Keywords

Poor farmers, Non-Poor Farmers, Price of Rice, Price of Paddy.

Introduction

Rice is the most important staple food in Indonesia, so it plays a strategic role in food security there. Thus, an important government policy is implemented to ensure the availability of rice, thereby ensuring food security. The availability of rice is based on three pillars: (1) availability, (2) affordability, and (3) stability (Bulog, 2020). The availability and stability pillars are supported by paddy production programs.

Besides paddy production, the availability and stability pillars can be achieved by importing rice, but this is not recommended as the international rice market is unstable. In 2008, there was a shock in the price of rice on the international market (Seck et al., 2010). The increase in the price of rice was due to a decrease in supply. This incident is dangerous for countries that are dependent on rice imports.

An increase in paddy production can be achieved if paddy farming is profitable. The profit of paddy farming can increase if the price of paddy increases.

One of the factors influencing the price of paddy is the price of rice (Makbul & Ratnaningtyas, 2017). An increase in the price of paddy is important for paddy farmers as it can motivate farmers to increase paddy production. An increase in the price of paddy can stimulate paddy production (Bingxin & Fang, 2011).

A high rice price policy can increase paddy production, but such a policy can have a negative effect on rice consumers and can increase poverty (Warr & Yusuf, 2014), thereby increasing the poverty of paddy farmers as well (McCulloch, 2008). Therefore, a rice price policy must consider poor paddy farmers. A question that arises is “what are the characteristics of poor paddy farmers?” The answer to this question is important to ensure an effective rice policy. The question can be answered by conducting research that compares poor and non-poor paddy farmers and shows how an increase in the price of rice benefits poor paddy farmers.

Makbul (Makbul et al., 2021) concluded that an increase in the price of rice can benefit poor farmers, depending on whether the rice market is efficient. If the price transmission from rice to paddy is above 60%, an increase in the price of rice can increase the income of poor families. However, for non-poor farmers, the price of rice can benefit them if the price transmission is above 20%. This indicates that non-poor farmers benefit more if the price of rice increases. These facts raise the following questions: “Why is the impact on poor and non-poor farmers different?” and “What is the difference between the characteristics of poor and non-poor farmers?” These questions can be answered by conducting a study that compares the difference in the impact of an increase in the price of rice on poor and non-poor farmers. This research conducts this analysis.”

Literature Review

Saka et al. (Saka & Lawal, 2009) analyzed the adoption and productivity of paddy farmers in Nigeria. They demonstrated that, from a sociocultural perspective, the factors that influence the adoption and productivity of paddy farmers are (1) gender, (2) education, (3) activities in farmer groups, (4) access to alternative income, (5) age, (6) experience in farming, (7) land area, and (8) frequency of attending counseling. They found that education, activity in farmer groups, access to alternative income, land area, and frequency of attending counseling significantly influence adoption and productivity. (Basorun & Fasakin, 2012) conducted research on food security in Nigeria. They profiled rice farmers based on (1) gender, (2) regional origin, (3) age, (4) motivation, (5) income, (6) land area, (7) use of labor, (8) business costs of farmers, and (9) problems in agriculture. They concluded that motivation is the most important factor affecting farm profit. (Sahara et al., 2011) conducted research on farmers in Indonesia. In the research, the following variables, which are based on the characteristics of rice farmers, were used for the analysis: (1) rice production, (2) non-rice (vegetable) agricultural production, (3) vegetable prices, (4) total profit, (5) number of workers, (6) labor wages, (7) land area, (8), amount of fertilizer, (9) total household income of farmers, (10) per capita income, (11) family members, (12) educational level of the head of the household, (13) total time spent working on agriculture, (14) amount of free time, (15) food consumption pattern, (16) total food consumption, (17) non-food consumption, (18) amount of food purchased, (19) non-food expenditure, (20) total household expenditure, and (21) participation in farmer groups. The research found that the price of the product is important in increasing production and profit. (Fakkhong & Suwanmaneepong, 2015) analyzed the characteristics of rice farmers in Thailand. The farmers were characterized based on the following socioeconomic factors: (1) gender, (2) age, (3) education, (4) marital status, (5) social status, (6) number of family members, (7) number of farm workers, (8) farming experience, (9) land area, and (10) rice varieties. The research found that education, number of family members, farm workers, and land size significantly influence rice production. Alam (Alam et al., 2011) conducted research on the relationship between social economics and the productivity of poor rice farmers. The analysis was based on the following characteristics of poor paddy farmers: the race of farmers, gender, age, secondary occupation, education, family size, ownership of land, non-agricultural to agricultural income ratio, number of available vehicles, distance between home and field, farm size, mixed ownership land, own land, number of available machineries, location of farmland, and known current issues. They found that the education of farmers has a significant impact on agricultural output and productivity. Another variable that has a positive impact on the productivity of farm output is machinery.

Methodology

Research Methods and Locations

In this research, a survey of rice farmers in the Gantar district, Indramayu Regency, was conducted. The Gantar district was chosen as it is the largest rice producer in Indramayu Regency (BPS Indramayu, 2020a), and Indramayu Regency is the largest rice producer in West Java, Indonesia (BPS Jabar, 2020). The high rice production for that location probability the community that region is rice farmer.

Simple random sampling was employed to select the respondents. The equation in the study by Bartlett (Bartlett et al., 2001) was used to determine the sample size.

(1)

n = size of sample

t = t table at α=0.05

S = standard deviation

d = deviation tolerance

Based on preliminary research, the standard deviation of land size in locations is 0.83, with a deviation tolerance of 0.1. The t table of α = 0.05 is 1.96. The sample size of this research is calculated as follows:

Thus, the sample size is 268 respondents.

In this study, the variables of the characteristics of rice farmers are from the existing literature. The research variables are presented in Table 1.

Table 1 shows the research variables. Each variable is then analyzed based on the scale measure. The X2 test was employed for the nominal scale analysis, the Mann–Whitney U test to measure the ordinal scale, and the t-test to measure the ratio scale.

Table 1 Research Variables
Variable	Name	Measure	Unit
X1	Group	Nominal	0=non-poor 1=Poor
X2	Age	Ratio	Year
X3	Education	Ordinal	1=Basic school 2=Middle school 3=High school
X4	Sex	Nominal	1=Male 2=Female
X5	Activity in Farmer Groups	Ordinal	1= Very low 2=Low 3=Middle 4=High 5=Very high
X6	Farming Experience	Ratio	Year
X7	Main Job	Nominal	1=Agriculture 2=non-agriculture
X8	Number of Family Members	Ratio	Person
X9	Native Farmer	Nominal	0=Non-native 1=Native
X10	Farm Motivation	Ordinal	1=Very low 2=Low 3=Middle 4=High 5=Very high
X11	Farm Employees	Ratio	Person/Season
X12	Working Time	Ratio	Day/Season
X13	Labor Wages	Ratio	IDR/Day
X14	Family Income Perception	Ratio	IDR/Month
X15	Percentage of Income from Farming	Ratio	Percentage
X16	Farmland	Ratio	Ha
X17	Land System	Nominal	1=Arable 2=Own 3=Rent 4=Own & Arable 5=Own & Rent 6=Rent & Arable 7=Rent & Own
X18	Farm Pattern	Nominal	1=Paddy-paddy-abandoned 2=Paddy-paddy-soybean 3=paddy-paddy-vegetable
X19	Household Rice Consumption	Ratio	Kg/Month
X20	Household Rice Expenditure	Ratio	IDR/Month
X21	Household Food Expenditure	Ratio	IDR/Month
X22	Household Non-Food Expenditure	Ratio	IDR/Month
X23	Farm Cost	Ratio	IDR/Season
X24	Farm Production	Ratio	Kg/Season
X25	Farm Production Sold	Ratio	Kg/Season
X26	Price of Farm Production	Ratio	IDR/Kg
X27	Farm Revenue	Ratio	IDR/Season
X28	Farm Profit	Ratio	IDR/Season
X29	Farm Income	Ratio	IDR/Season
X30	Non-farm Income	Ratio	IDR/Month

Results

The results are presented in Table 2.

Table 2 The Results
Variable	Name	Measure	Statistic Test	Significant Result
X1	Group	Nominal	X Square	0	**
X2	Age	Ratio	t-test	0.5420
X3	Education	Ordinal	Mann–Whitney U	0.7270
X4	Sex	Nominal	X Square	0.2970
X5	Activity in Farmer Groups	Ordinal	Mann–Whitney U	0.9930
X6	Farming Experience	Ratio	t-test	0.0570
X7	Main Job	Nominal	X Square	1.0000
X8	Number of Family Members	Ratio	t-test	0.8080
X9	Native Farmer	Nominal	X Square	0.0000	**
X10	Farm Motivation	Ordinal	Mann–Whitney U	0.0950
X11	Farm Employees	Ratio	t-test	0.0000	**
X12	Working Time	Ratio	t-test	0.0000	**
X13	Labor Wages	Ratio	t-test	0.2920
X14	Family Income Perception	Ratio	t-test	0.0220	*
X15	Percentage Income of from Farming	Ratio	t-test	0.4660
X16	Farm Land	Ratio	t-test	0.0010	**
X17	Land System	Nominal	X Square	0.1160
X18	Farm Pattern	Nominal	X Square	0.7290
X19	Household Rice Consumption	Ratio	t-test	0.0000	**
X20	Household Rice Expenditure	Ratio	t-test	0.0020	**
X21	Household Food Expenditure	Ratio	t-test	0.0000	**
X22	Household Non-Food Expenditure	Ratio	t-test	0.0000	**
X23	Farm Cost	Ratio	t-test	0.0200	*
X24	Farm Production	Ratio	t-test	0.0000	**
X25	Farm Production Sold	Ratio	t-test	0.0000	**
X26	Price of Farm Production	Ratio	t-test	0.0000	**
X27	Farm Revenue	Ratio	t-test	0.0000	**
X28	Farm Profit	Ratio	t-test	0.0000	**
X29	Farm Income	Ratio	t-test	0.0000	**
X30	Non-farm Income	Ratio	t-test	0.0410	*

The variables that are significant in this research are group, native farmer, farm employees, working time, family income perception, land farm, household rice consumption, household rice expenditure, household food expenditure, household non-food expenditure, farm cost, farm production, farm production sold, price of farm production, farm revenue, farm profit, farm income, and non-farm income.

There are significant differences among the groups. Poor paddy farmers are 16% of the total paddy farmers in this research, indicating that the number of poor paddy farmers is not high. In this research, the criterion for determining the poor is based on the Statistics Indonesia (BPS) for the Indramayu Regency. According to BPS (BPS Indramayu, 2020b), the criterion of the poor is an income of 447.378 IDR/year. It is good news for the Indonesian government that most paddy farmers are not poor.

The difference between native and non-native paddy farmers is significant. We found that 69% of poor paddy farmers are natives, implying that most poor farmers are natives. This finding can be a subject of future research “why are native farmers poorer than non-native farmers?” The reason may be that non-native farmers work harder than native farmers, but this opinion must be verified by another research.

The number of farm employees and the working time of the poor and non-poor paddy farmers are significantly different. The number of employees and the working time of non-poor paddy farmers are twice those of poor paddy farmers. Thus, non-poor paddy farmers work harder than poor paddy farmers, suggesting that the hard work of non-poor farmers is the reason why they are not poor.

Family income perception is significantly different among poor and non-poor paddy farmers. The mean incomes of poor and non-paddy farmers are 1.526.295,45 and 2.023.080,36 IDR/month, respectively, indicating that the mean income of non-poor farmers is 25% higher than that of poor farmers. This research used perceived income as it is difficult to know the actual income. Poor paddy farmers do not keep accounting records.

The farmlands of poor and non-poor paddy farmers are also significantly different. The mean land size of poor paddy farmers is 0.74 ha, whereas that of non-poor paddy farmers is 1.26 ha. Farmland is the ultimate factor for the success of the farm, which is not surprising.

Rice consumption and expenditure of households of poor farmers are higher than those of households of non-poor farmers, but regarding food and non-food expenditures, those of non-poor farmers are higher than those of poor farmers. This is because poor paddy farmers are more concerned about basic needs.

The farm cost, production, revenue, and profit of non-poor farmers are higher than those of poor farmers. This is logical as non-poor farmers have more land farms than poor farmers. However, interestingly, this research found that the prices of paddy from their farms are different; the price of non-poor farmers is higher than that of poor farmers, although the product has the same quality. This may be that the marketing skills and entrepreneurship of non-poor farmers are better than those of poor farmers. However, research is needed to confirm this assertion.

The non-farm income of non-poor farmers is better than that of poor farmers. This may be that non-poor farmers have better business skills than poor farmers. The non-poor farmers are not only better in their entrepreneurship farming business but also in non-farming business.

Discussion

In the Introduction section, we found that an increase in the price of rice has a different impact on poor and non-poor paddy farmers. This research aimed to determine whether the impact of an increase in the price of rice on poor and non-poor farmers is different and to identify the characteristics of poor and non-poor farmers. This research explores many characteristics of poor and non-poor paddy farmers.

The result of this research demonstrates that the following characteristics of poor and non-poor paddy farmers are significantly different: native farmer, farm employees, working time, family income perception, farmland, household rice consumption, household rice expenditure, household food expenditure, household non-food expenditure, farm cost, farm production, farm production sold, price of farm production, farm revenue, farm profit, farm income, and non-farm income.

The percentage of non-native farmers that are non-poor is more than that of poor farmers; this may be due to the economic hardship in the region. Because non-native farmers struggle to survive, they are encouraged to engage in farming. This attitude has probably a different impact on the increase in the price of rice. The price of paddy products of non-poor farmers is higher than that of poor farmers.

Other relevant characteristics that are significantly different among poor and non-poor paddy farmers are farm employees, working time, family income perception, farmland, farm production, price, and profit. Non-poor farmers have better results than poor farmers. This may be because non-poor farmers are concerned about both their farm and non-farm businesses.

There are similarities and differences between the current and previous research (Alam et al., 2011; Basorun & Fasakin, 2012; Fakkhong & Suwanmaneepong, 2015; Sahara et al., 2011; Saka & Lawal, 2009). (Alam et al., 2011) found that the educational level of farmers has a significant impact on agriculture and productivity, but this research finds that the impact of the education of poor and non-poor farmers is not significantly different. This is probably because, in this research, the educational levels of farmers are nearly homogeneous. The general educational level of farmers in the research location is basic, which is probably insignificant. If research is conducted in another location where farmers have various educational levels, the difference may be significant. (Basorun & Fasakin, 2012) found that motivation and farm profit are important to farm productivity. However, in this research, motivation is nearly significant (α = 0.09). If the criterion for significance was α<0.1, this characteristic would have been significant, but unfortunately, the criterion is α < 0.05. The findings about profit in this research are similar to those of the study by Basorun and Fasakin. This research found a significant difference between the profit of poor and non-poor farmers.

(Fakkhong & Suwanmaneepong, 2015) found that educational level, number of family members, farm employees, and land size are significant. With regard to farm employees and land size, the findings of this research are similar to those of the study by Fakhong; both found that they are significant. However, the farm employees and land size of non-poor farmers are higher than those of poor farmers. (Sahara et al., 2011) found that price is important to an increase in paddy production, which is similar to the finding of this research. The price of paddy of non-poor farmers is higher than that of poor farmers, indicating a significant difference.

(Saka & Lawal, 2009) found that education, activity in farmer groups, access to alternative income, land area, and frequency of attending counseling have a significant influence on adoption and productivity. The similarity between the study by Saka and Lawal and this research is that access to alternative income and land area is significant. The non-farm income and land size of non-poor farmers are significantly different from those of poor farmers.

The limitation of this research is that it only explores the characteristics of poor and non-poor farmers quantitatively. The research does not conduct a deep qualitative analysis of the characteristics. A future study can complement this research.

Conclusion

Non-poor farmers have more opportunities when the price of rice increases; it also increases their farm profit because they have entrepreneurship capability, and they are concerned about their farm business. For example, they have more farm working time and a greater number of employees. Moreover, in marketing their product, non-poor farmers set a higher price than poor farmers, although their paddy products are of the same quality. The limitation of this research is that it conducts only a quantitative analysis of the characteristics of poor and non-poor farmers. Future research can conduct a detailed qualitative analysis of the characteristics of both poor and non-poor farmers.

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