A Ricardian analysis of Mexican farms

2009 ◽  
Vol 15 (2) ◽  
pp. 153-171 ◽  
Author(s):  
ROBERT MENDELSOHN ◽  
JESUS ARELLANO-GONZALEZ ◽  
PETER CHRISTENSEN
Keyword(s):  
Land Value ◽  
Climate Scenarios ◽  
Economic Data ◽  
Farmland Values ◽  
Large Farms ◽  
The Impact

ABSTRACTThis paper measures the impact of climate on Mexican agriculture using a Ricardian analysis. The analysis relies on economic data from 621 individual farms that were collected in 2002. Data on climate, elevation, soils, and distance to nearest city were matched with each farm. The analysis reveals that farmland values in Mexico are sensitive to climate. On average, warmer temperatures reduce land value by 4,000 to 6,000 pesos per degree Celsius. Examining three climate scenarios for 2100, the models predict average losses of between −42% to −54% of land value in Mexico. As a percent of income, rainfed farms will suffer slightly larger damages than irrigated farms but comparisons between small and large farms are mixed.

scholarly journals Dynamics of soil organic carbon in the steppes of Russia and Kazakhstan under past and future climate and land use

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Susanne Rolinski ◽  
Alexander V. Prishchepov ◽  
Georg Guggenberger ◽  
Norbert Bischoff ◽  
Irina Kurganova ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Soil Organic Carbon ◽  
Arable Land ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Scenarios ◽  
The Impact

AbstractChanges in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.

scholarly journals Impact of Climate Change on Potential Distribution of Chinese White Pine Beetle Dendroctonus armandi in China

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 544
Author(s):  
Hang Ning ◽  
Ming Tang ◽  
Hui Chen
Keyword(s):  
Climate Change ◽  
Potential Distribution ◽  
Greenhouse Gas Emission ◽  
Central China ◽  
Qinling Mountains ◽  
Climate Scenarios ◽  
Impact Of Climate Change ◽  
Precipitation Seasonality ◽  
Suitable Area ◽  
The Impact

Dendroctonus armandi (Coleoptera: Curculionidae: Scolytidae) is a bark beetle native to China and is the most destructive forest pest in the Pinus armandii woodlands of central China. Due to ongoing climate warming, D. armandi outbreaks have become more frequent and severe. Here, we used Maxent to model its current and future potential distribution in China. Minimum temperature of the coldest month and precipitation seasonality are the two major factors constraining the current distribution of D. armandi. Currently, the suitable area of D. armandi falls within the Qinling Mountains and Daba Mountains. The total suitable area is 15.83 × 104 km2. Under future climate scenarios, the total suitable area is projected to increase slightly, while remaining within the Qinling Mountains and Daba Mountains. Among the climate scenarios, the distribution expanded the most under the maximum greenhouse gas emission scenario (representative concentration pathway (RCP) 8.5). Under all assumptions, the highly suitable area is expected to increase over time; the increase will occur in southern Shaanxi, northwest Hubei, and northeast Sichuan Provinces. By the 2050s, the highly suitable area is projected to increase by 0.82 × 104 km2. By the 2050s, the suitable climatic niche for D. armandi will increase along the Qinling Mountains and Daba Mountains, posing a major challenge for forest managers. Our findings provide information that can be used to monitor D. armandi populations, host health, and the impact of climate change, shedding light on the effectiveness of management responses.

scholarly journals Spatial-temporal changes in river runoff and terrestrial ecosystem water retention under 1.5 °C and 2 °C warming scenarios across China

2017 ◽  
Author(s):  
Ran Zhai ◽  
Fulu Tao ◽  
Zhihui Xu
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
River Runoff ◽  
Water Retention ◽  
Terrestrial Ecosystem ◽  
Maximum Temperature ◽  
Climate Scenarios ◽  
Warming Scenario ◽  
Basin Scale ◽  
The Impact

Abstract. The Paris Agreement set a long-term temperature goal of holding the global average temperature increase to below 2.0 ℃ above pre-industrial levels, and pursuing efforts to limit this to 1.5 ℃, it is therefore important to understand the impacts of climate change under 1.5 ℃ and 2.0 ℃ warming scenarios for climate adaptation and mitigation. Here, climate scenarios by four Global Circulation Models (GCMs) for the baseline (2006–2015), 1.5 ℃ and 2.0 ℃ warming scenarios (2106–2115) were used to drive the validated Variable Infiltration Capacity (VIC) hydrological model to investigate the impacts of global warming on river runoff and Terrestrial Ecosystem Water Retention (TEWR) in China. The trends in annual mean temperature, precipitation, river runoff and TEWR were analysed at the grid and basin scale. Results showed that there were large uncertainties in climate scenarios from the different GCMs, which led to large uncertainties in the impact assessment. The differences among the four GCMs were larger than differences between the two warming scenarios. The interannual variability of river runoff increased notably in areas where it was projected to increase, and the interannual variability increased notably from 1.5 ℃ warming scenario to 2.0 ℃ warming scenario. By contrast, TEWR would remain relatively stable. Both extreme low and high river runoff would increase under the two warming scenarios in most areas in China, with high river runoff increasing more. And the risk of extreme river runoff events would be higher under 2.0 ℃ warming scenario than under 1.5 ℃ warming scenario in term of both extent and intensity. River runoff was significantly positively correlated to precipitation, while increase in maximum temperature would generally cause river runoff to decrease through increasing evapotranspiration. Likewise, precipitation also played a dominant role in affecting TEWR. Our findings highlight climate change mitigation and adaptation should be taken to reduce the risks of hydrological extreme events.

scholarly journals Simulation of future climate scenarios and the impact on the water availability in southern Brazil

2021 ◽  
Vol 43 ◽  
pp. e56026
Author(s):  
Gabriela Leite Neves ◽  
Jorim Sousa das Virgens Filho ◽  
Maysa de Lima Leite ◽  
Frederico Fabio Mauad
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
Water Availability ◽  
Meteorological Data ◽  
Future Climate ◽  
Climate Scenarios ◽  
Southern Brazil ◽  
Climate Data ◽  
Intergovernmental Panel ◽  
The Impact

Water is an essential natural resource that is being impacted by climate change. Thus, knowledge of future water availability conditions around the globe becomes necessary. Based on that, this study aimed to simulate future climate scenarios and evaluate the impact on water balance in southern Brazil. Daily data of rainfall and air temperature (maximum and minimum) were used. The meteorological data were collected in 28 locations over 30 years (1980-2009). For the data simulation, we used the climate data stochastic generator PGECLIMA_R. It was considered two scenarios of the fifth report of the Intergovernmental Panel on Climate Change (IPCC) and a scenario with the historical data trend. The water balance estimates were performed for the current data and the simulated data, through the methodology of Thornthwaite and Mather (1955). The moisture indexes were spatialized by the kriging method. These indexes were chosen as the parameters to represent the water conditions in different situations. The region assessed presented a high variability in water availability among locations; however, it did not present high water deficiency values, even with climate change. Overall, it was observed a reduction of moisture index in most sites and in all scenarios assessed, especially in the northern region when compared to the other regions. The second scenario of the IPCC (the worst situation) promoting higher reductions and dry conditions for the 2099 year. The impacts of climate change on water availability, identified in this study, can affect the general society, therefore, they must be considered in the planning and management of water resources, especially in the regional context

scholarly journals Analysis of the Impact LEED-NC Criteria on Appraised Unit Land Value

2012 ◽  
Vol 12 (6) ◽  
pp. 596-606
Author(s):  
Kiyoung Son ◽  
Gwang-Hee Kim ◽  
Young Jun Park ◽  
Sun-Kuk Kim
Keyword(s):  
Land Value ◽  
The Impact

scholarly journals Specificity of transformational processes of management in the context of modern challenges for the system of agricultural relations

2021 ◽  
Vol 941 (1) ◽  
pp. 012002
Author(s):  
Tatiana P Maksimova
Keyword(s):  
National Economy ◽  
Small Businesses ◽  
Agricultural Production ◽  
Economic Effects ◽  
Government Support ◽  
Baseline Scenario ◽  
Economic Management ◽  
Global Pandemic ◽  
Large Farms ◽  
The Impact

Abstract The paper substantiates the relevance of the considered issue, which is associated with the preservation of general contradictions in determining the essential characteristics of modern forms of economic management, their typology, and scenario forecasts for the development of small and large forms of management. The dualistic nature of the results of the transformation of the main forms of economic management in the system of the national economy was explained. The economic effects of transformation processes over two decades were analyzed and compared. It was revealed that: firstly, in the structure of production large farms prevail over the small ones; secondly, similar trends are observed in the dynamics of output volumes; thirdly, over the period under study, these trends remain stable. Scenario forecasts of the main trends in the further development of small and large forms of economic management were determined. The conservative scenario assumes further concentration and oligopolization in the agrarian sphere of the national economy. The baseline scenario assumes the preservation of the existing proportions of large and small forms of farming in the structure of agricultural production. The optimistic scenario assumes that the combination of the phenomenon of the impact of the global pandemic with the improvement of government support instruments for small businesses will increase the level of competitiveness in agricultural production.

Effect of Urban Rail Transit Lines Linking the New Towns on Land Value Uplift in the Megacity Based on Difference-in-Difference Model

2020 ◽  
Vol 2674 (11) ◽  
pp. 317-328
Author(s):  
Junfang Li ◽  
Zhigang Liu ◽  
Jie Yu ◽  
Hua Hu
Keyword(s):  
Urban Rail Transit ◽  
Rail Transit ◽  
Land Value ◽  
Difference In Difference ◽  
Difference Model ◽  
Time Saving ◽  
New Towns ◽  
Business District ◽  
The Impact ◽  
Over Time

There already exist some rail transit lines linking the new towns to the center business district (LTC) in megacities. However, few lines between the new towns (LTT) exist. The paper examines whether, when, and how LTT cause land value uplift with LTC as the benchmark, which in turn can be used for feasibility analysis for value capture financing for the implementation of LTT. Evaluate the value in catchment and control area over time to confirm uplift. Difference-in-difference model (DID) is used to analyze when and how LTT raise the uplift. In the case study of Tokyo, DID estimators show the following homogenous results: firstly, the implicit land value (ILV) of LTT is all lower than LTC except that related to time saving to the center business district (CBD) in the announcement period, implying LTT are expected significantly to link to CBD then; secondly, ILV goes down over time sharply for LTT than LTC, implying the impact of LTT on the uplift is less sustainable than that of LTC; thirdly, sustainability of ILV as to time saving to the capital of the new town is more than that to CBD for LTT; lastly, ILV in the announcement period presents significantly distance-decay performance for both lines. Heterogeneity among the stations is detected for both lines; for LTT, the impact of proximity to the huge interchange station on land value uplift is slight. These results provide an evidence base for policy-makers to quantify the potential to raise financial funding for LTT.

A Novel Method to Improve the Accuracy of Grey Prediction Model in Economic Prediction

2013 ◽  
Vol 347-350 ◽  
pp. 3331-3335
Author(s):  
Qian Ru Wang ◽  
Xi Wei Chen ◽  
Da Shi Luo ◽  
Yu Feng Wei ◽  
Li Ya Jin ◽  
...  
Keyword(s):  
System Theory ◽  
Time Series Data ◽  
Grey System Theory ◽  
Series Data ◽  
Model Parameters ◽  
Economic Data ◽  
Grey System ◽  
Forecasting Accuracy ◽  
Highly Nonlinear ◽  
The Impact

Grey system theory has been widely used to forecast the economic data that are often highly nonlinear, irregular and non-stationary. Many models based on grey system theory could adapt to various economic time series data. However, some of these models didnt consider the impact of the model parameters, or only considered a simple change of the model parameters for the prediction. In this paper, we proposed the PSO based GM (1, 1) model using the optimized parameters in order to improve the forecasting accuracy. The experiment shows that PSO based GM (1, 1) gets much better forecasting accuracy compared with other widely used grey models on the actual chaotic economic data.

Societal impact of university innovation

2018 ◽  
Vol 41 (11) ◽  
pp. 1309-1335 ◽  
Author(s):  
Benjamin Yeo
Keyword(s):  
Economic Performance ◽  
Significant Proportion ◽  
Economic Data ◽  
Regional Economic ◽  
Content Type ◽  
Economic Productivity ◽  
Multiple Variables ◽  
Regional Economic Performance ◽  
The Impact ◽  
University Patent

PurposeThis study aims to use university patent and regional economic data to investigate the current and future impact of university innovation, measured using multiple variables, on real economic productivity.Design/methodology/approachUsing university patent and regional economic data, regression models are built to determine the impact of university innovation on current and future regional economic performance.FindingsThe findings demonstrate that university innovation generates sustained impact on economic performance, but by itself, is insufficient in driving economic performance; and different measures of university innovation have different degrees of impact. University innovation makes up a small, albeit significant, proportion of the drivers of economic performance.Research limitations/implicationsThere are four implications. First, developing countries can leverage university–industry collaborations for economic growth. Second, innovation management must encourage continuous university innovation for sustainable economic productivity. Third, Science, Technology, Engineering and Mathematics (STEM) and non-STEM innovation warrant attention. Fourth, successful innovation policies should be tailored to their unique societal contexts.Originality/valueAlthough innovation is a driver of economic performance, there is a lack of studies that focus specifically on universities, operationalize performance using gross domestic product measures and take into account impact lags by exploring universities’ current and future impacts.

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