Will advancement in technologies bring fear and damage human employment? Evidence from China's manufacturing industry.

Advancement in technologies such as robotic industries and artificial intelligence bring fear among human being that jobs will be substituted by robots. Base on the panel data of 28 China's manufacturing industries, this research analyzed the impact of technical progress bias on employment. First, we calculate the technical progress bias index of 28 industries base on the stochastic frontier model with transcendental logarithm function found 16 industries were toward the skilled labor while the remaining 12 industries were toward the unskilled labor. Second, the empirical results show that technical progress bias has a positive impact on the total manufacturing employment and significant positive effect on the unskilled labor, while no significant impact on skilled labor employment. Third, the threshold effect test proves that if taking industry value-added per capita or R&D capital stock as threshold variable, the threshold about the impact exist, making the impact on skilled labor was insignificant.

A machine learning-based Biding price optimization algorithm approach.

Trading companies of used product market are struggling to gain customers attentaion and to sell the products. The aim of this research is to develop a mechanism that can maximize the sale of products while considering profit implications. The literature review classifies the procurement mechanism. Given the limited-supply nature, that also includes unpredictable quality levels and a procurement mechanism that perceives the company offering prices to suppliers on a single-item basis. The academic literature has not covered such a mechanism. Techniques like those that improve the required bidding strategy are reviewed and considered fit to be included in the support tool as the procedures intention to maximize an objective function depending on the bidding price and contain the probability of winning the auction and the profit made from the proceeding, the motivation laid on the approach that predicts the probability. It is determined that this assembles a Response to Reverse Request for Quotation that meets the assumptions of a First-Price Sealed-Bid(FPSD) auction that potentially includes a hidden reservation price.

Does globalization and ecological footprint in OECD lead to national happiness.

This study examines the relationship between globalization, ecological footprint, innovation, and subjective wellbeing in the form of happiness, using a comprehensive assessment of OECD countries from 2008 to 2020. The study employs FGLS, Quantile, and Bootstrap Quantile regression estimation to investigate the quadratic effects of globalization, ecological footprint, and the moderating effect of innovation while controlling for renewable energy and population density. Happiness is a multidisciplinary subject, and this study focuses on the economic dimensions of happiness. The findings reveal a nonlinear relationship between ecological footprint and globalization, with negative effects on subjective wellbeing at high levels of ecological footprint and globalization. However, the moderating effect of innovation mitigates these adverse effects, indicating that innovation can help to offset the detrimental impacts of ecological footprint and globalization on subjective wellbeing. The study's implications are significant for policymakers promoting sustainable economic growth while enhancing subjective wellbeing. The findings highlight the importance of investing in innovation and sustainable development to promote subjective wellbeing in the face of increasing ecological footprint and globalization. Additionally, this research contributes to the multidisciplinary understanding of happiness and provides valuable insights for future research in this area.

Housing investment and family entrepreneurship: Evidence from China.

The aim of this article is to explore the impact of housing investment on household entrepreneurship. Using survey data from China and employing a Probit model, we examine three aspects of housing status and innovatively subdivide household entrepreneurship into agricultural entrepreneurship and business entrepreneurship. The results show that households with higher housing investment are less likely to become agricultural entrepreneurs, but more likely to start a new business. Households with full-owned housing enjoy a higher likelihood to become business entrepreneurs. However, other ownerships have no relation with the choice of entrepreneurship. More housing loans discourage entrepreneurial activities. One exception is that bank loan raises the chance of being agricultural entrepreneurs. Households who build their own houses have a higher agricultural entrepreneurship. Buying market price houses encourages households to be business entrepreneurs. Low-price house and inherited house prevent households from being business entrepreneurs.

Optimization of investment strategies through machine learning.

The main objective of this research is to develop a sustainable stock quantitative investing model based on Machine Learning and Economic Value-Added techniques for optimizing investment strategies. Quantitative stock selection and algorithmic trading are the two features of the model. Principal component analysis and economic value-added criteria are used in quantitative stock model for efficiently stocks selection, which may repeatedly select valuable stocks. Machine learning techniques such as Moving Average Convergence, Stochastic Indicators and Long-Short Term Memory are used in algorithmic trading. One of the first attempts, the Economic Value-Added indicators are used to appraise stocks in this study. Furthermore, the application of EVA in stock selection is exposed. Illustration of the proposed model has been done on United States stock market and finding shows that Long-Short Term Memory (LSTM) networks can more accurately forecast future stock values. The proposed strategy is feasible in all market situations, with a return that is significantly larger than the market return. As a result, the proposed approach can not only assist the market in returning to rational investing, but also assist investors in obtaining significant returns that are both realistic and valuable.

Ecological environment pressure state and response system for coupling coordinate development: an application on china data.

This research aims to develop an ecological carrying capacity index for the ecological environment under the principle of the pressure-state-response framework model and discusses the coupling coordination of ecological environment pressure, state, and response system of the urban region in china from 2011 to 2020. Furthermore, predicated the degree of security warning for each year while establishing the ecological carrying capacity index and the urban ecological coupling model. Results specify that the coordination degree of urban ecological development in Nanchang, Jiangxi has been improved year by year, the ecological carrying capacity security index shows an upward tendency from the overall view, and the security warning degree rises from comparative insecurity to comparative security. The analysis demonstrates that in the process of national ecological civilization construction demonstration zone construction, the ecological resources and environmental policies adopted by Nanchang city have played a great role in promoting ecological security. However, the ecological security index in Nanchang is still below 0.6, far from the high-security level (0.77), and the government and the public still need to do a lot to improve ecological security.

Financial performance of China's listed firms in presence of coronavirus: Evidence from corporate culture and corporate social responsibility.

Motivated from the shortage of the existing research studies on impacts of dangerously contagious diseases on firms' financial performance, this study sheds light on the impacts of Coronavirus (Covid-19) outbreak on financial performance upon on the quarterly data of 126 Chinese listed firms across 16 industries. Overall, the Covid-19 outbreak reduced Chinese listed firms' financial performance proxied by the revenue growth rate, ROA, ROE, and asset turnover. This outbreak's negative effects on Chinese firms' profitability were much smaller than that on their revenue growth rates. While this outbreak's negative effects on financial performance of Chinese listed firms were bigger for those that were seriously affected by this pandemic like airlines, travel, and entertainment (ATE), this pandemic's effects were positive for the medicine industry. In the meanwhile, Chinese listed firms that located in high-risk regions suffered a bigger financial loss during the outbreak, and especially there was a strong Hubei effect. The corporate culture and CSR moderated the inverse relationship between this outbreak and Chinese firms' financial performance. Findings of this study contribute to enrich the existing literature on impacts of the Covid-19 outbreak on firms' financial performance worldwide and suggest helpful practical and theoretical implications.

Transition to a low-CO2 emissions economy: China government policy for early-stage green finance.

The popularity of green economy as an innovative technique and financial mechanism has soared as a result of this exchange, the gross domestic product (GDP); transition economy (TE); CO2 emissions; human capital (HC); Government Fund Strategy (GFS); green finance (GF) play a very important role. When it comes to advancing genetic civilization, China's achievements in the field of green money have become firm proof of the country's progress. China has come to terms with the fact that it cannot continue on its current path of promoting monetary development at the expense of the environment, both for its own people and for the sake of the global community. The country has prioritized environmental concerns over equality with others through economic, political, social, and other factors. Furthermore, in order to accomplish the enormous goal, China's cross-country coal use must be covered to allow it to peak before 2020, and fossil fuel byproducts must peak before 2030. This article argues that China's "green drive" is a cause for optimism and concludes by arguing that the top 2030 goal for fossil fuel byproducts is ambitious but doable.

Entropy-based financial asset pricing: Evidence from Pakistan.

Entropy is an alternative measure to calculate the risk, simplify the portfolios and equity risk premium. It has higher explanatory power than capital asset price model (CAPM) beta. The comparison of Entropy and CAPM beta provide in depth analysis about the explanatory power of the model that in turn help investor to make right investment decisions that minimizes risk. In this context, this study aims to compare Shannon and Rennyi Entropies with the CAPM beta for measuring the risk. Ordinary Least square approach has been utilized using a dataset of 67 enterprises registered in Pakistan Stock exchange. The comparative analysis of CAPM beta and entropy has been carried out with the R2 parameters. The result indicates that entropy has more explanatory power as compare to CAPM beta's explanatory power, and this turns out to be the best option to evaluate the risk performances. The result implies that an investor should make the best investment decision by choosing an enterprise that provide with good returns at minimum risk based on entropy technique.

COVID-19 pandemic and unemployment rate prediction for developing countries of Asia: A hybrid approach.

Unemployment is an essential problem for developing countries, which has a direct and major role in economy of a country. Understanding the pattrens of unemployment rate is critical now a days and has drawn attention of researcher from all fields of study across the globe. As unemployment plays an important role in the planning of a country's monetary progress for policymakers and researcher. Determining the unemployment rate efficiently required an advance modeling approach. Recently,numerous studies have relied on traditional testing methods to estimate the unemployment rate. Unemployment is usually nonstationary in nature. As a result, demonstrating them using traditional methods will lead to unpredictable results. It needs a hybrid approach to deal with the prediction of unemployment rate in order to deal with the issue associated with traditional techniques. This research primary goal is to examine the effect of the Covid-19 pandemic on the unemployment rate in selected countries of Asia through advanced hybrid modeling approach, using unemployment data of seven developing countries of Asian: Iran, Sri Lanka; Bangladesh; Pakistan; Indonesia; China; and India,and compare the results with conventional modeling approaches. Finding shows that the hybrid ARIMA-ARNN model outperformed over its competitors for Asia developing economies. In addition, the best fitted model was utilised to predict five years ahead unemployment rate. According to the findings, unemployment will rise significantly in developing economies in the next years, and this will have a particularly severe impact on the region's economies that aren't yet developed.

An analysis of machine learning risk factors and risk parity portfolio optimization.

Many academics and experts focus on portfolio optimization and risk budgeting as a topic of study. Streamlining a portfolio using machine learning methods and elements is examined, as well as a strategy for portfolio expansion that relies on the decay of a portfolio's risk into risk factor commitments. There is a more vulnerable relationship between commonly used trademarked portfolios and neural organizations based on variables than famous dimensionality decrease strategies, as we have found. Machine learning methods also generate covariance and portfolio weight structures that are more difficult to assess. The least change portfolios outperform simpler benchmarks in minimizing risk. During periods of high instability, risk-adjusted returns are present, and these effects are amplified for investors with greater sensitivity to chance changes in returns R.

The impact of agricultural water salvation investment on economics development: Evidence from Eastern China.

Agricultural water salvation is the lifeblood of the national economy and is of great significance to the high-quality development of the region. In order to maximize the economic assistances of agricultural water salvation investment, this article focuses on panel data from 2005 to 2019 in 14 provinces in Eastern China, this research constructs an economic development evaluation index system from five dimensions: innovative development, coordinated development, green development, open development and shared development, and uses dynamic panel model to explore the influence relationship and path of Eastern Agricultural water salvation investment on economic development. The results represent that: there is a significant non-linear effect between agricultural water salvation investment and economic growth, showing an inverted U-shaped relationship. Which means that with the expansion of agricultural water salvation investment; economic growth has risen first and then declined. At present, the impact of agricultural water salvation investment in the Eastern region on economic development is in the promotion stage of positive and sustained growth. The recommendation of this research will help the state control in the amount of agricultural water salvation investment in the Eastern region, improve the efficiency of agricultural water salvation investment, and provide support in decision making.

The impact of foreign direct investment on environment: evidence from newly industrialized countries.

This research aims to investigate the effect of foreign direct investment on carbon emissions through the panel ARDL method using annual data for the 1990-2016 period for the newly industrialized countries (NICs), including China, Malaysia, Mexico, Philippines, Thailand, Turkey, India, and Brazil. The stationarity of the series was obtained through LLC, IPS, and Fisher ADF panel unit root tests, the cointegration relationship with the panel ARDL-PMG approach, and the causality relationship with Dumitrescu and Hurlin (DH) tests. As a result of the long-term analysis, the foreign direct investment, energy consumption, and trade openness have a positive and significant impact on carbon emissions, whereas economic growth has a negative and significant impact on carbon emissions. The result shows that a percent increase in foreign direct investment increases carbon emissions by 0.03%. As a result of the short-term analysis, it was seen that the coefficient of the error correction term (ECT) was negative and statistically significant. According to DH panel causality test results, there exists a bidirectional causality relationship among energy consumption and carbon emissions, and a unidirectional causality relationship from economic growth and trade openness to carbon emissions and from carbon emissions to foreign direct investment. As policy implication, in industrialized countries especially China and India, there is a greater need to invest in green energy consumption at a larger scale to achieve future sustainable development goals.

Nexus between fossil fuel consumption and infant mortality rate: a non-linear analysis.

For nations already facing pollution issues, fossil fuel energy consumption is deteriorating living standards. Though prevailing infrastructure makes fossil fuel energy use feasible for production, it still pollutes our environment. This study in the domain of environment and development assesses the impact of fossil fuel energy consumption on the infant mortality rate in 15 Asian economies during 1996 and 2019. The living standards are assessed using infant mortality rate, while non-linear fossil fuel energy consumption is used with gross capital formation, employment, and preprimary education as independent variables. The feasible generalized least square method evaluates the effects. The study concludes that fossil fuel energy consumption follows a U-shaped relationship explaining infant mortality. The results point out that over-consumption of fossil fuel energy is deteriorating the living standards considering low air quality levels in Asian economies.

Fishing grounds footprint and economic freedom indexes: Evidence from Asia-Pacific.

Environmental challenges are as wide as the universe so that its different dimensions can be the subject of diverse studies. In this research, using 17 data from Asia-Pacific during the period 2000 to 2017, an attempt has been made to investigate the economic factors responsible for the ecological footprint in the fishing sector. The main contribution of the present study is to investigate the effects of nine economic freedom indicators along with other control variables on environmental pressure on the status of fishery resources. Based on the results, the Kuznets curve hypothesis was confirmed in the fishing grounds footprint, so that the growth of GDP per capita shows a positive and significant effect, while its squared form coefficient is negative. Other control variables including natural resource rents, urbanization, and energy intensity, do not show significant effects on the fishing footprint. The different components of economic freedom show different effects, while their cumulative effects in the form of the total economic freedom index have a positive effect on the footprint of fishing and lead to increased extraction from fishing resources. The results show that the Government Integrity, Tax Burden, Business Freedom, Monetary Freedom indices increase the fishing footprint, while the indices of trade freedom and investment freedom, by revealing the negative effects on the fishing footprint, have beneficial environmental effects in reducing the pressure on the aquatic resources of countries. The results of the present study reveal the need to examine how the various dimensions of economic freedom affect to provide the proper management of fishery resources.

Role of globalziation defining the incidence of entrepreneurship.

Globalization boosts the process of market predictions in the pursuit of economic growth. When economic, political, and social forces gain traction by promoting policies and the climate favoring globalization, entrepreneurial results reach out. Policymakers are still searching for a context within which regional policies can be structured to foster long-term entrepreneurship opportunities. The literature on entrepreneurial phenomena is incomplete and uncertain as to how globalization forces establish a nonlinear mechanism to promote the entrepreneurial process. This study provides the basic context for identifying globalization forces to create a nonlinear effect on the entrepreneurial process in order to address this problem. The results propose that policymakers strengthen the social and political dimension of globalization to increase opportunities-based entrepreneurship.