How resilient is the labour market against natural disaster? Evaluating the effects from the 2010 earthquake in Chile

Jiménez, Maribel; Martínez, Mónica Jiménez; Romero-Jarén, Rocío

doi:10.1007/s11069-020-04229-9

Cited by 17 publications

(10 citation statements)

References 43 publications

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“…The 27 th of February 2010 Biobío earthquake is considered the second most severe in Chile's history and one of the ten strongest worldwide since these events have been recorded by instruments (Barrientos & CSN Team, 2018; Contreras & Winckler, 2013; M. Jiménez et al, 2020;Sanhueza et al, 2012). The seismic event, and subsequent tsunami, affected several regions in the central and central-south regions of the country that are inhabited by approximately 80% of the Chilean population.…”

Section: Disaster Context and Datamentioning

confidence: 99%

“…As noted above, the lack of published studies might also be attributed to a publication bias, whereby signi cant ndings generate higher chances of publication (Klomp & Valckx, 2014). Additionally, since disasters' interruption of economic activities is usually only temporary, most past research has focused on shorter-term impacts since it is more di cult to identify long-term effects (Jiménez et al, 2020). We contribute to this limited literature focusing on ICT labour.…”

Section: Introductionmentioning

confidence: 98%

“…But the insu ciency of studies is a general problem in the literature examining the interaction between labour and natural disasters. According to Jiménez et al (2020), between 1900 and November 2019, only 118 articles on the effects of disasters on labour were published in indexed journals. Most of them refer to Japan, the US and China.…”

Section: Introductionmentioning

confidence: 99%

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Natural disasters and technological upgrading measured by changes in demand for ICT labour: Estimating the impacts with text

Campos-González

2023

Preprint

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Extensive literature has studied the economic impact of natural disasters. However, specific impacts on labour markets have received less attention. Using a massive earthquake (> 8.0 Mw) that struck Chile in 2010 and proprietary data from a Chilean online job board (4,136 job postings published between 2008 and 2012), we examine changes in demand for Information and Communications Technologies, ICT, related labour as a proxy for technological upgrading, by assuming that ICT and related technologies drive much of the technical change in production. We implement a structural topic model to discover and estimate the difference in the prevalence of ICT and Construction labour. Our results show that ICT labour does not change. In contrast, Construction labour significantly differed after the disaster, suggesting that reconstruction activities led to employment differences. Our results suggest that there was no substantive technological replacement following the earthquake. JEL Classification: J20, Q54, O33

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Section: Disaster Context and Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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Natural disasters and technological upgrading measured by changes in demand for ICT labour: Estimating the impacts with text

Campos-González

2023

Preprint

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“…In 1985 a Mw 7.8 event with an epicentre located just 120 km west of the city, destroyed 70.000 houses and damaged an additional 140.000 dwellings, leaving 950.000 persons homeless, and caused losses of about $1.8 billion (Comte et al 1986). The 2010 Mw 8.8 earthquake caused structural damage to some buildings in Viña del Mar (de la Llera et al 2017) and impacted the labour market recovery and overall economy (Jiménez Martínez et al 2020). Furthermore, recent seismic activity has been noticeable during the 2017 Mw 6.9 which was triggered by a slow slip event described in Ruiz et al (2017).…”

Section: Context Of the Study Area: Valparaiso Chilementioning

confidence: 99%

Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models

Zapata¹,

Pittore²,

Cotton³

et al. 2021

Preprint

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In seismic risk assessment the sources of uncertainty associated to building exposure modelling have not received as much attention as other components related to hazard and vulnerability. We are introducing that the degree of knowledge of a building portfolio can be described within a Bayesian probabilistic approach to acknowledge the epistemic uncertainty of its composition (i.e. proportions per building class). We are investigating the impact of such uncertainty on earthquake loss models through a novel approach based on an exposure-oriented logic tree arrangement and scenario-based seismic risk simulations. We have found that the building class reconnaissance either from prior assumptions by desktop studies with aggregated data (top-down approach) or from building-by-building data collection (bottom-up approach), plays a fundamental role in statistical modelling of exposure. We successively show that the selection of the basic set of building classes is a major contribution to the uncertainties in the loss estimations given their dependence on specific fragility functions. If the set of fragility functions handle multiple spectral periods, cross-correlated ground motion fields are required for the vulnerability assessment which ultimately control the variability of the losses. When the exposure composition is poorly known due to, for instance, simplifications and assumptions over aggregated data, its absolute contribution to the loss uncertainties has been found to be larger than the one imposed by the spatially distributed cross-correlated ground motion fields. This work invites to redesign desktop exposure studies, while it also highlights the importance of a standardized iterative approach to exposure data collection and modelling.

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“…Many studies have explored the impact of natural disasters on economic activities (Eckhardt et al 2019;Yonson et al 2020;Adeel et al 2020;Chen and Chang 2020;Jiménez Martínez et al 2020); however, few studies have examined its impact on motor vehicle crashes. Several researchers (Hino et al 1996(Hino et al , 1997a have reported an increase in motor vehicle crashes following the 1995 Great Hanshin-Awaji Earthquake in Japan.…”

Section: Introductionmentioning

confidence: 99%

Increased motor vehicle crashes following the 2016 Kumamoto earthquake, Japan: an interrupted time series analysis of property damage crashes

Maruyama

Taguchi

2021

Nat Hazards

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Driving after natural disasters entails a substantial amount of stress; therefore, the number of motor vehicle crashes may increase. However, few studies have examined this issue. This study investigated motor vehicle crashes after the 2016 Kumamoto earthquake in Japan. Monthly data about crashes resulting in property damage from 49 municipalities in Kumamoto from 2015 to 2018 were used. An interrupted time series analysis using Poisson or negative binomial regression models was conducted for 49 municipalities; the models were estimated for four classified areas to obtain the robust results. We found that property damage crashes increased significantly in the heavily affected area (Relative Risk (RR) = 1.48, 95% Confidence interval (CI): 1.29, 1.71) and the affected area (RR = 1.25, 95% CI: 1.15, 1.36) after the earthquake. A mountainous area showed a reduction in property damage crashes despite its heavy damage (RR = 0.74, 95% CI: 0.67, 0.82), which can be attributed to the closure of its main gate routes. The unaffected area showed no difference before and after the earthquake. Geographical presentation of the result demonstrates a clear positive association of earthquake damage and increased crashes. The findings of this study highlight the importance of motor-vehicle-crash alerts after an earthquake.

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How resilient is the labour market against natural disaster? Evaluating the effects from the 2010 earthquake in Chile

Cited by 17 publications

References 43 publications

Natural disasters and technological upgrading measured by changes in demand for ICT labour: Estimating the impacts with text

Natural disasters and technological upgrading measured by changes in demand for ICT labour: Estimating the impacts with text

Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models

Increased motor vehicle crashes following the 2016 Kumamoto earthquake, Japan: an interrupted time series analysis of property damage crashes

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