7,580 research outputs found

    A model of power-biased technological change

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    New technologies have allowed firms to monitor low-skill workers more closely, thus reducing the power of these workers. We show that this ‘power-biased’ change may generate rising wage inequality and increases in the work intensity and unemployment of low-skill workers

    Power, productivity and profits

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    New information and communication technologies, we argue, have been 'power-biased': in many industries they have allowed firms to monitor workers more closely, thus reducing the power of these workers. An efficiency wage model shows that 'power-biased technical change' in this sense may generate rising inequality accompanied by an increase in both unemployment and work intensity. JEL Categories: J31, O33power-biased technical change, efficiency wages, inequality, work intensity.

    Information and communications technologies,coordination and control, and the distribution of income

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    We consider the links between information and communications technologies (ICTs) and the distribution of income, as mediated by problems of coordination and control within organizations. In the large corporations of the mid-twentieth century, a highly developed division of labor was coordinated and controlled with the aid of relatively underdeveloped ICTs. This created a situation in which the options of top manage- ment were constrained while the individual and collective power of lower paid workers was enhanced. Only in the late twentieth century, when the microprocessor and re- lated technologies transformed the information systems of organizations, did improve- ments in the tools of coordination and control race ahead of the growing demands of coordination and control. These technological changes have reduced the power of lower-paid employees, increased that for higher-paid employees, and led to an increase in income inequality. Thus, the more important aspects of new technology relate to the "power-bias", rather than the "skill-bias", of technological change. JEL Categories: J31, O33communications technology, power-biased technical change, inequality, work intensity, efficiency wage.

    Power-Biased Technological Change and the Rise in Earnings Inequality

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    New information and communication technologies, we argue, have been 'power-biased': they have allowed firms to monitor low-skill workers more closely, thus reducing the power of these workers. An efficiency wage model shows that 'power-biased technical change' in this sense may generate rising wage inequality accompanied by an increase in both the effort and unemployment of low-skill workers. The skill-biased technological change hypothesis, on the other hand, offers no explanation for the observed increase in effort. JEL Categories: J31, O33power-biased technical change, skill bias, efficiency wages, wage inequality, work intensity

    Power-Biased Technological Change and the Rise in Earnings Inequality

    Get PDF
    New information and communication technologies, we argue, have been ‘power- biased’: they have allowed firms to monitor low-skill workers more closely, thus reducing the power of these workers. An efficiency wage model shows that ‘power-biased technical change’ in this sense may generate rising wage inequality accompanied by an increase in both the effort and unemployment of low-skill workers. The skill-biased technological change hypothesis, on the other hand, others no explanation for the ob- served increase in effort.power-biased technical change, skill bias, efficiency wages, wage inequality, work intensity.

    Bonuses, Credit Rating Agencies and the Credit Crunch

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    The payment of bonuses can bring big benefits. But harm, too, can result. In the financial sector, this is especially true, above all when they are related to noisy indicators of performance over brief periods. This paper starts by exploring these ideas, then proceeds to examine credit rating agencies and their role in the 2007 credit crunch. It emphasizes the paucity of long term high frequency financial data to quantify tail event risks, the failure to apply analysis of fundamentals in financial and housing markets, and rewards structures to individual players that reinforced myopia as three key components of the crisis.bonuses; credit crunch; credit rating agencies.
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