Cao, Ruoxi
(2024)
Essays in Macroeconomics
Understanding Capital-skill Complementarity and Business Cycle Dynamics.
PhD thesis, University of Liverpool.
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Abstract
This thesis aims to provide a comprehensive analysis of the interplay between technological advance- ments, capital-skill complementarity, and labour market dynamics. The central focus is to explore the implications of these factors on business cycle dynamics. The research builds upon the existing literature while introducing novel elements, such as varying utilisation associated with different skill levels for labour. By employing empirical analyses and developing a stochastic dynamic general equilibrium (DSGE) model, this study seeks to offer insights into the intricate relationships among technology, labour composition, and economic outcomes. Chapter 1 revisits the study conducted by Basu et al. (2006) on constructing a measure of aggregate technology change while accounting for aggregation effects, non-constant returns, varying utilisation of capi- tal and labour, and imperfect competition. However, our study extends their work by incorporating varying utilisation associated with different skill levels for labour. Empirical findings demonstrate that techno- logical improvements lead to an increase in both output and input, with high-skilled labour experiencing higher utilisation while low-skilled labour experiences decreased utilisation. Furthermore, the analysis reveals sector-specific variations in the responses of high-skilled and low-skilled labour utilisation to technological advancements. Chapter 2 examines the capital-skill complementarity hypothesis across various industries in the U.S. economy. Applying Hansen’s (2002) data-splitting methodology, the study identifies four primary findings. Firstly, industries with higher capital-to-output ratios exhibit substitution between capital and skilled labour, while those with lower ratios demonstrate complementarity. Secondly, skilled and unskilled labour display a complementary relationship in both industry groups, with a stronger association observed in industries characterized by a higher-educated workforce. Thirdly, a time break in capital-skill substitution is identified in industries with high capital-to-output ratios, indicating a higher degree of substitutability between capital and skilled labour after 1980. These findings are robust across various sensitivity analyses, aligning with the non-linearity observed in the time-series analysis by Goldin and Katz (1998) using U.S. manufacturing data. This suggests the possibility of a transitory nature in the observed capital-skill complementarity phenomenon. Chapter 3 focuses on the development of a stochastic dynamic general equilibrium (DSGE) model that integrates capital-skill complementarity in production, Calvo prices, and nominal wage rigidity. The primary objective is to gain insights into the negative dynamics observed in the skilled to unskilled working hours ratio and the differential responses of hours worked by skilled and unskilled workers. Four distinct scenarios are simulated, including a generalized real business cycle (RBC) model, a frictionless monopolistic competition model, a generalized model incorporating Calvo (1983) pricing, and a model incorporating Calvo wage and Calvo price settings. The analysis reveals that with moderate capital-skill complementarity, both the generalized RBC model and the frictionless monopolistic competition model can explain the negative response of the skilled to unskilled hours ratio to technological advancements. However, these models fail to capture i the divergent responses of hours worked for the two skill levels. In contrast, a generalized model incorporating Calvo (1983) pricing provides a more satisfactory explanation. Additionally, the incorporation of Calvo wage and price settings further enriches the analysis, offering deeper insights into the interplay between technology, labour market dynamics, and economic outcomes.
| Item Type: | Thesis (PhD) |
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| Divisions: | Faculty of Humanities and Social Sciences > School of Management |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 02 Apr 2024 10:26 |
| Last Modified: | 03 Apr 2024 13:59 |
| DOI: | 10.17638/03179986 |
| Supervisors: |
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| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3179986 |
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