade liberalization, to help to optimize the resource allocation within firms. In contrast to the previous study which shows that trade liberalization can be not to the benefit of the development of weak (non-core) products (industries), we find that after the tariff reduction of intermediate goods, Chinese exporters tend to improve the markups more for the non-core products. Therefore, we suggest that one should continue to implement the product diversification strategy in the MFNs, so as to further enhance the comprehensive competitiveness of Chinese exporters and improve their ability to confront the worldwide intensive pressure by the frequent rising trade frictions, and then help to complement the strategy of building up national strength with international trade in the new era.

The Effect of the National Plan (2010–2020) on the Development of Special Education in China: Evidence from Before–After Design at a 7-Year Interval

The possible effect of the National Plan on the development of special education has not been examined, and there is no published evidence concerning both national and international readership about the realisation of this policy document in China. Given this, we conducted a before–after design study at a 7-year interval including six variables of special education: number of schools, total enrolment, new enrolment, graduates, educational personnel, and full-time teachers. The data were retrieved from the National Bureau of Statistics of China (NBSC). The results indicated two patterns of special education development in China. First, the National Plan has quantitatively affected some special education services (schools, new enrolments, educational personnel, and full-time teachers). Second, the National Plan has possibly resulted into better control of the quality of special education—evidenced by an insignificant increase in total enrolment and graduates at the two compared intervals.

A two-level comparison of CO2 emission data in China: Evidence from three gridded data sources

Carbon dioxide (CO2) emissions from fossil-fuel combustion are a global concern, and since 2007, China has become the nation with the highest amount of CO2 emissions. In order to understand China's carbon science research and reduction policies, it is crucial to benchmark CO2 emission estimates from different sources at multiple administrative levels. Therefore, this paper firstly compares the Emission Database for Global Atmospheric Research (EDGAR), the Fossil Fuel Data Assimilation System (FFDAS), and the China High Resolution Emission Gridded Data (CHRED) against energy census data from the National Bureau of Statistics of China (NBSC) at the province level. Results revealed that CHRED—today's finest resolution and most bottom-up approach of CO2 emission estimation in China—is the most consistent dataset with NBSC among the three (with both Pearson's R and Kendall's τ of 0.86). Secondly, EDGAR and FFDAS are compared with CHRED at the prefectural level. Finally, empirical models were developed to reconcile EDGAR and FFDAS with CHRED at both province and prefectural levels to facilitate future longitudinal studies of CO2 emissions in China.

Corporate governance, human capital, and productivity: evidence from Chinese non-listed firms

ABSTRACTThis article analyses the effects of corporate governance (CG) and human capital on productivity by using the 1999–2006 data from the National Bureau of Statistics of China (NBSC). The findings of this study are twofold. First, CG and human capital generate significant positive effects on the productivity of both state-owned enterprises (SOEs) and non-SOEs. Second, CG has significantly different moderate and mediate effects on the relationship between human capital and productivity. Our results are robust to different specifications and alternative measures. This study provides clear policy implications by suggesting that the firms in emerging markets, especially SOEs, must improve their CG and their allocation of human capital for them to enhance their productivity.

The puzzle of the missing meat: Food away from home and China's meat statistics

From 1985, an increasing gap has emerged between the official statistical measures of meat production and meat consumption in China, which has raised concerns from many researchers using such data. In this paper we report the results of 428 observations (survey of 107 urban and rural households×4 quarters) from 7 provinces conducted in 2010, and compare them with the official statistical data from the National Bureau of Statistics of China (NBSC). We conclude that the main reason for the discrepancy is due to the underreporting of consumption, which is due mainly to the omission of consumption away from home.

Credit constraints, quality, and export prices: Theory and evidence from China

This paper presents theory and evidence from highly disaggregated Chinese data that tighter credit constrains force firms to produce lower quality. The paper modifies Melitz’s (2003) model of trade with heterogeneous firms by introducing quality choice and credit constraints. The quality sorting model predicts that tighter credit constraints faced by a firm reduce its optimal prices due to its choice of lower-quality products. However, when quality cannot be chosen by a firm in an efficiency sorting model, there is an opposite prediction that prices increase as firms face tighter credit constraints. An empirical analysis using Chinese bank loans data and a merged sample of large trading firms based on Chinese firm-level data from the National Bureau of Statistics of China (NBSC) and Chinese customs data strongly supports quality sorting and confirms the mechanism of quality adjustment: firms optimally choose to produce lower-quality products when facing tighter credit constraints. Moreover, the predictions of the efficiency sorting model are supported by using quality-adjusted prices in regression analysis and by using quality variation across firms within the same product.

Approximating the DGP of China's quarterly GDP

We demonstrate that the Data Generating Process (DGP) of China's cumulated quarterly Gross Domestic Product (GDP, current prices), as it is reported by the National Bureau of Statistics of China (NBSC), can be (very closely) approximated by a simple rule. This rule says that the annual growth in any quarter is equal to the annual growth in its previous quarter plus an error term that is only nonzero in the first quarter of each year and with small variance. We show that this rule fits the data well for the period 1992Q1–2005Q4 for total GDP. It also gives accurate forecasts for 2006Q1–2009Q4.

Land use regionalization of rural settlements in China

This paper compartmentalizes regional land use of rural settlements in China by employing a hierarchical clustering method. The statistic data are sourced from the National Bureau of Statistics of China (NBSC) and the data of land use change from the Ministry of Land and Resources of China (MLRC). The population of rural settlement decreases from the southeast to the northwest of China and the density of rural settlement decreases from the east to the west of China. Land-use scale of rural settlement, the proportion of one-storey houses and the average household area decrease from the north to the south of China. The ratio of area of cultivated land to rural settlement is high in the northeast and southwest of China but low in the southeast of China. The land use regionalization of rural settlement can be divided into four regions, namely: the northern region of China, Qinghai-Tibet, Yunnan-Guizhou, and the middle and eastern region of China. The northern region of China and the middle and eastern region of China can be further divided into nine sub-regions: Xinjiang, Northeast China, Ningxia and Inner Mongolia, North China, the south of the Changjiang (Yantze) River and Sichuan Basin, Jiangsu-Shanghai, South China, the Loess Plateau, and Guangxi. In consideration of the significant regional differences, it is proposed that different policies should be implemented regarding the utilization and management of rural settlements.

Credit Constraints, Quality, and Export Prices: Theory and Evidence from China

This paper presents theory and evidence from highly disaggregated Chinese data that tighter credit constrains force firms to produce lower quality. The paper modifies Melitz's (2003) model of trade with heterogeneous firms by introducing quality choice and credit constraints. The quality sorting model predicts that tighter credit constraints faced by a firm reduce its optimal prices due to its choice of lower-quality products. However, when quality cannot be chosen by a firm in an efficiency sorting model, there is an opposite prediction that prices increase as firms face tighter credit constraints. An empirical analysis using Chinese bank loans data and a merged sample of large trading firms based on Chinese firm-level data from the National Bureau of Statistics of China (NBSC) and Chinese customs data strongly supports quality sorting and confirms the mechanism of quality adjustment: firms optimally choose to produce lower-quality products when facing tighter credit constraints. Moreover, the predictions of the efficiency sorting model are supported by using quality-adjusted prices in regression analysis and by using quality variation across firms within the same product.

Trend analysis of building height and total floor space in Beijing, China using ICESat/GLAS data

GLA14, one of the products of the spaceborne Light Detection and Ranging (LiDAR) sensor Geoscience Laser Altimeter System (GLAS), provides six Gaussian decomposition waveforms that represent different vertical layers of the ground target in a laser spot. In this article, we have extracted the relative height of ground targets from peak positions of the GLAS waveform, carried out the field validations, analysed the trend of building height in Beijing and then multiplied the building height and the percentage of building area within a pixel of the land-use/land-cover classification map to get the annual change of total floor space of buildings in Beijing. Based on the total floor space of buildings (TFSB) released by the National Bureau of Statistics of China (NBSC), we have established a linear regression model between the GLAS-estimated total floor space in Beijing and the data provided by NBSC. The results show that the building height and (TFSB) in Beijing increased from 2003 to 2008. The method proposed in this article expands research on urban change from a two-dimensional plane to a three-dimensional space to improve research accuracy, and is complementary to current remote-sensing methods.

Testing Heckscher-Ohlin Theorem Using Chinese Industrial Factor Intensity Data: Further Evidence from EU Import Markets

Following the approach proposed earlier, the authors extended the empirical tests of Heckscher-Ohlin Theorem to the European Union (EU) import markets. Utilizing extra-trade data provided by Eurostat on imports between 1995 and 2008 for EU15, those between 1999 and 2008 for EU27, and Chinese industry data from the National Bureau of Statistics of China (NBSC) for a sample of 32 Chinese industry groups, the findings provided further empirical evidences that industrial factor intensity was a significant factor explaining the export capability of the Chinese industries. In addition, results obtained from the EU import markets are compared with those from the US during the corresponding periods, and the initial evaluation seems to suggest that the EU import markets might subject to more distortions either due to artificial trade restrictions or to other peculiar characteristics.

Focusing on Industry Factor Intensity Testing of Heckscher-Ohlin Theorem with Chinese Industry Data

This paper presents a drastically different approach to testing the Heckscher-Ohlin Theorem (HO Theorem) of factor endowment theory by explicitly recognizing the underlying assumptions of the theory and designing a testing strategy that is capable of controlling most of the influencing forces implied by the assumptions. The testing strategy abandoned the methods of estimating and comparing product factor contents of imports and exports, or factor contents of net exports base on the input-output tables that to date has been default approaches in testing the HO Theorem. Instead, attention is focused on the industry factor intensity and its relationship with the export capability of the industry based on our restatement of the HO Theorem. Utilizing 1989-2008 Chinese industry data provided by the National Bureau of Statistics of China (NBSC) and US import data by the United States International Trade Commission (USITC), the authors constructed a data set consists of 30 industry groups for the 1989-1992 and 32 for the 1993-2008 periods that covers more than 80% of total US commodity imports from China, with proxies for industry factor intensity, industry competition intensity, average firm scale, and industry export capability. In testing the HO Theorem, both simple and multiple regressions are performed for each and every individual year, and the results invariably lend strong support for the factor endowment theory.