SPECIAL ARTICLE
Incidence, Forms and Determinants of Tenancy in the Agrarian Set-Up of the Assam Plains Binoy Goswami, M P Bezbaruah
Based on farm-level data generated through a primary survey, this paper reviews the contemporary tenancy situation across agro-economic conditions in the plains of Assam. The incidence of tenancy there has been found to be extensive, virtually all of which is informal and concealed from the law. Concealed tenancy is an unwarranted outcome of certain restrictive provisions in the tenancy law prevailing in the state as much as the shortening of the duration of tenancy contracts. Both outcomes have adverse implications for efficient, sustainable and equitable use of agricultural land under lease. Given the fact that supply of land for lease is expected to increase in the future as suggested by the present study, reforms in the tenancy law are required in order to ensure efficient and equitable utilisation of these lands. This, in turn, will involve relaxing the restrictive provisions of the law enabling separation of the user right of land from the right of ownership.
We are grateful to the referee for comments on an earlier version of this paper. Binoy Goswami (
[email protected]) teaches Economics at Dibrugarh University and M P Bezbaruah (
[email protected]) teaches Economics at Gauhati University.
60
1 Introduction
W
hen agricultural land is unequally distributed, the land lease market can play an important role in correcting the imbalance in factor endowments across farm households. Households with an abundance of labour but insufficient land to utilise it can lease in land from those who have land in abundance but lack the necessary manpower to utilise it fully. Thus leasing arrangements emerging in the form of tenancy contracts can potentially bring about a better match between the key factors of land and labour in agriculture. Between the two broad forms of tenancy, that of fixed-rent is viewed to be more efficient than the sharecropping one in traditional economic literature.1 Since the fixed rent is in the nature of fixed cost, it does not enter the tenant farmer’s marginal calculations in the optimisation decision. In choosing his optimal quantity of effort on land he equates the marginal product of his effort to his marginal cost, and consequently the economic surplus is maximised. In contrast, the sharecropper gets to retain only half of what he produces. In equilibrium he equates half of the marginal product of his effort to his marginal cost and thus stops supplying efforts at a point when the marginal product still exceeds marginal cost. Hence the economic surplus is not maximised (Marshall 1920). Despite its apparent inefficiency, sharecropping is, however, widely prevalent in the real world, the rationale for which can be traced to uncertainty in agriculture. Fixed rent places the entire risk of crop failure on the tenant. Sharecropping on the other hand emerges as a way to share not only the output but also the risk associated with it by varying the rent payable with the size of harvest (Stiglitz 1974). Hence, a sharecropping contract is usually preferred by the poor risk-averse tenant. While the tenant may prefer sharecropping as it insures him against risk, the landlord may also find the sharecropping contract convenient under certain circumstances. It would be assumed that the landlord would prefer a wage labour contract. But the problem with the wage-labour contract is that it places the entire risk on the landlord. Another problem associated with it is that of hidden action or moral hazard arising out of information asymmetry with regard to the skill of the tenant. This can be viewed as a classic case of the principal-agent problem. The tenant may not put in the required effort if his incentives to supply effort are weaker. Hence, to ensure the required effort from the tenant, the landlord will have to monitor the supply of effort. Monitoring involves costs which can be very high when lands are scattered and if the landlord is an october 19, 2013
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absentee. In fact the landlord especially when he is an absentee may be able to monitor only the output and not the inputs supplied by the tenant (Stiglitz 2004). Another situation when sharecropping may be the landlord’s choice is when there is limited liability2 (Basu 2005). Further, sharecropping may be the choice of both the tenant and the landlord when costs of production are shared between them and hence both the parties have to supply effort3 (Ray 1998). In the light of the above theoretical literature, we attempt to understand the contemporary status of the land lease market in Assam. The following issues have been considered as the specific objectives of the paper: (i) To document different forms of tenancy prevailing in Assam and to explain the prevailing forms of tenancy contracts in terms of the grass-roots level agro-economic realities. (ii) To identify the broad socio-economic characteristics of the lessors and lessees. (iii) To identify the factors influencing the leasing decisions of the rural households. Given the role that the land lease market plays in correcting the imbalance in the endowments of land and labour, all the issues under consideration assume crucial importance in the context of a state like Assam where agriculture still constitutes a sizeable proportion (24.44% in 2009-10) of the gross state domestic product (GSDP) and more than half of the workforce is engaged in agriculture (Government of A ssam 2012). Section 2 of the paper elaborates on the materials and methods used in the study. Magnitudes and patterns of tenancy and duration of tenancy contracts as extracted from the primary survey data have been presented in Section 3. Section 4 discusses the socio-economic characteristics of the people participating in the land lease market. Section 5 discusses the factors influencing the leasing decision of the households. Section 6 besides summarising the broad findings of the paper extracts the policy implications of these findings.
To make a relatively small sample fairly representative of the geographical scope of the study, a multistage sampling design was followed. In order to represent the agro-climatic variations within the plains, four dispersed districts were selected in the first stage of the sampling. The selected districts are Dibrugarh in upper Brahmaputra valley, Morigaon in central Brahmaputra valley, Nalbari in lower Brahmaputra valley and Cachar in Barak valley. In the second stage, in consultation with the district agriculture officers of the selected districts and keeping in view the representativeness of the district in terms of cropping pattern and socio-economic background, one development block from each of the districts was selected. From each block, three villages (thus a total of 12 villages) were selected at random. Finally, from each selected village 7 to 10% of households owning and/or operating on agricultural land were selected at random. A total of 240 households thus selected formed the final sample size covered in the survey. The sampling design explained above has been summarised in Chart 1. Chart 1: Selection Process of the Sample Districts
Dibrugarh
Morigaon
Nalbari
Cachar
Blocks
Borboruah
Mayang
Chamata
Narsimpur
Villages
V1: Dighaliya V2: Zamira V3: Khamtighat
V1: Bhakat Gaon V2: 2 No Murkota V3: Senimari
V1: Sorunaddi V2: Goalpara V3: Boloa
V1: Panibhora V2: Atharotilla V3:Sonabarighat
Households
V1: 20 (8.33) V2: 20 (8.33) V3: 19 (7.92)
V1: 21 (8.75) V2: 26 (10.83) V3: 18 (7.5)
V1: 20 (8.33) V2: 20 (8.33) V3: 13 (5.42)
V1: 21 (8.75) V2: 20 (8.33) V3: 22 (9.17)
(1) V1 – Village 1, V2 – Village 2 and V3 – Village 3. (2) Figures within () represent percentages of households in the village in the sample.
2 Materials and Methods
Given the sampling design, the sample, modest in size as it is, is arguably representative of the Assam plains as a whole.
2.1 Source of Data
2.2 Methodology
This study is based on primary data collected during JanuaryApril 2011. Assam comprises the Brahmaputra valley, the Barak valley and the hill region separating the two valleys. While the Brahmaputra valley and the Barak valley comprise about 72% and 9% of the total geographical area of the state respectively, the hills constitute the remaining 19%. Both system and institution-wise agriculture in the hills stands on a different footing from that in the plains. The traditional practice of shifting cultivation is still widely prevalent in the hills. Besides, though the traditional community ownership of land has been giving way to individual ownership, in the absence of a cadastral survey, transition to individual ownership of land has remained incomplete. In contrast, the farming systems and the agrarian institutions of the two plains are fairly similar. Hence, the present study is limited to the plains which together constitute 81% of Assam.
After documenting various forms of tenancy contracts prevailing in Assam, explanation for their existence has been sought in the variations in the agro-economic background conditions such as degree of risk involved in the agricultural operation, etc. The information about the general household characteristics is sufficient to fulfil the objective of identifying the broad socio-economic characteristics of the lessors and the lessees. A Tobit regression model was developed to identify the factors influencing the leasing decision of rural households. Details of the regression model have been elaborated in Section 5 where the model has been made use of.
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3 Magnitude, Patterns and Duration of Tenancy
This section presents magnitude of tenancy, patterns and duration of tenancy contracts prevailing in Assam as extracted from the primary survey data. 61
SPECIAL ARTICLE
3.1 Magnitude of Tenancy
The magnitude of tenancy is sought to be captured in terms of the number of tenant households and areas of sample farms under lease. Table 1: Percentage Distribution of the Sample Households in Terms of Tenure Status Field Study Locations
Pure Tenant
Owner Operator Cum Tenant
Owner Operator
Owner Operator Cum Lessor
Pure Lessor
Total
Dibrugarh Morigaon Nalbari Cachar Overall
11.86 13.80 18.90 14.30 15.00
40.68 36.92 34.00 27.00 34.20
33.90 32.30 34.00 23.80 30.80
5.09 9.20 5.70 25.40 11.70
8.47 7.70 7.50 9.50 7.90
100 100 100 100 100
From Table 1, it is evident that, on the whole, the owner operator cum tenant is the largest category (34.20%) followed by owner operator (30.80%), pure tenant (15%), owner operator cum lessor (11.70%) and pure lessor (7.90%). While 19.60% (i e, 11.70% owner operator cum lessor and 7.90% pure lessor together) of households have leased out their land, 49.20% of sample households (i e, 15% only tenant and 34.20% owner operator cum tenant together) have leased in land. Thus, 49.20% of the total sample households are either fully or partially tenant households. Table 2 shows that 32.84% Table 2 : Area of the Sample Farms of the total area of sample under Lease (as a Percentage of the Operational Holding) farms is used by tenant farmField Study Leased Owned Total ers and the remaining 67.16% Locations in Area is owner operated. The area Dibrugarh 28.50 71.50 100 under lease is the highest Morigaon 31.15 68.85 100 (41.75%) in Nalbari. Thus, TaNalbari 41.75 58.25 100 bles 1 and 2 show that while Cachar 32.00 68.00 100 almost half the farmers in Overall 32.84 67.16 100 our sample are tenant farmers (fully or partially), about one-third of the total area under sample farms is under lease.4 All the tenancy contracts in our sample are informal which confirms the overwhelming predominance of concealed tenancy in the state. 3.2 Location-Wise Patterns of Tenancy Contracts
Fixed rent and sharecropping are the two major forms of tenancy contracts prevailing in the land lease market in Assam. Another form of tenancy contract, although not very significant, is mortgage5. Again within fixed rent and sharecropping, there are alternative contractual arrangements. For example, fixed rent may be either in cash or in kind. Similarly, costs of cultivation under sharecropping may not be shared in certain cases while in some others it may be a cost sharing arrangement. Under cost sharing arrangement, the landlord usually provides the seed to the tenant which he saves from his share of the last year’s harvest. In a few cases, the landlords bore the cost of fertilisers and that of tilling the land besides providing the seed. Table 3 shows that while 49.64% of the tenant farmers are sharecroppers, 38.85% tenants have leased in under fixed rent. In terms of area (Table 4), 53.07% of the leased in area is under sharecropping and 38.59% is under fixed rent. Thus sharecropping is the prominent form of tenancy contract in Assam. 62
However, the nature of the tenancy contracts across locations of field study is not uniform. While fixed rent is the predominant form of tenancy contract in Morigaon, an overwhelming number of tenant farmers in the other three locations are sharecroppers. In Morigaon, 73.17% of the tenant farmers leased in under fixed rent with 82.51% of the leased in area under this contract. In contrast, 92.60% of the tenant farmers are sharecroppers in Cachar operating on 93.60% of the leased in area. Tables 3 and 4 further reveal that within fixed rent, except in Dibrugarh, fixed rent in kind is the more preferred. On the other hand, while in Cachar, cost sharing arrangement under sharecropping is largely prevalent, costs of cultivation are not shared under majority of the sharecropping contracts in Dibrugarh and Nalbari. Table 3: Distribution of the Sample Tenant Farmers by Terms of Lease Field Study Locations
In Cash
Fixed Rent In Kind
Total
Dibrugarh Morigaon Nalbari Cachar Overall
25.00 7.32 11.43 11.51
5.56 65.85 22.86 3.70 27.34
30.56 73.17 34.29 3.70 38.85
Sharecropping With Cost Without Cost Sharing Sharing
5.56 9.76 5.71 85.18 22.30
47.21 4.88 48.57 7.42 27.34
Mortgage Total
52.77 14.64 54.28 92.60 49.64
16.67 12.19 11.43 3.70 11.51
Figures in all the columns have been expressed as a percentage of the total tenant farmers.
Table 4: Distribution of the Area Leased in by Terms of Lease Field Study Locations
In Cash
Fixed Rent In Kind
Total
Dibrugarh Morigaon Nalbari Cachar Overall
33.26 19.32 5.19 15.12
7.49 63.19 18.51 4.57 23.47
40.75 82.51 23.70 4.57 38.59
Sharecropping With Cost Without Cost Sharing Sharing
7.03 8.36 9.03 88.11 24.73
43.33 2.35 53.27 5.49 28.34
Mortgage Total
50.36 10.71 62.30 93.60 53.07
8.90 6.79 14.00 1.83 8.35
Figures in all the columns have been expressed as a percentage of the total area leased in.
What explains the location-specific variations in the existence of tenancy contracts? The answer to the above question has been sought in the cropping patterns prevailing in the field study locations. A look at the location-wise and tenure statuswise cropping patterns, as shown in Tables 5 and 6 respectively, reveals that choice of tenancy contract is influenced by the crops grown. Table 5 shows that on the whole, winter paddy is the major crop (58.18%) grown in the locations under consideration followed by summer paddy (22.09%), winter vegetable (9.37%) and rape and mustard (7.78%). Table 5: Location-Wise Cropping Pattern Field Study Locations Winter Paddy Summer Paddy Winter Vegetable Rape and Mustard Potato Jute
Dibrugarh Morigaon Nalbari Cachar Overall
74.38 18.65 78.67 75.09 58.18
53.53 11.79 18.74 22.09
24.58 5.43 4.08 2.42 9.37
0.50 23.72 2.98 7.78
2.79 1.21 3.91 3.75 1.74 0.84
Table 6: Tenure Status-Wise Cropping Pattern Tenure Status
Owner operator Sharecropping Fixed rent Overall
Winter Paddy Summer Paddy Winter Vegetable Rape and Mustard Potato Jute
58.35 88.37 22.12 58.18
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7.72 1.31 16.20 7.78
2.21 0.48 0.39 1.74
0.90 0.44 0.39 0.84
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The scrutiny of the location-specific cropping patterns reveals that while summer paddy (53.53%) along with rape and mustard (23.72%) are the principal crops grown in Morigaon, about 75% of area is under winter paddy in each of the other three locations. These three are also the locations where sharecropping largely prevails whereas fixed rent is the major form of tenancy contract in Morigaon. Thus, from the above discussion, one can infer that sharecropping is usually the preferred form of contract when the crop grown is the conventional winter paddy. Winter paddy is grown during the rainy season and harvested during winter. As a result, it is subjected to greater risk and uncertainty caused by weather conditions than crops grown in the other seasons. Since, under sharecropping, the risk associated with the crop is also shared along with the output, the tenants prefer sharecropping when they grow winter paddy. On the other hand, crops like summer paddy, rape and mustard and winter vegetables involve little weather risk and this induces the farmers to apply costly inputs like high yield variety (HYV) seeds, irrigation, chemical fertilisers and pesticides while growing these crops. These inputs increase the production and productivity and help in fetching higher returns. Thus, due to the minimum risk involved and higher returns, the tenants like to lease in land under fixed rent contract for growing these crops and retain the entire returns. This explains as to why fixed rent is the principal form of tenancy contract in Morigaon where the tenants grow mainly summer paddy, rape seed and mustard. Again, when land is leased in for growing winter vegetable, rent is paid in cash as vegetables are perishable and cannot be stored for long. This is why fixed rent in cash is predominant in Dibrugarh where winter vegetables are grown on a sizeable portion of the sample area (24.58%). Table 6 further confirms the above discussion. It shows that 88.37% of the sharecropped area is under winter paddy. In contrast, the fixed rent tenants allocate their leased in area mainly to summer paddy (39.36%) followed by winter vegetables (21.54%) and rape and mustard (16.20%). 3.3 Tenancy Contracts and Rent Structure
The arrangement of fixed rent contracts differs across locations and even within a location (Table 7). The variability is more pronounced in case of rent paid in cash. On the whole, the cash rent varies within the range of a minimum of Rs 200 and a maximum of Rs 3,000 with an average rent of Rs 1,220 per bigha (one bigha = 0.13387 hectares) of land leased in. In
case of rent in kind, while 3.19 mounds (one mound = 40 kg) of paddy per bigha of land from the harvest is paid on an average, the minimum and maximum are two mounds and five mounds respectively. The average rent, whether in cash or in kind, is higher in Morigaon than in the other locations. In order to explain the variations in rent across and within locations, a regression model (details of the regression model have been presented in Appendix A, p 68) has been developed in which per hectare rent (in thousand rupees) has been regressed on the following independent variables:6 proportion of operational holding under irrigation, proportion of operational holding under seeds, capital expenditure per hectare of operational holding, access to credit, access to non-farm employment and inequality in landholding besides two locational dummies. The results of the regression analysis show that apart from access to credit and the locational dummies, the rest of the variables7 do not significantly influence the variations in per hectare rent. Access to the credit of tenants has a positive impact on per hectare rent.8 The sign and size of the coefficients of the locational dummies imply that after controlling for other factors included in the regression model, the average rent per hectare in Nalbari exceeds that in Dibrugarh by about Rs 280 and that in Morigaon by about Rs 580. The variations in rent across the three locations have to be understood in terms of variations in residual local conditions such as population pressure on agricultural land and natural fertility of the soil. The rent may vary positively with both the factors. Taking the rural population per hectare of net sown area as a measure of population pressure on land, it transpires that the pressure is the highest in Nalbari, somewhat less in Morigaon and much lesser in Dibrugarh9. As for natural soil fertility, the available statistics indicate that it is the highest in Dibrugarh followed by Morigaon and Nalbari.10 Thus in Morigaon fertility of land is not low, although it is not as high as in Dibrugarh, and the pressure of population on land is high though not as high as in Nalbari. Hence both the factors come into play pushing the rent up in Morigaon. On the other hand, in Dibrugarh while fertility is high, the pressure on land is less. The opposite is the case in Nalbari. In other words, one factor seems to neutralise the other in these two locations which may be the reason why the average rent is almost the same in these two locations. The slightly higher rent in Nalbari than in Dibrugarh is probably due to the higher demand for lease in Nalbari (Table 2). Under sharecropping, however, the output is shared on a 50:50 ratio in all the locations irrespective of whether costs of
Table 7: Types of Tenancy Contracts with Respective Rent Structure Types of Tenancy Contracts
Fixed rent in cash (in Rs for per Bigha*)
Fixed rent in kind (in maund# of paddy for per bigha)
Sharecropping with cost sharing (share of output) Sharecropping without cost sharing (share of output) Variants of sharecropping
Average Maximum Minimum Average Maximum Minimum
Dibrugarh
Morigaon
Nalbari
811 1,000 500 3 4 2 50:50 50:50 Guchi adhi and muthi adhi
2,000 3,000 1,000 3.85 5 3 50:50 50:50 Guti adhi
850 1,500 200 2.90 3 2.50 50:50 50:50 Guti adhi
Cachar
Overall
1,220 3,000 200 3 3.19 3 5 3 2 50:50 50:50 50:50 50:50 Guti adhi Guchi, Guti and Muthi
* One bigha = 0.13387 hectares, # one maund = 40 kg. Economic & Political Weekly
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inputs are shared or not. The crop sharing arrangement does not vary probably because the crop for which land is usually leased in under sharecropping is the same, i e winter paddy. Winter paddy is grown under the same conditions across locations and hence the rent in terms of the share of output also remains the same. The share of output that the lessors receive, however, is much higher than the amount stipulated11 in the existing tenancy legislation in Assam. Although, sharing of output does not vary, there are variants of sharecropping, such as – guchi adhi, guti adhi and muthi adhi – that exist in different locations. While guchi adhi and muthi adhi are found in Dibrugarh, guti adhi prevails in the other three locations. When the crop is divided equally in the field before the harvest, i e, the lessor harvests half the field and the tenant harvests the remaining half, it is called guchi adhi. In case of muthi adhi, the tenant harvests the entire field and carries the lessor’s share to his yard and then the lessor processes his part. On the other hand, when the arrangement is guti adhi, the tenant shares the guti (i e, the seeds) with the lessor after performing all the activities. 3.4 Duration of Lease
Most of the tenancy contracts, whether fi xed rent or sharecropping, are for short duration. A total of 14.8% of the fi xed rent contracts are for one agricultural season and another 50% contracts are for one to two years (Table 8). Thus a total of 64.80% fi xed rent contracts have been agreed upon for less than three years. In case of sharecropping, 60.80% contracts are for less than three years (Table 8). The short duration of tenancy contracts may be attributed to the provision in the existing tenancy legislation in Assam that allows a tenant to become an occupancy tenant12 and subsequently the owner of the land if he cultivates the land continuously for three years. This provision has prevented the owners, in most cases, from leasing out for a long period even when the contract is informal. The short duration of the contracts has an adverse implication for the sustainable use of land. The tenants may not be interested in investing in the development of the land. Besides, they may not have any incentive to use the land sustainably. Rather they may only be interested in maximising the returns from the land during the stipulated short period by making excessive use of chemical fertilisers and such inputs without caring for the natural quality of the land. This tendency may be particularly strong among the fixed rent tenants since after paying the rent the only objective that they have is to maximise the returns from the land. 4 Socio-economic Characteristics
A majority of the lessors also own a small amount of land. As is evident from Duration Fixed Rent Sharecropping Table 10 a total of 39.60% of 1 agri season 14.80 the lessors are in the size 1-2 years 50.00 60.80 class of one to two hectares 3-6 years 24.10 29.70 of ownership holding. How7-9 years 5.60 4.10 ever, few lessors are present 10-14 years 1.90 in the subsequent higher size 15-19 years 3.70 1.40 classes, though, we have nei20-24 years 1.40 ther a tenant nor any lessor 25-30 years 2.70 in our sample operating on Total 100 100 or owning more than six hectares of land. Thus it becomes clear that those who participate in the land lease market in Assam are essentially small and marginal farmers or small and at best medium landholders. Table 8: Percentage Distribution of Tenancy Contracts under Fixed Rent and Sharecropping by Duration of Lease
4.2 Caste, Education, Primary Occupation
While the Other Backward Classes (OBC) group is the predominant one and the general group is the second largest among Table 9: Percentage Distribution of the Lessees under Different Size Classes of Operational Holding Operational Holding (in Hectare) Dibrugarh
0-1 1-2 2-3 3-4 4-5 5-6 Overall
64
43.80 34.40 12.50 9.40 100
42.90 28.60 21.40 3.60 3.60 100
Total Cachar
46.20 46.20 7.70 100
39.30 37.60 16.20 4.30 1.70 0.90 100
Table 10: Percentage Distribution of the Lessors under Different Size Classes of Ownership Holding Ownership Holding (in Hectare) Dibrugarh
0-1 1-2 2-3 3-4 4-5 5-6 Overall
37.50 37.50 25.00 100
Field Study Locations Morigaon Nalbari
18.20 18.20 36.40 18.20 9.10 100
14.30 71.40 14.30 100
Total Cachar
13.60 40.90 22.70 13.60 9.10 100
12.50 39.60 20.80 12.50 12.50 2.10 100
the lessees, the opposite is the case with the lessors. The scheduled castes (SC) and the scheduled tribes (ST) together constitute only 18.81% of the lessees. While only 6.25% of the lessors are SC, there is no ST lessor (Figure 1). Figure 1: Percentage Distribution of the Lessees and the Lessors in Terms of Caste Panel A: Lessee
Panel B: Lessor
60
60
54.17
44.44
4.1 Operational Holdings and Ownership Holdings
Most of the tenant farmers are small and marginal farmers. A total of 39.30% of the tenant farmers are in the size class of 0-1 hectare of operational holding followed by 37.60% and 16.20% in the size classes of one to two hectares and two to three hectares respectively (Table 9).
25.80 41.90 22.60 3.20 3.20 3.20 100
Field Study Locations Morigaon Nalbari
40
36.75
39.58
40
16.24
20
20 6.25
2.57 0
General
OBC
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Again, in terms of education, as shown in Figure 2, most of the lessees have a low level of education. While 27% are not literate, 14% have had below primary level education and 46% Figure 2: Percentage Distribution of the Lessees and the Lessors in Terms of Education Panel A: Lessee
Panel B: Lessor
60
60
5 Factors Influencing Leasing Decision
48
46 40
40 27
20
25
0
NL
17
20
14
9
BP
P to HS
M to UG
8
4 G and A
0
2 NL
BP
P to HS M to UG
G and A
NL - Not Literate, BP - Below Primary, P to HS - Primary to High School, M to UG - Matriculate to Undergraduate, G and A - Graduates and Above.
only primary to high school level education. There are only a few matriculates and graduates among the lessees. As opposed to the lessees, a majority of the lessors have a relatively higher level of education with 48% matriculate or above and 17% graduates including some who have studied beyond that level. While only 8% among the lessors have below primary level education, a negligible proportion of them (2%) are illiterate. Figure 3: Percentage Distribution of the Lessees and the Lessors in Terms of the Primary Occupation13 of the Family 100 88.88 Farm
80
70.83
60 Non-farm 40 29.17 20
in the non-farm sector. The 29.17% of the lessors whose primary family occupation is agriculture are mostly owner operators who own land more than they can manage with their household labour. Hence, they lease out a part of their owned cultivable land to tenant farmers.
11.12
What induces the rural households to lease in or lease out farmland? Usually, as economic theory suggests, households owning more land but less labour to operate that land lease out to households who have sufficient labour but less land. Thus, presence or absence of farm workers and inequality of landholding may influence the leasing decision of rural households. The literature also identifies education as another factor inducing households to lease out as the level of education increases (Kuri 2003). In our sample also, it was found that most of the lessors have higher level of education relative to the lessees. Another interesting finding that has come out from our sample is that the lessees are primarily engaged in agriculture whereas more than 70% of the lessors earn their livelihood mainly from the non-farm sector. Some other factors that may influence the leasing decision of the households identified from the literature are – age of the head of the household, proportion of irrigated land to total landholding, possession of bullock, possession of tilling machinery and access to credit (Laha and Kuri 2011). Incorporating the above-mentioned explanatory factors; a multiple regression model has been developed to explain leasing decision of sample households. Additionally the model includes three locational dummies in order to capture possible effects of agro-climatic variations in the four locations on the leasing decision of the sample households therein.
0 Lessee
Lessor
As Figure 3 shows those who lease in land are primarily engaged in the farm or the agriculture sector. While 88.88% of the lessees depend on farm employment for livelihood, only 11.12% of them earn their livelihood from the non-farm sector. In contrast, 70.83% of the lessors are engaged primarily in the non-farm sector and only 29.17% have farm employment as the primary source of income. The lessors who primarily earn income from non-farm sources probably lease out their land for better utilisation of labour and other household resources
5.1 Construction of the Variables
Dependent Variable: Leasing decision (Y): the extent of tenancy, i e, the absolute amount of land leased in or leased out by a household, represents the leasing decision of the household. However, the shortcoming of considering the absolute amount of land leased in/out as the extent of tenancy is that it does not correctly reflect the intensity of the tenancy a rrangement. For instance, a large landholder may lease in a small part of land compared to the land owned. This farmer
Table 11: Explanatory Variables Included in the Regression Model for Leasing Decision Explanatory Variables
Notation
Farm workers Education of the head of the household
FW EDU
Primary occupation of the family Age of the head of the household Possession of bullock Possession of tilling machinery Access to credit Proportion of landholding under irrigation Inequality in landholding Location Dummies
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Definition
Expected Sign
Number of household members engaged in agriculture + Categorical variable with – 0: illiterate, 1: below primary, 2: primary to high school, 3: matriculate and undergraduate and 4: graduates and above – FOCCUP Dummy variable, D = 1 if the household is primarily engaged in non-farm sector and 0, otherwise – AGE Age in years – PB Dummy variable, D = 1 if the household possesses bullock and 0, otherwise + PTM Dummy variable, D = 1 if the household possesses power tiller or/and tractor and 0, otherwise + ACR Dummy variable, D = 1 if the household has access to bank credit and 0, otherwise + PLHIRRI Proportion of irrigated land (in percentage) + ILH Coefficient of variation of ownership holding – L1, L2, L3 Dibrugarh has been used as the reference category; thus L1 = 1 for Morigaon, 0 otherwise; L2 = 1 for Nalbari, 0 otherwise; and L3 = 1 for Cachar, 0 otherwise. +/–
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is predominantly an owner operator, but by absolute measure, he may appear to be a major tenant. Hence, for a correct picture, it is necessary to standardise the extent of land leased in/out by relating it to the total landholding and/or the total size of the operational holding. However, we encounter another problem if we use either land owned or operational holding as the standardising factor. If we divide the absolute measure of tenancy by land owned, the value becomes infinite for pure tenants. On the other hand, if we divide the same by operational holding, the value becomes infinite for pure lessors. Hence, for the present exercise, the sum of operational holding and land owned has been taken as the standardising factor. Thus, Y = {(operational holding – land owned)/(operational holding + land owned)}. It may be noted that Y will range between -1 and 1. It will take the value -1 for pure lessors, 0 for the pure owner operators and 1 for pure tenants. Explanatory Variables: Table 11 (p 65) shows the explanatory variables included in the model along with their notations, definitions and the expected signs of the coefficients. 5.2 Functional Specification of the Model
The dependent variable being bounded between -1 and 1, a linear regression model is not suitable as the predicted value from a linear regression will not necessarily be contained within the interval of -1 and 1. Again, as per the above formulation of the dependent variable, we see clusters of observations at both the ends in which the dependent variable takes the values -1 and 1 respectively. Hence, a censored Tobit model with censoring at both ends will be appropriate in the present context. The Tobit model is formulated with the help of latent variable Yi* which may take any probable value but is not always observable. Incorporating the explanatory variables mentioned above, Yi* has been formulated as follows. Yi* = β0 + β1FWi + β2EDUi + β3FOCCUPi + β4AGEi + β5PBi + β6PTMi + β7ACR i + β8PLHIRRIi + β9ILH + λ1 L1i + λ2 L2i + λ3 L3i + Ui
...(1)
where Ui is the random disturbance term which is assumed to be normally distributed with zero mean. The observed dependent variable Yi is linked to the latent variable Yi* as per the following formulation: Yi = -1 for Yi* < -1 = Yi* for -1 Yi* 1 = 1 for Yi* > 1 Finally the maximum likelihood estimates of the parameters have been obtained using STATA 10.0. Results of the regression analysis have been summarised in Table 12. Since the data used in the present exercise come from crosssection sample, before estimating the model, the BreuschPagan test has been applied to check for the presence of heteroskedasticity in the data set. The result of the test shows that 66
the problem is present in the sample data. Consequently, the robust standard has been estimated to overcome the problem. The results of the regression analysis show that only four14 explanatory variables contribute towards explaining the variations in the leasing decision of Table 12: Results of the Censored Tobit Regression of the Leasing the farm households. Besides, Decisions of the Sample all the variables bear the exHouseholds Breusch-Pagan test for heteroskedasticity pected signs. While the coeffiChi2 [11] = 18.62* cient of the variable FW is sigProb = 0.0981 Result: presence of heteroskedasticity nificant at 5% with a positive Variables/Constant Estimates of the sign, the coefficients of the Coefficients variables EDU and FOCCUP FW 0.064** (0.029) are significant at 1% with negaEDU -0.161*** (0.035) tive signs. Thus with respect to FOCCUP -0.473*** (0.090) the variable FW, the result imAGE -0.007** (0.003) plies that the households with PB 0.168 (0.131) more labour tend to lease in PTM -0.130 (0.147) ACR 0.065 (0.101) land. On the other hand, the PLHIRRI 0.0001 (0.0008) negative and significant coeffiILH -0.0054 (0.2524) cient of the variable EDU -0.080 (0.141) L1 proves our hypothesis to be 0.114 (0.129) L2 true, i e, education creates 0.029 (0.128) L3 aversion towards agriculture Constant 0.753** (0.366) and people with higher level 0.1973 Pseudo R2 of education tend to lease F[12,228] 8.05*** out. Again, with respect to Figures within ( ) and [ ] are robust standard errors and the degrees FOCCUP, a household which is of freedom respectively. primarily engaged in non-farm ***,**,* indicate significant at 1, 5 and 10% respectively. employment chooses to lease out as that enables the better utilisation of labour and other household resources in the non-farm sector. Further, the negative and significant coefficient of AGE implies that farm households headed by older persons are less keen to lease in land. 6 Conclusions with Implications for Policy
The predominance of tenancy in Assam’s agricultural scenario is evident from the fact that while half the farmers in our sample were either fully or partially tenant farmers, about onethird of the total area under sample farms were on lease. It is also worth noting that all the lessees and lessors were small and marginal or at best medium farmers. The tenancy contracts were short-duration informal contracts reflecting the presence of concealed tenancy as well as unsustainable use of agricultural land. On the whole, sharecropping is found to be the major form of tenancy contract though there are location-specific variations. The location-specific variations in the prevalence of tenancy contracts can be explained in terms of the prevailing cropping patterns in these locations. The preference towards sharecropping, meanwhile, is observed to be a manifestation of attempts to manage risk by the farmers. Sharecropping is more prevalent in those locations where the principal crop grown is winter paddy which involves weather risk. Since sharecropping contract enables sharing of the output and the risk associated with the crop as well, tenants prefer sharecropping when they grow winter paddy. october 19, 2013
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Our study also reveals that with the increase in the literacy rate and generation of employment in the non-farm sector through appropriate implementation of rural development programmes, there is a possibility of increased supply of land in the lease market in the near future. This prediction is based on the results of our econometric analysis indicating that people with higher levels of education as well as those who are primarily engaged in non-farm employment tend to lease out land. Given the present institutional set-up and legislative measures governing tenancy relations in Assam, the expected increase in supply of land in the lease market poses a policy challenge with respect to ensuring efficient and equitable utilisation of land. The existing tenancy law was formulated against the backdrop of agrarian relations prevailing at the time of Independence and incorporated within it certain restrictive provisions to safeguard the interests of the tenants. As per the provisions of this law a tenant may become an occupancy tenant if he holds the land for three years continuously and consequently may take over possession of the land. These stringent provisions in the tenancy law have instilled a sense of fear in the lessors leading to unwarranted outcomes like concealed tenancy and shortening of the duration of tenancy contracts. While concealed tenancy has made it impossible for the tenants to take recourse to the law in case they need to safeguard their interests, the shortening of the duration of the tenancy contracts has had adverse implications on the development and sustainable use of the land. Given these unwarranted outcomes, one may question the effectiveness and the necessity of continuing with the existing law in its present form. Besides the context in which the law was formulated has undergone considerable changes. At the time when the tenancy law was originally formulated, the landlords did not have much interest in agriculture other than exploiting the tenants. Notes 1 The counter theoretical exposition to the Marshallian proposition is the “monitoring approach” pioneered by Johnson (1950). According to this approach, sharecropping can be equally efficient as fixed rent provided the landlord specifies the amount of inputs to be supplied by the tenant and then monitors to ensure the desired supply of inputs by the tenant. 2 The limited liability axiom asserts that if individual i has some financial commitment towards j but happens to be bankrupt, then j has to forgo his claim. The presence of limited liability introduces a certain tension between the two agents (Stiglitz and Weiss 1981). In the presence of limited liability, the tenant would prefer risky projects whereas the landlord would act like a risk-averse person even if he is risk-neutral. Share tenancy enables the landlord to influence the tenant’s choice behaviour vis-à-vis alternative risky projects in his desired direction. 3 If it is a fi xed-rent contract, the landlord does not have any incentive to put his effort as the tenant gets to retain the entire marginal product. Opposite is the case when the contract is a wage-labour contract. Under such circumstance, sharecropping emerges as the compromise solution. Economic & Political Weekly
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The characteristics of the lessors of the present time are, however, different from those of the landlords of that time. In the context of the present study, it has been found that like the lessees, the lessors are too small and marginal or at best marginal landholders. In our sample, there is not a single lessor who owns more than six hectares of farmland. Hence, protecting the interests of the lessors is as important as safeguarding the interests of the lessees. Taking away land from the lessors to transfer it to the lessees will merely create another class of landless people. Thus, in view of the changes which have taken place over time and the harmful effects of the existing tenancy law, reforms in the existing tenancy laws are warranted. Such reforms are required which would facilitate hassle-free leasing in and leasing out of land and call for the scrapping off of all the restrictive provisions in the existing law as mentioned above which in turn would mean distinguishing the right of use from the right of ownership. This implies that while the lessors would have the ownership right, the lessee would have the right of use, allowing the lessors to lease out without the fear of losing the ownership right for a considerably long period of time. The positive outcome of a long duration tenancy contract is that with security of tenure the lessees have the incentive to invest in the development of the land and also to use it sustainably thereby ensuring the efficient utilisation of the land under lease. Further, the objective of equitable use of land may also get accomplished as the access to the land by the tenant will improve if the lessors do not hesitate to lease out land. Besides, if the lessors do not fear losing the ownership right they may not resist the recording of the tenancy contracts. Recording of the contracts would empower the tenants by allowing them to avail the benefits of the tenancy law especially with respect to protection against whimsical eviction by the lessors and payment of higher rent.
4 These findings are contrary to what the secondary data reflects. National Sample Survey (NSS) reports and Agricultural Census and Farm Management Studies of the Ministry of Agriculture are the two main sources of secondary data on landholdings and tenancy. While agricultural census is not at all reliable insofar as tenancy is concerned, NSS underestimates the magnitudes of tenancy. In the context of Assam, while Agricultural Census, 2000-01 show that there was no incidence of tenancy, NSS estimated the area under lease as a percentage of total operated area to be only 5.3% in 2002-03 (59th round, report number 492). The fact that NSS underestimates the incidence of tenancy has already been established by many studies (Ramachandran (1980), Sharma and Dreze (1998) and Ramakumar (2000). For a detailed discussion on the limitations of secondary data on tenancy, see Sharma (1995). 5 When land is leased in under mortgage, the lessee makes a one-time cash payment to the lessor. The amount of cash payment is decided through negotiation between the lessee and the lessor. The lessee continues to operate on the land until the lessor repays the money and gets back his land. 6 Potential yield from the land is conceivably a determinant of rent. However, yield itself vol xlviiI no 42
depends partly on the features of the land, such as natural fertility and availability of irrigation, and partly on practices and inputs applied by the farmer who takes the land on lease. The first set of factors has been accounted for by other independent variables of the model. But the latter group of factors is the results of post lease-contract activities of the farmer and hence should not have a bearing on the rent agreed upon. Hence the need to include yield as a separate independent variable was not felt necessary. 7 In the present context technology is unlikely to have significant impact on the rent as it is chosen by the lessee farmer and not dictated by the lessors beforehand. Hence technology should not enter into the bargaining of rent. As has been explained in Section 3.2, the fixed rent tenants grow summer paddy and winter vegetables which involve little weather risk. Lesser risk induces the tenants to use inputs like HYVs, fertilisers and irrigation. But these inputs are purchased by the tenants and not provided by the lessors. Even for irrigation, the source of irrigation being shallow tube wells, at least in the context of our sample, it is more a matter of choice of the tenants than of availability. 8 The probable explanation for access to credit having positive impact on per hectare rent may
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10
11
12
be the fact that access to credit enable the tenants to use higher doses of purchased inputs like chemical fertilisers, etc, and they may be able to pay higher rents from the ensuing higher returns. Rural populations per hectare of net sown area in Nalbari, Morigaon and Dibrugarh are 10.15, 9.61 and 7.77 respectively. These figures have been computed from the data sourced from Hand Book of Statistics, 2010 and Economic Survey of Assam, 2011-12 published by the Directorate of Economics and Statistics, Government of Assam. Data on yield of crops in districts of Assam going back to years even before the advent of the green revolution (when technology did not have a role to play and yield was a function of natural soil fertility only) show that the yield of rice, especially winter rice which in those years constituted 80%-90% of gross cropped area, tended to be lower as one goes south-west ward from districts in the north-eastern edge of the Brahmaputra valley (Phookan et al 1980). Data for recent years presented in Figure A1 in Appendix A confirm persistence of this pattern. This evidence is indicative of the fact that the natural soil fertility tends to decline continuously as one goes from upper Brahmaputra valley to the central and lower Brahmaputra valley in Assam, i e, from Dibrugarh to Morigaon and then to Nalbari. In case of crop rent, the rent as fixed in the existing tenancy legislation is one-fifth of the produce of the principal crop. In practice, however, the landlords receive half of the produce. However, when the costs of cultivation are shared, the landlord’s share may not be excessive. An occupancy tenant is one who holds land continuously for three years and has a
permanent heritable and transferable right of use and occupancy in the land. 13 If majority of the household members are mainly engaged in non-farm (farm) employment, then that household’s primary occupation is non-farm (farm). 14 In the context of Assam, it is not surprising that the inequality in landholding does not have significant influence on leasing decision (and on variations in rent too) as almost all the ownership holdings in Assam are small and marginal. The following statistics should make the point clear. According to the NSS reports 491 and 492 (59th round, 2002-03), 96% ownership holdings in Assam were marginal and small holdings and there was no large holding. In terms of area, marginal and small holding constituted 80% of the total area owned. The remaining 20% area was under semi-medium and medium holding. In the context of our sample also, we have found that lessors are essentially small or at best medium landholders.
References Basu, K (2005): “Limited Liability and the Existence of Share Tenancy” in Collected Papers in Theoretical Economics, Vol1: Development, Markets and Institutions, Oxford University Press, pp 192-207. Government of Assam (2010): Hand Book of Statistics, Directorate of Economics and Statistics. – (2011-12): Economic Survey of Assam, Directorate of Economics and Statistics. Johnson, D G (1950): “Resource Allocation under Share Contracts”, Journal of Political Economy, Vol 58, No 2, pp 111-23. Kuri, P K (2003): “Factor Market Imperfections and Explanation of Tenancy: Testing an Econometric Model Using Evidence from Assam of North
Appendix A In order to explain variations in rent paid under fixed rent contract across and within locations, a regression model has been developed in which rent per hectare (in thousand rupees) of operational holding has been modelled as a function of certain explanatory variables. Since the dependent variable, i e, rent per hectare, can take only positive value, the following exponential specification Table A1: Results of the Regression will be more suitable than the simAnalysis for Explaining variations ple linear formulation. in Rent Across and Within Locations Yi = exp (β0 + β1 POHIRRIi Breusch-Pagan test for heteroskedasticity + β2 POHHYVi + β3 CEi + β4 CR 2
Chi [7] = 9.57 Prob = 0.2963 Result: No heteroskedasticity Variables/Constant Estimates of the Coefficients
POHIRRI POHHYV CE CR ANFE ILH L1 L2 Constant R2 F[8, 40]
-0.0005 (0.0013) -0.0005 (0.0012) -0.00001 (0.000016) 1.88* (1.14) 0.0030 (0.0025) -0.025 ( 0.243) 0.58*** (0.13) 0.28** (0.12) 4.66*** (0.256) 0.6304 8.53***
Figures within ( ) and [ ] are standard errors and the degrees of freedom respectively. ***,**, * indicate significant at 1, 5 and 10% respectively.
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+ β5 ANFE + β6 ILH + β7 L1i + β8 L2i + Ui)
East India”, Indian Journal of Agricultural Economics, Vol 58, No 2, pp 234-45. Laha, A and P K Kuri (2011): “Rural Credit Market and the Extent of Tenancy: Micro Evidence from Rural West Bengal”, Indian Journal of Agricultural Economics, Vol 66, No 1, pp 76-87. Marshall, A (1920): Principles of Economics (London, UK: Macmillan). Phookan, U, K Gogoi and P C Neog (1980): “Agricultural Development in Assam: District Wise Study, 1950-51 to 1975-76”, Adhoc Study No 45, Agro-Economic Research Centre for Northeast Region, Assam Agriculture University, Jorhat. Ramachandran, V K (1980): “A Note on the Sources of Official Data on Landholdings in Tamil Nadu”, Data Series No 1, Madras Institute of Development Studies, Madras. Ramakumar, R (2000): “Magnitude and Terms of Agricultural Tenancy in India: A State wise Analysis of Changes in 1980s”, Indian Journal of Agricultural Economics, Vol 55, No 3, p 337. Ray, D (1998): Development Economics (New Delhi: Oxford University Press). Sharma, H R (1995): Agrarian Relations in India: Patterns and Implications (New Delhi: HarAnand Publications), pp 1-79. Sharma, N and J Dreze (1998): “Tenancy” in Peter Lanjouw and Nicholas Stern (ed.), Economic Development in Palanpur over Five Decades, Oxford University Press. Stiglitz, J E and A Weiss (1981): “Credit Rationing with Imperfect Information”, American Economic Review, Vol 71, No 3, pp 393-410. Stiglitz, J E (1974): “Incentives and Risk Sharing in Sharecropping”, Review of Economic Studies, Vol 41, No 2, pp 219-25. – (2004): “Information and the Change in the Paradigm in Economics” in M Szenberg and R Lall (ed.), New Frontiers in Economics, Cambridge University Press, p 34.
dummies where L1 = 1 for Morigaon, 0 otherwise; L2 = 1 for Nalbari, 0 otherwise. Dibrugarh has been used as the reference category.
Figure A1: Comparative Trends in the Yield Rate of Rice in Nalbari, Morigaon and Dibrugarh 8,000 Dibrugarh 6,000 4,000 Morigaon
2,000
Nalbari
0 2004-05
...(i)
where Yi = rent per hectare of operational holding POHIRRI = proportion of operational holding under irrigation POHHYV = proportion of operational holding under HYV seeds CE = capital expenditure per hectare of operational holding CR = credit ANFE = access to non-farm employment measured in terms of percentage of family members engaged in non-farm employment ILH = Inequality of landholding captured in terms of coefficient of variation of ownership holding L1 and L2 are two locational
2006-07
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The above formulation of the regression model is non-linear in nature. However, by taking logarithm in both the sides, it can be made linear and estimated easily. Thus the final form of the model to be estimated is: Ln Yi = β0 + β1 POHIRRIi + β2 POHHYVi + β3 CEi + β4 CR + β5 ANFE + β6 ILH + β7 L1i + β8 L2i + Ui
...(ii)
Results of the regression analysis have been summarised in Table A1. Since the data used in the present exercise come from cross-section sample, before estimating the model, the Breusch-Pagan test has been applied to check for the presence of heteroskedasticity. The result of the test shows that the problem is absent in the sample data.
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