#econometrics

Quantile Regression with Gaussian Processes for Spatial Data in Python and R

Scalable quantile regression with Gaussian processes using a novel Laplace approximation in GPBoost

Verilerin Gölgesinde Barut Kokusu: Savaşın Ekonometrik Anatomisi ve 2026 Krizi

Savaşın ekonomik maliyetlerini; arz şokları, sentetik kontrol yöntemi ve veriye dayalı projeksiyonlar üzerinden okumak.

Does Rupiah Depreciation Really Stimulate Indonesia’s Economy?

Nilai tukar merupakan salah satu variabel makroekonomi yang paling sensitif dalam perekonomian terbuka. Pergerakan nilai tukar tidak hanya…

Mining the Malacca Strait

Weaponised viscosity: What would happen to global power if a rogue state mined the Malacca Strait?

Mastering Non-Linear Data: Why Splines Outperform Linear Models

Learn how to use piece-wise polynomials and knots to build more flexible, disciplined, and accurate machine learning models.

Understanding Logistic Regression in R (With a Real Supply Chain Risk Case)

If you’ve already learned OLS regression, you probably feel comfortable modeling relationship like:

Bayesian Price Elasticity with PyMC

From a simple log-log model to cross-price substitution

How to Run OLS Regression in R (A Beginner-Friendly Guide)

If you are just starting econometrics, one of the first things you will learn is Ordinary Least Squares (OLS).

Understanding Y, X, Control, and Instrument Variables (Without the Confusion)

If you’re just starting econometrics or statistics, you’ve probably seen terms like:

How does money Supply and inflation rate affect the growth of the Nigerian economy?

In this research, we explore the intricate relationship between money supply, inflation rate, and economic growth in Nigeria from 1990 to…

Introduction to data science Part 29: How can Quantitative Finance inform about dLLMs?

We discuss the autoregressiveness property

Applied science in modern marketplaces: lessons from Faire and beyond

The four forces behind marketplaces — and the science that powers them.

Introduction to Causal Inference

Foundations of Causal Thinking for Data Analysis

Precision Influence: Mastering Uplift Modeling and Heterogeneous Treatment Effects (HTE)

Moving beyond “Does it work?” to “Who does it work for?” using Causal ML

Finding a Workflow That Let Me Use Python and R Together — Quarto

How I stopped exporting CSVs between two languages

Causal Inference: A 100-Year Story That Still Shapes How We Know What Works

Causal inference evolved from agricultural experiments to policy evaluation and machine learning.

Jangan Salah Tafsir: Tanda Bintang di R dan Stata Ternyata Beda

Jika kita baru belajar ekonometrika, pasti sering melihat output regresi dengan simbol bintang-bintang, iya kan? Misalnya ada yang ***, ada…

Why Econometrics Matters for Anti-Money-Laundering: A Practical Roadmap

Money-laundering is an economic problem dressed as a criminal problem: it distorts markets, corrodes institutions, and hides wealth that…

Memahami SRF (Sample Regression Function) dan PRF (Population Regression Function) dalam…

Pendahuluan

Belajar Machine Learning Sederhana dengan R: Memprediksi Harga Rumah

R adalah salah satu alat analisis data yang sangat powerful. Ada banyak hal yang bisa kita lakukan dengan R, misalnya saja adalah melakukan…

Understand the Problem and Get Better Results Using Exploratory Data Analysis in R: Practical…

This article shows how systematic Exploratory Data Analysis in R equips economists to clarify problems, discover important trends and…

Understand Problem and Get Better Results Using Exploratory Data Analysis in Python: A…

This article explains how systematic Exploratory Data Analysis with Python enables economists and financial analysts to uncover structure…

The Jujutsu of Statistics

How P.C. Mahalanobis Turned Eugenics into a Nation-Building Tool

Unlocking Australians’ Financial Behaviour: How Segmentation and Probit Regression Analysis Reveal…

Financial hardship manifests in diverse ways and is influenced not only by income but also by financial capability and, in some alarming…

The Diagnostic Triad: Autocorrelation, Heteroskedasticity & Multicollinearity Unveiled

‘The Silent Saboteurs of Statistical Modeling’

Forecasting Australian Beer Production using ARIMA & SARIMA Models in Python

A step-by-step guide to time series forecasting using ARIMA and SARIMA models, uncovering seasonal trends in Australian beer production

Heteroskedasticity in Regression Analysis

Heteroskedasticity is a common issue in regression analysis that affects the validity of statistical inferences. It occurs when the…

Greener Cities, Safer Streets? Exploring the Impact of Green Spaces on Crime

Amélie Madrona, Linne Verhoeven, Clara Bottinelli & You Li

Clase 3 Aplicación Econométrica UNITEC / Correlaciones e Introducción a las Regresiones Lineal…

Por Dr. Roberto Chang

Átila ou Marcelo: Qual rumo econômico de Mauá deve tomar?

Addressing Heteroskedasticity in Time-Series Modeling with Robust Standard Errors (in Python)

When you frequently model millions of time series, see Likely Spurious, you encounter heteroskedasticity quite often. Unfortunately, most…

My Experience Studying Econometrics as an Economics Student

Econometrics has been an integral part of my career in data. Econometrics was like my gateway, and made me fall in love with data. In this…

Information flows and systematic risk: A review.

Introduction

ESTUDO DE CASO: O Fenômeno Inflacionário no Brasil (Parte 2)

Sobre a Parte 1

Finding Self-Esteem with a Law of Large Numbers Argument

One common variation of the Law of Large Numbers is that as the number of samples increases to infinity, the average is a good estimator…

A Deep Dive on Vector Autoregression in R

Let the data speak! Let us purge a-priori expectations.

Structural Vector Autoregression in R

The Structural Vector Autoregression is a very flexible tool especially for the analysis of policy actions on the real economy.

R ve Ekonomi — 2

Aynı başlığın birinci yazısında R’ın ekonomik alanda kullanımına dair planlarımı yazmıştım.