In this paper, we present a review of tax research. We survey four main areas of the literature: (1) the informational role of income tax expense reported for financial accounting, (2) corporate tax avoidance, (3) corporate decision-making including investment, capital structure, and organizational form, and (4) taxes and asset pricing. We summarize the research areas and questions examined to date and what we have learned or not learned from the work completed thus far. In addition, we provide our opinion as to the interesting and important issues for future research.
Prior evidence that higher-quality financial reporting improves capital investment efficiency leaves unaddressed whether it reduces over- or under-investment. This study provides evidence of both in documenting a conditional negative (positive) association between financial reporting quality and investment for firms operating in settings more prone to over-investment (under-investment). Firms with higher financial reporting quality also are found to deviate less from predicted investment levels and show less sensitivity to macro-economic conditions. These results suggest that one mechanism linking reporting quality and investment efficiency is a reduction of frictions such as moral hazard and adverse selection that hamper efficient investment.
Service region design determines the geographic coverage of service networks, shaping long-term operational performance. Capital and operational constraints preclude simultaneous large-scale deployment, requiring expansion to proceed sequentially. The resulting challenge is to determine when and where to invest under demand uncertainty, balancing intertemporal trade-offs between early and delayed investment and accounting for network effects whereby each deployment reshapes future demand through inter-regional connectivity. This study addresses a sequential service region design (SSRD) problem incorporating two practical yet underexplored factors: a $k$-region constraint that limits the number of regions investable per period and a stochastic spillover effect linking investment decisions to demand evolution. The resulting problem requires sequencing regional portfolios under uncertainty, leading to a combinatorial explosion in feasible investment sequences. To address this challenge, we propose a solution framework that integrates real options analysis (ROA) with a Transformer-based Proximal Policy Optimization (TPPO) algorithm. ROA evaluates the intertemporal option value of investment sequences, while TPPO learns sequential policies that directly generate high option-value sequences without exhaustive enumeration. Numerical experiments on realistic multi-region settings demonstrate that TPPO converges faster than benchmark DRL methods and consistently identifies sequences with superior option value. Case studies and sensitivity analyses further confirm robustness and provide insights on investment concurrency, regional prioritization, and the increasing benefits of adaptive expansion via our approach under stronger spillovers and dynamic market conditions.
This study investigates the impact of Chinese energy loans on rural electrification in 68 emerging countries from 2001 to 2023, addressing a critical gap in understanding the role of external financing in alleviating energy poverty. Using country fixed-effect and System Generalized Method of Moments (S-GMM) models, the findings provide robust evidence that a 1 % increase in Chinese energy loans leads to an average increase of approximately 0.10 percentage points in rural electricity access. However, corruption significantly attenuates this relationship, underscoring the importance of institutional quality in mediating the impact of infrastructure outcomes. Drawing on development economics theory, the analysis demonstrates that Chinese energy loans help address capital and infrastructural deficits in rural areas by facilitating the expansion of national grids, promoting off-grid renewable solutions, and supporting critical energy infrastructure. Illustrative examples, such as the Kafue Gorge Lower Hydropower Project in Zambia and the Karuma Hydropower Project in Uganda, underscore the transformative potential of such investments. The study offers novel empirical insights into how Chinese financing contributes to Sustainable Development Goal 7 (universal energy access). Policy implications suggest that while Chinese energy loans are effective in improving rural electrification, complementary reforms in governance and transparency are essential to maximise their developmental impact.
Elizabeth Dadzie, Wilfried Kuissi-Kamdem, Marcel Ndengo
This paper investigates a robust optimal consumption, investment, and reinsurance problem for an insurer with Epstein-Zin recursive preferences operating under model uncertainty. The insurer's surplus follows the diffusion approximation of the Cramér-Lundberg model, and the insurer can purchase proportional reinsurance. Model ambiguity is characterised by a class of equivalent probability measures, and the insurer, being ambiguity-averse, aims to maximise utility under the worst-case scenario. By solving the associated coupled forward-backward stochastic differential equation (FBSDE), we derive closed-form solutions for the optimal strategies and the value function. Our analysis reveals how ambiguity aversion, risk aversion, and the elasticity of intertemporal substitution (EIS) influence the optimal policies. Numerical experiments illustrate the effects of key parameters, showing that optimal consumption decreases with higher risk aversion and EIS, while investment and reinsurance strategies are co-dependent on both financial and insurance market parameters, even without correlation. This study provides a comprehensive framework for insurers to manage capital allocation and risk transfer under deep uncertainty.
We examine optimal regulation of financial networks with debt interdependencies between financial firms. We first show that firms often have an incentive to choose excessively risky portfolios and overly correlate their portfolios with those of their counterparties. We then characterize how optimal regulation depends on a firm's financial centrality and its available investment opportunities. In standard core-periphery networks, optimal regulation depends non-monotonically on the correlation of banks' investments, with maximal restrictions for intermediate levels of correlation. Moreover, it can be uniquely optimal to treat banks asymmetrically: restricting the investments of one core bank while allowing an otherwise identical core bank (in all aspects, including network centrality) to invest freely.
Rinel Foguen Tchuendom, Dena Firoozi, Michèle Breton
Quantilized mean-field game models involve quantiles of the population's distribution. We study a class of such games with a capacity for ranking games, where the performance of each agent is evaluated based on its terminal state relative to the population's $α$-quantile value, $α\in (0,1)$. This evaluation criterion is designed to select the top $(1-α)\%$ performing agents. We provide two formulations for this competition: a target-based formulation and a threshold-based formulation. In the former and latter formulations, to satisfy the selection condition, each agent aims for its terminal state to be \textit{exactly} equal and \textit{at least} equal to the population's $α$-quantile value, respectively. For the target-based formulation, we obtain an analytic solution and demonstrate the $ε$-Nash property for the asymptotic best-response strategies in the $N$-player game. Specifically, the quantilized mean-field consistency condition is expressed as a set of forward-backward ordinary differential equations, characterizing the $α$-quantile value at equilibrium. For the threshold-based formulation, we obtain a semi-explicit solution and numerically solve the resulting quantilized mean-field consistency condition. Subsequently, we propose a new application in the context of early-stage venture investments, where a venture capital firm financially supports a group of start-up companies engaged in a competition over a finite time horizon, with the goal of selecting a percentage of top-ranking ones to receive the next round of funding at the end of the time horizon. We present the results and interpretations of numerical experiments for both formulations discussed in this context and show that the target-based formulation provides a very good approximation for the threshold-based formulation.
Abstract This study elaborates on the risk effects of corporate digital transformation (CDT). Using the ratio of added value of digital assets to total intangible assets as a measure of CDT, this study overall reveals an inverse relationship between CDT and revenue volatility, even after employing a range of technical techniques to address potential endogeneity. Heterogeneity analysis highlights that the firms with small size, high capital intensity, and high agency costs benefit more from CDT. It also reveals that advancing information infrastructure, intellectual property protection, and digital taxation enhances the effectiveness of CDT. Mechanism analysis uncovers that CDT not only enhances financial advantages such as bolstering core business and mitigating non-business risks but also fosters non-financial advantages like improving corporate governance and ESG performance. Further inquiries into the side effects of CDT and the dynamics of revenue volatility indicate that CDT might compromise cash flow availability. Excessive digital investments exacerbate operating risks. Importantly, the reduction in operating risk associated with CDT does not sacrifice the potential for enhanced company performance; rather, it appears to augment the value of real options.
History of scholarship and learning. The humanities, Social Sciences
The present study aimed to examine the effect of regulatory levels on industrial value-added growth, comparing the results between developed and developing countries. For this purpose, a nonlinear equation was estimated using the panel GMM method and the delta method for the period 2000–2019. The estimation results for a sample of 99 countries showed an inverted U-shaped relationship between regulatory variables and industrial growth. For approximately 67% of the observations, the regulatory level had increased, and its effect on industrial growth was positive and significant. In addition, the growth-maximizing regulatory level in the sample was estimated at 2.61 (on a scale of 0–10). Moreover, the findings made clear that the relationship between regulation and industrial growth in developed countries was fundamentally different from that in developing countries. Specifically, while the estimates for developing countries were consistent with those for the full sample and exhibited an inverted U-shaped pattern, no growth-maximizing regulatory level was observed for developed countries, which can be attributed to institutional differences between the two groups.IntroductionA main area of government intervention in the economy is the regulation aimed at promoting industrial development. The growing share of industry in the gross domestic product of industrializing countries highlights its special position in the world economy. Given the importance of government intervention and its capacity to play a regulatory role, a key question arises: to what extent have government regulatory institutions facilitated the process of industrialization, and to what extent have they created additional complexities for the industrial sector? Have the regulatory tools designed to support industrial policy contributed to industrial development, or have they instead led to industrial decline? Since government regulation has varying effects across countries, the present research is based on the hypothesis that an efficient level of regulation has a positive effect on industrial growth.Materials and MethodsRelying on the data from multiple countries, the empirical model used in this study was to examine the relationship between regulation and industrial growth, as presented in Equation (1):Growthi,t = 𝛼 + 𝛽1Regi,t + 𝛽2Reg2i,t + 𝛾Xi,t + 𝛼i + 𝜃t + 𝜀i,t (1)In Equation (1), Growthi,t represents the annual industrial growth rate, which is also used in the Industrial Competitiveness Index and thus reflects aspects of industrial development quality. Reg denotes the level of regulation, X is a matrix of control variables, and 𝜃 is the fixed effects. Moreover, i represents countries and t refers to time periods (2000–2019). Regarding the variables, international data from reputable institutions was selected to enable meaningful cross-country comparisons. Concerning the indicators, industrial value-added growth was taken from the UNIDO database. The regulation variable was derived from the Fraser Institute’s Economic Freedom Index, specifically from its subcomponents on credit market, labor market, and business (commercial) regulation. The Fraser dataset is the most widely used and internationally recognized measure of regulatory conditions. The Fraser Institute provides scores for more than 150 countries on a scale of 0 to 10, where higher values indicate less regulation. In the current study, the scale was reversed so that higher scores would reflect higher levels of regulation. Concerning the control variables, the economic freedom variable from the Fraser Institute and industrial value added per capita from UNIDO were employed. To test the hypothesis, the indicators were introduced and the maximum level of regulation was estimated through the Delta method. The baseline specification of the model was then estimated using the GMM approach in a dynamic panel structure, covering 99 countries over the period 2000–2019.Results and DiscussionAccording to the results, increasing the level of regulation generally had a positive effect on the growth rate of industrial value added. The findings indicated that regulation exerted a positive impact on industrial growth at lower levels, but its effect became negative at higher levels. In other words, maximum industrial growth occurred when regulation was relatively low, and increases in regulation up to the growth-maximizing point could have positive and significant effects on industrial value-added growth. However, once regulation exceeded the growth-maximizing level, its influence became negative. This highlights the importance of identifying the appropriate degree of regulation for guiding government intervention in the economy. The results also underscored the dual nature of regulation. Its effect on industrial value-added growth is not linear; rather, it follows a nonlinear pattern in which both positive and negative effects are possible—depending on the level of regulation. Thus, the expectation that government regulation will have a uniform effect across different contexts is unrealistic. Moreover, the findings reveal that the relationship between regulation and industrial growth differs between developing and developed countries. Thus, the expectation that government regulation will have a uniform effect across different contexts is unrealistic. Moreover, the findings revealed that the relationship between regulation and industrial growth differs between developing and developed countries. The inverted U-shaped relationship between regulation and industrial value-added growth suggests that discussions on regulatory reform require greater attention. A country with excessive regulation that seeks to enhance industrial growth should consider continuing regulatory reforms, but only to the extent that such reforms do not reduce growth relative to its current value.ConclusionThe results showed that the relationship between regulation and industrial value-added growth in developed countries differs fundamentally from that in developing countries. Specifically, while the findings for developing countries aligned with the results obtained from the full sample, the results for developed countries diverged significantly. In developed economies, the overall effect of regulation on industrial value-added growth is negative. This contrast can be attributed to differences in government capacity and the quality of market institutions. In countries with weaker institutions and lower administrative capacity, introducing certain regulatory mechanisms may actually be beneficial and can substitute for other missing capacities—a point emphasized by Mancur Olson in the theory of the market-augmenting government. It is also important to note that an over-regulated economy that attempts aggressive deregulation may encounter resistance from those who benefit from existing regulations and wish to preserve current rents. Therefore, the impact of regulation on industrial growth depends not only on the level of regulation itself but also on the extent of rent-seeking activity. When rent-seeking is pervasive, the diversion of resources away from productive activities in response to proposed regulatory changes reduces the likelihood that such reforms will successfully promote industrial growth.
Purpose: The production sector requires financial investment and high technology. One of the ways to deepen and increase the role of the capital market in financing and providing more attractiveness for the entry of domestic and foreign investors is policy making and adopting procedures for greater support. It is one of the rights of micro investors. Also, due to the increasing trend of globalization and international competition, it has advantages for local companies and can increase capital and market liquidity. But are local corporate governance systems affected by the scale of globalization and international competition? With the emergence of the knowledge-based economy, the issue of human capital has been considered as an important factor in creating competitive advantage and increasing the value of companies, which can affect the structure of corporate governance. For this purpose, this paper investigates the impact of economic openness (financial and trade) and human capital on the index of support for micro investors in developing countries using the panel GMM method during 2014-2021.Methodology: In order to analyze the effects of the international competition factors including the trade openness as well as the facilitation of capital inflow and outflow on protecting micro-investors index, the dynamic panel method (GMM SYS) has been used. The system estimator (GMM SYS) is actually an alternative to the GMM first-order difference estimator (GMM DIF). In this method, instrumental variables are used to eliminate endogeneity. Since it is very difficult to find a strong instrument that can cause reliable estimation, DIF and SYS estimators use the instrument available in the collection, i.e. the interval of the endogenous variable. It enters the model as the best instrument. It should be noted that there are two tests to ensure the validity of instrumental variables in GMM-based methods. The first is Sargan's test. In this test, the null hypothesis indicates the non-correlation of the means with the residue. Therefore, rejecting the null hypothesis confirms the validity of the results. Second, the correlation test of the residuals is AR(1) in the first order and AR(2) in the second order. In this test, the disturbance sentences should have first-order serial correlation AR(1) and not second-order serial correlation AR(2).Findings and discussion: The results showed that the expansion of trade relations as well as facilitating the entry and exit of capital helps to comply more with the standards of protection of micro-investors in developing countries, although the effect of trade openness is stronger. Meanwhile, the role of human capital (investment in human resources) in transferring spillover effects is undeniable. In other words, it can be said that improving corporate governance standards and supporting micro-investors in developing countries are affected by the scale of globalization and international competition (trade and financial), and human capital is important for knowledge transfer and productivity shocks. In addition, the development of the capital market in developing countries significantly reduces the representation problem between managers and micro-investors.Conclusions and policy implications: Acording to the results, the expansion of trade relations and the facilitation of capital entry and exit have made developing countries more attractive for foreign investors. Thus, domestic companies, to compete with foreign companies, would be motivated towards promotion of corporate governance standards and micro-investor protection. That means, local corporate governance systems are affected by the scale of globalization and international competition. It is noteworthy that exposure to international competition, although it has benefits for local companies and improves corporate governance standards, may create challenges for developing countries that must be addressed through frameworks. In such cases, strong supervision should be done. By facilitating the entry and exit of capital and the expansion of trade relationships, managers may prioritize short-term benefits over long-term sustainability. On the other hand, weak regulatory mechanisms in developing countries may make them unable to keep pace with the complexities of international markets, allowing companies to misbehave and reduce the quality of governance. Examining these challenges can be done in future research. Also, the role of human capital quality (investment in human resources) in transferring the spillover effects of corporate governance and as a moderating factor for the alignment of interests between managers and micro-investors is undeniable, which confirms the strategic policies of human resource management. In addition, governments should improve the stock market environment with strong institutional infrastructure in order to protect micro-investors and, thus, increase the confidence of foreign investors and provide incentives to increase cross-border investments in the host economies.
In this paper, we explore the economic, institutional, and political/governmental factors in attracting Foreign Direct Investment (FDI) inflows in the emerging twenty-four Asian economies. To examine the significant determinants of FDI, the study uses panel data for a period of seventeen years (2002-2018). The panel methodology enables us to deal with endogeneity and other issues. Multiple regression models are done for empirical evidence. The study focuses on a holistic approach and considers different variables under three broad areas: economic, institutional, and political aspects. The variables include Market Size, Trade Openness, Inflation, Natural Resource, Lending Rate, Capital Formation as economic factors and Business Regulatory Environment and Business Disclosure Index as institutional factors and Political Stability, Government Effectiveness, and Rule of Law as political factors. The empirical findings show most of the economic factors significantly affect FDI inflows whereas Business Disclosure is the only important institutional variable. Moreover, political stability has a significant positive impact in attracting foreign capital flow though the impact of government effectiveness is found insignificant. Overall, the economic factors prevail strongly compared to institutional and political factors.
We study an optimal investment problem that arises in the context of the vehicle-sharing system. Given a set of locations to build stations, we need to determine i) the sequence of stations to be built and the number of vehicles to acquire in order to obtain the target state where all stations are built, and ii) the number of vehicles to acquire and their allocation in order to maximize the total profit returned by operating the system when some or all stations are open. The profitability associated with operating open stations, measured over a specific time period, is represented as a linear optimization problem applied to a collection of open stations. With operating capital, the owner of the system can open new stations. This property introduces a set-dependent aspect to the duration required for opening a new station, and the optimal investment problem can be viewed as a variant of the Traveling Salesman Problem (TSP) with set-dependent cost. We propose an A* search algorithm to address this particular variant of the TSP. Computational experiments highlight the benefits of the proposed algorithm in comparison to the widely recognized Dijkstra algorithm and propose future research to explore new possibilities and applications for both exact and approximate A* algorithms.