Applied Science and Innovative Research ISSN 2474-4972 (Print) ISSN 2474-4980 (Online) Vol. 3, No. 1, 2019 www.scholink.org/ojs/index.php/asir 1 Original Paper Empirical Analysis on Local Farmers Perceptions towards Overseas Farmland Investments in Ethiopia Getamesay Tefera1 & Prof. Xinhai Lu1* 1 Huazhong University of Science and Technology, Wuhan, China * Prof. Lu Xinhua, Huazhong University of Science and Technology, Wuhan, China Received: November 19, 2018 Accepted: December 9, 2018 Online Published: January 17, 2019 doi:10.22158/asir.v3n1p1 URL: http://dx.doi.org/10.22158/asir.v3n1p1 Abstract In the past few decades there has been growing interest among multinational companies towards investment in overseas farmland. The whole process and result of such investments has become a hot topic of debate among scholars, media experts, social activists, and policy practitioners. The huge wave of overseas large scale farm land investment has generated conflicting views among scholars and developmental policy practitioners regarding its significance. Ethiopia has been in the spotlight in this regard as the government was avowed to attract investment in farmland and, in return, many foreign companies flocked to acquire large tracts of farmland, often dispossessing the local community. In this study we investigate the perceptions of local framers on overseas farmland investments in Ethiopia using a cross sectional survey data. We applied descriptive and inferential statistical analysis using SPSS. The findings indicate that out of the 440 participants covered by the survey 53.6 percent of the respondents were not happy with the activity of the investors’ in their local area. The correlation results indicate that there is significant positive relationship between the age, family Size, and off farm employment of the respondents with that of their perception, whereas there is negative correlation between migration statuses, educational level and farm land size with that of their satisfaction level. Finally the logistic result indicates perception of local farmers has significant relationship with age (0.001) and of farm employment of the respondents (0.0000) with P value less than 1 percent. Besides Migration status (.036), family size (.044), educational level (.004), income level (.044) and farm land size (.046) has significant association with the perception of the participants with P value of less than 5 and 10 percent, whereas sex (.537) and marital status (.843) of the respondents have no significant relationship with their perception. Keywords FDI, Demographic and socioeconomic variables, farmers Perception and Ethiopia www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 3, No. 1, 2019 2 Published by SCHOLINK INC. 1. Introduction Following the widespread interest towards overseas farm land investment in the past few decades, there has been a growing debate among scholars, media experts, social activists and policy practitioners regarding the whole process and implementation status of such investments. Some of them considered such large scale acquisition of farmland for agricultural investment as no different from colonization and simply call it land grabbing rather than an investment. Others, like Lu (2017) and a study by World Bank (2010) have positive view of large scale overseas farmland investments as a way to, on the one hand, improve rural and agricultural development, as well as local living standards; and on the other, increase global food production, activate global food market and achieve free movement of global food if it is properly managed. As a result in the last few decades there has been a growing research interest on the contribution of overseas farmland investment for the global economy in general and the host community and the private investors in particular. Many studies have examined the overall trends in and volume of overseas farmland investment as well as its contribution and impacts in most developing countries in a wide variety of setting. In this regard a study made by GRAIN (2008), Catula et al. (2009), and IFPRI (2009) indicate that the volume of transnational large scale land deal has steadily increased in volume from year to year such that total land transacted reached more than 20 million hectares since 20005. A report by World Bank (2010) raises the figure to 45 million hectares. The catch phrase ‘global land grabbing’ has been used to explain this phenomenal explosion of cross national commercial land transactions and land transfer deals that has prevailed in recent years around the large scale production, sale, and export of biofuel (Barros & Franco, 2010). In this regard Sub -Saharan Africa is considered as the site of the most speculative major land deals. For instance Daewoo, one of the South Korean firms, had a land lease deal to cultivate corn and other crops on 1.3 million hectares of farmland in Madagascar, though finally the company failed to cultivate it. Similarly Sudan has leased more than one million hectares of land to Gulf States, Egypt and South Korea for 99 years (Cotula et al., 2009; Kugelman, 2010). Ethiopia, which is the subject of this study, is among those African countries that have hosted a large number of overseas farm land investors in the last few years. According to a report by MoFED (2010) the country has shown an interest in overseas large scale farm land investment since the country has large land resources and thus is suitable for large scale land investment. For instance according to the office of the land investment report (EIA, 2011) the country has a total of 111 million hectares of irrigable land that is suitable for agricultural investment. Of course Ethiopian economy is fundamentally rural and relies heavily on the agricultural sector which contributes nearly half of the GDP, 85 percent of the export, and 85 percent of the total employment (CSA, 2010). Though the agricultural sector contributes for the lion share of the national economy, it is dominated by small scale farmers who earn their livelihood primarily from subsistence rain-fed agriculture with only limited use of modern inputs. Particularly, in the highlands of the country, where the majority of the country’s www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 3, No. 1, 2019 3 Published by SCHOLINK INC. population live, the farm land holding size is very small and highly fragmented, rainfall patterns erratic and level of productivity is low. As a result, the country has always been suffering from persistent food shortage, particularly evident in times of famine. By capitalizing on the available huge land resource and taking into account the need to tackle the frequently food shortage that the country faces, the current government of Ethiopia has made a policy shift towards large scale overseas farmland investment (MoFED, 2005). Following this policy shift, in the past few decades, the country has seen a significant increase in the number of large scale overseas farm land investments and it has transferred more than a million hectares of land to foreign investors (EIA, 2010). A study made by Ali et al. (2017) confirms this in finding that large scale acquisition of farmland by foreign investors has shown increment both in trends and total volume, though its contribution towards employment creations and yield spillover effect to the local farmers in Africa in general and in Ethiopia in particular is limited. However, since the inception of such large scale farmland transfer program in Ethiopia, activists, media pundit and other have expressed their criticisms of the phenomena in Ethiopia by stating that the whole process of land transfer is conducted by harassing and displacing the local poor farmers and in a way that unfairly favors the investors. In this regard Desalegn (2011) stated that the investment agreements take place in a style that unfairly favors the investors by ill-treating the local rural poor. In the same study Desalegn called the whole process as the land to the investor, by deviating from the motto “land to the tiller” which the present government espoused when it came to power by overthrowing the military regime. There is, however, no quantitatively informed empirical study undertaken to understand the perception of local farmers regarding the whole exercise of the overseas farmland investment, though some studies were conducted using cases analyses method at small scale level. Therefore in this study an attempt is made to investigate the attitude and perception of local farmers regarding overseas farmland investment in Ethiopia by taking a cross sectional survey data from a sample of 440 participants from five regions of Ethiopia where large number of overseas farmland investors have acquired large tracts of land. In doing so, this study utilizes various methodological procedures and data instrument utility in order to reach sound conclusion. And then statistical analysis follow and the results of the analysis are then discussed. This study concludes by recommending expanded and further study into the subject matter. 2. Methodology In order to undertake this research, data on various socio-economic and demographic variables from household members aged eighteen years and above were collected. Thus in this study data were obtained from primary sources through field survey. The primary data were collected through household survey by mean of structured questionnaires and interviews with key informants. To conduct the survey first structured questionnaire was developed comprising different parts on the lines of demographic and socio-economic profile of the respondents and issues which relate with overseas farm www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 3, No. 1, 2019 4 Published by SCHOLINK INC. land investment. Then the questionnaire was duplicated and admistered to each of the selected households to be filled by the head of the household. The data set for this study is cross sectional data types that are obtained from all regional states of Ethiopia where overseas farm land investors operate. A total of 440 local farmers were selected as participants for the research reported in this article. Besides the survey questionnaire, three focus group discussions, each discussing with six to eight discussants, were made to triangulate the information obtained through questionnaire and key informant interview. In order to test stated study hypothesis and attain objectives of the research, selected method of data analysis was employed. Following the data collection in the field using various instruments, editing, data entry and data cleaning processes were carried out. After selecting the study regions, the multi stage sampling technique was applied at regional and village level. Systematic and simple random sampling methods were applied to select the 440 participant farmers. In the systematic random sampling methods, the (n) units are selected by taking a unit at random from the first (Kth) unit and then every Kth unit thereafter distributed evenly over the listed population. The survey of the household was conducted using a standardize questioners. The questioners was designed to capture information about demographic characteristics such as family size, age, gender, marital status and socioeconomic issues such as income level, educational status, employment nature and others. Logistic Regression The logistic regression model is one of the most common approaches used to study the discussion between two alternatives (Field, 2005). This model predicts the probability that an individual with certain socioeconomic and demographic determinants chooses one of the alternatives (Gujarati, 2003; Field, 2005). Thus in this analyses the logistic model can be used to estimate the satisfaction maximization where the farmer is assumed to have preference of benefit from activates of the overseas farmland investment that make them satisfied. Therefore, in this research the perception of the local farmers from the benefit they incur out of the overseas farmland investments is predicted. In other words farmer’s perception on the benefit in terms of employment opportunity, salary, technology transfer they have got from the overseas investment is identified. Following Gujarati (2003) the logistic regression model form for binary choice problem could be introduced as it showed in the equation (1): 0 1 ln 1 k i i ij ji P X p        (1) Where; Pi = Probability of the event occurring β0 = constant term, βi = coefficient, X = Independent Variables. The coefficient demonstrates the effects of each explanatory variables on log of odds as www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 3, No. 1, 2019 5 Published by SCHOLINK INC. follows en Equation (2) ln 1 i i P p   Log odds ratio (2) The logistic model applies the maximum likelihood estimation after transforming the dependent in to a logit variable. The empirical mathematical model for the estimation is formulated as follows   0 1 1 0 1 1 0 1 1 ( ..... ) ( ..... ) ( ..... ) 1 1 1 1 i k ki i k ki i k ki x x i i x x x x e P prob y e e                       (3) Finally based on the empirical model presented in equation (3) the effect of explanatory variable on farmers perception by the farmland investment could be expressed through the following linear relationship 0 1 2 3 4 5 6 7 8 9 ....Age sex Mari Migra Famsize Educ Incom FARMSIZ offEmployFs                      (4) Where; Fs = Farmers Perception, Mari = Marital status, Migra = migration status, Famsize = Family Size, Educ = Educational Status, FARSIZ = Farmland size, Off Employ = Off-frame employment 3. Result For this article a sample of 440 respondents were taken as participants by means of structured questionnaire. Data was collected from December 21/2017 to March 31/2018. The target of the research were those farmers households who have at least their own plot of land for farming activity in five regional states of Ethiopia wherein overseas investors have acquired large plot of farmland for commercial agricultural investment. The results for descriptive and inferential statistics are displayed here under in the form of percentile, frequency, correlations, and regression analysis. Table 1. Distribution of Sample Respondents’ Demographic and Socioeconomic Characteristics Category Farmers perception Total Good Bad Age 18-30 68 (15.5%) 53 (12%) 121 (27.5%) 31-50 94 (21.4%) 95 (21.6%) 189 (43%) >50 42 (9.5%) 88 (20%) 130 (29.5%) Total 204 (46.4%) 236 (53.6%) 440 (100%) Sex Males 165 (37.5%) 205 (46.6%) 370 (84.1%) Females 39 (8.9%) 31 (7%) 70 (15.9%) Total 204 (46.4%) 236 (53.6%) 440 (100%) www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 3, No. 1, 2019 6 Published by SCHOLINK INC. Marital Status Married 132 (30%) 183 (41.6%) 315 (71.6%) Single 60 (13.7%) 27 (6.1%) 87 (19.8%) Divorced/window 12 (2.7%) 26 (5.9%) 38 (8.6%) Total 204 (46.4%) 236 (53.6%) 440 (100%) Migration Status Non-Migrant 120 (27.3%) 172 (39.1%) 292 (66.4%) Migrant 84 (19.1%) 64 (14.5%) 148 (33.6%) Total 204 (46.4%) 236 (53.6%) 440 (100%) Family Size 1-3 94 (21.4%) 84 (19.1%) 158 (35.9%) 4-7 70 (15.9%) 89 (20.2%) 159 (36.1%) >7 40 (9.1%) 63 (14.3%) 103 (23%) Total 204 (46.4%) 236 (53.6%) 440 (100%) Educational Status Illiterate 135 (30.7%) 178 (40.5%) 313 (71.2%) Non Formal Education 30 (6.8%) 37 (8.4%) 67 (15.2%) Grade 1_12 39 (8.9%) 21 (4.7%) 60 (13.6%) Total 204 (46.4%) 236 (53.6%) 440 (100%) Income Level <100 Dollar per annum 74 (16.8%) 108 (24.6%) 182 (41.4%) 100-500 Dollar per annum 12 (2.7%) 6 (1.4%) 18 (4.1%) 501-1000Dollar per annum 80 (18.2%) 74 (16.8%) 154 (35%) >1000Dollar per annum 38 (8.7%) 48 (10.8%) 86 (19.5%) Total 204 (46.4%) 236 (53.6%) 440 (100%) Farm land Size < 1 hector 80 (18.2%) 121 (27.5%) 201 (45.7%) 1-5 hectors 85 (19.3%) 74 (16.8%) 159 (36.1%) 5-10 hectors 39 (8.9%) 41 (9.3%) 80 (18.2%) Total 204 (46.4%) 236 (53.6%) 440 (100%) Off Farm Employment Have 146 (33.2%) 96 (21.8%) 242 (55%) Haven’t 58 (13.2%) 140 (31.8%) 198 (45%) Total 204 (46.4%) 236 (53.6%) 440 (100%) As it is shown in the descriptive table above out of the 440 participants covered by the survey 53.6 percent had bad perception with the activity of the foreign investors in their local area, whereas 46.4 percent of the respondents had good perception with the investment of the overseas investors. The www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 3, No. 1, 2019 7 Published by SCHOLINK INC. perception of the local farmers was checked across their demographic and socio economic characteristics. Accordingly, the result for the perception of the respondents based on their age group indicates that for the age group 18-30, 15.5 percent had good perception while 12 percent of them had bad perception. Among the adult age group of the study participants 21.6 percent had bad perception, which is a bit higher than with the proportion of those who had good perception (21.4 percent). In the old age group the result shows that most of the respondents had bad perception (20 percent) as compared to the 9.5 percent who had good perception. From this we can generalize that the satisfaction of the participants decreases as their age increase. The perception of the target group’s sample population analyzed in light of their marital and migration status indicates that the migrants had better perception (39.1 percent) than the non migrants (14.5 percent) while those participants who are married were more unsatisfied (41.6 percent) than those who are single (6.1 percent). The study participants who are educated had better good perception than the illiterate one (8.9 percent who had good perception in the first group as compared to the 4.7 percent had good perception in the latter). Further, those who have small family size had better perception (21.4 percent) than those having large family size (9.1 percent). Finally, the descriptive result for the perception of the respondents based on off farm employment opportunity and the farm land size they have for their endeavor indicate that those farmers that have less than one hectare of land were more had bad perception (27.5 percent) as compared with those who have large-sized farmland (With 19.3 and 8.9 percent good perception for those who have 1-5 and 5-10 hectares of land, respectively). Regarding perception of those who are off farm employed, the result show that those employed by the overseas investors had better perception (32.2 percent) than those who are not employed in the foreign investors’ farms. Table 2. Correlation Result among Demographic & Socioeconomic Variables and Perception of Local Farmers Age Sex Marital Status Migration status Family Size Educatio nal Level Income level Farm land size Off Farm Employment Percep tion Age 1 Sex -.006 1 Marital Status -.066** .610 1 Migration Status -.023 .539** .279** 1 Family Size -.011 -.128** -.018 -.114* 1 Educational Level -.090 .138** .130** .046 .002 1 Income Level -.082 -.024 -.026 .024 -.021 -.058 1 Farm Land Size -.107* .048 .000 .035 -.050 -.018 .680** 1 Off farm Activity .013 -.074 -.066 -.064 .003 -.021 .402** .331** 1 Perception .187** -.088 -.067 -..141** .107* -.138** -.058 -.094* .306** 1 www.scholink.org/ojs/index.php/asir Applied Science and Innovative Research Vol. 3, No. 1, 2019 8 Published by SCHOLINK INC. *Correlation is significant at the 0.05 level (2-tailed). **Correlation is significant at the 0.01 level (2-tailed). Note. Internal consistency reliabilities appear in parentheses along the diagonal. Age (1=18-30, 2=31-50, 3=>50); Sex (1=Males, 2=Females); Marital Status (1=Married, 2=Single, 3=Divorced/widowed); Migration Status (1=Non Migrant, 2=Migrant); Family Size (1=1-3, 2=4-7, 3=>7); Educational Level (1=Illiterate, 2=Non formal education, 3=Grade 1-12); Income level (1=<100 dollar, 2=100-500 dollar, 3 501-1000 dollar, 4=>1000 dollar); Farm land size (1=