Statistics Norway

About: Statistics Norway is a government organization based out in Oslo, Norway. It is known for research contribution in the topics: Population & Consumption (economics). The organization has 349 authors who have published 1261 publications receiving 39575 citations. The organization is also known as: Statistisk sentralbyrå & The Central Bureau of Statistics.

The Gender Revolution: A Framework for Understanding Changing Family and Demographic Behavior

Abstract: This article argues that the trends normally linked with the second demographic transition (SDT) may be reversed as the gender revolution enters its second half by including men more centrally in the family. We develop a theoretical argument about the emerging consequences of this stage of the gender revolution and review research results that bear on it. The argument compares the determinants and consequences of recent family trends in industrialized societies provided by two narratives: the SDT and the gender revolution in the public and private spheres. Our argument examines differences in theoretical foundations and positive vs. negative implications for the future. We focus primarily on the growing evidence for turnarounds in the relationships between measures of women's human capital and union formation, fertility, and union dissolution, and consider evidence that men's home involvement increases union formation and fertility and decreases union instability. Although the family trends underlying the SDT and the gender revolution narratives are ongoing and a convincing view of the phenomenon has not yet emerged, the wide range of recent research results documenting changing, even reversing relationships suggests that the gender approach is increasingly the more fruitful one.

The inconsistency of common scale estimators when output prices are unobserved and endogenous

Abstract: SUMMARY This paper explores the inconsistency of common scale estimators when output is proxied by deflated sales, based on a common output deflator across firms. The problem arises when firms operate in an imperfectly competitive environment and prices differ between them. In particular, we show that this problem reveals itself as a downward bias in the scale estimates obtained from production function regressions, under a variety of assumptions about the pattern of technology, demand and factor price shocks. The result also holds for scale estimates obtained from cost functions. The analysis is carried one step further by adding a model of product demand. Within this augmented model we examine the probability limit of the scale estimate obtained from an ordinary production function regression. This analysis reveals that the OLS estimate will be biased towards a value below one, and how this bias is affected by the magnitude of the parameters and the amount of variation in the various shocks. We have included an empirical section which illustrates the issues. The empirical analysis presents a tentative approach to solve the problem discussed in the theoretical part of this paper.