Abstract

AbstractFood security is an indispensable concept because human life depends on it. Although numerous studies have examined food security in developing economies, there has been a lack of attention given to this issue in developed countries. Thus, this study investigates the influence of carbon dioxide emissions (CO2) on food security in the United States from 1965 to 2022 using Quantile Autoregressive Distributed Lag (QARDL) and Wavelet Coherence methods. Food security is proxied by the food production index (FPI), while the control variables are gross domestic product (GDP), population growth (POP), and inflation. The Quantile Autoregressive Distributed Lag results show that: (i) In the short‐run, CO2 influences FPI positively at the 0.05 quantile, while it harms food security at the 0.50 and 0.95 quantiles. However, in the long‐run, the impact is positive across all quantiles; (ii) In the short‐run, GDP harms FPI at the 0.05 quantile while it benefits FPI at the 0.50 and 0.95 quantiles. In the long‐run, GDP's impact across all quantiles is beneficial; (iii) In the short‐run, POP negatively influences FPI at 0.05 and 0.50 quantiles, while it positively spurs FPI at 0.95 quantiles. In the long‐run, POP positively influences FPI at quantiles of 0.05, whereas it negatively influences FPI at 0.50 and 0.95 quantiles; (iv) inflation positively influences FPI in the short and long‐run across all quantiles; (v) The Wavelet Coherence analysis showed a robust correlation across all frequencies. Policy suggestions and implications are discussed further.

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