Predicting Bitcoin (BTC) Price in the Context of Economic Theories: A Machine Learning Approach.

Bitcoin (BTC)-the first cryptocurrency-is a decentralized network used to make private, anonymous, peer-to-peer transactions worldwide, yet there are numerous issues in its pricing due to its arbitrary nature, thus limiting its use due to skepticism among businesses and households. However, there is a vast scope of machine learning approaches to predict future prices precisely. One of the major problems with previous research on BTC price predictions is that they are primarily empirical research lacking sufficient analytical support to back up the claims. Therefore, this study aims to solve the BTC price prediction problem in the context of both macroeconomic and microeconomic theories by applying new machine learning methods. Previous work, however, shows mixed evidence of the superiority of machine learning over statistical analysis and vice versa, so more research is needed. This paper applies comparative approaches, including ordinary least squares (OLS), Ensemble learning, support vector regression (SVR), and multilayer perceptron (MLP), to investigate whether the macroeconomic, microeconomic, technical, and blockchain indicators based on economic theories predict the BTC price or not. The findings point out that some technical indicators are significant short-run BTC price predictors, thus confirming the validity of technical analysis. Moreover, macroeconomic and blockchain indicators are found to be significant long-term predictors, implying that supply, demand, and cost-based pricing theories are the underlying theories of BTC price prediction. Likewise, SVR is found to be superior to other machine learning and traditional models. This research's innovation is looking at BTC price prediction through theoretical aspects. The overall findings show that SVR is superior to other machine learning models and traditional models. This paper has several contributions. It can contribute to international finance to be used as a reference for setting asset pricing and improved investment decision-making. It also contributes to the economics of BTC price prediction by introducing its theoretical background. Moreover, as the authors still doubt whether machine learning can beat the traditional methods in BTC price prediction, this research contributes to machine learning configuration and helping developers use it as a benchmark.

Determinants of financial inclusion gaps in Pakistan and implications for achieving SDGs.

This study investigates the determinants of gender disparities in financial inclusion in Pakistan using Global Findex 2021 survey data. We aim to quantify gender gaps in financial access and use, and to analyze the socio-economic factors influencing these disparities. Grounded in Sen's capability approach and behavioral economics, we employ logistic regression to examine how gender influences the ownership and usage of financial products. Our results reveal significant gender gaps: only 13% of Pakistani women have financial accounts compared to 34% of men, with similar disparities in digital finance. Socio-economic variables like education, income, and employment are found to influence financial inclusion differently for men and women. While generally supportive of financial inclusion, these factors have a weaker effect for women, suggesting deeper societal barriers. This study adds to the global financial inclusion discourse by providing a comprehensive analysis of gender disparities in Pakistan. Our findings highlight the need for gender-sensitive policies that address these disparities to achieve Sustainable Development Goals related to gender equality and economic empowerment.

Exploring the impact of China-Europe Railway Express on the urban-rural income gap.

The China-Europe Railway Express (CRexpress) has established a new land transportation route between Asia and Europe as part of China's westward expansion. The resulting trade promotion effect has the potential to improve industrial development and factor flows, ultimately leading to a reduction in the income disparity between urban and rural areas in cities that use the CRexpress. The impact of the CRexpress on income disparities between urban and rural areas in cities that use the service is of particular interest, as the empirical evidence on the relationship between international trade and these disparities is inconsistent. Using a difference-in-differences model and macro panel data, this study found that the CRexpress significantly narrowed the urban-rural income gap in cities where it was operational, and that this effect had a spillover effect on nearby cities. However, the magnitude of this effect decreased with distance. The mechanism analysis indicated that the CRexpress narrowed the income gap by promoting secondary industry development, but this effect varied significantly by region, with pronounced effects in eastern coastal cities and less pronounced effects in inland cities in the central and western region. The study suggests that local governments in these regions should focus on improving the institutional environment and providing industrial support to promote industrial transfer in order to narrow the urban-rural income gap and promote overall economic development.

Mechanism and Impact of Digital Economy on Urban Economic Resilience under the Carbon Emission Scenarios: Evidence from China's Urban Development.

China is currently experiencing a phase of high-quality development, and fostering the resilience of the urban economy is key to promoting this development. The growth of the digital economy is seen as critical to achieving this goal. Therefore, it is necessary to study the mechanism by which the digital economy affects urban economic resilience and the impact of carbon emissions. To this end, this paper empirically analyzes the mechanisms and impacts of the digital economy on urban economic resilience using panel data from 258 prefecture-level cities in China between 2004 and 2017. The study employs a two-way fixed effect model and a moderated mediation model. The results show that: (1) The development of the digital economy can significantly improve the resilience of the urban economy in different periods and different city sizes; (2) The development of the digital economy promotes the economic resilience of developed cities and eastern cities more significantly; (3) In the context of carbon emissions, the digital economy positively contributes to urban economic resilience through population quality and industrial structure but negatively contributes to urban economic resilience through above-scale enterprises; (4) Carbon emissions have a positive moderation effect on the historical path of the industrial structure, above-scale enterprises, and the front path of population quality in the mechanism of the role of the digital economy on the economic resilience of cities, and a negative moderation effect on the front path of above-scale enterprises. Based on these findings this paper proposes several suggestions, such as revolutionizing the digital development of cities, optimizing regional industrial collaboration, accelerating the training of digital talents, and preventing the disorderly expansion of capital.

Can agricultural mechanization services narrow the income gap in rural China?

This paper examines the impact of agricultural mechanization services (AMS) on rural household income and income gap, utilizing the recentered influence function regression method and publicly available data collected through the China Labor-force Dynamics Survey. The results of this study shed light on various impacts of AMS. First, agricultural mechanization services can significantly increase rural household income, but there is heterogeneity in the impact on rural household income in different quantiles. The effect of income growth on medium-income and low-income groups is greater. Second, agricultural mechanization services help to narrow the income gap between rural households and alleviate income inequality in rural areas. Third, the effect of agricultural mechanization services on reducing the income gap between rural households in the eastern and western regions is significantly stronger than that in the central region. Finally, further analysis based on income source structure reveals that agricultural mechanization services can significantly reduce the non-agricultural income gap of rural households, but the impact on the agricultural income gap is negligible. Our findings highlight the importance of government's efforts in promoting the development of agricultural mechanization service market in order to improve the income inequality in rural areas.

Analyzing past and future trends in Pakistan's groundwater irrigation development: implications for environmental sustainability and food security.

Since the last four decades, groundwater irrigation has played a critical role in improving crop production and rural livelihoods. However, the flawed policies have allowed farmers to install private tube wells relentlessly, resulting in a slew of water quality and environmental issues. This study aims to investigate the key trends in temporal development of groundwater irrigation and its consequences in Pakistan. The dataset, which spanned 38 years (1981 to 2018), included variables such as the number of tube wells, wheat area and production, farm size, total cultivated area, and total irrigated area in Punjab province. Our results show that, while the number of government-installed tube wells has decreased over time, the number of private tube wells has increased by 579% since 1981. About 85% of these privately owned tube wells are diesel tube wells, while the remaining 15% are electric tube wells. The ARDL regression results show that groundwater development, as a result of growth in private tube wells, has significantly aided wheat production in both the short and long run. However, the results of ARIMA model show that, in the absence of any regulatory mechanism to limit private tube well growth, the number of private tube wells in Punjab will increase by 43% over the next two decades, potentially jeopardizing the country's groundwater sustainability and food security. To ensure the sustainability of groundwater use, farmers' incomes, and the food security of the population, there is an urgent need to devise policy options to limit the growth of probate tube wells in the province. In addition, the new regulations should consider the equity implications and the economic shock to poor farms and households.

Ecological Sustainability and Households' Wellbeing: Linking Households' Non-Traditional Fuel Choices with Reduced Depression in Rural China.

A sustainable and pleasant environment is deemed to offer various positive externalities such as scenic, visual and behavioral archetypes and patterns exhibiting in various forms. Such a scenario can significantly relieve households from many psychological and personal complications such as depression. Depression has aroused great concerns in recent years due to its personal and social burdens and unforeseeable damage. Many studies have explored the effects of air pollution caused by traditional fuel consumption on depression. However, limited evidence is available on how household non-traditional fuel choices affect depression. Based on a nationally representative dataset collected from China Family Panel Studies (CFPS) in 2012, this paper employs an endogenous switching regression (ESR) model and an endogenous switching probit (ESP) model to address the endogenous issue and to estimate the treatment effects of non-traditional fuel choices on depression in rural China. The empirical results show that non-traditional fuel users have significantly lower Epidemiologic Studies Depression Scale (CES-D) scores, indicating non-traditional fuel users face a lower risk of depression. Compared to solid fuels, employing non-traditional fuels will lead to a 3.659 reduction in depression score or decrease the probability of depression by 8.2%. In addition, the results of the mechanism analysis show that household non-traditional fuel choices affect depression by reducing the probability of physical discomfort and chronic disease. This study provides new insight into understanding the impact of air pollution in the house on depression and how to avoid the risk of depression in rural China effectively.

Food availability and shopping channels during the disasters: Has the COVID-19 pandemic changed peoples' online food purchasing behavior?

COVID-19 caused online buying channels to flourish across the globe. However, the extent to which online channels in Pakistan assisted peoples in coping with the pandemic remains unknown. This study aims to examine peoples behavior and perceptions regarding online food purchasing and its impact on different aspects of food security. The data were collected through online surveys of 1067 respondents in Punjab and Sindh provinces during the COVID-19 pandemic. We find that peoples access to food was adversely affected by the pandemic. However, people are increasingly purchasing food online, which has improved their accessibility to food. According to the findings, 62.51% of respondents reported to have changed their perception and behavior regarding online food purchasing. In addition, almost 46.40% of peoples reported that online shopping increased their access to food during the pandemic. Using logit regression, economic analysis shows that education, monthly income, and access to basic necessities such as clean drinking water, better sanitation, and better employment are positively related to online buying behavior. For future disaster situations in Pakistan to mitigate the adverse effects on food security, strengthening and promoting the use of online purchasing channels could be an important policy instrument.

Towards Sustainable Diets: Understanding the Cognitive Mechanism of Consumer Acceptance of Biofortified Foods and the Role of Nutrition Information.

Micronutrient malnutrition, also known as hidden hunger, continues to affect more than 2 billion people globally. Biofortification, which is a process of breeding staple crops with improved micronutrient contents such as vitamin A, iron, and zinc, offers a cost-effective and sustainable solution in reducing hidden hunger. However, the success of these foods depends on consumer acceptance. In contrast to previous studies, this research focuses on the mechanism of consumer acceptance of biofortified crops that undergo physical changes (i.e., changes in appearance) after biofortification. We use data on 473 Chinese consumers collected through online surveys to examine their purchase intentions for biofortified foods that have visible (vs. invisible) nutrition traits. Using two online surveys, we conduct two studies to reveal the mechanism and antecedents of consumer acceptance of different biofortified foods. In Study 1, we find that consumer purchase intentions vary depending upon the visibility of nutrition traits in biofortified foods. Specifically, consumers exhibit a nutrition-related food neophobia (NFN) regardless of visibility of the nutrition trait in biofortified foods; and a sensory-affective food neophobia (SFN) which is only pronounced when the nutrition trait in biofortified foods is visible. The results of the mediation analysis show that for both types of biofortified foods, NFN mediates consumers' purchasing intentions. For foods that involve visible changes after biofortification, SFN acts as an additional mediator of consumer purchase intentions. Using ordered logistic regression analysis, we find that both food neophobias have a negative impact on consumer acceptance of biofortified foods. The results of Study 2 confirm our findings and further show that nutrition information moderates the mediation of NFN and SFN, i.e., the negative impact of NFN and SFN on purchase intentions can be reduced by providing nutrition information to consumers. The results of this study have several theoretical and practical implications and are of interest to stakeholders and marketers in the promotion of biofortified foods.

COVID-19 Pandemic, Determinants of Food Insecurity, and Household Mitigation Measures: A Case Study of Punjab, Pakistan.

Policies centered to respond to the COVID-19 pandemic have created recessionary economic impacts. Adverse income shocks have caused malnutrition and food insecurity and have increased the need for food assistance. The present study examines the impact of the COVID-19 pandemic on food insecurity and investigates the determinants of food security and coping strategies in the Punjab province of Pakistan. Data were collected through the internet and received responses from 370 respondents. The household food insecurity access scale (HFIAS) model was applied to examine food insecurity, and a logit regression model was used to analyze its determining factors. The results illustrate that food insecurity substantially increased during the COVID-19 pandemic. Households' demographics and socioeconomic factors have influence on food insecurity. Households with a large family size and people in quarantine found more food insecurity during the COVID-19 pandemic, while financial assistance played a role in a decline in food insecurity. Households handle the negative income shocks by eating less preferred food and getting support from government and charity organizations. It is suggested that stakeholders and responsible institutes provide financial assistance to support low-income families in order to enhance food security. Furthermore, policymakers should strengthen social safety nets and aid programs such as the Ehsas income program in the province of the country.

Donation or Discount: Effect of Promotion Mode on Green Consumption Behavior.

Environmental issues are still challenging and of global concern. To improve the environmental consumption behavior of consumers, this study investigates whether the match between the promotion mode and product type can improve the conceptual fluency of consumers, so as to increase their purchase intention for green products. The results of three experiments reveal that the interaction between promotion mode and product type has a certain impact on the conceptual fluency of consumers, which can, in turn, promote their purchase intention. This research theoretically contributes to the research on green consumption by introducing promotion mode and revealing the mediation effect of conceptual fluency, it also provides some practical implications for alleviating environmental problems.

Pathways and Associations between Women's Land Ownership and Child Food and Nutrition Security in Pakistan.

Women's land ownership plays a noteworthy role in improving various development indicators, including her own wellbeing and children's food and nutrition security. However, the literature linking women's access to land rights to the nutritional security of children in Pakistan is limited, even though it is a country facing enormous challenges of childhood malnutrition and gender discrimination. This paper contributes to the existing literature on the benefits of empowering women by studying the association and pathways between women's land rights and child nutrition, using the 2012-2013 Pakistan Demographic and Health Survey. The ordinary least squares (OLS) regression results indicate that women's individual land ownership and women's autonomy in large-scale family purchases have a positive impact on children's food and nutrition security (FNS). The results of quantile regression (QR) show that these effects are more pronounced in cases of children with severe stunted growth. In addition, a structural equation model shows that the positive relationship between women's land ownership and child nutrition is partially mediated by women's increased decision-making power in large-scale household purchases. Our research concludes that ensuring women's land rights can improve women's autonomy, which can be an effective policy tool that not only improves women's welfare but also improves their children's nutritional security.

Can the informal groundwater markets improve water use efficiency and equity? Evidence from a semi-arid region of Pakistan.

Pakistani farmers are using groundwater at an increasing rate to supplement their irrigation needs. This practice has led to overexploitation of groundwater in the country, resulting in many negative externalities and increased resource costs. In response to the growing water shortage, the informal groundwater markets in the arid and semi-arid regions of Punjab have gradually emerged. These markets are believed to improve the fair distribution of groundwater and encourage more efficient use of agricultural water. This study aims to investigate these claims through conducting a field survey of 120 farmers that are further divided into three groups i.e. buyers, self-users cum sellers, and self-users (control group). Further, the study employed a Data Envelopment Analysis (DEA) approach to estimate the water use efficiency of all three type of groundwater actors. The study findings show that water buyers are mostly small farmers who do not own tube wells, hence buy water from tube well owners (large farmers). The study also found that groundwater markets improve the equity of water access to some extent, as water is transferred from large farmers to small farmers. The results of DEA analysis show water buyers and water sellers are more efficient in using water than the control group, making buyers the most efficient of all groups. Therefore, participation in water markets appears to be improving the WUE of farmers. The results of single bootstrapped truncated regression show that participation in water markets and access to extension services can improve WUE, while off-farm income and the diesel tube wells can reduce WUE in the study area. However, government could play an important role here through introducing groundwater regulations and improving water use efficiency for sustainable and equitable distribution of water among water users.