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on Network Economics |
| By: | Thuy Hang Duong; Weifeng Larry Liu |
| Abstract: | From the 1990s until COVID-19, the world experienced a sustained period of low and stable inflation, alongside a marked increase in trade integration among countries. This paper examines the impacts of international trade on inflation through production networks. We first construct a theoretical model of an open economy to illustrate how input-output networks propagate the price impacts of trade shocks. Using Australia as a case study, we find that the network impacts of trade shocks on inflation are as significant as their direct impacts, and primarily propagate upstream, based on data of 47 manufacturing industries from 2000 to 2023. Australia’s low inflation before COVID benefited from increasing exposure to China’s low-cost exports, while inflation surged during COVID due to global supply chain disruptions, among other factors. This paper underscores the importance of economic globalization for inflation through production networks, and offers several implications for monetary and trade policies. |
| Keywords: | inflation, international trade, production networks, propagation of shocks |
| JEL: | C67 D57 E31 F13 F41 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:een:camaaa:2025-23 |
| By: | Giovanna d’Adda; Jessica Gagete Miranda; Giovanni Righetto |
| Abstract: | We study how the influence of social networks on individual labor market outcomes varies across occupations, specifically between manual and cognitive jobs. Using data from over fourteen million Brazilian workers and exploiting exogenous job termination due to mass layoffs, we confirm that social networks reduce unemployment duration and increase wages in the new job, but show that these effects are heterogeneous depending on workers’ occupations at the time of displacement. Manual workers benefit more from networks in terms of job reentry but less in terms of wages compared to workers performing cognitive tasks. We argue that these different patterns are due to the fact that networks reduce the likelihood that manual workers find new jobs in the same occupation, given that occupational change is associated with reductions in wages. |
| Keywords: | Social networks, Labor Market Outcomes, Mass-Layoff, Brazil |
| JEL: | J01 J24 J62 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:fbk:wpaper:2025-02 |
| By: | Yasuo Hirose; Munechika Katayama; Kozo Ueda; Kota Watanabe |
| Abstract: | This study empirically examines the differences in inflation dynamics between the US and Japan. Using a structural model of sectoral inflation, we quantify the roles of production networks, price stickiness, and structural shocks in driving these variations. Our partial equilibrium framework captures sectoral inflation as a tractable form, enabling us to estimate the model and analytically explore the channels through which pass-through to inflation operates. The model can generate inflation persistence across sectors through production networks, further reinforced by price stickiness within each sector. The full-information Bayesian estimation results reveal that impulse response functions to sectoral shocks are similar between the two countries but that differences in inflation dynamics arise from two factors: the different sources of specific sectoral inflation, particularly in an energy-related sector, and contrasting price-setting behaviors. US firms tend to change prices in the same direction as import price shocks, leading to higher pass-through, whereas Japanese firms are inclined to set prices to absorb import price shocks. Policy experiments based on the estimated model demonstrate that a 10% increase in tariffs results in a 0.6–1.2% rise in US producer price inflation. |
| Keywords: | inflation dynamics, production networks, input-output linkages, price stickiness |
| JEL: | E3 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:een:camaaa:2025-22 |
| By: | Daiji KAWAGUCHI; Sagiri KITAO; Manabu NOSE |
| Abstract: | This study examines how CEO age influences the speed of technology adoption, focusing on e-commerce diffusion during COVID-19. Using unique survey data linked to credit scores and trading networks, we find firms are more likely to adopt e-commerce when their trading partners do, with adoption elasticity rising from 0.27 in 2020 to 0.37 in 2021. However, firms led by older CEOs respond more slowly, with elasticity decreasing by 0.13 to 0.21 for CEOs 10 years above the average. These findings highlight the role of leadership demographics in technology diffusion and firms' adaptability in digital transformation. |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:25023 |