Supply Response of Rice Supply Response of Rice and Implications for Food and Implications for Food Security Policy: A Case of Security Policy: A Case of

Mwea Irrigation Scheme in Mwea Irrigation Scheme in KenyaKenya

B.J.K Maina, C.W. Kabuti and R. Chepchirchir

   

Why Rice? Why care?Why Rice? Why care?

Rice is the 3rd most important staple food in Kenya after maize and wheat

Its rate of consumption has been growing rapidly and it is likely to overtake wheat over time.

95% is grown under irrigation in paddy schemes managed by NIB

Kenya has a potential to produce 400,000 ha (rain fed) &11,000 ha (irrigated).

Btwn 2007-2010, Kenya’s rice production ranged between 45,000 and 50,000 MT, against a consumption of over 210,000 MT (now 70k vs 300k)

BUT consumption averages btwn 180,000 - 250,000 MT

Balance is imported- mainly Pakistan- at a preferential rate of 35%.

Urban dd increasing by 12% annually

Urbanization is increasing by 4.2% - population growth is 3%

The policy side, what we The policy side, what we thinkthink

Staple foods: Maize is considered as the strategic grain for Kenya, wheat and wheat products also important

But Kenya has been exposed to food insecurity severally- weather risks(drought)

What we need: To diversify to more strategic grains to cushion the nation against such risks

Best option: Rice has been considered as a close substitute for maize but also as a high value crop which if produced in surplus could be exported

Policy Action Concentration on price policies to accelerate rice production

The problem Rice production in

Kenya has been on a steady decline – Kenya still food insecure & at risk

Population & urbanization are increasing – more food demand – more risks

Price policies alone cannot (have not) encouraged supply

Proposal Need to explore other

non-price incentives for rice farmers to increase their production and subsequent supply

Study area, Materials and Study area, Materials and MethodsMethodsStudy objective: to establish the determinants that influence rice supply and their significance

Study area: Mwea Irrigation Scheme; the biggest rice producer in Kenya

Data & Sources: Time series production and supply data from 1988 to 2007- from MIS, surrounding outgrowers, MRM &MRGMM

Independent variables: rice prices, water availability, rainfall, civil unrest, presence of NIB and real GDP

The model specification: Regression analysis methods - Nerlovian model (1958) on supply response

Models specifications Models specifications Nerlovian model for an annual crop (Askari and

Cummings, 1977)

Zt = other observed, exogenous factors affecting supply at time t are given by the expression

Model was a combination of expectation and adjustment lag variables.

Modified the equation by adopting rice supplies as the dependent variable instead of acreage

 

*0 1 2t t t tA P Z ……………..…(a)

*

1(1 )t t tA A A …………………………(b)

*

1(1 )t t tP P P ………………………...(c

1, , , , , , , , , ........................(1)t t m t t t tP P P R W Y GDP CI CVL P NIB

t t t m tln =f(lnW ,lnP ,lnP ,NIB,cvl,lnA ,lnR,lnCI,lnGDP)...........(2)Y

Data analysis, results & Data analysis, results & interpretationsinterpretations

Regression analysis -OLS methodNormality (Shapiro-Wilk and

graphical tests) and stationarity tests (ADF) were carried out to ensure accuracy of the data

values of the coefficients in a log-log model were directly interpreted as a measure the respective elasticities.

Elasticities of the individual variables in the model indicated the respective responses to rice supply

Summary StatisticsSummary Statistics

VariableMean- Total

Mean- NIB Mean-No NIB

Rice Supply (MT) 9,276

12,560 1,614

Input costs (Kshs)

12,616

14,056 9,256

Acreage

11,301

14,515 3,803 Import price (Kshs)

17

15 22

Water supply (M3/ha)

5

6 2

Price local rice (Kshs)

20

18 26

Real GDP (Kshs)

691,805

652,412 783,723

Rainfall (mm/yr)

988

977 1,014

Regression Results

•GDP, domestic price, import price, acreage, rainfall & presence of NIB were statistically significant•Water, input costs and civil unrest were not significant•Significant variables explain 97.9% of the variability in rice supply (R2 = 0.9796)

Elasticities

0.35030.82130.6463-0.27621.7880-0.96460.4695

Conclusions Conclusions local rice supplies are affected by own prices &

import prices- imported rice is relatively cheaper that locally produced rice

As the GDP improves importers get more of the relatively cheaper rice grains and the local farmers supply less since the prices are forced to match those of imports

The presence of NIB is significant in provision of necessary infrastructures and water for irrigation

Though water and input costs were not found to have any significance in influencing rice supplies, they are economically important in determining the amounts of rice that goes to the market

What Policy makers should What Policy makers should dodo

Development of policy guidelines for packaging, marketing and linkage to suppliers so as to trigger demand for locally produced rice

Need to monitor rice imports to protect the local farmers to safeguard their livelihoods – Argument for rice to be included in the list of sensitive products

Consider subsidizing farm inputs which would ensure local rice production increases in addition to becoming more globally competitive

Ensure that the scheme be continually managed by the NIB but prices be determined by the market forces of demand and supply

THANK YOUTHANK YOU

ACKNOWLEDGEMENTS ACKNOWLEDGEMENTS AfricaRice

Co-authors

University of Nairobi

Agricom Consultants, Ltd. Nairobi