Transactions Costs in Land Rental Markets and Their Impact on Youth Access to Agriculture: Evidence from Tanzania J. Ricker-Gilbert (Purdue University, USA) jrickerg@purdue.edu J. Chamberlin (CIMMYT, Addis Ababa Ethiopia) Jordan.chamberlin@gmail.com Paper prepared for presentation at the 2016 WORLD BANK CONFERENCE ON LAND AND POVERTY The World Bank - Washington DC, March 14-18, 2016 Copyright 2016 by Jacob Ricker-Gilbert, and Jordan Chamberlin. All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies.
Abstract The present study uses three waves of nationally representative panel data from Tanzania to addresses two important questions related to land access in SSA which remain largely unanswered to date. The first is to what extend do land rental markets allow households to increase or decrease their operational farm size so that it aligns with their desired land size (and, conversely, to what extent do transactions costs impede such adjustments)? Second, do land rental markets provide a pathway for youth to acquire land and thereby enter into agriculture? Our results suggest that transactions costs faced by younger farmers may be higher than those faced by older farmers. Reasons for this may include: weak credit markets (which disproportionately constrain younger farm households with fewer financial resources), and weak contract reinforcement (which may make rental arrangements contingent upon reputation, which may take many years to develop). Key Words: land rental markets, transactions costs, youth employment, Tanzania, sub-saharan Africa 2
Introduction Evidence suggests that farm land rental markets are growing within in the traditional tenure systems in many countries of sub-saharan Africa (SSA). At the same time, this growth is uneven across countries and even within the same country. The extent to which these rental markets function seems to depend on the strength of local institutions, population density, and market access among other factors (Holden et al. 2009; Chamberlin and Ricker-Gilbert 2015). Land rental markets generally have lower barriers to entry than land sales markets, and are thus more prevalent in smallholder agriculture. This gives rental markets the potential to provide more equal access to land and promote efficiency within the smallholder farming system (Holden et al. 2009). As such, the performance of land rental markets is critical for agricultural and economic development in SSA over the 21 st century. Population across the region is projected to increase to 2 billion people by 2050 from 856 million today (Bremner 2012). Furthermore, it is highly unlikely that urban areas of SSA will be able to absorb all of the growing population, leaving many people to remain in densely populated rural areas, where most of them will depend on agriculture for their livelihoods (Fine et al. 2012, Losch 2012, Jayne et al. 2014). Therefore, land rental markets can potentially play an important role in transferring land to a younger generation of farmers, and enable land and labor factor ratios to equalize. With these considerations in mind the present study addresses two important questions related to land access in SSA which remain largely unanswered to date. The first is to what extend do land rental markets allow households to increase or decrease their operational farm size so that it aligns with their desired land size (and, conversely, to what extent do transactions costs impede such adjustments)? Second, do land rental markets provide a pathway for youth to acquire land and thereby enter into agriculture? The two questions are inter-related, because in the absence of market frictions we would expect youth to be more likely to rent in land, given their higher labor endowment (relative to older farmers), and their longer time horizon. However, if transactions cost exist in the form of information 3
access and/or trustworthiness in the absence of contractual enforcement, then youth may be systematically disadvantaged. Thus, we would expect that transactions costs are, ceteris paribus, higher for young tenants who want to rent in land. While the literature on land rental market participation and farm-level impacts is growing, there is still relatively little evidence on these two salient issues surrounding rental market development. Using data from India, Skoufias (1995) builds a model operated land size is a function of observable household endowments, owned land and transactions costs. To our knowledge the only studies to empirical estimate the Skoufias model in Africa are Deininger et al. (2008), and Deininger et al. (2009) in Ethiopia, along with Yamano et al. (2009) and Jin and Jayne (2013) in Kenya. In addition, a recent article based on data in Ethiopia by Bezu and Holden (2013) is perhaps the only study to empirically investigate youth access to farm land in SSA. The present study builds upon the previous research on the topic by linking the pertinent questions of youth access to farm land and lack there-of and how that may be inhibited by transactions costs in land rental market transactions in customary tenure systems. We conduct our analysis using nationally representative panel data from Tanzania, which as a relatively active land rental markets within the traditional tenure system. There is significant variation in land scarcity, market access and population within the country, which appear likely to condition the demand for land access via rental markets. Data and Methods The analysis uses household panel survey data, and geospatial data from secondary sources, to address the research questions presented above. For Tanzania, we observe 2,860 households in each of 3 waves (2009/10, 2011/12, 2013/14), with a larger number showing up in the unbalanced panel. 4
Our empirical strategy estimates a model that builds on Skoufias (1995), where operated landholding depends on household factors, including age of household head, education level, and livestock and durable asset ownership. Hectares of land owned pre-renting is also included in the model along with proxies for transactions costs, such as distance to market, ethnicity of the household head and ethnicity of the majority of the farming population in the community, and if land is inherited through male or female children in the community. A key argument of Skoufias is that within a Tobit modeling framework, the coefficient on the pre-rental land endowment can be interpreted as a measure of transactions costs. In the absence of transactions costs, the coefficient on land for tenants (renters-in) should be -1; in the presence of transactions costs, this coefficient move away from -1 towards zero. Because we are interested in transactions costs may vary with age, we interact a youth dummy with the pre-rental land endowment in our Tobit specifications. The statistical significance of the interaction term will test whether or not youth face higher transactions costs to rent in land than do other households. We test the robustness of our estimates by adjusting the age limit for our definition of youth households from 20 to 25 to 30 years old. Results Our results indicate that smallholder participation in rural land markets is still limited, but nonetheless important. In Tanzania, the percentage of households renting in ranges from 7.5% to 9.1% over the 2009/10-2013/14 period (Table 1). Table 1: Rental market participation rates YEAR TENANT LANDLORD 2009 9.1% 1.1% 2011 6.2% 1.1% 2013 7.5% 1.5% TOTAL 7.5% 1.3% 5
We find that, on average, tenants (renters-in) are younger than non-tentants. Table 2 shows that the difference in median ages is about 8 years. This provides prima facie evidence that rental markets may be important avenues by which younger households acquire farm land. Table 2: Median ages of tenants and non-tenants NON- TENANT TENANT 2009 47 39 2011 47 39 2013 48 39 This finding is mirrored somewhat in Figure 1, which shows the percentage of households renting in, by age classes (of age of household head). In general, younger households are more likely to rent in than older households. Figure 1: Percentage of households renting in, by age of household head % renting in land, by age category 14% 12% 10% 8% 6% 4% 2% 0% <30 30-40 40-50 >50 % renting in land Table 3 shows measures of the intensity of renting in, by the same age categories. While the average amounts rented in do not differ radically across age groups, the % of total operated land area which is acquired via rental markets does show a pronounced trend across age groups: younger households rentin a larger share of their total farms than do older household heads. 6
Table 3: Intensity of renting in, by age categories (for tenants) AGE CATEGORY MEAN AMOUNT OF LAND RENTED IN (HA) % OF OPERATED LAND WHICH IS RENTED IN <30 0.68 71% 30-40 0.88 65% 40-50 0.83 64% >50 0.76 57% Tobit results are shown in Table 4, where the dependent variable is the amount of land rented in. Three specifications are shown: (1) our base specification includes the log amount of pre-rental land owned; (2) includes an interaction term which shows how the coefficient on the pre-rental land endowment changes when the household head is younger or older than 30; (3) includes a larger number of age categories as interaction terms. The basic story is the same across all specifications: younger households have coefficient estimates which are closer to zero, indicating higher transactions costs in rental markets. 7
Table 4: Determinants of amount of land rented in by tenants (Tobit estimator results) (1) (2) (3) log of pre-rental land -0.2768 (0.000)*** log of pre-rental land * [aged >= 30] -0.3690 (0.000)*** log of pre-rental land * [aged < 30] -0.0066 (0.945) log of pre-rental land * [ages: 17-30] -0.0410 (0.681) log of pre-rental land * [ages: 30-40] -0.1130 (0.193) log of pre-rental land * [ages: 40-50] -0.3893 (0.000)*** log of pre-rental land * [ages: >50] -0.4599 (0.000)*** age of head -0.0265-0.0253-0.0242 (0.000)*** (0.000)*** (0.000)*** household size 0.0199 0.0212 0.0233 (0.169) (0.146) (0.114) max. educ. attainment 0.0223 0.0219 0.0225 (0.205) (0.208) (0.194) female head = 1 0.1769 0.1547 0.1679 (0.133) (0.191) (0.152) number of plots 0.2145 0.2174 0.2215 (0.000)*** (0.000)*** (0.000)*** log value of farm assets 0.0244 0.0273 0.0234 (0.313) (0.247) (0.329) has ox plough = 1 0.5612 0.5711 0.5754 (0.000)*** (0.000)*** (0.000)*** has tractor = 1 0.1904 0.2209 0.2380 (0.346) (0.274) (0.240) log of fert. application -0.0524-0.0529-0.0520 (0.007)*** (0.006)*** (0.007)*** km to road 0.0039 0.0036 0.0037 (0.118) (0.136) (0.132) km to market -0.0027-0.0026-0.0027 (0.019)** (0.022)** (0.021)** elevation 0.0005 0.0005 0.0004 (0.000)*** (0.000)*** (0.000)*** slope -0.0708-0.0703-0.0712 (0.000)*** (0.000)*** (0.000)*** population density -0.0002-0.0002-0.0002 (0.173) (0.167) (0.145) bimodal rainfall = 1 0.1073 0.1135 0.1072 (0.452) (0.424) (0.449) 8
(1) (2) (3) mean annual rainfall -0.0006-0.0007-0.0007 (0.107) (0.096)* (0.077)* CV of annual rainfall 0.0516-0.0133-0.0652 (0.877) (0.968) (0.844) N 5780 5780 5780 * p<0.10, ** p<0.05, *** p<0.01 Conclusions Our study has provided evidence that, which rental markets are important avenues for the acquisition of farmland by young farmers, the transactions costs faced by younger farmers may be higher than those faced by older farmers. Reasons for this may include: weak credit markets (which disproportionately constrain younger farm households with fewer financial resources), and weak contract reinforcement (which may make rental arrangements contingent upon reputation, which may take many years to develop). Further study may help to clarify what these transactions costs are. Policy makers should seek to better understand and redress such transactions cost asymetries, as Tanzania like other countries in the region faces a rural demographic youth bulge which may drive labor out of rural areas in the absence of farmland access. This may be problematic if such an exodus exceeds the absorption capacity of non-agricultural sectors in urban areas. 9
References Bezu, S. and S. Holden. 2013. Land Access and Youth Livelihood Opportunities in Southern Ethiopia. MPRA Paper No. 49860. Norwegian University of Life Sciences, Norwegian University of Life Sciences, 16. September 2013. Online at http://mpra.ub.uni-muenchen.de/49860/ Bremner, J. 2013. Population and Food Security: Africa s Challenge. Population Reference Bureau Policy Brief. Population Reference Bureau, Washington DC. Deininger, K., D. A. Ali and T. Alemu. 2009. Land Rental Markets: Transactions Costs and Tenure Insecurity in Rural Ethiopia. Chapter 3 in: Holden, S. T., K. Otsuka and F. M. Place (editors). 2009. The Emergence of Land Markets in Africa: Impacts on Poverty, Equity and Efficiency (pp 57-73). Resources for the Future Press, Washington, D.C. Fine, D., van Wamelen, A., Lund, S., Cabral, A., Taoufiki, M., Dörr, N., Leke, A., Roxburgh, C., Schubert, J., Cook, P., 2012. Africa at Work: Job Creation and Inclusive Growth. McKinsey Global Institute, Boston. Hertel, T. 2011. The Global Supply and Demand for Agricultural Land in 2050: A Perfect Storm in the Making? AAEA Presidential Address. Holden, S. T., K. Otsuka and F. M. Place, eds. 2009. The Emergence of Land Markets in Africa: Impacts on Poverty, Equity and Efficiency. Resources for the Future Press, Washington, D.C. Jayne, T. S., J. Chamberlin and D. Headey. 2014. Land Pressures, the Evolution of Farming Systems, and Development Strategies in Africa: A Synthesis. Food Policy 48:1-17. Jin, S., and Jayne, T.S. 2013. Land rental Markets in Kenya: Implications for Efficiency, Equity, Household Income, and Poverty. Land Economics 89(2):246-271. Losch, B., 2012. Agriculture: The Key to the Employment Challenge, Perspective #19. CIRAD, Montpellier, France. Skoufias, E. 1995. Household Resources, Transaction Costs, and Adjustment through Land Tenancy. Land Economics 71(1):42-56. Yamano, T., F.M. Place, W. Nyangena, J. Wanjiku and K. Otsuka. 2009. Efficiency and Equity Impacts of Land Markets in Kenya. Chapter 5 in: Holden, S. T., K. Otsuka and F. M. Place (editors). 2009. The Emergence of Land Markets in Africa: Impacts on Poverty, Equity and Efficiency (pp 93-111). Resources for the Future Press, Washington, D.C. 10