Farmland loss and livelihood outcomes: A microeconometric analysis of household surveys in Vietnam

Dr Tran Quang Tuyen is a lecturer in economics at VNU University of Economics and Business, Vietnam National University, Hanoi. His research interests cover land, rural livelihoods, poverty, inequality and household welfare. His papers have been accepted for publication in international journals. Besides, he has several publications in national journals. Dr Steven Lim teaches economics at the Waikato Management School, New Zealand, and Senshu University, Tokyo. His research interests in business economics include the relationship between HIV/AIDS and poverty, the social and community health impacts of trade liberalization, the economics of landmine clearing and economic growth and the environment. Dr Michael P. Cameron is a senior lecturer in economics at University of Waikato, and a research fellow in the National Institute of Demographic and Economic Analysis (NIDEA). His current research interests include population, health and development issues, population modelling and stochastic modelling, financial literacy and economics education. Vu Van Huong is a lecturer in economics and econometrics at Academy of Finance, Vietnam and currently is a PhD candidate at University of Waikato, New Zealand. His research interests include international economics, development economics and applied econometrics. His recent papers have been published in the Economics Bulletin.

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small-sized farms or cow-grazing households. These activities, however, have significantly declined due to the spread of cattle diseases in recent years. Households Journal of the Asia Pacific Economy 9 D ow nl oa de d by [T &F In ter na l U se rs] , [ Ca ro lyn H ay ne s] at 03 :52 24 A pr il 2 01 4 T ab le 2 . M ea n an d co m p o si ti o n o f h o u se h o ld in co m e an d co n su m p ti o n ex p en d it u re , b y li v el ih o o d st ra te g y . L iv el ih o o d st ra te g ie s V ar ia b le s W h o le sa m p le In fo rm al w ag e w o rk F o rm al w ag e w o rk N o n fa rm se lf -e m p lo y m en t F ar m w o rk N o n la b o u r in co m e T o ta l an n u al h o u se h o ld in co m e 6 0 ,6 4 2 4 9 ,2 4 5 8 4 ,1 7 9 6 6 ,2 5 4 5 1 ,3 5 7 2 8 ,4 1 4 S D 3 3 ,0 3 4 1 7 ,0 8 8 3 7 ,9 3 4 3 6 ,7 8 3 2 3 ,5 0 9 1 8 ,5 4 2 M o n th ly in co m e p er ad u lt eq u iv al en t 1 5 0 0 1 2 0 0 1 8 4 1 1 7 3 8 1 2 1 5 1 4 2 7 S D 7 6 6 4 5 9 8 7 8 8 8 0 5 2 1 6 8 5 M o n th ly in co m e p er ca p it a 1 1 2 6 8 8 5 1 3 9 5 1 3 1 0 9 1 6 1 2 1 0 S D 5 9 1 3 4 5 6 8 1 6 7 6 4 0 0 6 0 6 P er ce n ta g e h o u se h o ld in co m e b y so u rc e F ar m w o rk 2 7 .6 9 1 7 .2 8 1 1 .7 7 1 3 .6 7 7 7 .6 8 7 .5 5 S D 3 0 .3 7 1 5 .1 0 1 3 .4 3 1 4 .3 1 1 8 .8 0 1 2 .2 8 In fo rm al w ag e w o rk 2 3 .2 0 7 4 .7 8 2 .9 5 3 .8 3 6 .9 8 1 8 .2 1 S D 3 3 .1 8 1 6 .4 0 8 .4 0 1 0 .7 8 1 3 .2 1 1 8 .8 4 F o rm al w ag e w o rk 1 6 .9 5 0 .8 3 7 5 .4 7 2 .7 1 4 .5 0 1 .2 4 S D 3 1 .0 2 5 .6 6 1 6 .2 9 9 .2 8 1 1 .3 3 5 .5 7 N o n fa rm se lf -e m p lo y m en t 2 5 .7 4 3 .7 2 3 .6 1 7 6 .3 4 9 .1 5 2 .5 5 S D 3 4 .7 0 8 .5 7 8 .9 1 1 6 .1 0 1 5 .2 0 7 .9 2 N o n la b o u r in co m e 6 .4 1 3 .4 0 6 .2 0 3 .4 4 1 .7 0 7 0 .4 5 S D 1 6 .2 5 8 .1 3 1 1 .9 0 7 .5 6 5 .6 6 1 8 .4 6 T o ta l an n u al h o u se h o ld ex p en d it u re 5 0 ,5 3 0 4 5 ,7 9 7 6 4 ,7 6 0 5 1 ,9 7 2 4 7 ,0 8 1 2 0 ,1 5 5 S D 2 2 ,0 9 7 1 6 ,1 5 6 2 1 ,5 9 7 2 3 ,4 2 7 1 9 ,4 1 7 1 0 ,4 8 8 M o n th ly ex p en d it u re p er ca p it a 9 3 8 8 2 3 1 0 7 3 1 0 2 8 8 4 0 8 5 8 S D 2 9 0 2 3 0 2 9 6 3 1 1 2 3 0 2 5 3 M o n th ly ex p en d it u re p er ad u lt eq u iv al en t 1 2 4 7 1 1 1 5 1 4 1 6 1 3 6 3 1 1 1 4 1 0 1 2 S D 3 8 9 3 0 2 3 8 2 4 0 9 3 0 9 2 7 6 M o n th ly fo o d ex p en d it u re p er ad u lt eq u iv al en t 6 4 3 6 0 0 7 1 4 6 9 3 5 7 2 5 5 3 S D 2 0 5 1 6 1 2 1 5 2 4 1 1 5 1 2 0 0 M o n th ly n o n fo o d ex p en d it u re p er ad u lt eq u iv al en ta 6 0 4 5 1 5 7 0 2 7 0 0 5 4 2 4 6 0 S D 2 4 0 1 9 5 2 6 2 2 3 5 2 1 5 1 5 3 N u m b er o f p o o r h o u se h o ld sb 6 4 2 2 8 1 0 2 1 3 N u m b er o f h o u se h o ld s 4 7 7 1 2 5 1 0 0 1 2 8 1 0 3 2 1 N o te s: M ea n an d S D (s ta n d ar d d ev ia ti o n ) ar e ad ju st ed fo r sa m p li n g w ei g h ts . In co m e, ex p en d it u re an d th ei r co m p o n en ts in 1 0 0 0 V ie tn am D o n g (V N D ) (1 U S D eq u at ed ab o u t to 1 8 ,0 0 0 V N D in 2 0 0 9 ). a T h is in cl u d es d ai ly an d y ea rl y n o n fo o d ex p en d it u re , h ea lt h , ed u ca ti o n , el ec tr ic it y , w at er an d h o u si n g ex p en d it u re . b T h ey w er e ca lc u la te d u si n g th e G S O -W B p o v er ty li n e d efi n ed b y th e G en er al S ta ti st ic al O ffi ce o f V ie tn am an d th e W o rl d B an k in 2 0 1 0 , w h ic h is b as ed o n th e m o n th ly co n su m p ti o n ex p en d it u re p er ca p it a o f 6 5 3 ,0 0 0 V N D (W B 2 0 1 2 ). 10 T.Q. Tuyen et al. D ow nl oa de d by [T &F In ter na l U se rs] , [ Ca ro lyn H ay ne s] at 03 :52 24 A pr il 2 01 4 T ab le 3 . S u m m ar y st at is ti cs o f h o u se h o ld ch ar ac te ri st ic s, li v el ih o o d as se ts an d p as t li v el ih o o d ch o ic e, b y li v el ih o o d st ra te g y . C u rr en t li v el ih o o d st ra te g ie s T h e w h o le sa m p le In fo rm al w ag e w o k F o rm al w ag e w o rk N o n fa rm se lf - em p lo y m en t F ar m w o rk V ar ia b le s M S D M S D M S D M S D M S D F a rm la n d lo ss L an d lo ss 2 0 0 9 1 0 .2 7 2 4 .5 0 1 2 .2 8 2 7 .0 0 8 .4 4 2 1 .9 7 8 .8 0 2 2 .1 1 6 .5 4 1 8 .9 6 L an d lo ss 2 0 0 8 1 0 .5 0 2 4 .0 0 1 6 .5 3 2 9 .0 6 7 .2 0 1 8 .9 1 1 0 .2 2 2 3 .6 0 5 .3 8 1 6 .4 0 H u m a n ca p it a l H o u se h o ld si ze 4 .4 9 1 .6 1 4 .6 4 1 .6 0 5 .0 3 1 .2 8 4 .2 1 1 .4 0 4 .6 7 1 .8 0 D ep en d en cy ra ti o 0 .6 1 0 .6 7 0 .5 8 0 .5 6 0 .6 3 0 .7 9 0 .6 0 0 .6 4 0 .6 0 0 .7 2 N u m b er o f m al e w o rk in g m em b er s 1 .2 5 0 .6 9 1 .3 8 0 .7 1 1 .5 0 0 .7 7 1 .1 0 0 .5 2 1 .2 4 0 .6 6 G en d er o f h o u se h o ld h ea d 0 .7 7 0 .4 8 0 .7 5 0 .4 3 0 .7 6 0 .4 3 0 .7 7 0 .4 2 0 .9 0 0 .3 0 A g e o f h o u se h o ld h ea d 5 1 .2 1 1 3 .2 4 5 1 .5 4 1 3 .2 4 5 2 .9 4 1 2 .5 6 4 7 .4 4 1 0 .6 5 5 1 .4 5 1 1 .3 6 A g e o f w o rk in g m em b er s 4 0 .4 6 8 .2 5 3 9 .2 1 6 .2 5 3 7 .2 5 5 .8 2 4 0 .7 0 7 .5 0 4 2 .9 7 8 .8 0 E d u ca ti o n o f w o rk in g m em b er s 8 .3 7 2 .9 0 7 .7 0 2 .1 7 1 1 .0 5 2 .2 4 8 .0 7 2 .8 4 6 .9 8 2 .3 6 N a tu ra l ca p it a l F ar m la n d p er ad u lt 3 .3 7 2 .7 0 2 .4 8 1 .8 0 3 .1 6 2 .7 1 3 .0 1 2 .1 0 5 .1 1 3 .3 0 R es id en ti al la n d si ze 2 1 .8 8 1 4 .6 2 2 0 .8 8 1 3 .6 4 2 6 .1 8 1 8 .2 7 1 9 .5 3 1 3 .6 5 2 2 .3 2 1 2 .8 8 H o u se lo ca ti o n 0 .3 2 0 .4 7 0 .1 5 0 .3 6 0 .1 9 0 .3 9 0 .6 3 0 .4 8 0 .2 5 0 .4 3 P h ys ic a l ca p it a l 8 .6 3 1 .1 7 8 .0 4 1 .2 6 8 .8 4 0 .8 0 9 .0 6 1 .0 7 8 .8 0 1 .0 0 S o ci a l ca p it a l 3 .4 3 2 .0 9 2 .9 5 1 .7 5 5 .4 3 2 .4 3 2 .8 8 1 .7 3 3 .0 4 1 .4 2 F in a n ci a l ca p it a l F o rm al cr ed it 0 .2 7 0 .4 4 0 .2 8 0 .4 5 0 .1 5 0 .3 6 0 .3 6 0 .4 8 0 .2 5 0 .4 4 In fo rm al cr ed it 0 .1 9 0 .3 9 0 .1 9 0 .3 9 0 .1 5 0 .3 6 0 .1 8 0 .3 8 0 .2 4 0 .4 3 P a st li ve li h o o d ch o ic e In fo rm al w ag e w o rk 0 .2 2 0 .4 2 0 .6 4 0 .4 8 0 .1 3 0 .3 4 0 .0 6 0 .2 4 0 .0 6 0 .2 5 F o rm al w ag e w o rk 0 .1 8 0 .3 8 0 .0 3 0 .1 8 0 .7 3 0 .4 4 0 .0 1 0 .1 0 0 .0 7 0 .2 5 N o n fa rm se lf -e m p lo y m en t 0 .1 9 0 .3 9 0 .0 1 0 .1 0 0 .0 1 0 .1 0 0 .6 1 0 .4 9 0 .0 0 5 0 .0 7 T o ta l 4 7 7 1 2 5 1 0 0 1 2 8 1 0 3 N o te s: M ea n s (M ) an d st an d ar d d ev ia ti o n s (S D ) ar e ad ju st ed fo r sa m p li n g w ei g h ts . T h e av er ag es fo r d u m m y v ar ia b le s in al l st ra te g ie s as w el l as th e w h o le sa m p le se rv e as p er ce n ta g es ; fo r ex am p le in li v el ih o o d A , a m ea n o f 0 .7 5 fo r th e v ar ia b le ‘G en d er o f h o u se h o ld h ea d ’ m ea n s th at 7 5 % o f th e h o u se h o ld s in th is ca te g o ry ar e m al e h ea d ed an d o n ly 2 5 % ar e fe m al e h ea d ed . Journal of the Asia Pacific Economy 11 D ow nl oa de d by [T &F In ter na l U se rs] , [ Ca ro lyn H ay ne s] at 03 :52 24 A pr il 2 01 4 following livelihood D were endowed with higher than average farmland per adult but their working members were less well educated and older than those in other labour income-based livelihoods. Finally, these households had a quite low level of income and expenditure, just slightly higher than those in livelihood A. Livelihood E was a small group of households that were dependent mainly or entirely on nonlabour income for their living. These households had a very small size and high dependency ratio, consisting mainly of very old members with a very low education level. The income and expenditure per adult equivalent in this group were quite high. Most of them were land-losing elderly farmers, living separately from their children with income derived mainly from remittances and interest earnings. Even though the number of house- holds in this livelihood group almost doubled after farmland acquisition, it accounted for just around 4% of the total sample. These households were excluded from the economet- ric analysis because of their small number. Such exclusion, nevertheless, is a limitation since changes in this group may reveal some important policy recommendations. Hence, some discussion on this issue will be made in the conclusion section. 5.2. Determinants of livelihood strategies Table 4 reports the estimation results from the MNLM. The results show that many explanatory variables are statistically significant at the 10% or lower level. 5.2.1. Farmland loss Farmland loss in both years was hypothesized to positively affect the likelihood of house- holds following strategies based on wage employment or nonfarm self-employment. However, only the farmland loss in 2008 is positively associated with the choice of the nonfarm-based strategies. Households that lost their farmland in 2008 may have had more time to respond to the shock of losing land than those with farmland loss in 2009 and therefore they had a higher chance of taking up an alternative livelihood based on nonfarm activities. As mentioned in Nkonya et al. (2004), changes in livelihood strategies usually require time and investment, such as time for learning new skills and attempts at developing market connections. The results reveal some typical patterns of livelihood choices under the impact of farmland loss. A first pattern shows that households with more farmland loss in 2008 are much more likely to purse a strategy based on manual labour jobs. Under the impact of farmland loss, the most common livelihood choice is informal wage work. This is in line with the previous finding in a case study of Hanoi’s peri-urban village by Do (2006), who found that the majority of land-losing households engaged in informal wage work soon after losing land. On the one hand, this is indicative of high availability of informal wage work in Hanoi’s urban and peri-urban areas. On the other hand, for a number of land- losing households, the easy switch-over from farming to informal wage work reflects a very low entry barrier to the paid jobs in the informal sector. According to Cling et al. (2010), the informal sector in Hanoi offers the main job opportunities for most unskilled workers. Such job opportunities are also often found in Hanoi’s rural and peri-urban areas (Cling, Razafindrakoto, and Roubaud 2011). A second pattern of activity choice is an income-earning strategy that is dependent on self-employment in nonfarm activities. The probability of pursuing this strategy increases with the farmland loss level in 2008. Unlike informal wage work, nonfarm self- employment may require more capital, managerial skills and other conditions. 12 T.Q. Tuyen et al. D ow nl oa de d by [T &F In ter na l U se rs] , [ Ca ro lyn H ay ne s] at 03 :52 24 A pr il 2 01 4 T ab le 4 . M u lt in o m ia l lo g it es ti m at io n w it h re la ti v e ri sk ra ti o fo r h o u se h o ld s’ li v el ih o o d st ra te g y ch o ic es . In fo rm al w ag e w o rk v s. fa rm w o rk F o rm al w ag e w o rk v s. fa rm w o rk N o n fa rm fa rm se lf -e m p lo y m en t v s. fa rm w o rk E x p la n at o ry v ar ia b le s R R R s S E R R R s S E R R R s S E F a rm la n d lo ss L an d lo ss 2 0 0 9 6 .9 8 (1 1 .1 4 2 ) 4 .1 2 (6 .2 6 6 ) 3 .4 9 (4 .9 3 5 ) L an d lo ss 2 0 0 8 1 4 7 .5 8   (2 0 3 .8 7 6 ) 1 9 .5 5  (2 7 .4 1 5 ) 1 6 .1 6  (2 1 .9 8 1 ) H u m a n ca p it a l H o u se h o ld si ze 0 .6 9  (0 .1 0 1 ) 0 .7 7 (0 .1 2 4 ) 0 .7 3  (0 .1 2 8 ) D ep en d en cy ra ti o 1 .0 5 (0 .3 4 8 ) 0 .8 9 (0 .4 2 0 ) 1 .2 5 (0 .4 2 1 ) N u m b er o f m al e w o rk in g m em b er s 2 .2 0  (0 .7 8 7 ) 1 .7 4 (0 .7 2 5 ) 0 .8 5 (0 .2 9 6 ) G en d er o f h o u se h o ld h ea d 0 .5 3 (0 .4 0 7 ) 0 .3 6 (0 .3 0 1 ) 0 .3 4 (0 .2 2 4 ) A g e o f h o u se h o ld h ea d 1 .0 2 (0 .0 2 6 ) 1 .0 3 (0 .0 2 8 ) 0 .9 9 (0 .0 2 5 ) A g e o f w o rk in g m em b er s 0 .9 1  (0 .0 3 5 ) 0 .9 3  (0 .0 3 4 ) 0 .9 7 (0 .0 3 5 ) E d u ca ti o n o f w o rk in g m em b er s 0 .9 7 (0 .1 0 0 ) 1 .3 6   (0 .1 3 9 ) 1 .1 2 (0 .1 1 3 ) N a tu ra l ca p it a l F ar m la n d p er ad u lt 0 .7 9  (0 .0 9 9 ) 0 .7 8  (0 .0 8 1 ) 0 .7 4  (0 .1 1 5 ) R es id en ti al la n d si ze 1 .0 0 (0 .0 1 4 ) 1 .0 3 (0 .0 1 9 ) 1 .0 1 (0 .0 1 8 ) L o ca ti o n o f h o u se 0 .2 8  (0 .1 6 7 ) 0 .9 7 (0 .5 5 6 ) 2 .9 2  (1 .4 5 4 ) P a st li ve li h o o d st ra te g ie s In fo rm al w ag e w o rk 3 2 .4 2   (2 7 .4 4 0 ) 1 8 .7 1   (1 6 .6 6 8 ) 1 .6 7 (1 .2 9 7 ) F o rm al w ag e w o rk 1 .5 5 (1 .7 0 9 ) 5 3 .5 8   (4 5 .3 8 2 ) 0 .4 4 (0 .4 6 4 ) N o n fa rm se lf -e m p lo y m en t 9 .5 5  (1 2 .2 5 4 ) 1 5 .8 5  (2 2 .1 7 8 ) 3 6 0 .3 8   (3 2 9 .7 5 5 ) C o m m u n e d u m m ie s (i n cl u d ed ) In te rc ep t 1 3 1 .5 4  (3 1 1 .2 0 6 ) 0 .5 4 (1 .4 1 2 ) 2 1 .1 3 (4 7 .1 6 0 ) W al d x 2 3 5 5 .9 3 P ro b > x 2 0 .0 0 0 0 P se u d o R 2 0 .5 6 9 5 O b se rv at io n s 4 5 1 N o te s: R R R s – re la ti v e ri sk ra ti o s.  ,  ,   m ea n st at is ti ca ll y si g n ifi ca n t at 1 0 % , 5 % an d 1 % , re sp ec ti v el y . E st im at es ar e ad ju st ed fo r sa m p li n g w ei g h ts an d ro b u st st an d ar d er ro rs (S E ) in p ar en th es es . Journal of the Asia Pacific Economy 13 D ow nl oa de d by [T &F In ter na l U se rs] , [ Ca ro lyn H ay ne s] at 03 :52 24 A pr il 2 01 4 Consequently, for land-losing households, their probability of choosing this strategy is lower as compared to that of pursuing the informal wage work-based strategy, with the corresponding relative risk ratios being 1.32 and 1.65, given a 10 percentage point increase in land loss in 2008. Hence, this may imply that land-losing households face a relatively high entry for this strategy. With respect to the third pattern of livelihood choice, households with more farmland loss in 2008 are more likely to undertake a strategy based on formal wage work. How- ever, the probability of adopting this strategy is less than that of pursuing the informal wage work-based strategy. This phenomenon may stem from a few main reasons. First, the farmland has been largely converted for the projects of construction of highways, urban areas and housing development rather than industrial zones and factories, which may generate few jobs for local people. Second, it normally takes investors a few years or longer to complete the construction of an industrial zone, a factory or an office. Hence, local people may only be recruited after the completion of construction, which suggests that the impacts of farmland acquisition on local labour may be insignificant in the short term but more significant in the long term. In general, the result indicates that the more farmland per adult a household owns the less likely it is to engage in wage work or nonfarm self-employment as its livelihood strat- egy. This result is in accordance with the previous findings in rural Vietnam by Van de Walle and Cratty (2004) and in some Asian countries by Winters et al. (2009). While the size of residential land is not related to activity choice; the prime location of a house or a plot of residential land is positively associated with the probability of a household pursu- ing the nonfarm self-employment-based strategy. Households that own a house (or a plot of residential land) with a prime location are more likely to take up household businesses such as opening a shop or a workshop. This implies that many households have actively seized emerging market opportunities in a rapidly urbanizing area. Such a similar trend was also observed in a peri-urban village of Hanoi by Nguyen (2009b) and in some urban- izing communes in Hung Yen, a neighbouring province of Hanoi by Nguyen, Vu, and Philippe (2011) where houses or residential land plots with a prime location were used as business premises for opening shops, restaurants, bars, coffee shops or for rent. Regarding the role of human capital in activity choice, the result reveals that, all else being equal, households with older working members are less likely to undertake paid jobs as the main income-generating strategy, which implies that some potential barriers had prevented elderly farmers from taking up these jobs. Better education of working members increases the probability of households pursuing a strategy based on formal wage work, meaning that households with low education levels will be hindered from adopting this strategy. Nonetheless, human capital is found not to be related to nonfarm self-employment and informal wage work, suggesting that in terms of formal education, there has been relative ease of entry into these activities. 5.3. Determinants of livelihood outcomes 5.3.1. Livelihood strategy Table 5 reports the estimation results from the IV regression of the expenditure and income models using 2SLS estimation. Both sets of results confirm that household well- being is greatly affected by the choice of livelihood strategy. In general, households that follow nonfarm-based livelihoods have higher well-being than those pursuing a farm work-based strategy. Such well-being disparities across various livelihood strategies 14 T.Q. Tuyen et al. D ow nl oa de d by [T &F In ter na l U se rs] , [ Ca ro lyn H ay ne s] at 03 :52 24 A pr il 2 01 4 imply that the livelihood choice is a crucial factor affecting household livelihood out- comes. Also, it suggests that moving out of agriculture may be a way to improve house- hold welfare. The result is partly consistent with previous findings in rural Vietnam. For instance, Van de Walle and Cratty (2004) found that households that farm only are poorer than all those who combine farming with some type of nonfarm employment. Moreover, as estimated in Pham, Bui, and Dao (2010), on average and ceteris paribus, the shift of a household from pure agriculture to pure non-agriculture raises expenditure per capita, and this outcome tends to steadily increase over time. Table 5. Determinants of household livelihood outcomes (livelihood outcomes: monthly income and consumption expenditure per adult equivalent in natural logarithms). Income (IV regression) Expenditure (IV regression) Explanatory variables Coef. SE Coef. SE Livelihood strategy Informal wage work 0.2796 (0.126) 0.3709 (0.102) Formal wage work 0.5087 (0.133) 0.4544 (0.105) Nonfarm self-employment 0.3210 (0.115) 0.3594 (0.081) Farmland loss Land loss 2009 0.1350 (0.086) 0.1795 (0.073) Land loss 2008 0.0632 (0.095) 0.0083 (0.062) Human capital Household size 0.1147 (0.016) 0.0203 (0.012) Dependency ratio 0.0254 (0.037) 0.0441 (0.032) Number of male working members 0.0578 (0.030) 0.0043 (0.027) Gender of household head 0.0301 (0.051) 0.0706 (0.037) Age of household head 0.0007 (0.002) 0.0005 (0.001) Education of working members 0.0365 (0.011) 0.0167 (0.008) Natural capital Farmland per adult 0.0408 (0.010) 0.0318 (0.008) Residential land size 0.0003 (0.001) 0.0003 (0.001) Physical capital Values of productive assets per working members in Ln 0.1184 (0.021) 0.1042 (0.016) Social capital Number of group memberships 0.0058 (0.012) 0.0032 (0.009) Financial capital Formal credit 0.1042 (0.049) 0.0623 (0.034) Informal credit 0.0699 (0.050) 0.0087 (0.034) Commune dummies (included) Intercept 5.8068 (0.248) 5.5723 (0.193) Centred R2 0.4628 0.3402 Uncentred R2 0.9978 0.9988 Observations 451 451 Notes: Coefficients and standard errors (SE) are adjusted for sampling weights. , , mean statistically signif- icant at 10%, 5 % and 1%, respectively. Journal of the Asia Pacific Economy 15 D ow nl oa de d by [T &F In ter na l U se rs] , [ Ca ro lyn H ay ne s] at 03 :52 24 A pr il 2 01 4 5.3.2. Farmland loss Farmland loss in 2009 is positively associated with expenditure. Nevertheless, a similar impact is not statistically significant for the case of farmland loss in 2008. This may be because households with land loss in 2009 partly used their compensation money for household expenses while those with land loss in 2008 might have used up their compen- sation money in 2008. As shown by the survey, 61% of land-losing households reported using part of their compensation money for daily expenses. For some households, the compensation money for farmland loss might be used to deal with the shock of farmland loss while other households might use this for additional expenditure to improve their well-being. A surprising result was that farmland loss in both years has no impact on income. Possibly, this implies that only a small amount of income that was contributed by agri- cultural production was lost due to the area of acquired farmland.11 However, it should be noted that there is also an indirectly positive effect of farmland loss on household welfare (through its positive effect on the choice of nonfarm-based strategies). As pre- viously discussed, a higher level of land loss in 2008 increases the likelihood of house- holds adopting nonfarm-based strategies, which are much more lucrative than a farm work-based strategy. Although only the land loss in 2009 has a positive impact on the choice of nonfarm-based livelihood strategies, the land loss in both years (2008 and 2009) has a positive effect on various nonfarm income shares (Tuyen and Huong 2013). This suggests that some household members might have moved out of farming to do some nonfarm jobs in order to supplement their income with nonfarm income. As a consequence, households might have derived more income from nonfarm jobs, which might have offset or even exceeded the amount of farm income lost by farmland loss.12 This explanation is also supported by the survey result findings obtained by Le (2007), who found that after losing land, households’ income from agriculture significantly declined but their income from various nonfarm sources considerably increased. In addition, Nguyen, Nguyen, and Ho (2013) found that households with higher levels of land loss have higher rates of job change and their income from new jobs is much higher as compared to that before losing land and that of those with lower levels of land loss. 5.3.3. Livelihood assets More owned farmland is linked with higher household well-being. However, farmland has an indirectly negative (via its negative impact on the choice of nonfarm-based strate- gies) impact on household welfare. The education of working members has a positive effect on household well-being. There is also an indirectly positive effect through the livelihood strategy because a higher education level increases the probability of a house- hold following a formal wage work-based strategy, which is closely linked with a higher income and expenditure level. There was statistical evidence for a positive association between access to formal credit and income and expenditure per adult equivalent. Similar evidence was not found in the case of informal credit. This phenomenon may be partly explained by the fact that the purpose of informal loans was mainly for nonproduction rather than production, which might generate little or no economic return.13 This explana- tion is partly in accordance with that of Pham and Izumida (2002) who found that in rural Vietnam, one of the purposes of borrowing informal loans was consumption (mainly for smoothing consumption at critical times). Finally, the ‘capital–labour ratio’ was 16 T.Q. Tuyen et al. D ow nl oa de d by [T &F In ter na l U se rs] , [ Ca ro lyn H ay ne s] at 03 :52 24 A pr il 2 01 4 positively associated with household well-being. The elasticity of income and expendi- ture per adult equivalent to higher values of ‘capital–labour ratio’ was around 0.12 and 0.10, respectively. 6. Conclusion and policy implications Given the loss of agricultural land due to urbanization and industrialization in Hanoi’s peri-urban areas, a number of land-losing households have actively adapted to the new context by pursuing nonfarm-based livelihood strategies as ways to mitigate their depen- dence on farmland. Among choices of activities, informal wage work appears to be the most popular livelihood choice. The availability of job opportunities in the informal sec- tor not only helps farm households mitigate negative consequences of land loss but also opens a new chance for them to change and diversify their livelihoods. However, as previ- ously discussed, farmland loss in 2009 is not associated with any choice of nonfarm-based livelihood strategies. Possibly, one year was not time enough for a number of land-losing households to switch to alternative livelihoods. Consequently, the short-term effect of farmland acquisition may be detrimental to land-losing households, especially to those whose main income was derived from farming. However, this study found no econometric evidence for negative effects of farmland loss on either expenditure or income per adult equivalent. For many land-losing house- holds whose living is based on farm work, their compensation money was used to cover daily household expenses, suggesting this financial resource enabled them to temporarily smooth consumption when facing income shortfalls caused by the loss of farmland. In addition, higher levels of farmland loss are closely associated with more participation in nonfarm activities. Some land-losing households might be ‘pushed’ into casual wage work or nonfarm self-employment in response to income shortfalls. For other land-losing households, they might be ‘pulled’ into nonfarm activities because of attractive income sources from these activities. Thus, an implication here is that having no farmland or farmland shortage should not be seen as an absolutely negative factor because it can improve household welfare by motivating households to participate in nonfarm activities. As previously discussed, changes in livelihood choice towards nonfarm activities may be a way to raise rural household welfare. Nevertheless, changes in livelihood strategies are determined by asset-related variables and other exogenous conditions. In particular, land (farmland and the location of houses or residential land plots), and education are cru- cial factors that are closely associated with more participation in nonfarm activities. As a result, state intervention in these factors can improve household well-being through pro- viding favourable conditions for livelihood transition and diversification. There are some policies that may help land-losing households to intensively engage in nonfarm activities. For instance, government policy can support the household livelihood transition by pro- viding land-losing households with a plot of land in a prime location for doing businesses. Encouraging parents’ investment in their children’s education is likely to give the next generation a better chance to get remunerative jobs. A better transportation and road sys- tem will result in a closer connection between land-losing communes and urban centres, which in turn generates more opportunities in nonfarm activities for local people. Although the current number of households whose living based on non-labour income sources accounted for a small proportion, this figure is projected to rapidly rise as a result of the massive agricultural conversion for urban expansion in the near future. This sug- gests that a large number of land-losing households will be forced to find alternative sour- ces of livelihoods. This, however, is not an easy task for elderly farmers. Fortunately, as Journal of the Asia Pacific Economy 17 D ow nl oa de d by [T &F In ter na l U se rs] , [ Ca ro lyn H ay ne s] at 03 :52 24 A pr il 2 01 4 mentioned in Section 3.2, households that lose more than 30% of their farmland will be compensated with a non-agricultural land parcel (đất dịch vụ) that can be used as a prem- ise for household businesses such as opening a shop, a workshop, or for rental accommo- dation. Accordingly, đất dịch vụ is a new source of livelihoods for land-losing households, particularly elderly family members, to switch from agricultural production to lucrative nonfarm activities in Hanoi’s peri-urban areas. In this sense, đất dịch vụ also plays a role as insurance for unemployed farmers and old-age landless farmers. However, this policy has been slowly implemented in the study district (Ha Noi moi 2010). There- fore, speeding up the implementation of this policy is likely to be one of the prerequisites to facilitate the livelihood transitions of land-losing households in Hanoi’s peri-urban areas. Such a compensation policy has been piloted in Vinh Phuc Province since 2004 where land-loss households utilized đất dịch vụ to open a shop or provide accommodation leases for workers in industrial zones (the Asian Development Bank (ADB) 2007). As noted by ADB (2007), this initially successful experience, therefore, should be worth con- sidering by other localities. The above discussion implies that the rising conversion of farmland for urbanization and industrialization, coupled with the compensation with land as mentioned above, can be seen as a positive factor that enables land-losing households to change their livelihoods and improve their welfare. Funding We thank the Vietnamese Government [Decision No. 3470/QĐ-BGĐT] and University of Waikato [Internal Study Award 1093637], New Zealand, for funding this research. Notes 1. According to the current Land Law of Vietnam, the compulsory acquisition of land by the State is applied to projects that are served for national or public projects, for projects with 100% contributed by foreign funds (including FDI (foreign direct investment) and ODA (offi- cial development assistance)) for the implementation of projects with special economic invest- ment such as building infrastructure for industrial and services zones, hi-tech parks, urban and residential areas (WB 2011). 2. According to the surveyed data, about 60% of land-losing households used the compensation for daily living expenses, and about a quarter of them purchased furniture and appliances, while a similar proportion of land-losing households spent this money in repairing or building houses. By contrast, only 4% among them used this resource for investing in non-farm production. 3. The prices of đất dịch vụ in some communes of Hoai Duc District ranged from 17,000,000 VND to 35,000,000 VND (Vietnam Dong) per m2 in 2011, depending on the location of đất dịch vụ (Minh Tuan 2011) (1 USD equated to about 20,000 VND in 2011). Note that farmers have already received the certificates, which confirm that đất dịch vụ will be granted to them but they have not yet received đất dịch vụ. However, these certificates have been widely pur- chased (Thuy Duong 2011). 4. More details for sampling frame, questionnaire and study site, see Tuyen (2013). 5. A prime location is defined as: the location of a house or of a plot of residential land that is sit- uated on the main roads of a village or at the crossroads or very close to local markets or to industrial zones, and to a highway or new urban areas. Such locations enable households to use their houses or residential land plots for opening a shop, a workshop or for renting. 6. According to Wooldridge (2013), an exogenous event is often a change in the State’s policy that affects the environment in which individuals and households operate. 7. The proportion of farmland acquired by the State is calculated by dividing the area of acquired farmland of households by their owned farmland before losing land. 18 T.Q. Tuyen et al. D ow nl oa de d by [T &F In ter na l U se rs] , [ Ca ro lyn H ay ne s] at 03 :52 24 A pr il 2 01 4 8. The correlation coefficient between the amount of compensation in 2008 and the level of land loss in 2008 is 0.86. The corresponding figure for the case of compensation in 2009 and the level of land loss in 2009 is 0.89. 9. Following Haughton and Haughton (2011), income and consumption expenditure per adult equiv- alent were calculated using the OECD equivalent scale (given by 1 þ 0.7 (Na  1) þ 0.5 Nc), where Na is the number of adults and Nc the number of children in a household. This formula assigns a value of 1 for the first adult (aged 15 and older), of 0.7 for each additional adult and of 0.5 for each child (less than 15 years old). 10. Productive assets include all production tools and equipment (e.g., tractor ploughs, rice mill- ing machines, threshing machines), livestock (e.g., bulls, buffaloes and breeding pigs), trans- port means (e.g., trucks, motorcycles, bicycles and trailers) and other production facilities (e.g., stores and workshops) (see more in Tuyen [2013], p. 173). The values of productive assets were estimated at the current values at the time of the interview by the surveyed households. 11. According to the survey data, on average, annual crop income per one sao (360 m2) was esti- mated at around 3.7 million VND ( 1 USD equated to about 18,000 VND in 2009). The corre- sponding figures for income from rice cultivation were extremely low, just around 1.5 million VND. 12. As reported by surveyed households, on average a manual labourer earned about 2.1 million VND per month. Accordingly, suppose one family member moves out of farming activities to engage as a wage earner in the informal sector in six months, he or she would earn 12.6 million VND – a greater amount than the annual crop income from three sao of agricultural land. 13. According to the survey, 46% of households said that one of the purposes of borrowing infor- mal loans was for consumption; around 30% reported that one of the informal loan’s purposes was for building or repairing houses and about 42% answered that one of the informal loan’s purposes was for production. Conversely, about 55% of surveyed households reported that one of their formal loans’ purposes was for production, and only around 10% and 8% among them said that one of the purposes of borrowing formal loans was for consumption and build- ing or repairing their houses, respectively. Notes on contributors Dr Tran Quang Tuyen is a lecturer in economics at VNU University of Economics and Business, Vietnam National University, Hanoi. His research interests cover land, rural livelihoods, poverty, inequality and household welfare. His papers have been accepted for publication in international journals. Besides, he has several publications in national journals. Dr Steven Lim teaches economics at the Waikato Management School, New Zealand, and Senshu University, Tokyo. His research interests in business economics include the relationship between HIV/AIDS and poverty, the social and community health impacts of trade liberalization, the eco- nomics of landmine clearing and economic growth and the environment. Dr Michael P. Cameron is a senior lecturer in economics at University of Waikato, and a research fellow in the National Institute of Demographic and Economic Analysis (NIDEA). His current research interests include population, health and development issues, population modelling and sto- chastic modelling, financial literacy and economics education. Vu Van Huong is a lecturer in economics and econometrics at Academy of Finance, Vietnam and currently is a PhD candidate at University of Waikato, New Zealand. His research interests include international economics, development economics and applied econometrics. 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