The Effects of Rising Food and Fuel Costs on Poverty in

Pakistan

Azam Amjad Chaudhry and Theresa Thompson Chaudhry

Abstract

This paper used PSLM and MICS household level data to analyze the impact of higher food and energy prices on the poverty head count in Pakistan.

Simulated food and energy price shocks present some important results:

• First, the impact of food price increases on Pakistani poverty levels is substantially greater than the impact of energy price increases.

• Second, the impact of food price inflation on Pakistani poverty levels is significantly higher for rural populations as compared to urban populations.

• Finally, food price inflation can lead to significant increases in Pakistani poverty levels: For Pakistan as a whole, a 20% increase in food prices would lead to an 8% increase in the poverty head count (from 36% to 44%).

Introduction and Motivation

The Situation in International Markets

• According to the World Bank:– Global food prices have risen by 83% from

February 2005 to February 2008– Food prices expected to peak in 2009, but

higher than average prices are expected to remain until 2015

Increase in International Food Prices

Figure 1. Food prices (Nominal $ Index, Jan 1995=100)

0

50

100

150

200

Jan-95 Jan-97 Jan-99 Jan-01 Jan-03 Jan-05 Jan-07

Source: DECPG

Increase in International Wheat Prices

The Situation in Pakistan:

• 20% increase in wheat prices between November 2007 and February 2008.

• Food and beverage prices had risen 14.7% from October 2006 to October 2007

• One-half of Pakistan’s population is considered to be “food insecure,” according to the World Food Programme

Causes: DEMAND SIDE

• Rising demand for food in India and China (especially meat, requiring large quantities of grain to raise)

• Bio-fuel initiatives in developed countries

• Speculation in commodities markets

Causes: SUPPLY SIDE

• High petroleum prices (affecting the price of fertilizer and transport costs)

• Disruptive weather patterns negatively affecting harvests in several regions

Additional local factors in Pakistan

• Hoarding by speculating millers and retailers

• Breakdown of the joint family system, putting nuclear families at greater risk when they face economic difficulty

Impacts on the poor:

• Large negative impacts on poor net consumers of food, because food is a large part of household budget.

• Potentially positive impact on net producers of food, if farmers have access to agricultural inputs and markets.

Data Sources

The data is taken from two different sources:

• Household level data from the Pakistan Social and Living Standards Measurement Survey (PLSM), 2004-2005 (using data on 14,100 households and 96,833 people)

• Household level data from the Punjab Multiple Indicators

Cluster Survey (MICS), 2003-2004 (using data on 29,342 households and 192,398 people)

Poverty Line and Head Count Ratio

• For PSLM data, poverty line used was Rs. 878.64 per person.

• For MICS data, the poverty line used was Rs. 750 per person.

• A household was characterized as poor if the average income of its members was below the poverty line.

• The poverty head count was calculated as the number of

people as a proportion on the population that had incomes below the poverty line. So a poverty head count of 0.30 implies that 30% of the population lies below the poverty line.

Various Categories of Expenditures and Budget Shares

Analysis looked at five categories of expenditures of each household, which were used to determine the budget share of each category of expenditure:

• (1) Food Expenditures • (2) Energy Expenditures (containing expenditures

on gas, electricity, cooking and heating oil and other fuel related expenditures)

• (3) Educational Expenditures • (4) Medical Expenditures• (5) Other Expenditures

Figure 3: Expenditure Shares on Major Budget Items by Income Per Capita Deciles in Pakistan (PSLM)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

FOOD

MEDICAL

EDUC

ENERGY

• Majority of household expenditures in Pakistan are made up of food expenditures which fall as a proportion of total expenditures as the income level increases.

• After food, the second most major expenditure category across households was energy expenditures

Figure 4: Expenditure Shares on Major Budget Items by Income Per Capita Deciles in Punjab (MICS)

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

FOOD

MEDICAL

EDUC

ENERGY

• In Punjab, the picture is similar, with Food making up the majority of expenditures and energy expenditures having the second largest budget share

Simulated Price Shocks

• In the first part of our analysis, we adjust per capita incomes given in the PSLM and MICS data sets for shocks to the price of food and energy.

• Given that the price rises will reduce real incomes, the price shocks bring additional households below the poverty line.

• We then recalculate what the new poverty head-count

ratio would be after each price shock. • Price shocks of 1%, 5%, 10%, and 20% on the price of

food and energy are simulated and the impact on the poverty head count is analyzed.

PSLM Results

Simulated Poverty Head Counts in Pakistan After Increases in the Prices of Food and Fuel

(PSLM Data)

Base Poverty Head Count for Pakistan = 0.364

1% Increase

5% Increase

10% Increase

20% Increase

Food Prices

0.368

0.383

0.402

0.441

Energy Prices

0.365

0.367

0.372

0.380

Simulated Poverty Head Counts in RURAL vs. URBAN Areas After Increases in the Prices of Food and Fuel

(PSLM Data)

Base Poverty Head Count for Rural Areas = 0.457

1% Increase

5% Increase

10% Increase

20% Increase

Food Prices

0.464

0.482

0.506

0.553

Energy Prices

0.459

0.463

0.469

0.478

Base Poverty Head Count for Urban Areas = 0.221

1% Increase

5% Increase

10% Increase

20% Increase

Food Prices

0.222

0.232

0.245

0.271

Energy Prices

0.221

0.222

0.225

0.232

Simulated Poverty Head Counts (by Province) after increases in FOOD prices

(PSLM Data)

1% Increase

5% Increase

10% Increase

20% Increase

PUNJAB Base Poverty Head Count = 0.364

0.368

0.379

0.395

0.427

SINDH Base Poverty Head Count = 0.371

0.376

0.392

0.411

0.453

NWFP Base Poverty Head Count = 0.392

0.394

0.409

0.434

0.476

BALOCHISTAN Base Poverty Head Count = 0.312

0.392

0.395

0.399

0.411

Simulated Poverty Head Counts (by Province) after increases in ENERGY prices

(PSLM Data)

1% Increase

5% Increase

10% Increase

20% Increase

PUNJAB Base Poverty Head Count = 0.364

0.365

0.367

0.372

0.379

SINDH Base Poverty Head Count = 0.371

0.372

0.376

0.378

0.385

NWFP Base Poverty Head Count = 0.392

0.392

0.395

0.399

0.411

BALOCHISTAN Base Poverty Head Count = 0.312

0.314

0.317

0.323

0.330

MICS Results

Simulated Poverty Head Counts in Punjab After Increases in the Prices of Food and Fuel

(MICS Data)

Base Poverty Head Count for Punjab = 0.412

1% Increase

5% Increase

10% Increase

20% Increase

Food Prices

0.428

0.439

0.458

0.501

Energy Prices

0.426

0.427

0.429

0.435

Simulated Poverty Head Counts in RURAL vs. URBAN Areas After Increases in the Prices of Food and Fuel

(MICS Data)

Base Poverty Head Count for Rural Punjab = 0.480

1% Increase

5% Increase

10% Increase

20% Increase

Food Prices

0.495

0.508

0.529

0.574

Energy Prices

0.493

0.494

0.496

0.500

Base Poverty Head Count for Urban Punjab = 0.306

1% Increase

5% Increase

10% Increase

20% Increase

Food Prices

0.325

0.333

0.350

0.389

Energy Prices

0.324

0.325

0.328

0.334

Important Results• For Pakistan, substantial changes in the poverty head

count accompanied the 10% and 20% increases in the food prices, increasing the poverty head count to 40.2% and 44.1% respectively. The impact of higher energy prices on poverty is substantially smaller that the impact of food prices.

• For Pakistan, a 10% increase in food prices pushes the

poverty head count to 50.5% while a 20% increase in food prices pushes the poverty head count to 55.3%. So substantial increases in food prices can be seen to have a dramatic impact on rural poverty levels (at least in the short run, since farmers should eventually benefit from selling at higher prices).

Important Results (cont’d)

• The impact of energy price increases on poverty is significantly smaller than the impact of food price increases, for all the provinces. The second interesting point worth noting is that though the impact of higher food prices is significant for all the provinces.

• Punjab level results obtained from the MICS dataset show that higher food prices lead to greater poverty in Punjab. 10% and 20% increases in energy prices lead to increases in the poverty head count from 41.1% to 45.8% and 50.1% respectively.

Conclusions• The results show that both food price shocks and energy price

shocks cause higher levels of poverty, though the analysis implies a greater short run impact for food price shocks (assuming that food and energy price shocks are of equal magnitude).

• The results show that the negative impact of food price shocks falls disproportionately on the rural poor, as opposed to the urban poor.

• The negative impact of food price shocks is significant across provinces.

• Food price inflation can lead to significant increases in poverty. For Pakistan as a whole, a 20% increase in food prices would lead to an 8% increase in the poverty head count, from 36% to 44%.

Policy Recommendations

• The government must ensure household food security in the face of dramatic food price shocks through targeted safety nets.

• The government must ensure food security by controlling domestic food prices.

• Government policies must focus on the supply side in order to stimulate greater food production in the medium and long terms.