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This study aimed to investigate factors influencing the adoption of improved cultivars (ICs) in peach production in Khyber Pakhtunkhwa province of Pakistan. A total of 270 respondents were randomly selected from the three different cultivated areas of Khyber Pakhtunkhwa, namely, Peshawar, Nowshera and Swat. Binary choice model was used in this study to categorise the ICs of peach farmers into adoption and non-adoption. The study identifies that socio-economic, institutional farm resources, and climatic factors are influencing the adoption of ICs of peach production. Results of the estimated model reveal that farmer’s age, education, household size, membership, cell phone, farm size, extension services and the role of the non-government organization have a positive effect on adoption of ICs. In addition, farmer’s experience, off-farm income, livestock and machinery ownership, credit access and inputs prices have a positive and significant impact on ICs adoption. Moreover, results of the logit model demonstrate that climatic related factors have a highly significant and positive impact on the adoption of ICs. These results suggested that institutional services should be strengthened to provide managerial and technical skills on ICs technology adoption and on time provision of financial services to enhance the productivity of peach farmers.

This study aims to contribute to the literature and examine the causal relationship between Pakistan’s agricultural products export, industrialization, urbanization, transportation, energy consumption, and carbon emissions. For the last four decades, time-series data were used to employ short-run and long-run nexus between the selected variables by analyzing the autoregressive distributed lag model (ARDL). The Granger causality test was analyzed to estimate the causality directions. The unit root test results indicate that all the selected variables are stationary at the level and first difference. The bound test confirmed that all variables are cointegrated at a 1% significance level. Long-run estimates suggest that an increase in energy consumption will increase the export of agricultural products. An increase in urbanization, transportation, and carbon emission resulted in a decrease in agricultural products export in Pakistan. In the short run, an increase in industrialization, transportation, and energy consumption leads to an increase in agricultural products export. Increasing urbanization and carbon emission decrease the agricultural products export of Pakistan. Based on our findings, we recommend sustainable agricultural production, renewable energy consumption, low carbon emission technologies, and a green portfolio for sustainable agricultural products export.

Pakistan is an agriculture-based country, so the agricultural sector is known as the backbone of the national economy. Considering the national economy and the agricultural industry, it is necessary to focus on earnings through agricultural products export to improve the livelihood of local farmers. Therefore, the current study aimed to analyse the short-term and long-term factors affecting agricultural products export. The annual time series of 1976–2016 were collected from World Bank indicators, the Food and Agriculture Organization, and the Statistical Bureau of Pakistan. An autoregressive distributed lag, along with a vector error correction model, was employed. A cointegration test showed long-term associations between the selected variables. While the autoregressive distributed lag model confirmed the short-term correlation between area sown and crop production towards agricultural products export, there is no long-term relationship between the selected variables. In addition, the bidirectional correlation between employment in agriculture and agricultural products export was confirmed by the vector error correction model. Therefore, it is essential to increase agricultural production with the available natural resources to increase foreign earnings.