Since the establishment of neoclassical economics in the nineteenth century, there has been a debate in the economics profession over the role played by mathematics. Mathematics can add precision to discussion of real-world empirical problems in economics, but care needs to be taken when formalizing a problem to ensure that errors of translation are not made. Formalism allows one to be sure that a chain of reasoning is correct but applying conclusions back to an empirical science problem is fraught if an error of translation has been made. We illustrate such a difficulty in the context of Arrow’s impossibility theorem, specifically the mistranslation of the non-dictatorship condition. The notion of dictatorship entails causality, but causality does not correspond to the usage of the implication sign in mathematics or logic. We use the rules of logic to illustrate that the way that dictatorship is rendered mathematically in the impossibility theorem makes the existence of a dictator (or dictators) not only reasonable but likely.

Speeding up digital development and building "digital China" is an important strategic deployment of the "14th Five-Year Plan" and a concrete measure to promote the high-quality development of China's sports industry and national health. Based on provincial data in China from 2011 to 2019, an empirical model is used to analyze the relationship between digital construction, sports industry development and national health investment. The results show that digitalization is instrumental for sports industry development and the improvement of national health in China. Digitalization has promoted the healthy development of sports industry and national health by increasing the input of public science and technology.

This work investigates the strength and the pattern of linkages among the three markets of qualitatively differentiated milk (i.e., conventional, organic without heymilk, and organic with heymilk) in Austria using the flexible TVP-VAR frequency connectedness approach and information on prices from 2018 to 2023. The main empirical findings are: (a) Taken together, the markets have maintained a moderate degree of connectedness to each other.  (b) Price linkages have been frequency-dependent; much of the adjustments to incoming information have been completed within 3 months. (c) Connectedness has been asymmetric; the highest quality (organic with heymilk) has been a net transmitter of price shocks to organic without heymilk. (d) The intensity of connectedness has been time-varying; however, the internal structure of the market network (i.e., the net transmitters and receivers of price shocks) has remained fairly stable.

This study underscores the chronic issue of gender pay disparity that prevails across different STEM fields and educational qualification levels in Australia. Despite instances where women's incomes may align or even surpass men's, the broader pattern of inequality remains undeniable. The study advocates for targeted strategies to address gender pay gaps, particularly in fields like Engineering and Science, and emphasises the significance of cultivating inclusive work environments that recognise and reward contributions regardless of gender. This study serves as a critical call to action to rectify these inequities and promote a more balanced and equitable STEM landscape.

Reckless behavior by business leaders can be a systemic risk for individual firms and the economies in which the firms exist. We propose that a synthesis of behavioral economics, in particular prospect theory, and the study of psychopathy may help researchers better understand why some business leaders engage in high-risk criminal activity. We propose that psychopathy is associated with an abnormal response to negative consequences. Where traditional Prospect Theory proposes that people are loss avoidant, we propose that people high on the trait of psychopathy may be more motivated by gains and will be risk seeking in high reward/high risk situations for which most people will avoid risk. We propose two empirical study designs that may be used to test the framework in the future.

Calculating the amount of regulatory capital to cover unexpected losses due to operational events in the upcoming year has caused problems because of difficulties in fitting probability distributions to data. It is consequently difficult to judge an appropriate level of capital that reflects the risk profile of a financial institution. We provide theoretical and empirical analyses to link the calculated capital to the sum of losses using appropriate statistical approximations. We conclude that, in order to reasonably reflect the associated risk, the capital should be approximately half the sum of losses, with a wide bound for the ratio of capital to sum.

China's carbon emission trading market has been formally established, but few studies have been conducted to analyze the impact of this policy on the regional urbanization level. Therefore, this paper evaluates whether the carbon trading pilot policy can enhance the regional urbanization level in China through the difference-in-differences method and analyzes the mediating role of industrial structure upgrading in this process. The results prove that the carbon trading market policy can accelerate the transformation and upgrading of industrial structure in the region so that it promotes the development of regional urbanization. Moreover, the effects of the policy are concentratedly manifested in the eastern region of China.

Vector Error Correction Models (VECM) have become a standard tool in empirical economics for analyzing nonstationary time series data because they integrate two key concepts in economics: equilibrium and dynamic adjustment in a single model. The current standard VECM procedure is limited to time series data with the same degree of integration, i.e., all I(1) variables. However, empirical studies often involve time series data with different de‐grees of integration, necessitating the simultaneous handling of I(1) and I(0) time series. This paper extends the standard VECM to accommodate mixed I(1) and I(0) variables. The conditions for the mixed VECM are derived, and consequently, we present a test and estimation for the mixed VECM.

I present a theoretical model and an empirical approach for jointly estimating the effectiveness of fiscal policy and the stochastic process of sovereign interest rate shocks. The theoretical model has features relevant to small open and emerging economies. Interest rate shocks affect the ability of firms to finance payroll expenses. This theoretical feature creates a propagation mechanism for interest rate shocks and affects government spending multipliers. This paper proposes a strategy for jointly estimating government spending multipliers and the interest rate shock process parameters.

The vigorous development of the digital economy has brought new opportunities and challenges to the construction of local fiscal revenue efficiency. Based on the panel data from 2011 to 2020, this paper uses the fixed effect model, instrumental variable method and other empirical studies to investigate the impact of the development of the digital economy on the efficiency of local fiscal revenue. The research results show that the development of the digital economy has directly improved the efficiency of local fiscal revenue, and the regression results of instrumental variables are still significant. The mechanism analysis shows that the development of digital economy mainly promotes local fiscal revenue such as efficiency improvement by cultivating tax sources.

Energy Performance Certificates are a key tool for achieving energy efficiency in the building sector. The existence of this type of legislation provides incentives for the energy renovation of buildings, increases energy-efficiency investments, and improves social welfare. At the same time, informational asymmetries are mitigated and energy consumption is reduced. However, the decarbonization of the building sector might influence regional energy poverty, especially because the rural energy poor are more vulnerable to energy price increases than their urban counterparts. Empirical research on rural-urban differences and the effects of Energy Performance Certificates is urgently needed, given the rising fuel prices and vulnerabilities of the energy market.

This paper examines the link between informality and corruption, two interlinked phenomena that have negative impacts on economic development. The paper presents a neoclassical model simulation that illustrates how informality can drive corruption in the economy, emphasizing the incentives for corruption in an economy with informal and formal sectors. The model provides insights into the mechanisms that promote corruption and how policymakers can reduce it through formalisation. The paper reviews the existing literature on informality and corruption, highlighting the empirical evidence and theoretical models that support the relationship between the two. The research finds that countries with larger informal sectors tend to have higher levels of corruption. The study contributes to the ongoing debate on how to reduce corruption and promote formalisation, which are crucial for sustainable economic growth.

This study empirically examines the influence of corporate financialization on trade credit financing, focusing on non-financial companies listed in China's A-share market from 2010 to 2022. The results indicate that as corporate financialization increases, companies will obtain less trade credit financing. Further incorporating moderating factors like market position and financing constraints, we find that a higher market position effectively mitigates the negative impact of corporate financialization on trade credit financing, whereas higher financing constraints exacerbate the adverse effects of corporate financialization on trade credit financing. Additional analysis shows that corporate financialization negatively affects trade credit financing by crowding out main business performance and increasing operational risks. Moreover, corporate financialization more strongly inhibits trade credit financing in state-owned companies.

Foreign direct investment (FDI) is widely viewed as a key driving force behind China’s exceptional growth performance in the last four decades. This paper investigates several questions posed by China’s success in capturing gains from FDI. What explains that success? Can other countries replicate it, or is it unique to China? What lessons are from China for other countries? China indeed has advantages in attracting FDI such as huge market and cheap labor, the well-designed policy and strategy, however, seem to play more important role in the successful story. Our empirical estimates support on four hypotheses: FDI and GDP growth in China positively interact each other; FDI is helpful to China’s technological progress, FDI promotes China’s industrial development, and FDI stimulates China’s manufactured exports.

In this paper, a portfolio analysis is carried out using the Sharpe ratio to identify the optimal market portfolio. The measure of investment performance with a Sharpe ratio is compared to results obtained with bootstrapped resamples of the Sharpe ratio. The results indicate that the choice of the market portfolio is highly affected by the uncertainty regarding the estimation of the expected returns and the variance-covariance matrix between the returns, that is, the estimation risk associated with these parameters.

We quantify financial returns to backers in reward-based crowdfunding projects on Kickstarter and show that such investments provide profitable opportunities in addition to non-monetary benefits. The average unconditional annualized return is 11.5% and the average return on successful projects is 30%. Hence, backing money near the end of a campaign, when the probability of success is already high, is a profitable strategy. The most attractive is the Design category, where successful projects yield 73%, on average. Short-term projects are more profitable than long-term ones. Financial return is an important type of extrinsic motivation in reward-based crowdfunding, which has generally been neglected in academic literature. Reward-based crowdfunding outperforms other forms of crowdfunding and other common alternative investments.

The workforce participation rate, and hence the level of employment, for women in Pakistan is among the lowest in South Asia – standing at 25 percent in 2023. Conventional explanations attribute this to poor skills and cultural norms of families and society at large. Empirical work has established that low levels of education, and community attitudes regarding gender roles, hinder women's labor force participation. Ethnographic work suggests that household rules – family culture – on who makes decisions about opportunities for married women to work outside of the home for pay – profoundly impact female employment. This is due to the limited availability of data pertaining to explicit assessments of familial traditions that are pertinent to women's participation in the workforce beyond their domestic sphere. Drawing on data from the Pakistan Social and Living Standards Measurement Survey (PSLM): 2005-2006 – which provides information, from married women, on who in the family decides if they can work – we address this shortcoming in the literature. We find that in families where the decision lies clearly, and exclusively, in the hands of males, married women are 18-19 percent less likely to be employed than if the family culture is for married women – alone – to make this decision. Moreover, this is a much larger deterrent to work than poor education and residential location.

Cryptocurrencies have gained popularity over the past five to six years. Most recently, events like the FTX bankruptcy fueled the interest in regulation. Moreover, it is possible that the FTX event disrupting the cryptocurrency market was a factor in Silicon Valley Bank's failure. While several countries consider regulation, from soft regulation, like Japan, to more rigid standards, like the total ban in China, we study the effect of other news or events on cryptocurrency prices. This paper looks at historical closing prices for Bitcoin, the largest of the cryptocurrencies, and how prices react to various events. Then we focus on modeling the time series considering an 'event,' China's ban on cryptocurrency exchanges, using intervention analysis. We find that intervention analysis provides a reliable approach to quantifying the impact regulation may have on cryptocurrency pricing.

We examine the impact of environmental provisions in regional trade agreements (RTAs) on the environmentally harmful exports. Results show that environmental clauses in RTAs help reduce “dirty” exports, whereas RTA depth promotes exports. The exporting country may divert its polluting exports to its trading partner if it faces more environmental provisions with other countries.