scholarly journals Historical Impacts of Precipitation and Temperature on Farm Production in Kansas

2014 ◽  
Vol 46 (4) ◽  
pp. 439-456 ◽  
Author(s):  
David K. Lambert
Keyword(s):  
Risk Management ◽  
Negative Temperature ◽  
Weather Effects ◽  
Temperature And Precipitation ◽  
Farm Production ◽  
On Farm ◽  
The Impact ◽  
Precipitation And Temperature

We quantify weather effects on output and incomes for a panel of Kansas farmers. The effects of weather are largely asymmetric with negative temperature and precipitation values affecting output and income differently than above average observations. Precipitation effects depend on timing and seasonal averages. The number of days exceeding 32.2°C (i.e., the “hot” years) negatively impacts production and income measures, although the impact is positive for crop output in the cooler years. The results indicate the importance of including weather in predicting output and income and designing risk management instruments to mitigate weather trends and variability.

scholarly journals Does Participation in Agricultural Cooperatives Affect Farm Sustainability? Empirical Evidence from Taiwan

2019 ◽  
Vol 11 (18) ◽  
pp. 4987 ◽  
Author(s):  
Bo Wang ◽  
Po-Yuan Cheng ◽  
Brian Lee ◽  
Lih-Chyun Sun ◽  
Hung-Hao Chang
Keyword(s):  
Farm Households ◽  
Agricultural Cooperatives ◽  
Food Labels ◽  
Potential Mechanism ◽  
Farm Production ◽  
Causal Mediation Analysis ◽  
Nationally Representative ◽  
Farm Sustainability ◽  
On Farm ◽  
The Impact

Recent research has highlighted the importance of agricultural cooperatives on farm production. Although the consensus from the literature suggests that participating in these organizations significantly affects farm production, there is inconclusive evidence on whether this effect is positive or negative. Moreover, previous studies solely focus on the magnitude of this effect and fail to explain the mechanism behind it. This study contributes to this knowledge gap by estimating the impact of agricultural cooperatives on farm profits. To do this, we apply the causal mediation analysis to explain the potential mechanism behind this relationship. Using a nationally representative survey of farm households from Taiwan in 2013, we find that participating in cooperatives increases farm profits. Furthermore, this effect is more pronounced for producers with higher profits. Concerning the mechanism, we find that the use of food labels accounts for approximately 15 to 28% of the total effect of cooperative participation on farm profits.

scholarly journals Mobilitas Sirkuler Daya Faktor-faktor Yang mempengaruhinya Di Desa Sidorejo Kec Ponjong Kab Gunung Kidul = Circular Mobility And The Factors Influencing It In Sidorejo Village Ponjong Sub District Gunung Kidul Regency

Agro Ekonomi ◽  
2016 ◽  
Vol 10 (1) ◽  
pp. 48
Author(s):  
Utami A Yulianti ◽  
Mas Sadjono ◽  
Slamet Hartono
Keyword(s):  
Affecting Factors ◽  
Factors Affecting ◽  
Farm Production ◽  
Rural Income ◽  
Wage Ratio ◽  
Urban Rural ◽  
Land Size ◽  
Farmer Income ◽  
On Farm ◽  
The Impact

The research aims to find out the factors affecting the circular mobility and the impact of circular mobility on farm production and farmers income.Primary data are .from sample farmers migrant and non migrant. The sample size is 70. The data analyzed by logit model and by difference mean testThe result showed. the affecting factors to circular mobility are. ll. The rural income is negatif flea. 2). Land size is posilif affect 3). wage ratio urban rural negatif affect, The impact of circular mobility increas production and .farmer income. The income ofmigrant familly is Rp -1722611 per year and Rp 2848168 per year for non migrant. The mobility activity contributed higher peoduction and income for migran.

scholarly journals The Impact of Agricultural Extension on Farm Production in Resettlement Areas of Zimbabwe

2003 ◽  
Vol 51 (2) ◽  
pp. 337-357 ◽  
Author(s):  
Trudy Owens ◽  
John Hoddinott ◽  
Bill Kinsey
Keyword(s):  
Agricultural Extension ◽  
Farm Production ◽  
On Farm ◽  
The Impact

Spatiotemporal Analysis of Vegetation Cover and Its Response to Terrain and Climate Factors in Duhok Governorate, Kurdistan Region, Iraq

2020 ◽  
Vol 54 (1A) ◽  
pp. 110-126
Author(s):  
Rebar Mzuri
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Temporal Distribution ◽  
Spatiotemporal Analysis ◽  
Climate Data ◽  
Remarkable Change ◽  
Temperature And Precipitation ◽  
Landsat Satellite ◽  
The Impact ◽  
Precipitation And Temperature

The integration of remote sensing techniques and Geographic Information System has a wide use to quantify the spatial and temporal distribution of vegetation cover. Over the last decade, a remarkable change was noticed in both climate and vegetation cover in Duhok. The Modified Soil Adjusted Vegetation Index (MSAVI2) was extracted from Landsat satellite images over the 20 years (2000 to 2019). For analyzing the vegetation changes, the terrain data including elevation, slope, and aspect and climate data temperature and precipitation are used. The result shows that from 2000–2019, the average mean MSAVI2 is 0.361 and the trend increased in 77.9% of the study area. The northern and northeastern areas of the study area revealed a significant increase in vegetation, while in the low land areas it is decreased. The amount of precipitation and temperature degree affect the spatiotemporal distribution of vegetation cover. The MSAVI2 showed a positive relationship with precipitation and temperature. At elevation less than 2000 m, with increasing elevation the MSAVI2 is increasing, but when the elevation reaches 2000 m, the MSAVI2 is decreasing and negatively related to elevation. The vegetation has a positive relation with slopes less than 45°, and at slopes higher than 45°, the MSAVI2 is decreased. The impact of aspect on the vegetation figured out that the largest MSAVI2 is detected in the shady slope due to relatively less evapotranspiration.

scholarly journals Bio-economic modelling of decisions under yield and price risk for suckler cow farms

2015 ◽  
Vol 55 (1) ◽  
pp. 64 ◽  
Author(s):  
Simon Briner ◽  
Niklaus Lehmann ◽  
Robert Finger
Keyword(s):  
Risk Management ◽  
Management Strategies ◽  
Economic Modelling ◽  
Gross Margin ◽  
Farm Model ◽  
Weather Risk ◽  
Risk Management Strategies ◽  
Margin Insurance ◽  
On Farm ◽  
The Impact

Applying a bio-economic whole-farm model, we assess the impact of price and weather risk as well as different risk-management strategies on the variability of the gross margin in Swiss suckler cow production. For instance, flexible adjustment of fodder composition, feed stocks, or land use as well as gross margin insurance are considered. Our results show that assuming moderate risk aversion farms’ gross margin variability is rather high, with a coefficient of variation of gross margin ranging from 19 to 21%. Accounting for on-farm risk-management strategies we find that gross margin variability can be reduced significantly, causing only low reductions of average gross margin levels. We find that the use of maize as a switch crop and a market for the trade of roughage are the most efficient risk-management strategies. Our results also indicate that gross margin insurance is not attractive for farmers. Thus in particular promoting better access to markets for feedstuffs provides a valuable opportunity for farmers to manage gross margin risks.

Effect of agricultural policy on income and revenue risks in Italian farms

2017 ◽  
Vol 77 (2) ◽  
pp. 295-311 ◽  
Author(s):  
Simone Severini ◽  
Antonella Tantari ◽  
Giuliano Di Tommaso
Keyword(s):  
Risk Management ◽  
Agricultural Policy ◽  
Robust Regression ◽  
National Sample ◽  
Farm Size ◽  
Farm Income ◽  
Management Behavior ◽  
Content Type ◽  
Farm Production ◽  
The Impact

Purpose The purpose of this paper is to assess how direct payments (DPs) of the Common Agricultural Policy affect income and revenue variability faced by Italian farmers. Design/methodology/approach Balanced farm-level panel data are used to construct coefficients of variation over the period 2003-2012. Nonlinear robust regression techniques are used to measure the effect of DP, farm size, fixity in resources, labor intensity, farm production orientation, and specialization on the variability of farm income (FI) and farm revenue. This is done on the overall sample as well as on subsamples of farms located in different regions and belonging to different types of farming. Findings DPs have mixed effects on the variability of FI. While a negative and significant relationship is found on the whole national sample, this is not generally the case when models are run on the considered subsamples. On the contrary, DPs have always significant variability increasing effects on revenue. This suggests that DPs reduce the degree of risk that farmers face allowing them to engage in riskier activities. Thus, DPs are less effective than expected in terms of income stabilization because these distort farmers’ risk management behavior. Because of this, DPs could constrain the development of markets for risk management instruments and reduce the effectiveness of policies supporting the use of these instruments. Originality/value The analysis is inspired by El Benni et al. (2012) but uses a different approach, applies it to a different country, and yields different results. Volatility measures are calculated over more years, and the paper accounts for differences in farm production orientation and is not based on an unbalanced panel of farms. Because of these differences, the authors obtained different results regarding the correlation between DP and income and, even more, revenue variability. Finally, comparing the results of models referring to FI and farm revenue improves the author’s understanding of the impact of DP on farmers’ risk management behavior and allows interesting policy considerations.

scholarly journals Impact of correcting sub-daily climate model biases for hydrological studies

2021 ◽  
Author(s):  
Mina Faghih ◽  
François Brissette ◽  
Parham Sabeti
Keyword(s):  
Diurnal Cycle ◽  
Bias Correction ◽  
Time Scale ◽  
Climate Model ◽  
Temperature And Precipitation ◽  
Diurnal Cycle Of Precipitation ◽  
The Impact ◽  
Small Catchments ◽  
Precipitation And Temperature ◽  
Daily Time

Abstract. The study of climate change impact on water resources has accelerated worldwide over the past two decades. An important component of such studies is the bias correction step, which accounts for spatiotemporal biases present in climate model outputs over a reference period, and which allows realistic streamflow simulations using future climate scenarios. Most of the literature on bias correction focuses on daily scale climate model temporal resolution. However, a large amount of regional and global climate simulations are becoming increasingly available at the sub-daily time step, and even extend to the hourly scale, with convection-permitting models exploring sub-hourly time resolution. Recent studies have shown that the diurnal cycle of variables simulated by climate models is also biased, which raises issues respecting the necessity (or not) of correcting such biases prior to generating streamflows at the sub-daily time scale. This paper investigates the impact of bias-correcting the diurnal cycle of climate model outputs on the computation of streamflow over 133 small to large North American catchments. A standard hydrological modeling chain was set up using the temperature and precipitation outputs from a high spatial (12-km) and temporal (1-hour) regional climate model large ensemble (ClimEx-LE). Two bias-corrected time series were generated using a multivariate quantile mapping method, with and without correction of the diurnal cycles of temperature and precipitation. The impact of this correction was evaluated on three small (< 500 km2), medium and large (> 1000 km2) surface area catchment size classes. Results show small but systematic improvements of streamflow simulations when bias-correcting the diurnal cycle of precipitation and temperature. The greatest improvements were seen on the small catchments, and least noticeable on the largest. The diurnal cycle correction allowed for hydrological simulations to accurately represent the diurnal cycle of summer streamflow on small catchments. Bias-correcting the diurnal cycle of precipitation and temperature is therefore recommended when conducting impact studies at the sub-daily time scale on small catchments.

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