Pham Thi Kim Phung
Master in Public Policy Programme, Fulbright School,
Ho Chi Minh City, Vietnam
Agriculture is highly dependent on natural condition (climate, soil, water), specifically in tropical regions, with many of the poorest countries, climate change impacts on agricultural productivity are expected to be particularly harmful and to be difficult in poverty reduction (Kurukulasuriya and Rosenthal, 2003). In Vietnam, rice cultivation is still the most important agricultural activity which has lasted about 4000 years to now. The objective of this study include:
- to quantify the potential climate factors on the farmers’ net rice revenue in Vietnam.
- to predict the potential future impacts on Vietnam’s rice agriculture under the climate change scenarios.
- to inform messages using the empirical results from the study in order to minimise the losses caused by climate change.
This study uses the Ricardian approach which presumes that land economic rent would reflect the net productivity of farmland and land also sensitive to climate. The farmland value (V), reflects the present value of future net productivity, captured by the following equation (Mendelsohn & Dinar 2003):
The approach was given some assumptions. These are (i) long-term intertemporal effects resemble the cross sectional effects of the specific year measured; (ii) the farmers make a series of production choices aimed at maximizing profit; (iii) the farm households are price takers in the model and hence individual farmers have no impact on market prices or competitive land market. Then the estimated specification of net revenues per hectare, PLE, can be written as follows:
Accordingly, the marginal impact of a single climate variable on net farm revenue depend on the coefficients of climatic varialbes in the regression which is being used and the climate which is being evaluated at the mean of each of the variables as follows:
The annual marginal effect can be calculated as the sum of the seasonal marginal effects. The change in welfare, ?V, resulting from a climate change from F0 to F1 can then be measured as follows:
The study was based on data from a Vietnam Household Living Standard Surveying 2008 (VHLSS, 2008), conducted by General Statistics Office included information of revenue, expenditure and some social-econonmic characteristics of 9818 households interviewed across the country. The temperature and precipitation data of 120 weather stations came from Ministry of Agriculture & Rural Development (2001-2010) and soil data, which were made available by FAO (2010) have classified into 28 main solid groups.
Climate variables are mainly of monthly temperature and precipitation data categorised into the distinct seasons. As typical of monsoonal tropical regions, the precipitation in Vietnam also differs significantly by seasons. In general, rainy season lasts from May to October and dry season last November to April of next year. However the duration of season can be changeable by climatic regions if we suppose that the rainy season are of continuous months with precipitation equal to or more than 100mm/month (Figure 1).
Figure 1 Month mean precipitation total and Month mean temperature of seasons by climatic regions
Soil variables included the dominant main soil groups are Acrisols, Gleysols, Fluvisols and Arenosols which occupy 92 percent main soil groups in Vietnam.
Figure 2 Variables affect to net rice revenue in Vietnam
Socio-economic variables included in the estimation are age, sex, completed educational grade (in 12 years programme), ethnicity dummy, household size, total cropped area, only rice growing dummy, irrigation dummy, selling rice to middle-man, retail, no-farm, credict access, extension contact.
Geographic Information System is regarded as a spatially powerful tool to integrate the data sets into the econometric model such as VHLSS, Climate, Soil, and Elevation. As a result, 4279 rice growing households were extracted with some specific criteria. (Figure 2).
Figure 3 Map of Rice Site Distribution for Quantity Analysis
Hình 3 Map of Rice Site Distribution for Quantity Analysis
Net rice revenue is finally regressed against various climate, soil, hydrological and socio-economic variables to help determine the factors that influence variability in net farm revenues presented in Table 1 as follow:
Table 1 Regressions of Net Rice Revenue
According to formula (2), marginal effects of seasonal temperature and precipitation on change in net rice revenue presented in Table 2
Table 2 Marginal effects of climate variables on net rice revenue
Trends of climate variables which impact on net rice revenue include the function is U-shaped (temperature and precipitation in rainy season) and the function is hill-shaped (temperature and precipitation in rainy season) (Figure 4). However, based on agronomic research and previous cross-sectional analyses it is expected that farm values will have a hill-shaped relationship with temperature (Benhin, 2008).
Figure 4 Trends of climate variables impact on net rice revenue
Accordingly, we can see that rice cultivation is currently grown at current average temperatures and precipitations are already over to optimum, except for precipitations in dry season. However, based on the median emission scenarios by MONRE, it is shown that average temperature have increase about 3oC and precipitations have increase to 5% in rainy season but have fall about 5% in dry season by the end of 21 century (MONRE, 2009). Consequently, rice farmer in Vietnam would suffer larger adverses by climate change and its losses would be averagely up to 15% compared to average net rice revenue in 2008. The results also shows that climatic regions which are close to equator might be more vulnerable (Figure 5). Especially South Central and South may likely to be damaged at the most dramatic losses . In addition, losses might reduce in higher latitude regions and even may benefit in specific sites of the north where almost ethnic-minority groups are living under the deficit conditions such as difficulty of transport, unstable production and lower productivity.
Figure 5 Map of Prediction of climate change impacts in 2100vào nam 2100
Ricardian approach has been highly evaluated as this approches automatically captures the farmers’ adaptation to maximun their profit. The important policy messages from the empirical findings are that to protect for rice cultivation land, especially to maintain the soil quality and resilience and to adapt to increased temperatures by irrigation using, especially solutions for efficient water use in the dry season. Other policies which could increase farmers’net rice revenue include labours contribution, selling rice to middleman and to retail, accessing extension center in commune. However, it is considerably concerned for credit support, ethnic-minority farmer, the number of rice crops cultivated in year because these factors have the negative effects to net rice revenue.
Limitations of this study are unavoidable such as access to long-term climate data and further analysis for rice agriculture in Vietnam a miss. The rice cultivation location beyond the scope of the weather station and its spatial surface error would influence on the outcome of this study. In addition, this study didn’t measure the impacts of CO2 which would mainly causes the climate change. If CO2 content has increased due to industiral production particularly in developed countries, it is also due to from deforestation and forest degradation of developping countries (WB, 2010). Thus, reforesting and sustainable forest management in Vietnam need to be highly paid attention due to consequence of remnats in the wars and sort-term economic befefits now. Climate change is a global issue which impose the collaborate of the whole world. A part from national policies, assistance of international organisations must bring the benefits to rice farmers in sustainable development future.
REFERENCES
Vietnamese documents
- GSO (2001-2010), Niên giám th?ng kê Vi?t Nam các nam 2001 – 2010, NXB Th?ng kê, Hà N?i.
- Ð? Nguyên H?i và Hoàng Van Mùa (2007), Giáo trình phân lo?i d?t và xây d?ng b?n d? d?t, Tru?ng Ð?i h?c nông nghi?p Hà N?i.
- MARD (2001-2010). “D? li?u th?i ti?t 2001 – 2010”, B? Nông nghi?p và Phát tri?n Nông thôn, truy c?p ngày 4/9/2011 t?i d?a ch?: www.fsiu.mard.gov.vn/data/khituong.htm.
- MONRE (2009), K?ch b?n bi?n d?i khí h?u và nu?c bi?n dâng cho Vi?t Nam, B? Tài Nguyên và Môi Tru?ng.
- WB (2010), Báo cáo phát tri?n th? gi?i 2010: Phát tri?n và bi?n d?i khí h?u, Washington DC, USA.
English documents
- Benhin (2008), Climate change and South African agriculture: impacts and adaptation options, Centre for Environmental Economics and Policy in Africa, University of Pretoria, South Africa
- FAO (2009), “Harmonize World Soil Database”, FAO, truy v?p ngày 8/11/2011 t?i d?a ch?: https://www.fao.org/nr/land/soils/harmonized-world-soil-database/en/
- Kurukulasuriya and Rosenthal (2003), Climate Change and Agriculture: A Review of Impacts and Adaptations, World Bank, Washington DC, USA.
- Mendelsohn, Dinar, Basist, et al. (2004), “Cross-sectional analyses of climate change impacts”, Policy Research Working Paper 3350, World Bank. Washington DC, USA.
- SRTM30 (2000), “World Elevation Database”, Diva-gis, truy v?p này 4/9/2011 t?i d?a ch?: https://diva-gis.org/datadown
