When the Dust Settles: Productivity and Economic Losses Following Dust Storms

Birjandi-Feriz, Maliheh; Yousefi, Kowsar

doi:10.2139/ssrn.3230265

Cited by 8 publications

(8 citation statements)

References 36 publications

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“…6. Several other (ongoing) studies are using this data sets, e.g., Rahmati and Karimirad (2017), Esfahani and Yousefi (2017), Birjandi-Feriz and Yousefi (2017), Rahmati and Pilehvari (2019), Mahmoudzadeh et al (2018), Esfahani and Amini Behbahani (2018).…”

Section: Notesmentioning

confidence: 99%

Growth through export: evidence from Iran’s manufacturing plants

Yousefi¹,

Madanizadeh

Sobhani³

2020

JES

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PurposeDoes the long-term growth rate of a firm increase by exporting? If yes, how large is that increase in a developing economy? The paper aims to discuss this issue.Design/methodology/approachThe authors incorporate data from the manufacturing plants in Iran as a developing economy for 2003–2011 to address this question. Using fixed effect panel and propensity score matching method, the authors examine whether exportation can affect a firm’s growth rate to test for the learning to grow hypothesis.FindingsThe findings document that: not only the exporters are larger and more productive than non-exporters, but they also grow faster in size and productivity measures as well. Additionally, the authors find that the rise in the growth rate is a short-term phenomenon and it disappears in the second year; meaning that exportation does not have a permanent growth effect. The findings are consistent with a spot effect of learning, compared to a permanent growth engine. Results are robust to different analysis tests.Originality/valueThe authors investigate the learning effect of exporting within recently released firm-level data of a developing country.

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Section: Notesmentioning

confidence: 99%

Growth through export: evidence from Iran’s manufacturing plants

Yousefi¹,

Madanizadeh

Sobhani³

2020

JES

Self Cite

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“…To estimate the causal impact of SDS on crop revenue and production, a fixed effect regression was selected to exploit random year-to-year variation in dust exposure in Mongolia. The analysis largely follow the recent literature on the impact of climate on economy [ 8 , 20 , 21 ], which are also more recently adopted by researchers analysis the impact of sand and dust storms [ 22 , 23 ]. Our econometric specification benfits from the previous literature and we construct a standard panel model to estimate the following Eq: …”

Section: Estimation Strategy and Identificationmentioning

confidence: 99%

“…In an attempt to address the endogeneity bias in our estimation, an alternate specification of the baseline model using only non-local dust events was employed as a possible workaround to address potential bias that may affect the robustness of the estimates from the baseline model. Referring to Table 1 , externally or non-local emitted dusts are indicated by the WMO’s weather state code 06 originated in areas more than 50 miles away [ 22 ]. Non-local dust events are therefore exogenous to the local production and should significantly mitigate the endogeneity bias.…”

Section: Estimation Strategy and Identificationmentioning

confidence: 99%

Assessing the impact of sand and dust storm on agriculture: Empirical evidence from Mongolia

2023

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Assessing the economic impact of sand and dust storms provides critical insights to policy development and reforms; a subject that is gaining more attention as risk management becomes the dominant approach for hazard mitigation policies. To assess the causal impact of sand and dust storms on agriculture, specifically on crop and livestock revenue and physical production, random year-to-year variations in dust exposure were analyzed using a fixed effect regression. To complete this analysis, weather and climate data from the on-ground meteorological stations was combined with the household level socioeconomic surveys conducted by Mongolia’s National Statistics Office (NSO) over a decade. The descriptive statistics of the meteorological data collected over the eight years period show that, on average, 29 dust events have occurred every year across the country, with greater variation among provinces (Aimags) and regions, reaching up to 108 events in a year in some provinces. The overall trend reveals a slight decrease in the dust events from 2009 to 2019. The econometric results show that value of crop and livestock production (gross income) and physical yields significantly decline in response to higher frequencies of sand and dust storms events. During this period, Mongolia experienced a 2.7% decline in crop revenue as a result of additional sand and dust storms. Assuming 2.7% constant decline in revenues across all agricultural sub-sectors and regions or Aimags, this could lead to about $37.8 million in losses to the economy, which is equivalent to about 0.27% of the national GDP of Mongolia. Increases in the frequency of sand and dust storms could reduce agricultural productivity by between 1.5% to 24%, depending on the crop. Estimates from the modelling exercise are robust to potential endogeneity bias in the measure of sand and dust storms; different specification and identification approaches accounting for the endogeneity bias consistently reveal negative and qualitatively similar impacts of sand and dust storms on crop and livestock productivity.

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“…Grapes (Behrouzi et al 2019 ) and oak forests (Moradi et al 2017 ) were also negatively impacted. The economic impact of reduced industrial productivity was estimated to be $US 149 million (0.04% GDP) per day for large dust events (Birjandi-Feriz andYousefi, 2017 ), mostly due to effects on workers’ health and safety as well as disruptions in transportation. Meibodi et al ( 2015 ) determined the total annual economic loss to Iran due to dust storms was $US 1 trillion (1000 million).…”

Section: Review Of Common Natural Hazards As Analogsmentioning

confidence: 99%

A review of common natural disasters as analogs for asteroid impact effects and cascading hazards

et al. 2023

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Modern civilization has no collective experience with possible wide-ranging effects from a medium-sized asteroid impactor. Currently, modeling efforts that predict initial effects from a meteor impact or airburst provide needed information for initial preparation and evacuation plans, but longer-term cascading hazards are not typically considered. However, more common natural disasters, such as volcanic eruptions, earthquakes, wildfires, dust storms, and hurricanes, are likely analogs that can provide the scope and scale of these potential effects. These events, especially the larger events with cascading effects, are key for understanding the scope and complexity of mitigation, relief, and recovery efforts for a medium-sized asteroid impact event. This paper reviews the initial and cascading effects of these natural hazards, describes the state of the art for modeling these hazards, and discusses the relevance of these hazards to expected long-term effects of an asteroid impact. Emergency managers, resource managers and planners, and research scientists involved in mitigation and recovery efforts would likely derive significant benefit from a framework linking multiple hazard models to provide a seamless sequence of related forecasts.

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When the Dust Settles: Productivity and Economic Losses Following Dust Storms

Cited by 8 publications

References 36 publications

Growth through export: evidence from Iran’s manufacturing plants

Growth through export: evidence from Iran’s manufacturing plants

Assessing the impact of sand and dust storm on agriculture: Empirical evidence from Mongolia

A review of common natural disasters as analogs for asteroid impact effects and cascading hazards

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