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    This study investigates the role of the land rental market in rural economic development with the province Chongqing, China, as case study region. The study focuses on the question participation in the land rental market can improve agricultural production efficiency and alleviate income inequality in rural areas. Finally, the factors that affect rental market participation of farm households are examined. A stochastic frontier approach was employed to measure effect of the land rental market participation on agricultural productivity. Two competing hypotheses are tested: 1) Less efficient farm households rent out land to more efficient farm households and agricultural productivity is improved; 2) More efficient farm households rent out land and work off of farm, which results in lower agricultural productivity. The results showed that both of these hypotheses are possibly true, but more efficient farm households are more likely to rent land rather than rent it out, which implies the productivity enhancive effect of land rental market. To investigate the impact of land rental market development on rural income distribution, firstly the income inequality was decomposed to measure the contribution of land rental income to total income inequality and the interactions between land rental income and other income sources. Then, relying on the inequality index calculated, a fixed effect model was used to investigate the impact of participation in the land rental market and land rental market imperfection on income inequality index. The results showed that contribution of land rental income to total income inequality is increasing over the observation period. And participation in land rental market may reduce income inequality, given an imperfect land rental market. Deriving from a farm household model, farm households’ supply and demand decisions in land rental market were explored. The multinomial Logit model is used to examine factors that influence farm household participation probability in the land rental market. Tobit models are employed to measure the impact on the quantity of renting and renting out by farm households. Results show the importance of off-farm work wage and off-farm labor market imperfection in defining the rental behavior of farm households: it prevents farm households from renting land and encourage them to rent out. Simulation results show that rising off-farm work wages and participation rate in the off-farm labor market lead to a lower equilibrium land rent in a closed economy.

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    The data included were collected from three villages of Chongqing, China in 2011. Topics related to land rental market participation were the theme of survey.

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    Data on investment licenses from Ethiopia's Licensing office in Addis Abeba (Feb 2011). For each investment, country of origin, requested land size, some information on planned production, as well as employment and capital is contained (N=2814). Data quality: This data-set was received from the Ethiopian Investment Authority during a field visit in 2011. It contains data from investors that invested in the agricultural sector and requested some land. Unfortunately the land size information was very noisy (Units not clearly specified and missing values). Some land was requested in ha, some in sq.m. Processing: The data set attached was filtered based on size-capital assumptions, leaving out those investments that are purely processing (less land intensive). A cut-off point of 100 ha was chosen and 2814 observations for the period 1992 to Dec 2010 remained. This data set was used for Baumgartner (2012) Large-scale investments in Ethiopia, in (eds.) Allan et al.: Handbook of Land and Water Grabs in Africa, Routledge; and in Baumgartner et al. (2015) Poverty impacts of Large-scale land acquisitions, WDev.

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    The Map shows the overlay of the number of land cover changes with NDVI decrease and increase between 2001 and 2011 referring to NDVI trends. Three classes among the trends are built. Besides a “tolerance class” meaning NDVI trends between -0.005 and +0.005 the dataset was classified into “decreasing” (NDVI Trend <-0.005) and “increasing” (NDVI trend >0.005) vegetation trends. The overlay highlights the southern part of Kenya, especially the counties Narok and Kajiado where a stable land cover and decreasing trends overlap. Within this overlap are also Kitui and Isiolo – both counties that were also highlighted in the OLS-regression output as underpredicting –, parts of Marsabit and some small areas along the coastline. Also again the northwestern area, mainly Turkana Region but also West Pokot and Baringo are expressing increasing trends and seem to be linked to a more stable land cover.

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    MODIS provides the Land Cover Type Product MCD12Q1 (Friedl et al., 2002) with 500m grid resolution which represents the same pixel size also used for the MODIS NDVI time-series analysis. Annually data provision and a matching pixel size with the MODIS NDVI data used earlier in this study were key elements for choosing this dataset. The Map shows the number of LULC changes as calculated based on the methods described in chapter II.3.3. Stable areas – where land cover changes are zero – can be identified in southern Kenya, Kajiado County in particular, but also in western Kenya north of Lake Victoria, around Lake Turkana, and in the northeastern part of Kenya bordering Ethiopia. Around 33.16% of the total land area experience zero changes from 2001-2011 while 16.11% changed once and 22.92% show two changes. Three (13.98%), four (9.53%) and five (3.42%) changes can still be observed in Map III.11 while areas experiencing more than five changes are occurring in less than 1% of the total land area. The different classes show the number of land cover changes within the observation period.

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    Household survey (N=121) of local communities surrounding one large-scale land acquisition. Data on household composition, land cultivation, labour market participation, source of food & income. Stratified random sampling at village level (kebele), representating about 1600 hhs and 8000 people surrounding the investement (35km radius). Data collected in Feb 2011, following survey testing and prior qualitative research. Two ethnic groups (Anyuak and Highlander settler from Derg time). Used in Baumgartner et. al. (2015) Impacts of Large-Scale Land Acquisitions in Ethiopia (WDev.). Data set was collected during villagisation programme of Ethiopian government. Only one settlement affected.