ANNEX III. ESTIMATES OF SUPPORT TO AGRICULTURE BY COUNTRY, 1991-2001 (continued)
2. Conceptualising the mechanism of price transmission
A framework for determining farm-gate parity prices of tradables
Most agricultural products are tradables. For small countries, i.e. price takers in the world market, domestic prices are assumed to be determined by world market prices. The framework for the analysis of price transmission and the measurement of elasticity follows from the following expressions for import and export parity prices.
Import parity price at the farm level is defined as:
PMfarm = (Pworld + Cfreight) * E * (Taxm) + Ctransp (1) Similarly, export parity price is:
PXfarm = (Pworld - Cfreight) * E * (Taxx) - Ctransp (2)
where, PMfarm and PXfarm are import and export parity prices at the farm level, Pworld is f.o.b.
world price, Cfreight is international freight cost, E is exchange rate, Taxm and Taxx are ad valorem import and export taxes, expressed in the form of (1+t) and (1-t), where t is the applied tariff so that if t=20%, Taxm is 1.2 and Taxx is 0.8. Ctransp is domestic marketing cost (e.g. between the border and farm).1
Rearranging terms in equations (1) and (2), one obtains (3) and (4) where the terms that do not vary with world prices are separated:
PMfarm = { Ctransp + Cfreight * E * Taxm } + {E * Taxm }* Pworld (3) PXfarm = { - Ctransp - Cfreight * E * Taxx } + {E * Taxx }* Pworld (4)
In these equations, domestic and world prices are related in a linear form, e.g. Pd = a + b Pw, where the term “a” is a constant, i.e. does not vary with the world price. If there are some other costs that do not vary with the world price, these can also be incorporated in “a”.
1. Note that transaction costs are added in the case of import parity price and subtracted in the case of export parity price.
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Transmission of world price changes in absolute and proportional terms
A great deal of confusion about the concept of price transmission results from not distinguishing clearly price transmission in absolute and proportional terms. To illustrate this point numerically, equations (5) and (6) were derived by assuming some values for the parameters in equations (3) and (4), as follows: Cfreight = USD 30, E = Rs10/USD, Taxm = 1.2 (20% tariff), Taxx = 0.80 (= 1-t, t = 20%
export tax) and Ctransp = Rs 200.
PMfarm = 560 + 12 Pworld (5) PXfarm = - 440 + 8 Pworld (6)
With assumed Pworld of $100 for some period, one obtains PMfarm of Rs1 760 and PXfarm of Rs360.
Now, if the world price rises by 10% in the next period to USD 110, then the new PMfarm is Rs1 880 and PXfarm is Rs440. The change in the domestic price, in absolute term, is Rs120 (20% tariff on USD 10 rise in world price times the exchange rate) in the import case and Rs80 in the export case.
The transmission is complete or perfect in an absolute sense because the full amount of the rise in the world price is passed on to the farm level (that in real life transmissions are unlikely to be complete even in an absolute sense is discussed below).
The elasticity of price transmission, on the other hand, refers to the price change in a proportional sense. This is defined like any other elasticity - percentage change in domestic price divided by percentage change in world price. In the above example, in the import case, the change in the domestic price following a 10% rise in world price was from Rs1 760 to Rs1 880, which is a 6.8% change. This, divided by 10%, gives an elasticity of 0.68, which is less than unity despite the complete pass-through of the price change in absolute terms. In the export case, the change in the domestic price (from Rs360 to Rs440) is 22%, which gives an elasticity of 2.2, greater than unity. The larger the constant term (e.g.
high transport and marketing costs), the lower the elasticity from unity in the import case, and further higher from unity in the export case. The elasticity values are invariant to the size of the change in world price – a 20% rise in the world price, for example, gives the same elasticity – nor to the assumed exchange rate, as long as these remain constant. In some global trade models, and in common usage, the word price transmission is used in a rather loose sense without indicating if the assumption made (e.g. perfect transmission) is in an absolute or a proportional sense. A fairly common practice is to assume an elasticity value of unity to indicate complete price transmission. This would be incorrect because as noted above the true value of the elasticity, for complete transmission, is less than unity in the import case and greater than unity in the export case. The assumption (perfect transmission) would be correct only if the transmission expression in the model is such that changes in world market prices are fully transmitted in an absolute sense, but even then the implied elasticity can not be unity.2
On the question asked above, i.e. are world price changes in real life likely to be transmitted fully to the farm or consumer level even in an absolute sense, the answer is - very unlikely. Although in theory there is no reason why transmissions can not be perfect, there are good reasons why this is rarely the case in practice even when estimation is flawless. The main reasons can be categorised into three groups: trade and domestic policies; market structure; and measurement errors.3 First, trade and domestic policies often weaken the relationship between domestic and world prices. A variable levy
2. An elasticity of unity would imply perfect transmission in a proportional sense only when the constant terms in equations (3) and (4) are zero, which is possible only if both Ctransp and Cfreight are zero, which is unlikely to be the case in real life.
3. Colman (1985, 1992 and 1995) and Westlake (1987) provide many insights on this.
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scheme is a classic example, but even where there is no such scheme in a formal sense (especially now with the Uruguay Round) the practice of varying tariffs in response to changes in world market prices seems to be a rule rather than exception (see section 3 on the Asian experience). Domestic market interventions, such as price support measures and open market operations to stabilise domestic prices, also weaken the link. Policy interventions are fairly common especially for staple foods. Second, on market structure, it is possible that marketing agents in the long chain from the export point to farm level do not pass the full change in the price to lower levels for strategic trade or marketing reasons.
Where market structures are not competitive, price changes may not be transmitted fully. The third category of reasons is measurement errors. These include many things: poor quality of the data, differences in quality and variety of the products related, and econometric problems (e.g. whether or not factors such as seasonality, structural breaks, autocorrelation and asymmetry are appropriately taken into account). Thus, altogether, there are many reasons for price transmission to be incomplete, and ultimately it is the empirical estimate that provides the answer and not the theory.
A practical question here is what difference does it make in modelling works to assume a low or high elasticity? To answer this, Table 1 reports some results from a simple comparative static equilibrium exercise. Although somewhat simplified from a fully specified multi-market model, the difference can be striking. For example, with an elasticity of 0.1, there is virtually no impact on production and trade of an assumed 10% rise in the world price of wheat, say following global trade liberalisation. By contrast, an elasticity of unity results, for example for Pakistan, into a reduction of imports of wheat from over 2 million tonnes in the base case to virtually zero. The difference is still about 1 million tonnes of imports between the more commonly used elasticity values of 0.5 and 1. Thus, depending on what elasticity is used, one could conclude that trade liberalisation has a significant positive impact on developing country agriculture (e.g. reduced imports, increased production and self-sufficiency rate), or that there is little impact. Indeed, different assumptions about the elasticities were one of the reasons why models showed different impact of the Uruguay Round Agreement on Agriculture on world market prices, agriculture and incomes (see Sharma et al., 1996 for a review of such studies, and OECD 2001 for a recent application).
Table 1. An example of the impact of a 10% rise in the world price of wheat for alternative values of price transmission elasticity
Unit Tunisia Pakistan Ecuador
Production Base level ’000 mt 3445 35226 487
et = 0.1 % change from base 0.5 0.4 0.9
et = 0.5 % change from base 2.5 2.0 4.3
et = 1.0 % change from base 5.1 4.1 8.9
Consumption Base level ’000 mt 4523 37587 942
et = 0.1 % change from base -0.2 -0.2 -0.3
et = 0.5 % change from base -0.9 -1.2 -1.4
et = 1.0 % change from base -1.9 -2.4 -2.8
Imports Base level ’000 mt 1079 2361 456
et = 0.1 % change from base -2.5 -9.8 -1.7
et = 0.5 % change from base -12.1 -49.0 -7.8
et = 1.0 % change from base -24.2 -98.4 -15.5
Note: “et” is assumed elasticity of price transmission. The impacts were computed on the basis of the base year values and elasticities of demand and supply (respectively, -0.20 and 0.52 for Tunisia, -0.25 and 0.42 for Pakistan and -0.30 and 0.89 for Ecuador). These numbers are from the ATPSM model data base.
Source: Author’s calculation.
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To conclude the section on the definition of market integration, it is worthwhile to note a fundamental point made by Barrett and Li (2002) that market integration does not equate to competitive spatial equilibrium as understood in the Enke-Samuelson-Takayama-Judge tradition. Barret and Li define market integration as a phenomenon that reflects the tradability of products between spatially distinct markets, irrespective of the existence or absence of spatial market equilibrium. Competitive market equilibrium is defined as a state in which extraordinary profits are exhausted by competitive pressures to yield efficient allocations, regardless of whether this results in physical trade flows between markets. They find that traditional spatial market analysis methods confuse these two concepts. The problem lies, to a large extent, on analysts using only price data to study spatial market relationships while to properly identify integration and equilibrium one would need information on trade flow as well as transfer costs. They claim that their analytical method (distinguishing between integration and equilibrium) and application (integration of soybean meal markets in the Pacific Rim) is the first published work using data on all three variables, i.e. prices, trade volumes and transfer costs. Although highly desirable that one uses all three variables to study market integration, most analysts are left with little choice but to use only price series for estimation due to a lack of data.