Lelo Nxumalo

In the fast-paced world of economic policy and financial markets, waiting for official GDP statistics can feel like an eternity. With quarterly GDP data often released weeks after the quarter ends, economists and policymakers need better tools to understand economic conditions in real-time. Enter GDP nowcasting  – a technique that uses machine learning to predict current-quarter GDP growth using timely economic indicators. What is GDP Nowcasting? GDP nowcasting bridges the gap between economic theory and practical decision-making by providing near real-time estimates of economic growth. Unlike traditional forecasting that predicts future values, nowcasting focuses on estimating the current state of the economy using available high-frequency data. The approach leverages the fact that while GDP data comes with a lag, many related economic indicators are available much sooner – employment figures, industrial production, retail sales, and consumer sentiment surveys are all published...

1. The Core Policy Question We begin with a question critical for many developing economies, including Morocco: When highly productive multinational corporations (MNCs) invest, what happens to the local economy? Do they drive out domestic firms, capture the entire market, and repatriate profits? Or can they coexist with domestic firms, creating moderate GDP gains and stable jobs? What are the trade-offs for skilled vs. unskilled workers? To answer this, we must build a model, but not just any model. We need one that is both economically realistic and computationally solvable . This document outlines the structure, key concepts, and findings of such a model. 2. Key Economic Concepts Explained This model is a DSGE model that combines TANK households with an S&M...

🚨 Executive Summary For decades, agricultural policy has focused on rainfall variability. A 24-year econometric analysis (2000–2023) reveals a more urgent threat: Heat Stress . Rising temperatures have become the dominant driver of declining crop health in Ghana. I have identified two critical "tipping points" that threaten the Northern breadbasket and the Cocoa economy by 2040. 1. The Evidence: Heat is the New Dominant Driver Using Fixed Effects regression models on satellite data from 2000 to 2023, I isolated the impact of temperature and rainfall on vegetation health (NDVI). NDVI it = β 1 Temp it + β 2 Rain it + α zone + γ year + ε it Model Specification: Where α zone controls for static location factors (soil/elevation) and γ year controls for global time trends. The results were conclusive: Temperature is the binding constraint. Fi...

The debate over minimum wage policy has raged for decades, with economists, policymakers, and business leaders offering sharply different predictions about its effects on employment. Critics warn that raising the minimum wage will force employers to cut jobs, while supporters argue that higher wages boost worker productivity and spending power. But what does the actual data tell us. Using a comprehensive difference-in-differences analysis and Federal Reserve Economic Data covering 43 U.S. states from 2012-2020 of the "Fight for $15" movement between 2012 and 2020, I provide some evidence about how minimum wage increases actually affect employment in the real world. The Perfect Natural Experiment The period from 2012 to 2020 provided economists with an ideal "natural experiment" to study minimum wage effects. Here's why this timeframe was perfect for analysis: Federal Stability : The federal minimum wage remained frozen at $7.25 per hour since 2009, creating ...

Three years ago, I documented rising land surface temperatures across Ghana , showing a clear warming trend from 2000 to 2020. This follow-up analysis links those temperature trends to agricultural productivity and explores their macroeconomic implications for Ghana's growth trajectory. Using 24 years of satellite data (2000-2023), I've quantified the relationship between rising temperatures and vegetation health across Ghana's three major agricultural zones. Key Empirical Findings Temperature-Agriculture Correlation: $r = -0.885$ $(p This is one of the strongest climate-agriculture relationships documented in African contexts. The relationship holds across zones (Northern Savanna: $r = -0.82$, Middle Belt: $r = -0.88$, Coastal: $r = -0.79$) and during critical growing seasons (Major: $r = -0.86$, Minor: $r = -0.81$). Establishing Causality Beyond Correlation While correlation doesn't prove causation, multiple ...

How do we measure the impact of a policy? In a laboratory, you have a control group. In the real world, we only have one California. We cannot observe the "counterfactual"—a parallel universe where California never passed its landmark Cap-and-Trade bill (AB 32) in 2013. However, using econometrics and Python , we can build that parallel universe. Using the Synthetic Control Method (SCM) , I analyzed real-world energy data to estimate the true impact of carbon pricing on California's emissions. Here is what the data says. The Methodology The Synthetic Control Method estimates the effect of an intervention (the policy) by comparing the treated unit (California) to a weighted combination of control units (other US states) that did not implement the policy. To ensure a robust "apples-to-apples" comparison, I pulled data directly from the EIA Open Data API (v2) , controlling fo...

Understanding labor market transitions is important for policymakers and researchers in developing countries. Changes in economic activity status (employed, unemployed, out of labor force) vary significantly from one country to another and also within countries from one socio-economic group to another. Below I summarize analysis from the latest Ghana Annual Household Income and Expenditure Survey ( AHIES ) published by the Ghana Statistical Service. The AHIES is a panel survey that has followed over 10,000 individuals since 2022Q1 to assess changes in their livelihoods. I am currently analyzing trends and show here what has happened to economic activity between Q2 and Q3.  Transitions in Ghana labor force status, 2022Q2 - 2022Q3 Source : Own analysis using AHIES from Ghana Statistical Service. Note : Left hand side is 2022Q2 and right side is 2022Q3 81 percent of working age individuals (15-64-years) who were  employed  in 2022Q2 were still employed in 2022Q3; 7 perc...