agricultural finance and micro and small enterprise growth

8/8/2019 Agricultural Finance and Micro and Small Enterprise Growth

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AGRICULTURAL FINANCE AND MICRO AND

SMALL ENTERPRISE GROWTH: A CASE OF

AGRICULTURAL FINANCE CORPORATION

MACHAKOS DISTRICT, KENYA

BY

JOSEPH MACHARIAKINYANJUI


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Statement of the research problem

SMEs in Kenya form a very crucial sector

in terms of employment generation, wealth

creation, welfare improvement and theirimmense contribution to the national GDP.

However, SMEs are generally

undercapitalized due to operational

difficulties in accessing finance.


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Statement of the problem cont

Lack of working capital and low liquidity limit the

entrepreneurs ability to purchase productivity

enhancing inputs like seeds, fertilizers and

pesticides and more stock (Nyoro, 2002).

The average production efficiency levels are

higher among producers who have access tofinance in agricultural related enterprises in

Kenya (Kibaara, 2005).


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The lack of finance is one of the most

binding constraints in the growth of SMEs,as only 14 percent of SMEs might resort to

borrowing, out of which two thirds was for

capital Investment.


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Many SMEs are not going to banks to

meet financial needs due to various

reasons including:

lack of knowledge regarding bank

products,

low market penetration by banks,

lengthy and difficult loan procedures, lack

of security,

lengthy documentation,

and social as well as religious reasons.


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Within the context of the agriculture

industry, there is a great need for credit forin order to accelerate the growth of MSEs.

The demand for rural credit has

outstripped the supply over time.

The current annual demand is estimated

at Kenya shillings 75 billion while the

supply stands at 1822 billion Kenyashillings (MoA, 1995; Kimuyu and Omiti,

2000).


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Agricultural finance is notoriously risky.

Many farmers need credit to purchaseseeds and other inputs, as well as to

harvest, process, market and transport

their crops. While borrowing on the basis

of anticipated crop production might seem

logical where collateral assets are few,

such loans expose the lender to

production and price risk..


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Natural disasters, a decline in

market prices, unexpectedly lowyields, the lack of buyers of

agricultural produce, or loss due

to poor storage conditions areonly some of the factors that can

result in lower than-expected

revenues. Such a fall in revenues

can often lead to high default

rates on agricultural loans


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Research objectives

The main objective of this study isto examine the role of agricultural

finance in MSE growth.

The study seeks to find out

whether agricultural finance has

played any role or no role in MSE

growth.


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Specific objectives of the study

Review the lending procedures of agriculturalfinance institutions.

Assess the effect of agricultural finance on MSE

expansion and growth.

To analyze the major constraints hindering theavailability of agricultural finance to small and

micro enterprises in the study area.

To evolve policy recommendations that will

improve the administration of agricultural finance

to small-scale enterprises in Kenya


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Research questions

The study seeks to answer the following

questions Do lending procedures of AFC affect the

availability of agricultural finance?

What is the effect of agricultural finance on SME

expansion and growth? What constraints hinder the availability of

agricultural credit in the study area?

What policy suggestions should be

recommended to ease administration ofagricultural finance to small scale enterprises inKenya?


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RESEARCH METHODOLOGY

Research design

The research design used in the study would beexploratory-descriptive research design. It is exploratoryin that the major emphasis would be on the discovery adtrying to get more insight on the effect of agriculturalfinance on SME growth. The design would also be

descriptive as the effect of the finance on the growth ofSMEs would be explained.

Target population

The study targeted entrepreneurs engaged in farming,

wholesale and retail trade, and primary processing ofagricultural products. The sample size was 120respondents drawn from six administrative divisions ofMachakos district.


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3.4 Sampling and sample size

This includes both credit and noncredit users. Theresearcher selected 120 small-scale. The entrepreneursidentified the available formal and informal sources of

credit from which they had benefited. There are sixadministrative divisions in Machakos district .Eachadministrative division was allocated 20 respondentsgiving a total number as 120. Purposive sampling wasthen applied in the selection of respondents who werewilling and satisfied the set criteria of being in business

for more than 18 months with 1-50 employees. Therequired sample size was selected using theproportionate stratified sampling and judgmentalsampling respectively.


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Each administrative division was allocated

20 respondents giving a total number as120. Purposive sampling was then applied

in the selection of respondents who were

willing and satisfied the set criteria of

being in business for more than 18 monthswith 1-50 employees.

The required sample size was selected

using the proportionate stratified samplingand judgmental sampling respectively.


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3. 5 Data collection methods

Data collection methods include the use of

questionnaires, observation anddiscussions.

3.5.1 Primary Data collection


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Data collection tools

The main data collection instrument used in thestudy was a questionnaire. Respondents whoare literate were asked to fill tone or the same

was used as an interview schedule for illiteraterespondents. This was administered in Kiswahilifor ease of understanding.

The researcher also used observation method tocomplement data generated from thequestionnaire. This data from the observationwas used for correlation purposes to enhancedata reliability.


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Secondary data collection

This was mainly done using data

from the Central bureau of

statistics and ministry of trade andindustry data on registered

businesses in Machakos district.

.


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3.6 Data analysis

Data was analyzed using both qualitative and

quantitative methods. Data was first coded and

organized into concepts from whichgeneralizations were made fro the entire

population. Data was then tabulated and

frequencies calculated on each variable under

study and interpretations made from the

collected finding in the field.


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Measures of central tendency such as

mean, mode and median and measures ofdispersion like standard deviation and

percentages were calculated and

interpretations made. Data is then

presented in form of tables and pie-chartsand graphs.

The analyzed data was then converted

into descriptive statements and/inferencesabout relationships


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Distribution of respondents by

gender

Distribution of respondents by

gender

6 %

3 %

e

fe e


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Distribution of responses by

educational level Distribution of responses by educational

level

The level of education is important as itdetermines the channels of communication usedby the respondent, degree of confidence and theease of acquisition of new managerial skills. Theeducation level also determines the level ofconfidence in approaching financial institutions.In order to determine the education levelsrespondents were asked to indicate theireducation levels and the results are tabulated intable


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Distribution of respondents by ownership

Entrepreneurs found at the business were askedto indicate the nature of the ownership of the

business. This was defined as soleproprietorship, partnership, limited company andany other form of ownership. No responses werereceived from any other form of ownership.Overwhelmingly most of the businesses are soleproprietorship. The frequency is indicated in thechart below.

Business ownership


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Ownership status of respondents

o e propreitership

i ited o pan

artnership

ownershipform

percentage


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Agricultural finance impact was best

reflected through increase in sales volume

(40 per cent), increase in profit (10 per

cent) and increase in number of

employees at 12 per cent, increase in

production levels is at 25 per cent. The

results are shown on the figure 4 below: Major areas of business growth


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Major areas of business business

growth

sa es o u e

ro u tion

rofits

new e o ees

in rease in sto

New businesses

others

Frequency


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The entrepreneurs also indicated the

entrepreneurial finance had an overall

impact on the growth of the business (7

per cent of the respondents) while 20 per

cent of the businesses had declined as a

result of the agricultural finance obtained.


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Sources of seed capital

Sources of starting capital

0 10 20 0 40 50 0 70

ersonal sa ings

Loans from relati es

ommercial ank

Sale of personal assets

thers

Source

re ue cy


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Lending procedures

Easy loan security system was cited as the main

reason for choosing a certain lending institution

(4 per cent) while no restrictions on loan use

was also cited as an important factor ( percent).Simple application procedures is also a

critical factor ( 5 per cent).Fast processing of

loan applications was also cited by 0 per cent

of the respondents as an important factor inchoosing a financial institution to cater for the

financial needs of the borrower.


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Characteristics of lending

institutions

ro i it to lender offices

ast rocessing of loan

i le a lication rocedures

as loan securi t s ste

oan si e a ro iriate to needs

o restrictions on loan use

n other


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When choosing financial institutions to approach for credit, 5 percent of potential borrowers would look at the interest rates chargedby the lender from the findings of the research. On establishing thatthey are relatively cheap in the market, then they would consider thefollowing issues in order of priority . 0 per cent of the respondentswould first consider whether the lending institution would consideradjusting the repayment premiums in this respect) therefore theywould prefer MFIs which would penalize the group members tocover for this shortfall rather than sell the individuals assets. 2 percent of the respondents consider the speed of processing loansthird is what collateral the institutions would ask for then fourthwhether the lender might consider rescheduling the loan in times ofmisfortunes. Application procedures, proximity to offices or theirofficers and size of loan available rank fifth sixth and seventhrespectively. A significant minority of entrepreneurs are happy withthe way things are.


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CONCLUSIONS

There is need to develop lending policiesthat recognize that financial services arepart of an interactive system of financial

institutions, financial infrastructure, legaland regulatory framework, social andcultural norms. There is need to simplifylending procedures and develop unique

loan products that cater for the needs ofthe entrepreneurs in the agriculturalsector.


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All the stakeholders must build and enhance thebusiness skill of the entrepreneurs in order to increasetheir growth potential .When the business capacity of theentrepreneurs is high, the can visualize the directionwhich they want their business to grow in the future. As aresult, with increased capacity, they can be able todevelop comprehensive business plans to achieve thatvision and as a result increase the demand for credit inthe market , improve productivity and employment andgenerally assist the government to meet its development

agenda. Treating the farm household as a financial unitintegrating a variety of economic activities, and basinglending decisions on repayment capacity rather than howfunds are utilized is also important to ensure more flowof funds to the MSEs that require agricultural finance.


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More research should be conducted on methods

of information gathering on the borrowers to

reduce default rates and strengthening capacity

of the agricultural finance institutions in order toenhance credit delivery. Further there is need to

carry out research on how agricultural finance

providers can adapt their services to become

more flexible in timing, amounts disbursed andrepayment schedules

agricultural finance and micro and small enterprise growth

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