Research 

Peer-Reviewed Publications

"Constructing Divisia Monetary Aggregates for the Asian Tigers" (with William A. Barnett & JongSoo Lee), Special Issue Editorial Board Members’ Collection Series: Journal of Risk and Financial Management, 2024 -  Link 

Abstract: This study constructs Divisia monetary aggregates for the “Asian Tigers”—Hong Kong (1999–2024), South Korea (2009–2024), Singapore (1991–2021), and Taiwan (2005–2024)—and assesses whether Divisia monetary aggregates explain nominal GDP better than simple-sum money. Our findings demonstrate that Divisia indices respond more sensitively to economic shocks. For Hong Kong and Taiwan, narrow Divisia money provides the best explanations for fluctuations in nominal GDP. Our results suggest that Divisia monetary aggregates can be beneficial for monetary policy analysis in these territories and underscore the importance of further research into the empirical performance of Divisia monetary aggregates in macroeconomic prediction. 

Working papers 

"Democratizing the Equity Premium: Progressive Investment Incentives During Disasters" (Job Market Paper, Under Review) - Link

Abstract: Economic crises amplify wealth divergence as constrained households liquidate assets while others with equity exposure capture recovery gains. Progressive investment subsidies can broaden equity market participation among vulnerable households by targeting the portfolio margin rather than just income. Using a heterogeneous-agent New Keynesian model with sectoral pandemic exposure, two-asset choice, and borrowing constraints calibrated to U.S. data, I analyze state-contingent transfers with 60:1 progressivity targeting low-income households in high-exposure sectors. The policy operates through three channels: relaxing liquidity constraints that prevent equity investment, insuring sector-specific income risk that induces flight to safe assets, and concentrating support when asset prices are depressed and risk premia are elevated. By enabling constrained households to maintain risky-asset positions precisely when expected returns are highest, the policy connects short-run stabilization to long-run wealth accumulation through portfolio reallocation. Bottom-quintile households increase equity participation and holdings substantially, demonstrating that well-timed, progressive transfers can democratize access to the equity premium.

"Analyzing GDP and Stock Market Dynamics" (Revise & Resubmit at Studies in Economics and Finance)

Abstract: This study examines the dynamic relationship between real Gross Domestic Product (GDP) and stock market variables using Vector Error Correction (VEC) and Markov-Switching VEC (MSVEC) models to capture both long-run equilibrium and regime-dependent short-run dynamics for quarterly U.S. data from 1990-2024. The analysis reveals significant long run cointegrating relationships with distinct regime-dependent characteristics: normal periods exhibit stable, positive growth of 0.71% with low volatility (0.47%) and strong correlations among the macroeconomic and stock market variables. In comparison, crisis periods show negative growth (-0.07%) with six-fold higher volatility (2.88%). The study identifies high persistence in normal regimes, with a 94.58% probability of remaining in stable conditions, reflecting strong systemic resilience in non-crisis periods.  This study integrates long-run equilibrium frameworks with regime-switching dynamics to analyze GDP and stock market interactions. Focusing on two major economic crises, the Great Recession and the COVID-19 pandemic, this study examines how these unprecedented events influence the interplay between financial markets and macroeconomic outcomes.   

"Leveraging Financial Indicators to Improve Macroeconomic Forecasting"

Abstract: This paper evaluates the predictive power of financial indicators by employing multiple forecasting models, including Vector Autoregressive (VAR) models, Dynamic Factor Models (DFM), Autoregressive models, and Bayesian Neural Networks (BNN). Additionally, the study incorporates Performance-based Shapley Values to assess the marginal contribution of financial indicators in predicting real GDP growth, providing a more granular understanding of feature importance. By conducting a comparative analysis of these models against professional forecasts and a naive benchmark, this study demonstrates that financial variables significantly contribute to improved forecasting performance. The findings indicate that BNN and DFM models incorporating financial market variables outperform conventional approaches, highlighting the importance of financial markets in macroeconomic forecasting. The study highlights the importance of integrating financial indicators, machine learning techniques, and interpretability measures, such as Performance-based Shapley Values, to enhance real GDP growth predictions.  

Works in progress

The Economic and Distributional Impact of Fiscal Consolidation in a HANK Model: Evidence from France and Italy (with Gee Hee Hong, Rasmane Ouedraogo, Maryam Vaziri) 

• IMF EUR Department Seminar Series, 2025

Search and Matching in OTC Markets (with YY Wong) 

Policy Report 

National Human Development Report of Bangladesh 2021 published by the United Nations Development Programme (UNDP) - Link 

• Contributed to Chapters 2 and 7 (with Selim Jahan)