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Succession decisions in Indonesia family dairy farm business

A Firman, M Paturochman, S L Budimulyati, M H Hadiana, D Tasripin, Opan S Suwartapradja1 and M Munandar

Faculty of Animal Husbandry, Universitas Padjadjaran, Indonesia
1 Department of Anthrophology, Faculty of Social Science and Politcs, Universitas Padjadjaran, Indonesia


Key factor for the sustainability of dairy farm business in Indonesia is young generation. Economic development and changes in social structure have a large impact on the interest of young people to work in prestigious jobs, such as industry. Working on a dairy farms for some young people in the agricultural area has become the last choice. This study aims to determine the potential successor’s views to work in dairy farms business, young farmers future goals, and factors that influence successor’s decisions to continue family dairy farming. The location of the study was conducted in Pangalengan district, West Java Province, Indonesia because it was the first place for introduce of dairy cows by the Netherlands in the 1880s. The number of farmers and their children was selected by multistage random sampling for each of 123 farmers and 123 children (in total 246 respondents). Research was held from March to April 2018. This study used an econometric model (logistic regression model) to find successor’s decision. The results of the study show that the majority of young farmers argue that working on dairy farms need time and effort; complicated, dirty, and not attractive wage; and not potential jobs in the future. More than 50% of potential successors have a dream to work out of dairy cow business. There are 16 explanatory variables involve in the model. The model has been tested and has responsible predictive power. There are only 2 (two) variables have a very significant effect on successor’s decision to continue family dairy farming, such as the number of family members (X11) and the time participation of successor on family dairy farming (X15). Therefore, social factors tend to influence successor’s decision to sustain family dairy farming.

Keywords: econometric, young farmer, small farms, sustainability


The Indonesian dairy industry has been dominated by small producers. The characteristics of small farmers have one to five cows, limited land, semi-permanent cages, traditional management, family based labor, poor and food insecure, having multiple economic activities, insufficient money and assets to maintain dairy cows (Daud et al 2015; Asmara et al 2017; Firman et al 2018; Rapsomanikis 2015). In contrast, it can be noted that dairy farmers in Australia, Europe (Germany and Austria) or the US differ in terms of production, assets, capital, and financial structure. However, smallholder dairy farmers are the most important players in the dairy industry to produce fresh milk because the small scale producer is the most dominant.

Pangalengan sub-district is one of the dairy farming centers in Indonesia. This location is the first area to introduce dairy cow by the Dutch government because the climate is suitable for dairy cow. Nowadays, rasing dairy cows has become a livelihood for most farmers in Pangalengan sub-district since 74 years ago. Eventhough raising dairy cows has not provided an adequate standard of living for families yet, livestock assets are higly liquid because farmers can sell some cows, such as bulls or calves or non-productive cows to meet family needs or cash that is urgent or motivating business (Nuhung 2015). In addition, smallholder producers can work from other sources to increase family income, such as agriculture or contruction labour, or depend on their skills. Unlike most farmers in the US, the farm is a physical asset that is a highly illiquid physical asset, cannot be divided in large part, and also as family wealth (Mishra et al 2010).

One important issue for the sustainability of dairy farmers in Indonesia is the young generation. The problem is not only for an Indonesia countries but also global problems. Since industrial expansion and economic structure changes, young people have been more interested in working in the industry because they offer competitive wage and more securely than dairy farms (Bohac and borec 2009; Hennessy 2002; Lobley et al 2010). Recently, the number of dairy farmers has declined. Based on data from Dairy Farmer Cooperative of South Bandung (KPBS) Pangalengan reported that the number of cooperative members decreased from 6,984 members in 2010 to 4,586 members in 2018 or decreased 2,498 members during eight years. The cooperative also reported that the decline of cooperative members has become a major problem in Pangalengan. One reason is the farm succession.

The farm succession is a key factor for the sustainability of dairy farm, especially in location study. Entering agriculture sector by the young people holds a very important place in determining the structure of agriculture and total number of farmers and farm families (Gale 1994 cited by Mishra et al 2010). According to the results of the study, it can be proven that most farmers who operate agricultural business are dominated by farmers over the aged of 40 (Asih 2009; Anindyasari et al 2015; Wiyono et al 2015). Meanwhile, it can be no doubt that majority of young farmers are more interested in migrating from village to city in search of attractive work (Firman 2010; Lucas 2004; Lobley et al 2010). The trend toward fewer entrants in agriculture is influenced by income prospects in farming relative to other sectors (Gale, 1993), while Hennessey (2002) says that neo-classical economic theory explains that individuals seek maximum profits and will always strive to look for profitable economic activities. There are many factors that will affect young people not to enter the farm such as poor, low income, and not prestigious job on agriculture or livestock (Wiyono et al 2015). Even though the younger generation decided to work in the farm for the future, the decision is still uncertain after young generation finished school.

The participation of young farmer plays an important role in small-scale dairy farm because the use of family labor is intended to reduce production costs. In general, the participation of young farmer is focused on cleaning stalls and dirt or milking cows or delivering milk to milk collecting point or feeding or looking for grass. The interaction between young farmer and parents about agriculture is part of socialization process. The process itself may take a long time, but interactions can transfer habits or culture, values, rules, knowledge, and beliefs of parents to children in the context of dairy farming (Garcia et al 2002 cited by Posso and Urbano 2017; Crisogen 2015). On the other hand, the young generation has activities outside the family, such as at school, the neighbourhood, associating with the community, spend time watching television or surving in the internet. This may have a direct or indirect impact on the successor’s decision to continue or not continue the family dairy farm business.

The phenomenon on the above is an intereting study because studies releated with farm succession on family dairy farming are very limited in Indonesia. The lack of research on this field is a starting point for exploring the successor’s view and decision on dairy farm. The sustainability of the family dairy farm business in the context of small scale dairy farms is strongly supported by the successor. Therefore, this study aims to determine the potential successor’s views to work in dairy farms business, young farmers future goals, and factors that influence successor’s decisions to continue family dairy farming. The study uses econometric model to analyze the succession decision.

Theoritical framework

The farm family is agriculture that are management, control, and ownership in the hands of the farmer family and handed down within in the family (Gasson and Errington 1993 cited by Lobley 2010). The typical of family farming in the world is different, especially in the ownership of assets. The majority of family farms in developing countries are dominated by smallholder farmers (Rapsomanikis 2015), however large scale farmers dominate family farming in developed countries. This situation describes the obstacles must be faced by smallholder farmers. Another problem is how to meet international standards for some agricultural products that produced by small farmers on the global market.

The issue of agriculture sustainability becomes a critical point, especially in the context of family farming. The basis for the sustainability of family farm is a regeneration (Kerbler 2012). The succession of the farming family is a complex, long-term or short-term process during which the farming family transfers the knowledge, occupation, skills, management, control and ownership of agricultural enterprises from generations that have retired to the next generation (Gasson and Errington 1993; and Glauben et al 2003). Meanwhile, succession on smallholder dairy farms is the regeneration process of dairy farms that occurs in the short or long term, in which the transfer of knowledge, norms, skills, management, and business control occurs during the primary socialization from one generation to the next (Firman 2019). The existence of family farming depends on successful intergenerational transfer (Mishra et al 2004). Regeneration at the family farming is an essential process of historical transformation and the values given by old regeneration to the young. Regeneration in the contex of family farming is the transfer of the farmhouse or the occupation of the necessary capital to establish a new farm business from parents to a successor or multiple successors (Lobley 2010). Meanwhile, succession is the process of transferring managerial control, abilities, traditions, and other intangible assets such as site (farm) specific knowledge (Lobley 2010; Bohak and Borec 2009). Farm transfer between generations can be grouped by time, namely as transfer itself or taking over, and as inheritance (Altig and Davis 1992; Kerbler 2012). The taking over of the family farming by the child is a family way to perpetuate the business that has been built by parents, especially in the context of saving and managing assets, capital, income and family welfare. Therefore, successor plays an important role in farm family business sustainability, as well as a key strategic for households in managing risk and expansion.

In fact, agricultural successors tend to choose other jobs outside agriculture sector because of the industrial developments. Competitive salary offers are a concern to attract young farmers to work in the industry. Negative view about working on agriculture, such pensions and not prestigious jobs, has been regarded as mirror images of succession (Lobley 2010). On the other hand, there are still some successors who decide to operate or take over the farms. The successor’s decision to continue family farming must be supported by parents through facilitating and transferring knowledge about farmhouse, such as feeding, breeding, seeding, maintainance, and administrative management. All of these activities can be called the succession process. The impact of successor’s participation on the family farming might not be revealed in the short time, however the participation can influence the successor’s view and indicates a desire to succeed in the farms (Lobley 2010). If young people are unwilling to engage in agriculture, it will have several impacts on the sustainability of family farming such as, the decline in production and productivity, the decline in the number of farmers, and old farmers dominate rural area (Gardner 1992 cited Hennesey 2002; Goddard et al 1993).

Recently, agricultural economists has focused more on various factors affecting succession by using econometric methods; meanwhile rural sociologists try to shed light on various practices and patterns of the process of farm succession, farm transfer, and farmers pension using classical statistical methods (Bohak and Borek 2009). The differences of scholar views are based on the goals of research. The studies of family farm succession using econometric methods have been studied in developed countries. The similar study is very limited in Indonesia. Several researches in developed countries has found the factors influenting successor decision to sustain their family dairy farming businesss. According to Kimhi dan Bollman (1999) who conducted research in Canada and Israel using a probit model showed that the possibility of leaving agriculture declined in both countries because the employment opportunities outside of agriculture also declined and the age of farmers was impossible to work outside of agriculture. Meanwhile, Stigelbauer and Weiss (2015) examined the differences in succession among families in the agricultural and non-agricultural sectors in upper Austria using multinomial logit model. The results of the study show that the probability of farm succession is significantly influenced by some factors such as farm size, previous farm growth, and on-farm diversification. In Austria, the successor can maintain the family farm without having to buy farm from parents, but instead must take care of them and cover some of their needs. Besides, successor also must cover a monetary compensation, which depends on the successor’s financial abilities.

According to Corsi (2004) examined the sucsession decision in Piedmont Region-Italy using probit model shows that one obvious determinant might be children’s individual tastes for farming, including professional pride, tradition and cultural heritage. Those factors could influence the successor’s decision. Hennessy and Rehman (2007) conducted a study in Ireland by using mulitinomial logit to identify factors that influence the choice of family heirs. The results of the study show that the occupational choice and the decision to continue with higher education are made jointly; the nominated successors on more lucrative farms are less likely to pursue tertiary education and therefore more likely to enter full-time farming.

The impact of farm location on succession process has been developed by Aldanondo et al (2007). The research used probit method and found that farm location has been a significant impact to influence successor’s decision to exit the farm. Farms are near center of the city, farm succession is a down. In Switzerland, the research using probit method determines that successors (men or women) who has involved in the family farms was an important factor in the context of family farming sustainability (Mann 2007). According to Mishra dan Hisham (2007) determines that the factor influencing successor’s decision to continue family farms were education, family welfare, debt, and successor participation on family farm. Hennessy (2002) conducted research in family dairy farming businesss in Ireland using logit method determined that the key factors in order to attract successor to work and maintaine family dairy farming businesss are income and dairy productivity.

Conceptual framework

Based on explanation above, there are two kinds of factors influence successors to maintain their family farming, such as economic and social factors. Factors influencing dairy farm succession has been identified. There are 19 explanatory variables that might influence successor’s decision to continue family dairy farm businesss in Pangalengan area, West Java province, Indonesia. The independent variables are divided into 2 factors, 8 varibles in economic factors and 11 variables in social factors. The conceptual framework of the research can be seen in Figure 1. Based on the group of factors, the formula can determine what kinds of factors have a significat effect on successor’s decision to continue family dairy business.

Figure 1. Conceptual framework of successor’s decision



The study was held in 2018 in Pangalengan sub district, West Java province, Indonesia. This area is selected due to the first existence of dairy business in Indonesia. Survey method was used in this study. Data was collected from 246 dairy household (active dairy farmers), including parents (123 respondents) and one child (man or woman) who nomited to be a potential successor (123 respondents). The criterias of child are he/she who have 14 – 30 ages and still stay with his/her parents (Mann 2007). The sample was selected using multistage random sampling. The validity of heterogenity data was measured with coefficients of variation. Coefficients of variation (CV) is standard deviation divided with sampel mean (Hendrayana 2013). The value of CV is < 25% means that the data is homogeny. The variables must exclude in the formula. All variables are used in the formula can be seen at Table 1. There are 3 (three) variables have been exluded in the model because the value of CV is lower than 25%.


Logit model is a model choice that used in dairy farm succession in Pangalengan area. The model was used in the succession researches in Europe (Stigelbauer and Weiss 2015; Hennessy and Rehman 2007; Hennessy 2002). According Utami (1988) cited by Julianti (1990) states that logit model has a simple numerical advantage than probit analysis. The logit model is a method of econometric analysis to describe the relationship between the response variable (dependent variable) which has two or more categories with one or more independent variable of the category or interval (Hosmer and Lemeshow, 2000). Logistic regression is a non linear regression to explain the relationship between Y (dependent) and X (independent), where the occurrence of variable Y is binner, diversity of non-constant response cannot be explained by ordinary linear regression model (Agresti, 1996). Logistic regression is a binary event that Y = 1 is a successor will continue the family dairy farming business business, and Y = 0 is a successor will not continue the family dairy farming business business. Based on Mc Cullagh and Nelder (1989) cited by Hendayana (2013) stated that the variable response is not free following the distribution of Bernouli with parameter π (Xi) which has an opportunity function:


Where the value Yi = 0 or 1, and πi is the chance of the i incident and Y = 1. The distribution is the exponential distribution. Ln (πi / (1- πi)) is the log odds at Y = 1 which is called the logit of πi. From equation (2), the binary response model in logit regression can be formulated as follows (Pindyck and Rubinfield, 1981; Gujarati, 1988):

(2)   if:

The formula can made a simple formula as follows:


Based on equation 4, it can be formulated as follows:


The equation can be formulated as follows:


To make an easy completion, the formula 5 is transformed into the Ln into the following equation:


where: πi is the young generation (πi = 1, if the generation will continue the family dairy farming business, πi = 0, if the younger generation will not continue the family dairy farming business); 1 – πi = opportunities for young people to continue or not continue the family dairy farming business; (πi/(1 – πi)) = Odds ratio; Xj = Vector of independent variables (j = 1,2, …..n); Dk = Vector of dummy variables (k = 1,2, …..n); α, βi, γk = parameters of alleged logistics function of random error. Therefore, the formula for the research as follows:



The odds ratio is to be measure used to see the relationship between dependent and independent variables. Interpretation of the odds ratio coefficient is if an explanatory variable has a positive sign, then the odds ratio value will be greater than one, otherwise if the coefficient is negative then the odd ratio value will be lower than one (Rokhman, 2012). There are several steps to make the formula 7 in a goodness of fit. According to Hendayana (2013) states that there are several methods to determine the feasibility of the model as follows

  1. The formula G test is based on hyphotesis:
    H0: βi =0; (Hi = at least one β)_i≠0 (i=1,2,3,…,p). G test statistic is the defined likelihood ratio test:
    where L0 = likelihood without explanatory variables and L0 = likelihood without explanatory variables and L1= likelihood with explanatory variables. The principle of maximum maximum likelihood is to seek βi value with maximizing likelihood function. G statistic follows χ2 with p. The rule of the decision is to refuse H0 if Gcount > χ2α(p). If H0 is refused, it means that model is significant (α).
  2. Wald test (W). Wald test is used to test βi partially, where hyphotesis H0: βi = = versus H0: βi ≠ 0 (ι=1,2,3,...,p). Wald test formula is:
    where where ^β is a predictor βi and SE βi is the default error estimator of βi. The rule of the decision is to refuse H0 if /Wcount/>Zα/2. If H0 is refused, these parameters are statistically significant.
  3. Concordant, Discordant and Ties are used to measure of association between the responses variable and predicted probabilities.


Description of dairy farmers in study area

Dairy farm has become a livelihood for most of farmers in Pangalengan area. Most of dairy farmers become a cooperative member (namely KPBS). The development of the number of cooperative members can be seen at Figure 2. The number of dairy cooperative members has been decreased gradually for eight years. The main factor that causes a decrease in the cooperative members is the price of fresh milk which is no longer in accordance with production costs. Many farmers have switched to becoming agricultural laborers or contruction workers.

Figure 2. Dairy farmer profiles in Pangalengan area

Dairy farm business are domintaed by smallholder farmers and almost 94% of farmers have 1-6 cows and the rest has more than 6 cows (Table 2). The domination of smallholder farmers has not changed since the 1980s when the Government of Indonesia strongly supported the development of dairy cow business at that time. Besides, most farmers who keep dairy cow are up to the age of 40. It means that older farmers maintain the business, meanwhile young farmers leave their village to find profitable activities in the city. The most farmers graduated from Elementry School, and only 26.83% of farmers graduated up to Elementry School. According to Sari et al (2009), the age of 40 years and low level education can influece the level of innovation adoption (namely ‘late adopter’). The table 2 also illustrates that 44.72% of farmers who are keeping dairy comes from the second generation followed by third generation, and pioneer. It can prove that the dairy farm business is passed down from one generation to the next generation in the study location.

Children’s perception on family farm succession

Family farm succession is a major factor in the sustainable of family farming. Therefore, it is important to explore and find out the views of young generation about dairy farm succession. In Table 3 reveals that potential successors insists of 77.24% men and the rest is women. They have some various ideas to get in the future, such as government official, army or police, farmer, entrepreneur, and others. The majority of children have a dream to work out of dairy business (67.48%) and the rest choose a farmer as their goals future. It means that their future goals reflect that individuals are profit maximizers and will always try to find the most profitable activities (Hennessy 2002).

Meanwhile, children’s perception about working on dairy farm can also be seen at Table 3. It is an interesting result that can be found in the research. Some children have a view that working on dairy farm is last choice work (32.43%). They argue that working on dairy farms need time and effort; complicated, dirty, and not attractive wage; and non potential jobs in the future. Besides, the sector outside the dairy farm is interesting and offer attractive income. On the other hands, 21.24% of children will continue family dairy farming business because the business is still quite promosing in the future.

Factors influence successors to continue family dairy farming

The logit results can be seen in Table 4. There are 16 variables can be involved in the model after 3 variables were selected to be not involved in the model. The logistic regression is formulated in the below.

Model must be tested to detect that the model used becomes fit or not fit to analyze this research. There are several tests that the formulation used in this study is goodness of fit, namely Pearson Method, Deviance Method, Hosmer-Lemeshow Method, the whole test model with G Test, and Partial Test with Wald (W).

The all tests and results can be seen at Table 4. The G test includes all explanatory variables that determine the results: a Log-likelihood of -63.229 with G statistics of 43.070 and p-value 0.000. Because the value of p-value is far below the real level (α = 0.05), it can be concluded H0 rejected or H1 accepted. This means that the overall Logistic Regression Model design is well characterized by at least one β parameter that is not equal to zero at a real α = 0.05. Meanwhile, the model is going to be excellent for used in terms of association measurement between independent and dependent variables. The association measurement used the Concordant, Discordant, and Ties. Concordant value of 80.4 percent can be concluded that approximately 80% of observations with the category of continuing family dairy farm business (Y = 1) was expected to have a greater opportunity than the category of non-continuing family dairy farming business. The discordant value of 19.2% means that about 19% of observations would not continue the family dairy farming (Y = 0). It means that the category of non-continuing family dairy farming was expected to have a greater opportunity than the category of continuing family dairy farming. Ties value of 0.4% means the percentage of observations with the category of continuing the family dairy farming business was equal to the chance of the category of not continuing the family dairy farming business. Last test model is partial test. This test used Wald (W) test that determined with Z coefficient per each variable. Based on Table 4, there are 2 variables that have a very significant effect at α = 0.05, such as number of family member (X11) and time participation of successor on family dairy farming per day (X15).

Based on analysis result, explanatory variables that involve in the model are only 16 variables. Unfortunately, there are 2 variables that have a very significant effect to successor’s decision to continue family dairy farming or the successor will work on family dairy farming, such as number of family members (X11) and time participation of successor on family dairy farming per day (X15). Others did not have a significant effect to young generation to continue the family business. The number of family members (X11) becomes a very influential variable on the choice of young generation to continue the family dairy farming due to the Wald (W) test results are shown from the Z coefficient value, X11 is p-value of 0.003 (α < 0.05). This variable also has odds ratio is 2.6 time. It means that the variabale will influence successor’s decision as much 2.6 times to continue the family dairy farming. This variable is an important choice by a potential successor because the large number of family members means that the burden of parents fulfilling their family needs is getting heavier, even though their dairy business is only a small scale business.

The X15 variable also has a very significant effect on successor’s decision to continue the family dairy farming. It can be shown that the Z coefficient value is 0.000 (α < 0.05). The odds ratio of the variable is 1.52 times to influence the successors continue family dairy farming. Children participation on family dairy cow business is a crutial moment. This participation will have a big impression on young generation decision to determine their future goals. Children participation on family dairy farming can maintain the existence of a family dairy farming in Pangalengan area. This variable is similar with Mishra and Hisam (2007) that successor participation on family farm can influence successor’s decision to continue family farms.


According to description above, the succession decisions in Indonesian family dairy farming whose main objective of this study has been identified. There are 19 explanatory variables have been involved in the model as a result of the literature review, unfortunately only 16 variables are selected in the model. The logistic regression model has been tested and the result determines that the logistical model of succession decisions has responsible predictive power. There are 2 explanatory variables have a very significant effect on successor’s decision to decide continue family dairy farming, such as number of family members and time participation of successor on family dairy farming.



Agresti A 1996 An Introduction to Categorical Data Analysis. Toronto: John Wiley and Sons Inc

Aldanondo O A M, Casanovas O V and Almansa S C 2007 Explaining farm succession: the impact of farm location and off-farm employment opportunities. Spanish Journal of Agricultural Research. 5:214-25

Altig D and Davis S 1992 The Timing of Intergenerational Transfers. Tax Policy. and Aggregate Savings. American Economic Review 82: 1199-1220.

Ambarwati A 2016 Regeneration problems in Agriculture. AKATIGA Bandung.

Anindyasari D, Setiadi A and Ekowati T 2015 Analysis of dairy farmer's income, Banyumanik sub-district, Getasan sub-district, and Cepogo sub-district. Mediagro, 11(2):22-3.

Asih D N 2009 Analysis of characteristics and earning level of shallots farming system in Central Sulawesi. Jurnal Agroland 16(1): 53 – 59.

Asmara A, Purnamadewia Y L and Lubisb D 2017 The relationship analysis between service performances of milk producer cooperative with the dairy farm performance of members. Media Peternakan, 40(2):143-150. DOI:

Bohak Z and Borec A 2009 The use of econometric methods in family farm succession studies. Revija za geografijo - Journal for Geography, 4 (1), 129-136.

Corsi A 2004 Intra-family succession in Italian farms. Paper prepared for presentation at the SFER Conference: Les mutations de la famille agricole: Consequences pour les politiques publiques. Paris.

Crisogen D T 2015 Types of Socialization and their importance in understanding the phenomena of socialization. European Journal of Social Sciences Education and Research 5 (1): 331-336.

Daud A R, Putro U S and Basri M H 2015 Risks in milk supply chain; a preliminary analysis on smallholder dairy production. Livestock Research for Rural Development. Volume 27, Article #137. Retrieved August 10, 2018.

Firman A 2010 Dairy agribusiness: upstream to downstream. PT. Widya Padjadjaran. Book

Firman A 2019 Succession on family dairy farms in relationship with social and economic factors. PhD dissertation, Animal Husbandry Faculty, Universitas Padjadjaran, Indonesia.

Firman A, Budimulati L, Paturochman M and Munandar M 2018 Succession models on smallholder dairy farms in Indonesia. Livestock Research for Rural Development. Volume 30, Article #176. Retrieved February 24, 2019.

Gale H F 1993 Why did the Number of Young Farm Entrants Decline? American Journal of Agricultural Economics 75: 138-146.

Gasson, R and Errington A 1993 The Farm Family Business. CAB International, Wallingford; ISBN 9780851988597

Glauben T, Hendrik T and Vogel S 2003 Farm succession patterns in Northen Germany and Austria – a survey comparisn. Christian-Albrechts Universitat zul Keil, Institute of Economics and Consumption studies.

Goddard E, Weersink A, Chen K and Turvey C G 1993 Economics of Structural Change in Agriculture. Canadian Journal of Agricultural Economics 475-489

Gujarati D N 1988 Basic Econometrics. Second Edition. McGraw Hill Book Company.

Hendayana R 2013 The aplication of logistic regression method in analyzing the adoption of agriculuture technology. Journal of Informatika Pertanian, 22(1): 1 – 9.

Hennessy T 2002 Modelling Succession on Irish dairy farms. Paper prepared for presentation at the Xth EAAE Congress ‘Exploring Diversity in the European Agri-Food System’, Zaragoza (Spain), 28-31 August 2002.

Hennessy T and Rehman T 2007 An investigation into factors affecting the occupational choices of nominated farm heirs in Ireland. Journal of Agricultural Economics. 58(1):61-75.

Hosmer D W and Lemeshow S 2000 Applied Logistic Regression. 2nd Edition. New Yor: John Willey and Sons

Kerbler B 2012 Factors affecting farm succession: the case of Slovenia. Cech Academy of Agricultural Science (CAAS), Agricultural Journal, 58 (6): 285–298.

Kimhi A and Bollman R 1999 Family farm dynamics in Canada and Israel: the case of farm exits. Journal of Agricultural Economics, 21(1999):69-79.

Lobley M 2010 Successionin the family farm business. Journal of Farm Management 13(12): 839 -851.

Lobley M, Baker J R, and Whitehead I 2010 Farm succession and retirement: Some international comparisons. Journal of Agriculture, Food Systems, and Community Development, 1(1): 49-64.

Lucas R E Jr 2004 Life earnings and rural–urban migration. Journal of Political Economy 112(1):29–59.

Mann S 2007 Tracing the process of becoming a farm successor on Swiss family farms. Agriculture and Human Values, Journal of the Agriculture, Food, and Human Values Society, 24(4):435-443

Mishra A K and Hisham S E O 2007 Factors Affecting Succession Decisions in Family Farm Businesses: Evidence from a National Survey. Journal of the American Society of Farm Managers and Rural Appraisers, 2007:1-10

Mishra A K, El-Osta H S and Johnson J D 2004 Succession in Family Farm Business: Empirical Evidence from the U.S. Farm Sector. Selected Paper for Presentation at the AAEA Meeting in Denver, CO August 1-4 : 1-28.

Mishra A K, El-Osta H S and Shaik S 2010 Succession decisions in U.S. farm family businesses. Journal of Agricultural and Resource Economics 35 (1), 133–152.,Apr2010,pp133,Mishra.pdf

Nuhung I A 2015 Factors motivating farmers to sell their land and its impacts in suburban areas. Jurnal Agro Ekonomi, Volume 33(1), 17-33.

Pindyck R S and Rubbenfield D L 1991 Econometrics Models and Economics Forcast 3th edition. Mc Graw Hill. New York

Posso M L and Urbano D 2017 Relevant factors in the process of socialization, involvement and belonging of descendants in family businesses. Revista Innovar Journal 27(63): 61-76

Rapsomanikis G 2015 The economic lives of smallholder farmers: An analysis based on household data from nine countries. Food and Agriculture Organization of the United Nations: 1-39

Rokhman M S 2012 The comparation between logit and probit regression model as explanatory response. Oseatek UPS Tegal.

Sari A I, Syahlani S P and Haryadi F T 2009 The characteristic of adopter categories on the innovation adoption of feed additive herbal usage for broilers. Journal of Buletin Peternakan, 33(3): 196-203.

Stigelbauer A M and Weiss C R 2015 Family and Non-Family Succession in the UpperAustrian Farm Sector. Cahiers d’Economie et de Sociologie Rurales, INRA Editions, 2000, 54, pp.5-26. hal01200950.

Wiyono S, Sangadji M, Ahsan M U and Abdulah S 2015 Farmer generation research on household farmers of paddy and holticulture. Oxfarm Indonesia, 1-41.

Received 17 July 2019; Accepted 8 August 2019; Published 1 September 2019

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