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The authors examine the factors influencing membership in farmer organizations (FO) and their effects on the decision to adopt farm technologies by rice farmers in Ghana.

This study uses a farm survey of 900 households from Northern Ghana and a recursive bivariate probit (RBP) model that accounts for selection bias and endogeneity.

The results indicate that the household head’s decision to adopt machinery and row planting increases by 38.4 and 25.3%, respectively, upon joining a farmer organization. Membership in farmer organization is positively influenced by off-farm income, asset value, farmer organization location and farmer location in Upper West region but negatively by males, age and total livestock units owned. Machinery adoption is positively influenced by membership in farmer organizations and respondent being male but negatively influenced by the years of schooling, farm size, farm distance and location of a farmer in Ghana's Upper East and West regions. Similarly, row planting adoption is positively influenced by membership in farmers' organization but adversely by farm size, farm distance and a farmer's location in Upper East region of Ghana.

It can be concluded that membership in farmers' organizations significantly impacts farm household head’s decision to adopt machinery and row planting in rice production, which potentially enhance crop productivity.

These results show the importance of agricultural stakeholders in encouraging the formation and strengthening of farmer organizations to support the adoption of modern farming technologies.

Developing literature has demonstrated that farmer organizations promote the adoption of agricultural innovations. However, most of these studies have concentrated on conventional agricultural innovations and have used methods that fail to account for potential selection bias. This paper fills this important gap.

Qatar, a wealthy country with an open economy has limited arable land. To meet its domestic food demand, the country heavily relies on food imports. Additionally, the over three year-long economic embargo enforced by regional neighbors and the covariate shock of the COVID-19 pandemic have demonstrated the country's vulnerability to food insecurity and potential for structural breaks in macroeconomic data. The purpose of this paper is to examine short- and long-run determinants of Qatar's imports of aggregate food, meats, dairy and cereals in the presence of structural breaks.

The authors use 24 years of food imports, gross domestic product (GDP) and consumer price index (CPI) data obtained from Qatar's Planning and Statistics Authority. They use the autoregressive distributed lag (ARDL) cointegration framework and Chambers and Pope's exact nonlinear aggregation approach.

Unit root tests in the presence of structural breaks reveal a mixture of I (1) and I (0) variables for which standard cointegration techniques do not apply. The authors found evidence of a significant long-run relationship between structural changes and food imports in Qatar. Impulse response functions indicate full adjustments within three-quarters of a year in the event of an exogenous shock to imports.

An exogenous shock of one standard deviation on this variable would reduce Qatar's food imports by about 2.5% during the first period but recover after the third period.

The failure of past aggregate food demand studies to go beyond standard unit root testing creates considerable doubt about the accuracy of their elasticity estimates. The authors avoid that to provide more credible findings.