40795562.pdf

Role of Targeted Credit in Rural Non-farm GrowthAuthor(s): Shahidur R. KhandkerSource: The Bangladesh Development Studies, Vol. 24, No. 3/4, RURAL NON-FARMDEVELOPMENT IN BANGLADESH (Sept.-Dec. 1996), pp. 181-193Published by: Bangladesh Institute of Development StudiesStable URL: http://www.jstor.org/stable/40795562 .Accessed: 06/02/2015 00:47

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The Bangladesh Development Studies Vol. XXIV, Sept.-Dec. 1996. Nos. 3 & 4

Role of Targeted Credit in Rural Non-farm Growth by

Shahidur R. Khandker* In a labour surplus country like Bangladesh, rural non-farm (RNF) sector

is important not only for poverty alleviation but also for promoting overall economic growth. Lack of credit has proved to be a binding constraint to the growth of RNF activities. Microcredit from Grameen Bank, BRAC, and RD-12 programme of the BRDB has played a significant role in relaxing this constraint and promoting RNF activities in Bangladesh. Data from household level survey show that both household characteristics and community factors are important determinants of RNF participaion. Better infrastructure promotes RNF participation while better income earning opportunities in agriculture reduce it. Trade and manufacturing are the dominant forms of RNF activities in Bangladesh. Household attributes, village characteristics, and prices and wages have been found to explain a significant part of variations of the choice structure of the RNF activities. Analysis of borrower-level data clearly indicates that because of skill training and other organizational help, BRAC borrowers have managed to sustain increased productivity with improved access to credit. Therefore, the supply of affordable credit for the expansion of RNF production must be supported by appropriate skill development, market promotion, and other organizational supports.

I. BACKGROUND Bangladesh's labour force has been growing at 2.4 per cent per

year, but its agriculture and modern sectors can absorb an increase of only 1.7 per cent per year. The surplus labour attempts to find employment in the country's rural non-farm (RNF) sector which is becoming an increasingly significant source of income and employment for the majority of the rural poor. This sector is important not only for poverty alleviation, but also for promoting overall economic growth .The extent to which RNF activities can lead to broad-based economic growth, however, depends critically on the profitability of the RNF activities, existence of dynamic market niches, and the strength of the forward and backward linkages of the sector with the rest of the economy.

*The World Bank.


182 The Bangladesh Development Studies

While the programmes for rural works, and other targeted interventions such as the vulnerable group development programme (VGDP) help the poor gain access to income and employment opportunities, they are short-term in nature and cannot sustain the productive means of the poor. Also it has been found that lack of access to affordable credit is a major obstacle to self-employment of the poor, particularly in RNF sector. In this context targeted credit interventions such as Grameen Bank, BRAC, and RD-12 programme of the BRDB play an important role in raising the income and employment of the rural poor. These programmes are found to increase RNF employment by providing credit and other organizational and skill development inputs. Collateral-based financial institutions such as commercial banks and agricultural development banks, and possibly even informal lenders, also finance the RNF sector, but their roles are not as significant as those of microcredit programmes.

This paper discusses the following: (1) the major sources of finance for RNF activities and their relative importance, (2) the extent of credit constraints faced and simultaneous borrowing by the households involved in RNF activities, (3) the determinate of participation in RNF sector, as well as in particular RNF activities, and (4) the rate of return in RNF activities, and sources of productivity.

II. SOURCES OF FINANCE FOR RNF ACTIVITIES In the absence of aggregate-level data, the relative roles of different

institutions have been examined at the household level using the household survey data collected in 1991/92 from 1,798 households in 87 villages. The households were selected randomly on the basis of a village census with more than the proportional number for certain groups of households. However, the household survey data were appropriately weighted in order to represent the actual population distribution of the villages surveyed.

The sources of RNF financing can be broadly classified into formal, informal, and microfinance. Formal finance constitutes collateral-based institutions such as commercial and agricultural banks, microfinance includes targeted credit programmes such as Grameen Bank (GB), BRAC, RD-12, and other NGOs and cooperatives, and informal finance includes friends, relatives, moneylenders, acquaintances and so on. In programme areas, targeted credit programmes have done the most to promote RNF activities. Among those who participate and borrow from any of these three programmes, RNF activities account for 62 per cent of the total


Khandker : Role of Targeted Credit 183

amount borrowed. Among those who are eligible but do not participate, RNF activities accounted for only 27 per cent of total borrowing. On the other hand, among those who are ineligible to participate but borrow from other sources, only 12 per cent of total borrowing is for RNF activities. As Table I shows, the RNF sector accounts for 48 per cent of the total loans advanced by formal financial institutions compared with 28 per cent of the informal loans and 60 per cent of microfinance. The majority of the loans from these three credit programmes were taken for the purchase of nonagricultural equipment and capital. The average loan size varied from Taka 4,212 for Grameen Bank to Taka 2,276 for BRAC, and Taka 2,584 for RD-12.

TABLE I RNF LOAN SIZE AND ITS SHARE IN TOTAL LOAN BY SELECTED SOURCES

(Total number of loans-2985)

Non-agricultural equipment/ capital Non-agricultural : Othersa

Sources Average Loan % of Total Averrage Loan % of Total Volume Size (taka) Volume of Loan Size (taka) of Loan

Formal credit 9611.4 8.2 64113.9 39.9 sources (17267.2) (61867.6) Microcredit sources

RD-12 2583.8 34.1 3282.1 22.8 (946.8) (1956.8)

BRAC 2275.9 35.6 3009.3 28.1 (1057.7) (1708.0)

Grameen . 4211.6 45.9 3911.8 15.6 Bank (1364.0) (1587.3) Informal 3800.2 9.2 5015.7 18.7 credit sources (2676.0) (5075.1)

Notes: Figures in parentheses represent standard deviations. a "Non-agricultural: Others" includes purchase of rickshaw/boat/ fishing nets, and purchase of land, house or other equipment for non-farm enterprises.

Grameen Bank, BRAC, and RD-12 account for 80 per cent of the credit advanced by all microcredit programmes. Among these three microcredit programmes, Grameen Bank has the largest network, covering more than half of all villages in Bangladesh. The RNF sector receives the lion's share (65-100 per cent) of the annual lending of all three programmes (see Figure 1).



Figure 1

RELATIVE DISTRIBUTION OF ANNUAL DISBURSEMENT BY CREDIT PROGRAMMES IN FARM AND RNF SECTORS, 1994

. DETERMINANTS OF HOUSEHOLD PARTICIPATION IN RNF ACTIVITIES

About 48 per cent of the 1,798 households covered in the survey participated in the RNF sector at any time over the crop year 1991/92. However, only 27 per cent of all households participated in RNF activities on a full-time basis. As Table II shows, both household and community factors as well as market wages and prices played important roles in household decision-making regarding any type of RNF participation. For instance, RNF participation is higher among male-headed households than among female-headed households. Landholding, which provides alternative employment opportunities, reduces the likelihood of a household's participation in the RNF sector. Similarly, higher prices for egg, potatoes and sugar, all of which lead to higher farm income, encourage households to concentrate on farming rather than off-farm activities. By contrast, female and child labour wages rates have a positive impact on RNF participation. Rural electrification increases RNF participation, but irrigation reduces it, perhaps providing alternative wage and income earning opportunities. RNF participation is higher in Grameen Bank villages than non-programme villages, although it does not vary among RD-12, BRAC and non-programme villages. In sum, better infrastructure promotes RNF participation, while better income-earning opportunities in agriculture reduce it.



TABLE II DETERMINANTS OP THE PARTICIPATION IN RNP ACTIVITIES

(Probit estimate)

Explanatory Variables Coefficients

Both Part and Full-time Participants

Sex of household head (l=male;O=female) 0.518 Log of household landholding (decimal) -0.045 Village price of hen egg (taka) -0. 137* Village price of potato (taka) -0. 177 Village price of brown sugar (taka) -0.046 Village female wage rate (taka/day) 0.020 Village child wage rate (taka/day) 0.038 Percentage of irrigated land area in village -0.394** Village has electricity? 0.434 Village has BRAC? -0. 107 Village has RD- 1 2? 0. 104 Village has GB? 0.221 Constant 0.239 Log likelihood -1157.33 Number of observations 1,798

Notes : Only the significant and programme placement variables are shown here. Variables are significant at 10% level Variables are significant at 5% level

The RNF activities are aggregated into five major categories by the similarity of the production process involved. The distribution of households involved in these avtivities is shown by programme participation status in Table III. Among the 1,108 households involved in any of these five major RNF activities, 19 per cent are involved in manufacturing, 16 per cent in transport, 47 per cent In trade, about 7 per cent in livestock and fisheries, and 11 per cent in other activities. So trade and commerce is the predominant form of RNF activities in Bangladesh. Next to trade, manufacturing is the second largest activity among all programme participants and non-participants, except for BRAC participants who were involved more in transport.



TABLE III DISTRIBUTION OF HOUSEHOLDS BY RNF ACTIVITIES FOR

DIFFERENT PROGRAMME PARTICIPATION STATUS

Programme Participation Status Activity

Non- Non- AU BRAC RD- 12 GB participants target households

Manufacturing (%) 13.8 20.5 23.1 17.2 17.7 19.3

Transport (%) 21.4 14.2 16.8 20.9 4.4 16.4 Trading (%) 47.8 42.5 45.1 44.6 63.7 47.1 Livestock and 4.4 14.2 7.0 7.1 3.5 6.6 fisheries (%) Others (mostly 12.6 8.7 8.0 10.1 10.6 10.5 services) (%) Number of 159 254 286 296 113 1.108 observations

Now, given the participation in RNF activities, what determines the choice structure of RNF activities in Bangladesh? A multinomial logit (MNL) was run (not shown here) to determine the choice of a particular activity relative to service activities due to a change in one of the explanatory variables. Grameen Bank promotes transport, trade, and livestock compared to service-oriented activities. On the other hand, BRAC promotes service-oriented activities over manufacturing, transport, and trade. Interestingly, commercial banks also promote trade and livestock relative to services. Better roads reduce trade and livestock activities relative to services. Village-level prices and wages also play an important role in a household's selection of RNF activities. Wages for a particular type of labour (male, female and child) represent an alternative of RNF activity (hence, a substitution effect and an income effect). For example, an increase in the male wage rate increases transport and livestock compared to services, while an increase in the female wage reduces transport but increases livestock activity. By contrast, the child wage increases manufacturing, but reduces livestock activities. A village that has no active wage market for female labour (and hence no observed female wage) promotes trade and livestock over service-oriented activities. Trade and livestock provide more self-employment for women than other activities, perhaps because they are compatible with women's role in household non-market production. The prices of different commodities also affect the choice structure of RNF activities. Of particular interest are the prices of rice, the major food crop in Bangladesh, flour and beef. The



rice price promotes the transport sector over the service sector. By contrast, the flour price reduces transport activities relative to services. The beef price increases livestock production as well manufacturing, transport, and trade over other activities. Both human and physical capital influence the choice structure of RNF activities. Thus, education of household head and household landholding status promote service-oriented activities over manufacturing, transport, and livestock. Overall, MNL model explains about 22 per cent of the variations of the choice structure of the RNF activities in terms of these household attributes, village characteristics, and prices and wages.

IV SOURCES OF PRODUCTIVITY IN THE RNF SECTOR The RNF sector is an important source of income and employment

for rural households, especially for the poor who do not have enough land to support themselves. Figure 2 shows the relative distribution of income and employment of individuals. It is worth noting that agricultural sector, despite providing more employment (65 per cent) than the RNF sector, has a return of only 45 per cent. This suggests that RNF activities are more rewarding than traditional farm activities.

Figure 2 RELATIVE DISTRIBUTION OF INDIVIDUAL

EMPLOYMENT AND INCOME

Given the significance of the RNF sector as a source of income and employment, it will be interesting to examine the relative contribution



of the three targeted credit programmes, and other factors to productivity in the RNF sector. The Cobb-Douglas production function framework is used (not shown here) to identify the relative roles of various factors. Sixty per cent of the productivity differences among target households and 55 per cent among non-target households are explained by the model for all RNF activities. Estimates show that Grameen Bank placement has increased RNF production in manufacturing for target households, trading for non-target households, and RNF sector as a whole for the target households. BRAC placement has increased production in manufacturing for target households, and in trading for non-target households, but it has increased production in the RNF sector as a whole for both target and non-target households. Similarly, RD-12 placement has increased manufacturing for target, trading for non-target, and overall RNF production for target households. Thus programme placements, in addition to influencing directly the productivity of participants, create induced demand or supply effect which benefit non-participating and non-target households too. However, there are inter-programme variations in raising productivity in a particular RNF activity. For example, in the Case of manufacturing, the growth of productivity is the largest for the BRAC (22 per cent) followed by the RD-12 (12 per cent) and the Grameen Bank ((11 per cent). But for all activities combined, the impact on target households is highest for the BRAC (10 per cent), followed by the Grameen Bank (8 per cent) and the RD-12 (4 per cent). Non-target households, however, benefit only from the BRAC (10 per cent).

Traditional banks apparently benefit target households more than non-target households. If the village has a bank, RNF production is increased by 3 per cent for target households. Seasonality is especially pronounced in the service sector and it is higher in the Aus season than in the Aman. The household head's education has a positive impact on manufacturing, trade, and overall RNF production for both target and non-target households. The private return on one year of education in the RNF sector is slightly higher for non-target (5 per cent) than for target households (3 per cent). Labour has positive impacts on the productivity of manufacturing, transport, trading, and other activities, and on RNF sector as a whole for target households. The marginal product of labour is calculated at 37 taka per manday for target households and 51 taka per manday for nontarget households. The figure for target household is close to the average daily wage rate of 40 taka for nonagricultural wage labour.



V. RATE OF RETURN, CAPITAL INTENSITY AND LABOUR PRODUCTIVITY

The growth potential of RNF activities is measured by rate of return (ROR) which is defined by the ratio of the difference between revenue and the cost of all types of inputs (including capital and family labour inputs at their opportunity costs) over the amount of fixed and working capital (in taka). Capital intensity is measured by the capital-labour ratio (CLR) where capital is the value of fixed capital and labour is the male equivalent manday. Capital productivity is measured by capital-output ratio (COR) which is the value of fixed capital over the total value of production (in taka). On the other hand, labour productivity is measured by the output-labour ratio (OLR) which is the value of output over the total number of mandays. Table IV presents these ratios by type of activity and by programme participation status. The ROR is highest in livestock and fisheries, followed by manufacturing, trading, services and transport. Capital intensity is highest for trading activities, whereas labour productivity is highest in livestock. Among the programme participants, ROR is highest for RD-12 participants, whereas capital intensity as also labour productivity is highest for non-target households.

TABLE IV RATE OP RETURN (ROR), CAPITAL-LABOUR RATIO (CLR), CAPITAL-OUTPUT

RATIO (COR) AND OUTPUT-LABOUR RATIO (OLR) OF RNF ACTIVITIES BY ACTIVITY AND PROGRAMME PARTICIPATION STATUS

Activity ROR(%) CLR COR OLR

Manufacturing 3.591 93.415 0.393 604.078 Transport 1.187 18.641 0.438 65.209 Trading 3.096 200.28 0.415 817.476 Livestock and fisheries 10.180 47.198 0.124 1247.711 Others (mostly services) 2.539 114.597 0.570 484.155 Total 3.214 129.068 0.413 633.111 Programme Participation Statue

BRAC 2.59 86.92 0.34 432.75 RD-12 4.43 46.93 0.34 428.21 G B 2.84 103.53 0.34 506.40 Non-participants 3.05 73.17 0.42 435.72 Non-target 4.03 362.46 0.48 1334.53



Data analysis shows that semi-urban areas have higher returns in manufacturing activities than that in rural areas. Also BRAC's role is worth noting for manufacturing, a key activity in rural led industrialization. As mentioned in the previous section productivity growth is highest in BRAC villages. In addition, BRAC borrowers not only have low capital intensity, but also the highest returns of labour for manufacturing. Given BRAC's intensive skill promotion training, it is likely that its members attain higher returns on manufacturing.

VL SUSTAINABBLITY OF THE BORROWERS

Programme participation helps increase employment for those who are unemployed or underemployed and provides self-employment opportunities for those who are wage-employed. An estimate of the incidence of poverty shows that incidence of both moderate and extreme poverty are higher among non-participants than among programme participants in programme villages. Programme participants also have more savings, assets, and networth than non-participants in all programme villages (Khandker and Chowdhury 1995).

Econometric estimates identifying the causal impacts of borrowing from targeted credit programmes show that borrowing, especially by women, substantially increases per capita expenditure and hence reduces poverty (Pitt and Khandker 1996). For example, for Grameen Bank borrowers the rate of return of borrowing on expenditure is 19 per cent for female borrowing and 12 per cent for male borrowing. When these rates of return, at current levels of borrowing and lengths of programme participation, are combined with the level of consumption required to alleviate poverty (5,250 taka per capita per year), it is found that it takes about 9 years for the average female Grameen borrower to lift her family out of poverty from the date of her joining the programme.

Although borrowers of the credit programmes pay a higher interest rate than the borrowers of commercial or development banks, Table IV suggests that they are able to pay this high interest rate and still earn profit from investment in RNF activities because of their high rate of return (2.8 for GB participants, 2.6 for BRAC participants, and 4.4 for RD-12 participants).



Vu. EXTENT OF CREDIT CONSTRAINT AND SIMULTANEOUS BORROWING

Average returns to capital are much higher for non-target households than for programme participants and target non-participants. As Table IV shows, the capital-labour ratio is highest (362.5) for non-target households. Thus, due to more capital per unit of labour, labour productivity in RNF activities is highest (1,335 Taka per manday) for non-target households, followed by Grameen Bank participants (506 taka), target non-participants (436 taka), BRAC participants (433* taka) and RD-12 (428 taka). This raises the question whether programme participants lack access to funds for increasing capital so as to increase both labour productivity and rate of return on capital.

From the aggregate production functions, marginal productivity of capital is calculated for both target and non-target households involved in the RNF sector. The marginal product of capital was found to be 0.48 for target households and only 0.05 for non-target households. Since the returns on capital are sufficient to increase the size of an enterprise's capital, the existence of a capital constraint in production implies the existence of a credit constraint from the supply side. This means that participants of targeted credit programmes such as the Grameen Bank, BRAC, and RD-12 cannot borrow as much as they would like to.

Also household survery data is used to identify the extent of the credit (supply) constraint. Households were asked if they would borrow at the prevailing interest rate if there were no constraints on the supply side. All activities were subject to credit constraint, ranging from 54 per cent in transport to 74 per cent in livestock. Similar credit constraints were found for borrowers of the credit programmes (67 per cent for BRAC borrowers, 73 per cent of RD-12 borrowers, and 63 per cent of GB borrowers).

Because of these credit constraints, it is possible that they draw on various sources to finance their enterprises. In fact, more than 40 per cent of BRAC members, 43 per cent of RD-12 members, and 51 per cent of Grameen Bank members use more than one source to finance start-up capital. Use of multiple sources of start-up capital is highest in livestock and fisheries (39 per cent) and lowest in transport and other activities (27 per cent).



VIII. SUMMARY AND CONCLUSIONS In a labour-surplus country such as Bangladesh, expansion in

rural non-farm production and employment is necessary for promoting broad-based economic growth. This is because RNF activities rely on and promote labour-intensive production, generating employment for a large number of people. Also, as mentioned before, RNF sector accounts for about 55 per cent of rural income while it provides 35 per cent of the rural employment.

Lack of access to credit is a binding constraint on RNF participation. The data shows that households with more than 50 decimals of land, and households with less than 50 decimals of land that are not part of any targeted credit programme, use mostly their own savings to start up an RNF activity. The fixed and working capital requirement of RNF activities renders self-financing difficult for many rural households and hence, programmes such as the Grameen Bank, the BRAC and the BRDB's RD-12 that provide credit and organizational help are likely to promote RNF production. Data analysis confirms that these programmes have increased overall village-level RNF participation.

An expanded market with better infrastructures can help promote RNF growth. Data analysis shows that the returns are higher in small towns than in rural areas for the important RNF activity, manufacturing. Despite the fact that rural towns have better access to competing non-rural non-farm goods, the returns on manufacturing are higher in semi-urban areas than that in rural areas. Better markets and infrastructure are perhaps good facilitators for RNF-led growth.

Improving access to affordable credit and raising the amount of credit available are ways to improve both participation and productivity in the RNF sector. However, only better credit availability may not ensure the dynamism in the RNF sector that is required to increase growth and employment. Analysis of borrower-level data for the three targeted credit programmes clearly indicates that because of skill training and other organizational help, BRAC borrowers have managed to sustain increased productivity with improved access to credit. Therefore, the supply of affordable credit for the expansion of RNF production must be supported by appropriate skill development, market promotio, and other organizational policy measures..



REFERENCES

Khandker and Chowdhury 1996: Shahidur R Khandker and Osman H. Chowdhury, 'Targeted Credit Programs and Rural Poverty in Bangladesh" in Credit Programs for the Poor: Household and Intrahousehold Impacts and Program Sustainability, Volume II, (eds.) Md. A. Latif et al.

Pitt and Khandker 1996: Mark M. Pitt and Shahidur R. Khandker, "Impact of Credit Programs for the Poor on Household Behavior in Bangladesh" in Credit Programs for the Poor: Household and Intrahousehold Impacts and Program Sustainability, Volume II, (eds) Md. A. Latif et al

Khandker, Shahidur R. 1996. Fighting Poverty with Microcredit: Experience of the Grameen Bank and Other Programs in Bangladesh. Poverty and Social Policy Department, The World Bank, Washington, D.C.

Khandker, Shahidur R. and Baqui Khalily 1996. 'The Bangladesh Rural Advancement Committee's Credit Programs: Performance and Sustainability." World Bank Discussion Papers No. 324. Washington, D.C.

Khandker, Shahidur R. Baqui Khalily and Zahed Khan, 1995. " Grammen Bank: Performance and Sustainability." World Bank Discussion Papers No. 306. Washington, D.C.

Khandker, Shahidur R., Zahed Khan and Baqui Khalily, 1995. "Sustainability of a Government Targeted Credit Program: Evidence from Bangladesh." World Bank Discussion Papers No. 316. Washington, D.CA


Article Contentsp. [181]p. 182p. 183p. 184p. 185p. 186p. 187p. 188p. 189p. 190p. 191p. 192p. 193

Issue Table of ContentsThe Bangladesh Development Studies, Vol. 24, No. 3/4, RURAL NON-FARM DEVELOPMENT IN BANGLADESH (Sept.-Dec. 1996), pp. i-viii, 1-258Front MatterEditors' Introduction [pp. i-viii]Employment Patterns and Income Formation in Rural Bangladesh: The Role of Rural Non-farm Sector [pp. 1-27]The Rural Non-farm Sector in Bangladesh: Evolving Pattern and Growth Potential [pp. 29-73]Rural Non-farm Employment in Bangladesh [pp. 75-102]The Emerging Pattern of Rural Non-farm Sector in Bangladesh: A Review of Micro Evidence [pp. 103-141]Rural Non-farm Sector in Bangladesh : Stagnating and Residual, or Dynamic and Potential ? [pp. 143-180]Role of Targeted Credit in Rural Non-farm Growth [pp. 181-193]The Non-farm Road to Higher Growth: Comparative Experience and Bangladesh's Prospects [pp. 195-248]Back Matter

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