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The international spillover effects of US Quality of Political Signals: A Global VAR approach
No full textWe investigate the influence of US quality of political signals (USQPOLS) on advanced and emerging markets using the Global Vector Autoregressive (GVAR) model that also accommodates the macroeconomic conditions of the shock recipient markets. We show an immediate negative impact on the equity markets with about 1.5% response to a 1 standard deviation shock due to the USQPOLS. However, we find impulse responses that transcend the immediate period for the high and low quality of political signals, albeit with contrasting evidence. Additional evidence involving Global Economic Policy Uncertainty (GEPU) suggests a direct and instantaneous effect on real equity prices. We are able to trace our evidence to the exchange rate channel and document important implications for policy and practice
Développement financier et réduction des inégalités de revenus en Côte d’Ivoire : une approche par la régression quantile
No full textThis study assesses the effect of financial development on income inequality in Côte d'Ivoire, using a multidimensional indicator of financial development that incorporates financial inclusion. We use ARDL and quantile regression methods to regress income inequality (measured by the Gini index) on the indicator of financial development and various control variables over the period 1986-2018. The results show that the financial development indicator only reduces income inequality in the short term. In the long term, it increases them at all quantiles, with a more accentuated effect in the upper quantiles than in the lower quantiles. This counter-intuitive result is explained by the lesser orientation of financial inclusion towards income-generating activities. The study recommends the following measures: link financial inclusion and income-generating activities and strengthen platforms aimed at reducing information asymmetry between borrowers and lenders
Home Production and Gender Gap in Structural Change
No full textWe document that the gender gap in non-agricultural work in developing countries exists primarily among rural married workers, not singles. Married women spend more time on home production, making them less likely to pursue non-agricultural employment. We extend a general equilibrium Roy model to incorporate the joint labor supply decisions of rural married couples, accounting for gender-specific labor distortions and entry barriers to non-agriculture. Calibrating the model to China, we find that the gender gap in non-agricultural employment can be largely explained by gender differences in home production and labor market distortions. Furthermore, within-household specialization among married couples greatly amplifies the effects of gender-specific labor distortions, and changes in entry barriers to non-agriculture widened the gender gap in China between 2000 and 2010. Enhancing public services such as childcare facilities can effectively induce more married women to work in non-agriculture. Extrapolating our model globally, it explains a quarter of the variation in the gender gap across countries
Blockchain-based E-commerce: It’s an Evolution, NOT a Revolution -- Experimental Evidence from Users’ Perspective
No full textProponents of blockchains believe that this technology will revolutionize e-commerce. To evaluate this belief, we invite several groups of students to transact on a decentralized peer-to-peer marketplace built on the platform provided by Origin Protocol Inc., and then we conduct a survey about their experience of usage. Based on our survey results, we find that 33% of respondents play tricks on others, which implies that this undesirable result may hinder the widespread adoption of blockchain technologies. We also attempt to propose a conceptual mechanism to mitigate fraudulent behaviors. In the event of disputation, a trusted authority is entitled to the right to downgrade the fraudulent side’s credit record, which is stored by a permissioned blockchain accessed only by the authority. Such a punishment can effectively decrease agents' incentives to sell counterfeits and leave fake ratings. In sum, we must distinguish what we proposed blockchains will do and what blockchains can do before enabling this technology in e-commerce
The short-term effects of gasoline price subsidy removal in Nigeria: an analysis of the economic and social Impacts
No full textThis study examines the immediate consequences of gasoline subsidy removal in Nigeria, focusing on economic and social outcomes. Utilizing monthly data from the 2000 to 2024 subsidy removals, the study analyzes inflation trends, transportation costs, public sentiment, and fiscal adjustments. It also estimated via econometrics model, the short-term partial effects of gasoline price subsidy removal on transportation costs and aggregate consumer prices. Findings reveal significant inflationary pressures, social unrest, and disproportionate impacts on low-income households, alongside modest fiscal gains. The study underscores the need for compensatory measures to mitigate short-term shocks. The conclusion is that the removal of gasoline subsidies in Nigeria is a double-edged sword with significant short-term implications. While it offers potential benefits such as reduced fiscal burden, improved government finances, and long-term economic reforms, it also poses immediate challenges, including increased inflation, higher transportation costs, and potential social unrest. The success of this policy will depend on the government’s ability to manage the transition effectively, implement complementary measures to cushion the impact on the populace, and ensure that the long-term benefits outweigh the short-term pain
Adjusted principal component estimation for binary factor model
No full textIn economic decision-making, the binary factor model is widely employed to characterize decision processes and capture individuals' exposures to various factors. This paper reveals that when the binary response is factorized, additional factors emerge, including an augmented time-invariant item that can lead to overestimation of the individual effect. These findings explain why
the principal component method often produces misleading estimates when applied to binary data. To address this issue, we develop an adjusted principal component (APC) method, which modifies the eigenvalue ratio test to determine factor numbers, estimates factors in the transformed model, and recovers estimates for the original binary model. It avoids parametric error distribution specifications and initial value selection, overcoming limitations of existing iterative methods. Extensive Monte Carlo experiments
confirm APC's robustness. We then apply APC to analyze dividend initiation factors using S&P 500 data (1998-2016), demonstrating its practical effectiveness
An Elementary Approach to GPIF Investment Allocation Optimization: A Basic Risk-Return Evaluation Perspective
No full textThis report examines a portfolio optimization methodology based on the investment allocation approach adopted by the Government Pension Investment Fund (GPIF). Employing quadratic programming, we derive optimal investment allocations for Japan, developed countries (excluding Japan), and emerging markets by incorporating market growth rates and variances. The analysis offers valuable insights into enhancing portfolio performance through a balanced approach to expected returns and risk management
Solving Heterogeneous agent models in Continuous Time with Adaptive Sparse Grids
No full textThis paper proposes a new approach to numerically solving a wide class of heterogeneous agent models in continuous time using adaptive sparse grids. I combine the sparse finite difference method with the sparse finite volume method to solve the Hamilton-Jacobian-Bellman equation and Kolmogorov Forward equation, respectively. My algorithm automatically adapts grids and adds local resolutions in regions of the state space where both the value function and the distribution approximation errors remains large. I demonstrate the power of my approach in applications featuring high-dimensional state spaces, occasionally binding constraints, lifecycle and overlapping generations
Comparing two simulation approaches of an energy-emissions model: Debating analytical depth with policymakers’ expectations
No full textAs global commitments to decarbonization intensify, energy-emission models are becoming increasingly vital for policymaking, offering data-driven insights to evaluate the feasibility and impact of climate strategies. These models help governments design evidence-based policies, assess mitigation pathways, and ensure alignment with national and international targets, such as the Paris Agreement and the EU Green Deal. Researchers often spend a lot of time considering their modelling choices to develop the best possible tools in terms of data-requirements, accuracy, computational demand, while there is always a ‘debate’ of complexity versus explicability and ready-to-use models for policymaking. Especially for energy-emissions models, given their increasing policy-relevance, and the need to provide insights fast for short-term policies (e.g. 2030, or 2050 net-zero goals), such considerations become increasingly pressing. In this paper, we present two different versions of the same energy-emissions model, and we run them for the same study area, planning horizon, and scenario analysis. The two versions differ only in how they approach complexity: Version1 is a more ‘detailed’, complex model, while Version2 is a ‘simpler’ and less data-hungry one. A set of evaluation criteria was then used to qualitatively compare these two versions, based on modelling- and policymaking-related considerations, debating modelers’ and policymakers’ expectations and preferences. We reflect on best modelling practices, discuss different goal-dependent approaches, providing useful guidance for modelers and policymaker
Kosten von Zahlungsmitteln für Konsumenten: Literaturauswertung und Sensitivitätsanalysen
No full textPayment costs for consumers are difficult to determine, are not recorded in an internationally harmonised manner and vary significantly from country to country. They are incurred in many forms, for example as fees for account management, for cash withdrawals at ATMs or for payment cards; but also as financial damage in the event of loss or fraud. On the other hand, this also includes time costs, e.g. for cash withdrawals or the payment process, and costs of data disclosure. To determine the total costs and for international comparisons, different key figures are calculated, such as the cost per transaction, as a percentage of the transaction value or relative to GDP. After clarifying the concept of costs, the focus of our paper is on a critical review of the literature on cost studies at the consumer level. In particular, the results of existing work are compared, the most important cost categories are identified and sensitivity analyses are carried out. We find some key cost drivers and show how the results are driven by key assumptions