giovanni andrea cornia, laura deotti and maria sassi

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Sources of Domestic Food Price Volatility and Child Malnutrition: evidence from Niger and Malawi GIOVANNI ANDREA CORNIA, LAURA DEOTTI and MARIA SASSI University of Florence, Save the Children and University of Pavia

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Sources of Domestic Food Price Volatility and Child Malnutrition: evidence from Niger and Malawi. GIOVANNI ANDREA CORNIA, LAURA DEOTTI and MARIA SASSI University of Florence, Save the Children and University of Pavia ----------- ICABR Annual Conference, Ravello, 17-21 June 2013. - PowerPoint PPT Presentation

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Sources of Domestic Food Price Volatility

and Child Malnutrition: evidence from Niger and Malawi

GIOVANNI ANDREA CORNIA, LAURA DEOTTI and MARIA SASSI

University of Florence, Save the Children and University of Pavia

-----------ICABR Annual Conference, Ravello, 17-21 June 2013

Much attention was paid to impact of world food prices of 2007-8/2010-11. This obscured domestic factors’ s impact on child nutrition in SSA, i.e.

• the long term food supply impact of agricultural policies;

• huge and persistent seasonal variation in food production;

• impact of (still recurrent!) famines.

After testing impact of changes in world food prices on domestic prices

….. this paper tests influence of 3 above variables on child malnutrition

How large the transmission of world food prices on domestic food prices in SSA?

• Large literature ….but conclusions vary on basis of specific factors such as • dependence on imported food, • magnitude of transport costs and trade margins, • world tradability of domestic staple food, and integration with global mkt• exchange rate variations,

• Thus in parts of SSA

• is difficult to argue that the world price is main driver of domestic food prices

• while domestic prices often exhibit large rises in parallell with declines of world prices

Niger and Malawi

• their structural features (small, land short, bordering bigger countries, landlocked, low input subsist. agriculture, single staple) make them representative of several SSA countries affected by major problems of:

- Chronic;

- Seasonal; and

- Acute;

food insecurity and child malnutrition.

Theoretical framework to asses child malnutrition (based on Sen’s entitlement approach)

A household’s ‘control over food’ (and thus child malnutrition) depends on its entitlement, i.e. a set of commodity bundles it commands in society

ENTITLEMENTS:

- Production-based entitlements (food produced for self-consumption)

- Exchange-based entitlements (food acquired through mkt exchange)

- wage–based entitlements

- Inheritance and transfer-based entitlements

These entitlements change (at different speeds) over the l.term, seasons & during famines

Food entitlement bundles of a household

Pf

A

Pf

Th

Pf

PwQw

Pf

PjQjQfscQ h

hhhh

Food available

Food produced for

self-consumption

Good sold Wage labour

Transfers received

Income form

assets sold

Factors affecting food entitlements & child malnutrition

- Long-term food price and security (which depends on gains in agricultural productivity – and therefore on agricultural policies);

- easonal variations in food prices (depend on storage capacity & credit availability);

- Price changes during food acute crises/famine (depend also on food security policies)

- Changes in value of the entitlements over these three time dimensions

Methodology of empirical analysis

• we decompose food price vector into three price sub-vectors reflecting the:

• Trend price component (reflecting – inter alia - long term gains in agricultural productivity)

• Seasonal price component (reflecting the efficiency of credit mkts and inter-temporal smoothing)

• Famine price component (reflecting the gov. capacity to respond to large price shocks )

• A residual price component (which reflects various effects, such as the price of inputs)

• We correlate these food price components (sub-vectors) to the number of children admitted to feeding centers

Methodology (cont’d)

• Nominal food price data were deflated with the CPI

• The dynamics of trend and seasonal component suggested that the 4 price components interact according to a multiplicative model:

FP = TPC x SPC x FPC x RPC

• Monthly Seasonal Adjust. Method allows separating seasonal (SPC) effects from the l.term component (TPC) of the aggregate price trend.

• the long term trend (TPC) was calculated by mean of the Hodrick-Prescot Filter and then subtracted from the aggregate price trend so as to obtain the random (RPC) and famine (FPC) price components.

Price trend component – monthly data

Malawi: Maize (January 2003 – December 2009)

Niger: Millet (January 2006 – December 2010)

Note: TPC = Trend price component

Seasonal and famine food price components and number of children admitted per feeding centre – monthly data

Malawi: Maize (January 2003 – December 2009)

Niger: Millet (January 2006 – December 2010)

Note: CAF/NC = child admissions by feeding centre; SPC = Seasonal price component; FPC = Famine price component

Methodology (cont’d)

• We regress the 4 price components on the n. of child admissions

• We control for ‘hunger season dummy’ and number of feeding centers

• Do not include – due to lack of data – the value of entitlements. Yet –during seasonal fluctuations/famines- they correlate(-) with food prices

• We ignore world prices as in the 2000s their trend did not significantly affect domestic prices

Variable Malawi Niger

Log-log OLS estimates Model 1 Model 2 Model 3 Model 1 Model 2 Model 3

Constant term 5.914*** 1.139*** 5.710*** 1.062** -0.613 1.056**

Trend price component - 0.769*** - 0.572*** -0.702*** 12.05*** 10.624*** 11.84***

Seasonal price component 1.676*** 1.908*** -0.189 1.926*** 1.727*** 1.089

Famine price component 0.333 0.219* 0.331* -2.881*** -2.012** -2.699***

Residual price component 0.239 0.744 0.381 -2.567 -3.341 -2.183

Number of feeding centre 1.205*** 0.427***

Hunger season dummy 0.782*** 0.317***

Adj R2 0.30 0.86 0.39 0.84 0.86 0.85

F- statistics 9.91*** 107.93*** 11.73*** 72.84*** 73.13*** 66.6***

Durbin Watson 1.30 0.85 1.44 1.04 1.27 1.21

OLS log-log regression of n.child admissions to feeding centres on price components – monthly data (2003-2009 – Malawi 2006-2010 Niger))

Results • Despite data & methodological limitations, regressions

analysis suggests that:

• the moderate l. term food price rise in Malawi (due to rising land yields) helped reducing child malnutrit. Opposite was true in Niger (no support to agriculture)

• Seasonal price rises are a major cause of child malnutrition in both countries. Such effect correlates closely with hunger seasons dummy (dominated by price effect)

• The 2006-2010 famines in Niger where well responded to, it helped contain child malnutrition. This was not the case in Malawi

• In both, the rise in feeding centers contributed to the increase in admissions

Implications for policy research

- Suitable policies aimed at intensifying agricultural production and rising land yield to contain domestic prices & reduce child malnutrition;

- Role of long-term policies, particularly in the agricultural sector;

- Role of credit/storage policies for addressing seasonal food price fluctuations;

- Rethinking food security policies during famines;