Sjoukje A. OSINGA

Mark R. KRAMER

Gert Jan HOFSTEDE

Adrie J.M. BEULENS

The pork cycle revisited with ABM- applied to a case of Chinese pig farmers

Wageningen University

Logistics, Decision and Information Sciences

sjoukje.osinga@wur.nl

Pork cycle: it’s still there – China exampleIncreased corn prices have likely exaggerated the shifts in supply associated with the natural market cycle for pork. Pork prices dropped sharply in the first half of 2006 while corn prices remained high. Consequently, hog profitability plummeted and many farmers reduced numbers of hogs being reared. This led to a marked

reduction in the supply of 2007, despite the fact that it only takes 4-6 months for commercially produced hogs to reach market weight. Figure 6 illustrates the cyclical nature for both pork and poultry over a six-year period as well as the general upward trend for both prices.

Source: China National Development and Reform Commission, Price Information Center, chinaprice.gov.cn

To smoothen: government interferes; buy / sell

surpluses (indicator: hog / grain price ratio)

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Two models of the pork cycle

Basic model without individuals (averages)

Model with individual behaviour

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Basic demand and supply system (=):From literature:

Cobweb model (1)𝑃

𝑄𝑑𝑒𝑚𝑎𝑛𝑑

𝑠𝑢𝑝𝑝𝑙𝑦

divergent cobweb

h𝑆

h𝐷

𝑃1

𝑄1

𝑃2

𝑄2

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𝑃

𝑄𝑑𝑒𝑚𝑎𝑛𝑑

𝑠𝑢𝑝𝑝𝑙𝑦

convergent cobweb

h𝐷

h𝑆

From literature:

Cobweb model (2)

stable

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Basic demand and supply system (=):

Typical for over- / under supply problem:

Problem arises due to production delay Pigs need 6 months to mature

Inaccurate price expectations Naive expectations:

assume price will be same as current price

Adaptive / rational expectiations:estimate price based on available

information

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Why model this by means of ABM?

1. Pork cycle “still happens”: Farmers demonstrate bounded rationality

2. Cyclical nature of over/under supply is emergent It’s the result of many individual farmers’ decisions

3. Revisiting some assumptions of classical model How valid / useful are they in an AMB?

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Research questions

1. Grow it to show it: can we generate “the pork cycle” with an individual-based ABM?

2. Can we dampen the pork cycle through improved information provision?

3. What can we learn regarding model assumptions?

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Agent-based information management model

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stock pig age info-items estimated-price 𝐸𝑃 𝑖=α 𝑖∗𝑃

𝑒𝑞+(1−α𝑖 )∗𝑃 𝑡

depends on the proportional accuracy of equilibrium price

α 𝑖=𝑖𝑛𝑓𝑜− 𝑖𝑡𝑒𝑚𝑠𝑖

∑𝑖

𝑖𝑛𝑓𝑜− 𝑖𝑡𝑒𝑚𝑠

Research models

Test 3 models (actually 1 model with 3 values for ): current-price-model ( = 0): perfect-price-model ( = 1): estimated-price-model ():

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Simulation process

𝑃 𝑡

𝑆𝑡

α 𝑖?

Farmers sell mature pigs (in batches): the actual supply Current market price is calculated based on actual supply:Farmers calculate estimated price based on info-items and Farmers decide whether to restock:

: total supply farmers expect using their estimated price

: maximum supply farmers could possibly restockActual supply changes at every time step, influencing the price, influencing the decision to restock, etc.

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Assumptions to this model:

Equal slopes (stable model) Farmers (fully) restock or not: discrete choice

This is what happens in reality Farmers know the total available capacity

But they do not know individual decisions of other farmers

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Results: current price model

Current price: naive expectations Result: periodical pattern, pork cycle

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Results: perfect price model

Perfect price: equilibrium price Only the decision whether to restock was randomized Result: random behaviour ?

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Results: estimated price model

Using parameter for information accuracy (many ‘s) This figure: = 0.5 (varying is consistent with expectation)

Result... periodicity or random behaviour ?

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Determine periodicity –Fourier transformation

Fourier graph shows clearly periodical frequencies

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Perfect price model results: periodical?

Fourier graph shows that there is no periodicity

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Results: estimated price model

Fourier graph shows periodicity left in frequencies

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Conclusions

1. Grow it to show it: can we generate the pork cycle with our individual-based ABM? Answer: yes, we can (when farmers have naive expectations).

2. Can we dampen the pork cycle through improved information provision? Answer: yes, more information leads to less periodicity

3. What can we learn regarding model assumptions? See next slide

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Conclusions (continued) / discussion

Mapping of economic supply-demand system to an ABM is not straightforward The theory works with total supply quantities In practice, farmers will restock or find alternative income

→ 40% restock (i.e. all stables 40% full)

≠

40% of the farmers (fully) restock their stables

!

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Conclusions (continued) / discussion

Transition point: only periodicity when overcapacity When farmers produce less than demand

→ problem does not appearno periodicity

In conventional approach, 2 models: model a for overcapacity, model b for undercapacity

in an ABM: the same model shows behaviour a or b

(emergent)

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Conclusions (continued) / discussion

Nr of farmers involved in restocking may be limited (depends on ratio max farmers’ supply / total demand)

Socio-economic consequences are not visible in a conventional model Majority of farmers may be out of business

→ not an issue in models without individual farmers

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Future improvements

Experiment with alternative information diffusion processes, or: ‘whom does it come from’ Network structures → information exchange Nature of info-items

Include interaction mechanisms between farmers Peer influence / imitative behaviour

(e.g. restock when your neighbour does) Implicit interaction is already present because it is assumed

that farmers know the maximum possible supply

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Future improvements (continued)

Include more heterogeneity Personality and cultural population attributes

Include external shocks Model government intervention based on grain price Fall/rise of grain price → costs of pig raising change

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Thank you

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