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Ensuring adequate access to food to all has remained a major challenge of the 21^st century. To aid the effort of hunger alleviation, many studies have quantified the prevalence of undernourishment (PoU), mostly at the national level. There has been limited attention to understanding the intra-country variation in undernourishment estimates.

Unlike past studies, this study tracks the substantial regional heterogeneity in the undernourishment status within Nepal. Employing Food and Agriculture Organization's methodology and Nepal Living Standards Survey data from 1995, 2003 and 2011, household energy consumption and requirements are computed to determine regional undernourishment.

Nepal's PoU declined between 1995 and 2003 but increased after 2003 affecting approximately 7.6 million Nepalese in 2011. The Terai domain – Provinces 2 and 5 – are found to be the most vulnerable to undernourishment concerns likely because of economic and natural shocks. Province 4 achieved higher progress in alleviating undernourishment during 2003, but its PoU doubled in 2011 (as in Province 6).

By examining where and how many are undernourished within Nepal, this study has provided a more accurate picture of the PoU for better-targeting assistance to improve the livelihood of its citizens.

Past studies indicate substantial variation in food access and PoU within Nepal. While they provide some answers to “where and how many” questions for some districts, provinces, belts and urban/rural domains at the cross-sectional level (or for selected locales), few have examined intra-Nepal heterogeneity, especially over time. Therefore, this study explores where and how many within Nepal have been undernourished during the past three decades.

This study aims to investigate the role of international price volatility and inventories on domestic market price dynamics in the case of agricultural commodities.

A structural model is employed to uncover relationships among commodity price, price volatility, inventories and convenience yield. Monthly producer price data along with annual data on trade, consumption, inventories and tariffs for 71 countries and 13 commodities covering 2010–2019 are assembled to estimate the model. With a first-stage Least Absolute Shrinkage and Selection Operator (LASSO) estimator to identify the best instrument set, a nonlinear approach is used to estimate the model.

Results show that international market information plays a critical role in domestic market price dynamics. International price volatility has a stronger effect on domestic prices than that of international inventories.

Current upheaval in commodity markets requires an understanding of how prices move together and inventories affect that movement. A country's internal price is not independent of the effects of global market events.

Although hypotheses exist that global market information (volatility and inventories) helps countries manage domestic commodity prices, there have been limited studies on this relationship, especially with a structured model and cross-country data.