The labour input response to permanent changes in output: an errors-in-variables analysis based on panel data

Article Abstract:

An errors-in-variables analysis is performed on a panel data set from Norwegian manufacturing firms for the period 1975-1982 to examine 'The increasing returns to scale puzzle' for labor inputs. This is done by examining the response of the input of white-collar and blue-collar workers and blue-collar work hours to permanent changes in output. Results indicate that 'the increasing returns to scale puzzle' remains for labor also when focusing on the response to permanent changes. However, output response indicates constant returns to scale for materials. These findings suggest a non-homotheticity in production technology.

Norway, Labor economics, Return on investment, Labor productivity, Rate of return

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Production function regressions, returns to scale, and externalities

Article Abstract:

The usage of linear regressions to study the market structure, the size of returns to scale and externalities in manufacturing industries was criticized based on three factors. These are that previous regression studies could be erroneous, that regression evidence could be influenced by variations in sample and instruments and that returns to scale regression imply that returns are almost constant. It was suggested that more research on possible aggregation bias is necessary and that alternative instrument sets which incorporate industry-specific components should be developed.

Usage, Regression analysis, Production functions (Economics)

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Dynamic complementarities: a quantitative analysis

Article Abstract:

A standard business cycle model modified with contemporaneous and dynamic complementarities was proposed to evaluate the significance of dynamic complementarities as an antecedent of propagation in a dynamic stochastic economy. The model relies on past data from Baxter and King (1991) and issues on propagation from dynamic complementarities from Cooper and John (1988). The complementarities are seen as contributing factors that augment and produce shocks to technology and tastes.

Research and Development in the Physical, Engineering, and Life Sciences, Economics, Research and Development in the Social Sciences and Humanities, Mathematics, Models, Business cycles, Monte Carlo method, Monte Carlo methods, Linear complementarity problem

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