Effect of input factors and price policy in Nepalese sugarcane

Abstract

The present study examines the effect of price policy, payment period and production factors in sugarcane production. Data were collected from 200 sugarcane producers in Nawalparasi and Kapilvastu district of Nepal. Linear multiple regression was used as the analytical technique. Findings revealed positive and significant effect of labour, chemical fertilizers, weeding and irrigation frequencies at 1% and 5% level of significance. The impact of Minimum Procurement Price (MPP) and direct cash subsidy were found insignificant, and delay in payment to the farmer was negative and significant at 5% level of significance. Similarly, the coefficient of multiple determinations (adjusted R²) was 0.93, which indicated that 93% variation in sugarcane yield was explained by all explanatory variables. The results showed delay in payment as major challenge disrupting the effective implementation of price policies (Minimum Procurement and direct cash subsidy) and farmer economy. The delay payment was responsible for the consequences of losses, financial distress, shift of sugarcane cultivation and ultimately decreasing the sugarcane area and production. Thus, scientific MPP, strict regulation and monitoring of sugar-mills, stock clearance of surplus sugarcane by government, incorporation of local crushers under sugarcane policies and activities, and release of direct cash subsidy during the sugarcane cultivation period could be a better solution to maximize sugarcane production.

Keywords:

• sugarcane
• procurement
• subsidy
• payment and production

PUBLIC INTEREST STATEMENT

Sugarcane is a commercial cash crop cultivated in Nepal and contributes 2.1% to Nepalese AGDP. The domestic production of Sugarcane covers 60% of sugar demand of the country. After the establishment of the sugar industries sugarcane commercial cultivation was started, thereafter the commercial production of the sugarcane and its area has increased. Government of Nepal annually announces Minimum Procurement Price (MPP) prior to crop harvest. Further, Government of Nepal (GoN) is providing direct cash subsidy and subsidy on chemical and organic fertilizers, mechanization and insurance services. Despite of these programs, sugarcane industry has some challenges like lower productivity, unscientific price fixation and delay payment by sugar-mills. Similarly, high cost of production, traditional cultivation practices and the problem of marketing are major hindering factors for sugarcane development. So, the study analyses existing problems, effects of price policy (MPP and direct cash subsidy) and production factors in sugarcane production.

Competing Interests

The authors declare no competing interests.

1. Introduction

Sugarcane is commercial cash crop cultivated in Nepal and contributes 2.1% to Nepalese AGDP (MoALD, 2019c). The cultivation of sugarcane is in 41 districts of Nepal but commercial cultivation is reported in 14 districts only (MoAD, 2013, 2014, 2015, 2016; MoALD, 2017, 2018). Sugarcane is extended in 78,609 ha with the average productivity of 45.26 MT/ha. The productivity of sugarcane reported is 45 MT/ha only which is comparatively very low in comparision to the potential capacity of recommended varieties in Nepal (MoALD, 2019a). It is the only source of sugar in Nepal, which is also used to produce food products like sugar, fructose, syrups, and molasses and jiggery (Dotaniya et al., 2016). The domestic production of Sugarcane covers 60% of sugar demand of the country (NSMA, 2018). After the establishment of the sugar industry sugarcane commercial cultivation was started; thereafter, the commercial production of the sugarcane and its area has increased.

Since 2036 for the first time Government of Nepal declared Minimum Procurement Price (MPP) in Nepal. Government of Nepal annually announces Minimum Procurement Price (MPP) prior to crop harvest. MPP estimation includes incurred cost of production, transportation cost, certain percentage of benefit to the farmers and cash subsidy of the government. In 2019/20 the MPP was Nepalese currency (NRs) 536.56 per quintal (MoALD, 2019b). Further, Government of Nepal (GoN) is providing subsidy on chemical and organic fertilizers, mechanization and insurance services (MoALD, 2019a). Since 2016 to encourage the farmer for higher production GoN initiated production-based cash subsidy. The subsidy system was initiated as sugarcane promotion expenditure NRs 25 per quintal in 2016. Since 2017 cash subsidy was increased from NRs 25 to NRs 65.68 per quintal. After 2019, there was provision of direct payment of cash subsidy to the farmer where cash subsidy was 65.28 NRs per quintal. Production-based cash subsidy is incorporated in MPP, during estimation of MPP (MoALD, 2019b). Government of Nepal allocated NRs 1.33 billion of budget as Value addition direct cash subsidy for cash subsidy to the farmer in 2020 (MoF, 2019). Despite of these promotion programs, Sugarcane industry has some challenges like lower productivity, unscientific price fixation and delay in payment by sugar-mills. There are disputes between farmers and sugar producers in relation to the MPP and price settlement. Similarly, high cost of production, traditional cultivation practices and problem of marketing are the major hindering factors for sugarcane development (Neupane et al., 2017; Pokharel et al., 2019; Sapkota et al., 2017). So, the study analyses existing problems, effects of price policy (MPP and direct cash subsidy) and production factors affecting the sugarcane production of Nepal.

1.1. Research methodology

The study performed multistage sampling for selection of research site. Nawalparasi and Kapilvastu district in Province no. 5 were the research area. Furthermore, Nawalparasi and Kapilvastu district rank third and fourth, respectively, in sugarcane production (MoALD, 2018).

The first stage selection of these districts was based on presence of sugar-mill. Nawalparasi district was randomly selected among the commercial sugarcane producer districts with sugar-mills and Kapilvastu district from commercial districts without sugar-mills. There are 34 registered sugar-mills in Nepal, among them only 14 sugars-mills are operating in 8 districts. Whereas other districts without sugar-mill are depending on local crushers and small-scale sugar refining industries (MoALD, 2020; NSMA, 2018). The district where there is presence of sugar-mill there is provision of price policy programs like MPP and direct cash subsidy through sugar-mills. But the local crushers and other small-scale industries are not bounded with the price policy programs. Thus, the selection of district with and without sugar-mill helps to study, analyze and compare the effect of the payment system, price, and status of MPP and cash subsidy in between these two districts.

Similarly, second stage sampling was purposeful to select municipalities and rural municipalities inside respective districts which had higher sugarcane production area and sugarcane farmer. Second sampling was based on FGD in Agriculture Knowledge Center (AKC) of both districts, discussion among the concerned authorities, and review of districts profile. The survey sites (wards) i.e. third-stage sampling procedure, was randomly selected from selected rural municipalities and municipalities of both districts. From each selected village, a list of sugarcane growers above 0.16 ha was made as a sampling frame. There were a large number of small-scale farmers, hence to prevent the selection of a large number of small-scale farmers and include all kind of famer in proportion, farmers with 0.16 ha and above were selected for the study. Proportional allocation of sampling technique was used to obtain an appropriate number of sugarcane farm household from each selected ward. For the household survey, approximately about 10% of the sample was selected randomly from the sampling frame (which is the population of the farm household above 0.16 ha) (Cochran, 1977). Thus, 200 sugarcane growers (135 from Nawalparasi and 65 from Kapilvastu) were selected from 5 wards of selected municipalities and rural municipalities. According to the FGD and discussion with respective AKC, probable number of farmers cultivating sugarcane above 0.16 ha in respective wards were noted and sample farm households were selected randomly (Table 1).

Table 1. Research site, population and sample number from the respective study area

District	Municipality	Population	Sample Number
Kapilvastu	Shivraj Municipality	300	30
Kapilvastu	Krishnanagar Municipality	350	35
Nawalparasi	Sunwal Municipality	300	30
Nawalparasi	Pratappur Rural Municipality	500	50
Nawalparasi	Susta Municipality	550	55
Total		2000	200

1.2. Research and data collection process

For primary information and triangulation of available information, four focal group discussion was done (2 in Nawalparasi and 2 in Kapilvastu). The sugarcane stakeholders like farmers, sugar-mill and crushers respondents, and officials of Agriculture Knowledge Center of both district were involved in FGD. Similarly, KIIs and household survey were done to collect required information, ideas and insights on certain area of interest. Thus, Primary information was gathered through FGD, KIIs, household survey and direct observation. Whereas the literature and publications of sugarcane were secondary sources of information.

1.3. Statistical analysis

Multiple regression analysis was used to measure the relative impacts of predictor variables on the sugarcane yield (Gujarati, 2009; Zou et al., 2003). This analysis is based to linear multiple regression model with more than two explanatory variables, Xij, for i = 1, …, n subjects, j = 1, …, n explanatory variables and linear with regression parameters. In general the multiple regression model is expressed as Yi = a + bXi +ei, where the regression parameter a is the intercept (on the y axis), and the regression parameter b is the slope of the regression line. The random error term ei is assumed to be uncorrelated, with a mean of 0 (normal distribution) and constant variance. Correlations were worked out between predictors with respective yield of crop. Similarly, heteroscedastic test was done to obtain significant multiple regression mo (Gujarati, 2009; Gujarati & Porter, 1999).

The model included the analysis of the marginal effect of price policy (MPP and direct cash subsidy), delay payment, weeding and irrigation frequency, and analysis of elasticity of the production factors like labour, chemical fertilizer, seed and machine hours. To measure elasticity, natural log was given to sugarcane yield (dependent variable) and labour, chemical fertilizer, seed and machine hours(independent variable) (Gujarati, 2009).

1.4. Model specification

The linear multiple regression was specified for this study.

The model used is given as Equation (1)1 $lnYi=\beta 0+{\beta }_{1}ln{X}_{1i}+{\beta }_{2}ln{X}_{2i}+{\beta }_{3}ln{X}_{3i}+{\beta }_{4}ln{X}_{4i}+{\beta }_{5}ln{X}_{5i}+{\beta }_6{X}_{6i}+{\beta }_7{X}_{7i}+{\beta }_8{D}_{2I}+{\beta }_9{D}_{3i}+{\beta }_{10}{X}_{8i}+ui$1

1 $lnYi=\beta 0+{\beta }_{1}ln{X}_{1i}+{\beta }_{2}ln{X}_{2i}+{\beta }_{3}ln{X}_{3i}+{\beta }_{4}ln{X}_{4i}+{\beta }_{5}ln{X}_{5i}+{\beta }_6{X}_{6i}+{\beta }_7{X}_{7i}+{\beta }_8{D}_{2I}+{\beta }_9{D}_{3i}+{\beta }_{10}{X}_{8i}+ui$1

where, the subscript “i”, denotes the ith farmer in the sample, and

Yi = Output of sugarcane (Kg/ha),

β0, … … … ., β10 = Parameters to be estimated,

X_1i = Human labor (human days/ha)

X_2i = Quantity of fertilizers (NPK) (kg/ha)

X_3i = Quantity of seed (kg/ha),

X_4i = Machine hour (hours/ha),

X_5i = Previous price of sugarcane (NRs/kg),

X_6i = Irrigation frequency (numbers per hectare),

X_7i = Weeding frequency (numbers per hectare)

D_2i = Minimum Procurement (Price MPP), Dummy variable (1 = MPP, 0 = MPP)

D_3i = Direct cash subsidy, Dummy variable (1 = yes, 0 = no)

X_8i = Delay in cash payment (years),

u_i = random error

n = Number of farms growing sugarcane

The computer statistical software Stata 13.1 version was used to estimate parameters of explanatory effects.

1.5. Validity of model assumptions

For validity of model assumptions hypothesis of homoscedasticity, normal distribution and no multicollinearity was tested. Brush-Pagan, Jerque Bera (JB) and Variance inflation factors (VIF) tests were carried, respectively, for heteroscedasticity, normal distribution and multicollinearity in the model (Gujarati, 2009).

From Table 2, the given test the model was found homoscedastic, no multicollinearity and normally distributed so the model is valid for prediction.

Table 2. Hypothesis testing for Heteroscedasticity, Multicollinearity and Normality

Null Hypothesis	Alternative hypothesis		P> Chi^2	Result
H0 = Constant variance of ui (Homoscedasticity)	H1 = Heteroscedasticity	Chi^2 = 2.18	0.1394	Null hypothesis is accepted the, model is homoscedastic
H0 = No multicollinearity	H1 = Multicollinearity	VIF = 2.35	VIF<5	Null hypothesis is accepted the, there is no multicollinearity
H0 = No Normal distribution	H1 = Normal Distribution	Chi^2 = 8.34	0.154	Null hypothesis is accepted the, model is normally distributed

2. Result and discussions

2.1. Description of socio-economic characteristics pertaining to the sugarcane farm household the study area

The average age of the household head was 47 years, the greatest age of sugarcane farm household head was 77 years and the smallest age was 20 years. Table 3 shows insignificant effect of the age in sugarcane production. Similarly, the average household size was 7 which was larger than average household size of Nepal i.e 4.8 (CBS, 2017). The coefficient for household size was positive and significant at 1 and 5% level of significance. This implies that family size contributed in increasing the sugarcane production. This might be due to involvement of more adult members from household as quality labour to carry farming activities in timely fashion, thus making the production process more efficient. This finding was parallel with finding of (Girei & Giroh, 2012). Similarly, from Table 3, average landholding of the sugarcane farm household was 0.93 ha (including both lease and own land), and average land area under the ownership of farm household was 0.76 ha which was greater than national landholding i.e. 0.6 ha of Nepal (CBS, 2012). Some sugarcane farm households devoid of land were found earning the lease land (Adhiya).Among the average of total land holding ie 0.93 ha, 0.75 ha was allocated for sugarcane production which depicts that major crop of the study area was sugarcane. The estimated coefficient of land area was negative and significant at 10% level of significance. Households with small size of land were producing more than large farm size. This might be due to easy and proper care with optimum allocation of resources in small area in comparison to the large land holding. Similarly, the management of large area is difficult than small area (Mohapatra & Sen, 2013). The finding was consistent with the finding of (Haq et al., 2016; Msuya & Ashimogo, 2005).

Table 3. Description of socio-economic characteristics pertaining to the sugarcane farm household

Economic parameters	Minimum	Maximum	Mean	tvalue	p>|t|
Age of Household head (year)	20	77	47	0.35	0.728
Household size	3	27	7	2.8***	0.005
Gender (1 = male, 0 = others)	-	-	182	0.12	0.907
Percent of area covered by irrigation facility	0	100	49	3.6***	0.000
Own land holding(ha)	0	5.3	0.76	1.44	0.152
Lease land holding(ha)	0	2.3	0.18	0.78	0.434
Total area of sugarcane cultivation(ha)	0.16	4	0.75	−1.92*	−0.056

Similalry, around 49% of area of farm household was available with irrigation facilities. The result estimated positive and significant effect of irrigation area in sugarcane production at 1% and 5% level of significance. But more than 50% of household were deprived of irrigation, some farm were irrigating through neighbour infrastructures.

2.2. Description of production, cost and price of sugarcane in study area

Table 4 shows the statistics of production data of a hectare land. The cost of production of main crop was NRs. 472.6/quintal and NRs. 389.7/quintal, respectively, in Nawalprasi and Kaplivastu district. Thus, Nawalparasi had higher cost of production than Kapilvastu. The study revealed average revenue from a hectare land for main crop in Nawalparasi and Kapilvastu NRs. 188107 and NRs. 158203, respectively. The average productivity of the main crop was 41.9 tonnes/ha which was lower than the national productivity of Nepal. Similarly, the minimum price in Nawalparasi was NRs. 200 and maximum NRs. 536.56, where fluctuation (Standard deviation) was 85, greater than Kapilvastu. Despite minimum procurement price (MPP) NRs 536.56 per quintal, farmers were found selling their product below the MPP. This shows even though declaration of MPP and direct cash subsidy, there was fluctuation in sugarcane price.

Table 4. Productivity, cost and price pertaining to sugarcane production

Description	Quantity		Main crop cost
	Quantity unit/ha	Quantity	Cost unit	Nawalparasi	Kapilvastu	Total
Labor	Number of labor days	178	NRs./ha	74949.44	66251.07	72122.7
Seed	Quantity of seed kg	7578.3	NRs./ha	38760.8	35572.6	37724.6
Tillage	Hours of machine for land preparation	15.77	NRs./ha	23126.8	16996.6	21134.5
Fertilizers	Quantity of chemical fertilizer in kg	330	NRs./ha	21961	19210	21066.93
Compost	Quantity of compost in kg	4347.5	NRs./ha	14481.6	12474	13829.3
Irrigation hour	Irrigation hour	9	NRs./ha	4948.79	2513.18	4157.22
Weeding frequency	Weeding frequency	2	NRs./ha	516.3	933.178	651.78
Transport			NRs./ha	20116.4	10658	17042.5
Yield			tonnes/ha	41.9	42.04	41.9
Total cost (NRs./ha)			NRs./ha	185217.8	152135.3	174466
Cost			NRs./Quintal	472.6	389.7	445.7
Total Revenue			NRs./Quintal	188107	158203	178388.4
Price	NRs./Quintal		Minimum	Maximum	Mean	St. dv
Nawalparasi			200	536.56	492	85
Kapilvastu			275	530	378	37

Source: Field survey, 2020.

2.3. Market and availability of MPP and direct cash subsidy

Figure 1. depicts majority of farm household in Nawalparsi district selling their cane to sugar-mill whereas, Kapilvastu farm household sold their cane solely to local crusher. Similarly, only 33 and 91% of sugarcane farm households from the Nawalparasi district only received MPP and direct cash subsidy, respectively. Farm households from Kapilvastu were devoid of MPP and cash subsidy due of absence of sugar-mill. Problem of delay payment was faced by 92% of farm households in Nawalparasi, whereas the farmers of Kapilvastu district were timely payed. Thus, this shows that sugar-mills were paying late than local crusher. Hence, the problem of delay payment and higher price fluctuation was in Nawlprasi district.

Figure 1. Percentage of farm household selling cane to sugar mills and local crushers, and receiving MPP and direct cash subsidy in study area.

2.4. Market price of sugarcane

In Nawalparasi, 12% of total production was sold to local crusher in low price at NRs 280/quintal. Similarly, 81% of total production was sold to sugar mill. Similarly, around 7% of production was sold to others like middleman, neighbours and kept for seed purpose. Similarly in Kaplivastu 82.8% of production was sold in crusher alone at price NRs 378/quintal, remaining 17.2% was kept for seed purpose. Kapilvastu farmers were compelled to sell their produce in local crusher. However, the cane price provided by local crusher in Kapilvastu was higher than price provided by local crusher of Nawalparasi. Overall, the price provided by sugar mill was NRs 496/quintal, higher than crusher price NRs 310/quintal (Table 5). Results showed that farmers were interested to sell their maximum product to sugar-mill due to MPP and direct cash subsidy. However,, the disputes in sugar mill and delay payment were major constraints in selling the cane to local crusher with lower price.

2.5. Statistical analysis of input and price policy (MPP and direct cash subsidy) in sugarcane yield

The coefficient of adjusted R² was 0.93, which indicates that 93% variation in sugarcane yield is explained by all of the explanatory variables. The F-value was 280.39 and p value (P = 0.00) highly significant at 1% level of significance, indicating that regression model of production function fitted very well.

In Table 6, the regression model has estimated the effect and elasticity of labour, chemical fertilizers, seed, machine and the previous year price of sugarcane in sugarcane yield. Similarly, significance of intercultural operations like irrigation and weeding frequency was estimated. Further, the market factors like price of previous sold sugarcane, delay in payment of sugarcane and price policy factors like cash subsidy and MPP was studied to analyze their effect in sugarcane production.

Table 5. Percentage of sugarcane production sold in available sugarcane market with respective average price (NRs./quintal)

Markets	Nawalparasi		Kapilvastu		Total
	Quantity Sold %	Price	Quantity Sold %	Price	Quantity Sold %	Price
Factory	81	496	0	0	60.2	496
Local crusher	12	280	82.8	378	32.5	310
Others	7	480	17.2	400	7.3	460

Source: Field survey, 2020.

Table 6. Regression analysis of inputs and price policy in sugarcane yield

Yieldln	Description	Coefficient	Std. Err	t value	P> |t|
Laborln	Number of labor days	.087***	.03	2.87	0.005
Fertln	Quantity of chemical fertilizer kg per ha	.096***	.022	4.31	0.00
Seedln	Quantity of seed kg per ha	−.062	−.058	−1.08	0.283
Macln	Hours of machine for land preparation	.0024	.019	0.13	0.898
Priceln	Price of cane sold (NRS per kg)	.04	.047	.85	0.396
Irrigation	Number of irrigation	.034***	.009	3.8	0.00
Weed	Number of weeding	.288***	.015	19.16	0.00
Minimum Procurement Price (MPP)	Dummy Variable (1 = yes, 0 = no)	−.031	−.020	−1.53	0.127
Direct cash Subsidy	Dummy Variable(1 = yes, 0 = no)	.0144	.024	.62	0.538
Delay payment	No of years delayed for payment	−.03**	−.0117**	2.56	0.013
Constant		8.84	.533	16.58	0.00
R-square		0.94
Adjusted R-square		0.93

*, ***, ***: significance at 10, 5, 1%, respectively.

From Table 6, the coefficient of the inputs like labour, chemical fertilizer was positive and statically significant at 1 and 5% level of significance, its means that yield is relatively elastic to the change in labour and chemical fertilizers. Increase in 1% of chemical fertilizer increases the yield by 9.6% keeping the other factor constant. This is not surprising, since the use of fertilizer tends to increase production. This finding was in line with (Dlamini et al., 2010; Hussain, 2010; Nanthakumaran & Palanisami, 2013).

Similarly, increase in 1% of labour increases the yield by 8.7%. The sugarcane cultivation in study area was labour intensive, engagement of labour for different operation weedings, trashing, application of pesticides, and fertilizers may have increased the labour number which had significant effect in increasing the yield. This finding was consistent with (Dlamini et al., 2010; Nanthakumaran & Palanisami, 2013)

Furthermore, the coefficient of seed was negative but statistically insignificant. This may be due to dense transplanting i.e. 70 to 90 cm) of traditional poor-quality varieties. There was lack of improved varieties and seed replacement in both districts. Farmers were planting the setts produced in their own field, or burrowing from neighbour and Indian farmers. 70.5% of farm household kept top portion of last year sugarcane stalk as setts, whereas 27% of farmers relied either on neighbours or even Indian source and only 2.5% used setts distributed from sugar factory. Likewise, 33.5% of respondents used local varieties without replacing seed even for 5 years and 66.5% of respondents used improved varieties, replacing within 5 years. Most of farmers (52.2%) were unaware and unknown to variety name. Some of the widely mentioned and cultivated varieties were early-991, Sher-Punjab, 1092, Haryana-70, and BU128.

Farmer household were found to using machines widely for land preparation, however, dominance of human labour was evident for other inter-culture operation. 97% of farmers were found to be using MB plough, rotator, disk plough, and land raiser and 3% farmers were found to be using draft power for land preparation. No machines were intervened for setts transplantation, weeding and harvesting. Around 15.77 h was allocated for land preparation. Since the coefficient of machine hours spent for land preparation was positive but statistically insignificant. This might be due to use of machines for only flat and furrow method i.e. conventional method. No farm households were practising trench method for sugarcane cultivation which has significant and positive effect in sugarcane yield (Bhullar et al., 2008; A. Singh et al., 2012; G. Singh et al., 2015). Similarly, the study of (G. Singh et al., 2015) reported insignificant effect of pre-planting conventional tillage hours in sugarcane yield which was in line to this finding.

The price of cane was found insignificant to the yield of sugarcane. This was due to the delay payment system of sugar-mills and low payment by local crushers. Since the farm households who were paid full MPP or higher price were getting their cash after certain period. And the farm household who sold their cane at negotiated price to the sugar-mills and local crushers, their price was lower than the cost of production. Thus, the delay payment and price fluctuation were reasons for reducing the production.

The coefficient of irrigation frequency was positive and statistically significant at 1 and 5% level of significant, depicts that when irrigation time is increased, yield increase by 3.4%. The result is not surprising because sugarcane is perennial and demand high amount of water for growth and development. The coefficient of weeding number was 0.288 and significant at 1% and 5% level of significance. This implies that the number of weeding had positive relation to the sugarcane yield, sugarcane output is elastic to weeding number, increase in 1% of weeding activities increases the yield by 0.288% and vice versa. The finding is not surprising, since the weed are host for diseases and pest, they compete for light, water and nutrients which restrict the quantity and quality of production. So the weeding activities help to reduce the weeds infestation, which helps in increasing the production of sugarcane (Showler & Reagan, 1991). The study of (Ahmad et al., 2014) was consistent with this result.

The coefficient of delay in payment was negative and significant at 5% level of significance which implies that increased number of years for payment decreases the yield of sugarcane by 3%. Due to the delay payment, farm household was unable to acquire the inputs like fertilizers, improved seeds, and carry out the intercultural operation like weeding, earthing and plant protection-related activities. Since, the farm household with sugarcane as major source of income, their livelihood was negatively and highly effected by the delay payment.

Similarly, coefficient of MPP was statistically insignificant and negative to the yield of sugarcane. Whereas the coefficient of direct cash subsidy and price of cane are positive but statistically insignificant. The reasons for insignificant effect of direct price and cash subsidy and MPP is interrelated to market type and delay payment which is discussed below.

2.6. Effect of delay payment in price policy and sugarcane production

Figure 2 illustrates the overall effect of delay payment in sugarcane. Every year MPP and direct cash subsidy is declared before harvesting. Sometime sugar-mill are reluctant to accept the MPP and the reason behind it is a uniform price fixation to the high quality and poor quality cane. With these issues after declaration of MPP, dispute arises between farmer and sugar-mill in relation to price and creates problem like delay opening, and sudden closing of sugar-mill. With initiation and continuation of dispute and closure if sugar-mill hampers the harvesting time and storage quality of canes. The uncertain of prolonging closure of sugar-mill compels the farmer to choose alternative market to sell their cane which results in intervention of middleman and local crusher in sugarcane market.

Local crushers are found in majority numbers as small-scale industry producing good, jaggery, molasses, and bagasse from canes. Almost of canes in Kapilvastu district was sold to local crushers due to absence of sugar-mills. Similarly, crusher intervention in Nawalparasi was mainly due to uncertainty of sugar mill operation. Government of Nepal has assigned MPP including direct subsidy through sugar-mill only, but the local crushers are not included on those policies. So crushers were found exploiting the price of sugarcane and they decided price themselves individually. Though crushers pay in time, the existence of price fluctuation, mostly the lower price makes the farmer in dilemma either to continue sugarcane cultivation or not. Comparatively, price of sugarcane in crushers of Nawalparasi was found lower than Kapilvastu that depict local crusher taking large situational advantages from the disputes and closure of sugar-mill.

In response to closure of sugar-mill and delay payment, the middle man and agents were found innervating in market channel. Although they paid in time, they were paying lower price and taking dual profit, one from the price margin and another from as cash subsidy provided by government.

Minimum procurement price is highly needed for all of the farm households, but only 45 farm household of Nawalparasi received MPP whereas other farmer negotiated for price below the MPP. Similarly the disputes of sugar-mill stakeholder and farmer regarding the MPP has led to delay payment of sugarcane. The delay payment was found more problematic than the price fluctuation, because the cost of capital involved for sugarcane cultivation becomes more than revenue when farmer receives the revenue later. Whereas the instant payment helps to repay the debt incurred in sugarcane cultivation and others which ultimately helps to balance and support the sound economic activities of farmers. The study reveals that with the increasing in the delay of payment farmers are unable to purchase the quality seeds, fertilizers, carry out inter-culture operation, and hire machine for land preparation. The next year production becomes comparatively very low resulting the lower production, further the delay payment of next and earlier production, farmer becomes more unable to buy the inputs and carry cultivation activities. This kind of cycle breaks the economy to the farmer leading famer to debt and deepens to poverty. Many of the farmers were found expending the direct cash subsidy to run their daily life activities rather than using for sugarcane promotion.

Figure 2. Effect of delay payment in sugarcane cultivation and production.

Figure 3. Perception to shift sugarcane cultivation (%).

2.7. Shift in sugarcane cultivation

The direct observation, FGD and survey found farmers reluctant to invest in sugarcane as the main crop. Most of the present crop was ratoon crop of more than three generations without practicing the inter-culture operations and application of adequate fertilizers. From the study, it was found that 52% of households were planning to shift the sugarcane by other crops. Among them 62% and 32% of farm households in Nawalparasi and Kapilvastu, respectively, were planning to replace sugarcane by other crops (Figure 3). The higher price fluctuation and delay payment in Nawalparasi were the main reasons for the shifting of sugarcane.

3. Conclusion

For the higher sugarcane production, inputs like chemical fertilizers, labours, weeding and irrigation frequency plays significant role. So, the guarantee supply of sufficient and subsidized agriculture commodities like high yielding variety setts, modern agri-machineries, organic and inorganic fertilizers, irrigation infrastructures and plant protection measure are boon for higher production. The cost for sett was higher thus subsidized and quality sett must be made available to farmer. Thus, the government should allocate sufficient budget for programs related to researches, varietal development and extension of advance technologies for research institute like Nepal Agriculture Research Council (NARC). For the agro-machineries the provincial government should conduct the program like custom-hiring centre for sugarcane production through where farmers can hire advanced sugarcane machineries at reliable price. Further to run the cultivation practices and purchase these inputs in time with sufficient amount, sugar-mill should provide the payment in time to the farmers. Delay in payment of cane by sugar-mill has hindered in obtaining and carrying these the cultivation practices which has created the risk for shifting the sugarcane cultivation. The MPP and direct subsidy as the supporting policy was initiated to control the price fluctuation. But these factors are not found successful to stabilize the price, protect farmer and in turn promote the sugarcane cultivation. This shows that delay payment has direct effect in breaking the chain of price stability, achieve the sound environment for effective implementation of MPP and reducing the sugarcane production. Thus, only the provision of MPP and direct cash subsidy may not enhance the sugarcane production.

Problem of delay payment should be solved by strict regulation and monitoring on the private sugar-mill. Similarly, local crushers should be considered in government price policies and activities to restrict their exploitation in pricing. Furthermore, while estimation of MPP along with cost of cultivation, transportation, profit margin and cash subsidy, quality of sugarcane and recovery percentage must be incorporated that prevent the loss of sugar-mill too. Provision of direct cash subsidy should be made in line with the planting period so that farmer can use those subsidy for hiring machines, weeding, quality seeds, plant protection, irrigation and fertilization, which have a positive and significant effect in sugarcane production. Similarly, there should be the provision of procurement the surplus stock of canes by the government, which are not brought by sugar-mill.

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Amita Pandey

Ms. Amita Pandey is agriculture officer in Agriculture Science Center, a research and extension wing of research and extension wing of Directorate of Research and Extension, Agriculture and Forestry University (AFU), Rampur, Chitwan, Nepal. She completed her Master’s Degree in Agricultural economics from Institute of Agriculture and Animal Science, Tribhuwan University, Nepal. Her area of interest includes agricultural applied economics, statistics, agriculture plant science, food security and gender.

Sudip Devkota

Mr. Sudip Devkota is agriculture officer in Ministry of Agriculture and Livestock Development (MoALD), Singhadurbar, Kathmandu, Nepal. He completed his Master’s Degree in Horticulture from Institute of Agriculture and Animal Science, Tribhuwan University, Nepal. His area of interest includes agriculture plant science, agricultural extension, agricultural economics and agriculture policy.