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The article "The impact of macroeconomic factors on food price inflation: an evidence from India" by Samal et al. investigates the relationship between macroeconomic factors and food price inflation in India. The study utilizes monthly time series data from January 2006 to March 2019 and employs the ARDL bounds testing approach to cointegration to confirm the long-run relationship among variables.

The study finds that per capita income, money supply, global food prices, and agricultural wages have a positive and significant impact on food price inflation in both the short and long run. On the other hand, food grain availability has a negative and significant impact on food price inflation in both the short and long run. The real exchange rate positively impacts food price inflation in the short run but is insignificant.

While the study provides valuable insights into the drivers of food price inflation in India, it has some limitations. For instance, it does not consider other potential factors that may affect food prices, such as weather conditions or government policies. Additionally, while the study acknowledges that global factors may influence domestic food prices, it does not explore how changes in trade policies or international agreements may affect domestic prices.

Moreover, there is a potential bias towards demand-side factors as opposed to supply-side factors. While the study includes both demand and supply-side factors in its analysis, it emphasizes demand-side factors such as per capita income more than supply-side factors such as agricultural productivity or input costs.

Furthermore, while the study examines causality between variables using Granger causality tests, it does not explore potential reverse causality or omitted variable bias that may affect its results.

In conclusion, while this study provides valuable insights into the drivers of food price inflation in India, it has some limitations that should be considered when interpreting its findings. Future research should consider additional potential drivers of food price inflation and explore potential biases or limitations in their analyses.