China’s Rural Economy and the Path Towards a Modern Industrial State
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Transcript of China’s Rural Economy and the Path Towards a Modern Industrial State
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
0%
20%
40%
60%
80%
100%
1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Year
off -farm busy season part time farm only
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
In 1980: only 4% worked full time off the farm
Percent of Workforce Off-farm, by Age Range
Age Range 1990 2000
16-20 23.7 75.8
21-25 33.6 67.2
26-30 28.8 52.5
31-35 26.9 47.6
36-40 20.5 43.3
41-50 20.8 37.6
Comparison of Off-farm work, by age range
Workers Aged 16-20
0%
20%
40%
60%
80%
100%
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Year
Workers Aged 41-50
0%
20%
40%
60%
80%
100%
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Year
Specialize in off farm work
Change in Type of Off-Farm Work
0%
4%
8%
12%
16%
20%
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
Year
Per
cen
t of
Tot
al W
ork
forc
e
migrants self-emp. migrants self-employed village wage earners
Migration
Self employed
TVEs
Percent of Workforce Off-farm, by Age Range and Gender, poor areas
Age 1990 2000 Range M F M F 16-20 15.8 8.8 68.3 69.8 21-25 39.6 5.4 70.3 40.4 26-30 38.0 4.1 67.3 31.7 31-35 35.8 2.3 64.1 17.1 36-40 26.9 2.7 61.0 14.4 41-50 26.9 2.4 52.1 10.3
Transformation Path
Percent of Pop’n in Ag. Sector
Income per Capita
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 …
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 (it is happening)• Provide Inexpensive Food (does not need)• Provide Export Earnings (does not need)• Provide Other Commodities (does not need)• Provide Income
– 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)
Part 2. Commodity Markets
Increase specialization
Raise allocative efficiency
-- Get incentives right (1978)
Part 1. New Technology
Increase output / unit of land
Raise technical efficiency
Stage 1
Transformation of Agriculture
Stage 2: allow for expansion of farm size
replace labor with capital
-- Commodity Markets
Increase specialization
Raise allocative efficiency
-- Get incentives right (1978)
-- New Technology/Investment
Increase output / unit of land
Raise technical efficiency
Mechanization
Substitute for ag labor
Raise labor productivity
Cultivate Land Rental Mkts
Increase land quantity
Raise labor productivity
Stage 1 Stage 2
Limitation of talk: focus on where China is – stage 1
Does China have the “technology tools”?
Agricultural Productivity and the Technology that is Driving it
TFP for Wheat in China, 1979-95
50
80
110
140
170
200
1979 1981 1983 1985 1987 1989 1991 1993 1995 1997
17 year period: 3.5 - 4% annually
Recent 10 years: 2% annually
Growth of Wheat, Rice and Maize TFP in China, 1979 to 1997
Rice
Wheat
Maize
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
Average Number of Varieties per Province per Year
Planted by Farmers, 1982-95
0
5
10
15
20
25
30
Ri ce Wheat Mai ze
Question: Does China have to technological base to continue its record in TFP in future?
Number of “Major” Varieties per Province by Year
Average Variety Turnover
0
0. 1
0. 2
0. 3
0. 4
0. 5
1983 1989 1995
Ri ce Wheat Mai ze
All varieties turnover every 2 to 5 years!!!
Varietal Turnover in China’s Agriculture, 1983 to 1995 (proportion of area planted to new varieties)
Yield “Frontier” of Rice, Wheat, and Maize,
0
2000
4000
6000
8000
10000
12000
1982 1984 1986 1988 1990 1992 1994 1995
Tons
per
Hec
tare
Ri ce Wheat Mai ze
Sown area weighted of sample provincesSown area weighted of sample provinces
Rise of “Yield Frontier” in China’s Experiment Stations for Rice, Wheat, and Maize
Around 2 percent per year growth
Plant biotech research expenditure(million yuan in 1999 price, 22 institutes)
0
10
20
30
40
50
60
70
80
90
100
1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 19992003
Total--1999: $100 million US
Total—2003: $300+ million
Performance of GM Rice in Field Trial
• Reduce pesticide use: - 40-50%• Reduce labor input: - 6-9%• Impacts on yield: + 6-8%
Scenario B: Bt cotton + GM riceImpacts on Welfare (EV, million US$) in 2010
0
1000
2000
3000
4000
5000
6000
Bt cotton GM rice Total
Cotton
Rice
Rice + Cotton
SummaryPart 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
Distance from port
y = -0.0002x + 2.00220
1
2
3
4
0 500 1000 1500 2000 2500
km
Pri
ce (
yuan
)
Changes in corn price across China as markets increase its distance from port, 2000
Port—New Orleans
Location of Major Corn Markets in Greater Mississippi Valley
St. Louis
U.S Soybean (1985) price
480.00
490.00
500.00
510.00
520.00
530.00
540.00
550.00
560.00
570.00
580.00
Sample markets: distance from coast
Pric
e ($
/100
bu)
US Corn Prices
Percentage change in price for every 1000 kilometers of distance from port
Corn Soybean Rice
China 1998 -4% -10% -10%
1999 -4% -9% -9%
2000 -3% -4% -7%
US – 1998 -5% -3.5% 8%
Dalian
Guangzhou (Shekou Port)
Soybean Market Integration between Regions
Year AH=>
SD
AH=>
SaX
AH=>
NX
JL=>
TJ
HLJ=>
DL
GD=>
SaX
GD=>
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
NE Region
Yellow River Region
Yangtse Region
South China Region
Conclusion: Interregionally China’s Agricultural Commodity Markets are Fairly Well Integrated!
But: How about between the Regional Marketing Centers and China’s 800,000 villages?
Village
Road between countryside and market town
Regional Market Town
To larger market
(“Distance to paved road”)
(“Distance to Market Town”)
Soybean, Maize and Rice Village Price Regression, 2000
Explanatory (1) (2) (3)Variable Soybean Price Corn Price Rice Price
Distance to the nearest county market
-0.029 -0.00064 -0.0095
(2.37)** (-1.63)* (3.24)**
Village-Level Shock to Production
-0.04 0.12 0.081
(-0.17) (-1.34) (-1.02)
Other Variables not shown
timing of sales / net purchase or seller /
International Markets
Nominal Protection Rates (%)
-20
0
20
40
60
80
100
78-79 80-84 85-89 90-94 95-97 98-99
Rice Wheat Maize Soybean
Huang, 2001
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
- 10000
-8000
-6000
-4000
-2000
0
2000
4000
6000
8000
10000
12000
1985 1987 1989 1991 1993 1995 1997 1999 2001
Land Labor
Agricultural Trade Balance by Factor Intensity, 1984 to 2002 (mil US$)
Labor intensive crops
Land Intensive crops
Net exports
Imports – soybeans, cotton, hides
Exports – fruits, meats, aquaculture
SummaryPart 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
0
10000
20000
30000
40000
50000
60000
1990 1992 1994 1996 1998 2000 2002
20 to 30 percent annual growth between 1998 and 2002
Number of Stores
Supermarket Sales
0
10
20
30
40
50
60
1990 1992 1994 1996 1998 2000 2002
Around 40 percent annual growth between 1998 and 2002
$US Billions
And growing!
Share in National Retail
0
2
4
6
8
10
12
1990 1992 1994 1996 1998 2000 2002
Percent of Total National Retail Sales
Nearly 50% of urban food purchases
World Bank: “Retail Olympics”
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
Increasing Sown Areas of Vegetablesin China and California (1000 ha)
700080009000
10000110001200013000140001500016000
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
0
200
400
600
800
1000CaliforniaChina
Every 2 years, + 1 California
Producer response:
Trends of Cultivated Areas of Fruits and Nuts in China and California (1000 ha)
2000
4000
6000
8000
1991 1992 1993 1994 1995 1996 1997 1998 1999 20000
2000
4000
6000
8000
CaliforniaChina
Campaign to upgrade quality
China has Higher Share of Land in Orchards than Most Other Countries
0. 0
1. 0
2. 0
3. 0
4. 0
5. 0
6. 0
EU- 15 France USA I ndi a Chi na
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, well-managed 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]
Greater Beijing Area
Location of Study’s Sample Site
= other major horticulture sites
= City Center … Beijing (Forbidden City)
= First Circle is 6th Ring Road (like beltway in DC)
Step 1: Develop the Spatial Stratas
x
40 km60
80
100
140 km
Spatial Sampling Approach for China Horticulture Survey
Choosing our sample: Consists of 6 steps
Step 1: Develop the Spatial Stratas
x
40 km60
80
100140 km
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)
Spatial Sampling Approach for China Horticulture Survey
Choosing our sample: Consists of 6 steps
Greater Beijing Area
This is the outer ring of our Study’s Sample area …
equivalent to an area the size of Denmark!
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)
x
xx
x
x
x
36o
4060
80
100140
Step 3: for each 36o arc (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)
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
x
xx
x
x
x
xx
x
x
x
xx
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
36o
4060
80
100140
x
x
x
x
x
x
x
x
xx
x x
x
xx x
xx
x
xx
Step 5: Repeat selection of sample towns 10 times (once for each of 10 wedges making up the circle)
Total Town Sample Size:
5 circles x
10 towns per circle =
50 towns
(or Nt = 50)
Also need to get populations of ALL towns in each strata – for weighting
Step 6. Choosing the Sample Villages
X
v1
v2v3
v4
Second: choose 4 sample villages (v) per town
(randomly selected from all villages in each sample town)
Each sample town (x)
First: get a list of all villages (on average about 12 villages per town – v1 to v12)
Total Village Sample Size:
4 villages per each of 50 towns =
200 villages
(or Nv = 200)
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 Household Sample (n=500)
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, 2005Household characteristics
HH size (person) 4
Age of HH head (year) 42 (male)
Education and training
Education of HH head (year) 7
Share of HH head with ag extension training
(%) 50
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$) 7882
The typical fruit growing farm in China, 2005
Farm Characteristic
Farm size (ha) 0.4 ha
Distinct Plots (number) 5 plots
Number of crops (diversification)
(number)3 crops (horticulture makes up
½)
Ownership and Control
Contracted from “collective” (%) 96%
Rented from other farmer (%) 4%
Share of area decided by farmer
(%) 95%
Labor
Own Labor Days / ha (mandays) 312
Hired Day / ha (mandays) 42
Wage (US$/day) 3.2
Degree of Commercialization of Fruit, Nut and Vegetable Farmers in
Greater Beijing Area, 2004
Sales as a Share of Production (97%)
Consumed at home (3%)
Data Source: authors’ survey
And, these small farmers are mostly “on their own”
Cooperative movement still small
Percent of villages with Cooperatives / FAs
Percent of households that belong to Cooperatives / FAs
8 % 2 %
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
0
20
40
60
80
100
US (early1900s)
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 52%– Nuts 14%– Vegetables 15%– None 19%
Vege
FruitNuts
None
Rise over time – Vegetables(greater Beijing area)
• Share of “cultivated area” (not including orchard area) sown to vegetable crops
• About 1/3 of this area is in greenhouses …
• Data source: authors’ survey data
0
2
4
6
8
10
12
14
2000 2004
Percent
Rise over time – Fruit (greater Beijing area)
• Share of “cultivated area” plus “orchard area” planted to fruit orchards
• Does not include nuts
• Data source: authors’ survey data
0
5
10
15
20
25
30
35
40
45
2000 2004
Percent
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? 0
5
10
15
20
25
30
35
1995 2004
Data source: China National Rural Economy Survey (CCAP)
Where are they being grown?Inside Ring / Outside Ring
020406080
40 km ring 140 km ring
010203040
40 km ring 140 km ring
Share of Cultivate Area
Area / Village (acres)
“Mostly here”
140
40
These figures for vegetables in 2000 / same for F&N’s
Who are growing them?Rich or Poor?
050
100150
Rich Poor
0204060
Rich Poor
Share of Cultivate Area
Area / Village (acres)
These figures for vegetables in 2000/ same for F&N’s
• Per capita income:
“Rich” -- $7.28/day
Poor -- $1.25/day
Fruits / Nuts / Vegetables are being increasing grown by poor farmers in relatively remote communities!
“They do”
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”
Farmer’s field
Small Trader:
Finds seller / contacts trucker / buys with cash
Small Trader -- Partner Networks
/ process inside China’s cities (>90% private)
Partners: in other villages
Small Trader -- Partner
Small Trader -- Partner
In the city wholesale mktGoing from village to village
Private, “contract” truckersDivision I
Div II
Small Trader-dominated System (2004)
0
20
40
60
80
100
Supermarkets
ProcessFirms
SupplyFirms
U-pick /Unitbuys
SmallTraders
Note; -- Supermarkets did not procure in any villages (ZERO)
-- Zero procured by coop
Percent of all purchases
/ coops
zero
“In-home Service” (2004)
0
20
40
60
80
100
WholesaleMkt
PeriodicMkt
Wet Mkt inCity
In theVillage
Note; -- “In the village” = Off the tree + From Home + Road-side
-- Share sold in wet markets in cities down over time
Percent of all purchases
Second Buyer in the Wholesale ChainStill Small Trader-dominated (2004)
0
20
40
60
80
100
Supermarkets
ProcessFirms
SupplyFirms
Consum-er
SmallTraders
Note; -- Supermarkets only directly involved in 3% of “second trades”
-- Share sold to processing firms rising over time
Percent of all purchases
51%
/ coops
Most common marketing chain for F,N&V in China
Farmers
Small Traders
Small Traders
Networks inside China’s cities (mostly starting at urban wholesale markets)
In rural areas In urban areas
Summary: Participants in China’s Fruit, Nut and Vegetable Markets
Farmer Private $2/day
95% own decisions
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. Small farmer-dominated / land is equally distributed (within
regions) / limited rental markets
2. No / few cooperatives
3. Unregulated trading sector, dominated by small, poor traders (with a low opportunity cost operating in an economy that has fairly good roads and communications)
4. Poor farmers (regionally—that is, in remote areas) are endowed with relatively more labor and land
5. 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!
Commodity Markets
Increase specialization
Raise allocative efficiency
New Technology/Investment
Increase output / unit of land
Raise technical efficiency
Mechanization
Substitute for ag labor
Raise labor productivity
Cultivate Land Rental Mkts
Increase land quantity
Raise labor productivity
Continue!
Stage 2 (continued)
Stage 2
Added Challenge
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