This study uses unit-record data on over 50,000 rural children, from the sixteen major states of India, to analyse the determinants of the risks of severe stunting and of being severely underweight. The importance of this study derives from the fact that the prevalence of under-nourishment in India is, even relative to other poor countries, shockingly high. The study focuses on the role of maternal literacy in reducing the risk of child malnourishment. It concludes that when the mother is literate, real benefits flow to children in terms of reduced risk; the same benefits, however, do not flow when the father, but not the mother, is literate. Literate mothers make more effective use of health-care institutions, like anganwadis and hospitals. Consequently, the benefits to children from expanding the supply of such institutions are greater when these institutions interact with mothers who are literate.
The notion that prices impound a wide array of information, including market expectations, has led to earnings forecast models conditioned on prices. Yet, presumably, analysts' forecasts capture both public information and certain private information not previously impounded in prices. Accordingly, price-based models are seemingly an inefficient, and less effective, source of expecta-tions. This article investigates this hypothesis using financial analysts', price-based, and naive forecasts. Results indicate that analysts' forecasts (1) are at least as accurate as price-based and naive models, and (2) yield better expectations for market tests relating returns and earnings. These inferences are robust across different information environments. The evidence suggests that analysts either possess private information or are more effective information processors, or both. 相似文献