Where to Look for the Morals in Markets?

Markets are ubiquitous in our daily life and, despite many imperfections, they are a great source of human welfare. Nevertheless, there is a heated recent debate on whether markets erode social responsibility and moral behavior. In fact, competitive pressure on markets may create strong incentives for unethical practices (like using child labor) to increase competitiveness. While markets have been considered as detrimental for moral behavior, it has turned out a challenging task to identify where moral behavior is reflected in a market. Recent work has suggested that falling prices in markets with externalities are an indicator of declining morals. Here we examine the relation between trading volume, prices and moral behavior by presenting an experimental study where we let buyers and sellers interact on a double auction market. In one set of treatments, concluding a trade has no externality; in the other set, there is a negative externality by voiding donations for a potentially life-saving measles vaccine to UNICEF. We find that moral behavior reveals itself in lower trading volume in markets with an externality, but that market prices are hardly different between markets with or without an externality. We also vary the number of buyers and sellers and show that prices depend mainly on the relative number of buyers and sellers, but not on the existence of an externality. Hence, the market forces of supply and demand work equally well in determining prices whether or not trading has an externality

Where to Look for the Morals in Markets?

Markets are ubiquitous in our daily life and, despite many imperfections, they are a great source of human welfare. Nevertheless, there is a heated recent debate on whether markets erode social responsibility and moral behavior. In fact, competitive pressure on markets may create strong incentives for unethical practices (like using child labor) to increase competitiveness. While markets have been considered as detrimental for moral behavior, it has turned out a challenging task to identify where moral behavior is reflected in a market. Recent work has suggested that falling prices in markets with externalities are an indicator of declining morals. Here we examine the relation between trading volume, prices and moral behavior by presenting an experimental study where we let buyers and sellers interact on a double auction market. In one set of treatments, concluding a trade has no externality; in the other set, there is a negative externality by voiding donations for a potentially life-saving measles vaccine to UNICEF. We find that moral behavior reveals itself in lower trading volume in markets with an externality, but that market prices are hardly different between markets with or without an externality. We also vary the number of buyers and sellers and show that prices depend mainly on the relative number of buyers and sellers, but not on the existence of an externality. Hence, the market forces of supply and demand work equally well in determining prices whether or not trading has an externality

Training Normalizing Flows from Dependent Data

Normalizing flows are powerful non-parametric statistical models that function as a hybrid between density estimators and generative models. Current learning algorithms for normalizing flows assume that data points are sampled independently, an assumption that is frequently violated in practice, which may lead to erroneous density estimation and data generation. We propose a likelihood objective of normalizing flows incorporating dependencies between the data points, for which we derive a flexible and efficient learning algorithm suitable for different dependency structures. We show that respecting dependencies between observations can improve empirical results on both synthetic and real-world data, and leads to higher statistical power in a downstream application to genome-wide association studies

Kernelized Normalizing Flows

Normalising Flows are generative models characterised by their invertible architecture. However, the requirement of invertibility imposes constraints on their expressiveness, necessitating a large number of parameters and innovative architectural designs to achieve satisfactory outcomes. Whilst flow-based models predominantly rely on neural-network-based transformations for expressive designs, alternative transformation methods have received limited attention. In this work, we present Ferumal flow, a novel kernelised normalising flow paradigm that integrates kernels into the framework. Our results demonstrate that a kernelised flow can yield competitive or superior results compared to neural network-based flows whilst maintaining parameter efficiency. Kernelised flows excel especially in the low-data regime, enabling flexible non-parametric density estimation in applications with sparse data availability

MixerFlow for Image Modelling

Normalising flows are statistical models that transform a complex density into a simpler density through the use of bijective transformations enabling both density estimation and data generation from a single model. In the context of image modelling, the predominant choice has been the Glow-based architecture, whereas alternative architectures remain largely unexplored in the research community. In this work, we propose a novel architecture called MixerFlow, based on the MLP-Mixer architecture, further unifying the generative and discriminative modelling architectures. MixerFlow offers an effective mechanism for weight sharing for flow-based models. Our results demonstrate better density estimation on image datasets under a fixed computational budget and scales well as the image resolution increases, making MixeFlow a powerful yet simple alternative to the Glow-based architectures. We also show that MixerFlow provides more informative embeddings than Glow-based architectures

The economic consequences of a Tobin tax: An experimental analysis

The effects of a Tobin tax on foreign exchange markets have long been disputed. We present an experiment with currency trading on two markets, where either none, one, or both markets are taxed. Our results confirm the hitherto undisputed issues: a tax reduces trading volume, shifts market share to untaxed markets, and leads to negligible tax revenues if tax havens exist. Concerning the controversial issues we find that (i) volatility effects depend on the existence of tax havens and on market size, (ii) market efficiency remains unaffected by the tax, (iii) short-term speculation is reduced, and (iv) the tax has persistent effects even after its abolishment

Mental accounting of income tax and value added tax among self-employed business owners

Mental accounting describes a series of cognitive operations that help organize financial activities and facilitate money management. Self-employed taxpayers who make use of a separate mental account for future income tax payments or collected value added tax (VAT) might find it easier to declare their taxes correctly than taxpayers who do not. This study used a questionnaire to investigate whether self-employed taxpayers (N = 350) use mental accounting to manage their income tax and VAT obligations, whether mental accounting relates to tax knowledge, business and personality characteristics, and to what extent mental accounting is related to intended tax behavior. Our results reveal that some taxpayers mentally segregate taxes from turnover (segregators) while others do not (integrators). We found small differences in mental accounting between income taxes and VAT. Moreover, confirmatory factor analyses suggested that tax knowledge and mental accounting are distinct constructs. Segregation of taxes was related to lower impulsivity and more positive attitudes toward taxation. Individuals who stated they segregate taxes due from turnover more often claimed to run financially prosperous businesses. Mental accounting was not related to intentions of evading taxes, but individuals with higher mental accounting scores reported more pronounced levels of tax planning. While our research design does not allow drawing causal inferences, these findings could suggest that increasing self-employed taxpayers’ ability to organize their financial activities might be a promising strategy to strengthen the competitiveness of their businesses. Keywords: mental accounting, tax, income tax, VAT, tax complianc