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Abstract
The present paper attempts to demonstrate that finding an appropriate trade-off between direct and indirect taxes can help smooth policy makers' way through reconciling the contradictory notions of equity and efficiency. Our theoretical and empirical analysis is based on the assumption that direct taxes discourage work effort, thus impinging on the incentives to supply labour, to save and to invest, and finally, to grow, whereas indirect taxes discourage consumption and bear more heavily on the poor. Central to our discussion is the argument that carefully designed adjustments in the tax mix can reduce distortions in the consumption-leisure decision, thus leading to an optimal allocation of resources between the equity and efficiency objectives. To derive a competitive equilibrium setting, a social welfare function is maximized and the first-order conditions are manipulated to trace out the optimal direct-indirect tax rates that pave the way for the equity-efficiency goals to be reconciled with each other.

AbstractWe investigate the reengineeering of interbank networks with a specific focus on capital increase. We consider a scenario where all other components of the network's infrastructure remain stable (a practical assumption for short-term situations). Our objective is to assess the impact of raising capital on the network's robustness and to address the following key aspects. First, given a predefined target for network robustness, our aim is to achieve this goal optimally, minimizing the required capital increase. Second, in cases where a total capital increase has been determined, the central challenge lies in distributing this increase among the banks in a manner that maximizes the stability of the network. To tackle these challenges, we begin by developing a comprehensive theoretical framework. Subsequently, we formulate an optimization model for the network's redesign. Finally, we apply this framework to practical examples, highlighting its applicability in real-world scenarios.

AbstractThe standard methodology on tax‐effort (i.e., the ratio of actual tax revenue to its optimal level) is to run a regression of actual tax revenue on countries' specific (macroeconomic, demographic, geographical, political, social, and institutional) variables. The resulting predicted (fitted) values are then taken to represent the optimal (desired or maximum) level of tax revenue. The crucial issue of tracing out how the optimal tax revenue should be allocated to the fiscal objectives (equity, efficiency) does not seem to be of any interest to the researchers on tax‐effort. The present paper argues that the standard methodology is not without faults and needs revising. We demonstrate that an optimal tax system can be safely derived from maximizing a utility function with respect to (in)direct tax rates. The manipulation of the first‐order conditions, using a novel mathematical module, leads to an infinite number of optimal direct–indirect tax rates. The selection of the optimal mix of these tax rates is dependent on the country‐specific households' preferences over equity/efficiency, as they are formulated by voters' volition in election periods. A simulation procedure helps understanding how the optimal tax revenue is chosen and how it can be optimally allocated to fiscal objectives, in the context of a panel data set including a large number of developed and developing countries. Throughout our text, the optimal tax revenue is defined as the sum of the products of the optimal (in)direct tax rates and their corresponding tax bases. In the simple Arrow–Debreu economy, the above sum is shown to be equal to the difference between income and consumption.

AbstractThis paper studies an agent‐based model of consumer demand. Agents are heterogeneous with respect to their preferences and incomes. There are two basic ingredients in the model. The first ingredient is a metric that captures the degree of heterogeneity between agents. The second ingredient is a serial computer algorithm that is used in order to compute a terminal consumption bundle at which income is exhausted and overall utility is maximized. Agents are clustered into heterogeneous groups based on their preferences and incomes. We extract information about the evolution of consumer expenditure under different price regimes and the buildup of optimal demand for varying levels of income and preference parameter values. These features cannot be obtained in the classical framework of static utility maximization. Our agent‐based data‐driven methodology can be applied to any relevant data set and so provide a reliable model for forecasting demand given some agent characteristics.