Abstract
The supply-driven IO quantity model is shown to be the pure opposite of the standard IO model. In this model, any change in the exogenous supply of primary inputs is passed on forwardly to purchasers that pass it on further with fixed intermediate and fixed final output coefficients. The Ghosh model furthermore assumes a single homogeneous input, which means that factories may work without labour. The Type II supply-driven model, additionally, has a supply-driven consumption function, which allows kitchen appliances to run without electricity. The dual of the Ghosh quantity model, the revenue-pull IO price model, simulates the backward passing on, under full competition, of any final output price change to the suppliers of intermediate inputs who pass them on further, to end up in changes in the prices of the primary inputs. Finally, all four basic IO models are compared and are shown to overestimate their typical impacts.
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Notes
- 1.
Note that Chen and Rose (1986) do report “counter-intuitive results” and talk about “absurd machinations of the supply model” in case of a 50% reduction of aluminium production in Taiwan. However, at that time, they did not conclude that the model could not be used for impact studies of such type of events.
- 2.
An alternative interpretation in which the Ghosh model is not the exact opposite of the Leontief model is presented by de Mesnard (2009). His point of departure is a physical IO table that has homogenous outputs along its rows and heterogeneous inputs along its columns. With this asymmetric base assumption naturally only asymmetric results can be derived. In reality, however, even tons of steel have different qualities and different prices and cannot be simply added in physical units. In reality, any IOT will have heterogeneous outputs along its rows as well as heterogenous inputs along its columns. This more realistic situation is our point of departure. This is also the reason why do not discuss IO models based on physical data (Miller and Blair 2009, ch. 2), as such data do not exist.
- 3.
The equivalent of this assumption in case of a supply-driven supply-use model consists of the product of two separate assumptions (de Mesnard 2004): (1) the fixed product mix assumption that applies to the rows of the supply table and (2) the fixed (intermediate and final) product sales ratios assumption that applies to the rows of the use table (see Fig. 3.2). Assumption (1) seems less implausible than the comparable SDIOM assumption, but assumption (2) is equally implausible.
- 4.
The solution of the Type II Ghosh model is derived in the same way as that of the Type I Ghosh model, now with the Type II Ghosh-inverse \({\mathbf{G}}^{ * } = ({\mathbf{I}} - {\mathbf{B}} - {\mathbf{D}}^{h} )^{ - 1}\), i.e. \({\mathbf{x}}^{\prime } = ({\mathbf{v}}^{rem} )^{\prime } {\mathbf{G}}^{ * }\) and \({\mathbf{Y}}^{rem} = {\hat{\mathbf{v}}}^{rem} {\mathbf{G}}^{ * } {\mathbf{D}}^{rem}\).
- 5.
Manresa and Sancho (2013) rightfully point out, partly in reaction to Oosterhaven (2012), that the mathematical symmetry between the Ghosh and Leontief models regards all outcomes. They, subsequently, suggest that it is equally problematic when production and consumption move in a different direction in case of the Type II Leontief model, as they do in Table 5.1 in two out of four cases, whereas they always move in the same direction in case of the Type II Ghosh model. I disagree. Mathematical symmetry does not imply symmetry in economic plausibility. There is no reason why moving in a different direction should be implausible in case of production and consumption, definitely not by industry and not even at the aggregate level.
- 6.
Note that the causality of the Ghosh price model in Fig. 6.2 runs in the same, backward way as that of the Leontief quantity model in Fig. 2.2. This implies that the Leontief quantity model may also be interpreted as the Ghosh price model expressed in values, instead of in prices, just like the Ghosh quantity model could be interpreted as the Leontief price model expressed in values (Dietzenbacher 1997).
- 7.
This is the basic assumption. In case of revenue-pull price impact studies it may equally well be assumed that say the foreign exports of different products from different regions have different price changes. See the first footnote of Chap. 5 for a comparable qualification in case of cost-push, price impact studies.
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Oosterhaven, J. (2019). Supply-Driven IO Quantity Model and Its Dual, Price Model. In: Rethinking Input-Output Analysis. SpringerBriefs in Regional Science. Springer, Cham. https://doi.org/10.1007/978-3-030-33447-5_6
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