The monsoon is approaching. The air is heavy, thick with the quiet anticipation of rain. Outside the local health post, a long queue has already formed. The municipality is distributing free mosquito bed nets before the weather turns. Health workers know what follows the rain: stagnant water, mosquitoes, and the seasonal return of malaria. Mina, […]
Mina, the smallholder we met in January, stands at the edge of her field in the heavy silence that follows a poor harvest. In her hands are two seed packets. One is bright and glossy, delivered by an agricultural programme—promising harvests nearly fifty per cent higher than her usual crop. The other is plain, a
The Wisdom of Saying No: Why Smart Choices Look Irrational? Read Post »
Three winters ago in Japan, my wife and I prepared for our first-ever skiing adventure. Excited but frugal, we decided at the last moment to save a few yen by buying universal-size ski gloves. They looked fine in the store—stretchy material, adjustable straps. Hope, as it often does, overrode experience. On the slopes the next
The Myths of the Average Person: One Number, Two Economic Lives Read Post »
In April 2025, a sudden loss of vision forced me into major eye surgery and an unusual recovery. For months, I remained face-down for hours each day; my world was reduced to darkness and sound. Reading was impossible. My usual tools—graphs, datasets, and regression tables—were inaccessible. Progress was not something I could observe or measure
Note: This post is a special year-end issue in my blog series, reflecting on recent policy discussions from a health economics conference in Nepal. “The policy logic behind taxing High-Sugar, Salt, and Fatty (HFSS) foods is compelling and urgent: curb consumption, expand fiscal space, and fund health to fight non-communicable diseases (NCDs).” The public health
From Slogans to Systems: Rethinking Junk Food Taxes in Nepal Read Post »
Imagine two researchers working with the same dataset to answer the same high-stakes policy question: Does a new vocational training program helps unemployed adults earn more? Both are well-trained. Both follow standard practices. Both make what they believe are reasonable, defensible choices in their models. Yet when they present their results, the headline numbers don’t
“The Program Worked. Or Did It?” How Model Dependence Shapes Policy Evidence Read Post »
In my previous post, we discussed the signal — the functional form. We saw how getting the shape of a relationship wrong (for example, assuming a straight line when the true effect is curved) can lead to biased policy estimates. Today, we turn to the other half of the story: the noise or the stochastic
Beyond the Signal: How Noise Defines What We Can Trust in Policy Analysis Read Post »
It has been a while since my last post—since March, to be exact. Life threw me an unexpected challenge: a detached retina. The fix? Surgery where surgeons injected silicone oil into my eye to press the retina back into place. But the oil does not work magic on its own. For it to work, I
When More Isn’t Always Better: The Shape of Impact in Policy Decisions Read Post »
When a new programme or intervention is implemented, we all want to know: “Did it work? ” A seemingly straightforward way to find it out is to compare outcomes before and after. If GPA scores go up, health improves, or incomes rise, many mistakenly assume this is clear proof of impact. But is it? In
The Pre and Post-Test Design Puzzle: What is Missing in the Impact Evaluation? Read Post »
Did you know that countries with higher rates of internet penetration tend to have longer lifespans? Or that nations with larger militaries often have healthier populations? At first glance, these patterns might seem logical. After all, internet access could improve healthcare access, and a strong military might indicate a stable government. But does this mean
The Dangers of Correlation: Why “Impact or Effect” Isn’t Always What It Means? Read Post »
Imagine planning a household survey in a rural village where access to a reliable and comprehensive sampling frame is limited or logistically challenging. OpenStreetMap may be useful in this context but the dataset is often riddled with inconsistencies. In my previous blog, we explored a method to extract households using OSM tags to guide sampling
GIS-Based Sampling Part II: A Grid-Based Approach for Field Research Read Post »
Have you ever found yourself staring at a blank map, wondering how to select the right households for your research? Field researchers often face this challenge, especially when a reliable sampling frame is scarce. One common workaround is a crude method where enumerators would spin a bottle to determine a walking direction and then select
Redefining Household Sampling: A GIS-Based Approach Using OpenStreetMap and Python Read Post »