Sectoral Technology and Structural Transformation

Herrendorf, Berthold; Herrington, Christopher; Valentinyi, Ákos

doi:10.1257/mac.20130041

Cited by 128 publications

(160 citation statements)

References 22 publications

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“…We also assume, consistent with the evidence in Herrendorf et al (2015) that µ, σ > 1. K 0 is elastically supplied at rental rate r 0 , so in equilibrium, 12 r 0 =…”

Section: Crop Production In An Open Economy With Alternative Technolosupporting

confidence: 77%

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Immigration Restrictions as Active Labor Market Policy: Evidence from the Mexican Bracero Exclusion

2017

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“…We also assume, consistent with the evidence in Herrendorf et al (2015) that µ, σ > 1. K 0 is elastically supplied at rental rate r 0 , so in equilibrium, 12 r 0 =…”

Section: Crop Production In An Open Economy With Alternative Technolosupporting

confidence: 77%

“…Using the parameter estimates of Herrendorf et al (2015) for postwar U.S. agriculture, the semielasticity (7) would be large, approximately 0.4. 16 In a typical high-bracero state with B/L = 0.3, farm wages rise by approximately 12 percent after exclusion.…”

Section: Workforce Reduction Policymentioning

confidence: 99%

Immigration Restrictions as Active Labor Market Policy: Evidence from the Mexican Bracero Exclusion

2017

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“…Following current practice (e.g., see Herrendorf et al, 2015), we use equations (2), (3), and (4) to estimate ε 1 . In these equations, Y l is the real output in sectors which are (very) intensive in general human capital input and Y h is the real output in the remaining sectors.…”

Section: Appendix -Elasticity Of Substitutionmentioning

confidence: 99%

On the Industry Specificity of Human Capital and Business Cycles

2016

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Abstract:We define specific (general) human capital as the set of occupations whose use is spread in a limited (wide) set of industries. Using the EU Labor Force Survey database, we identify these human capital types and analyze their employment and education. This exercise yields a persistent assignment of occupations into specific and general human capital types. The share of specific human capital varies across countries and has declined over time almost everywhere. We consider a stylized two-sector model where one of the sectors uses both types of human capital and the other specializes on general human capital. We show that a mean preserving increase in the share of specific human capital reduces (increases) the contribution of shocks in non-specialized sector and increases (reduces) the contribution of shocks in specialized sector to the variance of final output, when sectoral outputs are gross complements (substitutes).JEL Codes: E24,E30, I20, J23, J24, O41.

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“…Whereas Herrendorf et al (2015) analysed the importance of differential rates of technological progress among the three consumption sectors, Herrendorf et al (2013) focused on the preference side of structural change -i.e. they analysed the relative importance of both changes in income and changes in relative prices in the households' consumption bundles as a source of structural change-showing which preference specification should be used in applied work on structural change.…”

Section: Introductionmentioning

confidence: 99%

Technology of the Preferences: Linking Consumption Expenditures to Value Added with Minimal Information

Vázquez

Serrano

2017

SSRN Journal

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Abstract:The combination of consumption data from expenditure surveys with information contained in IO tables is a crucial step to structural change analysis. Herrendorf et al. (2013) focus the attention on applying a consistent definition of commodities on both the household and production sides -i.e. estimation of utility and production functions-when connecting models with data in any multisector general equilibrium model. The point of departure of these analyses consist, basically, on connecting the information on consumption made by households with the final demand vector (or matrix) present in the IO tables, which is then conveniently modified to produce the multipliers of interest. This process requires the construction of a concordance or bridge matrix to make this connection possible, since several issues affect the combination of these two data sources: differences in price valuation between consumption surveys and IO tables, the influence of taxes and margins or the different product classifications between these two frameworks make this combination a challenge for the researcher.In this paper we explore this challenge with a twofold purpose: (i) to investigate how important a "good" or "bad" conciliation of our consumption data between household surveys and IO tables affect our results in terms of the so-called total requirement matrix or impact analysis; and (ii) to propose a conciliation technique between both data structure, which using only minimal information provides a systematic way or reconciling them if detailed data are not at hand. This technique is based on entropy econometrics and it allows making statistical inference on the bridge matrix estimated. Both research objectives are illustrated by means of numerical simulation and by its application to a real-world case.JEL Codes: C1, O11,O41.

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Sectoral Technology and Structural Transformation

Cited by 128 publications

References 22 publications

Immigration Restrictions as Active Labor Market Policy: Evidence from the Mexican Bracero Exclusion

Immigration Restrictions as Active Labor Market Policy: Evidence from the Mexican Bracero Exclusion

On the Industry Specificity of Human Capital and Business Cycles

Technology of the Preferences: Linking Consumption Expenditures to Value Added with Minimal Information

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