Farm entry and exit are a process of livelihood diversification or transition in the agricultural sector, which contributes to global competitiveness of agriculture and efficient resources allocation between agriculture and other sectors in the economy (Binswanger-Mkhize, 2013). More than 2.5 billion out of the three billion rural population deriving their livelihoods from agriculture (FAO, 2021). However, the dwindling size of agricultural land, increasing population, low productivity and hostile agro-ecological factors often result in extreme income variability in agriculture. In response, rural households often use farm entry and exit to diversify their livelihood activities and smooth income variability. Off-farm livelihood opportunities in rural areas often play an important role in reducing food insecurity (Barrett et al., 2001). However, farm exit in the form of shifting from on-farm to off-farm activities does not necessarily create positive outcomes in terms of either reducing poverty or increasing incomes, particularly in developing agrarian countries. In some circumstances, this shift seems to have increased poverty (Imai et al., 2014).

Theoretically, structural transformation in the economy is driving on-farm labor into the off-farm sector for pursing a more sustainable livelihood. Some farming households exit farm and move to other sectors, as they consider agriculture a low productive and highly risky occupation (Haggblade et al., 2010; Hussain, 2014). Farm exit to off-farm sectors has been extensively investigated (Kimhi and Bollman, 1999; Pietola et al., 2002; Glauben et al., 2006; World Bank, 2007; Cai and Wang, 2010; Knight et al., 2011; Wang et al., 2011; Bhandari, 2013; Ahmad et al., 2020). In contrast, the shift from off-farm to on-farm as new farm entry has not been investigated yet in the context of agricultural-based economies including Pakistan. In such cases, promoting agricultural activities remains a priority in order to achieve the Millennium Development Goal (MDG), which is to reduce poverty and hunger, to sustain livelihoods by increasing new and well educated farmers and by stop farm exits as well (World Bank, 2008). Adjustments to an agricultural structure could also attract and encourage more people to enter farming and pursue farming either as a main occupation or an additional source of income (Mishra and El-Osta, 2016). In addition, the emphasis of farmers’ rights for self-sufficiency in food by growing their own food can encourage former farmers to return to farming (Agarwal and Agrawal, 2017).

Pakistan is heavily dependent on agricultural production which contributes 24% to its GDP (Pakistan Bureau of Statistics, 2019). Unfortunately, its agricultural system fails to maintain its growth due to serious challenges such as water shortage, climatic change, rising input prices, limited policy incentives for farming and low trust in government, making farmers reduce their cultivated area and worsen the country’s overall agricultural productivity (Pakistan Bureau of Statistics, 2018). Following the 9/11 event in U.S. in 2001, Pakistan has fought a long war of 19 years against terrorism as an ally of the US, by closing doors to foreign investments. Since then, the farm sector has been in its recession. Pakistan’s agriculture sector started to decrease in sizes since 2001 due to emerging water shortages, climatic changes and natural disastrous events (floods, heavy rain and drought), as well as high input prices, low output prices, which reduced the earnings of both farming and non-farming communities, and increased the unemployment rate in the country (State Bank of Pakistan, 2015). More importantly, the challenges mentioned above are causing farmers to exit from farming. For example, the agricultural sector has experienced an obvious decline at both the absolute and relative levels in farm employment percentage, from 45 to 38.5% over the last decade (Pakistan Bureau of Statistics, 2018). It is thus of importance to know why farmers exit agriculture and how their livelihoods change after exit (Ahmad et al., 2020).

This study aims to firstly close a significant research gap by identifying the factors driving farm entry and exit in Pakistan. Secondly, this study further investigates the impact of farm entry and exit on households’ wellbeing in terms of total household income, food security status and ability to save for an emergency funds. Thirdly, this study also aims to identify the beginner farmers, who are they, and why did they enter into farming? To the best of our knowledge, these can be the first empirical work to examine both farm entry and exit decisions for rural households in Pakistan.

To achieve the goals above, this study is organized as follows: The next section provides a comprehensive literature review, followed by introducing farmers’ livelihood options in Pakistan. Section 4 provides a conceptual framework, followed by introducing our methods and data. Section 6 provides estimated results and analyses, followed by a balance test and sensitive analyses. The last section concludes.

Over the past century, agriculture sector has transformed from a labor-intensive to a capital-intensive industry. The shift has allowed people to engage in secondary and tertiary sectors and to relocate to non-farm regions. As a result, farming workers have fallen significantly (Lobao and Meyer, 2001; Gale 2003; Conkin, 2008; Ahearn and Newton, 2009). For example, Gale (2003) noted that most farm exits are voluntary, retiring, passing management to the next-generation or leaving farming due to poor health and death in western countries. The family farm is viewed as the backbone of rural communities and the decline of farm number raises questions with regard to whether these communities can sustain themselves. Although intergenerational family transfer remains the dominant mechanism for farm succession, in most western European countries and the United States, the number of family farm transfers was decreasing (Gale, 2003; Calus et al., 2008).

For the new entry farm, there could be some barriers for the new farmers. For example, the studies consistently identify access to affordable land as the greatest barrier to entry to agriculture (Ackoff et al., 2017; Frost, 2017). Many beginning farmers said that they lacked the means to employ the number of skilled farm workers necessary to maintain and grow farm operations (Ackoff et al., 2017). Climate change could be the key issue causing an increase in unpredictable extreme weather events; increases in drought and flooding events threaten to destroy crops and reduce yields and most of the farmers have experienced the influence of climate changes (Ackoff et al., 2017). Therefore, many small- and mid-size farm operators require off-farm income to make ends meet (Gillespie and Johnson, 2010). In general, beginning farmers face steep start-up costs and barriers to accessing capital, land, and credit (Ahearn, 2011; Lusher Shute, 2011; Calo, 2018).

Farming is characterized by an ageing population with a reduced rate of entry into farming by younger farmers and a reduced rate of retirement by older farmers (ADAS, 2004). The farming industry has failed to attract “new blood” into the industry, partly due to the poor rewards and partly due to entry barriers such as high start-up costs and a shortage of available land (ADAS, 2004); something that is exacerbated by restructuring processes that are leading to fewer, larger farms within both the private and county estates (Whitehead and Millard, 2000). At the same time, a lack of suitable successors and taxation issues have been identified as making farmers reluctant to retire (Williams and Farrington, 2006). This is the result of a number of entry-exit challenges such as increasing capital requirements, low expected rates of return and higher off-farm career opportunities (Gale, 2003; Williams and Farrington, 2006). Several studies from developed countries have highlighted these adjustment challenges facing the farming industry (Caskie et al., 2002; Errington and Lobley, 2002; ADAS, 2004; Calus et al., 2008).

Concerns about the sustainability of an ageing farming population have brought interest in so called entry-exit issues in policy circles. Policy interventions to date have offered limited scope in stimulating farm transfer, however, the increase in unconventional tenures which include partnerships, share farming and contract farming, would appear to offer new opportunities for those wishing to enter or leave farming (Ingram and Kirwan, 2011). Bruce (2019) identified a new pathway into alternative agriculture that returning farmers come from farm families, but left agriculture to pursue higher education or a non-farm career and then re-entered agriculture later in life through Alternative Food Networks (AFNs). However, social movements promoting alternative models of agriculture have created organizations to support a new generation of farmers, and generated AFNs that provide new training opportunities and markets for aspiring farmers.

As most of agriculture farms in Pakistan are small and not well educated, thus they do not have better off-farm jobs in the country except daily paid labor. For example, a study from Khyber Pakhtunkhwa (KPK) province investigated the determinants of the off-farm employment of the small farm which showed that most of small farms (90%) were engaged in off-farm jobs along with agricultural activities (Ali et al., 2014). The nature of their job was in daily paid labor, part time employment, and different off-farm businesses. The effects of farm underemployment, working age group size (age of the farmer), income from other sources, and education were positive on the off-farm employment (Ali et al., 2014). For example, Rizwan et al. (2017) conducted a study in province Punjab, Pakistan and found that about 66% farmers were involved with off-farm activities along with on-farm activities. The results indicated that education has significant influence and stimulate for engagement in off-farm employment. However, presence of younger population in households and land renting opportunity stimulate migration in other cities and countries. Dependency ratio and large family size were the driving factors for participation in off-farm labour activities.

Though, off-farm activities as part-time are also being performed in Gilgit-Baltistan, Pakistan. In this case, farmer characteristics (e.g. farmer age, gender and education), farm characteristics (e.g., farm size, specialization in horticulture, etc.) and agricultural income (Shahzad et al., 2021). Tahir et al. (2012) investigated the factors contributing to off-farm employment in North West Pakistan. They found that farm size, family size, farm underemployment, education, and income from other sources were the main factors determining off-farm employment. It was also observed that farmers of the comparatively developed areas devote more time to off-farm employment. The study revealed that most of the farmers were engaged in daily paid labor. Overall there is a gradual shift from farm to off-farm employment which is resisted by the underdeveloped means of transport and communication, education and lack of basic infrastructure.

Few studies that investigated the factors that affect occupational choices of populations living in rural areas of Pakistan. Jan et al. (2012) revealed that the likelihood to participate in non-farm informal sector increases for household having relatively younger head with no education. Household size positively and significantly related to all the occupational groups while additional working members in a household reduces the odds to engage in farming by about 67% relative to non-farm informal sector. Similarly, per capita income also plays a significant role in pursuing occupations other than informal activities. In addition, to know the influence of migration on farm exit, Abbasi and Kim (2018) investigated that agriculture is not the primary source of income and 32% agriculture labor force migrated and migration is the main reason for declining labor force and increasing shifted to off farm activities.

However, the youth (aged between 15 and 29 years) in Pakistan seems less interested in performing agriculture activities. They regarded the agriculture sector as non-profitable, hence they do not see them joining the agriculture sector due to high cost of production, crashed marketing system, absence of farmer-friendly policies, environmental issues and lack of support from government in agriculture sector (Ahmad et al., 2020; Aftab et al., 2021). Thus, most of farms are involved in non-farm income generation activities in southern Punjab, Pakistan. The majority of the farmers offered labor for off-farm work followed by self-employment ventures. The major reason to pursue non-farm work includes low income from agriculture, mitigating risks associated with farming. A range of socioeconomic and infrastructure-related variables are associated with the decision to participate in specific off-farm activity, such as age, education, family size, farm income, dependency burden, farming experience, and distance to the main city.

In case of Pakistan, there has been a steady shift from subsistence farming to cash crops and fruit production, which is particularly noticeable in the accessible parts of the region that are located closer to urban centers. In addition, the rising proportion of household income from non-farm activities (increasing from 43% in 1994 to 63% in 2005 and more than 70% in 2020 (Shahzad et al., 2021), plays an important role in the transformation of the rural economy. Similarly, the increased labor outmigration towards the services sector in down-country Pakistan stemming from the improved formal education systems has increased the share of non-farm employment plays an important role in the transformation of the rural economy. Similarly, the increased labor outmigration towards the services sector in down-country Pakistan stemming from the improved formal education systems has increased the share of non-farm employment.

Under these circumstances, the maintenance of farming communities is largely under threat. The increased rate of rural-to-urban migration (Gioli et al., 2014), particularly that of younger people (Benz, 2016) and the rapid growth of the non-farm sector (Gioli et al., 2014; Shahzad et al., 2021) have resulted in decreased agricultural land-use and increased uncertainty regarding farm continuation.

Studies on rural off-farm and on-farm activities consider livelihood diversification and income stabilization (or risk minimization) as the major motives for working outside of agriculture (Rose, 2001; Haggblade et al., 2010). Livelihood diversification is driven by “pull” factors (e.g., markets, opportunities, infrastructural facilities and supportive institutions) and “push” factors (e.g., various idiosyncratic shocks such as floods, droughts, environmental degradation, chronic rainfall deficit). Similarly, off-farm labor could shift towards farming activities in case of unemployment, old age, job insecurity and health issues (Mishra and El-Osta, 2016). Also, farmers’ rights for self-sufficiency in food by growing their own food can encourage former farmers to return to farming (Agarwal and Agrawal, 2017). As a result, a large part of the world’s labor force work in agriculture, not by choice, but due to lack of alternatives (Cain, 1977; Kumar and Hotchkiss, 1988; Chitrakar, 1990; Karan and Ishii, 1995; Filmer and Pritchett, 1997; Agarwal, 2014). It is important to understand households’ motives of diversifying beyond agriculture or moving away from off-farm work. Therefore, we base our theoretical framework on livelihood vulnerability as diversification/transition motive, because it best serves the main objective of the study, which is to investigate the determinants of households’ diversification decisions ¹ of farm entry and exit.

To better understand the Pakistani agriculture sector, we classify the factors associated with “farm entry and exit” into the following groups: 1) human capital referring to characteristics of household head and household; 2) natural capital including land, livestock and irrigation systems; 3) economic capital comprising of loans or credit, off-farm employment, and off-farm income and sources; 4) climate shocks, including natural disasters and severe crop diseases; 5) climate change investment ² referring to access to micro finance institutions (MFIs), all weather road and climate knowledge (Eifert and Ramachandran, 2004); and 6) locational characteristics such as home remoteness and the extent of commercialization and urbanization.

It is hypothesized that a household can involve in one of the two livelihood transition scenarios: 1) exit farming and shift to off-farm activities; or 2) enter farming and shift to on-farm activities. Each household is assumed to make a rational choice, which is when income generated from the new sector is higher than that from the last. Households that intends to enter farming face barrier such as capital investment, climate challenges, farming experience, knowledge and skills and other household constraints. Similarly, households that want to exit farming could face barriers in off-farm employment, age, skilled labor, education, family labor and other household constraints. We assume that a farming household i has fixed capital and labor endowments, assigned among different activities in agriculture, which is expressed in Equation One: I i = E t ∑ τ = 1 T β τ − 1 π i I P , O P , L C i , φ t , ε i (1) Where   I i is the income of household i , E t   is expectation operator providing information at time t, β is the subjective discount factor, T is the number of periods, π i isthe profit generated for household i which is a function of input price I P , output price O P , fixed labor and capital endowments L C i , a vector of economic shocks that could affect household income and livelihood diversification φ t , and ε i includes unobserved characteristics that could affect income. Suppose a household is generating income from agricultural activities, Equation One is adapted to Equation Two with subscript A indicating agriculture: I A i = E t ∑ τ = 1 T β τ − 1 π A , i I P A , O P A , L C i , φ t , ε i (2)

For farm entry, household income is denoted by I B i and expressed in Equation Three: I B i = − C i , t N i ,   I i ,   H i , + E t ∑ τ = 1 T β τ − 1 π B i I P B , N i ,   I i , O P B N i ,   I i , L C B , i , μ i (3) Where C i , t is farm entry cost, which could be affected by investment I i such as climate, capital and farm machinery assets and other inputs. Furthermore, other factors like availability of financial services, government policies, taxes and infrastructure could reduce or increase the entrance barrier. These characteristics could also capture input-output markets at specific locations and availability of micro finance institutions (MFIs) and farm advisory services. Furthermore, farm entry could also be affected by the characteristics of household head H i such as age, education, migration status and location N i . Input prices I P B and output prices O P B are part of the entry function into farming, which could be affected by location factors that may be associated with lower than market prices for crop outputs ³ and μ i isunobserved characteristics.

Households assign their total amount of fixed labor and capital for different activities, which can be expressed as: L C i = L C A i + L C B i (4)

As we mentioned above, household could diversify income strategy through farm entry if on-farm income is greater than off-farm income, as shown in Eq. 6. I A i + I B i > I i (5)

OR I B i > I i − I A i (6)

Following Eq. 6, the probability of diversifying to farming can be written as: p r o b B i = p r o b ( − C i t N i ,   I i ,   H i , + E t ∑ τ = 1 T β τ − 1 π B i I P B , N i ,   I i , O P B N i ,   I i , L C B i , μ i ) > p r o b ( E t ∑ τ = 1 T β τ − 1 π i I P , O P , L C i , φ t , ε i − π A i I P A , O P B , L C i , φ t , ε i ) (7)

As input and output prices do not change whether the household works only in agriculture or diversity to off-farm work. Therefore, we do not expect them to play a significant role in affecting household’s choice except when the actual level of profit is estimated. Hence, we expect that household labor and capital endowments, which are fixed, may play a vital role in decisions on farm entry and exit.

If a household enters into farming, d B i is defined as 1, and 0 if a household stays in off-farm activities (see Supplementary Appendix SA1). Stochastic factors ε i and μ i are assumed to be identically and independently distributed, and then the probability of farm entry is given as: f H i , N i , I i , φ t i f   d B i = 1 0 o t h e r w i s e (8)

Further, once households enter into farming, they could face two choices: either continue or exit farming. Households could face barriers when existing farming, such as investment made on non-transferable fixed assets, land rent, farm machinery and long run investment. Whereas, incentives at household level such as high grain prices could encourage farm entry, particularly for those who enter to produce domestic grain food. The income generated from agriculture will then depend on the trade-off between the cost of farm exit and the profit earned from continuing farming. Moreover, households’ earnings depend upon farming inputs and output prices which are determinants of farm entry together with other factors such as land status, yields, etc. Given these, if the present value of on-farm income is less than off-farm income, household will decide to exit farming, which can be expressed as: I B i E < I i E − I A i E (9) where I i E is income of an incumbent household i . Likewise, the probability of farm exit is a function of household specific characteristics H i , farming capital factors F C i , fixed inputs of labor and capital L C i , locational specific factors N i , I i and climate shocks affecting agriculture φ i .

The characteristics of exit and continue farming households are shown in Table 4. We find that the difference between exit and continue farming was statistically significant in household owned off-farm business, owned land (family farm), access to canal irrigation source and poor village infrastructure. Regarding the household owned off-farm business, exit farmers significantly were less (5%) compared to continued farms (8%). Similarly, we found that the household that exit farms were also those who had family farm (owned land), anyhow these were less (43%) compared to continued farms (77%). We also observe that canal source of irrigation significantly associated with farm exit (60%), which is lower than farm continuing households (74%). More important, natural disasters significantly increases the percentage of exit farm (56%) which was higher than continued farming (33%). Furthermore, village infrastructure also significantly associated with farm exit, the results show that 14% households exit farming due to poor village infrastructure particularly connection of roads which is mud or kacha road.

Table 5 represents the characteristics of new entrance into farming. We find that the difference between new entrance and stay at farm was statistically significant and higher in new entrance (2.602) compared to stay at farm (2.377). Similarly, we find that the new entrance farms were also those who had owned family farm (owned land) were higher (16%) compared to stay at farm farms (5%). We also observe that canal source of irrigation significantly associated with new entrance and attract new entrance as 82% household enterd into farming due to canal irrigation source. More important, natural disasters significantly associated with new entrance by 15%. Furthermore, Khal Panchayats system significantly attracts 15% new entrance. More important, household affected by natural disasters significantly increases the percentage of exit farm by 56% which was higher than stay at farm farming (33%).

Table 6 presents the logit regression to generate the propensity scores. The goodness of fit can be measured by the pseudo R ² value, and logit estimation gives a pseudo R ² of 0.158 in farm exit model. The results indicate that, all other things being equal in our sample, migration, land ownership, irrigation source (canal), natural disasters, crop inputs used as credit, water shortage during seasons and poor village infrastructure are more likely to be exit farming. Similarly, Table 7 also presents the logit regression to generate the propensity scores and logit estimation gives a pseudo R ² of 0.141 in new entrance model. The results indicate that, all other things being equal in our sample, land ownership, irrigation source (canal), natural disasters, water shortage during seasons and Khal Panchayats system work actively are more likely to be entrance into farming.

Tables 8, 9 show the results of balancing tests for the PSM with before and after nearest neighbor 1-to-1 matching method (refer to Supplementary Appendix SA2, Supplementary Appendix SA3, Supplementary Appendix SA4). Further we used t-test to compare the mean of each covariate between the treatment and control group after the matching procedure. If the matching was successfully accomplished, the mean difference after matching should be insignificant. The results of the t-test showed that the differences in most of the covariates became significant after the matching procedure, which indicates that the observable characteristics of the control group were sufficiently similar to those of the treatment group after matching.

Table 10 presents household wellbeing results for entry and exit for three outcome variables (Total household income, Domestic food shortage, and Able to earn money in an emergency) by using nearest neighbor 1-to-1 matching method. The results provide strong evidence that entry decision has significantly and negatively associated with household wellbeing in terms of total household income, whereas positively associated with Domestic food shortage and Able to earn money in an emergency but results are insignificant. The results indicated that households that have entered into farming on average have an annual income Rs. 39,340.8 ($409.79) less than those who have not entered into farming. Furthermore, we find that the standard matching ATTs of Domestic food shortage is positive and statistically insignificant, indicating that entering into farming results in increase in food shortage. However, these results void our hypothesis that entry into farming could be an excellent effort for hushed to be self-sufficient in food security in the future. Turning to farm exit, the ATTs of Able to earn money in an emergency is statistically significant and indicates that households that have exit farming on average have an annual income Rs. 11,716.63 ($122.04) more than those who have not exit farming but the results are insignificant. Furthermore, we find that the standard matching ATT of Domestic food shortage is positive and statistically significant, indicating that exit from farming results increase in food shortage. However, these results are in line towards our hypothesis that exit farming could lead household to be food insecure in the future.

Furthermore, we calculated the critical value of Γ † (Table 10). For the significant ATTs, the value of Γ † total household income is 1.2. It implies that matched entry farmers with the same observed covariates would have to differ in terms of unobserved covariates by a factor of 1.2 for total household income inference of a significant treatment effect. Similarly, in case of farm exit decision, the value of Γ^† for Able to earn money in an emergency is 1.6. It implies that matched exit farmers with the same observed covariates would have to differ in terms of unobserved covariates by a factor of 1.6 for able to earn money in an emergrncy to invalidate the inference of a significant treatment effect. Therefore, we conclude that the impact estimates are fairly robust to potentially hidden bias. Apel et al. (2010) reported that the estimation results in applied research often become sensitive to Γ value as small as 1.15. However, the results are sensitive to unobserved characteristics of other insignificant ATTs.

This article has investigated and identified factors that affect households’ farm entry and farm exit based a dataset of 1867 households. This study also investigates the impact of entry and exit decisions on households’ wellbeing by using PSM approach for three wellbeing outcomes. This study has brought fresh insights into sustaining rural livelihoods of both the farming and off-farm sectors.

Firstly, our results suggest that household decision of entry into farming significantly decreases household income, while household decision of exit from farming significantly increases domestic food shortage. This finding indicates that farming would be rural household income source in Pakistan. This finding might explain why a larger share (24%) of rural off-farm working labor has shifted into farming as new entrants in Pakistan since 2014.

Secondly, we found that climate shocks could significantly affect farm entry and farm exit decisions, respectively. It is meant that climate shocks could change farmers’ future attitudes towards farming. This finding points out a potentially concern as Pakistan agricultural production and livelihoods are particularly vulnerable to climate shocks. In fact, as stated previously, Pakistan’s agriculture sector has been faced serious challenges of water shortages and natural disastrous since 2001, and even currently massive floods are still in this country.

Thirdly, descriptive statistics show that approximate 60% of smallholders exited from farming between 2012 and 2014, and 15% of smallholders exit farming after 2014, because they had to sell off their borrowed or credit crop inputs (mainly fertilizer). The major reason is due to the lack of national macro agricultural support policies. In fact, there are more than 80% are samllholders, but the agricultural subsidies (e.g., fertilizer and machinery purchase) are only provided for large farms (over 12 acres of land) in Pakistan (Ali et al., 2019).

Gernally, agriculture is still major income source for most of rural huseholds and that is why smallholders exist in Pakistan on the one hand. On the other hand, off-farm income also reduces smallholders to exit farming. More importantly, climate shocks and national agricultural support policy can be the crucial factors for smallholders whether to enage in agricultural production.

As with most research, this study has some limitations. For example, we did not discuss whether any household member inherited family farms as a successor or not. We are also unable to identify whether the entrants into farming were permanent or temporary. These questions are also potential for future research.