1 / 17

WP 6 Methodological research related to the database

WP 6 Methodological research related to the database WP 6.4 Multiplier bias from Supply and Use Tables José M. Rueda-Cantuche (JRC-IPTS) Erik Dietzenbacher (RUG, NL) Esteban Fernández (University of Oviedo, ES) Antonio F. de Amores (Pablo de Olavide University, ES). Rationale.

rudolf
Download Presentation

WP 6 Methodological research related to the database

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. WP 6 Methodological research related to the database WP 6.4 Multiplier bias from Supply and Use Tables José M. Rueda-Cantuche (JRC-IPTS) Erik Dietzenbacher (RUG, NL) Esteban Fernández (University of Oviedo, ES) Antonio F. de Amores (Pablo de Olavide University, ES)

  2. Rationale

  3. Following Dietzenbacher (2006): • Leontief inverse, L, plays a relevant role in inter-industry economics • L captures direct + indirect effects of an exogenous shock on industry/commodity output • L can also describes the inter-industry core of a CGE model

  4. As far as, typically, L = (I – A)-1, it is subject to the many sources of measurements errors that are very well known for IOT, A and SUT. • Hence, it seems plausible assuming A stochastic, which leads to L is biased, with input coefficients: • totally independent(Simonovits, 1975) • biproportionally stochastic (Lahiri, 1983) • moment-associated (Flam and Thorlund-Petersen, 1985).

  5. More recently, stochastics was alternatively imposed on the intermediate transactions of an input-output table rather than on its technical coefficients (e.g. Dietzenbacher, 2006). • The findings of these experiments turned out that the bias tends to be rather small and needs a large sample size to get significant relevance. • Complementary to Roland-Holst (1989).

  6. This work however shifts the attention to supply and use tables, which really constitute the basic units of the elements of an input-output table and therefore, of the technical coefficients. • Six kind of multipliers discussed in the form of multiplier matrices • Supply-use based Monte Carlo experiment

  7. Multiplier matrices

  8. Domestic supply and use table • B = input coefficient per unit of industry output • C = share of industry output stemming from producing one commodity • D = commodity output proportions (market shares)

  9. M1 = Industry technology assumption for product by product tables M6 = Product technology assumption for product by product tables M2 = Fixed product sales structure for industry by industry tables M5 = Fixed industry sales structure for industry by industry tables M3 = DT· M1          (industry by product) M4 = C-1 · M6 (industry by product) M7 = D-T· M2          (product by industry) M8 = C· M5 (product by industry)

  10. Monte Carlo experiment

  11. Empirical application for Spain (2006): Monte Carlo experiment • Data sources: SUT (basic prices), 59 ind. x 59 prod. (Eurostat and INE). • Two approaches: • Supply-side • Use-side

  12. SUPPLY-SIDE APPROACH Randomization of V Randomization of u, f, h, w Reconciliation h, f, p RAS-based Solution

  13. USE-SIDE APPROACH Randomization of V Randomization of u, f, h, w RAS-based Solution

  14. ITMC X C FPSI X I ITMI X C PTMI X C FISI X I PTMC X C

  15. CONCLUSIONS: • The absolute average values of the bias in all cases are not very significant and may probably be considered negligible as in Roland-Holst (1989) and Dietzenbacher (2006). • This is just an almost definite answer that deserves further research for a bigger number of iterations (say, 10,000); more countries and/or years and different levels of variability in the randomized supply and use values.

  16. Thank you! http://ipts.jrc.ec.europa.eu

More Related