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Title: An empirical evaluation of news and uncertainty shocks as sources of business cycles
Author: Cascaldi-Garcia, Danilo
ISNI:       0000 0004 7431 7334
Awarding Body: University of Warwick
Current Institution: University of Warwick
Date of Award: 2018
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This Thesis contributes to the literature of business cycles driven by agents' beliefs. In Chapter 3, we provide novel empirical evidence linking the effects of technology news shocks to uncertainty shocks. Their correlation implies that when financial uncertainty shocks hit the economy, utilization-adjusted total factor productivity (TFP) increases over the medium-term. This leads to an attenuation of the effects on economic activity from news shocks in the short-term and from uncertainty shocks in the medium- term. Supported by these results, we propose an identification strategy to measure the effects of `good uncertainty' shocks and disentangle the importance of technological news, good and bad uncertainties, and ambiguity shocks in explaining business cycle variation. In Chapter 4, I investigate the empirical relationship between agents' responses to future technological changes and the level of uncertainty in the economy. I show that the economic responses to news shocks change substantially over time, and that this dynamic couples with periods of high and low uncertainty. Periods of high uncertainty are characterized by higher positive economic effects of news shocks on output, consumption, investment and real personal income. These results indicate that the continuous updating of agents' expectations about the current and future economic situation operates as a transmission channel for news shocks, amplifying its positive outcomes. Kurmann and Otrok [2013] show that the effects on economic activity from news on future productivity growth are similar to the effects from unexpected changes in the slope of the yield curve. In Chapter 5, I show that these results do not hold in the light of a recent update in the utilization-adjusted TFP series produced by Fernald [2014]. In Chapter 6, I propose a novel method of identifying technological news shocks through instrumental variables based on forecast revisions from the Survey of Professional Forecasters. I construct proxy measures for the slope of the long-run trend of GDP, investment and industrial production, which are strong instruments for recovering the underlying news shock. The procedure has the advantage of relying on information about agents' expectations, instead of the statistical procedures currently used for the news shock identification. By employing a proxy SVAR, I show that news shocks produce substantial effects on impact on GDP and investment. The effects on consumption in the short-run, however, are milder than usually presented by the news shock literature.
Supervisor: Not available Sponsor: CAPES (Brazil)
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: HB Economic Theory