Climate change influences on agricultural research productivity

RePEc: Research Papers in Economics, 2002

c Differences in estimates of the impact of climate change on U.S. agriculture can be explained the failure to adequately allow for differences between rain-fed and irrigated agriculture as well as urban influences. We derive feasible GLS weights to obtain an efficient estimator and unbiased test statistics. A 1ayesian outlier analysis shows that irrigated and urban counties can not be pooled with dryland counties. When we limit the analysis to dryland and non-urban counties, the different damage estimators from previous studies overlap and the confidence intervals are cut by up to half. Dryland agriculture is unambiguously damaged under the CO2 doubling scenario. JEL Ql, Q2, C5) We gratefully acknowledge comments on an earlier draft by John

2020 Annual Meeting, July 26-28, Kansas City, Missouri, 2020

International Journal of Global Warming, 2015

The increased frequency and severity of drought episodes have characterised the natural environment of the Sahel region in Africa during the past four decades. With little to no mitigation option available to them, countries of the Sahel will face a further deterioration of their economic environment, as an ill-agricultural sector will most likely drag down their whole economies. This paper uses a six-month standardised precipitation index and average temperature during the growing season days to quantify the adverse impacts of climate change on agricultural productivity. I first estimate a Malmquist productivity index and its efficiency and technical change components. I further assess the statistical significance of the indices by estimating confidence intervals around the point estimates using a bootstrap method. In the second stage of the analysis, I model the adverse effects of drought and temperature on agricultural productivity using a probit specification. The findings of this paper point to a dismal agricultural productivity. These findings also highlight the significant cumulative negative impacts of higher temperatures and recurrent droughts on agricultural-based economies.

RePEc: Research Papers in Economics, 2012

Global warming has been an issue lately in many aspects because it has been in increasing trend since 1980s. This paper estimates the climate change effects on U.S. agriculture using the pooled cross-section farm profit model. The data are mainly based on the annual Agricultural Resource Management Survey (ARMS) from USDA for the time period between 2000 and 2009 in the 48 contiguous States. For climate measure, growing season drought indices (the Palmer Drought Severity Index (PDSI) and Crop Moisture Index (CMI)) are applied to the analysis and both indices have a negative relationship with temperature. The estimates indicate that one unit increase in PDSI (CMI) leads to 5.5% (13.9%), 4% (9%), and 5% (14%) increase in farm profits for all farms, crop farms, and livestock farms. This paper provides several contributions to the literature. First, the data set is very rare and unique national survey that provides an individual farm level observation. Therefore, it gives more detailed farm structure and financial information for the analysis compared to other studies. Second, drought indices (PDSI and CMI) are used for estimating the impact of weather on farm profits while temperature, precipitation, and growing degree-days are typical weather variables in literatures.

Review of Economics and Statistics, 2006

We link farmland values to climatic, soil, and socioeconomic variables for counties east of the 100th meridian, the historic boundary of agriculture not primarily dependent on irrigation. Degree days, a non-linear transformation of the climatic variables suggested by agronomic experiments as more relevant to crop yield gives an improved fit and increased robustness. Estimated coefficients are consistent with the experimental results. The model is employed to estimate the potential impacts on farmland values for a range of recent warming scenarios. The predictions are very robust and more than 75% of the counties in our sample show a statistically significant effect, ranging from moderate gains to large losses, with losses in the aggregate that can become quite large under scenarios involving sustained heavy use of fossil fuels.

Climatic Change, 2000

We examined the impacts on U.S. agriculture of transient climate change as simulated by 2 global general circulation models focusing on the decades of the 2030s and 2090s. We examined historical shifts in the location of crops and trends in the variability of U.S. average crop yields, finding that non-climatic forces have likely dominated the north and westward movement of crops and the trends in yield variability. For the simulated future climates we considered impacts on crops, grazing and pasture, livestock, pesticide use, irrigation water supply and demand, and the sensitivity to international trade assumptions, finding that the aggregate of these effects were positive for the U.S. consumer but negative, due to declining crop prices, for producers. We examined the effects of potential changes in El Niño/Southern Oscillation (ENSO) and impacts on yield variability of changes in mean climate conditions. Increased losses occurred with ENSO intensity and frequency increases that could not be completely offset even if the events could be perfectly forecasted. Effects on yield variability of changes in mean temperatures were mixed. We also considered case study interactions of climate, agriculture, and the environment focusing on climate effects on nutrient loading to the Chesapeake Bay and groundwater depletion of the Edward's Aquifer that provides water for municipalities and agriculture to the San Antonio, Texas area. While only case studies, these results suggest environmental targets such as pumping limits and changes in farm practices to limit nutrient run-off would need to be tightened if current environmental goals were to be achieved under the climate scenarios we examined

Australian Journal of Agricultural and Resource Economics, 2010

This article empirically examines the impact of R&D and climate change on the Western Australian Agricultural sector using standard time series econometrics. Based on historical data for the period of 1977-2005, the empirical results show that both R&D and climate change matter for long-run productivity growth. The long-run elasticity of total factor productivity (TFP) with respect to R&D expenditure is 0.497, while that of climate change is 0.506. There is a unidirectional causality running from R&D expenditure to TFP growth in both the short run and long run. Further, the variance decomposition and impulse response function confirm that a significant portion of output and productivity growth beyond the sample period is explained by R&D expenditure. These results justify the increase in R&D investment in the deteriorating climatic condition in the agricultural sector to improve the long-run prospects of productivity growth.

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Agricultural productivity, and the degree to which other inputs (such as fertilizer, pesticides, and irrigation) are needed to augment production, depend a great deal on local climate conditions. Increases in average temperature, changes in precipitations patterns, and increases in the frequency of extreme weather events would significantly alter local production environment, through the distribution of crop yields, crop acreage planted to different crops, reliance on dryland and irrigated production systems, and the geographic range and severity of pest outbreaks. Changes in water availability for crop production will be an important factor affecting regional agricultural production. Shifting precipitation patterns in

Mitigation and Adaptation Strategies for Global Change, 2000

This paper presents a conceptual framework of the impact of climate change on agriculture. It assumes that climate change will result in a fertilization effect and a shift of agro-ecological conditions away from the Equator towards the Poles. The agro-ecological shift is likely to reduce yield because of reduced acreage and the fertilization effect will increase yield. The aggregate effect depends on whichever of the two dominates. The overall effect of climate change may be less significant than its distributional effects and the results are consistent with previous empirical studies. The impact of climate change depends on its pace. Faster changes in climate will result in higher cost. The assessment of the cost has to consider that climate change is a dynamic phenomenon that may require continuous adjustment. Environmental regulation that emphasizes conservation may increase cost of adjustment and environmental policies should emphasize adaptation and flexibility.

Frontiers in sustainable food systems, 2024

Climate change is expected to have differential impacts on different zones. In this study, we employed the Ricardian technique, estimated through ordinary least squares (OLS) to assess the impact of climate change on farmers' revenue. We use survey data from two distinct agroecological zones in Cameroon. Our results show that rainfall is the main climatic variable affecting farmers' revenue. The results are statistically different for the two agroecological zones. While rainfall in the dry season affects revenue in the western highland zone. No climatic variable seems to affect farm revenue in the bimodal forest zone. These results suggest that the abundance of forest in the bimodal zone maybe be shielding the zone from the effects of climate change. We therefore recommend that farmers employ water harvesting and low-cost irrigation methods to cope with changes in rainfall pattern especially in extended dry seasons. Facilitating farmers' access to climate information particularly with respect to the onset and cessation of rains will improve the planning of farm operations.