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Research Group

A collaborative effort to advance the understanding of macroeconomic dynamics through rigorous data analysis and economic theory.

3

Joint Publications

5

Collaborative Years

Macro

Academic Focus

20k+

Data Points

Core Members

Collaboration History

2020

Formation

Met at the University of Copenhagen. Established a collaborative workflow for Microeconomics and Mathematical Analysis.

2023

Exchange Rate Dynamics

First major joint research project. Analyzed inflation and relative exchange rates in Denmark using high-frequency data.

2024

ECB Taylor Rules

Advanced seminar paper. Implemented GMM estimation to test for asymmetric policy responses in the Eurozone.

2025

Master's Thesis

Upcoming magnum opus focusing on the Global Financial Cycle and its transmission to small open economies.

Methodology & Workflow

Data Engineering

Automated Python pipelines ensure reproducibility. We never clean data manually.

01

Econometrics

Rigorous identification in Stata. From simple OLS to GMM and structural VAR models.

02

Dissemination

LaTeX for academic papers, Astro for interactive web dashboards. Clarity is king.

03

Thesis Tracker

Global Financial Cycles

Expected Completion: Summer 2025

35% Complete
Literature Review 80%
Data Collection 60%
Model Validation 10%
Drafting 5%

Data Scale

20M+ Observations

High-frequency financial data from Bloomberg and Datastream.

150+ Variables

Macroeconomic indicators across 30+ countries.

40GB Raw Data

Processed and structured in SQL databases.

The Knowledge Bank

Gabaix, X. & Maggiori, M. (2015). International Liquidity and Exchange Rate Dynamics. QJE.

Rey, H. (2015). Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence. NBER.

Miranda-Agrippino, S. & Rey, H. (2020). U.S. Monetary Policy and the Global Financial Cycle. RES.

Bruno, V. & Shin, H. S. (2015). Cross-Border Banking and Global Liquidity. RES.

Gallery

The Stack 2.0

Stata

reghdfeivreg2gmmestout

Python

pandasnumpyscipymatplotlib

LaTeX

tikzbeamerbiblatexpgfplots

DevOps

gitgithub-actionsdockerduckdb

Open Science Pledge

We believe in transparency. All data cleaning is scripted, and we strive for full reproducibility via public replication packages for every major release.

Scripted Cleaning
Version Control

Network & Affiliation

  • University of Copenhagen

    Department of Economics (ØI)

  • CeBIL

    Data Support & Research

Academic Supervision

Research Log

Feb 2025

Automating FX Data

Implemented a fully automated pipeline for fetching ECB exchange rates via API.

Jan 2025

Mastering DuckDB

Migrated large datasets from CSV to DuckDB/Parquet format for 50x faster I/O.

Dec 2024

GMM Estimation

Successful replication of Gertler & Karadi (2015) instruments in Stata.

pipeline.py
import pandas as pd
import statsmodels.api as sm

# 1. Load and Clean High-Frequency Data
df = (
    pd.read_parquet("data/raw/ecb_ticks.parquet")
    .query("currency == 'USD/EUR'")
    .resample("1min")
    .agg({"price": "ohlc", "vol": "sum"})
    .dropna()
)

# 2. Local Projection (Jordà, 2005)
model = sm.OLS(df["future_return"], df[["shock", "controls"]])
results = model.fit(cov_type='HAC', cov_kwds={'maxlags': 12})
print(results.summary())
                     
Code Behind the Numbers Reproducible & Robust

Academic Curriculum (M.Sc. Econ)

7.5 ECTS

Advanced Macroeconomics

DSGE models, real business cycles & New Keynesian theory.

7.5 ECTS

Econometrics II

Instrument variables, GMM, Time Series Analysis & asymptotic theory.

7.5 ECTS

Mechanism Design

Auction theory, contract theory & matching markets.

7.5 ECTS

Corporate Finance

Capital structure, valuation & financial options.