Date of Award

Spring 5-15-2018

Author's School

Graduate School of Arts and Sciences

Author's Department

Economics

Degree Name

Doctor of Philosophy (PhD)

Degree Type

Dissertation

Abstract

My dissertation investigates how technological progress shapes economy. Technological changes have heterogeneous effects on economic agents as they are often biased toward certain tasks or sectoral activities. The dissertation aims at understanding the sources of heterogeneity and their impacts on aggregate outcomes, focusing on economic growth and labor allocation.

The first chapter investigates a bi-directional relation between technology and occupational structure (job allocation). Jobs have polarized in the U.S. since at least the 1980s, but the growth of high-skill jobs has been stagnated since 2000s (skill demand reversal). I document that software innovation has increased compared to equipment innovation and relate this changes in the direction of innovation to the skill demand reversal, based on a novel empirical observation: The intensity of software- and equipment-use by occupation represents the cognitive- and routine-task intensity, respectively. I then propose a general equilibrium model that endogenously explains both employment share and software innovation trends. The productivity growth in the equipment-producing sector replaces the middle-skill occupations which use equipment more intensively. Thus the demand for equipment declines, resulting in more software innovation than equipment innovation. This, in turn, leads to a skill demand reversal by enhancing the productivity of high-skill occupations. Quantitative analysis shows that the model explains approximately 70 to 80\% of the rise in software and skill demand reversal in the data.

The second chapter, joint work with Tim Lee and Yongseok Shin, investigates the role of differential productivity growth across jobs (routinization) and industries to explain a slowdown in aggregate growth in the U.S. since the 2000s. In the model, complementarity across jobs and industries in production leads to aggregate productivity slowdowns, as the relative size of those jobs and industries with high productivity growth shrinks. We find that this effect was countervailed by the evolution of computer industry: Its productivity growth was extraordinarily high during the 1980s and 1990s and, at the same time, computer output became an increasingly more important input in production across all industries (computerization). It was only as the productivity growth in the computer industry slowed down in the 2000s that the negative effect of differential productivity growth across jobs became apparent for aggregate productivity.

In the third chapter, Dongya Koh, Raul Santaeulalia-Llopis, and I document a rise of intellectual property products (IPP) captured by up-to-date national accounts in 31 OECD countries. These countries gradually adopt the new system of national accounts (SNA2008) that capitalizes IPP---which was previously treated as an intermediate expense in the pre-SNA1993 accounting framework. We examine how the capitalization of IPP affects stylized growth facts and the big ratios (Kaldor, 1957). We find that the capitalization of IPP generates (a) a decline of the accounting labor share, (b) an increase in the capital-to-output ratio across time, and (c) an increase in the rate of return to capital across time. The key accounting assumption behind the IPP capitalization implemented by national accounts is that the share of IPP rents that are attributed to capital is equal to one. That is, national accounts assume that IPP rents are entirely owed to capital. We argue that this assumption is arbitrary and extreme. More reasonable assumptions about the split of IPP rents between capital and labor - for example, based on the cost structure of R&D - generate a secularly trendless labor share, a constant capital-to-output ratio, and a constant rate of return across time. We discuss the implications of these new measures of IPP capital for cross-country income per capita differences using standard development and growth accounting exercises.

Language

English (en)

Chair and Committee

Yongseok Shin

Committee Members

Michele Boldrin, Francisco Buera, Sungki Hong, Rodolfo Manuelli,

Comments

Permanent URL: https://doi.org/10.7936/K75B01XR

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