scholarly journals Nighttime Lights and County-Level Economic Activity in the United States: 2001 to 2019

2021 ◽  
Vol 13 (14) ◽  
pp. 2741
Author(s):  
John Gibson ◽  
Geua Boe-Gibson
Keyword(s):  
Time Series ◽  
Economic Activity ◽  
Validation Studies ◽  
National Level ◽  
Predictive Performance ◽  
The United States ◽  
Cross Sectional ◽  
Nation States ◽  
Nighttime Lights ◽  
Defense Meteorological Satellite Program

Nighttime lights (NTL) are a popular type of data for evaluating economic performance of regions and economic impacts of various shocks and interventions. Several validation studies use traditional statistics on economic activity like national or regional gross domestic product (GDP) as a benchmark to evaluate the usefulness of NTL data. Many of these studies rely on dated and imprecise Defense Meteorological Satellite Program (DMSP) data and use aggregated units such as nation-states or the first sub-national level. However, applied researchers who draw support from validation studies to justify their use of NTL data as a proxy for economic activity increasingly focus on smaller and lower level spatial units. This study uses a 2001–19 time-series of GDP for over 3100 U.S. counties as a benchmark to examine the performance of the recently released version 2 VIIRS nighttime lights (V.2 VNL) products as proxies for local economic activity. Contrasts were made between cross-sectional predictions for GDP differences between areas and time-series predictions of GDP changes within areas. Disaggregated GDP data for various industries were used to examine the types of economic activity best proxied by NTL data. Comparisons were also made with the predictive performance of earlier NTL data products and at different levels of spatial aggregation.

scholarly journals Nighttime Lights and County-Level Economic Activity in the United States: 2001 to 2019

2021 ◽  
Author(s):  
John Gibson ◽  
Geua Boe-Gibson
Keyword(s):  
Time Series ◽  
Economic Activity ◽  
Validation Studies ◽  
National Level ◽  
Predictive Performance ◽  
The United States ◽  
Cross Sectional ◽  
Nation States ◽  
Nighttime Lights ◽  
Meteorological Satellite

Nighttime lights (NTL) are a popular type of data for evaluating economic performance of regions and economic impacts of various shocks and interventions. Several validation studies use traditional statistics on economic activity like national or regional Gross Domestic Product (GDP) as a benchmark to evaluate the usefulness of NTL data. Many of these studies rely on dated and imprecise Defence Meteorological Satellite Program (DMSP) data and use aggregated units such as nation-states or the first sub-national level. Yet applied researchers who draw support from validation studies to justify their use of NTL data as a proxy for economic activity increasingly focus on smaller and lower level spatial units. This study uses a 2001-19 time-series of GDP for over 3100 US counties as a benchmark to examine the usefulness of the recently released version 2 VIIRS nighttime lights (V.2 VNL) products as proxies for local economic activity. Contrasts are made between cross-sectional predictions for GDP differences between areas and time-series predictions of GDP changes within areas. Disaggregated GDP data for various industries are used to examine what types of economic activity are best proxied by NTL data and comparisons are also made with the predictive performance of earlier NTL data products.

scholarly journals VIIRS Nighttime Lights in the Estimation of Cross-Sectional and Time-Series GDP

2019 ◽  
Vol 11 (9) ◽  
pp. 1057 ◽  
Author(s):  
Xi Chen ◽  
William D. Nordhaus
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Economic Activity ◽  
Cross Sectional ◽  
Areal Unit ◽  
Metropolitan Statistical Areas ◽  
Us States ◽  
Nighttime Lights

This study extends previous applications of DMSP OLS nighttime lights data to examine the usefulness of newer VIIRS lights in the estimation of economic activity. Focusing on both US states and metropolitan statistical areas (MSAs), we found that the VIIRS lights are more useful in predicting cross-sectional GDP than predicting time-series GDP data. This result is similar to previous findings for DMSP OLS nighttime lights. Additionally, the present analysis shows that high-resolution VIIRS lights provide a better prediction for MSA GDP than for state GDP, which suggests that lights may be more closely related to urban sectors than rural sectors. The results also indicate the importance of considering biases that may arise from different aggregations (the modifiable areal unit problems, MAUP) in applications of nighttime lights in understanding socioeconomic phenomenon.

“Justice of the Marketplace”: Legal Disputes and Economic Activity on America's Northeastern Frontier, 1700–1860

2008 ◽  
Vol 39 (1) ◽  
pp. 1-35 ◽  
Author(s):  
B. Zorina Khan
Keyword(s):  
United States ◽  
Eighteenth Century ◽  
Economic Activity ◽  
Critical Period ◽  
The United States ◽  
Market Exchange ◽  
Cross Sectional ◽  
Data Set ◽  
Community Norms ◽  
Over Time

The analysis of markets, courts, and civil litigation on the northeastern frontier of the United States provides a valuable opportunity to assess the evolution of institutions during economic development. The data set pools longitudinal and cross-sectional observations on 30,000 lawsuits filed in Maine during the critical period between 1700 and 1860. The earliest legal institutions moderated both social and economic norms, but courts quickly began to specialize in commercial issues. The residence of debtors and creditors and changes in spatial characteristics over time yield insights into the nature and extent of capital markets and impersonal exchange. The distribution and disposition of property and debt cases indicate that early markets were well developed and orderly; the evidence of “social tension” between debtors and creditors was minimal. The results do not support the standard claim of a transition from interactions based on community norms to impersonal market exchange late in the eighteenth century.

scholarly journals Global Utilization Trends of Direct Acting Antivirals (DAAs) during the COVID-19 Pandemic: A Time Series Analysis

Viruses ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1314
Author(s):  
Ahmad Shakeri ◽  
Natalia Konstantelos ◽  
Cherry Chu ◽  
Tony Antoniou ◽  
Jordan Feld ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
The United States ◽  
Interrupted Time Series Analysis ◽  
Cross Sectional ◽  
Series Analysis ◽  
Hcv Prevalence ◽  
Direct Acting ◽  
The Impact

The 2019 novel coronavirus (COVID-19) pandemic has placed a significant strain on hepatitis programs and interventions (screening, diagnosis, and treatment) at a critical moment in the context of hepatitis C virus (HCV) elimination. We sought to quantify changes in Direct Acting Antiviral (DAA) utilization among different countries during the pandemic. We conducted a cross-sectional time series analysis between 1 September 2018 and 31 August 2020, using the IQVIA MIDAS database, which contains DAA purchase data for 54 countries. We examined the percent change in DAA units dispensed (e.g., pills and capsules) from March to August 2019 to the same period of time in 2020 across the 54 countries. Interrupted time-series analysis was used to examine the impact of COVID-19 on monthly rates of DAA utilization across each of the major developed economies (G7 nations). Overall, 46 of 54 (85%) jurisdictions experienced a decline in DAA utilization during the pandemic, with an average of −43% (range: −1% in Finland to −93% in Brazil). All high HCV prevalence (HCV prevalence > 2%) countries in the database experienced a decline in utilization, average −49% (range: −17% in Kazakhstan to −90% in Egypt). Across the G7 nations, we also observed a decreased trend in DAA utilization during the early months of the pandemic, with significant declines (p < 0.01) for Canada, Germany, the United Kingdom, and the United States of America. The global response to COVID-19 led to a large decrease in DAA utilization globally. Deliberate efforts to counteract the impact of COVID-19 on treatment delivery are needed to support the goal of HCV elimination.

scholarly journals Changes in live births, preterm birth, low birth weight, and cesarean deliveries in the United States during the SARS-CoV-2 pandemic

2021 ◽  
Author(s):  
Alison Gemmill ◽  
Joan A. Casey ◽  
Ralph Catalano ◽  
Deborah Karasek ◽  
Tim-Allen Bruckner
Keyword(s):  
Time Series ◽  
Birth Weight ◽  
Preterm Birth ◽  
Low Birth Weight ◽  
Cesarean Delivery ◽  
Very Low Birth Weight ◽  
National Level ◽  
Health Indicators ◽  
The United States ◽  
Live Births

Background: The SARS-CoV-2 pandemic and associated social, economic, and clinical disruption have been widely speculated to affect pregnancy decision-making and outcomes. While a few US-based studies have examined subnational changes in fertility, preterm birth, and stillbirth, there remains limited knowledge of how the pandemic impacted childbearing and a broader set of perinatal health indicators at the national-level throughout 2020. Here, we use recently released national-level data to fill this gap. Importantly, we, unlike earlier work, use time-series methods to account for strong temporal patterning (e.g., seasonality, trend) that could otherwise lead to spurious findings. Methods: For the years 2015 to 2020, we obtained national monthly counts of births and rates (per 100 births) for six perinatal indicators: preterm birth (<37 weeks gestation), early preterm birth (<34 weeks gestation), late preterm birth (34-36 weeks gestation), low birth weight birth (<2500 g), very low birth weight birth (<1500 g), and cesarean delivery. We use an interrupted time-series approach to compare the outcomes observed after the pandemic began (March 2020) to those expected had the pandemic not occurred. Results: For total births as well as five of the six indicators (i.e., all but the rate of cesarean delivery), observed values fall well below expected levels (p<.0001 for each test) during the entire pandemic period. Declines in preterm birth and low birth weight were largest in magnitude in both early and later stages of the 2020 pandemic, while those for live births occurred at the end of the year. Discussion: Our findings provide some of the first national evidence of substantial reductions in live births and adverse perinatal outcomes during the SARS-CoV-2 pandemic. Only cesarean delivery appeared unaffected. These declines were not uniform across the pandemic, suggesting that several mechanisms, which require further study, may explain these patterns.

scholarly journals Is There Shareholder Expropriation in the United States? An Analysis of Publicly Traded Subsidiaries

2010 ◽  
Vol 45 (1) ◽  
pp. 1-26 ◽  
Author(s):  
Vladimir Atanasov ◽  
Audra Boone ◽  
David Haushalter
Keyword(s):  
United States ◽  
Time Series ◽  
Operating Performance ◽  
The United States ◽  
Publicly Traded ◽  
Cross Sectional ◽  
Subsidiary Performance ◽  
Abnormal Performance ◽  
Parent Companies

AbstractThis paper examines the relation between the performance and valuations of publicly traded subsidiaries in the United States and the ownership stake of their parent companies. Cross-sectional and time-series tests demonstrate that subsidiaries of parents that own a substantial minority stake exhibit negative peer-adjusted operating performance and are valued at a 23% median discount relative to peers. In contrast, majority-owned and fully divested subsidiaries show no abnormal performance or valuations. The results of our study indicate that the association between parent ownership and subsidiary performance is nonlinear and that some parents behave opportunistically toward their publicly traded subsidiaries.

scholarly journals The Geography of Chronic Pain in the United States and Canada.

2021 ◽  
Author(s):  
Anna Zajacova ◽  
Jinhyung Lee ◽  
Hanna Grol-Prokopczyk
Keyword(s):  
National Level ◽  
Decomposition Methods ◽  
The United States ◽  
Deep South ◽  
Geographic Variations ◽  
Cross Sectional ◽  
National Geographic ◽  
Pain Frequency ◽  
The Difference ◽  
The U.S

Our understanding of population pain epidemiology is largely based on national-level analyses. This focus, however, neglects potential cross-national, and especially sub-national, geographic variations in pain, even though geographic comparisons could shed new light on factors that drive or protect against pain. This article presents the first comparative analysis of pain in the U.S. and Canada, comparing the countries in aggregate and analyzing variation across states and provinces. Analyses are based on cross-sectional data collected in 2020 from 2,124 U.S. and 2,110 Canadian adults 18 years and older. Our pain measure is a product of pain frequency and pain-related interference with daily activities. We use regression and decomposition methods to link socioeconomic characteristics and pain, and inverse-distance weighting spatial interpolation to map pain scores. We find significantly and substantially higher pain in the U.S. than in Canada. The difference is accounted for by Americans' lower economic wellbeing. Additionally, we find variation in pain within countries; the variation is statistically significant across U.S. states. Further, we identify nine hotspot states in the Deep South, Appalachia, and the West where respondents have significantly higher pain than those in the rest of the U.S. or Canada. This excess pain is partly attributable to economic distress, but a large part remains unexplained; we speculate that it may reflect the sociopolitical context of the hotspot states. Overall, our findings identify areas with high need for pain prevention and management; they also other scholars to consider geographic factors as important contributors to population pain.

scholarly journals Politics or Economics? International Migration during the Nicaraguan Contra War

2005 ◽  
Vol 37 (1) ◽  
pp. 29-53 ◽  
Author(s):  
JENNIFER H. LUNDQUIST ◽  
DOUGLAS S. MASSEY
Keyword(s):  
United States ◽  
Costa Rica ◽  
Latin American ◽  
National Level ◽  
The United States ◽  
Direct Result ◽  
Cross Sectional ◽  
Timing Of Migration ◽  
Or Economics ◽  
Economic Trends

The issue of whether Central Americans in the United States are ‘political’ or ‘economic’ migrants has been widely debated, yet little empirical research has informed the controversy. Earlier studies have relied primarily on cross-sectional aggregate data. In order to overcome these limitations we draw on recent surveys conducted in five Nicaraguan communities by the Latin American Migration Project. Using retrospective data, we reconstruct a history of a family's migration to the United States and Costa Rica from the date of household formation to the survey date and link these data to national-level data on GDP and Contra War violence. While out migration to both Costa Rica and the United States is predicted by economic trends, US-bound migration was more strongly linked to the level of Contra War violence independent of economic motivations, especially in an interactive model that allows for a higher wartime effect of social networks. We conclude that elevated rates of Nicaraguan migration to the United States during the late 1980s and early 1990s were a direct result of the US-Contra intervention. The approach deployed here – which relates to the timing of migration decisions to macro-level country trends – enables us to address the issue of political versus economic motivations for migration with more precision than prior work.

Organizational-Level Characteristics in Right-Wing Extremist Groups in the United States Over Time

2016 ◽  
Vol 45 (2) ◽  
pp. 250-266 ◽  
Author(s):  
Victor Asal ◽  
Steven M. Chermak ◽  
Sarah Fitzgerald ◽  
Joshua D. Freilich
Keyword(s):  
Time Series ◽  
Law Enforcement ◽  
Single Point ◽  
The United States ◽  
Organizational Level ◽  
Future Research ◽  
Right Wing ◽  
Far Right ◽  
Cross Sectional ◽  
Extremist Groups

This study compares the organizational-level variables of violent and nonviolent far-right extremist groups. This study makes an important contribution by coding for attributes for each specific year that an organization existed. Prior research has only examined organizational characteristics at a single point of time. Our strategy here better specifies differences between violent and nonviolent extremist groups. We used a pooled cross-sectional time series analysis using logistic regression because our dependent variable is dichotomous (the organization used violence this year vs. it did not). We clustered on the organization and we included dummy years to control for time series effects. We also included a lagged variable if the organization used violence in the year before. We found that organizations were more likely to use violence if they were previously involved in violence, had multiple alliances with other extremist groups, had a large membership, had weak or decentralized leadership or a strong ruling council, and advocated for inherent racial or ethnic superiority. These results have important implications for law enforcement and future research on extremism and violence.

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