Transcript Slides - KU Leuven

China’s Rural Economy
and the Path Towards a
Modern Industrial State
Scott Rozelle, UC Davis
Jikun Huang, CCAP, Chinese Academy of Sciences
Transformation Path
Percent
of Pop’n
in Ag.
Sector
Income per Capita
Overall Increase in Off-farm Work
100%
80%
60%
40%
In 2000: 45% of rural labor force have
jobs off the farm … more than 80% of
households have at least 1 person
working off the farm
20%
In 1980:
0%
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
only 4%
Year
worked full
off-farm busy season part time farm only
time off the
farm
Percent of Workforce Off-farm, by Age
Range
Age Range
16-20
21-25
26-30
31-35
36-40
41-50
1990
23.7
33.6
28.8
26.9
20.5
20.8
2000
75.8
67.2
52.5
47.6
43.3
37.6
Comparison of Off-farm work, by age
range
Workers Aged 41-50
Workers Aged 16-20
100%
100%
80%
80%
60%
60%
20%
20%
0%
0%
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
40%
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
40%
Year
Year
Specialize in
off farm work
20%
Migration
16%
12%
TVEs
8%
Self employed
4%
0%
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
Percent of Total Workforce
Change in Type of Off-Farm Work
Year
migrants
self-emp. migrants
self-employed
village wage earners
Percent of Workforce Off-farm, by Age
Range and Gender, poor areas
Age
Range
16-20
21-25
26-30
31-35
36-40
41-50
1990
M
15.8
39.6
38.0
35.8
26.9
26.9
F
8.8
5.4
4.1
2.3
2.7
2.4
2000
M
68.3
70.3
67.3
64.1
61.0
52.1
F
69.8
40.4
31.7
17.1
14.4
10.3
Transformation Path
Percent
of Pop’n
in Ag.
Sector
China: with only about 30-40
percent of population in urban
areas … if it is successful in
developing … it will necessarily
move along this rural-urban
transformation path … clearly the
progress during the reforms has
been great …
Income per Capita
Necessary but not Sufficient
• Shifting labor to off farm sector / shifting
population from rural to urban is necessary
• But not sufficient …
– Need to make sure those who are left behind
are taken care of …
– Need to make sure those who do not get jobs
off the farm are being invested in …
– So: process can continue …
– And, so: there is stability …
Role of Agriculture in Development
[Johnston and Mellor, AER, 1960]
•
•
•
•
•
Provide Labor for Industry
Provide Inexpensive Food
Provide Export Earnings
Provide Other Commodities
Provide Income
(it is happening)
(does not need)
(does not need)
(does not need)
– Demand for Domestic Markets
– Maintain or Increase Rural Incomes
– Poverty Alleviation
Goal of Presentation
• Understand how “healthy” is China’s agricultural
sector …
[Is it developing in a way that is going to facilitate the
nation’s transformation into a modern economy?]
• Can it provide rural population with the resources so
the rural population has income:
– In the present in order to:
• Raise domestic demand
• Maintain minimum standard of living
– In the future in order to:
• Invest in the move to the city
• Invest in human capital of children
Focus on Two Indicators
1. Rise in Productivity of Agriculture –
Institutional Change and Technology (for
rise in productivity)
2. Emergence of Commodity Markets –
Domestic and International – and Rise in
Specialization (for shifts to specialization
and rises in allocative efficiency)
– Illustrate how producers are doing: Case of
Horticulture
Transformation of Agriculture
Stage 1: get incentives right (property rights)
increase efficiency (new technology)
get prices right (markets)
-- Get incentives right (1978)
Part 1. New Technology
Increase output / unit of land
Raise technical efficiency
Part 2. Commodity Markets
Increase specialization
Raise allocative efficiency
Stage 1
Limitation of talk: focus on where China is – stage 1
Transformation of Agriculture
Stage 2:
allow for expansion of farm size
replace labor with capital
-- Get incentives right (1978)
-- New Technology/Investment
Increase output / unit of land
Mechanization
Substitute for ag labor
Raise labor productivity
Raise technical efficiency
-- Commodity Markets
Cultivate Land Rental Mkts
Increase specialization
Increase land quantity
Raise allocative efficiency
Raise labor productivity
Stage 1
Stage 2
Does China have the “technology
tools”?
Agricultural Productivity and the
Technology that is Driving it
Maize
200
170
TFP for Wheat in China, 1979-95
Wheat
Rice
140
110
80
17 year period: 3.5 - 4%
annually
Recent 10 years: 2% annually
50
1979 1981 1983 1985 1987 1989 1991 1993 1995 1997
Growth of Wheat, Rice and Maize TFP in China, 1979 to
1997
Contributions to Productivity
• Before 1984:
– ½ property rights reform
– ½ technology
– a bit to extension and education
• After 1984
–
–
–
–
ZERO to decollectivization
a bit to market emergence and education
none to extension
MOST to technology
Question: Does China have to technological base to
of Varieties
continue itsAverage
record in Number
TFP in future?
per Province per Year
Planted by Farmers, 1982-95
Number of “Major” Varieties per Province by Year
30
25
20
15
10
5
0
Rice
Wheat
Maize
Varietal Turnover
China’s Agriculture,
AverageinVariety
Turnover1983 to
1995 (proportion of area planted to new varieties)
0.5
All varieties turnover
every 2 to 5 years!!!
0.4
0.3
0.2
0.1
0
1983
1989
Rice
Wheat
1995
Maize
Tons per Hectare
Rise
of “Yield
Frontier”
in China’s
Experiment
Yield
“Frontier”
of Rice,
Wheat, and
Maize,
Stations for Rice, Wheat, and Maize
12000
10000
8000
6000
Around 2 percent
per year growth
4000
2000
0
1982
1984
1986
1988
Rice
Sown area weighted of sample provinces
1990
Wheat
1992
Maize
1994
1995
Total—2003: $300+ million
Plant biotech research expenditure
(million yuan in 1999 price, 22 institutes)
100
Total--1999: $100 million US
90
80
70
60
50
40
30
20
10
0
1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
2003
Performance of GM Rice in Field Trial
• Reduce pesticide use: - 40-50%
• Reduce labor input: - 6-9%
• Impacts on yield:
+ 6-8%
Scenario B: Bt cotton + GM rice
Impacts on Welfare (EV, million US$) in 2010
6000
5000
4000
Rice
3000
Rice +
Cotton
2000
1000
Cotton
0
Bt cotton
GM rice
Total
Summary
Part 1 of Stage 1
(technology tools)
•
•
•
•
Technology has been there
Farmers have been using it
Efficiency has been increasing
Incomes certainly rising
• Biotech: China trying to position itself so
technology will be available in coming
years
Part 2 of Stage 1:
“getting prices right”
Improvements to Domestic and
International Markets
Domestic Markets
Corn and Soybean
Marketing
Regions and Flows
Price (yuan)
Distance from port
4
3
2
1
y = -0.0002x + 2.0022
0
0
500
1000
1500
2000
2500
km
Changes in corn price across China as markets increase its
distance from port, 2000
Location of Major Corn Markets in
Greater Mississippi Valley
St. Louis
Port—New
Orleans
US Corn Prices
Percentage change in price for every
1000 kilometers of distance from port
Corn
Soybean
Rice
China
1998
1999
-4%
-10%
-10%
-4%
-9%
-9%
2000
-3%
-4%
-7%
-5%
-3.5%
8%
US – 1998
Guangzhou
(Shekou Port)
Dalian
Soybean Market Integration between Regions
Year
AH=> AH=> AH=> JL=>
SD
SaX
NX
TJ
HLJ=>
DL
GD=> GD=>
SaX
GS
1996
-5.36* -5.87* -4.84* -3.93* -4.01* -4.33* -4.83*
1997
-3.88* -4.33* -5.21* -4.15* -3.21* -3.82* -3.84*
1998
-4.13* -5.56* -4.84* -4.72* -4.67* -4.85* -4.05*
1999
-3.57* -3.73* -4.02*
-
-
-
-
Dicky-Fuller Test critical value rejecting null of no integration @ 5% (10%) level is -3.3 (-3.0)
Integration in China’s Markets (percent of
market pairs that have integrated price series)
1991-92
1997-00
2001-2003
Corn
46
93
100
Soybean
56
95
98
Conclusion: Interregionally China’s
Agricultural Commodity Markets are Fairly
Well Integrated!
But: How about between the Regional
Marketing Centers and China’s 800,000
Yellow River
villages?
Region
NE
Region
Yangtse
Region
South China
Region
To larger
market
Road between countryside
and market town
(“Distance to paved road”)
(“Distance to Market Town”)
Village
Regional
Market Town
Soybean, Maize and Rice Village Price Regression, 2000
Explanatory
Variable
Distance to the
nearest county
market
Village-Level
Shock to
Production
Other Variables not
shown
(1)
Soybean Price
(2)
Corn Price
(3)
Rice Price
-0.029
-0.00064
-0.0095
(2.37)**
(-1.63)*
(3.24)**
-0.04
0.12
0.081
(-0.17)
(-1.34)
(-1.02)
timing of sales / net purchase or seller /
International Markets
Nominal Protection Rates (%)
100
80
60
40
20
0
78-79
-20
Huang, 2001
80-84
Rice
85-89
Wheat
90-94
Maize
95-97
Soybean
98-99
WTO commitments are “radical”
• Aggressive tariff reductions on most
commodities
• Fairly sizeable TRQs and strict rules to make
sure they operate on market principles
• Low above-quota tariff bindings (around 60 to
70 percent … more like Australia and New
Zealan than Japan, Korea, or the EU)
• Strict rules against “dumping”
• Liberalize many rules that are keeping inputs out
Net
exports
12000
Labor intensive
crops
10000
8000
Exports –
fruits, meats,
aquaculture
6000
4000
2000
0
1985
1987
1989
1991
1993
1995
1997
1999
2001
- 2000
- 4000
- 6000
- 8000
-10000
Land Intensive
Land
Labor
crops
Imports –
soybeans,
cotton, hides
Agricultural Trade Balance by Factor Intensity, 1984
to 2002 (mil US$)
Summary
Part 2 of Stage 1
(getting prices right)
• Domestic markets have improved remarkably
• Price signals getting through to farmers
• International markets also integrating with world
… China beginning to trade (exports and imports)
according to their comparative advantage
• Increased in allocative efficiency and incomes
• at least in theory … how about in practice?
The Case of Horticulture
• So how have producers inside China fared in this
process?
• Are they able to respond to the signals of the food
economy that are being transmitted from the urban
sector?
• Who is benefiting? Is household welfare
improving?
• What types of households? Rich or poor? Those
in the periphery or those in more remote areas?
Rise of Supermarkets:
Increasing Store Units
Number of Stores
60000
20 to 30 percent
annual growth
between 1998
and 2002
50000
40000
30000
20000
10000
0
1990
1992
1994
1996
1998
2000
2002
And
growing!
Supermarket Sales
$US Billions
Around 40
percent annual
growth between
1998 and 2002
60
50
40
30
20
10
0
1990
1992
1994
1996
1998
2000
2002
Share in National Retail
Percent of Total
National Retail Sales
12
10
8
6
4
2
0
1990
1992
1994
1996
1998
World Bank: “Retail Olympics”
2000
2002
Nearly
50% of
urban food
purchases
Summary of the Nature of Changes
in China’s Demand for FN&Vs
• Large increase in demand
– incomes
– falling prices
– migration
• Increase in access to export markets
• Rise of Supermarkets
Producer response:
Increasing Sown Areas of Vegetables
in China and California (1000 ha)
China
16000
15000
14000
13000
12000
11000
10000
9000
8000
7000
California
1000
800
600
400
200
Every 2 years, + 1 California
1991
1992
1993
1994
1995
1996
1997
1998
1999
0
2000
Trends of Cultivated Areas of Fruits and Nuts
in China and California (1000 ha)
China
California
8000
8000
6000
Campaign to 6000
upgrade
4000
quality
4000
2000
2000
0
1991 1992
1993 1994
1995 1996
1997 1998
1999 2000
China has Higher Share of Land in
Orchards than Most Other Countries
6.0
5.0
4.0
3.0
2.0
1.0
0.0
EU-15
France
USA
India
China
In summary: at least at the aggregate level, there has been a huge
rise in the production of horticulture crops – traditionally a crop
that yields higher levels of profits (and/or return to hh labor)
But, what does this mean for small, poor farmers?
• Accepted (?) Theory:
To meet rising demand, supermarkets will go to those
producers that can produce a standard, safe product
with a great deal of reliability (at a reasonable price)
…
• Observed behavior, worldwide:
Supermarkets work increasingly with large, wellmanaged growers … often larger, well-educated
producers … supermarkets often have been accused of
hurting the poor … and letting the rich get richer
Important Questions (again)
• Can China’s small, poor farmers (in this
environment that we described above) benefit
from the rise in demand from consumers,
supermarkets and exports?
• Who is responsible for the emergence of China’s
horticulture economy?
• What should we expect to occur in the future?
To provide some answers
• Need to get good information
• Understand the sector:
– Profile of Producers
– Profile of Those the Procure (including Supermarkets /
Cooperatives / Small Traders)
– Role of the Government
• Explain the rise with a conceptual framework
[this should help us try to predict how China’s
horticulture economy will evolve in the coming years]
Location of Study’s Sample Site
Greater Beijing
Area
= other major
horticulture sites
Spatial Sampling Approach for China Horticulture Survey
140 km
Choosing our sample: Consists of 6 steps
100
80
60
40 km
x
= City Center …
Beijing (Forbidden City)
Step 1: Develop the Spatial
Stratas
= First Circle is 6th
Ring Road
(like beltway in DC)
Spatial Sampling Approach for China Horticulture Survey
Choosing our sample: Consists of 6 steps
40 km
60x
80
100
140 km
Step 1: Develop the Spatial
Stratas
Outside ring: Radius of 140
km means that the diameter
of circle is about 170 miles
(from Sacramento to
Fresno / Half Moon Bay to
Turlock)
This is the outer ring of our Study’s
Sample area …
equivalent to an area the size of
Denmark!
Greater Beijing
Area
Step 2:
Superimpose a 36o angle on the set of
concentric circles, creating a “wedge” with 5 arcs
(repeat 10 times or 10 wedges x 36o = 360o)
36o
x
x
Step 3: for each 36o arc
x
x
x
40
60x
80
100
140
(5 per wedge), choose a
random number, R,
between 0 and 36 (e.g.,
R=15), mark with a dot ( )
repeat 5 times—one for
each circle (5 points per
wedge)
x
Step 4: Using GIS map/coordinates of Greater Beijing, choose the
town (x) that is the closest linear distance to the dot ( ); repeat 5
times/wedge or 5 sample towns/wedge
36o
x
x
x
x
x
x
x
x
x
x
x
x x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
40xx
x
x
60x
x
80
x
100
x 140
x
x
Step 5: Repeat
selection of sample
towns 10 times (once
for each of 10 wedges
making up the circle)
x
x
x
x
Total Town Sample Size:
x
x
5 circles x
x
x
10 towns per circle =
x
x
50 towns
(or Nt = 50)
Also need to get populations of ALL towns in each strata – for weighting
Step 6. Choosing the Sample Villages
First: get a list of all villages (on average about 12
villages per town – v1 to v12)
v1
X
Each sample
town (x)
v2
v3
v4
Second: choose 4
sample villages (v)
per town
(randomly selected
from all villages in
each sample town)
Total Village Sample Size:
4 villages per each of 50 towns =
200 villages
(or Nv = 200)
The Household Sample (n=500)
Step 1. From the 200 sample villages, randomly choose 50 villages
(1 out of 4) – these are called the “household survey villages.”
Step 2. From a comprehensive list of all households (including
those with and without “hukou” or village resident permits) generate
two lists:
a.) those that produce the horticulture crop (“hort producers”);
b.) those that do not (“non-hort producers”) including all those that
farm and do not farm.
Step 3: randomly choose sample households:
7 hort producers / 3 non-hort producers
Total household sample size:
50 villages x 10 households/villages = 500 households
The Village/Household Surveys
• Village/Household Characteristics:
• Horticulture growing history (2000-2004)
• Marketing channels
(2000-2004)
• Technology shifts
(2000-2004)
The typical farming household in FN&V-growing
regions in China, 2005
Household characteristics
HH size
Age of HH head
(person)
4
(year)
42 (male)
(year)
7
(%)
50
Education and training
Education of HH head
Share of HH head with ag
extension training
Off-farm job
(%)
Share of HH head who has
off-farm jobs (in factory)
(%)
20
Share of household head who
has off-farm jobs (self
employed)
(%)
25
Assets: Farm equipment
(US$)
402
Housing
(US$)
7882
The typical fruit growing farm in China, 2005
Farm Characteristic
Farm size
(ha)
0.4 ha
Distinct Plots
(number)
5 plots
Number of crops
(diversification)
(number)
3 crops (horticulture makes up ½)
Contracted from “collective”
(%)
96%
Rented from other farmer
(%)
4%
Share of area decided by
farmer
(%)
95%
Own Labor Days / ha
(mandays)
312
Hired Day / ha
(mandays)
42
Wage
(US$/day)
3.2
Ownership and Control
Labor
Degree of Commercialization of
Fruit, Nut and Vegetable Farmers in
Greater Beijing Area, 2004
Consumed at home (3%)
Sales as a Share of Production (97%)
Data Source: authors’ survey
And, these small farmers are mostly
“on their own”
Cooperative movement still small
8%
Percent of villages with
Cooperatives / FAs
2%
Percent of households that
belong to Cooperatives / FAs
In Greater Beijing: only 4% of villages had cooperative /
only 8% of farmers (China Horticulture Survey)
Comparing with other nations:
Percentage of Households
Participating in Coops/FAs
100
80
60
40
20
0
US (early
1900s)
Japan
(1950s)
Korea
(1970s)
China
(now)
Summary – nature of China’s farms
• China’s farms are:
–
–
–
–
–
extremely small
highly diversified (both on farm and between on/off farm)
more land / less off farm jobs in poorer areas
cooperatives/FAs are rare
operate in an environment that is highly marketized
• So leads to two questions (again):
– Are these producers able to meet China’s rising demand for
Fruits, Nuts and Vegetables?
– Which ones?
Distribution of Fruit, Nuts and
Vegetables in greater Beijing area
• More than 80 percent of
sample villages have
households that produce
horticulture crops
–
–
–
–
Fruit
Nuts
Vegetables
None
52%
14%
15%
19%
None
Vege
Nuts
Fruit
Rise over time – Vegetables
(greater Beijing area)
• Share of “cultivated
area” (not including
orchard area) sown to
vegetable crops
Percent
14
12
10
8
• About 1/3 of this area
is in greenhouses …
• Data source: authors’
survey data
6
4
2
0
2000
2004
Rise over time – Fruit
(greater Beijing area)
• Share of “cultivated
area” plus “orchard
area” planted to fruit
orchards
Percent
45
40
35
30
• Does not include nuts
25
20
• Data source: authors’
survey data
15
10
5
0
2000
2004
Rise of specialization (entire nation)
• In a recent survey of
650 communities in
China, we asked the
leaders:
– Do farmers in your
village specialize in the
production of a field
crop, tree crop or
livestock commodity?
35
30
25
20
15
10
5
0
1995
2004
Data source: China National Rural Economy Survey (CCAP)
Where are they being grown?
Inside Ring / Outside Ring
Share of Cultivate Area
140
“Mostly here”
80
60
40
20
0
40 km ring
40
140 km ring
Area / Village (acres)
40
30
20
10
0
40 km ring
140 km ring
These figures for vegetables in 2000 / same for F&N’s
Who are growing them?
Rich or Poor?
Share of Cultivate Area
• Per capita income:
“Rich” -- $7.28/day
150
100
50
0
Poor -- $1.25/day
Rich
“They do”
Area / Village (acres)
Fruits / Nuts / Vegetables are
being increasing grown by
poor farmers in relatively
remote communities!
Poor
60
40
20
0
Rich
Poor
These figures for vegetables in 2000/ same for F&N’s
The Buying Landscape:
Who might be out procuring the crop?
• Supermarkets / Coops
• Processing Firms (e.g., apple juice crushers)
• Professional Supply Firms (on contract to exporters /
supermarkets / hotels / restaurants)
• Consumers (“u pick ‘em” / bought by companies/gov’t
agencies for distribution to their employees as bonuses)
• Small traders
[2 to 6 people working together / No warehouse; no office; no
license; often no transport / Pay cash on the spot / From
Henan; Hubei; Anhui / Poor (will work for $2-3/day) ]
Profile: Typical 6-man Trading “Firm”
Private, “contract”
truckers
Division I
Small
Trader:
Farmer’s
field
Finds
seller /
contacts
trucker /
buys with
cash
Partners: in
Small
Trader -Partner
Small
Trader -Partner
Small
Trader -Partner
Div II
Networks
/ process
inside
China’s
cities
(>90%
private)
other villages
Going from village to village
In the city wholesale mkt
Small Trader-dominated System (2004)
Percent of all purchases
100
80
60
40
20
zero
0
Super
markets
/ coops
Process
Firms
Supply
Firms
U-pick /
Unit
buys
Small
Traders
Note; -- Supermarkets did not procure in any villages (ZERO)
-- Zero procured by coop
“In-home Service” (2004)
Percent of all purchases
100
80
60
40
20
0
Wholesale
Mkt
Periodic
Mkt
Wet Mkt in
City
In the
Village
Note; -- “In the village” = Off the tree + From Home + Road-side
-- Share sold in wet markets in cities down over time
Second Buyer in the Wholesale Chain
Still Small Trader-dominated (2004)
Percent of all purchases
100
80
51%
60
40
20
0
Super
markets
/ coops
Process
Firms
Supply
Firms
Consumer
Small
Traders
Note; -- Supermarkets only directly involved in 3% of “second trades”
-- Share sold to processing firms rising over time
Most common marketing chain
for F,N&V in China
Small
Traders
Small
Traders
Farmers
In rural areas
Networks
inside
China’s
cities
(mostly
starting at
urban
wholesale
markets)
In urban areas
Summary: Participants in China’s
Fruit, Nut and Vegetable Markets
Farmer
Private
95% own decisions
$2/day
Small Trader*
Private
$3/day
Trucker*
Private
$2.5/day
Second buyer
>90% private (?)
?
* 2000 Rural China Income and Land Survey (CCAP, UC Davis and U. of Toronto)
Potential Influence of Government
• On-farm (nearly unregulated: few projects or
low-interest rate loans / very little extension)
• Trading (nearly unregulated: pay fee for stall
space in city-run markets / FN&V traders are
untaxed and unlicensed)
• Trucking (nearly unregulated: one-time (high)
fees and taxes when buying their truck …
gasoline bought at world market rates … untaxed
and unlicensed)
Why don’t buyers make demands of farmers?
• Extent of formal contracting: Almost ZERO
• When we asked farmers if traders / procurement
agents were able to dictate their application of
fertilizers and pesticides, the most common
answer was:
– A laugh
– A pause (as if they did not understand the question)
… and then: “of course not … how could the trader
ever observe my actions?”)
Raises a series of questions
• Where are the supermarkets?
• Why is this system so completely
dominated by hundreds of thousands of
small, poor traders?
• Why is it that China’s small, poor and
remote farmers appear to be benefiting?
• Is the literature wrong? Do we need a new
theory?
FN&V production and marketing
with Chinese characteristics
China food economy is characterized by 5 elements:
1.
2.
3.
4.
5.
Small farmer-dominated / land is equally distributed (within
regions) / limited rental markets
No / few cooperatives
Unregulated trading sector, dominated by small, poor traders
(with a low opportunity cost operating in an economy that
has fairly good roads and communications)
Poor farmers (regionally—that is, in remote areas) are
endowed with relatively more labor and land
China is still a relatively poor, developing country, even in
the cities  premium for high quality (safe) food relatively
low [consumers are always on the look out for a “good buy”]
Implications of these 5 characteristics
• Supermarkets can not compete with small traders in
procurement
– contracting costs are too high / the monitoring and coordination
effort of doing so for millions of farmers with 1/2 acre orchards
are almost inconceivable / premium is still too low to justify the
high expense (i.e., consumers will not pay for the quality/safety)
• Supermarkets can procure reliably on urban wholesale
markets
– small traders keep abundant supply of FN&Vs flowing to
China’s urban wholesale markets and do so at a very low price
(markets are integrated, competitive and efficient)
• Exporters need to develop a very sophisticated, highly
labor intensive ways to manage the FN&V production
– but they can afford to do so, since the premiums are so high (e.g.,
S. Korea’s tariff on many of China’s FN&Vs are greater than
500%)
So is the literature wrong? No!
Just too far ahead of his time!
• According to our “explanation,” let any of the 5 elements break
down (or disappear) and we likely will see the emergence of more
“normal, super market-dominated” marketing patterns
• Do thought experiments
–
–
–
–
–
–
Promote coops
Allow for rental of large tracts of land
Increase migration opportunities for the poor in remote areas
Raise wages [both farmers and small traders]
Ban small traders from procurement channel (e.g.,, by requiring licenses)
Get rich (raise premium for food safety)
[all of these likely lead to emergence of the direct participation of
supermarkets in the production and in-field procurement of
FN&Vs … probably in areas nearer China’s cities (because it is
more convenient; lower transaction costs)]
Final Summary
So where is China? What does it
need to do to keep moving?
Percent
of Pop’n
in Ag.
Sector
Income per Capita
Stage 1 – Development Strategy
• Get Property Rights Right (1978)
• Provide Technology
• Get Price Right
Summary of this presentation:
China is doing this well … mostly … so far
What do they need to do in next stage?
Transformation of Agriculture – Stage 2
In the longer run, the challenge may be more complicated!
Continue!
New Technology/Investment
Added Challenge
Mechanization
Increase output / unit of land
Substitute for ag labor
Raise technical efficiency
Raise labor productivity
Commodity Markets
Cultivate Land Rental Mkts
Increase specialization
Increase land quantity
Raise allocative efficiency
Raise labor productivity
Stage 2
(continued)
Stage 2
Final Lesson
• It is exciting to follow the development of a
country like China …
• It is complicated to follow it as a researcher
… it is dynamic / it is multidimensional
• Encourage students / faculty / research staff
to invest in the study of countries, like
China … and beyond China