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Extreme Weather Events and Internal Migration: Evidence from Mongolia
Julian Roeckert1,2 &
Kati Kraehnert ORCID: orcid.org/0000-0001-7319-95811
Economics of Disasters and Climate Change volume 6, pages 95–128 (2022)Cite this article
This article examines the effects of extreme weather events on internal migration in Mongolia. Our focus is on dzuds, extremely harsh winters characterized by very cold temperature, snowfall anomalies, and/or storms causing very high livestock mortality. We exploit exogenous variation in the intensity of extreme winter events across time and space to identify their causal impacts on permanent domestic migration. Our database is a time series of migration and population data at provincial and district level from official population registries, spanning the 1992-2018 period. Results obtained with a two-way fixed effects panel estimator show that extreme winter events cause significant and sizeable permanent out-migration from affected provinces for up to two years after an event. These effects are confirmed when considering net change rates in the overall population at the district level. The occurrence of extreme winter events is also a strong predictor for declines in the local population of pastoralist households, the socio-economic group most affected by those events. This suggests that the abandonment of pastoralist livelihoods is an important channel through which climate affects within-country migration.
Extreme weather events, like droughts, floods, storms, and hot spells, cause considerable economic losses. Rural farm households in developing countries suffer more than others from such weather shocks due to their geographical exposure and their dependency on rain-fed agriculture (Harrington et al. 2018). In the absence of effective post-shock coping and long-term adaptation strategies, exposed households may resort to migration when climate-sensitive livelihoods are threatened by extreme weather events (Jha et al. 2018). The sudden occurrence of extreme weather events may lead to migration choices that are forced, rather than the result of a carefully planned process (Berlemann and Steinhardt 2017). If changing climatic conditions indeed matter for population mobility, the number of climate migrants is likely to accelerate in the years to come (Hunter and Nawrotzki 2016), as extreme weather events are predicted to increase both in their frequency and their intensity with global warming (Pachauri et al. 2014; WMO 2020). This outlook has stimulated an increased interest among policy stakeholders and the academic community alike in what role changing climatic conditions play as drivers for internal and international migration (Hoffmann et al. 2020).
The empirical literature on the climate-migration nexus has evolved rapidly in the new millennium (Berlemann and Steinhardt 2017). While most studies identify extreme weather conditions as a relevant driver for population mobility, the empirical evidence does not provide a clear-cut picture. Different results are obtained for internal and international migration as well as for the effects of gradual climate change and sudden weather events. The effect size also varies substantially across approaches and data used (Hoffmann et al. 2020). A further source of heterogeneity in results stems from the specific weather conditions and the institutional context considered. Besides climate, migration is also shaped by cultural, geographical, institutional, and socio-economic factors at the place of origin (Grecequet et al. 2017). In order to advance the state of knowledge, studies examining the climate-migration nexus in individual countries are particularly warranted (Berlemann and Tran 2020), as climate-related internal migration flows are more pronounced than cross-border migration (Hoffmann et al. 2020). This is particularly relevant in the context of developing countries, where internal migration is often more feasible and affordable to households as compared to costly international movements (Beine and Parsons 2015).
In this paper, we investigate internal migration dynamics in Mongolia. This East Asian country is particularly exposed to extreme winter events, locally referred to as dzuds, which puts Mongolia among the most severely affected countries by natural hazards globally (CRED 2020).Footnote 1 Such extreme winter events cause mass livestock mortality by starving or freezing animals to death. Through livestock mortality, winter events destroy the income, consumption, and asset base of pastoralist households, thereby directly threatening the livelihood of large parts of the rural population that live from animal husbandry. Our analysis aims at quantifying if, and to what extent, extreme winter events drive internal migration in Mongolia. We draw on a long time series of annual in- and out-migration and population data from population registries at the provincial and district level, spanning the 1992-2018 period. Using a two-way fixed effects panel estimator, we exploit spatial and temporal variation in the intensity of extreme winter events to identify the causal effects of these events on migration and population dynamics.
The exceptionally rich data at hand allow us to expand the existing literature on internal migration and climate in four ways. First, existing macro-level studies almost exclusively proxy internal migration with urbanization rates, a rather imprecise measure that overlooks certain forms of internal migration, such as rural-to-rural migration (Hoffmann et al. 2020). In contrast, the availability of annual population registry data at the provincial and district levels allow us to study internal migration dynamics across administrative units throughout the country. Second, in existing micro-level studies that draw on population census data, a timely attribution of extreme weather events is complicated by long census intervals and potential biases stemming from self-reported migration information. Studying longer-term within-country migration dynamics using existing household panel surveys is also challenging, as panel surveys are scarce for developing countries and often only cover narrow regional settings and time periods. Against this backdrop, the yearly migration data at hand spanning almost three decades allow us to directly link the occurrence of extreme weather events with migration responses. Third, our analysis provides insights into the channels through which extreme weather events affect migration by considering net changes in the local population of pastoralist households whose livelihood is immediately affected by these events. Fourth, while existing studies on climate-induced migration focus on extreme temperatures (Hirvonen 2016; Thiede and Gray 2017), precipitation (Thiede et al. 2016), flood (Ruiz 2017), storms (Groeger and Zylberberg 2016; Koubi et al. 2016; Mahajan and Yang 2017), and drought (Dallmann and Millock 2017; Ruiz 2017), we provide evidence from another type of extreme weather event that has received less scholarly attention – extremely harsh winter conditions featuring extremely cold temperature, snowfall anomalies, and/or storms.
Results from the two-way fixed effects panel estimator show that extreme weather events occurring during the 1992-2018 period trigger significant and sizeable net out-migration from affected provinces for up to two years after an event. The finding is robust to the inclusion of time-varying controls for provincial characteristics. The district-level analysis confirms these results: We find a significant, negative, and strong effect of extreme weather events on the net population change rate across districts. Lastly, both province and district-level analyses reveal that extreme weather events significantly reduce the local population of pastoralist households.
The paper is organized as follows. Section 2 reviews the existing literature on climate-related internal migration dynamics. Sections 3 and 4 provide background information on extreme weather events and migration patterns in Mongolia. Section 5 introduces the empirical model and the data employed in the study. Results are discussed in section 6, while section 7 summarizes the key findings and concludes.
Review of the Evidence on Climate-Induced Internal Migration
The Intergovernmental Panel on Climate Change (IPCC) stressed the significance of climate-related migration and displacement as early as 1990. In that year, the IPCC put forth that the single most significant impact of climate change could be human migration, through the displacement of millions of people through the occurrence of shoreline erosion, coastal flooding, and agricultural disruption (Brown 2008). Since then, various predictive studies aimed at estimating the expected number of climate-induced migrants in the decades to come. For internal migration, Rigaud et al. (2018) estimate that without global and national climate action, climate change will displace more than 143 million people within their countries by the year 2050 in Sub-Saharan Africa, South Asia, and Latin America alone.
The empirical literature quantifying whether and how climate change affects migration flows only started to evolve in the early 2000s (Berlemann and Steinhardt 2017). With the increased availability of weather and migration data, the literature has developed rapidly since then. Existing studies differ in a number of dimensions, including the type of migration considered (international versus internal), the push factors analyzed (extreme weather events versus gradually changing climate), and the approach taken (micro versus macro). In the following, we outline developments and limitations in the empirical literature on climate and within-country migration.Footnote 2 The two main approaches used in existing research – macro-level approaches capturing gross migration flows and micro-level approaches building on survey and census data – are discussed in turn.
In the existing macro-level literature, internal migration flows are most commonly proxied by national urbanization rates (Hoffmann et al. 2020). For instance, Barrios et al. (2006) estimate the impact of rainfall shortages on urbanization patterns in a cross-country dataset, using a year- and country fixed effects approach. Findings suggest that declines in rainfall are an important determinant of urbanization in Sub-Saharan Africa. Applying a similar approach to fine-grained data, Henderson et al. (2017) exploit district-level heterogeneity in precipitation to analyze the determinants of urbanization rates across Sub-Saharan African countries and find that drier conditions increase urbanization in regions where cities are likely to be manufacturing centers. In contrast, in market cities that provide local services to farmers and lack structural transformation, drying has little impact on urbanization or total urban incomes. A positive link between rainfall shortages and urbanization is also documented by other studies of Sub-Sahara Africa (e.g., Brueckner 2012; Marchiori et al. 2012). Beine and Parsons (2015) examine urbanization in the aftermath of both sudden-onset disasters recorded by the Centre for Research on the Epidemiology of Disasters (CRED) as well as gradual changes in precipitation and temperature patterns, using cross-country data. When looking at the sub-sample of developing countries, Beine and Parsons find that extreme weather events significantly increase urbanization, while no significant effects are found for international migration. One limitation of these macro-level approaches is the rather narrow focus on rural-to-urban migration, thus providing an incomplete picture of overall internal migration dynamics (Hoffmann et al. 2020). Furthermore, the multi-country approach and, in turn, the usage of a country fixed effects specification makes it impossible to examine the role of socio-economic and contextual factors that are specific to individual countries.
Micro-level studies building on census or survey data from a single country are partly able to overcome these limitations as micro data usually allow controlling for a wide array of local characteristics (e.g., Carvajal and Pereira 2009; Goldbach 2017; Gray and Mueller 2012; Groeger and Zylberberg 2016; Koubi et al. 2016; Paul 2005). Given that surveys are often only collected in selected regions within a country, movements of whole households outside the survey area lead to attrition bias if households are not traced. For this reason, studies building on household survey data tend to focus on the determinants of migration decisions of individual household members. In most of these studies, variants of the gravity model are used as a flexible approach to modeling spatial interactions, assuming that migration varies with the degree of the force of attraction and is inversely proportional to distance (Poot et al. 2016). In more advanced applications, the gravity model is extended by variables representing economic, climatic, and other characteristics of the place of origin and destination (Tsegai and Bao Le 2010). Within this group of studies, gradual climate change and extreme weather events are often found to matter for migration (e.g., Carvajal and Pereira 2009; Gray 2009; Groeger and Zylberberg 2016; Koubi et al. 2016). Notwithstanding, the overall evidence remains mixed, with other studies finding no systematic evidence of weather-induced within-country mobility (Bohra-Mishra et al. 2014; Di Falco et al. 2012; Goldbach 2017; Gray and Mueller 2012; Paul 2005).
Most closely related to our approach, another group of studies analyzes migration flows between regions by aggregating micro-level data to higher administrative divisions. In a study on Costa Rica, Robalino et al. (2015) analyze the impact of extreme weather events on internal migration flows over the 1995-2000 period. The authors use population census data from 2000, aggregated to the canton level, which are combined with the DesInventar database that records both the frequency and intensity of natural disasters, such as floods and landslides. In a gravity model framework, cross-canton gross migration rates are modeled as a function of population size, distance, as well as a set of push and pull factors that influence migration decisions, such as education levels, health infrastructure, security, and amenities. Robalino et al. find that natural disasters resulting in fatalities decrease out-migration, while the opposite holds for those disasters not causing numerous deaths. Using a similar approach, Saldana-Zorilla and Sandberg (2009) draw on population census data from Mexico, aggregated to the municipality level, and merge this database with secondary data on the occurrence of natural disasters. An increase in disaster frequency significantly increases out-migration from affected municipalities between 1990 and 2000. This effect is particularly pronounced in those regions defined as marginalized by government agencies, where agricultural production continues to constitute the main resource of livelihoods. In a study on Vietnam, Berlemann and Tran (2020) test if exposure to natural disasters cause households to temporarily or permanently emigrate from their communes. The database used in this study is commune-level data collected as part of a household panel survey implemented in 2012, 2014, and 2016. The measure of shock intensity – whether a given commune was affected by floods, typhoons, and droughts in the one and two years preceding each survey wave and whether each disaster type became worse over the last decade – is recorded from administrative officials in the commune questionnaire. Using a commune and year fixed effects approach, Berlemann and Tran show that droughts primarily cause temporary out-migration, while flood events tend to induce permanent out-migration from affected communes. In contrast, typhoons remain without any significant effects in both the short and the long runs.
Yet, studies building on micro-level data are often constrained by the quality and availability of suitable data. Specifically, there is a trade-off between the frequency of observations and geographical coverage in micro data, a common issue in the migration literature (Berlemann and Steinhardt 2017). While drawing on population census data allows for undertaking nationwide studies of internal migration, these are typically only available at five-year intervals. This makes a timely attribution of adverse weather effects difficult, which is problematic for sudden-onset disasters. Although socio-economic household surveys tend to be collected at shorter intervals, these are often limited in their geographical scope. In addition, household panel survey data is typically not available for long time horizons. This is especially the case for developing countries, where migration in response to adverse climatic conditions is likely to be most pronounced. Further, information on migration is usually self-reported through retrospective survey questions on censuses and surveys, while several studies also rely on measures of weather shocks that are self-reported by respondents. This renders studies based on micro-level data prone to reporting and reinterpretation biases.
We contribute to the existing literature by exploiting a long time series of annual in- and out-migration data at the provincial and district levels in Mongolia, which allows us to capture heterogeneity in the frequency and intensity of extreme weather events across time and space. The availability of yearly data allows us to attribute the effects of extreme weather events to migration patterns in the same year. From a methodological perspective, the rare possibility to exploit long-term population registry data at the sub-national level offers two advantages. First, as the measure of migration is based on reliable registration data, our analysis is not subject to reporting bias. Second, we capture migration rates across administrative units, while existing studies often have to draw on urbanization rates as an imprecise proxy for internal migration dynamics. Thus, our analysis overcomes common shortcomings of both micro- and macro-level studies on internal migration in the aftermath of extreme weather shocks.
Rural Livelihoods and Extreme Weather Events in Mongolia
Mongolia is already severely impacted by climate change. Temperature data recorded at weather stations across the country show that the annual mean air temperature has increased by 2.24 degrees Celsius between 1970 and 2015, a figure well above the global average (Ministry of Environment and Tourism 2018). Evidence also suggests that precipitation patterns and intensities are changing (Nandintsetseg et al. 2021; Goulden et al. 2016). Aside from gradual climatic changes, the country is increasingly exposed to extreme winter events (Palat Rao et al. 2015; Nandintsetseg and Shinoda 2015). In Mongolian, extreme winter events are referred to as dzuds, which literally means the mass deaths of livestock without attributing an exact underlying cause.Footnote 3 Extreme winter events may result from the interplay of several unfavorable weather phenomena, while the exact triggering conditions differ across winters (Lehmann-Uschner and Kraehnert 2018). The Mongolian language uses various terms to distinguish between different types of dzud (Hahn 2017, p. 42 f.; Murphy 2011, p. 32 f.): In tsagaan dzud, deep snow inhibits animals from reaching the grass underneath the snow cover, thus causing animal to die from starvation. A khar dzud is characterized by a lack of snow (often in combination with harsh and cold winter storms), thereby reducing the available forage and the main source of drinking water for animals during winter. A tumer dzud features excessive precipitation during the winter months, followed by a sudden temperature drop that creates a shield of ice that is impenetrable for animals and, in turn, leads to animal starvation. A khuiten dzud is characterized by extremely low temperatures, causing animals freezing to death, which may occur jointly with harsh winter storms. Lastly, a khavsarcan dzud is identified by a combination of deep snow and extremely cold temperature.
Extreme winter events have severe impacts on the rural economy, especially the agricultural sector. In 2018, 40% of the labor force living outside of the capital of Ulaanbaatar derived their livelihood solely from animal husbandry (NSO 2021). Herding continues to be the single most important occupation in rural areas. Most pastoralist households keep large shares of their wealth in their herds, holding an average of 288 animals as of 2018 (ibid.). The five most commonly held species – goats, sheep, horses, cattle, and camels – not only provide food and income to households but also serve as collateral for loans (Hahn 2017). Practicing an extensive system of livestock production, Mongolian pastoralists graze their animals on open rangelands year-round, which makes them directly dependent on weather conditions. Most, though not all, pastoralists are either semi or fully nomadic, moving their herd between two and 14 times per year (Teickner et al. 2020), typically performing the same cycle of movements every year. Extreme winter events that cause livestock to freeze to death or die of starvation within short periods of time pose an immediate threat to the viability of pastoralist livelihoods (Hahn 2017). Sudden mass livestock mortality is often aggravated if drought conditions in the preceding summer led to a situation where animals are not starting the winter months at full strength (Palat Rao et al. 2015).
Extreme winter events have occurred throughout Mongolian history. However, such events have become both more frequent and more severe, with historic records indicating that 15 extreme winter events in the eighteenth century were followed by 31 extreme winter events in the nineteenth century and 43 events in the twentieth century (Hahn 2017). Figure 1 illustrates that five extreme winter events that affected large parts of the country occurred between 1992 and 2018, the period under study here. Further extreme events occurred in specific regions over this time period.
Annual livestock losses in Mongolia, 1990-2020. Note: The vertical dashed lines indicate years when extreme winter events affected large parts of the country (while in some further years, extreme winter events occurred in specific regions). Livestock losses are the sum of losses across the five dominant species (goats, sheep, horses, cattle, and camels). Source: Mongolia Livestock Census
With more than 10 million dead animals, the 2009/10 extreme winter caused roughly 24% of the total national livestock to die, the largest livestock losses recorded in a single winter in the last 50 years (NSO 2021). Some 40% of all herding households lost more than half of their herd during the 2009/10 winter (UNDP NEMA 2010). With these tremendous losses of livestock, it can take years for herders to rebuild their herds following an extreme winter event (Bertram-Huemmer and Kraehnert 2018). Exposure to extreme winter events also increases the likelihood that pastoralists are forced to abandon the herding economy (Lehmann-Uschner and Kraehnert 2018), particularly if their herd size is pushed below the threshold of 100 animals that is often considered the minimum necessary for sustaining a pastoralist livelihood in the long term (Goodland et al. 2009). There is also large spatial heterogeneity in the intensity of any given extreme winter event (Middleton et al. 2015). Figure 2 shows that different areas of the country were hit by extreme events in different years, while their intensity differed even across neighboring provinces and districts.
Spatial variation in livestock mortality in selected years. a Province-level livestock mortality rate. b District-level livestock growth rate. Note: Livestock mortality and growth rates are calculated as the average across the five dominant species (goats, sheep, horses, cattle, and camels). Source: Mongolia Livestock Census
Migration Patterns in Mongolia
Throughout the twentieth century and beyond, internal migration has played an important role in Mongolia (IOM 2018a). In the era of centrally planned economy, influenced by the Soviet Union, industrial centers were established in urban areas across the country. While migration was controlled by the administration, large parts of the rural population were attracted to these centers because of employment prospects (Guinness and Guinness 2012). Thereby, the share of the urban population rose dramatically. The fall of the Iron Curtain brought profound political changes and the collapse of wide parts of the industrial sector. The resulting freedom of movement led to reverse migration dynamics from urban to rural areas (ibid.). The herding economy offered a promising prospective for many Mongolian families, as livestock ownership was privatized and collectives disappeared.
Since the late 1990s, Mongolia has experienced renewed rural to urban migration, in particular to the capital of Ulaanbaatar. The percentage of Mongolians living in urban areas increased from 53% in 1995 to 68% in 2018 (NSO 2021). From one million inhabitants in 2007, Ulaanbaatar grew to 1.5 million in 2018 (United Nations 2021). Most migrants arriving in Ulaanbaatar seek shelter in the so-called ger districts, where most dwellings are traditional Mongolian tents (gers) (Sigh et al. 2017). In 2014, approximately 60% of Ulaanbaatar's population lived in these districts, which are mostly located on the outskirts of the city (Engel 2015). As many of the ger districts formed in a hastily and uncontrolled way, they are often poorly connected to urban utilities and infrastructure. Many inhabitants have to buy and fetch drinking water from government-run kiosks, overall sanitation is poor, and waste removal is organized irregularly (Henreckson 2018). As dwellings in ger districts are poorly insulated and stoves are fired by coal or other biomass, ger districts are hotspots for air pollution, especially in winter.
Intensive urbanization is a major topic in Mongolian politics and urban planning. At the beginning of 2017, the governor of Ulaanbaatar, together with the mayor of the capital, issued a law officially prohibiting domestic permanent migration from rural areas to the capital city (IOM 2018b). In 2018, the migration ban was extended to the beginning of 2020 (NSO 2020). As the law prevents migrants from rural areas from registering in the capital, the number of unregistered migrants in Ulaanbaatar has risen. Without an official resident status, it is difficult to find stable employment and impossible to access basic services, such as schools, daycare, health care, and social welfare, causing high vulnerability among unregistered migrants (IOM 2018b).
In the Mongolian context, the driving forces of internal migration are not well understood. The few existing qualitative studies associate rural to urban migration dynamics with poverty, low agricultural incomes at origin, income opportunities at destination, environmental degradation, and climate change (IOM 2018a; IOM 2018b; Guinness and Guinness 2012). We are only aware of a single study, by Xu et al. (2021), that examines the drivers of internal migration with a quantitative approach, using cross-sectional data from the Mongolian Labor Force Surveys implemented in 2006, 2010, and 2014. Xu et al. find that being male, young, better educated, and married are strong predictors for rural to urban migration decisions of single household members. Yet, the analysis does not examine the effects of extreme winter events on migration.
Empirical Strategy
We exploit plausibly exogenous variation across time and space in the occurrence of extreme winter events to study their impacts on internal migration dynamics. We estimate the following two-way fixed effects model:
$${M}_{i,t}={\beta}_1{extreme\ event}_{i,t,\left(t-1;t-3\right)}+{\beta}_2{C}_{i,t}+{\alpha}_i+{\lambda}_t+{\mu}_it+{\varepsilon}_{i,t}$$
As the outcome of interest, we employ various proxies for internal migration Mi, t, measured at province (or district) i in year t. Extreme eventi, t measures the intensity of an extreme winter event in a given province (or district) and year. Several lags of this measure are included to examine the timing of migration in the aftermath of such events. Ci, t is a vector of time-varying control variables. Province (or district) fixed effects αi control for the unobserved time-constant heterogeneity across administrative units. Year fixed effects λt capture events and developments affecting all administrative units in the same way, while province- (or district-) specific linear time trends μit control for different long-run trends in migration figures of individual provinces (or districts). εi, t denotes the unexplained residual. Standard errors are clustered at the province (or district) level.
The empirical analysis builds on data at the level of provinces and districts, the first- and second-level administrative subdivision of Mongolia, respectively. Aside from the capital city, the country consists of 21 provinces (aimags), which are subdivided into 331 districts (soums). The capital of Ulaanbaatar is subdivided into nine so-called düüregs, which are often considered equivalent to districts. In the empirical analysis, we follow this categorization and, furthermore, treat Ulaanbaatar as one province. Our sample consists of 22 provinces and 340 districts, for which yearly data spanning the 1992-2018 period is available.
Province-Level Analysis
The first outcome is the net migration rate per province and year, which we calculate as follows:
$$M{\left( net\ migration\ rate\right)}_{i,t}=\frac{\left({I}_{i,t}-{E}_{i,t}\right)}{\left({P}_{i,t}/\mathrm{1,000}\right)}$$
where Ii, t stands for the number of in-migrants entering province i during year t, Ei, t captures the number of out-migrants leaving province i during year t, and Pi, t is the mid-year population of province i in year t. A positive value reflects net immigration, a situation where an excess of persons are entering a given province, while a negative value mirrors net emigration, a situation where an excess of persons are leaving a given province. Specifically, a value of −10 in the net migration rate for a given year means that 10 out of 1000 inhabitants leave their province in the course of one year. Across all provinces and years, the net migration rate has a negative mean (−10.3) because of international out-migration.Footnote 4 Data on the number of in- and out-migrants and the total population come from official population records maintained by the National Statistical Office of Mongolia (NSO 2013). Mongolian law requires migrants to de-register at their place of origin and re-register at destination within ten days after moving. Note that this outcome does not capture temporary migration, for instance, individuals searching for seasonal employment outside of their registered place of residence or nomadic herders crossing province boundaries as part of their annual cycle of movements. One limitation that goes along with using official registration data is that it does not capture any form of unofficial movements of migrants who either choose not to register or are banned from registering at their destination.Footnote 5 Our results should be considered as lower bound estimates of total internal migration.
The second outcome is the net change rate in the local number of pastoralist households,Footnote 6 the socio-economic group we expect to be most immediately affected by extreme weather events:
$$M{\left( net\ change\ rate\ pastoralist\ households\right)}_{i,t}=\frac{\left({PPbegin}_{i,t}-{PPend}_{i,t}\right)}{\left({PPmid}_{i,t}/\mathrm{1,000}\right)}$$
where PPbegini, t is the number of pastoralist households in province i at the beginning of year t, PPendi, t is the number of pastoralist households in province i at the end of year t, and PPmidi, t represents the mid-year number of pastoralist households in province i and year t.
We proxy the intensity of extreme winter events with livestock mortality per province and year. Livestock mortality is considered an appropriate measure for the intensity of such events (Murphy 2011; Skees and Enkh-Amgalan 2002).Footnote 7 The data come from the annual Mongolia Livestock Census, which the NSO has been implementing since 1918. Each year in December, enumerators record the number of livestock held by herders across the country as well as the number of livestock that died in the previous 12 months, both broken down for each of the five commonly held species. Based on this historical data, we proxy the occurrence of an extreme winter event with a dummy variable taking the value of one if the average livestock mortality rate across species exceeds 6% for a given province and year. Our choice of the 6% threshold is informed by the operating index-based livestock insurance, where a livestock mortality rate of 6% triggers indemnity payouts to insured households.Footnote 8 We employ an alternative threshold as well as the continuous livestock mortality rate as robustness test.
To select a set of province-level control variables, we draw on the existing literature that employs variants of the gravity model for migration (e.g., Berlemann and Tran 2020; Borjas 1987; Dallmann and Millock 2017; Tsegai and Bao Le 2010).Footnote 9 To proxy the local economic performance, we include the revenue of the provincial government, which consists of tax income; revenues from interests, dividends, and fines; as well as transfers and grants from the central government and the fund for local development. Another economic measure is the unemployment rate, which reflects the economic attractiveness of a province. As proxy for the quality of the local infrastructure, we account for the number of households with access to portable water. As this indicator does not represent the situation of all nomadic households, we additionally include the total number of water supply stations per province.Footnote 10 The number of physicians per 10,000 inhabitants is used as measure for the quality of health care provision. Lastly, we employ the share of students continuing from the first to the fifth grade as proxy for the quality of the local educational system. Overcontrolling is an issue that often arises when quantifying the impact of major shocks on an outcome variable in a gravity model framework (Berlemann and Steinhardt 2017; Dell et al. 2014). If a control variable is in itself influenced by the shock, any empirical migration model that includes such control is likely to capture only partial effects of the shock on the outcome (Berlemann and Tran 2020). We approach this issue by presenting results both obtained from a model without controls and with the full set of controls.
District-Level Analysis
We further estimate migration dynamics at the district level, which increases the number of observations by factor 15. As data on the number of migrants is not publicly available at the district level, we employ the net population change rate as a proxy for overall migration dynamics as main outcome, which we define as follows:
$$M{\left( net\ population\ change\ rate\right)}_{i,t}=\frac{\left({Pbegin}_{i,t}-{Pend}_{i,t}\right)}{\left(P{mid}_{i,t}/\mathrm{1,000}\right)}$$
with Pbegini, t representing the resident population in district i at the beginning of year t, Pendi, t stands for the population in district i at the end of year t, and Pmidi, t is the mid-year population of district i in year t. Besides migration, the net population change rate is also shaped by the number of births and deaths.Footnote 11 A value of −10 in the net population change rate for a given year means that the district population decreased by 10 out of 1000 inhabitants in the course of one year. The second outcome is the net change rate in the total number of pastoralist households per district, which is calculated analogously to eq. 3 above.
For the period of interest, annual district-level data from the Mongolia Livestock Census is only available for the total number of living animals (by species), but not for the number of deceased animals. We approximate the district-level livestock mortality with year-to-year changes in overall livestock numbers.Footnote 12 To proxy the occurrence of an extreme winter event, we define a dummy variable that takes the value of one if the yearly growth rate in total livestock numbers across species is below −6% for a given district and year. As no time-varying controls are available at the district level, we employ the same controls as in the province-level analysis.
Summary statistics of the key variables of interest are tabulated in Table 1.
Table 1 Summary statistics
Results from the baseline two-way fixed effects OLS regression on the determinants of the province-level net migration rate are displayed in Table 2. When considering the impact of extreme winter events on the net migration rate in the same year (column 1), the estimated coefficient of the extreme events proxy is negative, indicating higher total emigration, albeit not statistically significant at conventional levels. When lagging the shock measure by one year (column 2), the effect size more than triples in magnitude and is statistically significant at the 1% level. The occurrence of an extreme winter event on average decreases the net migration rate by 7.045 in the year after the event strikes. This corresponds to a net out-migration of more than 7 individuals per 1000 or 0.7% of the provincial population. This is a sizable effect, constituting roughly 70% of the sample mean and 36% of the standard deviation.Footnote 13 The effect of extreme winter events on the net migration rate in affected provinces remains statistically significant (at the 10% level), although it is slightly smaller in magnitude, two years after an extreme weather event (column 3). Exposure to such events has no significant effect on net migration rates three years after an event (column 4). Column 5 displays results when including the full set of time-varying province-level controls in model 2, which yields the strongest results.Footnote 14 The effect of the extreme event is highly significant, though smaller in magnitude compared to the model without controls. This is in line with expectations, as more and possibly endogenous controls absorb parts of the total effect. In column 6, we interact the shock proxy with the five regions of Mongolia. The marginal effects of the lagged extreme weather event on the net migration rate for individual regions are negative and significant in the Western, Khangai, and Central regions, while it is positive and significant for the capital city of Ulaanbaatar. This finding is in line with qualitative reports suggesting that internal migration in Mongolia is particularly driven by rural-to-urban migration.
Table 2 Determinants of net migration rate at the province level, 1992-2018
All baseline results hold when we restrict the sample to a more narrow time window, including the 1995-2018 period, the 1992-2016 period, and the 1995-2016 period (Table 7 in the Appendix). These findings assure us that potential anomalies in the net migration rate in the direct aftermath of the fall of the Iron Curtain and the migration ban to Ulaanbaatar enacted in 2017 are not individually or jointly driving the results. In a further robustness test, we only consider the most extreme events, in which the annual livestock mortality rate exceeded 15% in a given province and year (Table 8 in the Appendix). As in the baseline specification, the effect of particularly severe extreme events on the net migration rate is statistically significant and economically large one year after the event (column 2). In contrast to baseline results, the effect is also significant in the year the disaster occurs (column 1). We obtain similar findings – statistically significant and sizable effects of livestock mortality on the net migration rate in the same year as well as one and two years later – when proxying shock intensity with a continuous measure of livestock mortality (Table 9 in the Appendix).Footnote 15
Table 3 displays results from the district-level model. The outcome is now defined more broadly as the net population change rate, which, besides migration, is also shaped by the number of births and deaths. Results confirm the patterns found in the baseline model: The occurrence of a local extreme weather event significantly and strongly lowers the population in districts up to two years after an extreme event (column 1-3), while the effect is no longer significant three years after an event (column 4). Again, the estimated effect remains comparable in terms of significance level and magnitude when including the full set of time-varying controls (column 5). The inclusion of regional interaction terms in column 6 shows that the negative effects on the population change rate are particularly pronounced in the Western and Khangai regions. When differentiating between the net population change rate among the female population (column 7) and the male population (column 8), the estimated coefficients of extreme weather events are of similar size (we cannot reject the null hypotheses of equality of coefficients, with the p value of a Wald chi square test accounting for the simultaneous (co)variance matrix of the coefficients of extreme weather events being 0.47). This suggests that entire households migrate as response to extreme events.
Table 3 Determinants of net population change rate at the district level, 1992-2018
Next, we investigate the effects of extreme winter events on the net change rate of pastoralist households, the population sub-group whose livelihood is most immediately affected by such events and climate change in general (Table 4). The occurrence of an extreme event significantly reduces the number of pastoralist households in affected districts in the year the disaster strikes by about 6% (column 1). The effect becomes smaller, but remains significant at the 1% level, one year after the disaster (column 2). Including the full set of time-varying controls yields similar results (column 5).Footnote 16 When differentiating the effect by region (column 6), we find that extreme events significantly reduce the population of pastoralists in all five regions of Mongolia, including Ulaanbaatar.
Table 4 Determinants of net change rate in the number of pastoralist households at the district level, 1992-2018
Lastly, we explore how extreme winter events affects the number of pastoralist households with different herd sizes. We separately estimate the model for seven wealth categories of pastoralist households: (1) households with less than 51 heads of livestock, (2) 51-100 livestock, (3) 101-200 livestock, (4) 201-500 livestock, (5) 501-999 livestock, and (6) 1000 and more livestock. Data on the number of pastoralist households in each wealth category in each province is collected as part of the annual Mongolia Livestock Census. Province-level data is available for 2003 through 2018.Footnote 17 Table 5 displays results. When using the net change rate in the total number of pastoralist households per province as outcome, irrespective of wealth (column 1), we obtain qualitatively similar findings as in the district-level analysis for the 1992-2018 time period displayed in Table 4. When differentiating the effects by wealth category (columns 2-7), we find that extreme winter events significantly reduce the number of pastoralist households owning more than 100 heads of livestock. Indeed, the effect size is largest (−53%) for the wealthiest category of pastoralists owning more than 999 heads of livestock and becomes smaller with decreasing herd size. In contrast, extreme winter events have a significant and positive impact (8%) on the net change rate of pastoralist households in the poorest wealth category who own 1-50 heads of livestock (column 2). We draw two conclusions from these results. First, the occurrence of extreme winter events not only reduces the total number of Mongolian pastoralist households over time. It also increases the number of pastoralists with marginal herd sizes that are considered too small to sustain a herding livelihood in the long term in the harsh Mongolian environment. The poorest category of herders is particularly vulnerable to the impacts of future extreme events. Hence, there is reason to expect that the downward trend in the population of pastoralists will persist if extreme weather events continue to strike in the future. Second, it appears that livestock wealth does not protect households from the adverse effects of extreme winter events, as even the group of wealthiest pastoralists diminishes after such events. This again underlines the sheer magnitude of such extreme events.
Table 5 Determinants of net change rate in the number of pastoralist households by wealth at the province level, 2003-2018
One potential threat for our identification strategy is potential positive autocorrelation across extreme weather events over time, which would result in biased estimates. If the occurrence of extreme weather events is positively autocorrelated, inhabitants of strongly exposed areas may systematically differ in their migration behavior from households in low-risk areas. In order to test for positive autocorrelation across events, the province-level livestock mortality rate for the 1992-2018 time period is regressed on its lagged values in a two-way fixed effects model (Table 6). In addition, we employ an Arellano-Bond estimator. Across specifications, we only find significant effects of livestock mortality lagged by two years on livestock mortality in the current year. As none of the employed models reports positive effects, positive autocorrelation and foresighted migration decisions should not be a major concern.
Table 6 Autocorrelation in province-level livestock mortality rate, 1992-2018
As an additional falsification test, the baseline model is estimated with lead values of the shock proxy (Table 10 in the Appendix). In line with our expectations, extreme weather events that lie 1, 2, or 3 years in the future do not have significant effects on the province-level net migration rate (columns 1-3, respectively).
Our analysis documents that the occurrence of extreme weather events is an important push factor for internal migration in Mongolia. The country is increasingly affected by extremely harsh winters that result in very high livestock mortality, thereby threatening the livelihood of large parts of the rural population. We examine the causal impacts of extreme winter events on internal migration spanning the 1992-2018 period in a two-way fixed effects panel estimator, drawing on migration and population data at the province and district levels.
Findings show that extreme winter events have significant, negative, and sizeable effects on internal migration in Mongolia. The local occurrence of an extreme winter event triggers net outmigration from affected provinces and reduces the overall population in affected districts. Reductions in the local population are strongest in the year an event strikes and remain statistically significant up to two years following an event. The negative effects on population dynamics are particularly pronounced in the Western and Khangai regions. Results are robust to the inclusion of time-varying controls, alternative definitions of the shock proxy and the outcomes, as well as the censoring of the data to more narrow time windows. Furthermore, results do not appear to be driven by positive autocorrelation of extreme weather events over time.
Moreover, the local occurrence of extreme winter events significantly and strongly reduces the population of pastoralist households. This effect is observed across all regions of Mongolia, including the capital city. Wealthiest pastoralists, owning 1000 animals or more, face the strongest reductions in their population size in the aftermath of a winter event. In contrast, the group of pastoralists in the poorest wealth group, owning up to 50 animals, grows significantly in the aftermath of an extreme winter.
One limitation of our study is that with the official population registry data at hand, we are unable to capture informal migration where individuals either chose not to register or are banned from registering. Additionally, temporary migration, such as seasonal employment, is not covered by the available data. The obtained results should be interpreted as the lower bound of actual effects.
Extreme winter events in Mongolia have been increasing in both intensity and frequency throughout the 20th century and beyond (Hahn 2017). The pressure on the herding economy as well as migration responses to weather disasters will in all likelihood further intensify. This has three policy implications: First, there is a need to accommodate a growing urban population, especially in the capital city. This may warrant investments in urban infrastructure, for instance by expanding the water supply network, sewage system, electricity grid, transport system, as well as educational and medical services. Former pastoralists may need to acquire labor market qualifications tailored to the urban job market, while the demand for job opportunities in urban areas will likely rise in general. Second, there is the need to assist pastoralists in adapting to and better coping with future extreme events. Index-based livestock insurance (Bertram-Huemmer and Kraehnert 2018) and early action cash transfers (FAO 2018) appear to be promising tools. Third, more generically, there is a need to foster climate change mitigation and to avoid high-end climate scenarios.
The datasets generated during and/or analyzed during the current study are publically available from the Mongolian Statistical Information Service repository, https://www.1212.mn
Code Availability
The econometric analysis in this study was implemented using the STATA software. The code to replicate the findings are available from the corresponding author upon request.
The original version of this paper was updated to add the missing compact agreement Open Access funding note.
In a 2020 report on the human costs of disasters over the 2000–2019 period, published by the Centre for Research on the Epidemiology of Disasters, Mongolia is ranked as the fifth most affected country when impacts are standardized to population size (CRED 2020, p. 20).
A comprehensive overview of the literature is provided by Berlemann and Steinhardt (2017), Hoffmann et al. (2020), and Millock (2015).
Murphy (2011, p. 42 f.) highlights that, unlike earthquakes or hurricanes, which can also strike and be measured in uninhabited regions, the term dzud is only used to refer to events in which livestock die as a result of extreme conditions of some kind.
Note that the mean does not account for population sizes in respective provinces. The mean national-level net migration rate is −0.169 for the 1992-2018 period.
A survey conducted by the International Organization for Migration in 2018 of some 1000 migrant households arriving in the provinces of Selenge, Dornogovi, and Ulaanbaatar, finds that only one-third of the migrant households registered within the legal timeframe (IOM 2018a). In urban areas of Selenge and Dornogovi, about 93 and 71% of the surveyed households registered, respectively, while in Ulaanbaatar only 49% registered. While the high number of non-registered migrants in the capital is likely due to the migration ban, the figures suggest that a considerable share of migrants remains unregistered.
The NSO defines pastoralist households as one or several herders and their nuclear family who conduct livestock husbandry around the year for their main purpose of livelihood and source of income (NSO 2015). The number of pastoralist households is recorded each year in December as part of the Mongolia Livestock Census.
Modeling the intensity of extreme winter events with weather data is challenging because the specific weather conditions triggering each extreme winter vary considerably across events. As outlined in section 3, triggering conditions include, but are not limited to, extremely cold temperature, harsh winter storms, excessive snowfall, rainfall combined with sudden temperature drops, as well as summer-season drought conditions. Among climate scientists modeling extreme weather events in Mongolia, there is no consensus regarding what weather data and variables best measure the intensity of extreme winter events (Tachiiri et al. 2008; Palat Rao et al. 2015; Nandintsetseg et al. 2018).
Note, however, that a livestock mortality rate of 6% at the district level triggers index insurance payouts, while we define livestock mortality at the province level.
The gravity model assumes that individuals compare characteristics between destination and origin region and maximize their utility while accounting for the cost of migration. Aside from wage differentials, regional attributes, such as infrastructure, environmental conditions, and socio-economic characteristics at origin and destination are typically taken into account (Tsegai and Bao Le 2010). For Mongolia, only single-sided migration data is available at an aggregate level, which renders it impossible to estimate a full gravity model. Instead, we refer to the gravity model in more general terms as a reference point for selecting control variables.
Water supply stations are wells designated to supply drinking water. Wells are either connected to the central water supply system or filled by water tank trucks of authorized entities.
We did not come across reports of human casualties caused by extreme winter conditions.
District-level data on the number of deceased animals is only available from 2012 onwards. For the 2012-2018 period, the coefficient of correlation between the annual livestock mortality rate and annual livestock growth rate is 0.51. We conclude that both measures are reasonably comparable.
Qualitatively similar findings are obtained (but not displayed here) when using the net migration in absolute terms, net out-migration, or net out-migration rate as outcome.
Similar results are obtained (but not displayed here) when including the set of time-varying controls in models 1 and 3.
Qualitatively similar results are obtained when employing alternative outcome variables, such as total out-migration in absolute terms or the net out-migration rate.
The estimated coefficient of the shock variable is larger in magnitude in column 5 compared to the model without controls (column 1). Note that several controls have missing values, which reduces the sample size considerably. When estimating column 1 on the same reduced sample as in column 5, the estimated coefficients are very similar in magnitude.
We are very grateful to Banzragch Nandintsetseg for sharing this data.
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We gratefully acknowledge helpful comments by Svenja Fluhrer, Roman Hoffmann, Lukas Mogge, and Lisa Murken. The paper also benefited from comments received at the EAERE annual conference 2021 and the Migration and Development Economics seminar organized by Sulin Sardoschau at Humboldt University of Berlin. Nergui Sunjidmaa provided excellent research assistance. Responsibility for the content of this paper lies solely with the authors.
Open Access funding enabled and organized by Projekt DEAL. The research was generously funded by the German Federal Ministry of Education and Research in the "Economics of Climate Change" funding line, research grant 01LA1804A, and the German Academic Foundation Cusanuswerk.
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, D-14412, Potsdam, Germany
Julian Roeckert & Kati Kraehnert
Faculty of Life Sciences, Department of Agricultural Economics, Humboldt-University of Berlin, Invalidenstraße 42, D-10115, Berlin, Germany
Julian Roeckert
Kati Kraehnert
Correspondence to Kati Kraehnert.
Conflicts of Interest/Competing Interests
We, Julian Roeckert and Kati Kraehnert, declare that we have no conflict of interest.
Table 7 Robustness test: Determinants of net migration rate at the province level in different time windows
Table 8 Robustness test: Determinants of net migration rate at the province level with different threshold of the shock proxy, 1992-2018
Table 9 Robustness test: Determinants of net migration rate at the province level with continuous shock proxy, 1992-2018
Table 10 Robustness test: Determinants of net migration rate at the province level with lead values of the shock proxy, 1992-2018
Roeckert, J., Kraehnert, K. Extreme Weather Events and Internal Migration: Evidence from Mongolia. EconDisCliCha 6, 95–128 (2022). https://doi.org/10.1007/s41885-021-00100-8
Issue Date: March 2022
Internal migration
62P20


text:
Successful Investment Round for Brazilian Fintech into Agro
Essent Agro startup from Rio Grande do Sul is present in almost all Brazilian states and promises to simplify financial and tax management
In South America, two sectors are promising for fast-growing startups: AgTech and Fintech. Latin America relies deeply on AgTech, due to its important agricultural sector that it's exporting to Europe and China. Meanwhile, the Fintech startups are helping to incorporate in the financial system to a wide portion of the population. For that reason, it's not strange that investors gave their confidence (and money) to Essent Agro, a Brazilian fintech focused on agricultural companies.
In Latin America, Agrobusiness has a big potential to grow up in the coming years, receiving a boost in its production through AgTech. However, for achieving that goal, companies, and producers of the agricultural sector need to get capital for adopting the last technology and expanding their business.
Investors rely in Essent Agro
The CEO of startup Essent Agro from Rio Grande do Sul, Giandrei Basso, was surprised last week by raising 100,000 reais (around $20 000) an hour in an investment round, according to Brazilian business journal Exame. Almost 260 investors became partners in the company with shares starting at 800 reais. The capture, made through CapTable, reached the goal of 700,000 reais ($140 000) in 7 hours.
The value represents a record for the startup, which was born in 2018 in Tucunduva, Rio Grande do Sul. The business model promises to help rural producers and accountants with financial management, especially tax. With the complex tax payment system in Brazil, a change in the way a tax is calculated generates savings. The cost of the service is 247 reais ($50) a month.
According to Basso, the company was surprised by this business round,
We didn't imagine it would be so fast. This proves that our business has everything to grow even more, mainly because the agro sector is at a totally different time from the Brazilian economy"
Giandrei Basso, CEO of Essent Agro
The agribusiness was the one that grew the most in the first quarter of 2021, with an increase of 5.7% compared to the previous three months. The sector was highlighted in the composition of the country's gross domestic product (GDP), which grew above expectations at the beginning of the year.
And it is precisely on this growing wave that fintech intends to surf. Currently, the startup has more than 400 producers from almost all Brazilian states that have hired its financial services. Sales rose from 16,000 reais in 2019 to 386,000 reais in 2020. In the first quarter, Essent Agro grew 33% and the expectation is that sales will double in 2021.
Read more: Seven Latin American AgTech that revolutionize the countryside
Category: Money
Keywords: brazil

redpajama_set_name: RedPajamaCommonCrawl


text:
Facebook's drivers are only making about $36k a year
"Sometimes we get a lot of negative comments. 'Go get another job,' stuff like that. All we really want is some understanding."
Facebook is famous for gifting its employees with perks (amazing sushi, an on-site barber, egg-freezing) but that is far from the case for the contracted bus drivers who shuttle these employees to and from work every day. The company's implementation of a "split shift" schedule has these drivers so dissatisfied that they are organizing a union through the Teamsters in order to reach a more agreeable arrangement with the company.
One such driver is Cliff Doi. He formerly drove buses for Stanford University and the San Jose Airport, and has been driving Facebook employees to and from the company's Menlo Park headquarters for the last three and a half years. He's not presently working a split shift (it ended a couple weeks ago), but he tells us that when he was, it was hardly an ideal situation.
"I'd drive interns to Facebook headquarters between 7 and 11am, then I'd drive everyone home from 5 to 9pm. To do this, I was waking up at 4am and getting home at 10pm every day," he said.
"We're essentially dealing with a 15-hour workday with a bunch of downtime in between," said Kara Deniz, Teamsters communications project manager. "We're trying to find alternatives, like a place to sit in the office. The area is comparable to New York City or D.C., with a lot of the drivers having to commute some distance before they can go to work."
"The drivers transport Facebook employees to work every day and they want a voice."
There is a trailer that the drivers are welcome to hang out in when not on the clock, but "it's too small for 40 drivers," said Doi. "There are only four beds—two for males, two for females. Mostly you just try to get lunch somewhere, kill time until 5pm. It's boring. You can't do much and most people take naps in their cars. I don't think it's possible to get rid of the split shift system completely, but we want some comforts for that time."
Facebook contracts its drivers through a company called Loop Transportation, paying them around $18 per hour for an annual salary near $36,000. Were these drivers driving a public bus for the city of San Francisco, they could expect to earn "on average, about $60,000 base salary," said Paul Rose, media relations manager for the San Francisco Municipal Transportation Agency.
"The drivers transport Facebook employees to work every day and they want a voice," said Deniz. "Representation voted to organize around the abusive split shift schedule. The Facebook drivers deserve a union. As for how a union could specifically benefit the drivers, that conversation would take place in negotiation."
Google has also come under fire for its own employee bus system, which it facilitates through a company called WeDriveU. A WeDriveU representative passed our inquiry along to Google, saying that "Google requested that WeDriveU route media inquiries regarding their shuttle program to Google's team." We followed up with Google directly and have yet to hear back.
"These drivers are part of the invisible work force that makes Silicon Valley run," said Derecka Mehrens, Executive Director of Working Partnerships USA, a community group that participated in the rally. "They are members of our communities that work hard every day, but live in poverty, and the business model of tech companies like Facebook counts on that. Tech companies write the checks to subcontractors who hire these drivers and the thousands of other service workers who make these tech giants able to function. They need to set the standards, too, and say 'no' to poverty jobs."
"Most people who have eight-hour jobs don't know about the split shift," said Doi. "Sometimes we get a lot of negative comments. 'Go get another job,' stuff like that. All we really want is some understanding."
Photo via Marcin Wichary/Flickr (CC BY 2.0)
'You oughta be fired for not answering': Man confuses TikToker's number for the CDC, leaves multiple angry voicemails
'Maybe redevelop the education system': Anti-cheating software featured in Samsung showcase sparks debate on TikTok
Facebook disproportionately rejects ads for women's health, report finds


text:
Bank robber pleads guilty in Metairie bank robbery
By FOX8Live.com Staff
Published: Aug. 3, 2016 at 10:28 PM CDT|Updated: Aug. 3, 2016 at 11:39 PM CDT
NEW ORLEANS (WVUE) - A New Orleans man pleaded guilty Wednesday to charges that he brandished a gun during a bank robbery.
U.S. Attorney Kenneth Polite said that London Carter, 24, guarded the door of a Capitol One bank in Metairie during a robbery on August 26, 2011. While at the door, court documents said that Carter pointed a semi-automatic pistol at various customers in the bank.
Carter now faces a mandatory minimum sentence of seven years in prison and a maximum sentence of life in prison. He will have to pay a $250,000 fine and serve up to 5 years supervised release following any prison time.
U.S. District Judge Sarah S. Vance set sentencing for Dec. 7.


text:
LIMINANAS, THE
Le Bel Ete
BECAUSE MUSIC
BEC 5650382 BEC 5650382
Taken from the movie Le Bel Été, written and directed by Pierre Creton, this new album from The Limiñanas is the first OST written by Lionel Limiñanas. The main theme "One Blood Circle" features French pop legend, Etienne Daho. Lionel Limiñana about writing this soundtrack: "We met Pierre during the Shadow People tour, he came to the concert and wrote to us asking for music for his film Le Bel Été. Pierre sent me the script. I thought I didn't have time to work because of the tour but I took a three-day break to give it a try. I wrote a theme and then two, three... I had a work base and I was able to continue at the hotel or in the band's van, which explains why the music is very electronic. I invited Ivan Telefunken, Pascal Comelade's Catalan guitarist, to play on some melodies. When we arrived in St Malo for La Route du Rock Festival we met Etienne Daho with whom we had wanted to work for a long time. We played the script to Etienne and the demo of 'One Blood Circle', the main theme of Le Bel Été. Etienne worked on the text and quickly returned to the studio in Paris to record his voice and choirs. The O.S.T. was done." 12" white vinyl in sleeve with 3mm spine with paper inner-sleeve.
Other releases on BECAUSE MUSIC
Other releases by LIMINANAS, THE


Sonic drilling uses high frequency vibration to provide amazing results in less time and with less mess. Hydraulic motors on the drilling head oscillate offset weights to create a high frequency vibration of the entire drill string. This vibration fluidizes the soil, greatly reduces friction, and allows the drill string to penetrate up to 3x faster than conventional drilling.
Drill up to 3x faster with less waste!
Sonic drilling is ideal for environmental and geotechnical applications with the ability to produce continuous, undisturbed core samples. You can achieve reduced overall project costs due to the fast drilling speed and reduced spoils.
Continuous undisturbed sampling. Larger volume, higher quality samples.
Easier drilling through difficult surfaces.
Ability to constantly case the borehole.
Sonic drilling throughout the Southeastern U.S.


Annalena and I went back-to-school shopping at the Holyoke Mall. High school these days is all about skinny jeans. We popped into Borders where I picked up the September issue of Saveur that has a wonderful cover story about watermelon traditions from around the world.
It got me thinking, again, about Jello (which I know is technically spelled Jell-O, but I can't bring myself to be that corporate here) and I told her that I want to write a story about Mexican Jello.
She said that she remembers Mexican Jello from nursery school in Pátzcuaro when she was two years old. Everyday at lunch they'd eat gelatina shaped liked the Virgin of Guadalupe. She remembers guessing each day what color it would be.
The video below doesn't show any Virgin of Guadalupe Jello, but it does illustrate a bit of the wonder that is Mexican gelatina artistica.


text:
Frederick Henry "Harry" Wyld, född 5 juni 1900, död 5 april 1976 i Derby, var en brittisk tävlingscyklist.

Wyld blev olympisk bronsmedaljör i lagförföljelse vid sommarspelen 1928 i Amsterdam.

Källor

Brittiska tävlingscyklister
Brittiska olympiska bronsmedaljörer
Olympiska bronsmedaljörer 1924
Olympiska bronsmedaljörer 1928
Tävlande i cykling vid olympiska sommarspelen 1924
Tävlande vid olympiska sommarspelen 1924 från Storbritannien
Tävlande i cykling vid olympiska sommarspelen 1928
Tävlande vid olympiska sommarspelen 1928 från Storbritannien
Födda 1900
Avlidna 1976
Män

redpajama_set_name: RedPajamaWikipedia


text:
---
title: A Custom useDebounce Hook
---

```reason
/* this is a hook that takes 2 arguments */
let useDebounce = (value, delay) => {
  let (debouncedValue, setDebouncedValue) = React.useState(_ => value);

  React.useEffect1(
    () => {
      let handler =
        Js.Global.setTimeout(() => setDebouncedValue(_ => value), delay);

      Some(() => Js.Global.clearTimeout(handler));
    },
    [|value|],
  );

  debouncedValue;
};
```

redpajama_set_name: RedPajamaGithub


Here is an interior pic after Tif got all the books out and took down a few of the bookshelves.
this is a shot of the front, the window letters are gone, replace by our "future home of.. signs"
I was just walking by your new store today and saw the signs. After reading your blog, I can't wait to have a new store so close by. Good luck!
is that green carpet on the floor? You guys gonna tear it out?
yes, it's green for now.


As your partner, we can provide laboratory testing and determine the correct cleaning chemistry for the application. We perform TOC testing during product recommendation testing and develop new validated documents to help support your operations.
With best-in-class, innovative solutions and hands-on support, Ecolab is there for you. Learn more about our Microbiology and Analytic Lab services and how our advanced expertise can impact food safety and benefit your operation's productivity.


text:
Fact Check: Why planet orbiting white dwarf star is a breakthrough discovery
Some 4.5 billion years from today, our Sun will run out of fuel and shed its outer layers. What will remain of the Sun is called a "white dwarf". Can any planet orbiting a star survive such an event?
By: Express News Service | New Delhi | Updated: December 7, 2019 9:07:44 am
Artist's impression of the discovery. (Source: University of Warwick/Mark Garlick)
Some 4.5 billion years from today, our Sun will run out of fuel and shed its outer layers. In the process, it will destroy Mercury, Venus and probably Earth, and is expected to radiate enough high energy photons to evaporate Jupiter, Saturn, Uranus and Neptune.
What will remain of the Sun is called a "white dwarf". Can any planet orbiting a star survive such an event? New evidence suggests it can.
Astronomers from the University of Warwick and the University of Valparaíso have reported the first indirect evidence of a giant planet orbiting a white dwarf star (WDJ0914+1914). It is the first time any such planet has been found. The study, in the journal Nature, suggests there could be many more planets around such white dwarf stars waiting to be discovered.
The Neptune-like planet orbits the white dwarf every ten days, and cannot be seen directly. The evidence is in the form of a disc of gas (hydrogen, oxygen and sulphur) formed from its evaporating atmosphere. Spikes of gas were detected by the Very Large Telescope of the European Southern Observatory in Chile.
The discovery is significant, because while there was growing evidence accumulated in the past two decades that planetary systems can survive into white dwarf stars, only smaller objects such as asteroids had been detected so far. This is the first evidence of an actual planet in such a system.
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text:
U19-Europamästerskapet i fotboll för damer hade premiär 1998, och var en U18-turnering innan reglerna ändrades inför säsongen 2001/2002. Turneringen är även kvalificerande för U20-världsmästerskapet i fotboll.

Resultat
Finaler.

U18

U19

2020

Mästerskapet ställdes in på grund av covid-19-pandemin.
2021

Mästerskapet ställdes in på grund av covid-19-pandemin.

Referenser

Noter

Webbkällor
Uppdatering för värdländer 2023–25:
Uppdatering för värdländer 2021–22:
Kontroll av bland annat segrande lag i ovanstående tabell:

Externa länkar
 Women's Under-19 på UEFA.com.


text:
News Displaying items by tag: development
Displaying items by tag: development
Cemex receives Port of Gijón terminal concession
Spain: The Port Authority of Gijón granted Cemex España a 30-year concession for use of 2480m2 of the El Musel terminal for unloading, storage and bagging on 20 December 2019, subject to the Mexican company's use of the facilities for a minimum of 50,000t/yr of cement and derived products for the first two years of the arrangement, 0.1Mt/yr for the subsequent three years, and 0.15Mt/yr thereafter. La Nueva España newspaper has reported that Cemex España applied for the concession in February 2019. Its plans consist of a Euro5.0m investment in a development including two 6000t-capacity silos, a 44m crane and bagging facilities. Cemex España will take an estimated 10 months to complete the works from beginning the project in early 2020.
Odisha state government announces 27 projects
India: The government of the state of Odisha will invest US$1.25bn in infrastructure development, including construction of several industrial facilities. These will include a 1.0Mt/yr integrated plant owned by JSW Cement subsidiary Shiva Cement and a total of 4.0Mt/yr grinding capacity in new Shiva Cement and Shree Cement plants. The projects will source their cement from Odisha's existing installed capacity of 7.3Mt/yr, consisting of 3.8Mt/yr integrated and 3.5Mt/yr grinding capacity at plants owned and operated by Dalmia Bharat's OCC India, Toshali Cement, UltraTech Cement and Lafarge Holcim's ACC Cement.
Indian government launches development debt fund
India: The Union Council of India has approved a US$1.4bn distress fund to help developers finish partially completed residential developments. Business Today has suggested that the financing, which prioritises affordable and middle-income housing projects, will bolster demand for cement producers. The launch of the scheme follows India's decision not to join the Regional Comprehensive Economic Partnership on 4 November 2019, for which it stated reasons of a trade deficit with 11 of the 15 other signatories and the rejection of its proposed three-tier structure for phasing out tariffs.
Fives and Suez part of consortium to develop industrial complex at Duqm
Oman: Four French investors and technology suppliers, including Fives and Suez, have created a syndicate to develop business opportunities in the Special Economic Zone Authority of Duqm. The other partners are CMA CGM and EDF Renewables. The companies intend to assess various investment options in the area and develop them. In particular, the syndicate has an interest in a 'global approach to cement factory ecosystems' and related facilities including transport facilities, a solar power generation plant and the production of alternative fuels.
Nuevitas plant to develop LC3 cement in Cuba
Cuba: The Nuevitas cement plant will test LC3 cement, according to the Adelante newspaper. LC3 is a blend of limestone and calcined clay that reduces the amount of clinker used. The plant is one of three units in the country earmarked for upgrades in 2018.
No new use for Weardale after 15 years
UK: The owner of the former cement plant at Weardale, which has planning permission for a multi-million pound eco village, is working to finding a new use for the land. Lafarge UK sold the former Blue Circle cement plant in 2015, after plans to create a green energy village on the land ground to a halt due to the recession.
Durham County Council said it was still keen to support the development of the site by any interested party. A spokesperson for the owner said, "The owners are continuing to work with the council, who are very supportive, to find a solution for the works site. The new owners believe any solution has to be demand led. Although the planning consent for the eco village is still live, all parties recognise that with an estimated cost of delivery in excess of Euro110m, it was never likely to be built."
Last Wednesday 9 August 2017 marked the 15th anniversary of the closure in 2002 and councillors and former employees have expressed frustration that the site remained empty, despite millions of pounds being spent developing the eco-village scheme so far.
New Xiongan development expected to boost cement demand in Hebei
China: A new special economic development zone in the north of Hebei province is expected to significantly boost demand for cement in the region. President Xi Jinping announced that that the new development named Xiongan New Area would be built southwest of Beijing, according to the ET Net News Agency. The development will be on the same scale as Shenzhen and Shanghai Pudong. Using these previous projects as a benchmark HSBC Global Research estimated that Shanghai Pudong uses around 6Mt/yr and that the region had used 133Mt since its creation in the early 1990s.
BBMG's shares spiked following the announcement. The largest cement producer in the Beijing-Tianjing-Hebei area is widely expected to benefit from the project. After its restructuring with Jidong Cement it will hold 57% of cement production capacity in the region.
Adelaide Brighton concerned about housing plans near Birkenhead cement plant
Australia: Adelaide Brighton has raised concerns about a South Australia state plan to build housing and tourism facilities near to its Birkenhead cement plant in Adelaide. At a public meeting held by the Development Assessment Commission, a local planning body, the cement producer expressed its concerns that building more housing would create more complaints about the plant's activities, according to the Portside Messenger newspaper. It added that the government should consider building buffers to reduce noise and dust pollution from the site. The local government wants to build a tourism development near Cruickshank's Beach and the cement plant.
Insee Cement signs partnership with local universities
Sri Lanka: Insee Cement has signed research and development partnership deal's with the Universities of Peradeniya, Moratuwa and Ruhuna. The agreements are intended to enhance the local construction industry through education, innovation and knowledge sharing, according to the Sunday Observer newspaper. The agreement was signed by Janaka Weerakoon of Siam City Cement and Upul Dissanayake of the University of Peradeniya, Ananda Jayawardena of the University of Moratuwa and SGJN Senanayake of the University of Ruhuna. Insee Cement was previously known as Holcim Lanka before it was purchased by Thailand's Siam Cement in 2016.