Did rapid smallholder-led agricultural growth fail to

reduce rural poverty? Making sense of Malawi’s poverty

puzzle

Ulrik Beck, University of CopenhagenRichard Mussa, Chancellor College, University of

MalawiKarl Pauw, Malawi Strategy Support Program, IFPRI

9 April 2014Crossroads Hotel, Lilongwe

Background

2004/05 – 2010/11 characterized by rapid economic growth, averaging 7.1% per annum

Led by strong growth in agric. GDP (10.1% growth; 34.2% contribution to GDP expansion)

Significant rise in maize yields (fig.)

Legitimate expectation of rapid poverty reduction

Official poverty results (NSO)

Estimates from “interim” WMSs suggested systematic decline in poverty (in line with expectations) between 2004/05 and 2009 But 2010/11 estimates disappointing: − Overall

poverty declined 52.4 to 50.7%

− Rural poverty increased from 55.9 to 56.6%

How can this be explained?

Growth did not trickle down to the poor? − Some evidence of this in rising inequality − Yet growth originated among smallholder maize producers

who also account for the bulk of the poor

Growth is overestimated? − Questionable crop production estimates underlying

agricultural GDP estimates: price behavior (Jayne et al. 2008); fertilizer use efficiency (Dorward et al. 2008; Pauw & Thurlow 2014)

Poverty reduction is understated (Pauw et al. 2011)? − Revisiting poverty estimation is the focus in

this study… leave national accounts validation for later

Poverty estimation refinements

Introduce several refinements compared to NSO poverty estimation procedure, including:− Cost of basic needs approach used in both periods with

price data from survey rather than external data source− Nonfood consumption share permitted to change over time− Entropy-based method used to ensure that chosen bundles

are utility-consistent across space and time (Arndt and Simler 2010)

Above have marginal implications; major differences between revised and NSO poverty results explained by: − Our use of regional poverty lines to account for differences

in preferences and prices (urban, and rural north, center and south)

− Systematic checking and revision of consumption conversion factors (following Ecker & Qaim 2011)

Inflation faced by the poor (%)

National average fairly comparable (132.8% vs. 128.9%)

Analysis of implicit prices of consumption baskets of poor people across different regions suggest:− Higher urban poverty line inflation (186.6%), driven by

nonfood inflation (212.6%)− Lower rural poverty line inflation (119.8%), with food

inflation (136.5%) much higher than nonfood inflation

Food Nonfood TotalCompare

NSONational 137.8 127.7 132.8 128.9

Urban 151.3 212.6 186.6 128.9

Rural 136.5 101.5 119.8 128.9

North rural 129.0 124.0 126.8 128.9

Central rural 144.9 102.7 123.9 128.9

South rural 127.0 91.9 111.9 128.9

NSO’s 128.9% inflation estimate from revised CPI series; same rate applied for food/nonfood and urban/rural

Poverty results

2004/05 (IHS2)

2010/11 (IHS3)

National 55.1 49.0 -6.1 ± 2.7 -1.7 ± 2.4Urban 38.2 36.0 -2.2 ± 9.1 -8.1 ± 6.8Rural 57.3 51.3 -6.0 ± 2.9 0.7 ± 1.4

North rural 66.1 60.6 -5.5 ± 6.2 3.6 ± 6.5Central rural 49.7 46.0 -3.7 ± 4.6 2.0 ± 4.2South rural 62.3 53.6 -8.7 ± 4.3 -1.1 ± 3.7

Compare official change in poverty (NSO)

Change in regional poverty

Our rural poverty rates comparable with NSO, but much larger and significant declines over time in all rural areas, especially south

Urban poverty significantly higher using our method, and also smaller (but statistically insignificant) decline compared to NSO

Cumulative distribution functions and poverty

lines

Difference in consumption CDFs explained by conversion factor adjustments and way in which food consumption is aggregated; nonfood components similar

Slightly higher consumption level in rural and urban areas, but also higher cost/poverty line (same applies in 2004/05)

Rural areas: higher consumption compensates for higher estimated cost of living lower poverty rate

Urban areas: cost of living well above national average also higher poverty estimate

Conclusions

Evidence of rapid rural poverty reduction and only marginal decline in urban poverty is consistent with − Pro-poor smallholder-focused growth strategy coupled with

experience of rapid urban (nonfood) inflation− Available non-monetary poverty indicators (Mazunda et al.

2012) Poverty measurement is challenging at best, and

results highly sensitive to assumptions However, our analysis addresses several

shortcomings of NSO method relating inter alia to price data, regional preferences, utility-consistency, consumption conversion factors, costing of poor households’ consumption bundles, and estimating the related poverty lines

Ultimately we believe poverty outcomes in rural areas not as bleak; FISP may in fact have had a significant impact