Lelo Nxumalo

In the world of risk modeling, natural disasters are notoriously difficult to quantify. While frequency is relatively predictable, economic impact is chaotic. A single "Black Swan" event—like the 2011 Tohoku Earthquake or the 2004 Indian Ocean Tsunami—can cause more economic damage in an afternoon than thousands of smaller events combined over a decade. I analyzed global disaster data from EM-DAT (2000-2025) to understand these patterns. Below, Wi look at the geography of these events and, crucially, how I am using a Composite Log-Normal Pareto model to estimate their economic costs when data is missing. The Geography of Risk To understand the scope, I first look at where these events occur. As the data shows, the distribution is far from uniform. Figure 1: Natural Disasters by Region. Asia is the undisputed global epicenter of natural disaster frequency, accounting for nearly double the event count o...

In the fast-moving world of international trade, data is often the bottleneck. Detailed Inter-Country Input-Output (ICIO) tables—the maps that tell us exactly how many semiconductors Japan sold to Germany—often lag by years. Yet, policymakers and analysts need to know what the world looks like today . How do we reconcile the detailed structural data of the past with the aggregate economic realities of the present? In this analysis, we deployed the RAS Method (Bi-Proportional Adjustment) to "Nowcast" the 2022 global trade structure using only historical patterns and current headlines. The Methodology: A Blind Simulation To rigorously test the RAS capability, we set up a "Blind Simulation" using Python. Although we possessed the full 2022 Input-Output tables, we deliberately ignored the interior data —the specific supply chain connections between countries. Instead, we fed the algorithm only two specific ...

Executive Summary This analysis evaluates the macroeconomic impact of expanding social protection (unemployment benefits) in Turkey by 33%. Using a micro-founded DSGE model calibrated to the Turkish economy, we find that financing methods determine policy success. Labor Tax Financing (The "Death Spiral"): Attempting to fund benefits via labor taxes causes the formal sector to collapse. The model identifies a "Fiscal Cliff" at a 40% tax rate. VAT Financing (The Viable Path): A Consumption Tax (VAT) increase from 18% to 20.6% successfully funds the program with significantly less damage to employment. 1. Country Context: The Turkish Economy in 2024-2025 To understand the simulation results, it is essential to situate them within Turkey's current macroeconomic reality. The economy is currently navigating a "rebalancing" phase ch...