Narrow your search

Library

National Bank of Belgium (2)


Resource type

book (2)


Language

English (2)


Year
From To Submit

2021 (1)

2019 (1)

Listing 1 - 2 of 2
Sort by

Book
The Technology-Employment Trade-Off : Automation, Industry, and Income Effects
Author:
Year: 2021 Publisher: Washington, D.C. : The World Bank,

Loading...
Export citation

Choose an application

Bookmark

Abstract

New technologies can both substitute for and complement labor. Evidence from structural vector autoregressions using a large global sample of economies suggests that the substitution effect dominates in the short-run for over three-quarters of economies. A typical 10 percent technology-driven improvement in labor productivity reduces employment by 2 percent in advanced economies in the first year and 1 percent in emerging market and developing economies (EMDEs). Advanced economies have been more affected by employment-displacing technological change in recent decades but the disruption to the labor market in EMDEs has been more persistent. The negative employment effect is larger and more persistent in economies that have experienced a larger increase, or smaller fall, in industrial employment shares since 1990. In contrast, economies where workers have been better able to transition to other sectors have benefited more in the medium run from the positive "income effect" of new technologies. This corresponds with existing evidence that industrial jobs are most at risk of automation and reduced-form evidence that more industrially-focused economies have tended to create fewer jobs in recent decades. EMDEs are likely to face increasing challenges from automation as their share of global industry and production complexity increases.


Book
New Approaches to the Identification of Low-Frequency Drivers : An Application to Technology Shocks
Authors: --- ---
Year: 2019 Publisher: Washington, D.C. : The World Bank,

Loading...
Export citation

Choose an application

Bookmark

Abstract

This paper addresses the identification of low-frequency macroeconomic shocks, such as technology, in Structural Vector Autoregressions. Whilst identification issues with long-run restricted VARs are well documented, the recent attempt to overcome said issues using the Max-Share approach of Francis and others (2014) and Barsky and Sims (2011) has its own shortcomings, primarily that they are vulnerable to bias from confounding non-technology shocks. A modification to the Max-Share approach and two further spectral methods are proposed to improve empirical identification. Performance directly hinges on whether these confounding shocks are of high or low frequency. Applied to US and emerging market data, spectral identifications are most robust across specifications, and non-technology shocks appear to be biasing traditional methods of identifying technology shocks. These findings also extend to the SVAR identification of dominant business-cycle shocks, which are shown will be a variance-weighted combination of shocks rather than a single structural driver.

Listing 1 - 2 of 2
Sort by