FFTC Agricultural Policy Platform (FFTC-AP)

ABSTRACT

As Myanmar has a great potential to expand rice cultivation, the government has prioritized irrigation for rice cultivation since rice is the key crop in the agriculture and the main food item for Myanmar people. Irrigation has also great significance for the national economy. The total irrigated area has reached 2.3 million hectares after the completion of 342 dam projects, 208 pumping stations, and 7,578 tube wells during the period of 2018-2019. Percentage of total irrigable area has reached 17.2 % of the total net sown area in 2018-2019, from 15.6 % in 2011-2012. One of the central themes of this study is, therefore, to examine the impact of irrigation infrastructure development on the poverty incidence of rice based farming system households in the Central Dry Zone Area of Myanmar. The study selected 10% of total households for each group of farmers. The total number of respondents was 225 in this study. Poverty prevails in irrigated areas as well as in rainfed areas. However, the incidence and depth of poverty is significantly less in irrigated areas than in the rainfed areas, indicating that irrigation has poverty-reducing impact. Further, the incidence of poverty varies across irrigation systems (dam and pump systems). The results revealed that dam irrigation system had better performance in reducing poverty than pump irrigation system. Overall, irrigation facilities can contribute not only in improving productivity, cropping intensity, and farm income but also in reducing poverty among rural households. Water management, operation and maintenance of existing irrigation facilities are also important and can lead to crop productivity.

Keywords: Poverty, Irrigation, Rice based farming system

INTRODUCTION

Water is the most important input for agricultural production, especially in rice production. As Myanmar has a great potential to expand rice cultivation the government has prioritized irrigation for rice cultivation since rice is the key crop in the agriculture and the main food item for Myanmar people.  In addition, it has also great significance for the national economy. In Myanmar, rice cultivation is fairly high in delta regain and central dry zone of Myanmar, the first area is including the Ayeyarwaddy, Bago and Yango regions in which rice is cultivated mainly by rainfed cultivation while the second area comprises Mandalay, Sagaing and Magway regions in which supplemental irrigation need to be supplied for monsoon rice cultivation due to rainfall is not sufficient for crop water requirement (Naing, 2005)

The government of Myanmar introduced a rice production policy, it is called the summer paddy program in 1992/93. The introduction of this programme was along with an investment in irrigation. The total irrigated area has reached 2.3 million hectares after the completion of 342 dam projects, 208 pumping stations, and 7,578 tube wells during the period 2018-2019. Percent of total irrigable area has reached 17.2 % of the total net sown area in 2018-2019, from 15.6 % in 2011-2012.

The government has been constructing many irrigation facilities in Central Dry Zone Area in order to expand crop sown area, increase crop production, and enhance the livelihood of farmers in Myanmar which comprise the regions of Mandalay, Magway and Sagaing, where water is scarce due to erratic rainfall. However, it remains unclear whether the large amount of government budgets on irrigation development in the country has led to significant improvements in the livelihood of the poor. Therefore, this study determined the factors contributing to the reduction of poverty incidence in irrigated and non-irrigated area rice-based farming households in the study area.

Objective of the study

One of the central themes of this study is, therefore, to examine the impact of irrigation infrastructure development on the poverty incidence of rice-based farming system households in the Central Dry Zone Area of Myanmar. The analysis considered the impacts by type of irrigation systems (dam versus pump type) on rice based farming households. After examining the impact, the study suggested some corrective measures for future irrigation intervention in Myanmar. The findings of this study may also have implications for other irrigated areas within the country having similar characteristics. The objective of the study was to determine the factors contributing to the reduction of poverty incidence in the study area 

Selection of the study area

The study purposively selected two areas, Wann Twin Township and Nyaung Oo Township. Both townships are located in Mandalay Region of Myanmar in the Central dry zone area. The former is represented as an area for dam irrigation and rainfed areas, while the latter is represented as an area for river pumping irrigation. 

Sampling procedure

The study conducted field survey and the sample farmer-respondents were drawn using stratified random sampling technique based on type of irrigation scheme, i.e., dam/canal and pump irrigation. The field survey was conducted for farmers in rainfed area for the same study area. The study selected 10% of total households for each group of farmers. The sample size for rainfed, dam irrigators and pump irrigators, are presented in Table 1.

Table 1. Sample size by type of water sources

Analytical Tool

For measuring poverty, a poor household is defined as one with income less than a specified level to meet basic food and non-food needs. Therefore, income was used for measuring poverty. Household income is defined as total income received from farm and non-farm activities. The study examined whether irrigation is one of the key determinants of poverty by using the dichotomous variable indicating whether a household is poor or non-poor as dependent variable. This study used the poverty line specified by the Integrated Household Living Conditions Assessment II, 2010, Myanmar, that is 376,151 Kyats per person per year. On per person per day basis, it was 1,045 Kyats and was equivalent to US$ 1.23/day in purchasing power parity terms. It is nearly the same as the poverty line set by the World Bank for international countries, that is, US$ 1.25/ day/person. Therefore, in this study, the person whose income was less than 1.25 US$ was recognized as a poor and was equal or higher than 1.25 US$ was recognized as not a poor person.

The poverty variable was defined as a dummy, which is equal to 1 if per capita income of a particular household was lower than the stated poverty line and 0, otherwise. The explanatory variables used were gross value of product per hectare (GVP),  size of farm holding in irrigated farm (FSIZE), family size (FMSIZE), years of schooling of household head (EDU),  and credit access (D_CREDIT=1 if yes, 0 otherwise),  and dummy for irrigation (D_IRRI=1 if irrigated farmers, 0 otherwise).

Moreover, dummy variable for dam irrigation system (D_DAM) was used to capture the impact of difference in availability and access to water on poverty. In this case, pump irrigation was used as base category.

To determine the factors contributing to poverty incidence, the following logit regression model was estimated.

Where, Z=1 if household is poor, 0 otherwise GVP= Gross value product per hectare of monsoon rice

FSIZE= Average land holding/farm size under monsoon rice cultivation

FMSIZE= Number of family members in the household

D_CREDIT= Access to credit (Yes=1, 0 otherwise)

EDU= Years in school of household head

D_IRRI= Dummy for irrigation (Irrigated farmer=1, 0 otherwise),

D_DAM= Dummy for dam irrigation (Dam irrigated farmer=1, 0 otherwise)

Table 2 shows the determinants of poverty and their expected signs.

Table 2.  Expected signs of the determinants of poverty.

To determine the partial effect of independent variables X_i on Z_i, the marginal effect was calculated by taking the partial derivative of Z_i with respect to X_i. The marginal effect represents the change in probability of household being poor caused by a unit change in X_i, ceteris paribus. The formula for marginal effect is as follows (Nwet, 2011):

Where; P_i is the vector of probability of household being poor

X_i is the vector of independent variables

e is the base of natural logarithms

β is the vector of other estimated coefficients of corresponding X in the model

RESULTS AND DISCUSSION

Determinant of Poverty in Irrigated and Rainfed Area

Table 3 presents the generated coefficients of the logit model for irrigated and rainfed areas. Results of the analysis show that the variables exhibiting significant effects on poverty were gross value product, farm size in irrigated area, family size and dummy for irrigation. The positive and significant coefficient for family size implies that the greater the number of family members, the higher the probability of that household to remain poor compared to a household with a smaller number of family members. The coefficient of the gross value product per hectare was negative and significant, indicating that the higher productivity could significantly contribute to reducing poverty. Similarly, the size of landholding had significant impact on poverty, that is, the probability of a household being poor is higher for household with smaller land holding. The negative coefficient for dummy of irrigation indicates that the probability of households being poor is less for those households located in irrigated area compared to those located in rainfed area. Therefore, irrigation had a significant impact on reducing poverty. As show in Table 4, the result of marginal analysis revealed that irrigation system would reduce the probability of the household being poor by 25% more than rainfed area.

Table 3.  Estimated coefficients of the logit regression model for poverty in irrigated and rainfed areas, Wann Twin and Nyaung U townships, Myanmar, 2011.

*, ** and *** Significant at 10%, 5% and 1%  level, respectively

 ^ns Not significant at 10% level

Table 4.  Estimated marginal effects of the predictor variables on poverty in irrigated and rainfed areas, Wann Twin and Nyaung U townships, Myanmar, 2011.

*, ** and ***Significant at 10%, 5% and 1%  level, respectively

^ns Not significant at 10% level

Determinants of Poverty in Dam and Pump Irrigated Areas

The summarized results of estimated logit model and marginal effect analysis for dam and pump irrigation systems are presented in Tables 5 and 6. In this case, the variables contributing to poverty incidence with negative sign were gross value product per hectare and farm size while family size had positive sign. These variables contributed to poverty incidence significantly at 1 % level. Moreover, dummy for dam irrigation negatively contributed to poverty incidence, being significant at 5 % level. The result of marginal analysis revealed that dam irrigation system would reduce the probability of the household being poor by 19% more than pump irrigation system.

Table 5.  Estimated coefficients of the logit regression model for poverty in dam and pump irrigated areas, Wann Twin and Nyaung U townships, Myanmar, 2011.

*, ** and *** Significant at 10%, 5% and 1%  level, respectively

^ns Not significant at 10% level

Table 6.  Estimated marginal effects of the predictor variables on poverty in dam and pump irrigated areas, Wann Twin and Nyaung U townships, Myanmar, 2011.

*, ** and *** Significant at 10%, 5% and 1% levels, respectively

^ns Not significant at 10% level

CONCLUSION

Poverty prevails in irrigated as well as in rainfed areas. However, the incidence and depth of poverty is significantly less in irrigated areas than in the rainfed areas, indicating that irrigation has poverty-reducing impact. Further, the incidence of poverty varies across irrigation systems (dam and pump systems). The results revealed that dam irrigation system had better performance in reducing poverty compared to pump irrigation system. Overall, irrigation facilities can contribute not only in improving productivity, cropping intensity, and farm income but also in reducing poverty among rural households.

Water management, operation and maintenance of existing irrigation facilities are also important and can lead to crop productivity. Thereby, the income of farmers will be affected by poor water management and increase in level of poverty. Therefore, there is a need to improve water management, operation and maintenance of existing irrigation facilities. Construction of new irrigation facilities may not have large positive impacts if after construction, they are not properly maintained.

REFERENCES

Myanmar Agriculutral Sector Review Investment Strategy. Volume 1- Sector review.

NAING M. M. 2005. Paddy field irrigation systems in Myanmar. Irrigation Department, Ministry of Agriculture and Irrigation, Myanmar.

Nwet Y.Y. 2011. Factors affecting the decision-making of farmers and traders on rice storage in selected areas of Ayeyarwaddy region, Myanmar. Thesis, M.S. Department of Agricultural Economics. The University of the Philippines Los Banos.