<p>Mumbai: A research team led by the <a href="https://www.deccanherald.com/tags/goa">Goa</a> Institute of Management has developed a satellite-based framework to evaluate the effectiveness of government <a href="https://www.deccanherald.com/tags/agriculture">agricultural</a> policies even in the absence of traditional survey data, offering a new approach to policy assessment in developing countries where data gaps often hamper welfare evaluation.</p><p>The study, led by Prof. Muddasir Ahmad Akhoon of GIM in collaboration with researchers from Azim Premji University and Indian Institute of Management Ahmedabad, has been published in the <em>Journal of Agricultural Economics</em>.</p><p>The research comes at a time when governments across India are spending thousands of crores on farm subsidies, cash-transfer schemes and rural welfare programmes, while policymakers increasingly face questions about the actual impact of such interventions on productivity and livelihoods.</p><p>Researchers said the framework combines satellite imagery with econometric methods to assess large-scale public welfare schemes where baseline survey data is unavailable — a common challenge in many developing regions.</p><p>The study focused on Telangana’s Rythu Bandhu scheme, launched in 2018 to provide financial assistance to landowning farmers. Researchers noted that the lack of pre-implementation survey data made it difficult to independently measure the programme’s impact.</p><p>To address this, the team analysed satellite images from areas within a 10-km strip along Telangana’s border with neighbouring states. These regions shared similar agricultural and environmental conditions but differed in exposure to the scheme.</p><p>“One of the biggest challenges in developing countries is that policies often remain unevaluated due to the absence of reliable baseline data,” said Prof. Akhoon. “This study shows satellite data can fill that gap rigorously and at scale.”</p>.Why India’s farmers may be left behind in the upcoming Union Budget.<p>The researchers monitored nearly 100,000 agricultural locations over time using satellite imagery. The study found that cash transfers under the Rythu Bandhu scheme increased agricultural productivity during the kharif season by around 1.47 to 2.05 per cent compared to neighbouring regions that did not receive similar support.</p><p>Rice, wheat and maize also recorded measurable productivity gains, with researchers noting that direct cash support could particularly benefit rainfed farming systems vulnerable to weather uncertainty and financial stress.</p><p>Experts say the study highlights the growing role of satellite technology and data analytics in governance and policy evaluation. With climate change, erratic monsoons and rural distress increasingly affecting agriculture, accurate and timely assessment of farm interventions is becoming critical for both state and central governments.</p><p>Dr. Abhishek Shaw, Assistant Professor at Azim Premji University, said the framework was tested using multiple satellite systems and historical datasets to ensure reliable results.</p>
<p>Mumbai: A research team led by the <a href="https://www.deccanherald.com/tags/goa">Goa</a> Institute of Management has developed a satellite-based framework to evaluate the effectiveness of government <a href="https://www.deccanherald.com/tags/agriculture">agricultural</a> policies even in the absence of traditional survey data, offering a new approach to policy assessment in developing countries where data gaps often hamper welfare evaluation.</p><p>The study, led by Prof. Muddasir Ahmad Akhoon of GIM in collaboration with researchers from Azim Premji University and Indian Institute of Management Ahmedabad, has been published in the <em>Journal of Agricultural Economics</em>.</p><p>The research comes at a time when governments across India are spending thousands of crores on farm subsidies, cash-transfer schemes and rural welfare programmes, while policymakers increasingly face questions about the actual impact of such interventions on productivity and livelihoods.</p><p>Researchers said the framework combines satellite imagery with econometric methods to assess large-scale public welfare schemes where baseline survey data is unavailable — a common challenge in many developing regions.</p><p>The study focused on Telangana’s Rythu Bandhu scheme, launched in 2018 to provide financial assistance to landowning farmers. Researchers noted that the lack of pre-implementation survey data made it difficult to independently measure the programme’s impact.</p><p>To address this, the team analysed satellite images from areas within a 10-km strip along Telangana’s border with neighbouring states. These regions shared similar agricultural and environmental conditions but differed in exposure to the scheme.</p><p>“One of the biggest challenges in developing countries is that policies often remain unevaluated due to the absence of reliable baseline data,” said Prof. Akhoon. “This study shows satellite data can fill that gap rigorously and at scale.”</p>.Why India’s farmers may be left behind in the upcoming Union Budget.<p>The researchers monitored nearly 100,000 agricultural locations over time using satellite imagery. The study found that cash transfers under the Rythu Bandhu scheme increased agricultural productivity during the kharif season by around 1.47 to 2.05 per cent compared to neighbouring regions that did not receive similar support.</p><p>Rice, wheat and maize also recorded measurable productivity gains, with researchers noting that direct cash support could particularly benefit rainfed farming systems vulnerable to weather uncertainty and financial stress.</p><p>Experts say the study highlights the growing role of satellite technology and data analytics in governance and policy evaluation. With climate change, erratic monsoons and rural distress increasingly affecting agriculture, accurate and timely assessment of farm interventions is becoming critical for both state and central governments.</p><p>Dr. Abhishek Shaw, Assistant Professor at Azim Premji University, said the framework was tested using multiple satellite systems and historical datasets to ensure reliable results.</p>