Volume 30, Issue 1. Crop Diversification to Mitigate Flood Vulnerability in Bangladesh: An Economic Approach

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1 Volume 30, Issue 1 Crop Dversfcaton to Mtgate Flood Vulnerablty n Bangladesh: An Economc Approach Md. Israt Rayhan Insttute of Statstcal Research and Tranng (ISRT) Ulrke Grote Insttute for Envronmental Economcs and World Trade Abstract It s hypotheszed that more vulnerable farmng households are more lkely to choose tradtonal crop varetes over rsker but more proftable new ones. The analyss s based on a cross sectonal survey of 1050 rural households, beng conducted just two weeks after monsoon and flash floods had occurred n four dstrcts of Bangladesh n After estmatng vulnerablty based on the expected poverty method, results show that 58 percent of the rural flooded households are estmated to be poor whle 67 percent are estmated to be vulnerable. The monsoon flood causes more damage to cash crops whereas flash flood s rsker for staple crops. Ths study suggests a mxed croppng system n rural Bangladesh to mnmze households' vulnerablty to floods. Ths paper s an orgnal work form our research and t has not been submtted elsewhere for publcaton. Ctaton: Md. Israt Rayhan and Ulrke Grote, (2010) ''Crop Dversfcaton to Mtgate Flood Vulnerablty n Bangladesh: An Economc Approach'', Economcs Bulletn, Vol. 30 no.1 pp Submtted: Apr Publshed: February 18, 2010.

2 Generated by Foxt PDF Creator Foxt Software For evaluaton only. 1. Introducton Bangladesh conssts mostly of a low-lyng rver delta wth over 230 rvers and trbutares, stuated between the foothlls of the Hmalayas and the Bay of Bengal. The combnaton of ts geography, populaton densty, and extreme poverty makes Bangladesh very vulnerable to rsks and dsasters lke floods, cyclones etc. In 1998, over 68 percent of the country were nundated by floods (Nnno et al. 2001), about 2,400 people ded, and 2.2 mllon tons of crops were damaged (Dsaster Management Bureau, 2005). In the year 2004, close to 36 mllon people were affected, 726 ded, and 1.7 mllon acres of crop area were damaged (Dsaster Management Bureau, 2005). In the lterature (Dercon and Krshnan 2000, Glewwe and Hall 1998, Amn et al. 1999), vulnerablty s defned as the ablty to smooth consumpton n response to shocks, measured by observed changes n consumpton over tme. Households reduce ther exposure to rsks and smooth ther ncome ex ante, as ther capacty to smooth consumpton ex post s often lmted (Barrett et al. 2001). Dversfcaton s known to reduce the dsperson of the overall return by selectng a mxture of actvtes that have net returns wth negatve correlatons (Alderman and Paxson 1992; Reardon et al. 2000). Sometmes crop rotaton plans maxmze expected return (Hardarker et al. 2004). In the year 2005, Bangladesh was affected by two types of floods. A monsoon flood occurred durng md August to September n the eastern and western parts of the country and a flash flood occurred n the northern areas durng November. A three stage stratfed random samplng technque was appled to the survey aftermath of floods. The analyss s based on a cross sectonal survey of 1050 rural households, beng conducted just two weeks after monsoon and flash floods had occurred n four dstrcts of Bangladesh n The four selected dstrcts whch were chosen randomly accordng to the flood proneness and damage are Jamalpur, Shrajganj, Sunamganj and Nlphamar. The frst three were affected by a monsoon flood, whle the latter was ht by a flash flood. 2. Methodology In order to estmate the vulnerablty of flooded households, the vulnerablty to expected poverty (VEP) approach by Chaudhur et al. (2002) s appled. They defne a household as vulnerable f t s expected to be poor n the near future. Ths methodology s also descrbed and used n other studes (Chrstaensen et al. 2000, Chaudhur 2003). Accordng to the VEP, the vulnerablty level of a household at tme t s defned as the probablty that the household wll be n ncome poverty at tme t 1: vt Pr( y, t 1 z).....(1) Where, y, t 1 s the household s per capta ncome level (welfare ndcator) at tme t 1 and z s the ncome poverty lne. The assumptons for the stochastc process, generatng the ncome of a household : ln y e.(2) Where, y represents the per capta ncome before flood, and s a set of observable household characterstcs, such as: - demographc factors: famly sze, dependency rato (rato of the number of household members of 0-14 years and over 60 years to the number of members of years), number of male and female members above 18 1

3 Generated by Foxt PDF Creator Foxt Software For evaluaton only. years, age and age squared of household head, mean educatonal years of ncome earners, gender of household head and major source of ncome; and - economc factors: per capta cultvable land, per capta asset value (anmals, poultry, trees, household tems: char, table, rado, televson, cycle, ornaments, utensls for cultvaton: tractor, shallow machne, rrgaton pump, tube well etc.), dstance and cost to reach nearest market place, access of meda and ownershp of a dwellng place. Household are asked about the current market prce of land and assets. An assumpton s made on the functonal form of the varance of e (and hence of ln y ), that s, the varance of e depends on the observable household characterstcs n the 2 followng parametrc way: e,.(3) The estmaton of the parameters and can be carred out by the three-step Feasble Generalzed Least Squares (FGLS) procedure suggested by Amemya (1977). In FGLS 2 estmaton the unknown matrx e, s replaced by a consstent estmator. The steps are descrbed as follows: Frst, the estmaton procedure apples the OLS method to equaton (2) and estmates the resdual. Then, the estmated resdual s squared to estmate the followng equaton: 2 eols,..(4) 2 e For flooded households, OLS, s regressed on demographc and economc factors, as well as copng factors (such as: per capta loan for flood, wthdrawal of savngs for flood, membershp of the cooperaton), shock factors (such as: flood heght and duraton, loss of workng days, loss of asset value, loss of crop value), and communty characterstcs (such as: avalablty of electrcty, flood shelter, publc hosptal, prmary school). Second, the estmate OLS s used to transform the equaton (4) as follows: 2 e OLS,...(5) OLS OLS OLS It s also feasble to get a consstent estmate, 2 FGLS, of e,, the varance of the shock factor of household ncome. The standard devaton can be evaluated as follows: ˆ e, FGLS..(6) Thrd, to estmate, equaton (2) s transformed as follows: ln y e..(7) ˆ ˆ ˆ e, e, e, An OLS estmaton of equaton (7) yelds a consstent and asymptotcally effcent estmate βˆ of the parameter. Therefore, usng the FGLS estmates of and, the FGLS 2

4 Generated by Foxt PDF Creator Foxt Software For evaluaton only. methodology fnally estmates the expected value and varance of log per capta ncome as follows: Therefore, usng the FGLS estmates of and, the methodology fnally estmates the expected value and varance of log per capta ncome as follows: ln y ˆ FGLS 2 ˆ and FGLS E Var ln y e, (8) Lettng (.) denote the cumulatve densty of the standard normal dstrbuton, the estmated probablty can be expressed as follows: vˆ = Prln y ln z ln z ln y ln z ˆ Var ln y = (9) The value of vˆ vares from 0 to 1. The estmate vˆ thus denotes the vulnerablty of the th household wth the characterstcs. The vulnerablty threshold s assumed to be The poverty lne used n ths study s BDT per person per month whch s equvalent to about US$ 8.5. Ths s the lne obtaned by the Household Income and Expendture Survey (HIES) of Bangladesh, Econometrc Results Applyng the VEP approach, the followng vulnerablty estmates are obtaned (table I). They are compared wth actual poverty levels before and after the flood exstng n the surveyed dstrcts. Table I: Vulnerablty estmates by the VEP approach (n %) Sample Dstrcts Poverty before flood Vulnerablty Overall Idosyncratc Covarate Flooded Total Jamalpur Nlphamar Note: Vulnerablty threshold pont s 0.5. Source: Own complaton from survey data For the flooded households, the vulnerablty was estmated to 67 percent whch s 9 percent hgher than the before flood poverty level, about 58 percent. Households from the Nlphamar dstrct, who faced the flash flood n the year 2005, have the hghest poverty and vulnerablty rates. Idosyncratc rsks affect only households or ndvduals lke n the case of a death of a household member, and covarate rsk affects a group of households or the whole communty. Households facng a monsoon flood have been found to be on average more vulnerable to dosyncratc shocks. Ths study also examnes vulnerabltes accordng to dfferent ncome sources. The followng table II shows the ncome sources, poverty levels and vulnerablty estmates for the surveyed households. It s found that farmers are the most vulnerable to flood shocks, followed by day laborers. 1 BDT means Bangladesh Taka or currency 3

5 Generated by Foxt PDF Creator Foxt Software For evaluaton only. Table II: Major sources of ncome and vulnerablty by the VEP approach (n %) Major source of ncome Flooded Poverty Poverty Change n Vulnerablty before flood after flood poverty (1) (2) (2) - (1) Agrculture Servce Busness Day labor Dary and Poultry Remttance Boatman and Fsherman Source: Own complaton from survey data Percentages of farmers for Srajganj, Jamalpur, Sunamganj and Nlphamar dstrcts are 6.5, 63.3, 4.1 and 43.9, respectvely. Hence, only farmers from the Jamalpur and Nlphamar dstrct are consdered for econometrc analyses due to larger sample szes. In the Jamalpur dstrct, 53 percent of the farmers reported to produce jute (cash crop) as major crop and 42 percent produce paddy rce (staple crop) as major crop. The major crop s defned by the response of the surveyed households n terms of the amount of land, labor allocatons and nput costs devoted to a certan crop. The households were asked to ndcate ther expected (normal) yelds of jute and paddy rce producton wthout any adverse effects of floods. These expected yelds were subtracted from ther actual crop yelds after the flood n The total yeld loss of the cash crop (jute) was hgher n proporton (86%) than that of the staple crop. The proporton of yeld damage n the staple crop (paddy rce) was reported to 54 percent. The farmng households n the Jamalpur dstrct, who reported paddy rce to be ther major crop, manly produce Aus paddy whch s a specal type of rce from Bangladesh. However, jute producers (Whte and Tossa) also affected by the nundaton of flood, snce jute s harvested durng July to September. Table III shows the socoeconomc and vulnerablty dfferentals of the Jamalpur farmers dstngushng between those who produce jute and those who produce paddy rce as ther major crops. Table III: Vulnerablty dfferentals for dfferent crop producers n Jamalpur Crop Yeld loss due to flood n klo per Value (yeld x market prce) loss due to flood n Taka Asset value n Taka Land holdng n acre Poverty before flood (%) Vulnerablty (%) Vulnerablty to Poverty rato household (1) (2) (3) (4) (5) (6) (6) Jute (cash) Paddy (staple) Note: Column 1, 2, 3 and 4 represent the mean values; Vulnerablty s measured by Chaudhur et al. 2002; number of households for jute = 39 and for paddy = 50; Source: Own complaton from survey data The vulnerablty estmates nclude the before flood per capta ncome as dependent varable; household member, dependency rato, age and gender of household head, 4

6 Generated by Foxt PDF Creator Foxt Software For evaluaton only. educatonal year of hghest educated member, ownershp of dwellng place, per capta asset value, and per capta arable landholdng are ncluded as ndependent varables. The addtonal varables, yeld and value (yeld x market prce) loss n crops are ncluded for estmatng the error term (to catch the nter-temporal ncome varablty). From the above table III, t s depcted that on the one hand, households wth larger assets and more arable land area, go for more proftable but rsker cash crop producton (value per klo jute s Taka, whereas value of per klo paddy s Taka). But n case of flood nundaton, cash crop s much more vulnerable n terms of average value loss n nomnal value terms, though the average yeld loss for jute s even 40 percent lower than that for paddy rce. On the other hand, the poorer farmers tend to grow paddy rce whch s relatvely less proftable. Thus, the results support the hypothess that poorer households, n mperfect nsurance markets, prefer to cultvate tradtonal or staple crops over rsker cash crop lke jute or more proftable new varetes (Morduch 1994). The poverty rate s 2 percent hgher n paddy cultvatng households but the vulnerablty to poverty rato s lower than that of the cash crop producers. So, t could be better for jute producers to cultvate mxed crops (jute and paddy) nstead to mnmze ther vulnerablty or future rsk. The Nlphamar dstrct data show that 66 percent of the farmers cultvated paddy rce (staple) and 32 percent produce groundnuts (cash crop) as major crops. The yeld loss of the staple crop (paddy) was hgher n proporton (95 percent) than for the cash crop. The proporton of yeld damage n cash (groundnut) crop was reported to 84 percent. The Nlphamar dstrct was affected by flash flood (caused by unexpected ran and sudden overflow of rver basn) n early November and feld survey was conducted durng November 25 th to December 5 th. The average duraton of the flood was three days, and the average flood water heght was 0.78 feet n the homestead as reported by the affected households. Most of the farmers faced crop damage due to the flood. The farmers reported that they mostly ploughed the Aman paddy rce and that the flood nundaton occurred just before ther harvestng tme. Accordng to the farmers, Aman paddy and groundnut both share a smlar pattern of sowng and harvestng tmes. Thus, groundnut producers faced smlarly the dsastrous effect of the flood but less than the paddy producers, because of the heght of the paddy plants s bt hgher that the groundnuts. The vulnerablty and socoeconomc dfferentals of the two groups of farmers n the Nlphamar dstrct are shown n the followng table IV. Table IV: Vulnerablty dfferentals for dfferent crop producers n Nlphamar Crop Yeld loss due to flood n klo per household Value (yeld x market prce) loss due to flood n Taka Asset value n Taka land holdng n acre Poverty before flood (%) Vulnerablty (%) Vulnerablty to Poverty rato (1) (2) (3) (4) (5) (6) (6) Nut (cash) Paddy (staple) Note: Column 1, 2, 3 and 4 represent the mean values; Vulnerablty s measured by Chaudhur et al. 2002; number of households for nut = 21, and for paddy = 44; Source: Own complaton from survey data 5

7 Generated by Foxt PDF Creator Foxt Software For evaluaton only. In the Nlphamar dstrct, the pattern of crop loss n yeld and values for staple and cash crops are smlar to that of Jamalpur dstrct. The cash (groundnut) crop takes the hgher loss n values than the staple one but mean losses n yeld are lower. Households wth hgher asset values and more arable land prefer to cultvate groundnuts more than paddy because of the hgher market value. From the sample survey, the average value of per klo paddy s calculated as Taka and for groundnuts as Taka. The better-off households have the opton and ablty to spend more money on more proftable crops lke groundnuts. But opposed to the above mentoned jute producers, the nuts producers are found to be less vulnerable to flash flood nundaton. Comparatvely poorer households have generally fewer optons n terms of crop dversfcaton and they rather prefer to grow staple crops due to the low nput cost and to ensure ther own household s rce supply. However, staple crop producers are found to be more vulnerable to flash flood n the Nlphamar dstrct. It mght be concluded that poorer households may allocate a small share of ther land also to cash crop (e.g. groundnut) cultvaton, whch s lkely to be more proftable and less prone to losses for floods. 4. Concluson Flooded households have the hgh rsk of fallng below the poverty lne due to monsoon and flash floods. From two dfferent flooded dstrcts (Jamalpur and Nlphamar), econometrc results show that farmers who grow ether cash or staple crops may be vulnerable due to the downsde effects of monsoon or flash floods. Thus, ths study suggests a mxed croppng system n rural Bangladesh to mnmze households vulnerablty to floods as the rrgaton facltes are already exst n the arable lands of two sampled dstrcts. From the econometrc results, t s depcted that crop dversfcaton or mxed croppng systems have hgh potentals to reduce the flood rsk for the rural farmng households n Bangladesh. There are ample opportuntes to mtgate flood rsk, dsasters and aftermaths by crop dversfcaton whch can balance the producton of major crops wth that of mnor crops. In ths way, the agrcultursts recuperate the aftermath flood damage and reduce the vulnerablty to floods. References Alderman, H. and C.H. Paxson (1992) Do the Poor Insure? A Synthess of the Lterature on Rsk and Consumpton n Developng Countres World Bank Polcy Research Workng Paper Amemya, T. (1977) The Maxmum Lkelhood Estmator and The Non-lnear Three Stage Least Squares Estmator n The General Nonlnear Smultaneous Equaton Model Econometrca 45, Amn, S., A. S. Ra, and G. Topa (1999) Does mcrocredt reach the poor and vulnerable? Evdence from northern Bangladesh Center for Internatonal Development Workng Paper 28. Barrett, C.B., T. Reardon and P. Webb (2001) Nonfarm Income Dversfcaton and Household Lvelhood Strateges n Rural Afrca: Concepts, Dynamcs and Polcy Implcatons Food Polcy 26,

8 Generated by Foxt PDF Creator Foxt Software For evaluaton only. Chaudhur, S., J. Jalan and A. Suryahad (2002) Assessng Household Vulnerablty to Poverty from Cross-sectonal Data: A Methodology and Estmates from Indonesa Dscusson paper no , Department of Economcs, Columba Unversty, New York. Chaudhur, S. (2003) Assessng Vulnerablty to Poverty: concepts, emprcal methods, and llustratve examples (last access January 31, 2010) Chrstaensen, L. J., R. N. Bosvert and J. Hoddnott (2000) Valdatng Operatonal Food Insecurty Indcators aganst a Dynamc Benchmark: Evdence from Mal Polcy Research workng paper no. 2471, World Bank. Dercon, S. and P. Krshnan (2000) Vulnerablty, Seasonalty and Poverty n Ethopa Journal of Development Studes 36(6), Dsaster Management Bureau, Lbrary and Reports, Mohakhal, Bangladesh. Glewwe, P. and G. Hall (1998) Are some groups more vulnerable to macroeconomc shocks than others? Hypothess tests based on panel data from Peru Journal of Development Economcs 56(1), Gujarat, Damodar N. (2003) Basc Econometrcs, Fourth edton, McGraw-Hll: New York. Hardaker, J.B., R.B.M. Hurne, J.R. Anderson and G. Len (2004) Copng wth Rsk n Agrculture, second edton, CABI publshng: Oxfordshre. Household Income and Expendture Survey (HIES, 2005) Report of Bangladesh Bureau of Statstcs, Dhaka, Bangladesh. Morduch, J. (1994) Poverty and Vulnerablty The Amercan Economc Revew 84(2), Nnno, C.D., P.A. Dorosh, L.C. Smth and D.K. Roy (2001) The 1998 floods n Bangladesh: dsaster mpacts, household copng strateges, and response IFPRI Research Report 122. Reardon, T., J.E. Taylor, K. Stamouls, P. Lanjouw, A. Balsacan (2000) Effects of Nonfarm Employment on Rural Income Inequalty n Developng Countres: An Investment Perspectve Journal of Agrcultural Economcs 51(2), Rayhan, M.I. (2008) Assessng Household Vulnerablty and Copng Strateges to Floods: A Comparatve Study of Flooded and Non-flooded Areas n Bangladesh, 2005 Cuvller Verlag: Goettngen. 7