Nighttime Lights as a Proxy for Economic Performance of Regions

Studying and managing regional economic development in the current globalization era demands prompt, reliable, and comparable estimates for a region’s economic performance. Night-time lights (NTL) emitted from residential areas, entertainment places, industrial facilities, etc., and captured by satellites have become an increasingly recognized proxy for on-ground human activities. Compared to traditional indicators supplied by statistical offices, NTLs may have several advantages. First, NTL data are available all over the world, providing researchers and official bodies with the opportunity to obtain estimates even for regions with extremely poor reporting practices. Second, in contrast to non-standardized traditional reporting procedures, the unified NTL data remove the problem of inter-regional comparability. Finally, NTL data are currently globally available on a daily basis, which makes it possible to obtain these estimates promptly. In this book, we provide the reader with the contributions demonstrating the potential and efficiency of using NTL data as a proxy for the performance of regions

Evidence from Satellite Nighttime Lights

학위논문(박사) -- 서울대학교대학원 : 사회과학대학 경제학부, 2021.8. 곽노준.This dissertation investigates the status and the determinants of regional economic performance in North Korea, overcoming data limitations of regional research on the North Korean economy using nighttime light data and geospatial data. The first chapter estimates regional level GDP per capita, assessing the regional economic inequality of North Korea at the county level using nighttime light as a proxy for economic level. The research calculates base gross regional domestic product (GRDP) per capita based on urbanization rates and Bank of Korea’s GDP estimates and derives nighttime light-based GRDP per capita based on the relationship between base GRDP per capita and nighttime light. It also assesses the inequality of North Korean regions at the county level, revealing severe county-level inequality within the province, representing 87% of the total inequality, whereas most previous studies have focused on between-province inequality. In the second chapter, the determinants of regional economic performance in the Kim Jong-un era are analyzed using nighttime light as a proxy for economic performance, revealing that market size and involvement in trade, measured as proximity to trade hubs, contribute to higher nighttime light, while industries do not appear to have a significant effect. Sanctions are shown to significantly reduce nighttime light overall, but the magnitude of the impact is highly divergent across regions. The damage of sanctions is greater in regions with large markets or near trade hubs. In contrast, regions near major wholesale markets appear to better cope with sanctions, although the aggregate effect of sanctions on the region is negative. In the final chapter, the channel of trade effect on regional economies is investigated for the period of recovery from the “Arduous March,” 2001–2016. Three hypotheses of export-led growth, import-led growth, and marketization channel are examined. Historical data from the Japanese colonial era are used as instrumental variables to manage the endogeneity problem of the market. The results indicate that resource export and growth of market in response to trade are the main channels through which sanctions affect regional economies. Conversely, input import does not affect regional economies through any industry. The findings imply that North Korea’s economic recovery from the Arduous March was mainly the result of resource export and market expansion.본 논문은 북한의 시군 단위 지역경제의 현황 및 결정요인을 분석한다. 자료의 부재로 북한의 지역경제 연구는 매우 미흡한 실정이었으나, 기존에 사용되지 않았던 위성 야간조도 및 지리정보라는 새로운 자료를 활용하여 시장, 무역, 산업, 대북경제 제재가 지역경제에 미치는 영향을 실증적으로 분석한다. 첫 번째 연구에서는 김정은 정권 하 북한의 시군 단위 1인당 GRDP를 추정하고 불평등 수준을 평가한다. 북한의 GDP를 도시인구 비중에 비례하여 각 지역별로 배분한 후, 이와 야간조도 간의 관계를 도출하여 1인당 GRDP 를 추정한다. 또한 이를 바탕으로 지니계수 및 일반화된 엔트로피 지수를 도출해 북한의 불평등 추세를 분석하고 불평등 분해를 실시한다. 분석 결과 북한의 1인당 GRDP에는 지역간 상당한 격차가 있었으며, 도 단위에서는 평양대비 56-71%의 수준을 보였다. 그러나 불평등 분해 결과 도 단위의 격차보다 동일 도 내 시·군 간 격차에 따른 불평등이 약 87%를 차지하여 시·군 단위의 지역경제 연구가 매우 중요한 것으로 나타냈다. 두 번째 연구에서는 시장, 무역, 산업을 중심으로 김정은 정권 하 북한 지역 경제 수준의 결정요인과 대북제재가 지역경제에 영향을 분석한다. 이를 위하여 2013-2019년 야간조도 수준을 지역별 경제 수준의 대리변수로 사용하며, 일 부 지역에서 야간조도 값이 관측되지 않는 좌측중도절단(Left censoring) 문제가 발생함에 따라 OLS와 함께 토빗 모형을 사용한다. 분석 결과 시장 규모와 무역 중심지 접근성이 북한 지역경제수준에 긍정적 영향을 미치는 것으로 나타났으며, 산업변수의 영향력은 유의하게 나타나지 않았다. 한편, 대북제재는 북한의 지역 야간조도를 평균적으로 5.4% 감소시키며 특히 시장 활동이 활발하고 무역접근성이 높은 지역에 더 큰 피해를 입히는 것으로 나타났다. 한편, 제재 하에서 도매시장으로의 접근성이 높은 지역은 상대적으로 제재의 효과가 상쇄되는 것으로 나타났는데, 이는 제재 하에서 북한의 국내유통망이 상대적으로 중요해지고 한정된 자원이 도매시장으로 먼저 집중되기 때문인 것으로 해석된다. 세 번째 연구에서는 두 가지 종류의 야간조도 자료를 결합하여 2001-2016년 무역이 지역경제에 영향을 미치는 경로를 분석한다. 북한의 무역 자료는 연간 시계열만 존재하며 북한의 지역단위 변수들은 시간에 대해 불변하므로 무역변수와 지역변수 간의 교차항을 통하여 무역이 어떠한 경제적 특성을 가진 지역에서 더 큰 영향을 미치는지 분석함으로써 수출주도 성장, 수입주도 성장 및 시장화 촉진의 세 가지 가설을 검증한다. 이 때, 시장 변수에 내생성이 존재할 수 있으므로 일제강점기의 지역별 시장 및 기차역 개수를 시장의 도구변수로 사용하여 이를 해결한다. 분석 결과 수입주도 성장은 유효하지 않았으며, 수출의 경우 광업이 발달한 지역에 더 큰 긍정적 영향을 미치는 것으로 나타났다. 또한 수출과 수입 모두 시장의 규모가 큰 지역에 더 큰 긍정적 영향을 미치는 것으로 나타나 무역이 시장의 성장을 촉진하고, 시장이 지역경제를 성장시키는 긍정적 외부효과가 중요한 역할을 한 것으로 나타났다. 수출의 시장을 통한 영향은 시장 정책과 무관하였으나 수입의 경우 친시장 정책이 심화될수록 긍정적 외부효과가 강화되었다. 이상의 결과는 종합적으로 2000년대 이후 및 김정은 정권 하에서 북한 지역경제 성장의 주요 동력은 시장과 무역 및 그 둘 간의 상호작용임을 보여준다. 김정은 정권하는 물론 고난의 행군 이후 북한 경제의 회복기에도 지역별 시장 발전 수준 및 무역 참여도가 지역 경제수준에 큰 영향을 미쳤다. 또한 2017년 이후의 UN 안보리 대북제재가 북한경제에 부정적 영향을 미쳤으며, 특히 북한의 핵심 성장동력인 시장과 무역에 큰 피해를 입히므로 상당한 실효성을 가짐을 시사한다.Introduction 1 Chapter 1. Estimation of North Korean Regional GDP in 2012-2019 Using Nighttime Light Data 5 1. Introduction 5 2. Nighttime Light Data 8 2.1. Introduction 8 2.2. Features of Energy Use in North Korea 10 2.3. Nighttime Light and Welfare Level 13 3. Method and Data 18 3.1. Methodology 18 3.2. Data 21 4. Results 22 4.1. Estimation of GRDP per capita 22 4.2. Regional Disparity of North Korea 29 5. Conclusions 32 Chapter 2. Determinants of the North Korean Regional Economy and the Effect of Sanctions in the Kim Jong-un Era 34 1. Introduction 34 2. Data and Method 37 2.1. Data 37 2.2. Descriptive Statistics 43 2.3. Methodology 47 3. Results 49 3.1. The Determinants of Regional Economic Growth 49 3.2. The Effect of Sanctions 52 3.3. Transmission Channels of the Sanction Effects 54 3.4. Robustness Check 61 4. Conclusions 70 Chapter 3. The effect of trade on the North Korea Economy: Analysis of the Channel 72 1. Introduction 72 2. Method and Data 75 2.1. Hypothesis 75 2.2. Regression model 77 2.3. Data 79 3. Results 86 3.1. Export-Led Growth 86 3.2. Import-Led Growth 89 3.3. Marketization Channel 91 4. Conclusion 99 Concluding Remarks 100 Appendix 102 Reference 107 국문초록 114박

County-level CO2 emissions and sequestration in China during 1997–2017

With the implementation of China’s top-down CO2 emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO2 emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO2 emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO2 emissions in 2,735 Chinese counties during 1997–2017. Moreover, as vegetation has a significant ability to sequester and reduce CO2 emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO2 emissions in China

Utility of High Resolution Human Settlement Data for Assessment of Electricity Usage Patterns

Electricity is vital for modern human civilization, and its demands are expected to significantly rise due to urban growth, transportation modernization, and increasing industrialization and energy accessibility. Meeting the present and future demands while minimizing the environmental degradation from electricity generation pathways presents a significant sustainability challenge. Urban areas consume around 75% of global energy supply yet urban energy statistics are scarce all over the world, creating a severe hindrance for the much-needed energy sustainability studies. This work explores the scope of geospatial data-driven analysis and modeling to address this challenge. Identification and measurements of human habitats, a key measure, is severely misconceived. A multi-scale analysis of high, medium, and coarse resolution datasets in Egypt and Taiwan illustrates the increasing discrepancies from global to local scales. Analysis of urban morphology revealed that high-resolution datasets could perform much better at all scales in diverse geographies while the power of other datasets rapidly diminishes from the urban core to peripheries. A functional inventory of urban settlements was developed for three cities in the developing world using very high-resolution images and texture analysis. Analysis of correspondence between nighttime lights emission, a proxy of electricity consumption, and the settlement inventory was the conducted. The results highlight the statistically significant relationship between functional settlement types and corresponding light emission, and underline the potential of remote sensing data-driven methods in urban energy usage assessment. Lastly, the lack of urban electricity data was addressed by a geospatial modeling approach in the United States. The estimated urban electricity consumption was externally validated and subsequently used to quantify the effects of urbanization on electricity consumption. The results indicate a 23% lowering of electricity consumption corresponding to a 100% increase in urban population. The results highlight the potential of urbanization in lowering per-capita energy usage. The opportunity and limits to such energy efficiency were identified with regards to urban population density. The findings from this work validate the applicability of geospatial data in urban energy studies and provide unique insights into the relationship between urbanization and electricity demands. The insights from this work could be useful for other sustainability studies

Planes, Trains, and Automobiles: Night-time Lights of the USA

This paper seeks to advance understanding of the lights-income relationship by linking the newest generation of night-time satellite images, the VIIRS images, to nationwide, panel data on 3,101 US counties, including data on both population and income. I leverage the quality and frequency of those data sources and the VIIRS lights images to decompose the links between population growth, official GDP growth, and nighttime lights growth at the county level. I use a between-county estimator to identify the effects of time-invariant infrastructure features on night-time light. Roads, rail, ports, and airports I find to be strong contributors to increases in light. I find GDP growth is weakly linked with night-time lights though light growth is strongly linked with population growth even when controlling for substantial non-linearities which appear to be present

What Can We Learn from Nighttime Lights for Small Geographies? Measurement Errors and Heterogeneous Elasticities

Nighttime lights are routinely used as a proxy for economic activity when official statistics are unavailable and are increasingly applied to study the effects of shocks or policy interventions at small geographic scales. The implicit assumption is that the ability of nighttime lights to pick up changes in GDP does not depend on local characteristics of the region under investigation or the scale of aggregation. This study uses panel data on regional GDP growth from six countries, and nighttime lights from the Defense Meteorological Satellite Program (DMSP) to investigate potential nonlinearities and measurement errors in the light production function. Our results for high statistical capacity countries (the United States and Germany) show that nightlights are significantly less responsive to changes in GDP at higher baseline level of GDP, higher population densities, and for agricultural GDP. We provide evidence that these nonlinearities are too large to be caused by differences in measurement errors across regions. We find similar but noisier relationships in other high-income countries (Italy and Spain) and emerging economies (Brazil and China). We also present results for different aggregation schemes and find that the overall relationship, including the nonlinearity, is stable across regions of different shapes and sizes but becomes noisier when regions become few and large. These findings have important implications for studies using nighttime lights to evaluate the economic effects of shocks or policy interventions. On average, nighttime lights pick up changes in GDP across many different levels of aggregation, down to relatively small geographies. However, the nonlinearity we document in this paper implies that some studies may fail to detect policy-relevant effects in places where lights react little to changes in economic activity or they may mistakenly attribute this heterogeneity to the treatment effect of their independent variable of interest

Planes, Trains, and Automobiles: What Drives Human-Made Light?

This paper expands on our understanding of the lights-income relationship by linking the newest generation of nighttime satellite images derived from the Visible Infrared Imaging Radiometry Suite, VIIRS, to nationwide, panel data on population and income from 2012-2018 for both Brazil and the United States including 3,095 US counties, and 5,570 municipios. I leverage the quality and frequency of those data sources and the VIIRS lights images and confirm that nighttime light responds to changes in income when controlling for population effects. I find positive effects of GDP on light in both USA and Brazil, though light is less responsive to changes in GDP in Brazil than in the USA. Consistent with the literature, I discover nonlinearities in the form of decreasing marginal effects of GDP on nighttime light. This result holds across many specifications and is robust to sub-sample analysis and placebo tests. Leveraging the large sample size, I use regressions by centile of nighttime light to present a clear picture of the effects of GDP and population on nighttime light. In many cases, results are shown for the combined USA and Brazil samples, as well as the dis-aggregated samples. Finally, I use a between-county estimator to identify the effects of time-invariant infrastructure features on night-time light. Roads, rail, ports, airports, and border crossings I find contribute positively to nighttime light