The Effects of Education Quality on Income Growth and Mortality Decline

Previous work shows that higher levels of education quality (as measured by international student achievement tests) increases growth rates of national income. This paper begins by confirming those findings in an analysis involving more countries over more time with additional controls. We then use the panel structure of our data to assess whether the mechanism by which education quality appears to improve per capita income levels is through shifting the level of the production function (probably not), through increasing the impact of an additional year of education (probably not), or through increasing a country's rate of technological progress (very likely). Mortality rates complement income levels as indicators of national well-being and we extend our panel models to show that improved education quality increases the rate of decline in infant mortality. Throughout the analysis, we find a stronger impact of education quality and of years of schooling in open than in closed economies.

India's Health Initiative: Financing Issues and Options

In response to the challenge of sustaining the health gains achieved in the better-performing states and ensuring that the lagging states catch up with the rest of the country, the Indian government has launched the National Rural Health Mission. A central goal of the effort is to increase public spending on health from the current 1.1 percent of GDP to roughly 2–3 percent of GDP within the next five years. In this paper, we examine the current status of health financing in India, as well as alternatives for realizing maximal health gains for the incremental expenditures.health financing, public spending, India, cost-effectiveness

An Evaluation of Unmanned Aircraft Systems\u27 Ability to Assess Stripe Rust in Large Wheat Breeding Nursies

Stripe Rust (Puccinia striiformis f. sp. tritici) is a foliar disease that significantly impacts global wheat production, and resistant cultivars provide the most efficient method of control. High-throughput phenotyping using unmanned aircraft systems (UAS) offers a potentially more efficient method for field-based phenotyping compared to visual assessment. Here we tested the ability of remote sensing to predict stripe rust severity in a diverse population of 594 soft red winter wheat lines, planted in single-rows, and evaluated them by visually rating stripe rust intensity and remotely using the dark green color index (DGCI), normalized difference vegetation index (NDVI) and blue NDVI. Significant relationships (p In a second study, the effect of plot size (single-row, two-row and four-row) on relationship between visual and remote sensing data (DGCI and NDVI) was explored. We evaluated a panel of 13 genotypes preselected to range from 0 to 100% severity, planted in three plot sizes across two measurement days. Significant (