The Nutrient Rich Food Price Index: a nutrition-relevant adaptation of the Laspeyres price index to track the cost of affordable nutrient density.

Background: The Laspeyres price index is the ratio of the current cost of a market basket of commodities or food groups relative to base period prices. Objective: To develop a nutrition-relevant version of the Laspeyres price index, using market baskets based on tertiles of the nutrient rich food (NRF9.3) nutrient density metric. Methods: Nutrient composition data for 151 foods from the 2012 Mexico national health and nutrition survey (ENSANUT) were merged with food prices and price indices from the national institute of geography and statistics (INEGI). Nutrient Rich Food Index (NRF9.3) was the measure of nutrient density. May 2012 was the base period. Nutrient rich food price index (NRFPI) values were calculated for each tertile of NRF nutrient density scores for each month between June 2011 and March 2022. Results: The market basket of foods in the top tertile of NRF nutrient density scores cost more per 100 kcal and had higher NRFPI values compared to foods in the bottom tertile. Higher NRF9.3 scores were correlated with greater monthly inflation. The NRFPI for foods in the top tertile of NRF9.3 scores was marked by seasonal price spikes, and greater volatility compared to foods in the bottom tertile. Conclusion: The present adaptation of the Laspeyres Index used market baskets defined by nutrient density tertiles instead of commodity groups. This approach allows for easier tracking of the cost of nutrient dense foods and healthful diets across geographic regions and over time. Applied to Mexico food prices prior to and during the Covid-19 pandemic, the NRFPI was sensitive to time trends, seasonality, and price fluctuations. The new tool may be useful in monitoring the rising cost of healthy foods worldwide.

Identifying resilient industries in Mexico's automotive cluster: Policy lessons from the great recession to surmount the crisis caused by COVID 19.

This study investigates regional employment and production resilience to adverse crisis shocks. We extend the concept of resilience beyond the notion of resistance and fast recovery to include the potential of positive spillovers to related industries in neighboring regions. The industrial analysis of the automotive cluster in Mexico relies on a spatial shift-share approach to characterize the resilience ability of regional industries. The study employs the Sub-Prime crisis as a benchmark to identify the type of employment and production recovery after an adverse shock of similar magnitude. Four industries within the automotive cluster present various degrees of spatial dependence-those industries with the most significant spillover effects on neighboring regions. The type of resilience shown by these automotive industries in the regions during the Sub Prime Crisis serves as a benchmark to base policy government and corporate decisions after the economic crisis caused by the outbreak of SARS-CoV-2.