Role of Perennial Crops in Rural Households’ Income in Kyaukpadaung Township under the Climate Change Scenario Thadar Htwe1*, Shwe Mar Than1, Nang Ei Mon The1, Cho Cho San1 Abstract Climate change affects both on seasonal and on perennial crops production, however, obviously affects more on seasonal crop production. Central dry zone is said to be very vulnerable to climate change. This study was conducted to analyze income diversification, to point out the important role of income from perennial crops in rural household income and to find out the most practicing strategies for climate change adaptation in central dry zone of Myanmar. Main survey was carried out in two villages of Kyaukpadaung Township and 100 sample farmers were personally interviewed during November, 2016. In the study areas, various occupations of sample households were seasonal crop cultivation, perennial crop cultivation, government staff, broker, wage labor, tailor, driver, mason, carpenter, shopkeeper, and casual labor. Respondents had moderate income diversification with the average Herfindahl index of 0.65. Major perennial crops grown were banana, custard apple, dragon fruits, mango and tamarind. According to regression analysis results, perennial crop income was positively and significantly influenced on total household incomes at 5% level. Furthermore, expanding perennial crop cultivation was the first choice of climate change adaptation strategy for farmers and followed by changing cropping pattern and changing crop varieties. In order to raise income level of the rural households for combating climate change impact, perennial crop income is vital and it would be enhanced. Key Words: adaptation strategies, climate change, income diversification, perennial crops, rural household income ________________________________________________________________________________________________________________ 1 *
Department of Agricultural Economics, Yezin Agricultural University, Yezin, Nay Pyi Taw, Myanmar Corresponding author.
[email protected]
Introduction Myanmar is heavily dependent on the agriculture sector for income, survival and economic growth, and thus the improvement of agricultural productivity is critical. However, climate change has been the important factor in reducing agricultural crop productivity and the income of rural farm households gradually. Vulnerability, uncertainty and risk are essential features in agricultural sector. In the Dry Zone of Myanmar, most farmers are poor and so vulnerable to climate change. Furthermore, climate change causes low productivity, low profitability and high debt and which traps rural majority in poverty. Central Dry Zone of Myanmar is the most serious region in terms of land degradation because of climatic change impacts in crop production, productivity and income generation of the farmers and their social welfare are affected (Myo Win Maung et. al.2016). Climate change affects both seasonal crop production and perennial crop production. Zhang (2011) stated that relative to annual crop species, perennial crops would solve many agricultural problems, as well as substantial ecological and economic benefits. In addition, they can produce more ground cover, and perform longer growing seasons and more extensive root systems and more effective at capturing nutrients and water. Therefore, perennial crops can be used in reducing soil erosion and minimizing nutrient leaching, which would be a strong support for sustainable agriculture. Most farmers grow perennial plant for several purposes in Central Dry Zone of Myanmar such as for income, for fuel wood, for animal feed, for shade and so on. Common perennials in CDZ are toddy palm, jujube for cash and non-cash income, mango and tamarind for shade and income, dragon fruit for high value income, thanakha for high value as a safe,
2
neem tree for shape and extra income, lead tree for fodder and fuel wood, rain tree and acacia tree for shade. If perennial cash crops were grown in commercial production, higher income and higher net profits can be obtained. Belyi (2015) stated that perennial fruit crop can resilient to climate change impact through higher incomes. Those extra earnings allow the farmers to invest in inputs to increase their income further. On the other hand, rural households in many different countries have been found to diversify their income sources allowing them to spread risk and achieve better consumption. This is often necessary in agriculture based peasant economies because of risks such as variability in soil quality, livestock and crop diseases, price shock, unpredictable rainfall and other weather related events. Nelson et. al. (2016) stated that diverse rural income is less vulnerable than undiversified ones. Improved access to diversification options will allow households to more effectively manage financial risk, leading to more stable incomes. Climate change impacts can be roughly divided into two groups; biophysical impacts and socio-economic impacts. Adaptation is any change in behavior or capital that an actor (household, firm, or government) makes to reduce the harm or increase the gains from climate change (FAO 2007). Mendelsohn and Dinar (1999) stated that large reductions in adverse impacts from climate change are possible when adaptation is fully implemented. Therefore, local level initiatives are important to promote adaptation strategies for climate change. This study was conducted by three main objectives: (1) to analyze income diversification of rural household in Kyaukpadaung Township, central dry zone of Myanmar, (2) to point out the important role of income from perennial crops in rural household income
3
to combat climate change impacts, and (3) to find out the most practicing strategies for climate change adaptation in central dry zone of Myanmar. Research Methodology Study Area Kyaukpadaung Township, a township of Nyaung U district located in the Mandalay Region of Central Myanmar, was selected for this research. Kyaukpadaung Township is situated between North Latitudes from 20˙ 32' to 21˙5' and East Longitude from 95˙ to 95˙ 32' 46", and it is located at 252 meter above sea level. However, in this study, two villages, Popa and Nagale villages were selected on the basis of perennial crops cultivation. Although Kyaukpadaung was situated in the Dry Zone area, the two selected villages were located in special region (oasis) of the Dry Zone. Popa village is far about 16 km North-East from Kyaukpadaung and located at 366 meter above sea level. Nagale village is far about 32 km North-East from Kyaukpadaung and located at 457 meter above sea level. Data Collection and Sampling Procedure In this study, both primary and secondary data were used. The primary data were collected by using simple random sampling method. Field survey was conducted in November 2016. Total farm household was 284 households in Popa and 855 in Nagale village. Therefore, 20 respondents from Popa and 80 from Nagale village were interviewed based on total farm household during the survey. A set of structured questionnaires was used to conduct primary data collection. Both qualitative and quantitative data such as socioeconomic characteristics of age, education level, farming experience, family size, farm size, farm production, income and their coping strategies to climate change were collected. Secondary data were collected from published and official records of Ministry of Agriculture, Livestock and Irrigation (MOALI), Department of Agriculture (DoA), Department of
4
Planning (DoP), various journal articles, books, thesis and other relevant data sources from internet websites. Method of Analysis Herfindahl index (Ogundari, 2013) was used to analyze the degree of income diversification of sample rural households for the analysis.
Yj =Income share occupied by the jth occupation in total household incomes Y J =Total number of occupations The index ranges from zero to one. In the case of interpretation, zero reflects complete diversification and one reflects complete specialization. Multiple regression function was used to identify the important independent factors for household income. In this analysis, annual household income was used as the dependent variable. The independent variables were perennial crop income, age of household head, farming experience, education level of household head, number of family labor, total farm size, number of income sources, total number of crops grown, gender of household head, migration of household member, change in cropping pattern, change in crop variety and access to credit. LnY = β0+ β1LnX1+ β2LnX2+ β3LnX3+ β4LnX4+ β5LnX5+ b1D1+b2D2+b3D3+e Where, Y
= Annual household income (MMK/year)
X1
= Age of households’ head (years)
X2
= Education of household head (years)
5
X3
= Family size (Number)
X4
= Total farm size (Number)
X5
= Number of income sources (Number)
D1
= Perennial Crop Income (Yes=1, No=0)
D2
= Gender of Household’s head (Male=1, Female=0)
D3
= Migration (Yes=1, No=0)
β and b = Estimated coefficients e
= Error term The climate change adaptation strategies of the respondents were measured by a 4-
pointLikert scale which is rating as (3) for a lot, (2) for fair,(1) for few and (0) for never. The weighted average score was determined and used to order the rank. Descriptive statistics such as frequency counts, percentages, and weighted average were used to describe the data. According to literature and pilot survey, in the study areas, twelve adaptation strategies were selected for this analysis. Results and Discussion Perennial crops grown in Kyaukpadaung Township Table 1 shows major and minor perennial crops grown in Kyaukpadaung Township. In Kyaukpadaung Township, 83% of the respondents have perennial crop income. In Popa village, major perennial crops grown were dragon fruits, mango and tamarind, and minors were banana, custard apple, guava, jackfruit and papaya. Major perennial crops in Nagale village were banana, custard apple, dragon fruit, mango and tamarind, and cashew nut, coffee, guava, jackfruit and papaya were minor perennial crops. In the study areas, land use pattern changed from seasonal crop production such as maize, pigeon pea, sesame, groundnut, etc. to perennial crop cultivation due to climate change impact. In fact, dragon fruit production was grown in study areas since last 15 years but being a popular crop within last 3 years. Commercial production of guava was introduced 6
within last 3 years. Mango and banana were local perennial crops, however, widely produced within last 16 years and 35 years respectively. Custard apple and cashew nut were introduced since last 70 years and 40 years, but they were widely produced within last 7 years and 13 years respectively. Annual income amount of sample households Amount of income earned by sample households is shown in Table 2. In Popa, household income was derived from five main groups; seasonal crop production, perennial crop production, salary jobs, remittance and non-farm jobs. In Popa, although 95% of respondents had seasonal crop income, the average annual income of annual crops was 2 million MMK per household. Perennial crop income was the highest amount of income per year (3.1 million MMK), and 70% of respondents had perennial crop income. The average income of the respondents earned from salary, remittance and non-farm jobs amounted to 2.5 million MMK, 1.2 million MMK and 1.3 million MMK respectively. In Nagale village, household income was derived from seven main sources; seasonal crop production, perennial crop production, farm labor, salary, remittance, non-farm jobs and livestock rearing. Perennial crop income was the main income source because among the sample farmers 91% of respondents had perennial crop income, and Perennial crop income was the highest amount of income per year (2.7 million MMK). Seasonal crops were grown by 49% of respondents and its average income was only about 0.5 million MMK per household per year. In addition, the average income of the respondents earned from farm labor, salary, remittance, non-farm jobs and livestock amounted to 0.06 million MMK, 1.79 million MMK, 1.5 million MMK, 1.29 million MMK and 0.4 million MMK respectively. Annual average total incomes earned by sample households in Popa (5.9 million MMK) as higher than that of Nagale (3.7 million MMK). That is why seasonal crop
7
production earned more income in Popa than in Nagale. Although there were more perennial crop income earners in Nagale, it earned higher amount of income in Popa. In addition, 40% of respondents in Popa had salary income, and earned 2.5 million MMK per household per year while only 11% had salary income in Nagale and earned 1.79 million MMK. Income sources and their share for sample households Figure 1(a) illustrates income sources and their share for sample households in Popa village. In Popa, the main income source was perennial crop income which contributed 37.3% of the household income. About 32.7% and 16.9% of the household income earned from seasonal crop production and salary jobs respectively. In addition, remittance income was about 7.3% of household income and non-farm income was about 5.6% of the household income. Figure 1(b) illustrates income sources and their share for sample households in Nagale village. The main income source was perennial crop income which contributed 65.9% of the household income. About 13.3% and 8.2% of the household income earned from non-farm jobs and remittance income respectively. Seasonal crop income contributed 6.8% of annual household income, and salary income was about 5.3% of household income. Only about 0.3 % and 0.1% of the household income were livestock income and farm labor income. Income diversification of sample households Table 3 shows income diversification of sample households. Herfindahl index was used to determine income diversification of the respondents. Index ranges from zero to one; zero reflects complete diversification, and one reflects complete specialization. Sample households were categorized into three groups, high diversification (index range from 0 to 0.35), moderate diversification (index range from 0.36 to 0.7), and low diversification (index range from 0.71 to 1) group.
8
According to Herfindahl index method, 13% of the sample households were within the index range of 0 to 0.35, and that means they had highly diversified income. The largest group of the respondents (46%) was within the index range of 0.36 to 0.7, and therefore, they had moderate income diversification. Moreover, 41% of the sample households had low income diversification with the index range of 0.71 to 1. The average Herfindahl index in Kyaukpadaung Township was 0.65, and maximum and minimum indices were 1 and 0.27. Determinants of average annual household income Selected factors for Household’s income were considered as independent variables in the model and their descriptive statistics were presented in Table 4. Factor affecting average annual household income is presented in Table 5. To determine the factor affecting average annual household income, nine independent variables were used in this regression analysis. Age, education and gender of household head, total farm size, number of income sources, perennial crop income and migration were positively related to average annual household income. Total farm size and number of income sources were significantly influenced on average annual household income at 1% level. This indicated that one percent increases in farm size and number of income sources expressing the average annual household income was expected to be increased by 0.43% and 0.58% respectively. It is clear that the more the number of income sources, the higher the income earns. Having of perennial crop income significantly influenced on average annual household income at 5% and thus, if the household had perennial crop income, the average annual household income will increase significantly by 0.42%. Households earned high income from perennial crops because perennial crops cultivation could give high profit. Migration influenced on average annual household income at 10% significant level, and if the household had migrant labor, the average annual household income will be increased significantly by 0.29%. Number of family labor was negatively related to average annual household income. If most of the 9
family members work only on farm, the average annual household income will be decreased by 0.07%, but it was not significant. Adaptation strategies for climate change used by sample households Table 6 shows distribution of respondents on adaptation strategies for climate change. By using four-point scale method, the weighted average score for adaptation strategy was determined and used to order the rank. As it was expected, weighted average score of expanding perennial crop cultivation was the highest, and it ranked the first strategy that farmers used to adapt with climate change impacts. Changing cropping pattern, changing crop varieties and crop diversification were ranked in 2nd, 3rd and 4th respectively. That is why farming practices are easier to follow by farmers than other strategies. Organic farming was rarely used in Kyaukpadaung Township, and it was in 11th rank. Selling out the land was the last choice for farmers. Conclusion and Recommendation The results of the study indicated that perennial crop income played an important role in rural household’s income in Kyaukpadaung Township. Respondents changed their land use pattern from seasonal crop production to perennial crop cultivation to combat with climate change impact. In addition, perennial crop production earned the highest amount of income, and the average annual income of perennial crops was the main income source among other income sources. Moreover, having perennial crop income was positively and significantly influenced on annual household income. Perennial crops cultivation earned higher income with greater profits. As expected, expanding perennial crop cultivation ranked the first adaptation strategy that farmers used to adapt with climate change impacts. In order to raise income level of the rural household for combating climate change impact, perennial crop income is vital and it would be enhanced. The share of non-farm income was very low, thus non-farm job opportunities would be created in the villages. If 10
farmers earn a lot of income from non-farm job, they will be able to bear risk and uncertainty and it may reduce migration, consequently. References Belyi, A. (2015, May 6). World Economic Forum. Retrieved May 25, 2017, from World Economic Forum Web site: https://www.weforum.org/agenda/2015/05/3-waysfarmers-can-combat-climate-change FAO. (2007). Adaptation to climate change in agriculture, forestry and fisheries: Perspective, framework and priorities. Food and Agriculture Organization of the United Nations. Mendelsohn, R., & Dinar, A. (1999, August 1). Climate change, agriculture, and developing countries: Does adaptation matter? The World Bank, 14(2), 277-293. Myo Win Maung, Juan, M. P., Maria Victoria, O. E., & Nelita, M. L. (2016, June). CLimate change awareness and farm level adaptation of farmers (Central Dry Zone) in Monwya Township, Sagaing Region, Myanmar. Journal of Environemntal Science and Management, 19(1), 46-57. Nelson, N., Igwe, F. A., K, C., & Iroadighiogu, M. (2016, September). Nigerian Journal of Agriculture, Food and Environment. Retrieved 3 20, 2017, from Nigerian Journal of Agriculture, Food and Environment: http://www.njafe.org/najafe2016vol12n3/30_ Nse_Nelson_et_al.pdf Ogundari, K. (2013). Crop diversification and technical efficiency in food crop production: A study of peasant farmers in Nigeria. International Journal of Social Economics, 40 (3), 267-288. Zhang, Y., Li, Y., Jiang, L., Tian, C., Li, J., & Xiao, Z. (2011). Potential of Perennial Crop on Environmental Sustainability of Agriculture . Procedia Environmental Sciences , 10, 1141–1147 .
11
Table 1 Perennial crop grown in Kyaukpadaung Township Perennial Crops Village Major Popa
Nagale
Minor
Dragon fruits, Mango,
Banana, Custard apple, Guava,
Tamarind
Jackfruit, Papaya
Banana, Custard apple,
Cashew nut, Coffee, Guava,
Dragon fruit, Mango,
Jackfruit, Papaya
Tamarind Table 2 Amount of annual income for sample households in Kyaukpadaung Township Types of Income
Income (‘000 MMK per annum)
No. of Households
Mean
Max.
Min.
SD
Popa Village (N=20) Seasonal crop income
19 (95)
2,058
8,902
333
1,910
Perennial crop income
14 (70)
3,184
13,250
400
4,113
Salary income
8 (40)
2,528
5,940
960
1,554
remittance income
7 (35)
1,251
4,920
360
1,646
Non-farm income
4 (20)
1,344
100
3,960
1,011
20 (100)
5,970
22,152
360
5,231
Total Income Nagale Village (N=80) Seasonal crop income
39 (49)
526
3,175
75
565
Perennial crop income
73 (91)
2,725
12,700
271
2,821
63
150
20
60
Farm labor income
4 (5)
Salary income
9 (11)
1,793
2,520
1,080
387
Remittance income
16 (20)
1,549
3,000
200
914
Non-farm income
31 (39)
1,299
3,960
100
1,037
Livestock income
2 (3)
425
500
350
106
3,772
14,425
430
2,970
Total Income
80 (100)
Note: Numbers in the parentheses represent percentage.
12
Non-farm income, 5.6% Remittance income, 7.3% Perennial crop income, 37.3% Salary income, 16.9%
Seasonal crop income, 32.7% Figure 1(a) Income sources and their share for sample households in Popa
Salary income, 5.3%
Livestock income, 0.3% Farm labor income, 0.1%
Seasonal crop income, 6.8% Remittance income, 8.2%
Non-farm income, 13.3%
Perennial crop income, 65.9%
Figure 1(b) Income sources and their share for sample households in Nagale
13
Table 3 Distribution of Herfindahl Index for Income Diversification No. of respondents
Herfindahl index
(n=100)
0.0-0.35
Highly diversified income
13 %
0.36-0.7
Moderately diversified income
46 %
0.71 -1.0
Low diversified income
41 %
Average=0.66,
Maximum=1.00,
Minimum=0.26,
SD=0.24
Table 4 Descriptive statistics of dependent and independent variables Description of variables
Unit
Mean
SD
Dependent variable Annual household income
Million MMK/year
4.347
3.596
Age of HH’s Head
Year
55.6
10.6
Education of HH’s Head
Year
7.2
3.4
No. of family labor
No.
2.4
1.0
Total farm size
No.
2.4
1.9
No. of income source
No.
2.2
0.9
Perennial crop income
Dummy
Independent variables
Yes = 1
(83)
No = 0
(17)
Gender of HH’s Head
Dummy
Male = 1
(91)
Female = 0 Migration
(9) Dummy
Yes = 1
(25)
No = 0
(75)
Note: Numbers in the parentheses represent percentage.
14
Table 5 Income function of the sample households in Kyaukpadaung Township (n=100)
Independent variables Constant Age of HH’s Head Education of HH’s Head No. of family labor Total farm size No. of income sources Perennial crop income Gender of HH’s Head Migration R Square Adjusted R Square Durbin-Watson statistics
Unstandardized Standardized Coefficients Coefficients B β *** 12.124 0.202ns 0.048 ns 0.210 0.112 ns -0.067 -0.031 *** 0.432 0.389 *** 0.584 0.298 ** 0.420 0.180 ns 0.259 0.085 * 0.288 0.143 0.420 0.368 1.990
t-value
Sig.
7.204 0.524 1.127 -0.334 4.225 3.692 2.027 0.853 1.769
0.000 0.601 0.263 0.739 0.000 0.000 0.046 0.396 0.080
Note: Dependent variable = Annual household income HH=Household ***, ** and * are significant at 1%, 5% and 10% level respectively and ns = not significant
Table 6 Distribution of respondents on adaptation strategies for climate change by using four-point scale rating method in Kyaukpadaung Township (n=100) Coping Strategies Expanding perennial crop cultivation Changing cropping pattern Changing crop varieties Crop diversification Agro forestry Adjusting sowing time Migration of household member Willingness to change occupation Willingness to migrate Selling out the livestock assets Organic farming Selling out the land
Never 0 32 69 62 59 86 83 83 83 86 97 98 98
15
A Few 1 16 10 22 32 3 11 12 12 11 2 1 2
Fair A Lot Weighted Rank average 2 3 17 35 1.55 1st 3 18 0.70 2nd 3 13 0.67 3rd 1 8 0.58 4th 2 9 0.34 5th 3 3 0.26 6th 3 2 0.24 7th 4 1 0.23 8th 2 1 0.18 9th 1 0 0.04 10th 1 0 0.03 11th 0 0 0.02 12th
