2 resultados para information economy

em DRUM (Digital Repository at the University of Maryland)


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In 2013, a series of posters began appearing in Washington, DC’s Metro system. Each declared “The internet: Your future depends on it” next to a photo of a middle-aged black Washingtonian, and an advertisement for the municipal government’s digital training resources. This hopeful discourse is familiar but where exactly does it come from? And how are our public institutions reorganized to approach the problem of poverty as a problem of technology? The Clinton administration’s ‘digital divide’ policy program popularized this hopeful discourse about personal computing powering social mobility, positioned internet startups as the ‘right’ side of the divide, and charged institutions of social reproduction such as schools and libraries with closing the gap and upgrading themselves in the image of internet startups. After introducing the development regime that builds this idea into the urban landscape through what I call the ‘political economy of hope’, and tracing the origin of the digital divide frame, this dissertation draws on three years of comparative ethnographic fieldwork in startups, schools, and libraries to explore how this hope is reproduced in daily life, becoming the common sense that drives our understanding of and interaction with economic inequality and reproduces that inequality in turn. I show that the hope in personal computing to power social mobility becomes a method of securing legitimacy and resources for both white émigré technologists and institutions of social reproduction struggling to understand and manage the persistent poverty of the information economy. I track the movement of this common sense between institutions, showing how the political economy of hope transforms them as part of a larger development project. This dissertation models a new, relational direction for digital divide research that grounds the politics of economic inequality with an empirical focus on technologies of poverty management. It demands a conceptual shift that sees the digital divide not as a bug within the information economy, but a feature of it.

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I investigate the effects of information frictions in price setting decisions. I show that firms' output prices and wages are less sensitive to aggregate economic conditions when firms and workers cannot perfectly understand (or know) the aggregate state of the economy. Prices and wages respond with a lag to aggregate innovations because agents learn slowly about those changes, and this delayed adjustment in prices makes output and unemployment more sensitive to aggregate shocks. In the first chapter of this dissertation, I show that workers' noisy information about the state of the economy help us to explain why real wages are sluggish. In the context of a search and matching model, wages do not immediately respond to a positive aggregate shock because workers do not (yet) have enough information to demand higher wages. This increases firms' incentives to post more vacancies, and it makes unemployment volatile and sensitive to aggregate shocks. This mechanism is robust to two major criticisms of existing theories of sluggish wages and volatile unemployment: the flexibility of wages for new hires and the cyclicality of the opportunity cost of employment. Calibrated to U.S. data, the model explains 60% of the overall unemployment volatility. Consistent with empirical evidence, the response of unemployment to TFP shocks predicted by my model is large, hump-shaped, and peaks one year after the TFP shock, while the response of the aggregate wage is weak and delayed, peaking after two years. In the second chapter of this dissertation, I study the role of information frictions and inventories in firms' price setting decisions in the context of a monetary model. In this model, intermediate goods firms accumulate output inventories, observe aggregate variables with one period lag, and observe their nominal input prices and demand at all times. Firms face idiosyncratic shocks and cannot perfectly infer the state of nature. After a contractionary nominal shock, nominal input prices go down, and firms accumulate inventories because they perceive some positive probability that the nominal price decline is due to a good productivity shock. This prevents firms' prices from decreasing and makes current profits, households' income, and aggregate demand go down. According to my model simulations, a 1% decrease in the money growth rate causes output to decline 0.17% in the first quarter and 0.38% in the second followed by a slow recovery to the steady state. Contractionary nominal shocks also have significant effects on total investment, which remains 1% below the steady state for the first 6 quarters.