Search Results (6)

Climate stress poses a threat to the agricultural sector, which is vital for both the economy and livelihoods in general. Quantifying its risk to food security, livelihoods, and sustainability is crucial. This study proposes a framework to estimate the impact climate stress on agriculture in terms of three objectives: assessing the regional vulnerability (exposure, sensitivity, and adaptive capacity), analysing the climate variability, and measuring agricultural performance under climatic stress. The vulnerability of twenty-two sub-regions in Jammu, Kashmir, and Ladakh is assessed using indicators to determine the collective susceptibility of the agricultural framework to climate change. An index-based approach with min–max normalization is employed, ranking the districts based on their relative performances across vulnerability indicators. This work assesses the impact of socio-economic and climatic indicators on the performance of agricultural growth using the benchmark Ricardian approach. The parameters of the agricultural growth function are estimated using a linear combination of socio-economic and exposure variables. Lastly, the forecasted trends of climatic variables are examined using a long short-term memory (LSTM)-based recurrent neural network, providing an annual estimate of climate variability. The results indicate a negative impact of annual minimum temperature and decreasing land holdings on agricultural GDP, while cropping intensity, rural literacy, and credit facilities have positive effects. Budgam, Ganderbal, and Bandipora districts exhibit higher vulnerability due to factors such as low literacy rates, high population density, and extensive rice cultivation. Conversely, Kargil, Rajouri, and Poonch districts show lower vulnerability due to the low population density and lower level of institutional development. We observe an increasing trend of minimum temperature across the region. The proposed LSTM synthesizes a predictive estimate across five essential climate variables with an average overall root mean squared error (RMSE) of 0.91, outperforming the benchmark ARIMA and exponential-smoothing models by 32–48%. These findings can guide policymakers and stakeholders in developing strategies to mitigate climate stress on agriculture and enhance resilience. Full article

The paper aims at the need for economic policy evaluators to assess how and whether specific measures can influence the development of markets in a way that achieves greater wealth. Therefore, this study concentrates on well-documented firms’ heterogeneity that significantly impact their ability to compete, influence the market structure, and decide to participate in trade. For the initial attributes and features of the simulated model, we chose Ottaviano demand function. However, we took a different approach regarding demand and its elasticities in the market by employing distributional functions to model the market demand and the demand for each firm’s product. Allowing for the evolution of the market structure, the model reveals the importance of endowment factors and suggests the crucial role of firms’ abilities to compete. What is more important—it affects the time needed for the market structure formation. Although the model does not track all the aspects of a firm’s heterogeneity, it might guide economic policy makers to not only support the business in increasing its capabilities but keep it struggling over the competition to impede the collecting of Ricardian rents. Full article

Climate change affects crop production by distorting the indestructible productive power of the land. The objective of this study is to examine the economic impacts of climate change on net crop income in Nile Basin Ethiopia using a Ricardian fixed effect approach employing the International Food Policy Research Institute (IFPRI) household survey data for Ethiopia in 2015 and 2016. The survey samples were obtained through a three-stage stratified sampling technique from the five regions (Amhara, Tigray, Benishangul Gumuz, Oromia, and Southern Nation Nationality and People (SNNP) along the Nile basin Ethiopia. There are only 12–14% female household heads while there are 80–86% male households in the regions under study. In the regions, more than half of (64%) the household heads are illiterate and almost only one-tenth of them (12%) had received remittance from abroad from their relatives or children. Crop variety adoption rate is minimal, adopted by the 31% of farmers. Only 30% of the surveyed farmers mentioned that they planted their crop seeds in row whereas the rest 70% had not applied this method. The regression results from the fixed effect least square dummy variable model showed that literacy, household size, remittance, asset value, and total land holdings have significant and positive impacts on the net crop income per hectare. The regional dummy variables estimate indicated that all the regions are negatively affected by climate change at varying levels. Strategies to climate change adaptation have significant and positive contributions in leveraging the damaging effects of climate change. The results also showed that increased winter and summer temperature and rainfall increase net crop income per hectare. The estimated coefficient of the interaction term of spring temperature and rainfall is significant and negative. On the other hand, while the mean annual temperature is damaging to crops, annual rainfall is beneficial. It can be deduced that, while increased temperature and rainfall in summer and winter increase the net crop income, the converse is true for winter and spring seasons. The study also proposes a specific, context-dependent, farm-level adaptation analysis of how farmers cope with the different climatic impacts of the Nile Basin and maintain the income levels that they have previously enjoyed. Full article

Myanmar is the country with the highest economic vulnerability (EV) to climate change in the Southeast Asian region. The dry zone of Myanmar occupies two-thirds of the agricultural lands and it has higher temperatures than elsewhere in the country. Climate change has severe impacts on agricultural production in this region. Moreover, changes in the precipitation patterns increase the likelihood of crop failures in the short-run and production declines in the long run. Therefore, an assessment of the economic impacts of climate change on crop production in the dry zone of Myanmar is very relevant. This paper examines the interactions between agriculture and climate and assesses the economic impact of climate change while using a Ricardian model. A cross-sectional survey covering three regions in the central dry zone: (Magwe, Mandalay, and Sagaing regions) was conducted, yielding a sample of 425 farmers. A non-linear relationship between climate indicators (temperature and precipitation) and revenue of land was found. The marginal effects were calculated by selecting economic and socio-demographic variables. The estimated marginal impacts suggest that the projected changes in temperature will affect the crop productivity of the region. The results also show that the temperature and rainfall components of global warming are both important. Predictions from three global circulation models all confirm that temperature is predicted to increase in all seasons. A significant marginal impact of increasing temperature on the net revenue of farm households was observed in the region. These findings call for policy makers and development planners to articulate the necessary climate change adaptation measures and mitigation options for reducing the negative impacts of climate change. Improved management and conservation of the available water resources could generate water for irrigation purposes and the dissemination of climate smart agricultural practices could lessen the negative impacts of climate change effects on agriculture in the dry zone of Myanmar. Full article

This study uses the Ricardian (hedonic) approach to estimate the impact of potential climate change on agricultural farmland values in the Southeast U.S. as a distinct agricultural region. Using the Agricultural Resource Management Survey and seasonal county-level climate and data, we find that regional farmland values increase with spring and fall temperatures and fall precipitation and decrease with winter and summer temperatures. Long-term climate change projections predict aggregate farmland value losses of 2.5–5% with differential state-level impacts, ranging from large losses in Florida to significant gains in Virginia. The results are consistent with recent research and can be helpful in policy design and forecasting land use change. Full article

This paper investigates the economic impacts of climate change on cereal crop production in Northern Ghana using 240 households comprising maize and sorghum farmers. The Ricardian regression approach was used to examine the economic impacts of climate change based on data generated from a survey conducted in the 2013/2014 farming seasons. Forty-year time-series data of rainfall and temperature from 1974 to 2013, together with cross-sectional data, were used for the empirical analysis. The Ricardian regression estimates for both maize and sorghum showed varying degrees of climate change impacts on net revenues. The results indicated that early season precipitation was beneficial for sorghum, but harmful for maize. However, mid-season precipitation tended to promote maize production. Temperature levels for all seasons impacted negatively on net revenue for both crops, except during the mid-season, when temperature exerted a positive effect on net revenue for sorghum. Our findings suggest that appropriate adaptation strategies should be promoted to reduce the negative impacts of prevailing climate change on cereal crop production. Full article