Factor Market Imperfections and Rural Land Rental Markets in Northern Ethiopian Highlands
By
Hosa’ena Ghebru and Stein Holden
Department of Economics and Resource Management Norwegian University of Life Sciences
P.O. Box 5033, N_1432, Ås, Norway Email: [email protected]
Abstract
In response to the national land policy that bans the formal land markets (sales market) and the infrequent administrative land redistribution, the informal land rental markets in Ethiopia plays a pivotal role in smoothing the imperfections in other farm factor markets. A three round household panel data set (1998, 2001 and 2003) from the northern highlands of Ethiopia (Tigrai) has been used to empirically explore the determinants of participation and intensity of transaction in the land rental market and assess the role of the recent regional policy reform that halts further land redistribution and executes certification of rural land ownership titles. Results from the study indicate that the land rental market (which involves 53% of the sample respondents) serves as a crucial venue to correct the disproportional distribution factor endowments and the imperfections in the non-land factor markets. However, frictions in the land rental market itself cannot be denied which was found to asymmetrically (unequally) affect the demand and supply sides of the tenancy market.
Though the study does not provide evidences to support the bargaining power of farm households, the large number of constrained tenant households as compared to landlords implies that, even if tenants are with better endowments of farm asset and other durable asset endowments, the fragmented land holding may cause the supply constrained tenancy market that favours landlord households. Thus, policy measures to facilitate the transferability of land (legal enforcement of lease contracts) and functioning of other farm input markets can significantly enhance the allocative efficiency role of the rural land rental markets.
Key words: Land tenancy, market participation, transaction cost, selection bias, Ethiopia
I. INTRODUCTION
With markets being perfect, renting or buying land would be identical. Tenants would pay rent to landlords and buyers would pay equivalent amounts to bank as interest to loans. In a world, however, with asymmetric information (costly or unavailable) and market imperfections in capital and various agricultural inputs markets, there are good reasons for farm households (landlords and tenants) to prefer transferring land through land lease markets than the formal land markets (buying and selling). Here tenancy contracts are serving as way of tackling the market imperfections in the land, labour, capital and other agricultural input markets.
(Sadoulet et al: 1998).
Besides the acute market imperfections for farm factors of production and high transaction cost of non-land factor markets, the Ethiopian constitutions (1995) gives the land rental markets an exceptional importance making it the only venue of land transfer among farmers. In the current constitution (Ethiopian constitution - article 40 / 1995) the right of ownership of rural and urban land, as well as natural resources, is exclusively vested in the state and the peoples of Ethiopia. It further states that land is a common property of the nations, nationalities and peoples of Ethiopia and shall not be subject to sale or any other means of exchange.
In this context of prohibited land sales, mounting land scarcity and reduced frequency of land reallocation, land rental markets take a particular importance with possible efficiency and equity effects. Indeed, to the extent that land use rights cannot be given to all farmers, access to land for cultivation or pasture can only be achieved through short-term rental agreements between farmers with and without (enough) land. Had it not been for land rental markets, such legal ban on the land sale and purchase, and some reservations with regard to the administrative land redistribution would have put the country in a very pressing problem of high market gap concerning the demand and supply of rural arable land. Owing to this fact, the functioning of such rural land rental markets affect, in one way or another, the functioning of the overall economy and the strive towards poverty reduction.
As the constitution permits, short-term leases, such as rental and sharecropping, are practiced all over the country [Ethiopia] in response to land scarcity in all regions.
Moreover, the regional land policy reform in the study area (Tigray) that halts administrative land redistribution and certification of land ownership titles magnify the role the informal land lease market could play in providing access to land and facilitate households’ farm resource adjustment decisions.
The rural land tenancy market has received ample attention, both theoretically and empirically. Much of the attentions, however, has focussed on the efficiency aspects of alternative land tenure contracts (Otsuka, Chuma, and Hayami, 1992; Singh, 1989;
Otsuka and Hayami, 1988; Pender and Fafchamps, 2001; Stiglitz, 1974; Sadoulet et al., 1997; Gavian and Ehui, 1999 and Ahmed et al., 2002) while considerable studies have also been made on factors explaining farm households’ choice among various tenure arrangements (Chaudhuri and maitra, 1996; and Allen and Lueck, 1992).
Majority of the studies, however, fail to address the primary factors influencing the first hand decision of households’ participation in the tenancy market. Handful researches have been made with particular emphasis on the role of factor market imperfections as an important factor explaining the leasing behaviour of households (Bliss and Stern, 1982; Bell, 1977; Nabi, 1985; and Skoufias, 1995).
These empirical literatures on the leasing behaviour of households, however, are dominated by studies conducted in South and Southeast Asia leaving the Sub-Saharan Africa (SSA) case to be still under explored. With particular reference to Ethiopia, despite the highly debated issue of land tenure system in the country that lasts for several decades, few studies have been conducted that address the issue of land tenancy market (Pender and Fafchapmps, 2001; Kebede, 2003; Deininger, 2003; and Teklu, 2004). Similar study by Tikabo and Holden (2003) has also been conducted using data from highlands of Eritrea, which experience, more or less, similar farming and agro-ecological features with the study area – Tigray, Ethiopia. To the best of our knowledge, no study has been conducted to empirically explore the role of transaction cost (factor market imperfections) in dictating the land tenancy market in the country. The whole theme of this paper, thus, is to help filling this research gap in the country and the SSA at large and, thereby, evaluates the impact of the recent policy reform that started to individualize land rights and eliminate the scope for further land redistribution.
In an attempt to explore the role of factor market imperfection in dictating the leasing behaviour of households, the study focuses on the following three broad objectives: i) to investigate factors that affect farm households’ probability of participating (market entry) in the informal land rental markets, ii) to assess the role of factor market imperfections in the farm resource adjustment decisions (intensity of participation) of household, and iii) to examine the bargaining power status (market symmetry) of the trading partners - landlord and the tenant. We address these issues by analysing a household survey data from 400 sample households from 16 villages of Tigray – northern highlands of Ethiopia.1 Conceptually, we build upon the model with factor market imperfections (see Holden et al., 2001).
The overall results of the study indicate the unique structure of the tenancy market which contradicts the predominantly customary literature of rich landlord and poor tenants. Supporting our basic hypothesis, the farm asset endowment variables oxen and the tropical livestock unit other than oxen (TLUOXP) were found significantly (with OXP at 1% level) affecting farm households’ likelihood of participation indicating households with relatively poor endowment of such non/semi-tradable farm inputs tend to rent-out their land while the vice versa holds true for the tenant households. The household relative labour (male and female) endowments, however, were found to have weak effect on the likelihood of participation on both side of the tenancy market which can be asserted as a sign of relative abundance of farm labour or a relatively better functioning labour market with respect to oxen.
Like the cases of non-land factor markets, the regression results show the persistence of frictions (imperfections) in the tenancy market that cause an incomplete factor ratio adjustment process through the land lease market. The empirical evidence shows 38%
of the non-participant households are reported as constrained households who involuntarily assume the autarky position of the tenancy market while 33% of the participant (tenant and landlord) households still claim to operate less than their optimal level of land transaction.
The simultaneous test for a balanced (equal) market response of two sides of the market (the demand and supply sides) shows the hypothesis of asymmetric
1 Due to incompleteness of data and respondent dropouts, the entire analysis in this paper considers 372 sample respondents only.
(unbalanced) land lease market could not be rejected at 1% level of significance. In support of this argument, the empirical evidences show 56 % of the tenant households operate (transact) less than their desired level - they manage to obtain 64% of their desired level of transaction. On the contrary, it is only 5% of the landlord households that are identified as constrained agents though, in aggregate terms, they manage to transact 98% of their desired level of land transaction.
The rest of the thesis is organized as follows. Charter 2 presents the conceptual framework of the paper with some testable hypotheses. Chapter 3 presents the conceptual framework including the testable hypotheses. Estimation methods (econometric models) utilized to analyse the probability and intensity of land rental transactions are addressed in the fourth chapter. In addition, description of the study area, the method of data collection and statistical description of the data are discussed in this chapter. Chapter 5 is devoted for results and discussion of the empirical findings of the study. Summary and conclusions of the study with important policy implications appear in chapter 6.
II. Conceptual frame work
With well functioning markets and perfect information, no or little economic justification can possibly be given for the existence of rural land lease market. In a world of perfect information and complete markets with zero transaction costs, the ownership and distribution of land only affects households’ welfare without having any efficiency outcomes. This is so since resource adjustment for efficiency purpose can be made in any of the factor markets: Land, labour, oxen, etc. Thus, the common existence of the informal land tenancy market in many developing societies shows that the standard economic theory (with market clearing price) cannot explain such economies.
A typical feature of such agrarian economies is the tenacious persistence of imperfections in a number of factor markets. Thus, the absence of certain markets and the functioning of others is in response to the behavioural and material factors that influences household production and consumption decisions. Various literatures (Binswanger and Rosezweing, 1986; De Janvry et al., 1991) show that, in such rural
settings, factor markets, especially non-land factor markets, will either be highly imperfect or simply non-existent.
Thus, factor ratio adjustments through land rental market participation can only be justifiable by comparing the relative costs associated with transacting of such farm inputs (in this case, only when resource adjustment costs through transactions in Non- land (NL) farm input markets) out-weighs the land lease transactions. Given this situation, the development of rural land rental market plays a uniquely important role in factor ratio adjustment process. For instance, having an alternative decision either to take part in hiring-out excess NL input or renting (leasing)-in farm land, a rational cost effective farm household opts for the later only under the condition of prohibitively high imperfection (transaction costs) in the NL factor markets. Land lease markets, therefore, facilitate easy transfer of land to productive households with different initial relative endowment of farm inputs.
With considerable variations in methods and model specifications, recent empirical works, from Asia, Latin America and Africa, witnessed that the relative ease of cost of transaction in the land rental market makes it more preferable alternative venue of factor ratio adjustment.
Giving more emphasis on leasing as an adjustment of land area cultivated to farm inputs (Explicitly mentioned as labour and bullock) fixed for the farm household, Bliss and Stern (1982) developed a land leasing model using data from the Indian village of Palanpur. Describing ‘Desired Cultivated Area (DCA)’ as an area which accords with the availability of non-land farm input (labour – L and Bullock – O) supplies for the household, the model, then, considered leasing in or our as an adjustment of land owned (A) towards DCA which they call the difference as ‘Net land leased-in (NLI)’.
Showing the possible imperfections in the land lease market, the model defined DCA and NLI as:
(1) DCA = f(L,O), and (2) NLI = h(DCA - A)
Linear approximation by a first-order Taylor series expansion of equation (2) yields,
(3) NLI = K + φfLL+φfOO−φA
Where K is the constant term; ф = ∂h/∂DCA and fL and fO respectively are L
f ∂
∂ / and ∂f /∂O
Thus, the BS model was estimated using a reduced form econometric expression of equation 3 as NLI = β0 + β1L + β2O – β3 A + e, with β3 showing the imperfection in the land rental market. Accordingly, they argued that as β3 (coefficient of the owned farm size) converges to -1, it has a clear evidence of a perfectly functioning land rental market showing a complete adjustment process.
Overall, their study from India shows the imperfect functioning of the tenancy market with a coefficient of β3 = -0.78 which was found significantly different from -1.
However, the BS model may not be a plausible approach since variables common to decision of leasing-in and leasing-out may have different directions and degree of influence in the two sides (the demand and supply sides) of the land rental market.
(Tikabo and Holden: 2003)
In addressing the problem of failure to capture zero values of the dependent variable, various successive studies have utilized a censored tobit model. Studies by Pender and Fafchamps (2000); Kebede (2003) and Deininger et al. (2003) all from Ethiopia and studies from Skoufias (1995) were few among the recent studies that utilized the tobit model in analysing factors explaining the leasing behaviour of households.
Using data from four villages of Ethiopia, Pender and Fafchamps (2000) addressed the issue of leasing decisions from the demand side of the market (leasing-in decisions). Their maximum likelihood estimates support the argument that imperfection in the non-land factor markets (oxen market) to cause farm households leasing in decisions for the oxen endowment variable to have a positive significant influence. Consistent with the findings of BS, the empirical evidence from the study shows a pronounced imperfection in the land tenancy market witnessed by the significant positive correlation between the area under cultivation (operational land) and the amount of land owned. Contrary to studies by Kebede (2003) from Ethiopia which further identifies livestock holding as an important factor dictating the tenancy market participation, labour endowment of the farm household was reported to have weak effect on the leasing behaviour of households.
Using a panel data from six villages of India, Skoufias (1995) separately analyse the demand and supply side of the market for further test of symmetry between the two sides of the market. The empirical evidence shows that imperfections in non-land factor markets are the key factors explaining the arrangements of the informal tenancy market. The findings from the study described leasing decisions as ways of pooling land to non/semi-tradable factors of production like family labour and bullocks.
Furthermore, the study witnessed considerable imperfections in the land lease market with asymmetric (unbalanced) impacts on the demand and supply sides of the market.
Separately treating the two sides of the market, the tobit results of Deininger et al.
(2003) are consistent with findings of other fellow studies from Ethiopia magnifying the importance of agricultural ability (relative farm resource endowment) as key factor in dictating the leasing behaviour of households. Robust with studies from Pender and Fafchamps (2000) but contrary to findings of Kebede (2003), the family labour endowment was not found to have a significant effect on the leasing decision of households. Showing the persistence of imperfection in the oxen market, however, the livestock holding (notably oxen) of farm households significantly affects household participation decisions.
Here, it is important to note that, in all the three studies from Ethiopia, the number of bullocks owned by a farm household was found to play a leading role in the tenancy market showing the high imperfection in the sales and rental markets of such farm resource. Holden and Shiferaw (2001) confirmed this with their study from the central highlands of Ethiopia where they found liquidity constraints and moral hazard involved in the oxen rental market to cause the imperfection in both sales and rental markets.
Such studies with the censored tobit model, however, were not free from criticism since they imposes a simplifying assumption that the same set of factors to influence the decision to participate and decisions of how much to transact. Thus, the sequential nature of the leasing decisions with different sets of factors explaining the first-hand decision of participation and the extent of transaction may cause a selection bias problem with censored tobit results.
To escape the persistence of such sample selection problem where different factors influencing the participation and intensity of transaction, studies by Teklu et al.
(2004) and Tikabo and Holden (2003) adopted the two stage Heckman (1979) selection model in analysing factors explaining the leasing behaviour of households with the later study treating the two sides of the market separately.
Using data from three villages of Ethiopia, Teklu and Lemi (2004) analyse the leasing decision of households as a sequential decision between participation and intensity decision focusing on the supply side of the market (leasing-out decision). The Heckman estimation results of the study found the relative endowment of family labour and allocated farm land size significantly affect landlords leasing decision though it couldn’t reject the weak effect of household livestock holding on the participation as well as intensity of transaction.
Similarly, the study by Tikabo and Holden (2003) using data from the highlands of Eritrea found the skew ness of distribution and imperfections in the non-land farm inputs (both labour and bullocks) play an important role in influencing the leasing decision of households. Moreover, the study also revealed the non-symmetrical nature of the lease market with potential tenants facing a prohibitively high transaction cost that caused severe entry barriers. Unlike similar studies from India and Ethiopia, the results from the study witnessed a relatively well functioning tenancy market in Eritrea with complete resource adjustment process in the informal rural land lease market.
III. The Model and hypotheses
As mentioned before, the missing formal land markets (sales market) and fairly egalitarian land distribution in the country (which takes less, if not no, account of household farming ability) call for farm households to adjust farm input combinations either through participation in the non-land farm input markets or the informal land (land lease) markets.
The basic hypothesis is that, in an attempt to adjust farm input combinations, the persistence of relatively high imperfections in non-land factor markets as compared to the informal land markets determines farm households’ participation and level of transaction in the land rental market. These imperfections can be attributable to endogenous factors related to each respective household and/or other factors which are exogenous to the household.
Thus, given the rural setting in the study area (where land selling is legally banned) and review of some related literatures, a theoretical model is developed that includes imperfections in land and non-land factor markets.
The model is developed under the assumption that the non/semi-tradability of non- land farm inputs affect households’ decisions to take part in land lease markets.
Owing to the idiosyncratic production activities in the study area due to rain-fed nature of cultivation system, market friction is believed to be relatively higher in the non-land factor markets as compared to the land rental market. Accordingly, it is postulated that household specific farming ability and variation in relative endowment of land and non-land farm inputs across farm households participation in the tenancy market. The model below uses Holden et al. (2001) as a spring board.
Let the representative farm household ‘i’ be endowed with cultivable land (Ā), labour supply (
_
L), and oxen power (Ō). With simplifying assumptions of: 1) perfectly functioning farm output market, 2) complementary relationship between farm land and non-land farm inputs; and 3) prohibitively high transaction cost of exchanging oxen services, the farm household total income can be derived from:
1. Farm activity
2. Labour income (off-farm employment) 3. Land rental market participation.
1. Farming activity
Here, the representative household crop production activity follows the standard production function which is given by:
Qi = f (Ai, Lia
, Ōi)
Where: Ai is operational land (area under cultivation) Lia
is labour power devoted for agricultural activity
Ō is oxen power which is fixed2
The production function Qi satisfies the standard assumptions of production function:
fLa, fA and fo > 0 and f LaLa, fAA, and foo < 0 as well as complementarities between farm inputs.
2. Labour income (farm and off-farm employment)
A second possibility to generate income for the farm household is by devoting LH = L – Lia
(LH is positive, zero and negative for households that hires in labour, non participant and hires out labour, respectively) amount of labour in the labour market at the endogenously determined shadow wage wΨ. Similar to the oxen exchange market, with the idiosyncratic nature of crop production activity and fairly egalitarian land distribution, it is assumed that farm labour employment and income generation is limited unlike the off-farm labour employment.
3. Land rental market
As part of adjustment of farm input combination through land lease market participation, farm households can lease out part of their land endowment or lease in additional land for farm production (AR = Ā – Ai) ( AR is positive, zero and negative for households that lease in land, don’t participate and lease out land, respectively) where AR is net land rented-in and Ai is the operational land holding.
Taking all these elements together, we obtain the representative household i’s income yi as:
Yi = P f(Lia
, Ai, Ōi) + rΨ(Ā – Ai) + wΨ ( L – Lia
) Where: P is market price of farm output
rΨ is land rental value wΨ is the wage rate
Ψ Є {s, * , b} s : Leased out land / Hires out labour * : Self – sufficient in land / labour b : Leased in land / Hires in labour
Assuming the farm household maximizes utility from income , the maximization problem will be:
Max U = V [P f{(Ā + AR), ( L + LH), Ō)} + rΨ AR + wΨ LH]
2 It is our priori belief that oxen as farm input is fixed in response to the high liquidity constraint and seasonality of crop cultivation system that limits the oxen sales and rental markets, respectively, accompanied by the moral hazard involved in the later case.
AR LH
Where: AR, LH Є {s, * , b}
The utility maximization problem above satisfies the standard assumption of a utility function (twice differentiable quasi-concave utility function with positive and negative first and second derivatives, respectively) and yields the following first order conditions for the land and labour factors:
By differentiating the above utility maximizing problem with respect to AR (As, A*, and Ab), we may derive the following three FOC’s:
FOC1: s A P f
∂
∂ = rs…….. the price a household face as seller (landlord)
FOC2: A P f
∂
∂ = r* ……the shadow price of land (endogenous price)
FOC3: b A P f
∂
∂ = rb …the price a household face as buyer (tenant)
The price bands - (rs, and rb) show the persistence of transaction cost in farm input markets (the semi – tradability of the factors) with some households selling, some non – participant (difficult to say self – sufficient) and some buying households which may be a more realistic representation of factor markets in Ethiopia where a rental market exists for farm inputs. The price band reflects possible transaction costs may accrue due to search cost, moral hazard and seasonality (labour market), immobility of land and transportation cost (land markets) (Holden et. al. 2001). The size of the price band depends on the relative degree of imperfection showing rs < rb.
Generally, farm households’ participation in the land lease market and their respective position in the market (landlord or tenant households) depend on two major factors: 1) the magnitude or level of the endogenous factor price r* (shadow price of land), and 2) the size of the price band which depicts the persistence and degree of transaction cost that dictates market prices as a seller and as a buyer. This indirectly shows households’ leasing behaviour (to participate or not as well as the intensity of participation) depends, much, on the relative cost of transacting the land with respective to non-land farm inputs.
Shadow price of land (r*)
When factor markets are imperfect and prices become unobservable, the shadow price (household specific endogenous factor price) reflects the relative endowment of factors – supply versus demand (in this particular case, land to non-land). For instance, with a farm household endowed with relatively higher land to non-land farm inputs will have a relatively lower shadow price of land (r* = ∂f/∂Ā = MVPĀ) than households with lower relative endowment of land. Thus, shadow prices, here, largely dependent on household specific farm factor endowments though it is not a sufficient condition to trigger household participation in the informal land tenancy market.
In the absence of well functioning markets, farm households face different sets of prices depending on their respective positions (net seller or net buyer) they take in such imperfectly functioning markets. Such price variations for a net-buyer and a net- seller (the price band) reflect the degree of market imperfection (level of transaction cost) which could possibly be household specific (owing to various socio-economic geographical and policy/institutional factors) or common (fixed) for all participants in the market. See the figure below.
Figure 2 : Effects of transaction costs (price bands) on land transactions
Adopted from: Sadoulet et al. (1995)
price
r
1* case 3
r
bAb
r
2* case 2
As
r
sr
3* case 1
Quantity of land
Where: case 1 = Condition for leasing-out land
Case 2 = Autarky position due to high transaction cost (wide price bands)
Case 3 = Condition for leasing-in land
rs, and rb = Market price observed in the supply and demand side of the market
As and Ab = Amounts of land leased-out and leased-in , respectively r1*
, r2*
and r3*
= The shadow prices perceived by the tenant, non- participant and landlord households.
Based on these argument, a farm household may assume three alternative positions in the informal land tenancy market depending on the two influential foreces mentioned above.
Case 1: Landlords (leasing out land) when:
[ s
A P f
∂
∂ = rs] ≥ [ A P f
∂
∂ = r*]
Where: rs : Market price in the supply side of the market (Landlord price)
r*: The shadow price of land,
Note: We use the ≥ sign deliberately to include the possible cases of incomplete resource adjustments
Case 2: Non – participants households (Autarky)@
[ s
A P f
∂
∂ = rs] < [ A P f
∂
∂ = r*] < [ b A P f
∂
∂ = rb]
Where: rb : Market price in the demand side of the market (tenant price)
Case 3: Tenant (leasing in land) when,
[ b
A P f
∂
∂ = rb] ≤ [ A P f
∂
∂ = r*]
Testable hypotheses
With zero or negligible transaction cost in farm input markets, the skew ness of endowments in non-land farm inputs would rather not trigger the farm households decision to participate in the informal rural land tenancy market for they can even out this resource endowment gap by direct participation in labour or oxen markets.
However, owing to the very nature of crop cultivation which demands continuous and
dynamic adjustment decisions, hired labour is far from a perfect substitute of family labour where the later is more involved in sharing output risks. Such supervision constraints on the labour market accompanied by the liquidity constraint and moral hazard involved in the oxen sales and rental markets, respectively, magnifies the persistence of market imperfections in the non-land factor markets.
Therefore, Pooling non/semi-tradable inputs play a dominant role in rural household decisions to participate in land lease markets as well as their level of transaction.
Landlords with low endowments of semi/non – tradable inputs (such as family labour – male and female, oxen and other draft animals) relative to their land holdings will look for potential tenants with high endowments of such farm inputs. (Hypothesis 1)
The semi/non-tradability and skewed distribution of the non-land farm inputs among farm households cause farmland (physically immobile factor and fairly distributed factor) to be more mobile than non-land farm factors (contrary to its ease of physical mobility and highly skewed distribution). (Hypothesis 2)
Similar to the non-land farm factor markets, however, the persistence of production risk, missing insurance markets, high searching and supervision cost and weak property rights with lack enforcement tools, may result in imperfections in the rural land tenancy market (Sadoulet, et al., 2001; Stiglitz, 1974; Cheung, 1969). Moreover, the informal (poorly developed) nature of the tenancy market itself accompanied by the past national land policy failures that legally ban any form of land transfer threatens the functioning of the rural land tenancy market. Exposing the informal nature of the tenancy market, almost all of the sample respondents from the 2003 survey were reported to have no legal contractual agreements regarding their land lease transactions. Such imperfections directly associated with the rural land rental markets limit the extent to which farm households are able to adjust the size of their cultivated area (incomplete resource adjustment process) to even out imperfections in other resource markets. (Hypothesis 3)
Moreover, access to land through the land rental market is constrained in communities with weak property rights and poor institutional tools to enforce contractual agreements (Sadoulet, 2001). Kinship networks are thus particularly effective in
providing mutual insurance and reduce market frictions (Sadoulet, et al., 1997).
Kinship ties among farm households, therefore, trigger more participation, and hence the levels of transaction, in the informal land lease market. (Hypothesis 4)
In response to the supply constrained nature of the land lease market with a very high land scarcity and population density, the imperfections in the tenancy market causes non-symmetry and favours the landlord side of the market. (Hypothesis 5)
4. Estimation methods
In addressing the major research questions, four dependent variables have been utilized to identify the determinants of participation in the informal land rental market as well as farm households’ intensity of land transactions. Two dummy dependent variables TENT and LLORD (for decisions to participant as a tenant and landlord, respectively) and two log transformed continuous variables lnLLI and lnLLO (for decisions how much to lease-in and how much to lease-out, respectively) have been used.
Probability of participation (probit models)
As mentioned above, we model the decision to participate in the land lease market as binary decision model (with left-hand side variables: 1 if lease-in or lease-out land and 0 otherwise) treating two sides of the market separately. With major problems of non-normality of the error term and heteroscedasticity (non-constant variance of the error terms) concerning the standard OLS estimation of such models, we utilize the maximum likelihood binary response model – probit model (Woldridge, 2000;
Gujarati, 2003;Green, 2000)
In making the decision regarding participation in the informal land lease market, we assume there is unobserved factor (utility index) Ri* that explain why farm households lease in or out land. We postulate this variable Ri* (latent variable) is a function of vector of exogenous variables with the relationship specified as:
*
Ri = γ′Zi + εi (1)
Where Ri* is a latent variable (unobserved) that shows the perceived net benefits from participation in the informal land lease market; Zi is a vector of exogenous variables
(household demographic variables, asset and physical endowment variables and other village level factors such as distance to major market and population density) that influence leasing behaviour of households; γ′ is a vector of parameters; and εi is independent of Zi which represents factors unobserved by the researcher but known to the farmers (sample respondents). We further assume the random disturbance term εi is normally distributed with zero mean and variance equal to one (εi ~ N (0,1)).
Instead of observing the latent variable Ri* (perceived net-benefit of market participation), we only observe a dichotomous variable (indicator variable) Ri , which follows the sign of the latent variableRi*. When the perceived net-benefit of participation (leasing in or out of land) is positive (Ri* > 0), the farm household participates in the informal land lease market with Ri = 1.
Therefore, for farm household ‘i’, the observed binary response can be given as:
Ri = 1 if Ri* = γ′ Zi + εi > 0. ………(2) Ri = 0 if Ri* = γ′ Zi + εi ≤ 0……….…(3) Thus the distribution of Ri given Zi can be obtained as:
P (Ri = 1 Zi) = P (Ri*> 0 Zi) = P(γ′Zi + εi > 0 Zi)
= P (εi > -γ′ Zi Zi) ………(4)
Denoting θ3 as the standard normal cumulative distribution function (cdf), equation (4) yields:
P(Ri = 1 Zi) = 1 – θ(-γ′Zi)
P(Ri = 1 Zi) = θ(γ′Zi) ………(5)
Thus, the probit model takes the basic form of equation (5) with 0 ≤ Pi ≤ 1.
Intensity of participation (level of land transaction)
3 Ri = Zi =
∫
−∞'Zie−k2dk2 ) 1 ( )
( * ' γ
γ π θ
θ , where k is the standard normal variable i.e., k ~ N(0,δ2)
Having the above probit model been estimated for decisions to transact or not (probit model estimation), the test for selection bias involve two procedures: computing the selectivity bias variable (Inverse Mill’s Ration – IMR); and estimation of the intensity of leasing (the amount of land leased-in or out) using Ordinary least square (OLS) methods by incorporating this new variable (IMR) to the intensity (second stage) regression model.
To analyse the level (intensity) of transaction of farm households, let the land transaction function be given by:
i i R
i X U
A =β' + ………(6)
Where β' is a vector of parameters to be estimated, Xi is a vector of regressors (household demographic variables, asset and physical endowment variables and other village level factors such as distance to major market and population density), Ui is a normally distributed random disturbance term.
With the normality assumptions for the error terms Ui ~ N (0, σ2), εi ~ N(0,1) and corr (Ui, εi) ≠ 0, estimating equation 6 using OLS method would yield inconsistent estimates because the expected value of the error term conditional on the sample selection criterion is non-zero (Madalla, 1983). Thus, conditional upon Ri = 1 (positive values of Ri*), the second stage Heckman selection model (1979) provides consistent and asymptotically efficient estimates with the regression function given by:
i R
i X
A =β' + ηλ(γ′Zi) + Ui ………..…..(7)
Where: λi is the selectivity bias variable (Inverse Mill’s Ratio) computed as λ(γ′Zi) = φ(γ′ Zi) /Φ(γ′Zi), where φ and Φ are the density and cumulative standard normal distribution function, respectively. As shown in Equation (7), the IMR is then included as an additional regressor in the OLS lease intensity regression where the regressors (variables) in the first stage model (Zi) are allowed to differ from the regressors in the second regression equation (Xi) to meet the identification condition.
However, to avoid identification problems of picking the right variable that significantly explain the first equation (probit estimation) but not the later, we use different functional specification (double log function) in the second stage equation
while linear specification was adopted for the probit model estimation. This procedure was required since identification of the indicator variable is necessary to apply the two-stage Henchman selection model. (Tikabo and Holden: 2003)
Data and Sample Area Description
To analyse the probability and intensity of land lease transactions, a survey data consisting of 16 villages (a sample 25 farm households from each) has been collected from five administrative zones of the Tigray region of Ethiopia that covers 11
‘woredas’ or districts of the region (see figure 3 for detailed description of the study area). The sampling method was administered at two levels: stratified random sampling (taking agricultural potential, population pressure, access to irrigation, and access to market into consideration) at village level and a simple random sampling at a household level. The survey was conducted in May-July 2003 that represents the 2002/2003 crop season. Descriptive summary of the village level and household level variables are shown in table 1 and 2, respectively
5. Results And Discussions
As mentioned in the previous section, four maximum likelihood probit model specifications have been utilized to analyse the first stage estimation (the likelihood of farm household participation in the informal tenancy market). As shown in table 4, Prob(LI)-2 and Prob(LO)-2 models are the likelihood estimates of leasing-in and leasing-out decisions using various household level variables and selected village level attributes (like village access to major market, to irrigation project, etc) while the remaining two (Prob(LI)-1 and Prob(LO)-1) are village fixed effect models - probit models with the same household level variables but using 15 site dummies instead of using the village level attributes.
To assess the intensity of participation, we utilized these two model specifications Prob(LI)-2 and Prob(LO)-2 for having a relatively high predictive power over the remaining two model specifications. The results using the Heckman selection model (see table 6 and 8 for the demand and supply side of the market, respectively) show that the problem of selection bias could not be rejected at 5% level of significance in the leasing-in decision while there is no significant selection bias problem in the landlord side of the market. Accordingly, we estimated the analysis of intensity of
leasing-out using alternative models of ordinary least square (OLS) (Tikabo and Holden, 2003) and censored Tobit model (Skoufias, 1995; Pender and Fafchampe, 2001; Deininger, 2003; and Tikabo and Holden, 2003). On the other hand, two-stage Heckman selection model has been utilized in analyzing households’ intensity of leasing-in decisions since it captures and corrects the Selection bias problem (Tikabo and Holden, 2003).
Likelihood of participation
Supporting our basic hypothesis (hypothesis 1), the relative endowment of non-land farm inputs with respect to owned farm size were found to significantly influence the household decisions to participate in the land lease market. As shown in table 4, oxen per unit of owned land (Oxp) and the tropical livestock unit per unit of owned land (Tluoxp) were found highly significant (with Oxp at 1% level) affecting the leasing behaviour of households in all the models utilized.
This result supports our basic hypothesis of the non/semi-tradability of non-land farm inputs triggers farm household participation in the tenancy market. This result may indicate that there are higher transaction costs I the oxen rental market than in the tenancy market with respect to access to those markets. This finding has be supported by the fact that 43% of the sample respondents were reported to have no ox and yet only 11.5 % of them engaged in oxen rental market. The highly significant and negative coefficient of ownership of other livestock per unit of own land (tluoxp) in the supply side of the market indicates that more wealthy households were less likely to rent out their land. Households that have animals may need their land themselves to produce fodder for their animals and landlords tend to be the poorest households that lack the resources to farm their land themselves.
Consistent with our expectations, the coefficients showing household relative endowments of labour (Totmalp and Totfemp) were found to have strong effect on the leasing-out and leasing-in decisions, respectively. This finding appears to be consistent across similar studies from Ethiopai (Deininger, 2001; Teklu et al, 2004;
Pender and Fafchamps, 2001) which can be an indication of an abundance of labour or relatively better functioning labour market as compared to the oxen markets.
Though it plays a less important role in the leasing-out decidion, the gender coefficient (Hhhs) was found to be consistent and highly significant in both models utilized to assess the likelyhood of renting-in land. Accordingly, female-headed households were less likely to rent in land after controlling for other differences in endowments. This may be because landlords have less trust in female-headed households as land managers. Potential female-headed tenant households may therefore have been totally rationed out of the market even if they had the necessary oxen endowment for farming. As a proxy variable for capturing farm experience and physical ability, the age of the household head (Hhha) was found to a strong significant effect on the land renting out decision showing that the older the age of the household head, the higher the probability of renting-out land.
Previous participation in the market for tenancies had a strong positive effect on current probability of participation in both sides of the market, attesting our priori expectation that households well acquainted with the existing tenancy market (having insiders market information) are more likely to participate in the market than otherwise. This could be due to the high initial cost (fixed transaction cost) an agent may face when first attempting to enter the market. All variables that capture village level attributes appeared to play less important in relation to access to tenancy markets.
Intensity of market participation
Intensity of leasing-out
We will now look at the determinants of the intensity of participation on the landlord side of the market. As mentioned before, we found no signs of selection bias related to participation on this side of the market (see table 7). We therefore discuss the results from an ordinary least square and a truncated tobit model presented in Table 5.
We used a village level kinship variable (vilkin), which was constructed as the share of all contracts in the village that were all among kin partners.
As the result shows, ownership status of farm inputs (all labour and livestock endowment variables), though having a significant effect on the probability of participation, both the OLS and truncated Tobit regression results shows a weak effect of such factors on the amount of land rented out. The facts that 50% of the landlords
leased out all the land they owned (zero operational holding) and 83% of them with zero oxen could be a possible explanation for the absence of partial factor ratio adjustment with respect to oxen. Moreover, the fragmented land holding of farm households (an average number of plots and farm size of :::: and :::, respectively), might also explain the weak effect of these asset endowment variables on the intensity decisions.
We see that land leased out did not adjust smoothly with the farm size of landlords as the coefficient on farm size (fs) is only 0.136 and 0.151 in the OLS and truncated Tobit models. Further attempt has been made to test if this is significantly less than 1.0, which was expected with a perfect land tenancy market with zero transaction costs and constant returns to scale. The result rejects the hypotheses that fs=1 that explains imperfect resource adjustment in the landlord side of the tenancy market.
In contrast with our 4th hypothesis, kinship networks were found to have a negative impact in dictating the leasing behaviour of households. We hypothesised that trust may be higher among kin and therefore adjustment would be smoother in kin contracts. This could imply that the land rental market functions better in villages with a high share of kinship contracts. The highly significant but negative coefficient of vilkin variable, on both the OLS and Tobit regression results, however, shows the land rental market functions significantly better in villages with low share of kinship contracts. A large share of kinship contracts could be a sign of a low-trust community (Vilkin to have positive effect) or only due to a highly supply constrained (a very small land holding) tenancy market where potential tenants solely rely on kin related landlords to get any access to arable land. Thus, the counter-intuitive result could be explained if the second case dominates the first one where social capital plays less role than the miniature land holding of farm households.??? T his finding contrasts with the theoretical foundation that social capital (mutual trust and minimized moral hazard among kin tied partners) matters in wining the hearts of transacting agents - landlords (Sadoulet, 2001).
More unequal land distribution (vgini) stimulated significantly renting out of land.
This contrasts with the participation models. The probability of land being rented out was lower but those renting out land rented out more land in villages with more
skewed land distribution. This may indicate that those landlords who trusted the market were willing to rent out more land where the demand was higher due to more in egalitarian distribution.
Another interesting finding in Table5 was that households with off-farm income rent out more land. This may indicate that there were imperfections in the labour market since extra (“high-pay”) off-farm income was not used to hire (“low-pay”) labour to substitute for lost household labour in farming. There are additional transaction costs related to hiring and monitoring hired labour and such costs may even be higher for households engaged in off-farm work than for other households.
Intensity of leasing-in
We used a maximum likelihood Heckman (1979) selection model for the analysis of tentants’ degree (intensity) of participation in the land rental market, and we found significant selection bias. The results of the second stage of the model are presented in Table 6. We also run a Deaton regression model for testing the robustness of results across these two models. The results of the Deaton regression model are also presented in Table 6.
Unlike their profound effect on the likelihood of participation, both the Heckman and Deaton regression results show oxen endowment to have a weak effect in dictating the intensity of leasing-in land. This could be a strengthening force for our hypothesis for having a supply-constrained tenancy market in the study area. The fact that rental markets for such farm inputs (oxen) are highly imperfect and yet the statistical insignificance of such parameters could lead to a strong argument that exogenous factors (possibly, screening criteria of landlords) rather than the relative endowment of farm inputs explain the level of transaction (degree of access to leased land).
Livestock wealth other than oxen (lntluox), however, was found to have a significant and positive effect on the amount of land to rent in. Households with more endowment of other livestocks tend to rent in more land possibly to provide fodder for their livestock.
With both the endowments of family male and female labour having a weak effect on the likelihood of participation (first-hand decision), the endowment of adult female
labour in a family, however, significantly reduces the amount of land rented in. This result confirms the gender-specific nature of an agricultural task where the social constraint on female labour market participation is very high.
Similar to the case of the landlord side of the market, the significant but negative coefficient of vilkin variable using the Heckman model contrasts to our hypothesis that tenants with kin related landlords enjoy relative ease of barriers in the process of factor ratio adjustment through the informal lease market. This counter-intiutive result could be the outcome of a possible interaction between two contradicting factors (the share of kinship contracts in a village and the land holding status of households in a village).
Contrary to the predominantly customary explanations, we found a significant positive coefficient on the owned farm size variable. Surprisingly, the result is puzzling as households with a relatively high “allocated” farm size are expected to have less demand for rented plots and to lease-in less land. Spurious correlations between plot size, farm size and area sizes leased-in/out could possibly cause the situation. Locations with large farm sizes could typically be areas with larger sizes of land lease-in or out. In an effort to correct the possible spurious correlation, an attempt has been made to estimate the lease-in intensity regression using a relative farm sizes with in villages (individual land holding / total village farm size). The result, however, remains robust across these alternative models with the farm size variable still having a positive significant effect on the amount of land leased-in.
There are good reasons, however, to treat the result cautiously since no further effort (test) has been exerted to address the issue of scale of production (efficiency analysis) due to the drought nature of the data collection perdior.
With some degree of reservation, the unexpected positive sign could possibly imply that large farmers endowed with large farm sizes possess abundant complementary farm assets (labour, oxen and other farm implements) and yet their relative factor ratio (land to non-land) endowment remain to be low which may demand further adjustment actions by leasing-in more land. This result, thus, could justify our argument that relative rather than absolute farm resource endowment matters in dictating the leasing behaviour of households.
As indicated in table 6, tenants who reside in villages with irrigation facilities (irrg), more skewed land distribution (vgini), and less access to a major market (Mktd) were found to rent in more land than otherwise. Due to low opportunity cost of farm labour in remote areas (no or less off-farm engagements), landlords may opt for own cultivation of their plots leaving few amount of land to be tenant operated.
Tenancy market friction and resource adjustment process
Our expectation of incomplete factor ratio adjustment through the land lease market (Hypothesis 3) was not rejected for the coefficient of the allocated farm size in the two intensity models (OLS for leasing out and Heckman for leasing in decisions) were found to be significantly different from 1 in both sides of the tenancy market.
The result is more pronounced as 56% of the actual tenants were reported to be constrained tenants who all want to lease in more land (see table 9). This shows, like the imperfections in the non-land factor markets, frictions in the tenancy market cause participant households to transact less than their optimal level. Fragmented land holding and highly skewed distribution of non-land farm inputs accompanied by the supply constrained nature of tenancy market, might be possible explanations behind the observed fact in the demand side of the market.
Though it was only 5% of the landlord households that were identified as constrained landlords who want to lease out more land, the informal nature of the tenancy market4, the past policy failure which discourages leasing out practices and other cultural and traditional factors5 could explain the frictions in this supply side of the market.
Market symmetry and rationing out problem
In an attempt to test the hypothesis of asymmetric (non-symmetrical) nature of the informal land lease market, a market symmetry test6 has been made applying the censored Tobit model that analyse the determinants of net land leased-in as adopted by Skoufias (1995). Using the tobit regression output (see table 10) from both the
4 Almost all of the land lease market participants have no formal contractual agreements while transacting in the tenancy market.
5 Informal discussions with some of the elderly farmers show that farm households consider leasing out the entire land one owns as socially undesirable act.
6 Testing the equality of two sides of the market both the signs and significance level of variables.
demand and supply side of the market, the results of the various Wald tests conducted to test market symmetry (the equality of coefficients on both sides of the market) show that the hypothesis of asymmetric resource adjustment in both sides (the demand and supply sides) of the tenancy market could not be rejected.
As shown in table 7, the simultaneous test for the equality of all coefficients in the two sides of the market (market symmetry test) is rejected with Wald statistic of 132.36 at 1% level of significance. To identify the factors (variables) responsible for the asymmetric nature of the tenancy market, individual variable tests have been made comparing the two sides of the market. As the result reported in the above table shows, variables like owned farm size, kinship network, village access to market, village distribution of land and previous participation in the tenancy market have been identified as factors causing the non-symmetrical nature of the market. These results suggest that the households’ marginal responsiveness towards adjusting the desired cultivated area for these variables is not the same in each sides of the market.
Great caution, however, has to be exercised since the results (tests) are entirely based on censored tobit model that fail to capture the sample selection problem (selection bias) which was found significant in the tenant side of the market.
Despite the limitation of this econometric evidence, summary of relevant observed evidences exhibit similar result showing imperfections in the tenancy market affect the two sides of the market in an unbalanced way, mostly, favouring the landlord side of the market. The is shown as both the fixed transaction costs (due to market entry barriers) and variable transaction costs (cause incomplete resource adjustments) affected more of the leasing-in decision than leasing-out decision. The prohibitively high transaction cost that cause the non-symmetry in the market is more witnessed as almost 1/3 of the current non-participants were reported to be rationed out tenants (denied access to the tenancy market) while it is only 5% of them that would like to lease-out but fail to find any trading partner.
Even among those farm households who manage to break the entry obstacle (the current tenancy market participants), the intensity of degree of resource adjustment through the tenancy market is more limited in the tenant side of the market where 55% of them were reported to operate (lease-in) land less than their optimal level
while it is only 4% of the landlords that lies under similar category. Tenant and landlord households manage to transact 64% and 98% of their desired level of transaction. This indicates a highly significant variable cost of transaction affects the tenant households more than that of the landlord side where high population density (growth), aggravating scarcity of land and very low off-farm employment opportunities are to be mentioned as few among other causes.
6. Concluding Remarks
This paper has been motivated by the observations that the legally prohibited formal land markets (sales market) and the recent halt in administrative land reallocation by regional authority (Tigrai) make the land rental market the sole venue for land transfer among farm households. Consistent with the anticipated impact of these policy matters and the imperfections in non-land factor markets, the overall result of the study shows the important role the informal tenancy market plays in bringing land to imperfectly or non-tradable farm factors of production.
Supporting our basic hypothesis, the farm asset endowment variables oxen and the tropical livestock unit other than oxen (TLUOX) were found significantly (with OXEN at 1% level) affecting farm households’ likelihood of participation indicating households with relatively poor endowment of such non/semi-tradable farm inputs tend to rent-out their land while the vice versa holds true for the tenant households.
Contrary to our expectations, however, the household relative endowments of male and female labour were found to have weak effect on the likelihood of participation on both the demand and supply side of the tenancy market. Conditional upon participation in the land lease market, tenant households’ intensity of participation seem to be more responsive towards adjusting their relative endowment of non-land farm inputs while landlord households are more responsive towards household demographic variable (gender and age of the household head) than relative resource endowments.
Like the cases of non-land factor markets, the regression results show the persistence of frictions (imperfections) in the tenancy market that cause an incomplete factor ratio adjustment process through the land lease market . This has been witnessed by the fact that the parameters on the farm size variable were significantly lower than one
for landlords and had even a positive sign for tenants, indicating that there are economies of scale in farming and transaction costs in the rental market. Past policies in form of land redistributions, prohibition of tenancy contracts and later limiting the length of tenancy contracts to one year may explain the low allocative efficiency of the market for tenancies.
The simultaneous test for a balanced (equal) market response of two sides of the market (the demand and supply sides) shows the hypothesis of asymmetric (unbalanced) land lease market could not be rejected at 1% level of significance. This result shows the imperfections in the land lease market affect the two sides of the market (the tenant and landlord households) asymmetrically. In support of this argument, the empirical evidences show 56 % of the tenant households to operate (transact) less than their desired level - they manage to obtain 64% of their desired level of transaction. On the contrary, it is only 5% of the landlord households that are identified as constrained agents though, in aggregate terms, they manage to transact 98% of their desired level of land transaction.