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This study investigates the role of intersectoral networks in the transmission of aggregate technology shocks to sectors' growth. First, we develop a theoretical model to obtain insights into the propagation of shocks through input–output linkages, which suggests that the network effect arises via sectoral downstream linkages. We then quantitatively assess this theoretical implication with United States manufacturing industries, where the aggregate technology shocks are derived from a dynamic factor model. We find that aggregate technology shocks lead to an increase in the output growth of the sector, both directly and indirectly via its intersectoral linkages. More interestingly, we document a crucial role of the intersectoral network channel, which contributes about 50% of the total effect. In addition, the network‐based effect comes mostly from downstream linkages of sectors, which is broadly consistent with theory. [ABSTRACT FROM AUTHOR]

The monetary economics literature has highlighted four issues that are important in evaluating US monetary policy since the late 1960s: (i) time variation in policy parameters, (ii) asymmetric preferences, (iii) real-time nature of data, and (iv) heteroskedasticity. In this paper, we exploit advances in sequential monte carlo methods to estimate a time-varying nonlinear Taylor rule that addresses these four issues simultaneously. Our findings suggest that US monetary policy has experienced substantial changes in terms of both the response to inflation and to real economic activity, as well as changes in preferences. These changes cannot be captured adequately by a single structural break at the late 1970s, as has been commonly assumed in the literature, and play a non-trivial role in economic performance. [ABSTRACT FROM AUTHOR]