Welcome to story time

Topics

1. Causal Inference in Policy Design x Economics

Causal identification in policy evaluation is a central challenge in economic research. Machine learning methods offer promising tools for denoising causal estimates, particularly in small-sample settings. The key here is to Reduce the Estimator Variance first.

TLDR - Key References

• 2025 IZA World of Labor - Machine learning for causal inference in economics
  
  

Possible Solutions 🪨

• Causal forest
  

• Double/debiased machine learning - DML - by Sample-splitting, cross-fitting and repeated cross-fitting
  

• Bayesian Shrinkage - for Macro Panel - 2025 Bayesian Shrinkage in High-Dimensional VAR Models: A Comparative Study
  

• Regularization - 2022 IMF - Structural Reforms and Economic Growth: A Machine Learning Approach
  

• Random Walks - 2024 IMF - Reconciling Random Walks and Predictability: A Dual- Component Model of Exchange Rate Dynamics
  

• PCA - Principal Component Analysis - 2024 IMF - Exchange Rate Dynamics: A Principal Components Analysis

  • 2024 IMF - Exchange Rate Dynamics: A Principal Components Analysis

Key References

• 2024, Estimating Causal Effects with Double Machine Learning – A Method Evaluation
  
  

• 2024, How do applied researchers use the Causal Forest? A methodological review of a method
  
  

• 2023, IMF - Dining and Wining During the Pandemic? A Quasi-Experiment on Tax Cuts and Consumer Spending
  
  

• 2023, Swiss Journal of Economics and Statistics - Causal Machine Learning and its use for public policy
  
  

• 2022, Econometrica - Automatic Debiased Machine Learning of Causal and Structural Effects
  
  

• 2019, IMF - Machine Learning and Causality: The Impact of Financial Crises on Growth
  
  

Topics

1. Why does History Reduplicate Itself

2. Models Matching

• References
  
  
  • The economy needs agent-based modelling, 2009.
    
    
  • Economics PINN: Deep learning for solving and estimating dynamic macro-finance models
    
    
  • Payne, Jonathan, Adam Rebei, and Yucheng Yang. 2025. Deep Learning for Search and Matching Models. February 1, 2025.
    
    
  • Xu, Jun, Xiangnan He, and Hang Li. 2020. Deep Learning for Matching in Search and Recommendation. Vol. XX, No. XX, pp. 1–193. DOI: XXX.
    
    
    
    

If you’re interested in the field of Academic Economics, pay attention to our Top 5 journals:

• 1 AER - American Economic Review
• 2 QJE - Quarterly Journal of Economics
• 3 JPE - Journal of Political Economy
• 4 Econometrica
• 5 Review of Economic Studies
  
  
  
  

For Working Papers:

• 1 NBER Working Papers
• 2 Journal of Economic Literature (JEL)
• 3 SSRN - Social Science Research Network
• 4 VoxEU.org
• 5 Nobel Prize-winning Research
• 6 John Bates Clark Medal - AEA
• 7 BBVA Frontiers of Knowledge Award – Economics, Finance, and Management
• 8 Yrjö Jahnsson Award - EEA
  
  
  

Others:

• 1 Journal of Finance
• 2 The Accounting Review
• 3 IMF - Working papers