Is there help indeed, if there is help in need? The case of credit unions during the global financial crisis(with Andre Guettler, Mahvish Naeem, and Bernardus Van Doornik), Economic Inquiry 59, no. 3 (2021): 1215-1233.

Credit unions (CUs) may respond to a financial shock differently than other types of banks because of their unique membership-based governance structure. We exploit the financial crisis of 2008/09 as a negative shock to Brazilian banks and analyze the lending behavior of CUs in comparison to non-CUs and the subsequent effects on the commercial clients' labor force. We find that during the financial crisis, CUs tightened their members' access to credit to a lesser extent (insurance effect) than did other bank types. Notably, the labor market impact of the insurance effect of CUs is positive for very small firms.

Conflict and the nature of precautionary wealth(with Rishabh Sinha and Ahmed Rostom), Oxford Economic Papers, Volume 74, Issue 2, April 2022, Pages 567–593.

This article examines the accumulation of precautionary wealth in Afghanistan using detailed data from a large household survey. A percent increase in income variance is associated with a 0.22 and 0.84% increase in broad and narrow wealth, respectively. This precautionary response is most pronounced at the extremes of wealth distribution. Wealthy households rely exclusively on livestock, while less affluent use jewelry for self-insurance. Conflict amplifies the precautionary motive, with households in high-conflict provinces reporting higher wealth at the same level of uncertainty. An increase in conflict intensity is also associated with an expansion of livestock weight in the asset portfolio.

Credit cycles in countries in the MENA region- Do they exist? Do they matter?(with Ahmed Rostom), Global Economy Journal, Vol. 2, No. 01, 2050001 (2020).

This paper estimates the private sector credit cycles for most of the oil-importing and oil-exporting countries in the Middle East and North Africa. Credit cycles are the medium-term component in spectral analysis of real private sector credit growth. Besides, the paper estimates the credit cycles for several developed countries. The analysis finds substantial differences and rare similarities between credit cycles in the Middle East and North Africa and advanced countries. During 1964–2017, credit cycles in the Middle East and North Africa do not appear to be associated with GDP growth. They only explained a fraction of the growth in private sector credit, and they do not seem to be synchronized across oil-exporters and oil-importers.

The Transmission of Real Effects of Monetary Policy: Evidence from Brazil (with Sophia Chen, Deniz Igan, Bernardus Van Doornik)

We investigate the role of government credit on monetary policy transmission using detailed credit registry data from Brazil. We find that government direct lending effectively facilitates the transmission of monetary policy through credit to small and medium enterprises. However, in- direct lending introduces complexities, notably cross-subsidization between earmarked and non- earmarked credit, impacting loan interest rates and their responsiveness to monetary policy shifts. We uncover distinct effects across loan segments and asymmetries during monetary policy easing and tightening. These insights inform policymakers about the impacts and trade-offs associated with government credit.

JEL: E44, E51, E52, E58, G21, G28

Keywords: Monetary policy, Government banks, Government direct credit, Earmarked credit, Emerging market, Brazil

From Cooperative to Digital and Back: The Symbiosis of Credit Unions and Fintech

Credit Unions (CUs) have long served as pillars of financial inclusion, offering tailored financial services to communities often underserved by traditional banks. As the financial landscape evolves with the rapid rise of financial technologies (fintech), this paper argues for a symbiotic relationship between CUs and fintech innovations. The integration of AI, blockchain, and digital banking solutions presents unprecedented opportunities to enhance the stability, transparency, and inclusivity of CUs. However, realizing this potential requires forward-thinking policy frameworks, public-private partnerships, and a commitment to digital literacy. This paper provides a comprehensive analysis of how CUs can leverage these technologies to remain competitive while continuing to fulfill their mission of community empowerment. Policymakers play a crucial role in facilitating this mutually beneficial relationship, ensuring that CUs can harness the power of fintech while preserving their core mission of serving their communities.

JEL Classification: G21, G28, O33,
Keywords: Credit Unions, Financial inclusion, Fintech, Innovations, Technology Adoption

The Impact of AI on Consumer Protection in the Financial Sector: Risks, Opportunities, and Regulatory Challenges

This paper explores the impact of artificial intelligence (AI) on consumer protection within the financial sector. As AI technologies are increasingly integrated into financial services, they offer numerous opportunities for enhancing consumer experiences and operational efficiencies. However, these advancements also bring significant risks and challenges that need to be addressed to protect consumers effectively. The paper examines the benefits of AI in financial services, such as improved fraud detection, personalized financial advice, and streamlined customer service. It also analyzes the risks, including data privacy concerns, algorithmic biases, and the potential for increased financial exclusion. Additionally, the study reviews current regulatory frameworks and proposes policy recommendations to ensure that AI-driven financial services are safe, fair, and inclusive. By providing a comprehensive analysis of the impact of AI on consumer protection, this paper aims to contribute to the development of effective regulatory strategies that balance innovation with consumer safeguards.

JEL Classification: C63, D12, I32
Keywords: Artificial Intelligence, Pricing Models, Social Inclusion, Essential Services, Marginalized Communities

Sustainable Economic Development through Green Tech: A Policy Framework

The increasing global focus on sustainable development has spurred interest in the role that green technologies can play in driving economic growth while achieving environmental targets. This paper explores how investments in green technologies—such as renewable energy, energy-efficient data centers, smart grids, and carbon-neutral infrastructure—contribute to Gross Domestic Product (GDP) growth and support Sustainable Development Goals (SDGs). Through case studies and econometric analysis, the paper evaluates the economic impact of transitioning from traditional infrastructure to green tech solutions in both developed and emerging markets. It highlights the importance of public-private partnerships, policy incentives, and regulatory frameworks in facilitating this transition. The findings demonstrate that strategic investments in green technologies not only enhance long-term economic resilience but also promote inclusive growth by creating jobs and reducing environmental risks. The paper concludes by providing a policy framework for governments and corporations to align their economic development goals with sustainability imperatives, ultimately contributing to a greener and more prosperous future.

JEL Classification: Q44, G13, Q42, O13, H23.
Keywords: Green Technology, Sustainable Economic Development, Public-Private Partnerships, Economic Resilience.

Predictive Models for Assessing the Economic Impact of AI on Regional Economies

The advent of artificial intelligence (AI) is reshaping industries, labor markets, and economic growth trajectories globally. This paper develops predictive models to assess the economic impact of AI adoption on regional economies, focusing on key metrics such as Gross Domestic Product (GDP), employment, and productivity. The study analyzes how AI-driven automation and innovation affect different sectors, with particular attention to the variation in outcomes across developed and emerging markets. By leveraging econometric and machine learning techniques, the paper provides forecasts on how AI technologies are likely to influence economic growth, workforce dynamics, and regional competitiveness over the next decade. The findings demonstrate that while AI can drive significant productivity gains and GDP growth, its impact on labor markets may differ across sectors and geographies, necessitating targeted policy interventions. This paper concludes by offering recommendations for policymakers and businesses on how to harness the economic benefits of AI while mitigating potential social and economic disruptions.

JEL Classification:O33, R11, C53, J23, O47, O14

Keywords: Artificial Intelligence, Economic Impact, Predictive Modeling, Regional Economies, GDP Growth, Labor Markets, Productivity, Automation, Policy Interventions, Economic Forecasting