Background
Objectives and purpose
Theoretical framework
Methodology
First results
Price transmission to local food prices: vulnerability
mapping
Lukas Kornher and Dr. Matthias Kalkuhl
Center for Development Research
January 31, 2013
Price transmission to local food prices
Background
Objectives and purpose
Outline
1
Background
2
Objectives and purpose
3
Theoretical framework
4
Methodology
5
First results
Price transmission to local food prices
Theoretical framework
Methodology
First results
Background
Objectives and purpose
Theoretical framework
Methodology
Why price transmission research matters?
Driver of local food prices (transmission as trigger)
Forecasting of local prices
Facilitates policy responses
Price transmission to local food prices
First results
Background
Objectives and purpose
Theoretical framework
Methodology
Who is vulnerable to international price shocks? - Cereal import
dependency?
−− > but are prices transmitted? trade necessary for transmission?
Price transmission to local food prices
First results
Background
Objectives and purpose
Theoretical framework
Methodology
State of research - there is a lot (e.g.maize):
Source: Minot, 2011; Greb et. al, 2012; Robles, 2010; Conforti, 2004.
But results are mixed and studies difficult to compare.
Price transmission to local food prices
First results
Background
Objectives and purpose
Theoretical framework
Methodology
Understand the price transmission mechanism better
Idenfity determinants of price transmission
Empirically test specific hypothesis regarding price transmission
Assess vulnerability to international price shocks
Calculate price transmission elasticities
Price transmission to local food prices
First results
Background
Objectives and purpose
Theoretical framework
Methodology
Research framework
Price transmission due to market integration - arbitrage
Transmission of price signals without physical trade
Price transmission to local food prices
First results
Background
Objectives and purpose
Theoretical framework
Methodology
First results
Theory
pit = pjt + m (Fackler and Goodwin, 2002)
Arbitrageurs will ship commodities from j to i until the price margin
equals the transaction costs m
and
pt + kt = βEt [pt+1 ] (Williams and Wright, 1991)
Prices between different periods are interrelated through storage; expected
future price expectations affect current prices
Price transmission to local food prices
Background
Objectives and purpose
Theoretical framework
Methodology
First results
Vulnerability to international price shocks
Why is vulnerability mapping important?
Country specific price forcasting
Distribution of food aid and CCT
Early warning for food crisis
How to measure vulnerability to international price shocks?
1
Estimate the actual transmission of international prices
2
Make transmission endogenous and conditional on determinants
Price transmission to local food prices
Background
Objectives and purpose
Theoretical framework
Methodology
First results
Determinants of price transmission
Directon of price movement matters (Ianchovichina et. al, 2012)
Differences between countries and crops (Robles, 2010; Minot, 2011)
Import/ export position (Greb et al., 2012)
Transaction costs (Barrett and Li, 2002; Baulch, 1997).
Policies
Seasonality (Cudjoe et. al, 2009)
Supply (Blinder, 1982; Mancini, 1978)
Price transmission to local food prices
Background
Objectives and purpose
Theoretical framework
Methodology
First results
How to calculate vulnerability from determinants
Country specific factors (taste, geography, historical relations, overall
inflation)
+ Crop specific factors
+ Transaction costs (tariffs, freight rates)-t
+ Level of supply within country (stocks & production)-t
+ Level of involvement in trade-t
+ National food related policies-t
= Total vulnerability
−− > Distinguish between price trend, volatility, and spikes
Price transmission to local food prices
Background
Objectives and purpose
Theoretical framework
Methodology
First results
Approach:
Trend, volatility, and spikes may have different causes
(Wright, 2011; von Braun and Tadesse, 2012)
1
Trend
Demand & supply, long-term food policies, trade balance, transaction
costs
1
Volatility
Low supply, trade balance, international prices, seasonality
1
Spike
Supply shocks, stocking & trade policies, international prices, low stocks
Price transmission to local food prices
Background
Objectives and purpose
Theoretical framework
Own price data base
1
FAO GIEWS
2
FEWS NET
3
WFP VAM
4
National sources (COUNTRY STAT, etc.)
Price transmission to local food prices
Methodology
First results
Background
Objectives and purpose
Theoretical framework
Methodology
First results
Annual panel model - determinants
Merge monthly prices with annual supply & demand data
The model (Mirzabaev and Tsegai, 2012):
Pit = IntPit + CP Iit + P rodiy + Stockiy + Demandit + National and international prices and CPI are calculated based on
monthly observations
Prices refer to one marketing year (USDA)
Production and beginning stocks resemble supply at the beginning of
the marketing year
Country and crop fixed effects control for unit specific factors
Price transmission to local food prices
Background
Objectives and purpose
Theoretical framework
Methodology
Definition:
y : marketing year m : month of marketing year
1
Trend - change in annual average prices
1 12
12 Σm=1 Pmy
1
−
1 12
12 Σm=1 Piy−1 ?
Volatility - coefficient of variation within one marketing year
1 12
Σm=1 Pmy
σPy / 12
1
Spike - abrupt price change at an extraordinary level
if
Pm −P
P
Price transmission to local food prices
> 0.1 &
Pm −Pm−1
Pm−1
> 0.15?
First results
Background
Objectives and purpose
Theoretical framework
Methodology
Volatility transmission
Why should volatility be transmitted?
Intuitively, when prices transmit, price volatility also transmit
Evidence:
eg. Rapsonmanikis and Mugera (2011) and Hu et. al (2012)
Basic model:
volPd = volPInt + volFPI +
Price transmission to local food prices
prod.
pop
+
stocks
pop
+
imp.
pop
First results
Background
Objectives and purpose
Theoretical framework
Methodology
Volatility transmission
vol international
vol fpi
(1)
vol marketing year
0.161***
(5.38)
(2)
vol marketing year
0.150***
(5.02)
(3)
vol marketing year
0.223***
(7.65)
0.557***
(7.20)
vol cpi
0.909***
(7.54)
cp beginning stocks
-0.797**
(-2.20)
-0.906**
(-2.55)
-0.763**
(-2.13)
cp production
-0.336**
(-2.53)
-0.346***
(-2.66)
-0.401***
(-2.98)
vol oil price
0.0874***
(3.40)
0.106***
(4.15)
0.0928***
(3.71)
cp imports
1.107
(1.38)
1.096
(1.39)
1.576**
(2.25)
import ratio
0.00730
(0.22)
0.00394
(0.12)
-0.00393
(-0.13)
cp imports*import ratio
-1.249
(-1.44)
962
-1.194
(-1.41)
932
-1.385*
(-1.69)
1075
N
t statistics in parentheses
* p < 0.10, ** p < 0.05, *** p < 0.01
Price transmission to local food prices
First results
Background
Objectives and purpose
Theoretical framework
Methodology
First results
Crop/ continent specific estimates
vol international
vol fpi
cp beginning stocks
cp production
vol oil price
cp imports
import ratio
cp imports*import ratio
N
maize
0.206**
(2.11)
0.575***
(3.77)
-0.942
(-1.47)
-0.395
(-1.16)
0.00538
(0.08)
2.491*
(1.85)
-0.103
(-1.33)
-1.624
(-0.98)
268
rice
0.216***
(8.50)
-0.00787
(-0.07)
-0.436
(-0.91)
-0.365
(-1.07)
0.100***
(3.31)
-0.504
(-0.45)
0.0431
(1.24)
-0.520
(-0.53)
332
t statistics in parentheses
* p < 0.10, ** p < 0.05, *** p < 0.01
Price transmission to local food prices
wheat
0.143
(1.63)
0.792***
(3.43)
-0.198
(-0.15)
-0.192
(-1.08)
0.0933**
(2.26)
-1.642
(-0.71)
0.165**
(2.36)
-0.387
(-0.17)
164
africa
0.157***
(3.41)
0.532***
(5.68)
-0.591
(-1.01)
-0.578**
(-2.18)
0.0785*
(1.89)
-0.0794
(-0.05)
0.0124
(0.28)
-0.986
(-0.71)
552
asia
0.163**
(2.07)
0.722**
(2.37)
-0.161
(-0.23)
-0.170
(-1.65)
0.114**
(2.59)
2.110
(1.23)
-0.0427
(-0.35)
-0.887
(-0.41)
95
latin
0.0472
(0.62)
0.541
(1.22)
0.173
(0.20)
0.961
(1.20)
0.122**
(2.33)
-0.0300
(-0.01)
-0.0728
(-0.26)
7.914
(1.12)
111
middle
0.181***
(3.17)
0.875***
(2.87)
-2.053 ***
(-2.64)
-0.824
(-1.44)
0.0848*
(1.89)
2.124*
(1.91)
-0.0703
(-0.89)
-1.434
(-1.07)
204
Background
Objectives and purpose
Theoretical framework
Methodology
Transmission and trade
autarkic
-0.0778
(-0.45)
importer
0.170***
(5.54)
exporter
-0.0600
(-0.53)
switch trade
0.149
(1.20)
vol fpi
1.053***
(4.30)
0.573***
(6.14)
1.117***
(5.32)
0.436***
(2.73)
cp beginning stocks
-13.36**
(-2.26)
-0.969*
(-1.84)
-0.211
(-0.12)
-0.308
(-0.39)
cp production
-0.543
(-0.82)
-0.554**
(-2.05)
-0.252
(-1.13)
-0.349
(-0.78)
vol oil price
0.307**
(2.59)
0.131***
(4.76)
0.152
(1.64)
-0.0422
(-0.52)
vol international
cp imports
1.365
(1.57)
9.394**
(2.08)
import ratio
0.00592
(0.18)
-0.0591
(-0.28)
cp imports*import ratio
-1.450
(-1.60)
755
-29.64**
(-2.34)
144
N
120
t statistics in parentheses
* p < 0.10, ** p < 0.05, *** p < 0.01
Price transmission to local food prices
167
First results
Background
Objectives and purpose
Theoretical framework
Methodology
Transmission and trade
vol international
vol fpi
cp beginning stocks
cp production
production & stocks
0.207***
(5.58)
0.550***
(7.11)
-0.612
(-1.33)
-0.230
(-1.47)
supply
vol oil price
cp imports
import ratio
cp imports*import ratio
vol*stocks
vol*production
0.0892***
(3.47)
1.307
(1.61)
0.00606
(0.18)
-1.441*
(-1.66)
-1.351
(-0.57)
-0.795
(-1.47)
vol*supply
N
962
t statistics in parentheses
* p < 0.10, ** p < 0.05, *** p < 0.01
Price transmission to local food prices
total supply
0.207***
(5.58)
0.549***
(7.11)
landlocked
0.102
(1.40)
0.906***
(6.72)
-0.596
(-0.89)
-0.209
(-0.64)
coastal
0.194***
(5.98)
0.335***
(3.50)
-0.721
(-1.49)
-0.252
(-1.60)
-0.289**
(-2.23)
0.0875***
(3.42)
1.225
(1.52)
0.00757
(0.23)
-1.407
(-1.62)
0.0787
(1.38)
8.315**
(2.14)
-0.0988
(-1.32)
-4.921
(-0.74)
0.0808***
(2.85)
0.573
(0.71)
0.0361
(0.86)
-0.983
(-1.13)
-0.871**
(-2.09)
962
244
718
First results
Background
Objectives and purpose
Theoretical framework
Methodology
First results
Preliminary conclusion
Domestic price (volatility) can be explained by international price
(volatility) to a significant portion
Differences between crops and to lesser extent between continents
Import countries experience highest degree of price transmisson
Supply reduces price transmission
Next steps
Complement price data base
Run panel regression for spikes and trend
Include further explanatory variables (interaction effect)
Verify results using other fundamentals data
Price transmission to local food prices
Background
Objectives and purpose
Thank you for your attention!
Comments?
Questions?
Suggestions?
Price transmission to local food prices
Theoretical framework
Methodology
First results