Proxy For Economic Activity Research Articles

How do Macroeconomic Indicators Shape Nonperforming Loans?

This study examines the influence of macroeconomic indicators on nonperforming bank loans. This research focuses on the period from 2010:1Q to 2019:4Q to capture significant trends and fluctuations in the economy. Data for receivables to be liquidated as a proxy for nonperforming loans, the consumer price index as a proxy for inflation, total private consumption expenditures as a proxy for economic activity, gross domestic product and total (private) fixed capital expenditures as proxies for economic growth are analyzed using the ARDL bound test, FMOLS, DOLS and VECM Granger methodologies. This study addresses several key questions. First, it examines how the receivables to be liquidated relate to changes in total private consumption expenditures (LNPCE). The findings indicate that higher LNPCE decreases the ability of receivables to be liquidated in both the long run and short run. Second, it explores the impact of gross domestic product (GDP) fluctuations on the amount of receivables to be liquidated, revealing that a higher GDP increases the amount of receivables to be liquidated in both the long and short run. Last, the study assesses the extent to which changes in the consumer price index (CPI) influence the receivables to be liquidated, finding that a higher CPI increases the receivables to be liquidated in the long run.

COVID-19 pandemic intensity, migration status, and household financial vulnerability: evidence from India

ABSTRACT This paper employs COVID-19 as a quasi-natural experiment to conduct an analysis of the heterogeneous effects of the pandemic on households’ financial vulnerability across districts in India and investigates the role of migration and gender of the household head in moderating financial vulnerability. Using Indian panel household surveys and a difference-in-differences approach with coarsened exact matching, we provide causal evidence of a larger increase in the financial vulnerability index (FVI) of households in Indian districts with a higher incidence of COVID-19 cases per capita. A similar effect is observed when considering satellite-based night-time lights, a proxy for economic activity. Furthermore, during the pandemic, households with an out-migrant family member experienced relatively lower FVI, with a more pronounced effect for female-headed households, likely due to the financial help given by migrants. However, households that had an out-migrant in the pre-pandemic period, but not during the pandemic, were more financially vulnerable. This study provides a novel contribution to the literature through a better understanding of the varied effects of the pandemic-induced health and economic shocks on households’ financial vulnerability based on pandemic intensity, migration status, and gender.

A unified dataset for pre-processed climate indicators weighted by gridded economic activity

Although high-resolution gridded climate variables are provided by multiple sources, the need for country and region-specific climate data weighted by indicators of economic activity is becoming increasingly common in environmental and economic research. We process available information from different climate data sources to provide spatially aggregated data with global coverage for both countries (GADM0 resolution) and regions (GADM1 resolution) and for a variety of climate indicators (total precipitations, average temperatures, average SPEI). We weigh gridded climate data by population density, night-time light intensity, cropland, and concurrent population count – all proxies of economic activity – before aggregation. Climate variables are measured daily, monthly, and annually, covering (depending on the data source) a time window from 1900 (at the earliest) to 2023. We pipeline all the preprocessing procedures in a unified framework, and we validate our data through a systematic comparison with those employed in leading climate impact studies.

The connectedness of Energy Transition Metals

We assess the degree of connectedness among 16 metals that are critical for the production of clean energy technologies. These commodities are the constituents of the Energy Transition Metals (ETMs) price index maintained by the International Monetary Fund and comprise base, precious, and minor metals. We rely on Vector Autoregressive models and generalised forecast error variance decomposition to quantify spillovers among ETMs returns and volatilities. By calculating both static and dynamic measures of connectedness, we gain insight into the patterns of shock transmission between ETMs. Our static analysis reveals that base and precious metals are net shock transmitters, while minor and most battery metals are net receivers. By splitting the analysis into three groups, we find that almost half of the connectedness originates within each group, whereas the other half is due to cross-group spillovers. Moreover, we find that the system-wide connectedness of returns is positively correlated with proxies of economic activity, whereas volatility connectedness seems to be more related to global economic policy uncertainty.

Rural road connectivity and local economic Activity: Evidence from Sri Lanka’s iRoad program

A large portion of the world's rural population has limited access to paved roads, which is widely believed to constrain rural economic growth opportunities. Using a panel of nighttime lights and road placement data from the Integrated Road Investment Program (iRoad), a large-scale rural road development program in Sri Lanka, this study examines the relationship between rural road connectivity and local nighttime luminosity. The program was found to result in better and more consistent rural road conditions. Rural areas with improved connectivity after two years show higher local nighttime luminosity, a proxy for economic activity, compared to areas without connectivity. These gains hold even for indirectly targeted rural areas where the iRoad passes through. The gains vary spatially, which are most pronounced in areas at a moderate distance to socioeconomic centers and with more adequate complementary infrastructure provisions. These findings support the notion that improving rural connectivity can ease development constraints, increase resilience in managing negative economic shocks caused by the COVID-19 pandemic, and contribute to post-pandemic economic recovery. The findings also lend to the idea that targeted placements based on the beneficiary's location and complementary infrastructure (e.g., educational and medical facilities) can enhance the effectiveness of rural road investments. An intensive margin analysis suggests that post-construction maintenance is effective in bringing about sustained impact.

BONO GETİRİLERİ, BIST-100 İLE BANKA KARLILIĞI ARASINDAKİ İLİŞKİ

The purpose of this study is to analyze the impact of bond return index (proxy for market interest rate) as well as BIST-100 (proxy for economic activity) upon bank profitability. The scope of this paper is Turkey. Data covers quarterly period between 2011 and 2021, data structure is panel data. Panel Dynamic Ordinary Least Squares (DOLS) is used in econometric analysis conducted in this study. ROA ratio of commercial bank, participation banks (non-interest banking industry) and investment & development banks are used as dependent variable; on the other hand, all-bond return index (as a reference for bond market interest rates) and BIST-100 return index are used as explanatory variables. Finding of the analysis indicate that the bond yield index (BOND) and the stock return index (BIST100) have a positive and statistically significant impact on the return on assets (ROA) of banks.

Nighttime light data reveal lack of full recovery after hurricanes in Southern US

As the climate warms, many areas of the world are experiencing more frequent and extreme weather events. Hurricanes carry some of the costliest short-term socioeconomic repercussions via economic losses and people displaced. There is, however, little quantitative evidence regarding medium- to long-term effects, nor factors moderating recovery. Here we show that areas affected by hurricanes of category 4 or 5 in the southern US between 2014 and 2020 generally do not demonstrate full recovery in the longer term. Utilizing Visible Infrared Imaging Radiometer Suite nighttime light (NTL) data as a proxy for economic activity and population density, we build a timeline of recovery via NTL radiance levels. We exploit the difference in the eligibility for aid from the Federal Emergency Management Agency (FEMA) to apply a quasi-experimental method to identify changes in NTL radiance attributable to hurricanes. We find that after three years, affected areas demonstrate a reduction in NTL radiance levels of between 2% and 14% compared to the pre-disaster period. Combining these results with machine learning techniques, we are able to investigate those factors that contribute to recovery. We find counties demonstrating smaller reductions in NTL radiance levels in the months following the hurricane are buoyed by the amount of FEMA aid received, but that this aid does not foster a longer-term return to normal radiance levels. Investigating areas receiving FEMA aid at the household and individual level, we find age and employment are more important than other demographic factors in determining hurricane recovery over time. These findings suggest that aid may be more important in motivating short-term recovery for public entities than for individuals but is not sufficient to guarantee complete recovery in the longer term.

The effect of natural disaster on economic growth: Evidence from a major earthquake in Haiti

We examine the average causal impact of the 2010 earthquake in Haiti on economic growth and recovery by conducting a disaggregated empirical analysis at the subnational level. To achieve this, we opt for a fixed effects difference-in-differences model and impulse response functions by using the earthquake’s intensity as the main exogenous variable and nighttime light data as a proxy for economic activity from 1992 to 2019. Results indicate a robust evidence that the earthquake caused a significant decrease in the country’s economic growth in the short-term. We also reveal that such declines in growth persited ten years after the disaster. Overall, estimates provide new insights on the short and long-run economic growth effects of major natural disasters. Therefore, our analysis of the effects of earthquake intensity on the growth of night lights is an important contribution to disaster economics. In the concluding reflections, the findings, implications, and avenues for future research are discussed.

Medium-run local economic effects of a major earthquake

AbstractExisting research is inconclusive regarding the longer-term economic effects of earthquakes. We examine the medium-run impacts of the 2010 earthquake in Chile, the sixth-largest ever recorded, using value-added tax collection as a proxy for economic activity at the municipal level and a measure of local ground-shaking intensity. We find that the affected municipalities suffered a relevant and persistent drop in their economic activity of about 10%, 8–9 years after the event. We discuss the plausibility of the assumption of conditional parallel trends and show that the overall results are robust to using alternative estimation methods.

The economic impact of weather anomalies

How do weather anomalies affect the economy at the local level? This paper presents a new data set that links weather data to annual average night-light emission data for 24.000 0.5°× 0.5° grid-cells around the globe for the period 1992–2013. Interpreting night-light emission as a proxy for economic activity, these data allow one to investigate how weather anomalies affect economic activity. Global coverage avoids selection bias, while high spatial resolution avoids averaging out heterogeneity in local impacts at higher aggregation levels. Our data show significant effects on the local growth of night-light for storms, excessive precipitation, droughts, and cold spells. Moreover, we find evidence for significant spatial spillovers to neighboring areas. Our results suggest that these offsetting spillovers are typically local. As positive and negative effects average out in larger areas, our results call for the analysis of economic effects of weather anomalies at a high geographical resolution. Finally, our results are driven by events in lower income regions. As climate change is expected to make weather patterns more erratic, our new data can inform emerging debates on how this will affect the economy in both science and politics.

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.

Operation Status Comparison Monitoring of China’s Southeast Asian Industrial Parks before and after COVID-19 Using Nighttime Lights Data

COVID-19 has had a huge impact on many industries around the world. Internationally-funded enterprises have been greatly affected by COVID-19 prevention and control measures, such as border controls. However, few studies have examined the impact of COVID-19 on internationally-funded enterprises. To this end, this paper considered 12 of China’s industrial parks situated in Southeast Asia, while comparing the operation status before and after the outbreak of COVID-19 based on remote sensing of nighttime lights (NTL). The NTL is generally used as a proxy for economic activity. First, six parameters were proposed to quantify and monitor the operation status based on NTL data. Subsequently, these parameters were calculated for the parks and for 10 km buffer zones surrounding them to analyze the differences in operating conditions. The results showed that (1) despite the negative impact of COVID-19, 9 out of the 12 parks had a mean NTL greater than 1, indicating that these parks are in better operating condition in 2020 than 2019; (2) 7 out of the 10 km buffer zones around the parks showed a decline in mean NTL. Only three parks showed a decline in mean NTL. The impact of COVID-19 on surrounding areas was greater than the impact on parks.

Using land cover, population, and night light data to assess urban expansion in Kimberley, South Africa

ABSTRACT Information on urban expansion is a significant input in forecasting upcoming land cover and land use changes in a city. This study combines Landsat 8, night-time lights, and population data to assess urban expansion in Kimberley, South Africa from 2013 to 2018. This study used a post-classification change detection approach to measure urban expansion. Urban and non-urban land use classes where the two classes mapped and evaluated for this analysis. Overall, urban expansion from 2013 to 2018 was 15% while the annual urban expansion rate experienced was 0.6%. Night-time lights, calculated from satellite imagery, are increasingly used by social scientists as a proxy for economic activity or economic development. During the period of 2013 to 2018, both the urban night-time lights and the urban population experienced high rates of growth. This study obtained a positive correlation for night-time light and population datasets of 0.51 for 2013 and 0.57 for 2018, to suggest a positive population and lighting increase in the study area. Municipal authorities and policymakers may use this knowledge as feedback during urban and environmental planning.

Viewing the COVID-19 Pandemic from Space: The Effect of COVID-related Mobility Declines on Night Light Brightness in Canada

High-frequency economic data for small areas is often difficult to obtain in Canada and other countries. This paper overcomes this limitation by using monthly data derived from satellite night light images as a proxy for economic activity in Canadian Census Divisions. This proxy is used in conjunction with Facebook mobility data to estimate the effects of mobility declines due to COVID-19 on economic activity. I find robust evidence that reductions in movements are strongly negatively associated with declines in luminosity. Further analyses suggest that this effect is weaker in more densely populated areas, but stronger in Census Divisions with a higher concentration of retail businesses. My findings suggest that policies which reduce the need for in-person activities can mitigate the negative effects of COVID-related mobility reductions on economic activity. This paper also further highlights the value of using monthly satellite night lights data in economic analysis.

NON-PHARMACEUTICAL INTERVENTIONS AND THEIR ECONOMIC EFFECTS DURING THE COVID-19 PANDEMIC

This paper evaluates the relationship between economic activity and non-pharmaceutical interventions implemented during the COVID-19 pandemic for 29 countries for the period between March 2020 and November 2020. Using industrial production as a proxy for economic activity and employing a dynamic panel data methodology to deal with the possible endogeneity problem, the empirical results suggest that non-pharmaceutical interventions negatively affect economic activity. Furthermore, this paper also contributes to the literature by analyzing the link between economic support provided by governments and economic activity during the pandemic. The findings indicate that governments can stabilize the decline in economic activity stemmed from non-pharmaceutical interventions by increasing the amount of economic support to households.

Diverse neighbors and post-conflict recovery at the village level: Evidence from Iraq after ISIL

Why do some towns recover faster than others after intrastate conflict? Many important decisions about post-conflict recovery are made at the substate level, but little empirical work has investigated what causes differences in recovery outcomes within a country. This article suggests that proximity to ethno-religiously diverse neighbors slows a town’s post-conflict recovery. A town has ‘diverse neighbors’ if towns with different plurality ethno-religious groups are nearby. This hypothesis is tested by exploring variation in recovery speed among Iraqi towns after the 2014–17 Islamic State insurgency (ISIL). The article constructs 81-month panels of economic activity for 379 Iraqi settlements occupied by ISIL by using satellite-observed nighttime light emissions as a proxy for economic activity. The panels reveal large variation in post-conflict recovery among towns during the first year of peace. Village-level survey data are then used to construct a measure of neighbor diversity, which is combined with lighting-based recovery scores in spatial autoregression. The results show that greater neighbor diversity is robustly associated with slower settlement recovery. The neighbor diversity penalty cannot be fully explained by cleavages between groups ‘on opposite sides’ of the conflict; proximity to out-group neighbors appears to slow recovery even between wartime allies. Several explanations are considered, and this article suggests that the types of post-liberation controllers that arise in diverse areas – which tend to be substate militias rather than the government – may be one important mechanism.

Flooded jobs: income development after the 2007 Tabasco flood

ABSTRACT Disasters are becoming more frequent events that affect an increasing share of the world population each year. In this paper I examine the economic effects of the 2007 flood in Tabasco, Mexico. Using the geographical coverage of the flood and detailed labour information I demonstrate that the flood caused an immediate decline in work income for the affected population. This result is mainly driven by an increase in the number of, predominantly male, workers that continue to work after the flood but now earn less than the minimum wage. The agricultural sector experienced the most severe income decline, although I find no changes in sectoral composition. Using night light as a proxy for economic activity I find no effects of the flood, which indicates that returns rather than activity levels were affected.

Political Dynasties and Economic Development: Evidence using Nighttime Light in the Philippines

Abstract Political dynasties, by limiting political competition, are thought to exacerbate corruption, poverty, and abuse of power. This paper examines the economic effects of the presence of political dynasties in Philippine cities and municipalities, taking into account possible channels in the local dynastic cycle – the framework in which politicians try to balance their goals to perform well for their constituents, to divert resources for personal gain, and to continue to be in power. Due to the lack of extensive income accounts or other economic indicators in finer geographical units (i.e., city or municipality level), we use the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) nighttime light data as our proxy for economic activity. Using a panel of Philippine municipalities and cities, we find that, in general, the relationship of political dynasties on economic performance is weak. However, we find that a higher share of economic expenditures leads to lower economic development in municipalities where the mayor, governor, and congressman belong to the same clan. We see this as an indication of weak institutions of checks and balances in localities with dynasties.

Economic activity and distribution of an invasive species: Evidence from night-time lights satellite imagery data

This study addresses economic and ecological aspects related to aquatic invasive species occurrence and spread. The relative importance of these two factors driving the probability of occurrence of Elodea canadensis species in lakes of Sweden is quantified. Night-time lights data, a proxy for economic activity, is generated from satellite imagery and mapped to key environmental variables known to constrain the species' distribution. Economic and environmental data are then matched with the species' observational records at the lake scale. Evidence from a spatial probit model shows a robust positive relationship between economic activity and invasion of uninvaded lakes.

Remote night-time lights sensing: Investigation and econometric application

Orientation: Some recent studies have been published that demonstrated the value of remote sensing night-time lights as descriptors and/or proxies for human activity. Research purpose: This article investigated the association between night-time light emissions and gross domestic product (GDP) estimates for South Africa. Motivation for the study: Satellite night-lights data seemed to be a useful proxy for economic activity at temporal and geographic scales for which traditional data are of poor quality, are unavailable or only available with a large time lag. Research approach/design and method: The article primarily used the remote sensing of night-time light emissions using satellite technologies. The methodology employed in this study involved estimating both a vector error correction modelling (VECM) and autoregressive distributed lag (ARDL) models that map light growth into a proxy for GDP growth. Main findings: Both the VECM and ARDL models confirmed a long-term co-integrating relationship between GDP (per capita) and night-time lights (total light intensity), a statistically significant short-term error correction term could, however, not be established through the VECM, but indeed through the ARDL model. Practical/managerial implications: The results of the study suggested that satellite remote sensing technologies held much promise and opportunities in terms of the field of Economics and Development. Contribution/value-add: This study contributes to our understanding of the spatial and temporal behaviour and trends in economic activity. It also suggested the use of satellite remote sensing technologies as part of official statistical frameworks and methodologies.