Search results

This study assesses distress in the lives of farming population in Ghana's northern interior. Whereas recent studies addressing mental health in Africa produce evidentially sound analyses of the correlated role of food and water insecurity, this study engages with how and why worries over educational costs feature so prominently in a measure of psychosocial well-being. While it is significant that education identifiably figures in escalating the experience with distress, my contention is that what is more important is putting that escalation into the context of why. I use Narotzky and Besnier's framework for understanding the economy as the interactions between crisis, value, and hope to situate a mixed methods study concerned with how distress is proximately shaped by the interactive socioeconomic features of daily life (paying school fees, buying food, cultivating maize, etc.) but ultimately shaped by structural features of the political economy that direct people's objectives amid chronic crisis. My proposition is that because education is where value resides, it is a primary vehicle by which people are acting in crisis in a hopeful manner. In this way, this study leverages the tools of economic anthropology within debates about how to best assess the ways in which health and illness are shaped by socioeconomic realms.

A major concern for policymakers and researchers is to ascertain the movement of price levels and employment rates. Predicting the trends of these variables will assist the government in making policies to stabilize the economy. The objective of this chapter is to forecast the unemployment rate and Consumer Price Index (CPI) for the period 2022 to 2031 for the Indian economy. For this purpose, the authors analyse the prediction capability of the univariate auto-regressive integrated moving average (ARIMA) model and the vector autoregressive (VAR) model. The dataset for India's annual CPI and unemployment rate pertains to a 30-year time period from 1991 to 2021. The result shows that the inflation forecasts derived from the ARIMA model are more precise than that of the VAR model. Whereas, unemployment rate forecasts obtained from the VAR model are more reliable than that of the ARIMA model. It is also observed that predicted unemployment rates hover around 5.7% in the forthcoming years, while the forecasted inflation rate witnesses an increasing trend.