MINISTRY OF EDUCATION AND TRAINING CAN THO UNIVERSITY SUMMARY OF DOCTORAL DISSERTATION Major: Agricultural Economics Code: 62621015 LE THI KIM LOAN ANALYZING THE IMPACT OF SALINITY
INTRODUCTION
Study Objectives
Analyzing the impact of salinity intrusion on the livelihoods of poor households in rural areas of the Mekong Delta to propose solutions to help households apply appropriate livelihood strategies to reduce damage caused by salinity intrusion, stabilize their livelihoods, and reduce sustainable poverty
(i) Compare the differences in rural households' livelihoods between different salinity intrusion areas
(ii) Analyze the impact of salinity intrusion on the livelihoods of poor households in rural areas of the Mekong Delta
(iii) Propose solutions to help households apply appropriate livelihood strategies to reduce damage caused by salinity intrusion, stabilize livelihoods, and reduce poverty sustainably.
Research Question and Hypothesis
(i) Are the sources of livelihood capital, livelihood strategies, and livelihood outcomes (income and poverty) of rural households in areas with frequent salinity intrusion different from other areas?
(ii) What is the impact of salinity intrusion on the livelihood capital, livelihood strategies, and livelihood outcomes (income) of poor households?
(iii) What is the solution to help households apply appropriate livelihood strategies to reduce damage caused by salinity intrusion, stabilize livelihoods, and reduce poverty sustainably?
(i) The sources of livelihood capital, livelihood strategies, and livelihood outcomes (income and poverty status) of rural households in areas with frequent salinity intrusion are different from those in other areas
(ii) Salinity intrusion affects the livelihood capital, livelihood strategies, and livelihood outcomes (income) of poor households more severely than those of non-poor households
(iii) Some solutions to appropriate livelihood strategies will help households reduce damage caused by salinity intrusion, stabilize their livelihoods, and reduce poverty sustainably.
Research scope
The research object of this thesis is to analyze the impact of salinity intrusion on the livelihoods of poor households in the rural Mekong Delta The livelihoods of rural households affected by salinity intrusion include livelihood capital, livelihood strategies, and livelihood outcomes expressed through income In particular, the study focuses on examining the heterogeneous impacts of salinity intrusion on the livelihoods of poor households compared to non-poor households in the region Therefore, the subject of the thesis's survey is rural households in the Mekong Delta with agricultural livelihoods to compare the impact of salinity intrusion on poor and non-poor households
The selected provinces demonstrate the impact of salinity intrusion from the west coast through the Cai Lon river branch and the east coast through the Tien and Hau river branches Therefore, the appropriate research area for the thesis is the rural areas of four provinces in the Mekong Delta region, including Ben Tre, Tra Vinh, Hau Giang, and Soc Trang
To compare the impact of salinity intrusion on first-time and permanent salinity intrusion households, the major salinity intrusion
4 event in the dry season of 2015–2016 is used to measure changes in household livelihoods before and after being affected Panel data of rural households in four Mekong Delta provinces is taken from the Household
Living Standards Survey Data Set 2014 (two years before impact) and
2018 (two years after impact) and was used for this study
In addition, to ensure relevance and topicality, this study continues to use additional survey data in 2022 of the above households to verify the impact mechanism of salinity intrusion using the qualitative method
LITERATURE REVIEW
Theory of sustainable livelihoods
The sustainable livelihoods framework developed by DFID (1999) has been widely used and has become a popular model in poverty and livelihoods research In this sustainable livelihood framework, the factors and components that make up a livelihood are mentioned, including: (1) priorities that people can recognize; (2) strategies they choose to pursue those priorities; (3) institutions, policies, and organizations that determine their access to assets or opportunities and the results they obtain; (4) their approaches to the five forms of capital and the ability to effectively use the forms of capital they have; and (5) human life context, including economic, technological, demographic trends, shocks, and seasons At the same time, the sustainable livelihoods framework also explores how these factors relate to each other in specific contexts.
Theory of sustainable rural livelihood framework
The Sustainable Rural Livelihoods Framework was proposed by Scoones (1998), which elaborates on three of the framework's elements: livelihood capital, livelihood strategies, and institutional processes and organizational studies Livelihood capital is the basic physical and social, tangible and intangible assets that people use to build their livelihoods (including natural capital, economic or financial capital, human capital, and social capital) on which people rely when pursuing different livelihood strategies
2.3 Theory of livelihoods and poverty
According to FAO's (2005) approach to livelihoods and poverty, the basic assets of poor households are much more limited than those of non-poor households due to unfavorable policies, institutions, and processes Limited access to land, water, natural resources, and other assets reduces the livelihood options of poor households The lack of backup assets in case of an emergency makes them vulnerable to shock Shocks contribute to negative livelihood outcomes and further depletion of household assets, leading to a deepening cycle of poverty Thanks to
6 enabling policies, institutions, and processes, non-poor households enjoy a better livelihood asset base, helping them expand their livelihood options and reduce vulnerability before shocks This allows non-poor people to pursue successful livelihood strategies
2.4 Theory of the poverty trap
Due to a lack of assets, dependence on natural resources, and the need for diverse income sources, the rural poor are vulnerable to poverty traps (Barbier, 2015) The impacts of adverse factors, especially natural disasters or disasters caused by climate change such as drought and erosion and changes in rainfall, temperature, and hydrology, can directly affect poor households through their negative impact on agricultural productivity and income or indirectly through their impact on land use and natural resources
The impact of the poverty spiral is as follows: The increasing use of livelihood capital sources (especially natural capital, including available agricultural land) causes a serious recession This leads to reduced productivity and reduced income for household dependent on these sources of capital, many of whom seek outside work to increase or supplement their income If there are a large number of households seeking outside employment in rural areas, the supply of labors for wage employment may exceed demand, leading to a decrease in market wages for labors For some households, wages will fall, which means these households will forgo outside employment opportunities and instead allocate all of their labor returns to resource-dependent productive activities If this process degenerates into a vicious cycle, these households will fall into a poverty trap.
RESEARCH METHODS
Analytical framework
The framework for analyzing the impact of salinity intrusion on the livelihoods of poor households in rural areas of the Mekong Delta is described in Figure 3.2
Figure 3.2: Framework for analyzing the impact of salinity intrusion on the livelihoods of poor households in rural areas
Data collection methods
Selected provinces demonstrate the impact of salinity intrusion from the west coast through the Cai Lon river branch and the east through the Tien and Hau river branches, including Ben Tre, Tra Vinh, Hau Giang, and Soc Trang
Data on 344 rural households in the study area from the General Statistics Office's Household Living Standards Survey Data Set in 2014 and 2018 Other data from statistical yearbooks, maps, scenarios, and
The frequent salinity intrusion area
The non-affected by salinity intrusion area
Verifying the impact mechanism and long- term livelihood changes
Compare difference s in livelihood s Group 1
2018 Livelihood strategy The non-frequent salinity intrusion area intrusion
Impact factor Data Research areas Content analysis
8 reports on salinity intrusion in the Mekong Delta, scientific studies are published.
The study additionally surveyed 344 households in 2022 on awareness and adaptation actions to verify the impact mechanism The thesis also consulted the opinions of 6 experts and 12 local officials.
Analytical methods
The research uses many quantitative and qualitative analysis methods to clarify the research objectives and questions (Figure 3.7)
Figure 3.7 Method for analyzing the impact of salinity intrusion on poor households' livelihoods
3.3.1 Build a variable system for the experimental model
The system of variables represents the livelihood capital indicator in Table 3.3
Livelihood outcomes (income and poverty)
ANOVA test on livelihood capital index
Difference-in-differences (DID) comparison on livelihood capital index
- Multivariate probit/tobit model for livelihood choice
- Binary/multinomial logit model for the combination of agricultural livelihoods
Probit model for changes in livelihood activities
Descriptive statistics and synthesis analysis
-Multiple linear regression using OLS for income
- Binary/hierarchical logit model for income quintiles and poverty status
-Multiple linear regression with fixed effects
Assessment of the impact mechanism
Table 3.3: Livelihood capital indicator system of rural households
Labor force H1 Number of household members participating in any type of livelihood
H2 Proportion of male workers in the total labor force of the household
H3 Highest degree of the labor force in the household (1=Secondary school or higher; 0=Vice versa)
Labor age H4 Average age of the household's labor force
Cultivated land area N1 Total area of farmland of the household
Diverse crop types N2 Ratio of types of plants grown on the household's cultivated land to the largest number of types of plants grown by households in the region (11 types of crops)
Housing quality P1 The household's housing is semi- permanent or higher (1=Yes, 0=No)
Housing area P2 Household area of the household m 2 Quantity of durable goods
P3 Number of household durable goods
Access to loans F1 Does the household have a loan
Livestock value F2 Total value of livestock owned by the household during the year
Participate in party organizations and unions
S1 Households have members participating in party organizations and unions such as farmers' associations, women's associations, and veterans' associations (1=Yes, 0=No)
S2 Does the household receive media information from the local loudspeaker system (1=Yes, 0=No)
S3 Distance from household's house to district center
Based on the 4g/l salinity boundary map in the Mekong Delta, there is a variable with a dummy value of 1 if the household affected by frequent salinity intrusion at 4g/l and a value of 0 otherwise, and a variable with a value of 1 if the household affected by first-time salinity intrusion at 4g/l in the dry season of 2015-2016 and value 0 otherwise Other explanatory variables are in Table 3.4
Table 3.4: Core explanatory variables used in the empirical research model
Province fixed effects TINH Province fixed effects (Base = Ben Tre)
Tra Vinh TV Dummy variable value 1 if the household belongs to Tra Vinh province Hau Giang HG Dummy variable value 1 if the household belongs to Hau Giang province Soc Trang ST Dummy variable value 1 if the household belongs to Soc Trang province
Salinity intrusion XNM Classify the extent of salinity intrusion
XNM1 Dummy variable value 1 if the household in area affected by frequent salinity intrusion, and 0 otherwise Salinity intrusion in the dry season of
XNM2 Dummy variable value 1 if the household in area affected by first- time salinity intrusion in the dry season of 2015-2016, and a value of 0 otherwise
Poor NGHEO The dummy variable takes the value 1 if the household belongs to the household category, 0 otherwise
3.3.2 Method for analyzing the impact of salinity intrusion on livelihood capital: Entropy weighting method
The calculated entropy weight, the study finds the livelihood capital index of rural households (3.3) and of the study area (3.4):
𝐶𝑃𝑍 = ∑ 𝑛 𝑖=1 𝑛 𝐶𝑃 𝑘 (3.4) CPZ ranges from 0 to 1, where a value of 0 indicates the weakest sustainable livelihood, while a value of 1 indicates the most sustainable livelihood
The double difference (Difference in Difference - DID) method evaluates the impact of salinity intrusion on the livelihood capital index The difference is estimated by the average treatment effect using the following equation:
3.3.3 Method to analyze the impact of salinity intrusion on livelihood strategies
3.3.3.1 Method to compare differences in livelihood strategies in different salinity intrusion areas a) Compare differences in the ability to choose livelihood activities
The multivariate probit model explains factors affecting the livelihood choices of farmers in the salinity intrusion area of the Mekong Delta
In particular, 𝑆𝐾𝑇𝑇 𝑖 ∗ , 𝑆𝐾𝑇𝑆 𝑖 ∗ , 𝑆𝐾𝐿𝐶 𝑖 ∗ , 𝑆𝐾𝑃𝑁𝑁 𝑖 ∗ equal to 1 if the second household 𝑖seeks income from crop, aquatic, wage employment, and non- agriculture, respectively
The multivariate tobit regression model captures the potential level of households deciding not to participate in a particular livelihood option
In which, 𝑇𝐻𝑈𝑇𝑇 𝑖 ∗ , 𝑇𝐻𝑈𝑇𝑆 𝑖 ∗ , 𝑇𝐻𝑈𝐿𝐶 𝑖 ∗and 𝑇𝐻𝑈𝑃𝑁𝑁 𝑖 ∗is the income of household i participating in crop, aquaculture, labor, and non-agriculture b) Compare the differences in the ability to combine agricultural livelihoods with other livelihoods
The binomial logit model determines whether the respondent household combines agricultural livelihoods with wage employment or non-agriculture
Where, 𝑃 𝑖 is the probability of the second household 𝑖participating in combined livelihoods and ranges from 0 to 1 The marginal impact of an explanatory variable 𝑋 𝑖 is:
A household will choose the livelihood combination that provides maximum utility from its income The multinomial logit model is built with three different livelihood combinations:
In which, probability 𝑃 1𝑖 , 𝑃 2𝑖 ,𝑃 3𝑖 households 𝑖choose a combination of agriculture and labor, agriculture and non-agriculture, or all three strategies compared to just agricultural livelihoods The marginal impact effect is:
3.3.3.2 Method to analyze the heterogeneous impact of salinity intrusion on livelihood strategies
Probit model analyzes the impact of salinity intrusion on the change in livelihood strategies of rural households in the period 2014- 2018:
𝑌 1𝑖 ∗ = 𝛽 1 𝑋𝑁𝑀1 𝑖 + 𝛽 1𝑋 𝑋 𝑖 + 𝜀 1𝑖 ; 𝑌 1𝑖 = 1 if 𝑌 1𝑖 ∗ > 0if the household continues to participate in crop,
𝑌 2𝑖 ∗ = 𝛽 2 𝑋𝑁𝑀1 𝑖 + 𝛽 2𝑋 𝑋 𝑖 + 𝜀 2𝑖 ; 𝑌 2𝑖 = 1 if 𝑌 2𝑖 ∗ > 0if the household continues to participate in aquatic,
𝑌 3𝑖 ∗ = 𝛽 3 𝑋𝑁𝑀1 𝑖 + 𝛽 3𝑋 𝑋 𝑖 + 𝜀 3𝑖 ; 𝑌 3𝑖 = 1 if 𝑌 3𝑖 ∗ > 0if the household increases the number of wage employment,
𝑌 4𝑖 ∗ = 𝛽 4 𝑋𝑁𝑀1 𝑖 + 𝛽 4𝑋 𝑋 𝑖 + 𝜀 4𝑖 ; 𝑌 4𝑖 = 1 if 𝑌 4𝑖 ∗ > 0if new household engages in non-agriculture,
The probability of continuing crop, continuing aquaculture, increasing the number of wage employment or participating in new non- agriculture of household i is:
3.3.4 Method to analyze the impact of salinity intrusion on income and poverty
3.3.4.1 Method to compare differences in income and poverty in different areas affected by salinity intrusion
Multiple linear regression model for household income in 2018 using the least squares method is as follows:
In which, 𝑌 𝑖 is the natural logarithm of household income
The order probit model estimates the impact of salinity intrusion through the probability of belonging to income groups The model is as follows:
In which, 𝑌 𝑖 is the household's income quintile with j=5 income groups ranked from low to high (from 1 to 5)
The propensity score matching method compares the income of households affected by salinity intrusion using the average treatment effect (ATT):
In there, 𝑋𝑁𝑀1 reflects the extent of salinity intrusion; 𝑌 1𝑖 and 𝑌 0𝑖 is the income of the household when the group sample is frequent salinity intrusion at 4g/l and when the group sample is non-frequent salinity intrusion at 4g/l
3.3.4.2 Method to analyze the heterogeneous impact of salinity intrusion on income and poverty
The double difference (DID) method evaluates the impact of salinity intrusion on income and poverty of households in the period 2014-2018 Income sources are converted to 2014 values by CPI index The ATT value of the income difference between the treatment group (1 and 2) and the control group using the DID method is estimated:
The binomial logit model analyzes factors affecting household poverty due to the impact of salinity intrusion In particular, the dependent variable has value 1 if the household is poor and value 0 if the household is not poor
In which, 𝑃 𝑖 is the probability of the second household falling below the poverty threshold
Finally, the impact of salinity intrusion on the livelihoods of rural households is verified by the impact mechanism using qualitative methods and the assessment of households in the affected area
Additional household survey data in 2022 serves as a basis for analyzing households' awareness of salinity intrusion in the past and households' assessment of the impact mechanism of salinity intrusion on capital livelihoods, livelihood strategies, income, and poverty status of households
RESULTS AND DISCUSSION
Impact of salinity intrusion on the livelihood strategies of rural
Table 4.11 shows that the total income of the group of poor households in salinity areas is often lower than that of poor households in other areas (23.4 and 62.73 million VND per year) The reason is that crop income and wage employment for poor households in salinity areas are often lower On the other hand, non-poor households in salinity areas often have an advantage in aquatics compared to non-poor households in other areas The aquatic income of non-poor households in areas with frequent salinity intrusion is 12.08 million VND/year and is nearly four times higher than that of non-poor households in the other areas
The test results in Table 4.12 find differences in the number of livelihood activities that poor households in the region pursue Accordingly, the average number of livelihood activities that poor households in areas affected by frequent salinity intrusion participate in is 2.00, lower than the value of 2.65 for poor households in other areas This further confirms that poor households face many limitations in diversifying their livelihoods in the face of frequent salinity intrusion, while non-poor households in this area do not have difficulty implementing a diversification strategy
The results of estimating multivariate probit and multivariate tobit models show that, compared to a household in an area with little salinity, a household in an area with frequent salinity has a 13.6% lower probability of participating in crop activities and a lower crop income of 4.8% Meanwhile, salinity intrusion increases the probability of choosing aquatic livelihoods by 12.8% for households living in frequent sallinity intrustion areas In fact, aquatic is an adaptive livelihood activity for households in areas affected by salinity intrusion
The estimation results of the binomial logit model and multinomial logit model show that households in areas with frequent salinity intrusion will have a lower probability of combining non-agriculture or wage employment than areas with low wages (14.7%), focusing on reducing the probability of choosing a combination of agriculture and wage
19 employment by 17.3% This implies that households affected by salinity intrusion face many difficulties in accessing and exploiting capital to be able to implement many different livelihood strategies at the same time
Table 4.11: Comparison of income from livelihood activities of rural households in different salinity intrusion areas
Poor households Non-poor households
Note: *, **, *** are significance levels at 10%, 5% and 1% respectively
- F1 is the ANOVA test value of the average difference between two groups of poor households in areas with frequent salinity intrusion and other areas
- F2 is the ANOVA test value of the average difference between two groups of non-poor households in areas with frequent salinity intrusion and other areas
- F is the ANOVA test value of the average difference between the poor household group and the non-poor household group
Source: Author's calculations based on VHLSS 2018 data
Table 4.12: Comparison of number of livelihood activities of rural households
Object Medium Standard deviation ANOVA test value (F)
Poor households Frequent salinity intrusion (n() 2.00 1.08 5.36**
Non-frequent salinity intrusion (n1) 2.65 1.05 Non-poor households
Note: ** is the 5% significance level
Source: Author's calculations based on VHLSS 2018 data
Impact of salinity intrusion on income and poverty of rural
Table 4.18: Heterogeneous impacts of salinity intrusion on household livelihood strategies: Probit model
Dependent variable: Probability of changing the household's livelihood
Increase the number of wage employment
Yes Yes Yes Yes Yes Yes Yes Yes
LR chi2 42.31*** 39.12*** 32.22** 32.28** 28.17** 26.42** 19.01* 17.76* Log likelihood -76.75 -78.35 -75.09 -75.06 -55,56 -56.43 -51.17 -51.05 Note: *, **, *** are significance levels at 10%, 5% and 1% respectively
(1) is a probit model with explanatory variables for frequent salinity intrusion and control variables (livelihood capital and province fixed effects)
(2) is a probit model with explanatory variables for the first salinity intrusion in the dry season 2015-2026 and control variables (livelihood capital and province fixed effects)
Source: Author's calculations based on VHLSS 2014 and 2018 data
4.3 Impact of salinity intrusion on income and poverty of rural households
4.3.1 Compare household income in different salinity intrusion areas
Table 4.19 shows that households living in areas with frequent salinity intrusion have a 29.7% decrease in income compared to those living in other areas Table 4.20 presents the income difference between
22 rural households with frequent (treatment group) and occasional (control group) salinity intrusions using propensity score matching (PSM) The comparison results show that households in areas with frequent salinity have an income of 41.3 million VND per year lower than households with less salinity
Table 4.19: Impact of salinity intrusion on rural household income: OLS method
Dependent variable: Natural logarithm of income
Note: *** is the 1% significance level OLS(1) is a linear regression model with frequent salinity intrusion explanatory variables OLS(2) is a linear regression model with the explanatory variable of frequent salinity intrusion and the variables of livelihood capital
Source: Author's calculations based on VHLSS 2018 data
Table 4.20: Comparison of impacts of salinity intrusion on rural household income in different salinity intrusion areas: PSM
Note: **, *** are significant at the 5% and 1% levels
Source: Author's calculations based on VHLSS 2018 data, n44
Table 4.21 shows that salinity intrusion puts households at risk of falling into the lower income group with a probability of 46.5%
Table 4.21: Impact of salinity intrusion on income quintiles of rural households: Order probit model
Explanatory variables Symbol Dependent variable: Quintiles of income
Control variables Are not Have
Note: *** represents the 1% significance level, respectively (1) is a order probit model with frequent salinity intrusion explanatory variables (2) is a order probit model with frequent salinity intrusion explanatory variables and livelihood capital variables and province fixed effects
Source: Author's calculations based on VHLSS 2018 data
4.3.2 Heterogeneous impacts of salinity intrusion on the income of poor and non-poor households
Table 4.22 shows that the income of poor households is reduced more due to salinity intrusion than that of non-poor households (61.8% and 16.4% respectively)
Table 4.22: Heterogeneous impacts of salinity intrusion on income of poor and non-poor households: OLS method
Dependent variable: Natural logarithm of income Poor households Non-poor Households
Note: *, *** are significance levels at 10% and 1% respectively The control variables are livelihood capital
Source: Author's calculations based on VHLSS 2018 data
Table 4.23 is the result of the logit model, with the dependent variable having a value of 1 if it belongs to a poor household, showing that households living in areas with frequent salinity intrusion will increase the risk of poverty by 7.3% compared to poor households in other areas This further strengthens previous analyses on the negative impact of salinity intrusion on the income of poor households in the region
Table 4.23: Impact of salinity intrusion on poverty status of rural households: Binomial logit model
Note: *, *** are significance levels at 10% and 1%, respectively
Source: Author's calculations based on VHLSS 2018 data
4.3.3 Heterogeneous impacts of salinity intrusion on rural household income
Table 4.25 of the DID estimation results shows that salinity intrusion in the dry season 2015-2016 significantly reduced the total income and income from crop in 2018 compared to 2014 for households in areas affected by salinity intrusion compared to unaffected households (26.29 and 15.44 million VND/year, respectively) The study found no difference in aquatic income between these two groups of households, showing the role of aquatic livelihoods in stabilizing the income of households in the region
Table 4.25: Impact of salinity intrusion on income of households with frequent salinity intrusion: DID method
Household income difference between treatment group 1
Note: *, *** are significance levels at 10% and 1%, respectively
Treatment group 1: Households in areas affected by frequent salinity intrusion
Control group: Households in areas not affected by salinity intrusion
Source: Author's calculations based on VHLSS 2014 and 2018 data
Table 4.26 shows that salinity intrusion in the dry season 2015-
2016 made the crop and aquatic income of households experiencing salinity intrusion for the first time lower than households without salinity intrusion, by 45.07 and 6.38 million VND/year, respectively
Table 4.26: Short-term impacts of salinity intrusion on household income: DID method (Treatment group 2 and control group)
Household income difference between treatment group 2
Note: *, ** are significance levels at 10% and 5%, respectively
Treatment group 2: Households in areas affecteted by first-time salinity intrusion in the 2015-2016 dry season
Control group: Households in areas not affected by salinity intrusion
Source: Author's calculations based on VHLSS 2014 and 2018 data
In summary, both first-time and frequent salinity intrusion affect the income of rural households in the Mekong Delta
4.4 Mechanism of impact of salinity intrusion on rural household livelihoods
Table 4.29 shows that approximately 71.7% of the total households have implemented measures to cope with salinity intrusion, such as shifting crop or aquaculture structures, storing water before salinity occurs, changing farming methods, adopting new agricultural techniques, and integrating shrimp farming Notably, some households have transitioned to business activities to diversify their livelihoods and minimize the risks posed by salinity intrusion
Table 4.29: Actions to respond to salinity intrusion in rural households by different areas affected by salinity intrusion (Unit: %)
Poor households Non-poor households
Total Areas with frequent salinity (n)
Changing the structure of farming or aquaculture
Change the form of agricultural cultivation 17.9 7.7 14.6 26.7 19.0 22.6 17.23
Source: Author's calculations based on 2022 supplemental survey data
However, these coping measures will impact the livelihood assets and livelihood strategies that households pursue (Figure 4.13)
Figure 4.13: Poverty trap of rural households in areas affected by salinity intrusion Source: Author's compilation based on 2022 survey data
In summary, the results from Sections 4.1 to 4.3 of this chapter show that most of the impacts of salinity intrusion are negative for household livelihoods, reducing income and hindering the ability of households to escape poverty While salinity intrusion presents opportunities for aquaculture activities, only non-poor households are
27 currently able to capitalize on them effectively Poor households, on the other hand, bear the brunt of the negative impacts, further weakening their already vulnerable livelihood components
Table 4.30: Summary of main results of quantitative analysis on the impact of salinity intrusion on rural household livelihoods
Impact of salinity intrusion Classify Poor households
- Decline in human capital Negative X
- Decline in natural capital Negative X
- Limits the ability to diversify livelihood activities Negative X
- Limited ability to participate in crop Negative X
- Limits the ability to continue crop livelihoods Negative X
- Limits the ability to combine agriculture and wage employment
- Limiting the ability to increase the number of new labors entering wage employment
- Increase the ability to participate in aquatic Positive X
- Reduce total annual income Negative X
- Reduced income from crop activities Negative X
- Reduced income from wage employment Negative X
- Increase income from aquatic Positive X
4.5.1 Solutions to enhance livelihood capital for poor households
Solutions based on the internal capacity of poor households: Poor households should engage in self-learning and skill development by studying successful models within the community They should seek additional livelihood activities such as fruit cultivation, poultry farming, or the production of handicrafts to increase income and reduce economic risks It is essential for poor households to build and join community support groups to share experiences and provide mutual assistance in developing livelihoods
Solutions based on external support: The government should implement programs that create non-agricultural employment
28 opportunities for poor households and connect them with suitable job transition opportunities in line with the region’s economic context Low- cost or free vocational training programs will help poor households acquire new skills, increase their income, and improve their quality of life The government should enhance policies that provide tuition exemptions and financial support for the children of poor households
4.5.1.2 Solutions to improve financial capital
Poor households need to establish a habit of saving, even with small amounts, and manage their finances wisely to gradually accumulate capital They should also utilize their available land and skills to develop small-scale economic activities such as animal husbandry or handicraft production The government should adjust and improve loan policies with low interest rates and simplified procedures to make it easier for poor households to access financial capital
4.5.1.3 Solutions to improve the efficiency of other capital sources
Poor households need to adopt alternative farming methods, grow salt-tolerant crops, and develop aquaculture models such as the rice- shrimp system Encouraging households to participate in community organizations like women's unions and farmers' associations will allow them to share knowledge and support each other in production Poor households can also leverage support from NGOs and the community to improve living conditions and use information tools to enhance skills and access markets
4.5.2 Solutions for livelihood adaptation of poor households a) Solutions based on the internal capacity of poor households: Poor households need to improve their understanding of salinity intrusion and manage water resources efficiently They should participate in training sessions and adopt new farming techniques, adjust cropping calendars, and apply appropriate farming models Combining agricultural and non-agricultural activities such as growing water hyacinths, raising poultry, or using integrated farming models will help increase income and reduce risks
29 b) Solutions based on external support: Raise livestock breeds that are resilient to salinity intrusion, such as sea ducks, goats, or bio-organic cows combined with biogas production Develop transportation services, small businesses, and cottage industries with support through loans and technology Promote the cultivation of salt-tolerant crops such as lemongrass and soursop Use the rice-shrimp integrated farming model with low investment to take advantage of both freshwater and saltwater environments The government and related agencies should provide technical assistance, crop varieties, and soil improvement to maximize production efficiency for poor households.
Solutions
4.5.1 Solutions to enhance livelihood capital for poor households
Solutions based on the internal capacity of poor households: Poor households should engage in self-learning and skill development by studying successful models within the community They should seek additional livelihood activities such as fruit cultivation, poultry farming, or the production of handicrafts to increase income and reduce economic risks It is essential for poor households to build and join community support groups to share experiences and provide mutual assistance in developing livelihoods
Solutions based on external support: The government should implement programs that create non-agricultural employment
28 opportunities for poor households and connect them with suitable job transition opportunities in line with the region’s economic context Low- cost or free vocational training programs will help poor households acquire new skills, increase their income, and improve their quality of life The government should enhance policies that provide tuition exemptions and financial support for the children of poor households
4.5.1.2 Solutions to improve financial capital
Poor households need to establish a habit of saving, even with small amounts, and manage their finances wisely to gradually accumulate capital They should also utilize their available land and skills to develop small-scale economic activities such as animal husbandry or handicraft production The government should adjust and improve loan policies with low interest rates and simplified procedures to make it easier for poor households to access financial capital
4.5.1.3 Solutions to improve the efficiency of other capital sources
Poor households need to adopt alternative farming methods, grow salt-tolerant crops, and develop aquaculture models such as the rice- shrimp system Encouraging households to participate in community organizations like women's unions and farmers' associations will allow them to share knowledge and support each other in production Poor households can also leverage support from NGOs and the community to improve living conditions and use information tools to enhance skills and access markets
4.5.2 Solutions for livelihood adaptation of poor households a) Solutions based on the internal capacity of poor households: Poor households need to improve their understanding of salinity intrusion and manage water resources efficiently They should participate in training sessions and adopt new farming techniques, adjust cropping calendars, and apply appropriate farming models Combining agricultural and non-agricultural activities such as growing water hyacinths, raising poultry, or using integrated farming models will help increase income and reduce risks
29 b) Solutions based on external support: Raise livestock breeds that are resilient to salinity intrusion, such as sea ducks, goats, or bio-organic cows combined with biogas production Develop transportation services, small businesses, and cottage industries with support through loans and technology Promote the cultivation of salt-tolerant crops such as lemongrass and soursop Use the rice-shrimp integrated farming model with low investment to take advantage of both freshwater and saltwater environments The government and related agencies should provide technical assistance, crop varieties, and soil improvement to maximize production efficiency for poor households
CONCLUSION AND RECOMMENDATIONS
Conclusion
Poor households in areas frequently affected by salinity intrusion tend to have low livelihood assets due to a lack of human and financial resources In contrast, the impact of salinity intrusion on natural capital primarily affects non-poor households in these regions Additionally, poor households in salinity-prone areas are less capable of diversifying their livelihood activities compared to other groups Households in areas with frequent salinity intrusion have a 13.6% lower probability of engaging in crop farming and 4.8% lower farming income compared to households in less affected areas Conversely, salinity intrusion increases the likelihood of participation in aquaculture by 12.8% However, contrary to expectations, households in areas with frequent salinity intrusion have a 14.7% lower probability of combining livelihoods compared to other regions Under the persistent impact of salinity intrusion, the proportion of households continuing in farming has steadily declined, and the availability of wage labor within the region has also diminished
Households in frequently salinity-affected areas experience an annual income reduction of VND 41.3 million The total annual income of households first affected by salinity during the dry season of 2015-
2016 decreased by 24%, while those in areas of frequent salinity intrusion saw a 38% reduction compared to households not affected by salinity Ultimately, income declines increase the risk of households falling into lower income brackets by 46.5% and raise the likelihood of poverty by 7.3% Furthermore, the heterogeneous impact of salinity intrusion on income losses is more pronounced among poor households than non-poor households In areas frequently affected by salinity, poor households experience income losses of up to 76%, compared to 31% for non-poor households In summary, whether the impact is initial or recurrent, salinity intrusion affects all components of rural household livelihoods in the Mekong Delta The severe reduction in income heightens the risk of
31 poverty and hinders the sustainable poverty alleviation efforts of poor households in the region.