It's not who you know, but who you are: Explaining income gaps of stigmatized-caste business owners in India.

Scholars across disciplines and around the world have diverted research attention to rising income inequalities across groups and strategies to reduce them. The literature has broadly identified human capital and social capital as two potential tools to facilitate economic mobility and to reduce inequalities. However, it is not known whether these tools work equally well for stigmatized groups, particularly in societies with systemic inequalities. Analyzing data from a pan-India survey, we show that business owners from stigmatized groups (i.e., Dalits in India, who are stigmatized as untouchables) experience a business income gap of around 16% compared to others, including those business owners who are from communities that are disadvantaged but are not similarly stigmatized. We find that, instead of being reduced, this gap in fact increases at higher levels of social capital, especially bridging social capital, illustrating the social processes of stigmatization that limit the benefits that Dalits can reap from social capital. By contrast, Dalits can reap similar income benefits as others from human capital. Our results show that human capital helps stigmatized groups mitigate the implications of stigma, but social capital does not.

The impact of digital financial development on corporate leverage ratio: The case of a-share listed non-financial enterprises in China's Shanghai and Shenzhen stock exchanges.

This study investigates the impact of digital finance on corporate leverage ratios. The study employed a large sample of China's Shanghai and Shenzhen A-share non-financial listed enterprises from 2011-2020. The study's results depict that the development of digital finance can significantly reduce the leverage ratio of enterprises. We empirically identified that digital finance affects the difference in the term structure of the corporate leverage ratio. It was found that the development of digital finance has a significant negative impact on enterprises' short-term and long-term leverage ratios. Moreover, our heterogeneity analysis shows that the negative effect of digital financial development on corporate leverage ratios is different in state-owned and non-state-owned enterprises, large-scale and small-scale enterprises, and high-leverage and low-leverage enterprises. Mechanism analysis shows that the development of digital finance can reduce corporate leverage by lowering financing costs, alleviating financing constraints, and weakening non-systemic risks. Therefore, policymakers should focus on developing and adopting digital finance by creating a supportive regulatory environment, improving access to digital financial services, and encouraging innovation in the digital finance sector. Finally, our results remain robust after addressing endogeneity issues and conducting robustness checks.

Measurement and analysis of the distortion of factor prices in China.

This study uses the extended C-D production function method to measure the total distortion of factor prices and the distortion of capital, labor and land factor prices in China's provinces and cities. The results indicate that between 2000 and 2019, due to factors such as the dual economic structure between urban and rural areas, human intervention in the capital market, and lagging land marketization reform, both capital and land factor prices showed negative distortions, except for positive distortions in labor factor prices. The degree of this positive distortion began to gradually weaken, and even showed a negative distortion trend in some regions.

Dynamic impacts of public health events on price fluctuations in broiler industry Chain in China: Evidence from COVID-19 epidemic.

Using weekly data from January 2020 to December 2021 on the prices of various links in the Chinese broiler industry chain and the COVID-19 epidemic, we employed a time-varying parametric vector auto-regressive (TVP-VAR) model to investigate the dynamic effects of public health events on price fluctuations of upstream, midstream, and downstream products in the Chinese broiler industry chain. Our findings showed that the COVID-19 epidemic had different effects on the prices of various broiler products, both in direction and magnitude, at different lags and time intervals. Chicken and live chicken prices were impacted the most, followed by broiler chick prices, while broiler feed prices were impacted the least. The epidemic constantly impacted broiler chick and chicken prices, while its effect on live chicken prices was initially negative but turned positive afterwards. Additionally, the impact of the COVID-19 epidemic on broiler product prices consistently increased with more extended lag periods. The impulse responses at different epidemic time points were heterogeneous. With the results of this study, policy recommendations can be suggested to relevant government departments to optimize the prevention and control measures for public health emergencies and ensure price stability in the broiler industry.

Uncertainty in banking and debt financing of firms in Vietnam.

This study explores the effects of banking uncertainty on firms' debt financing. Employing data from 2007 to 2022 of Vietnam-a bank-based economy, we document that banking uncertainty negatively impacts corporate debt. The impact firmly holds across various debt maturities and sources, with the most predominant driver witnessed in bank debt. We also investigate the potential underlying mechanism linking banking uncertainty to debt financing, thereby validating the working of three crucial channels, including increased costs of debt, substitution of trade credit, and contractions in firm investment. Furthermore, conducting extended analysis, we find that debt financing exhibits more pronounced reactions to banking uncertainty for firms with closer ties to banks or during macroeconomic shocks, as captured by the financial crisis and the COVID-19 pandemic. Our findings survive after robustness checks by alternative measurement, static and dynamic econometric models, and endogeneity controls.

Short-term forecasting of vegetable prices based on LSTM model-Evidence from Beijing's vegetable data.

The vegetable sector is a vital pillar of society and an indispensable part of the national economic structure. As a significant segment of the agricultural market, accurately forecasting vegetable prices holds significant importance. Vegetable market pricing is subject to a myriad of complex influences, resulting in nonlinear patterns that conventional time series methodologies often struggle to decode. In this paper, we exploit the average daily price data of six distinct types of vegetables sourced from seven key wholesale markets in Beijing, spanning from 2009 to 2023. Upon training an LSTM model, we discovered that it exhibited exceptional performance on the test dataset. Demonstrating robust predictive performance across various vegetable categories, the LSTM model shows commendable generalization abilities. Moreover, LSTM model has a higher accuracy compared to several machine learning methods, including CNN-based time series forecasting approaches. With R2 score of 0.958 and MAE of 0.143, our LSTM model registers an enhancement of over 5% in forecast accuracy relative to conventional machine learning counterparts. Therefore, by predicting vegetable prices for the upcoming week, we envision this LSTM model application in real-world settings to aid growers, consumers, and policymakers in facilitating informed decision-making. The insights derived from this forecasting research could augment market transparency and optimize supply chain management. Furthermore, it contributes to the market stability and the balance of supply and demand, offering a valuable reference for the sustainable development of the vegetable industry.

Quantifying economic vulnerabilities induced by interdependent networks.

Under economic globalization, countries are linked through trade and investments. This economic interdependence creates vulnerabilities. The indirect vulnerability induced by interdependent networks of trade and investments can put a country's economy at risk, but this risk has yet to be systematically quantified and investigated. In this paper, we developed the novel Potential Indirect Vulnerability Index (PIVI) to capture how interdependencies between networks of trade and foreign direct investment (FDI) may induce economic vulnerabilities. The model consisted of three main components: a target country (the importer of goods), an investing country (the exporter of FDI), and the intermediary countries that export commodities to the target country and receive FDI from the investing country, serving as conduits of the vulnerabilities caused indirectly by the investing country. The PIVI quantifies the indirect vulnerabilities based on the product of two fractions: 1) the dependency of the target country on commodities from each intermediary country; and 2) the dependency of each intermediary country on FDI from the investing country. We demonstrated the utility of PIVI by examining the US economy's vulnerability to China using 2019 trade and FDI data. Several Asian countries and a mix of agricultural products and raw materials were identified as conduits through which China could potentially influence the US economy. Vietnam was a sizeable risk because, while it has been a primary source of many US imports, it also received about 30% of its FDI from China. The US policy makers might opt to increase diversity in trade partners or to promote investment in countries such as Vietnam. We also applied the PIVI analysis to critical minerals, identifying cobalt, tungsten, and copper as the most vulnerability-inducing among them. PIVI is a flexible metric than can be aggregated and modified to provide a more nuanced and focused assessment of an economy's vulnerability.

Gender effects in crowdfunded business loan campaigns.

Crowdfunding is a growing source of finance for entrepreneurs. In this paper, we investigate the existence of a gender effect in the time needed to obtain a business loan through crowdfunding. Using data from three Dutch crowdfunding platforms, survival analysis of the time to completion for 934 business loan campaigns shows that female entrepreneurs have a 20% shorter campaign completion time compared to male entrepreneurs, whereas couples do not differ from males. This effect persists across the different platforms. Subsequent analysis shows that female entrepreneurs do not have the disadvantage they face in traditional lending channels when requesting funds through crowdfunding, and that herding behavior by investors benefits female entrepreneurs most.

Pricing strategies for shared manufacturing platform considering cooperative advertising based on differential game.

Shared manufacturing is a new business form that focuses on all aspects of production and manufacturing, mainly relying on the shared manufacturing platform to achieve the optimal allocation of idle resources. For enterprises, in the process of deciding to lease idle resources, the pricing and advertising investment efficiency of the shared manufacturing platform is a valuable research issue. The shared manufacturing model in this paper consists of one manufacturer and one shared manufacturing platform, which will invest in cooperative advertising while the shared manufacturing process is completed. The cooperative advertising involves four models: the traditional cooperation model, the cost-sharing contract model, the revenue-sharing contract model, and the bilateral cost-sharing contract model. We investigate the impact of some key parameters on the prices and profits of the manufacturer and the shared manufacturing platform based on the differential game. The numerical examples demonstrate the viability of the model. Finally, we provide suggestions based on the decision-making of the manufacturer and the shared manufacturing platform under different cooperative advertising models.

Granting analysis of the credit financing of the platform-type highway transportation supply chain.

Against the background of digital development, this study's research object is the platform-based highway transportation supply chain. It also analyzes two modes of supply chain financial credit financing, namely, upstream, and downstream enterprises of the platform, and network freight platform as the main financing body. Notably, the financial provider sets up a transaction credit based on the principle of business truth, and closed-loop transactions, determine the upper limit of the credit line based on the principle of financing self-compensation, build the expected profit maximization model, and establish the optimal credit line. Combined with the Highway Freight Index and Logistics Prosperity Index, the dynamic early warning value is established for the financing mode, where the platform as the main financing body. Through numerical analysis, the credit line and expected profit increase with the transaction credit, expected freight volume, and credit interest rate under the two modes, and the increase deriving from the credit interest rate is more significant. Finally, this paper describes the two-dimensional credit matrix of the financing subject via transaction credit and credit interest rate, which provides an intuitive credit reference for financial institutions to conduct the credit financing of the platform-based highway transportation supply chain.

Systemic risk spillover between the stock market and banking deposits: Evidence from a sustainability perspective in the South Asian countries.

This research explores the link between stock markets and banking deposits in South Asian (Pakistan, India, Sri Lanka, Nepal) countries. This study empirically examines the systemic risk potential of financial institutions in South Asia using current systemic risk statistics. Yearly data on stock prices and banking deposits from January 2000 to December 2020 were analyzed using a two-stage process. In the first phase, we measure VaR (value at risk), and in the second step, we measure the DCC GARCH model for our empirical analysis. The study findings reveal systemic risk spillover between the stock markets of South Asian countries and the relevant country's banking system deposits. The policymakers can use our study findings to create a more sustainable financial sector.

Da Vinci Medal Address: Material Political Economy.

On the occasion of the award of the author's da Vinci Medal in 2022, this article sketches a perspective, material political economy, employed by the author, explaining it by drawing on Marc Bloch's classic account of the dispute in European feudalism between milling grain on watermills or windmills controlled by feudal superiors, who could exact fees, and common people's use of hand mills. It considers the material political economy aspects of two modern technologies. The first is automated high-frequency trading in finance, where there are typically conflicts with incumbents and material efforts to favor "market-making" over "aggressive" algorithms. The second is the automated auctioning of digital display advertising opportunities, showing tension between two forms of these auctions' material organization: centralized auctioning via Google's systems and decentralized "header bidding."

Share pledge and accounting conservatism in share-pledging firms: Evidence from a natural experiment in China.

This paper focuses on firms in which insiders pledge their shares as collateral for loans. By investigating a natural experiment-China's enactment of provisions on share reductions that restrict pledge creditors' cashing-out behavior-we find that pledging firms exhibited more conservative financial reporting after the implementation than non-pledging firms. This effect was pronounced in firms with a higher ratio of pledged shares, a longer maturation period of the pledged shares, and more concentrated pledge creditors. Additionally, we show that pledging firms increased their accounting conservatism after the shock, leading to a lower risk of margin calls and stock price crashes. The effect on accounting conservatism was stronger in firms with controlling pledgers or when the pledge creditors were banks. Our results remained consistent after we performed several robustness tests. These behaviors are economically logical because the provisions heighten creditors' liquidity risk and the potential losses of loan default. Pledging shareholders embrace more accounting conservatism to mitigate creditors' concerns about agency costs and avoid triggering margin calls. Our findings provide direct support that creditors have a real demand for accounting conservatism and highlight the impact of shareholder-creditor conflicts on the financial reporting policies of pledging firms.

Modelling the impacts of volumetric and minimum unit pricing for alcohol on social harms in Australia.

AIMS: Alcohol pricing policies may reduce alcohol-related harms, yet little work has been done to model their effectiveness beyond health outcomes especially in Australia. We aim to estimate the impacts of four taxation and minimum unit pricing (MUP) interventions on selected social harms across sex and age subgroups in Australia. METHODS: We used econometrics and epidemiologic simulations using demand elasticity and risk measures. We modelled four policies including (A) uniform excise rates (UER) (based on alcohol units) (B) MUP $1.30 on all alcoholic beverages (C) UER + 10 % (D) MUP$ 1.50. People who consumed alcohol were classified as (a) moderate (≤ 14 Australian standard drinks (SDs) per week) (b) Hazardous (15-42 SDs per week for men and 14-35 ASDs for women) and (c) Harmful (> 42 SDs per week for men and > 35 ASDs for women). Outcomes were sickness absence, sickness presenteeism, unemployment, antisocial behaviours, and police-reported crimes. We used relative risk functions from meta-analysis, cohort study, cross-sectional survey, or attributable fractions from routine criminal records. We applied the potential impact fraction to estimate the reduction in social harms by age group and sex after implementation of pricing policies. RESULTS: All four modelled pricing policies resulted in a decrease in the overall mean baseline of current alcohol consumption, primarily due to fewer people drinking harmful amounts. These policies also reduced the total number of crimes and workplace harms compared to the current taxation system. These reductions were consistent across all age and sex subgroups. Specifically, sickness absence decreased by 0.2-0.4 %, alcohol-related sickness presenteeism by 7-9 %, unemployment by 0.5-0.7 %, alcohol-related antisocial behaviours by 7.3-11.1 %, and crimes by 4-6 %. Of all the policies, the implementation of a $1.50 MUP resulted in the largest reductions across most outcome measures. CONCLUSION: Our results highlight that alcohol pricing policies can address the burden of social harms in Australia. However, pricing policies should just form part of a comprehensive alcohol policy approach along with other proven policy measures such as bans on aggressive marketing of alcoholic products and enforcing the restrictions on the availability of alcohol through outlet density regulation or reduced hours of sale to have a more impact on social harms.

Impact of RMB internationalization on China's competitiveness in financial services trade based on the VAR model: Evidence from China-US.

An increase in a currency internationalization levels can positively impact its credibility in international economic activities, and expand the effective demand and optimize the supply structure for the country's financial service trade. In this way, a state can improve its financial service trade competitiveness in the international market. This study builds a vector autoregressive model based on time-series data of China-US financial services trade from 2010 to 2021, analyzes the impact of different quantitative indicators of RMB internationalization on this trade from the impulse response results, and validates the conclusions using various inspection methods. The results show that the increase in RMB internationalization helps to narrow the China-US financial services trade balance, but with a significant lag. And this effect is heterogeneous in different dimensions, demonstrated by the fact that the development of overseas RMB securities business is more important for the level of RMB internationalization to narrow the China-US financial services trade balance. Finally, among the specific measures to improve its financial services trade, China should focus on developing the international competitiveness of the traditional RMB deposit and loan financial sector, while the competition in the overseas market for high value-added financial businesses must also not be neglected. Furthermore, China needs to implement more targeted RMB internationalization development policies at different levels in the future to provide high-quality financial services to the rest of the world and aid in the economic recovery of the world in the "post-pandemic" era.

Allocation of the household food budget among shopping basket items: How is it influenced by promotions?

Retailers have been using promotion as a differentiation strategy that influences consumers' expenditures and their shopping basket budgetary allocation. This study assessed the effect of retail promotions on total shopping basket expenditure and determined whether promotions provoke a reallocation of the shopping budget. The analysis was performed on a chain of supermarkets in Catalonia, Spain using a consumer scanner data set from Kantar Worldpanel for 2017. The methodological approach had two steps: prediction of the effect of promotion on household expenditures using an expenditure regression model and estimation of the promotion own- and cross-effect using the censored Exact Affine Stone Index. Promotion had a positive own-effect and mostly a negative asymmetric cross-effect, implying a small but significant budget reallocation.

Can digital economy foster synergistic increases in green innovation and corporate value? Evidence from China.

The rapid evolution of the digital economy has significantly accelerated progress towards achieving green and sustainable processes, particularly in the field of green production. While existing research has delved into the effects of the digital economy on Green Innovation (GI) and the consequences of digital transformation on Corporate Value (CV), there remains a notable gap in the literature regarding the potential for synergistic enhancements in firms' GI&CV through the ongoing digital revolution. This study utilizes an evolutionary game model and employs system dynamics methods to simulate the dynamic evolution trajectory of the influence of the digital economy on the synergy between GI&CV. Subsequently, it empirically assesses the interconnected synergies between GI&CV using a dataset comprising information from Chinese listed firms spanning from 2011 to 2020, examining the impact of the digital economy on these synergies. Moreover, the study delves into the analysis of the transmission mechanism and conducts an extended investigation to further explore this phenomenon. The findings of this paper including: (1) The digital economy acts as a driving force behind the synergistic enhancement of firm GI&CV. Moreover, this effect is further augmented by governmental environmental regulation and green subsidy policies. (2) Drawing upon the information asymmetry theory and the resource-based theory, the regional marketization level and firms' digital transformation play intermediary roles. (3) The heterogeneity test indicate that firms situated in eastern regions and those classified as non-heavily polluted benefitted to a greater extent. This study sheds light on the incentive implications of digital economy for the synergistic upgrading of GI&CV, thereby extending the breadth of study on the consequences of digital economy. Moreover, it offers actionable suggestions for enterprises to leverage digital economy development towards achieving a synergistic improvement of GI&CV.

Factor-GAN: Enhancing stock price prediction and factor investment with Generative Adversarial Networks.

Deep learning, a pivotal branch of artificial intelligence, has increasingly influenced the financial domain with its advanced data processing capabilities. This paper introduces Factor-GAN, an innovative framework that utilizes Generative Adversarial Networks (GAN) technology for factor investing. Leveraging a comprehensive factor database comprising 70 firm characteristics, Factor-GAN integrates deep learning techniques with the multi-factor pricing model, thereby elevating the precision and stability of investment strategies. To explain the economic mechanisms underlying deep learning, we conduct a subsample analysis of the Chinese stock market. The findings reveal that the deep learning-based pricing model significantly enhances return prediction accuracy and factor investment performance in comparison to linear models. Particularly noteworthy is the superior performance of the long-short portfolio under Factor-GAN, demonstrating an annualized return of 23.52% with a Sharpe ratio of 1.29. During the transition from state-owned enterprises (SOEs) to non-SOEs, our study discerns shifts in factor importance, with liquidity and volatility gaining significance while fundamental indicators diminish. Additionally, A-share listed companies display a heightened emphasis on momentum and growth indicators relative to their dual-listed counterparts. This research holds profound implications for the expansion of explainable artificial intelligence research and the exploration of financial technology applications.

Procurement practices and value for money in State Corporations in Kenya.

Public procurement related expenditure is approximately fifty to seventy percent of the national budget of developing countries and accounts for almost a third of the gross domestic product. Cognizant of the significant funds committed in public procurement, the quest for value for money is critical. This study sought to determine the effect of procurement practices on value for money in State Corporations in Kenya. Specifically, the study investigated the effect of procurement planning, supplier sourcing, supplies management and E-procurement on value for money. Data collected from 87 State Corporations in Kenya was used in this study. The results of the study indicated that procurement planning, supplier sourcing, supplies management and e-procurement positively and significantly affect the value for money in state corporations in Kenya. The study concluded that proper procurement practices positively and significantly affect the value for money in state corporations in Kenya. The findings of this study contributes to literature by providing an empirical examination on the impact of procurement practices and value for money from a developing country perspective.