Primary Versus Secondary Production Techniques in U.S. Manufacturing

Mattey, Joe P.; Raa, Thijs ten

doi:10.1142/9789812833679_0016

Cited by 4 publications

(7 citation statements)

References 2 publications

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“…Miernyk et al (1970) quantify the level of uncertainty in measured technical coefficients. Mattey and ten Raa (1997) support the commodity technology hypothesis for United States manufacturing.…”

Section: From Data To Coefficients and From Coefficients To Multipmentioning

confidence: 70%

Stochastic Analysis of Input–output Multipliers on the Basis of Use and Make Tables

Raa

Rueda‐Cantuche

2007

Review of Income and Wealth

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Although technical coefficients are estimated on the basis of flow data (use and make matrices), they are rarely treated as random variables. If this is done, an error term is added to the coefficients, rather than derived from the distribution of the data. Even so, the calculation of multipliers, by means of the Leontief inverse, is difficult. Due to the nonlinearity of this operation, the multiplier estimates are biased. By going back to the flow data, this paper provides unbiased and consistent employment and output multipliers estimates for the Andalusian economy. Rectangular use and make matrices are accommodated and problems associated with the construction and estimation of technical coefficients and the Leontief inverse are circumvented.

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Section: From Data To Coefficients and From Coefficients To Multipmentioning

confidence: 70%

Stochastic Analysis of Input–output Multipliers on the Basis of Use and Make Tables

Raa

Rueda‐Cantuche

2007

Review of Income and Wealth

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“…The commodity technology assumption is considered theoretically superior [11,13,15,16,22,24], but agreement is not uniform. For instance, de Mesnard [6] stated that the commodity technology hypothesis has to be rejected since it breaks the linkages of commodity flows internal to the industries.…”

Section: Background Contextmentioning

confidence: 99%

The Problem of Negatives Generated by the Commodity Technology Model in Input-Output Analysis: A Review of the Solutions

Raa

Rueda‐Cantuche

2021

Efficiency and Input-Output Analyses

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Many economic models (e.g., computable general equilibrium models, econometric input-output models) revolve around a matrix of technical coefficients. However, these matrices can be estimated only once every 5 years as long as they are calculated from input-output tables and these are only published on a 5-year basis. Alternatively, use and make (or supply) tables are being regularly published on a yearly basis. However, they need to be converted into input-output tables as a previous step to form the matrix of technical coefficients. In doing so, this paper aims to shed light on the construction process of input-output tables and to guide economic modelers in making a decision on the way to make such conversion and how to deal with the subsequent problems, particularly with negative technical coefficients. Keywords Input-output analysis • Technical coefficients • Use and make tables • Input-output modeling JEL Classification C67 • D57

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“…--ten Raa and van der Ploeg (1989): using SUTs data variances and a maximum likelihood approach, obtain new, updated SUTs that are consistent with non-negative IO coefficients under commodity technology model, sensitivity of input coefficients with respect to SUTs entries is examined. See also ten Raa (1988), Mattey and ten Raa (1997), and Rueda-Cantuche and ten Raa (2013).…”

Section: Supply and Use Tables/flows (Suts)mentioning

confidence: 99%

“…nonbasic (service or local) activities/industries distinctions in related literature of economic base studies that also run regressions somewhat similar to (5) with service employment as dependent variable in order to estimate regional employment multipliers (see e.g. Hildebrand and Mace, 1950;Weiss and Gooding, 1968;Park, 1970 Raa (1997), and Rueda-Cantuche and ten Raa (2013).…”

Section: Econometric and Other (Non-bayesian) Statistical Approachesmentioning

confidence: 99%

Volatility of the structure of intersectoral relations of Ukraine's economy

Yastremskii¹,

KULYK²

2020

Economy and forecasting

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The article deals with the volatility of intersectoral flows in Ukrainian economy during 2000–2017. For this purpose, the authors construct a dynamic matrix series of direct cost coefficients in comparable detail (19 economic activities (EAs)); calculate statistical characteristics of 361 dynamics (19x19) and coefficients of direct expenses of Ukraine's intersectoral balance; and analyze the dynamics of cost indicators of Ukraine's economy (the ratio of GDP to total output, the Frobenius – Perron numbers) and those of economic activities (the Brauer – Perron numbers). Construction of the historical series of the matrix of direct costs in comparable detail is achieved by aggregating the "input - output" tables. Volatility is assessed using indicators of variation, relative variation, sample standard deviation, standard deviation per mean, historical volatility, and standard trend error (regression), i.e. trend volatility. Volatility of intersectoral flows in Ukraine is significant. The maximum variation for the coefficients of direct costs for EA "Information ..." for all years of observation was 0.3144, for EA "Water Supply" - 0.3004, and for EA "Art" - 0.2673. Derivative aggregates (Brauer-Solow numbers, relative EA cost) are also volatile. According to estimates of the standard deviation, the agrosector is the most stable, the most unstable - public administration. Economy Ukraine has a significant margin of productivity. A sufficient Brauer-Solow condition for the productivity of the direct cost matrix is guaranteed to be satisfied for all years of observation. Out of 361 coefficients of direct costs, time trends are recorded for 166. Among them, 91 have an upward trend, 65 - a downward trend. To fix the presence of the trend, the authors use the probability of deviation of the hypothesis about the significance of the linear dependence of the coefficients of direct costs on time. The high cost intensity of the economy is a general economic problem of Ukraine. The ratio of GDP to total output in Ukraine is about 40%, while in developed countries, this figure is close to 60%. Reducing costs is a significant resource for economic growth in Ukraine.

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Primary Versus Secondary Production Techniques in U.S. Manufacturing

Abstract: Note:We thank an anonymous referee and participants at numerous seminars for helpful comments.

Cited by 4 publications

References 2 publications

Stochastic Analysis of Input–output Multipliers on the Basis of Use and Make Tables

Stochastic Analysis of Input–output Multipliers on the Basis of Use and Make Tables

The Problem of Negatives Generated by the Commodity Technology Model in Input-Output Analysis: A Review of the Solutions

Volatility of the structure of intersectoral relations of Ukraine's economy

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