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The impacts of the economic matrix, particularly the Gross Domestic Product (GDP), within the cadre performance target system (CPTS) on the trade‐offs between local environment and economy have been extensively researched. However, few studies have adequately considered the transition from a single‐target to a multi‐target system and the effects of dynamic changes in this system. This study addresses this gap by assessing the causal effects of China's historic adjustment of GDP‐centric CPTS on local environmental quality. By introducing a dynamic analytical framework of CPTS and employing a time‐varying Difference‐in‐Differences (DiD) design with county‐level data from 2009 to 2018, this study reveals two key findings: (1) Counties that shifted away from a GDP‐centric performance target system experienced a significant average reduction in PM2.5 pollution levels by 6.6%, highlighting the environmental benefits of moving beyond GDP‐focused CPTS; (2) The observed environmental improvements are driven by two mechanisms—correcting land misallocation and optimizing industrial structure. This study advances previous static and single‐goal analyses by introducing a dynamic, multi‐target perspective to cadre performance target‐setting. [ABSTRACT FROM AUTHOR]

The South African Reserve Bank (SARB) uses interest rates to control inflation. The Computable General Equilibrium (CGE) model can contribute to inflation targeting objective and also determine the effects on banks and the economy. We improved the accuracy of the results from previous work on the banking sector CGE model by estimating the elasticities of the reduced form equations of the model instead of arbitrarily choosing them. Our results conform with the established view that lower policy rates lead to an increase in inflation and a reduction in banks' profits. However, because of the adverse supply shocks arising from the effects of the COVID‐19 pandemic, the increase in the GDP is crowded out. The CGE model is a useful tool for the SARB for monetary policy implications on financial stability, informing and providing analysis on its repo rate decision, and determining the consequent effects on the economy. [ABSTRACT FROM AUTHOR]

This study investigates the intricate relationship between energy consumption, economic growth, and environmental quality in Pakistan from 1990 to 2022, highlighting the critical role of natural resources rent (NRR) and renewable energy consumption (REC) in shaping carbon dioxide emissions. The study aims to understand how these variables interact and influence each other, particularly focusing on the impact of NRR and REC on CO2 emissions within the context of Pakistan's economic growth and energy consumption patterns. Given the country's rapid economic growth and increasing energy demands, there is an imperative need to investigate how these factors influence environmental quality, particularly CO2 emissions employing the autoregressive distributed lag approach with structural breaks, we analyze the long‐term interactions and causality among NRR, REC, energy use (EU), gross domestic product (GDP), and CO2 emissions. Our findings demonstrate that while NRR and REC negatively correlate with CO2 emissions, a positive association exists between EU, GDP growth, and emissions. These results underscore the potential of strategic environmental policies, aligned with Sustainable Development Goals 7, 13, and 8, to foster sustainable development pathways in Pakistan. By comparing this study's approach with existing methodologies, we highlight our study's unique contribution to the literature, offering policymakers a robust foundation to formulate effective strategies for balancing economic growth with environmental sustainability. [ABSTRACT FROM AUTHOR]

This paper uses OECD data to examine whether winning the men's FIFA World Cup boosts GDP growth, as claimed by analysts and media outlets concomitantly with every edition of this football competition. By implementing both an event‐study design and a synthetic difference‐in‐difference strategy, the analysis shows that winning the World Cup increases year‐over‐year GDP growth by at least 0.48 percentage points in the two subsequent quarters. This result seems primarily driven by enhanced export growth, which is consistent with a greater appeal enjoyed by national products and services on the global market after victory in a major sporting event. [ABSTRACT FROM AUTHOR]

The increasing nexus between economic growth and the resultant environmental and health challenges are of particular concern for developing countries. However, there is less evidence on the net effect of economic growth (EG) on air pollution, health spending, or vice‐versa in the Asia‐Pacific region. Therefore, this study explores important research questions: (a) Whether there exists any simultaneous relationship between Gross Domestic Product (GDP) per capita (a proxy for EG), carbon dioxide (CO2) emissions per capita, and health expenditure (HE) per capita?; and (b) Does there exist any unobserved distributional heterogeneity across the Asia‐Pacific region that influence the elasticity? To address these questions, we examine the interface between GDP per capita, CO2 emissions per capita, and HE per capita in 52 countries from the Asia‐Pacific region for the period 2000–2014 using bootstrapping fixed‐effects (FEs) quantile regression model. Our results show that there is a variation in distributional effects between HE, EG, and CO2 emissions. By and large, there is a positive relationship between HE, EG, and CO2 emission across quantiles, though the coefficient values differ, and elasticity could be greater or lesser than one. It is also observed that growth raises health spending and increases pollution in lower‐income countries. On the contrary, income growth also promotes the adoption of green technology, reduces pollution, improves population health, and reduces healthcare spending in higher income countries. The study brings out some important suggestions from public policy perspectives to streamline the healthcare and sanitation sectors, and environmental quality across countries as integral aspects of sustainable growth strategies and the achievement of the United Nations SDG Agenda 2030. The findings and suggestions assume added significance in the post‐pandemic COVID‐19 scenario, as it calls for revamping the healthcare management systems across countries. [ABSTRACT FROM AUTHOR]

The properties of multi‐horizon forecasts are investigated by specifying and estimating a model nesting rational forecasts, as well as deviations from rationality resulting from horizon‐specific biases and idiosyncratic errors. Identification of the model's parameters is achieved by combining information on forecasts for a given point in time with different information sets, and forecasts at different points in time based on the same information set. Both sets of forecasts are used to estimate the model's parameters by generalised method of moments. A test of rationality is proposed with the twin advantages of circumventing parameter identification and boundary issues. The finite sample properties of the GMM estimator and the rationality test are also investigated. Applying the approach to US GDP growth forecasts of the Survey of Professional Forecasters, the empirical results show that forecasts deviate from rationality over all forecast horizons, with the strength of the deviations from rationality increasing with the forecast horizon. [ABSTRACT FROM AUTHOR]

Our study examines the comparative impact of governance quality on the dynamic relationship between monetary policy rate, saving, and economic growth in emerging economies in sub‐Saharan African countries from 2005Q1 to 2022Q4. Using the Toda‐Yamamoto (TY) model, we found that governance quality influence on monetary policy rate is negative with adverse effect on investment‐growth while exerting positive influence on savings‐growth nexus in Nigeria but the contribution is quite appreciative and can be leverage on. Governance quality exert negative influence on monetary policy rate but with positive direction from investment and savings to growth in Egypt. The magnitude of the monetary policy rate, savings, investment is quite negligible in Egypt. For South Africa, governance quality exerts positive influence on monetary policy rate but failed to translate to positive effect on investment, savings to growth in South Africa. Although, the contribution of monetary policy rate, savings, investment to growth is significant in South Africa. Thus, enhancing institutional development to foster a more effective financial incentive system and seamless policy transmission is crucial to address the impact of governance quality on monetary policy outcomes and enable better macroeconomic interactions. [ABSTRACT FROM AUTHOR]

There have been very few studies done on measuring the influence of all prefecture‐level cities on a national scale due to the limited availability of public data, challenges in data collection, and insufficient data comprehensiveness. In this paper, we aim to fill this gap by investigating this problem in China. We first collected 692,859 news articles spanning one full year from the WeChat Official Accounts of 339 cities and Taiwan Province, which served as our study area and dataset. Then, we developed a city extractor module to reduce the ambiguity of place names and constructed a city interaction network. Then, we modeled the City Influence Index (CII) and the intensity of its influence. Finally, we proposed an analytical framework that examines the relationship between CII and Gross Domestic Product (GDP), compares it with the Global Cities Index, conducts influence analysis of cities at different levels, and more. The experimental results demonstrate that our analytical framework can effectively measure the influence of cities on a national scale and uncover the implicit relationships between cities. In doing so, our study offers a new perspective for measuring city influence. Code is available at: https://github.com/vczero/CII. [ABSTRACT FROM AUTHOR]

Climate change is one of the most pressing challenges of our time, with far‐reaching implications for ecosystems, economies, and societies worldwide. Human capital (HUC) and economic complexity (ECC) "understood as structural transformation toward more sophisticated and knowledge‐based production" can be pivotal in curtailing ecological degradation. In this context, the study explores the intricate relationship between HUC, financial development, financial globalization, gross domestic product, ECC, and ecological footprints from 1995 to 2021. To achieve this objective, advanced econometric estimation methods are employed. The results indicate the presence of cross‐sectional dependence and slope heterogeneity in the dataset. The variables present a mixed order of stationarity, while the Westerlund test indicates the presence of a long‐run equilibrium association. The results from the Method of Moments Quantile regression indicate that ECC posed a positive but insignificant effect in the lower quantile (τ = 0.1–0.25), while negative and significant in the middle (τ = 0.50) and upper quantiles (τ = 0.75–0.90). Moreover, financial globalization negatively and significantly affects ecological footprints through all the quantiles except the lower quantile (τ = 0.1). Financial development, gross domestic product, and HUC enhance environmental degradation by escalating ecological footprints. Based on the results, the study suggested enhancing the ECC and financial globalization, while sustainable utilization of HUC and strict regulations for the financial sector to foster sustainable development in E7 countries. [ABSTRACT FROM AUTHOR]

This study investigates the dynamic effect of resource productivity and green technologies on renewable energy (RE) use in 28 middle‐income countries from 2006 to 2022 using MMQR, QR and causality techniques. Results suggested that green technology innovation substantially influences RE use. Second, the significant positive coefficients show that resource productivity leads to higher RE consumption at the upper quantile due to decoupling Gross Domestic Product (GDP) growth from extracting natural resources, indicating a transition towards more sustainable and efficient practices. Based on the empirical findings, several policy implications are suggested for middle‐income economies. [ABSTRACT FROM AUTHOR]

The study explores the effects of data transparency on economic growth for developing economies over a unique time period ‐ at the onset of the 2007–2009 global financial crisis and thereafter. Data transparency is defined as the timely production of credible statistics as measured by the statistical capacity indicator. The paper finds that data transparency has a positive effect on real gross domestic product per capita during a period of considerable uncertainty. The estimates indicate an elasticity of the magnitude of 0.03 percent per year, which is much larger than the elasticity of trade openness and schooling in the estimation sample. The empirics employ a variety of econometric estimators, including dynamic panel and cross‐sectional instrumental variables estimators, with the latter approach yielding a higher estimated elasticity. The findings are robust to the inclusion of several factors in addition to political institutions and exogenous commodity‐price and external debt‐financing shocks. [ABSTRACT FROM AUTHOR]

Countries with abundant natural resources often possess greater wealth, yet the impact of these resources on economic growth remains unclear. This paper examines how natural‐resource abundance and its volatility impact economic growth. It questions whether natural resources themselves are a curse or if the negative growth effects are due to the volatility of natural‐resource revenues. The study also investigates how volatility of natural resources affects key economic growth channels, such as investment, human capital, and institutional quality. Using the standard panel model and panel smooth transition regression (PSTR), the paper analyzes data from 125 countries (1988–2020). Results show that natural‐resource abundance boosts economic growth, contradicting the resource‐curse theory. However, the growth impact is non‐linear and varies with natural‐resource volatility. Countries with high volatility face up to a 22 percentage point annual GDP growth loss compared with those with low volatility, suggesting that volatility and poor government responses drive the resource‐curse paradox, not the abundance of resources per se. [ABSTRACT FROM AUTHOR]

The conflict between economic development and ecological protection in land use (LU) has been a significant and widely discussed topic. The city circle concept has been proposed to promote economic growth through its strong agglomeration effect. It contains the core city and its surrounding area, and economic activities and ecosystems are highly intertwined within this geographic unit. Meanwhile, population, industry, and infrastructure are often concentrated within the urban sphere, which results in a concentrated demand for land, water, and ecosystem services. As a result, LU conflicts are more pronounced in urban areas. Here, we used gross domestic product (GDP) and gross ecosystem product (GEP) to reflect economic and ecological levels, then linked LU change into the coupling relationship between GDP and GEP of the Wuhan City Circle (WHCC), China, to analyze the economic and ecological developments of WHCC. Finally, we constructed a partial least squares structural equation modeling to explore the key drivers affecting the coupling of real GDP and GEP. Our results revealed significant LU changes between 1990 and 2020 for the WHCC. Paddy fields, dry lands, and some forestlands decreased, while built‐up lands and water areas both increased. Real GDP of the WHCC increased from $1.04 × 106 in 1990 to $3.04 × 107 in 2020. While the GEP of the WHCC increased during 1990–2010 and decreased during 2010–2020. Additionally, GEP exhibited a significant spatial heterogeneity, with high GEP concentrated in the central and southeastern regions. Moreover, we constructed a conceptual model for coupling real GDP and GEP, then used structural equation modeling to reveal their relationship. Real GDP had a positive effect on GEP. Furthermore, the proportion of construction land and ecological land as intermediate variables played an important direct and indirect role in real GDP and GEP. Consequently, landscape planning was proposed to enhance the green infrastructure of the WHCC. Our findings provide a reference and experience on land resource allocation for maintaining sustainable development in the city circle. [ABSTRACT FROM AUTHOR]

Railways were an important driver of global economic growth in the nineteenth and early twentieth centuries. Whilst their role is well documented in industrial economies, we know less about their macro‐economic impact in developing countries. In this paper, we first estimate the aggregate growth impact of Indian railways, one of the largest networks in the world in the early twentieth century. Then, we compare their impact in India to four emerging Latin American economies (Argentina, Brazil, Mexico, and Uruguay) and the Cape colony. Using growth accounting techniques common to the cross‐country estimates, we argue that the aggregate growth impact of Indian railways was significant, increasing Indian gross domestic product (GDP) per capita by 13.5 per cent by 1912. We also find that the growth impact of Indian railways was similar to Brazil and Mexico, but smaller than Argentina and the Cape. Compared with the latter, India had a smaller size of railway freight revenues in the economy and lower wages to fares leading to lower passenger time savings. Railways were the most important infrastructure driver of economic growth in India during the first era of globalization from 1860 to 1912, but they contributed less than in richer and more dynamic developing economies. [ABSTRACT FROM AUTHOR]

Supermultiplier models, which show how autonomous demand can drive both business cycles and long‐run GDP growth, are based on a stability assumption. In this paper I look at recent efforts to justify this assumption, and argue that they are not convincing. The supermultiplier literature generally assumes that business investment reacts very slowly to changes in the state of the economy, but faster adjustment speeds are consistent with US data and can generate instability. [ABSTRACT FROM AUTHOR]

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This paper investigates the drivers of international fiscal spillovers across 62 countries for the period covering 1970–2021. Using the local projections method at the country‐pair level, fiscal spillovers are estimated as the cumulative response of the real gross domestic product (GDP) growth in spillover destination countries to a unit shock in the real government spending growth in spillover source countries. Pairwise estimation results (for 3782 country pairs) suggest that there are statistically significant fiscal spillovers for 36% of country pairs, whereas this ratio is 49% for country pairs within the euro area. For the median country pair, a unit shock of real government spending growth in the spillover source country results in about 0.09% of the increase in the real GDP growth of the spillover destination country, whereas this fiscal‐spillover estimate goes up to 0.42% when the spillover source is in the euro area, and the spillover destination is an oil producing country. A secondary investigation based on the Heckman selection model is used to identify the drivers of fiscal spillovers across country pairs, where the existence of statistically significant fiscal spillovers is shown to be connected to the proximity between countries. The size of fiscal spillovers is further shown to increase with the initial (as of 1970) country size, trade openness, and government size of the spillover source country, whereas it decreases with the initial country size and trade openness of the spillover destination country. Important policy suggestions follow. [ABSTRACT FROM AUTHOR]

Materialism is fundamental to the human value or goal system; therefore, an understanding of its level among Chinese college students and its changes over time is of great value. In the present study, a cross‐temporal meta‐analysis was performed by reviewing studies that conducted Material Values Scale‐based assessment of the materialism level among Chinese university students from 2007 to 2020. Moreover, a time lag analysis was performed to clarify whether variations in materialism level are interpretable with macro‐social indicators. Finally, 82 articles on studies enrolling a total of 45,966 Chinese university students were reviewed. The materialism score significantly increased on a yearly basis. Furthermore, macro‐social changes in diverse areas, including economic condition (gross domestic product per capita, consumption level of all residents and national disposable income per capita), social connectedness (urbanisation degree and divorce ratio) and overall threat (rate of university enrollment), were the major factors influencing the degree of materialism among the students. By identifying the inclining trend of materialism among these college students across time and using relevant macro‐social indicators, a theoretical three‐dimensional framework was established to elucidate the degree of materialism among Chinese college students as a group. [ABSTRACT FROM AUTHOR]

Few studies have acknowledged and quantified the economic contribution in expenditures of recreational fisheries. Additional economic value attributed to fishers' willingness to pay (WTP) for recreational fisheries in excess of expenses was estimated for 33 countries in Europe. Benefit transfer was used in a meta‐regression analysis of 184 studies and 1001 observations of WTP per day for recreational fisheries. Most studies of fishing were in the USA, but also in Europe, Australia, New Zealand, South America and Canada. Mixed‐effects regression models were estimated with income, climate variables, population density and study characteristics as explanatory variables. Income and temperature positively affected WTP per day. Benefit transfers with these variables and different transfer methods among European countries showed that the estimated total WTP could amount to 11.4 billion USD (purchasing power parity corrected to 2020 prices). Variation in WTP per day was large, and ranged 9–62 USD among countries and transfer methods. For several countries, WTP for recreational fisheries exceeded 0.1% of gross domestic product. [ABSTRACT FROM AUTHOR]

Background: This SRMA reviewed and assessed the changes in the severity of disorders of gut‐brain interaction (DGBI) symptoms during the COVID‐19 pandemic, and evaluated factors associated with symptom severity changes. Methods: Electronic databases were searched until February 2024, for articles reporting on changes in symptom severity in DGBI patients during the COVID‐19 pandemic. The proportion of DGBI patients who reported a change in their symptom severity were pooled using a random‐effects model, and subgroup analyses were conducted to assess the effect of socio‐cultural modifiers on symptom severity in DGBI. Key Results: Twelve studies including 3610 DGBI patients found that 31.4% (95% CI, 15.9–52.5) of DGBI patients experienced symptom deterioration, while 24.3% (95% CI, 10.2–47.5) experienced improvement. Countries with high gross domestic product (GDP) had a 43.5% (95% CI, 16.3–75.2) likelihood of symptom deterioration, compared to 9.2% (95% CI, 1.4–42.2) in lower GDP countries. Similarly, countries with low COVID fatality rates had a 60.1% (95% CI, 19.7–90.3) likelihood of symptom deterioration, compared to 18.3% (95% CI, 7.8–36.9) in higher fatality rate countries. Countries with lenient COVID policies had a 58.4% (95% CI, 14.1–92.3) likelihood of symptom deterioration, compared to 19% (95% CI, 8.2–38.1) in countries with stricter policies. Patients in high vaccine hesitancy countries had a 51.4% (95% CI, 19.5–82.2) likelihood of symptom deterioration, compared to 10.6% (95% CI, 2.7–33.4) in low vaccine hesitancy countries. Conclusions & Inferences: This meta‐analysis reveals that a significantly higher proportion of DGBI patients experienced deterioration of symptoms during the COVID‐19 pandemic. Various sociocultural, economic and environmental factors potentially modify the effects of the COVID‐19 pandemic on DGBI. [ABSTRACT FROM AUTHOR]

Land use change (LUC), including deforestation, agriculture, and urbanization, is a major contributor to climate change (CC). This change in land use has impacts on food, water, and energy systems, creating a complex interconnected web of issues. This study aimed to investigate the global link between LUC and CC from 1990 to 2012. Using time‐series data from the World Bank, LUC was represented by irrigated land, arable lands, and forest areas, while CC was represented by CO2 emissions. Moreover, the relationship between economic growth in high‐income and low‐income countries and LUC and CC was examined in this study. Based on the findings of this study, in low‐income countries, the intensity of LUC is higher in comparison with high‐income countries. Meanwhile, CO2 emissions are increasing in middle‐income and high‐income countries. Economic growth is closely related to CO2 emissions in countries with different levels of income. The study indicated that managing land use is of high importance to mitigate CO2 emissions globally. According to the findings, recent LUC has shown more obvious effects on ecological variables than CC. Although LUC is not inherently directly related to CC, humans change land use, especially in terms of land management, to adapt to CC, and these changes will inevitably bring many environmental impacts. This study contributes significantly to advancing the understanding of the complex relationship between CC and LUC, emphasizing the need for integrated approaches in policy development. These measures are crucial to achieving resilience and meeting global CC reduction targets. [ABSTRACT FROM AUTHOR]

Multivariate analysis can help to focus on important phenomena, including trend and cyclical movements, but any economic information in seasonality is typically ignored. The present paper aims to more fully exploit time series information through a multivariate unobserved component model for quarterly data that exhibits seasonality together with cross‐variable component correlations. We show that economic restrictions, including common trends, common cycles and common seasonals can aid identification. The approach is illustrated using Italian GDP and consumption data. [ABSTRACT FROM AUTHOR]

Gross ecosystem product (GEP) is the aggregate economic value of the final goods and services of the ecosystem produced within a given area, providing a potentially effective means of linking nature protection and restoration to development.In this study, we calculated the values and distribution of biodiversity, GEP and gross domestic product (GDP) in the 547 counties of Southwestern China, a biodiversity hotspot. We then divided the region into nine types of area based on spatial correlations between the three indicators.Areas with high biodiversity, GEP per km2 and GDP per capita were mainly found in and around the large cities of Kunming, Chengdu and Guiyang, reflecting a reasonably high degree of coupling coordination between ecosystems and the local economy.Contrary to our hypotheses, areas with high biodiversity do not necessarily have high GEP, and regions with high GDP do not inherently have low biodiversity. This suggests that synergies exist between biodiversity conservation and economic development, and that increasing the value of material and non‐material services in GEP could improve this alignment.Based on our findings, we argue that GEP can act as a bridge between biodiversity conservation and economic development. Understanding the interactions between biodiversity, GEP and GDP can inform the design of effective policies. In particular, we suggest that sustainable agricultural intensification and forestry along with ecotourism offer promising pathways for advancing nature‐positive development in this ecologically critical region. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Services provided by nature and ecosystem capital are unpriced and their contributions cannot be observed through factor payments. Estimates of nature's gross domestic product contribution are thus based on bottom‐up extrapolations of local ecological valuations or various sectoral dependency assumptions. These estimates are hence partial and wide‐ranging. On the other hand, omission of nature and ecosystem capital in standard growth regressions potentially biases estimated returns to other factors of production. This paper incorporates various categories of natural capital and biodiversity into growth regressions, with annual data covering more than 100 economies over more than two decades. A range of econometric specifications are used, including fixed effect panel regressions, Arellano and Bond, and Pseudo Poisson Maximum Likelihood. The estimates point to natural capital, especially the narrower and specific ecosystem capital, having a sizeable positive elasticity of around one‐third of total gross fixed capital. Ecosystem capital is thus estimated to contribute around USD6–12 trillion (or 10–20 trillion in purchasing power parity terms) annually for the global economy. This estimated contribution is significantly higher than what is implied by existing stock valuations, underscoring the importance of ecosystem capital to sustainable growth. [ABSTRACT FROM AUTHOR]

This paper discusses the economic effects of a potential cut‐off of the German economy from Russian energy imports. We use a multi‐sector open‐economy model and a simplified approach based on an aggregate production function to estimate the effects of a shock to energy inputs. We show that the effects are likely to be substantial but manageable because of substitution of energy imports and reallocation along the production chain. In the short run, a stop of Russian energy imports would lead to an output loss relative to the baseline situation, without the energy cut‐off, in the range 0.5% to 3% of GDP. This paper is part of the Economica 100 Series. Economica, the LSE "house journal" is now 100 years old. To commemorate this achievement, we are publishing 100 papers by former students, as well as current and former faculty. Benjamin Moll is the Sir John Hicks Professor of Economics at the LSE. David Baqaee was an Asst. Prof. of Economics at the LSE. Moritz Schularick obtained his MSc from the LSE. [ABSTRACT FROM AUTHOR]

Gastric cancer (GC) remains a significant health concern in Gansu province, China, with morbidity and mortality rates surpassing national averages. Despite the recognized health risks associated with ambient particulate matter with an aerodynamic diameter <1 μm (PM1), the relationship between PM1 exposure and GC incidence has not been extensively studied. Data on GC cases from 2013 to 2021 were gathered from 262 hospitals in Gansu, China. Concurrently, data on the normalized vegetation index (NDVI), gross domestic product (GDP), drinking and smoking behavioral index (DSBI), PM1, PM2.5, and PM2.5–1 were collected. Utilizing a Bayesian conditional autoregressive (CAR) combined generalized linear model (GLM) with quasi‐Poisson regression, we evaluated the impact of PM1, PM2.5, PM2.5–1, NDVI, DSBI, and GDP on GC morbidity while adjusting for potential confounders. Our analysis indicated that exposure to PM1 (μg/m3) is significantly positively correlated with GC incidence in regions with an overall age‐standardized incidence rate (ASIR) >40 (relative risks [RR]: 1.023, 95% confidence intervals [CI, 1.007, 1.039]), male ASIR >50 (RR: 1.014, 95% CI [1.009, 1.019]), and female ASIR >20 (RR: 1.010, 95% CI [1.002, 1.018]). PM2.5, PM2.5–1, DSBI, and GDP were positively correlated with GC incidence, while NDVI was negatively correlated in the study regions. Our findings provided evidence of a positive correlation between PM1 exposure and GC incidence in high‐risk areas of GC within arid regions. Further research is warranted to elucidate the complex nonlinear relationships between environmental factors and GC. These insights could inform strategies for improving the control and prevention of GC in Gansu and similar regions. [ABSTRACT FROM AUTHOR]

The global economy has been witnessing increasing geopolitical risk (GPR) in recent years. The rise in GPR has several consequences, and the impact of this situation on natural resource rent (NR) has not yet been analyzed for the major oil‐producing countries. Given this deficiency, this study analyzes the impact of GPR, gross domestic product, the labor force (LBR), load capacity factor, population density, and trade openness on the NR for the five major oil‐producing countries (namely, Canada, China, Russia, Saudi Arabia, and the United States of America). To this end, the study analyzes data for the period 1995/Q1‐2021/Q4 by using a cross‐sectional Autoregressive Distributed Lag approach. The results demonstrate that (i) an increase in GPR and load capacity factor declines the NR; (ii) an increase in gross domestic product stimulates the NR; and (iii) a rise in population density, labor force, and trade openness has a stimulating impact on the NR. Overall, the research shows that all variables substantially impact the NR. Based on the results, various policy options are discussed, such as assessing geopolitical tensions as leverage to sustainably regulate the natural resource market and growth to prevent negative impact from managing the NR effectively for the five major oil‐producing countries. [ABSTRACT FROM AUTHOR]

The influence of oil proceeds on an economy remains a subject of debate among scholars. Most scholars agree that income from oil has direct effect on economic expansion. We explore the impact of revenue from oil on economic growth in Nigeria from 1986 to 2016. Data were collected from the Nigerian Central Bank and the World Data Indicators. We employed a non‐linear autoregressive distributive lag approach to analyse the data. The outcome exposes a direct and significant association between revenue from oil and GDP both in the short and long term. Trade openness exhibits a significant negative effect on GDP from both short‐ and long‐term perspectives. Gross capital formation directly influences GDP in the short and long run, with significant impacts primarily in the long term. The study suggests that revenue from oil has a direct and significant impact on the Nigerian economy during the period from 1981 to 2016. We recommend that the Nigerian government create a conducive environment for private investment to thrive, thereby sustaining the nation's growth potential. Additionally, the government should wisely utilise revenue from oil to revitalise non‐booming productive sectors in the economy, thus diversifying revenue sources. [ABSTRACT FROM AUTHOR]

ABSTRACT Gross domestic product (GDP) is frequently used as a proxy for well‐being. Such use of GDP is problematic for many reasons, for GDP excludes activities that contribute to well‐being and includes others that have a negative impact instead. As a result, a vast array of metrics has been developed to complement or replace it and put well‐being at the heart of policymaking. Nonetheless, previous research has shown that their use and impact on policymaking has been limited. This article examines the use and impact of well‐being metrics according to their own developers and intended users in the crucial cases of Scotland and Italy, focusing specifically on the two countries' official well‐being frameworks. Despite being at the forefront of the well‐being debate, both countries have never been studied in this regard before. This article fills this gap, collating views from more than 100 stakeholders, including statisticians, members of interest groups, policymakers and journalists. Findings show that the vast majority of informants could not cite any examples of cases in which either framework impacted on policymaking, or in which they themselves had used these. In some cases, this was due to them not being aware of what such frameworks were in the first place. Those who could identify some examples were those who were or used to be part of the government. Examples would, however, tend to be vague, in some instances remarkable yet merely anecdotal, and still in others the result of an ‘ex‐post rationalisation’. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is a rapidly expanding field. Given the dynamic nature of AI research, staying up‐to‐date with this evolving landscape is imperative to guide the global race in this field. Using the world's largest bibliometric database (SciVal/Scopus), we analyzed the research output of the top 15 countries in AI research productivity between the years 1998 and 2022. Over the past 25 years, the global research output in AI has increased by 26 folds, with China leading the way in the overall number of AI publications (~281,650 articles). During this period, China and India had the highest fold growth (~240–250) and compound annual growth rate (CAGR) (~25). However, when normalized to population size and gross domestic product (GDP), Singapore (250 AI publications per million capita) and India (7.7 AI publications per billion GDP) were the best performers in 2022, respectively. When normalized to the number of researchers and gross expenditures on research and development (GERD), again, India was the best with 36.8 AI publications per thousand researchers and 0.77 AI publications per million GERD in 2020. When the overall quality of AI publications over the past decade was considered, Hong Kong and Singapore performed the best with respect to publications in higher percentile journals (the top 1%, 5%, and 10% journals), and Switzerland performed the best with respect to citations/publication and field‐weighted citation impact (FWCI). Finally, when the quality measures of publications were normalized to country or research metrics, the three best performers were Hong Kong, Singapore, and Switzerland (although India stood out for citations/GERD). These three countries (along with the United States) also had the highest economic impact as measured by the patent citations per scholarly output, which was aligned with the high FWCI values for these countries. Long‐term strategies to help leading countries gain an advantage in the AI frontier have been discussed at the end of the manuscript. These strategies include government initiatives and financial support, talent creation and networking, public awareness, and mindful considerations of rules, guidelines, and ethics. [ABSTRACT FROM AUTHOR]

This study intends to empirically evaluate the effects of economic globalization and its components (i.e. trade and financial openness) on unemployment in high‐, middle‐ and low‐income countries from 1991 to 2020. Further, it considers real GDP per capita (sectoral divisions of income, i.e. agriculture, industry and service sector) and urbanization as control variables in the unemployment function. On the empirical front, this study employs the Panel Dynamic Simulated ARDL model and the Kernel‐Based Regularized Least Squares for long‐run influence estimations. The emanating outcome of these analyses states that economic globalization destroys employment opportunities for low‐income countries as it enhances unemployment in the long run. However, in high‐ and middle‐income countries, economic globalization creates employment, which implies reducing unemployment in the long run. The result also indicates that trade and financial openness destroy employment opportunities in low‐income countries. Although trade openness in middle‐income countries shows the same effect, financial openness does not mimic the same. For high‐income countries, trade openness reduces unemployment, but financial openness fosters it. Therefore, these findings indicate that to keep unemployment at a low level, policies related to the opening up of the economy in terms of factor mobility, offshoring, outsourcing and international trade need to be implemented in low‐income countries. Moreover, a similar consideration is needed for high and middle‐income countries to avoid faraway repercussions on unemployment due to becoming a peripheral country. [ABSTRACT FROM AUTHOR]

A country's institutional quality (INS) influences its export performance (EXP) and plays a vital role in international trade. The purpose of this study is to investigate the short‐run and long‐run relationships among these macroeconomic factors in Pakistan. Annual data from the World Development Indicators and the International Country Risk Guide were used from '1989 to 2019'. To investigate the short‐run and long‐run linkage between INS and EXP, the non‐linear auto‐regressive distributed lag and error correction model are used after incorporating structural breaks. Additionally, the macroeconomic explanatory variables used are the exchange rate (ER), human capital (HC), gross domestic product (GDP) and foreign direct investment (FDI). In the long run, INS, HC, GDP and FDI have a significant positive relationship with EXP, whereas the ER has a significant negative relationship. In the short run, INS is significant and positive, whereas HC, GDP and FDI with EXP are modest but significantly positive. To improve export performance in Pakistan, strategic reform of governmental institutions is required. [ABSTRACT FROM AUTHOR]

Background: Disorders of gut–brain interaction (DGBI) are characterized by debilitating symptoms not explained by structural or biochemical abnormalities. While functional conditions present with complex, likely heterogeneous pathophysiology, we aimed to investigate if proxy measures of sociocultural and environmental factors are associated with the prevalence of various DGBI in populations across the world. Method s : We performed an ecological study utilizing peer‐reviewed published datasets reporting for 26 countries prevalence rates of DGBI (Rome Foundation Global Epidemiology Study, RFGES), with six independent variables: Helicobacter pylori prevalence and household size as proxy measures for orofecal infections, gross domestic product per capita (GDP), and median age as a proxy measures for socioeconomic development, density of fast food outlets (FFO) per 100,000 population as proxy measure for processed food exposure, and suicide mortality rate per 100,000 people, and world happiness scores were used as a proxy for psychological stress. The data were retrieved from publicly accessible datasets (United Nations, CIA World Factbook, World Bank, World Happiness Report, commercial/financial reports of a global FFO chain). We used linear regression to assess variables in univariate and multivariate analysis and report standardized β coefficients with 95% confidence intervals (CI). Key Results: The regression model revealed that the overall prevalence of DGBI was inversely associated with both GDP per capita (β = −0.57, 95% CI: −0.92, −0.22, p = 0.002) and happiness scores (β = −0.433 95% CI: 0.821, −0.065, p = 0.023), while being positively associated with H. pylori prevalence (β = 0.40, 95% CI: 0.008, 0.81, p = 0.046). The prevalence of functional constipation (FC) was also inversely associated with GDP per capita (β = −0.50, 95% CI: −0.86, −0.13, p = 0.01) and happiness scores (β = −0.497, 95% CI: −0.863, −0.132, p = 0.01), while being positively associated with H. pylori prevalence (β = 0.53, 95% CI: 0.16, 0.91, p = 0.007). The Multivariate model analysis revealed that combining the factors of H. pylori prevalence, suicide rate, household size and happiness scores showed statistically significant association with FC (p = 0.039). Household size (β = −0.43, 95% CI: −0.82, 0.038, p = 0.033) and suicide rates (β = 0.55, 95% CI: 0.19, 0.90, p = 0.004) were statistically significantly associated with functional diarrhea. Irritable bowel syndrome (IBS) was associated with GDP per capita (β = −0.40, 95% CI: −0.79, −0.014, p = 0.043) and happiness scores (β = −0.390, 95% CI: −0.778, −0.003, p = 0.049). Conclusions & Inferences: Utilizing publicly available data, the prevalence of DGBI across diverse countries is linked to various socio‐cultural and environmental factors. Collectively, the data suggests that the prevalence of DGBI is increased in less prosperous regions of the world. [ABSTRACT FROM AUTHOR]

The precarious nature of climate change and its consequences on the resilience of economies require examination. This study investigated climate change resilience in the "big three" economies in Africa—Egypt, Nigeria, and South Africa—using macroeconomic data. Results indicated that Nigeria had the highest vulnerability score and South Africa had the highest resilience score. Readiness for climate change was low in all countries, especially in Nigeria. Climate vulnerability had a significant dampening effect on per capita Gross Domestic Product (GDP) in the three economies. In addition, reducing inflation is associated with increased welfare and resilience by raising per capita GDP, although the effect needs to be magnified with sound economic policies. The low adaptive capacity presents policy direction to develop human resource capacities, improve safety net delivery, and ensure effective early warning systems. [ABSTRACT FROM AUTHOR]

In the context of sub‐Saharan Africa (SSA), characterized by abundant natural resources and persistent challenges in economic growth, this paper explores the effect of economic complexity (EC) on natural resource depletion (NRD) from 1997 to 2017. To this end, the study employs data mainly from the World Development Indicators on 36 SSA countries. Using both the pooled ordinary least squares and the two‐step system generalized method of moments estimation techniques, the results indicate that EC significantly contributes to reducing the exhaustion of natural resources in SSA during the study period. The findings equally suggest that government expenditure on education, as well as gross domestic product per capita, exert a reducing effect on NRD, while energy use, foreign direct investment, and urbanization are vectors of resource exhaustion in the region. The results remain consistent when an alternative measure of EC is applied as well as when different estimation strategies are used. This offers scope for a reminder for proper management policies to be edited and applied regarding these mostly nonrenewable resources. [ABSTRACT FROM AUTHOR]

The key purpose of this study is to explore the relationship between inflation and output dynamics in a global macroeconomic framework by utilising time‐series data from Pakistan and thirty‐two trading partners which account for around 95 per cent of foreign trade of Pakistan, over the period 1979Q2–2016Q4. By featuring the GVAR approach, this paper empirically examined the international linkages to account for cross‐country inflationary spillovers. The findings show that both foreign and global variables jointly and significantly matter for the inflation‐output relationship in developing economies, in general and, in particular, in the economy of Pakistan. The findings from general impulse response functions (GIRF) reveal that shocks to the US real output, oil prices and food prices are transmitted and settled quickly, and put forward a significant impact on real GDP and inflation in Pakistan and its trading partner economies. Inflation in Pakistan is driven more strongly by the global changes in oil and food prices than GDP. For monetary policy formulation, the central bank should take into account developments in inflation‐output dynamics of Pakistan's major trading partners. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the evolution of inequality in Greece from 2004 to 2021 in light of the Greek debt crisis that led to a sharp drop in gross domestic product per capita between 2008 and 2013. While aggregate measures of income inequality, such as the Gini coefficient, suggest a marginal improvement, domestic perceptions of social fairness remain bleak. To delve deeper into this paradox, we explore additional aggregate and distributional aspects of Greece's social landscape during this period. Our analysis reveals several contributing factors: a compression of earnings, benefits and pensions; a sharp increase in social exclusion; and high inequality in access to basic public services and housing. These factors go beyond what headline inequality indices indicate, illustrating how the sovereign debt crisis and subsequent austerity measures have affected individuals differently based on their socio‐economic background, while also reducing overall welfare across the Greek population. Moreover, chronic institutional inefficiencies and widening disparities in access to services and housing significantly influence perceptions of inequality and contribute negatively to the country's social cohesion. [ABSTRACT FROM AUTHOR]

This study delves into the effect of environmental, social and governance (ESG) indicators on economic growth trajectory of an emerging economy. A sample of firms listed on the ESG index of the National Stock Exchange (NSE) was examined. The findings reveal a positive and statistically significant relationship between ESG performance indicators and economic growth represented as gross domestic product (GDP) per capita. The sample is further segregated into energy and non‐energy sectors, where the aggregate ESG scores exhibited a statistically significant influence on economic growth in both sectors. However, upon a closer examination of the individual ESG pillars, the governance pillar is observed to exert a negative influence on economic performance in non‐energy firms. In contrast, the environment and social pillars show no significant influence. The analysis then employs a unique approach by applying a Difference‐in‐differences estimator to assess the impact of Business Responsibility and Sustainability Reporting (BRSR) regulations, which confirms a positive impact on economic growth after regulations but exclusively within the non‐energy sector. This study underscores the substantial impact of ESG aggregate and individual scores on GDP per capita, which translates to economic growth. [ABSTRACT FROM AUTHOR]

Micro, small, and medium‐sized enterprises (MSMEs) are fundamental to the economy of Bangladesh, significantly contributing to job creation and poverty alleviation. Securing financing is essential for the growth and development of the MSME sector. This research investigates the entrepreneurial environment in Bangladesh, highlighting challenges and opportunities to enhance youth entrepreneurship. By analyzing secondary data from 2010 to 2022, the study employs a multiple regression model to examine the statistical relationship between MSME financing and economic growth. Gross domestic product Regression Equation Specification Error Test per capita is the dependent variable, loans to MSMEs are used as a proxy for MSME financing, and the unemployment rate is included as a control variable. The results indicate that MSME financing has a substantial positive impact on economic growth, while the unemployment rate has a significant negative effect. The study suggests implementing blended finance funds and a variety of supply, demand, and financial solutions to strengthen the MSME ecosystem in Bangladesh, thereby supporting national development goals and sustainable development. [ABSTRACT FROM AUTHOR]

Agricultural and applied economists make substantial positive contributions to the domestic economy. Defining a measure of the true total value of their contributions is likely impossible, because so much about their efforts is difficult to comprehensively observe and quantitatively document. In this paper, we adopt a conservative approach to generating an estimate of the contributions ag and applied economists make to U.S. economic output and the associated welfare of society through their teaching, research, and outreach efforts. To conduct the analysis, we implemented a nationwide survey of Agricultural and Applied Economics (AAE) departments and developed a framework to calculate the value of their contributions to national income, or Gross Domestic Product (GDP). We estimate that AAE departments increase overall U.S. GDP by $2.6 billion, annually. Through its efforts to improve the human capital of its graduates, AAE teaching raises the (expected) national income by $2.2–$2.3 billion, while we value direct research and outreach contributions at $207 million and $146 million, respectively. Because we do not observe the opportunity cost of the resources used to generate those contributions, we do not claim to estimate a true net economic impact but rather attempt to quantify the gross economic contributions of the professional services AAE departments currently offer the economy. The values we provide—especially the research and extension estimates which are exceedingly difficult to measure—likely underestimate the true benefits AAE offers to the nation. [ABSTRACT FROM AUTHOR]

As an efficacious solution to remedying the imbalance of medical resources, the online medical platform has burgeoned expeditiously. Apt allotment of medical resources on the medical platform can facilitate patients in reasonably selecting physicians and time slots, coordinating doctors' clinical arrangements, and generating precise projections of medical platform service volume to enhance patient satisfaction and alleviate physicians' workload. To this end, grounded in the data‐driven method, this paper assembles an exhaustive feature set encompassing hospital features, physician features, and patient features. Through feature selection, appropriate features are screened, and machine learning algorithms are leveraged to accurately forecast doctors' online consultation volume. Subsequently, to glean the influence relationship between online medical services and offline medical services, this paper introduces features of offline medical services such as hospital registration volume and regional gross domestic product (GDP) to solve the prediction of offline medical service volume using online medical information. The findings signify that online data feature prediction can pinpoint superior machine learning models for online medical platform service volume (with the optimal accuracy up to 96.89%). Online features exert a positive effect on predicting offline medical service volume, but the accuracy declines to some degree (the optimal accuracy is 73%). Physicians with favorable reputations on the online platform are more susceptible to attain higher offline appointment volumes when online consultation volume is a vital feature impacting offline appointment volume. [ABSTRACT FROM AUTHOR]

This study presents a novel and fully probabilistic approach for combining model‐based forecasts with surveys or other judgmental forecasts. In our method, survey forecasts are integrated as penalty terms for the model parameters, facilitating a probabilistic exploration of additional insights obtained from surveys. We apply this approach to estimate a growth‐at‐risk model for real GDP growth in the United States. The results reveal that this additional shrinkage significantly improves prediction performance, with the information from surveys even exerting an influence on the lower tails of the distribution. [ABSTRACT FROM AUTHOR]

Objective: To estimate the number of people in Australia with long COVID by age group, and the associated medium term productivity and economic losses. Study design: Modelling study: a susceptible–exposed–infected–recovered (SEIR) model to estimate the number of people with long COVID over time following single infections, and a labour supply model to estimate productivity losses as a proportion of gross domestic product (GDP). Setting: Australia, 2022–2024. Main outcome measures: Estimated number of people infected with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) during 2022–2023 (based on serosurvey data) who have long COVID, 2022–2024, by age group; estimated GDP loss during 2022 caused by reduced labour supply attributable to long COVID. Results: Our model projected that the number of people with long COVID following a single infection in 2022 would peak in September 2022, when 310 341–1 374 805 people (1.2–5.4% of Australians) would have symptoms of long COVID, declining to 172 530–872 799 people (0.7–3.4%) in December 2024, including 7902–30 002 children aged 0–4 years (0.6–2.2%). The estimated mean labour loss attributable to long COVID in 2022 was projected to be 102.4 million (95% confidence interval [CI], 50.4–162.2 million) worked hours, equivalent to 0.48% (95% CI, 0.24–0.76%) of total worked hours in Australia during the 2020–21 financial year. The estimated mean GDP loss caused by the projected decline in labour supply and reduced use of other production factors was $9.6 billion (95% CI, $4.7–15.2 billion), or 0.5% of GDP. The estimated labour loss was greatest for people aged 30–39 years (27.5 million [95% CI, 16.0–41.0 million] hours; 26.9% of total labour loss) and people aged 40–49 years (24.5 million [95% CI, 12.1–38.7 million] hours; 23.9% of total labour loss). Conclusion: Widespread SARS‐CoV‐2 infections in Australia mean that even a small proportion of infected people developing long COVID‐related illness and disability could have important population health and economic effects. A paradigm shift is needed, from a sole focus on the immediate effects of coronavirus disease 2019 (COVID‐19) to preventing and treating COVID‐19 and treating long COVID, with implications for vaccine and antiviral policy and other mitigation of COVID‐19. [ABSTRACT FROM AUTHOR]

The rapid decline of global biodiversity has engendered renewed debate about the social, economic, and political factors contributing to it. Specifically, there is little understanding of the role that political ideology within a country (e.g., nationalism, conservatism, socialism) plays in determining biodiversity outcomes. We used negative binomial generalized linear models to investigate the importance of national regime ideology in predicting threatened animal species and protected area establishment compared with other factors that affect biodiversity outcomes, such as gross domestic product, inequality, and democracy. For threatened animals, the model with the highest Akaike weight suggested adverse biodiversity outcomes arose from larger gross domestic product (β = 0.120, p < 0.001). However, nationalism (β = 0.371, p < 0.01) and socialism (β = 0.293, p < 0.05) were also significantly associated with increased proportions of threatened species. For protected areas, the model with the highest Akaike weight suggested increases in democracy (β = 0.880, p < 0.001) led to a rise in relative protected area estate. Conservative regime ideology was also associated with greater protected area estate, although this did not increase the weight of evidence in support of the best models. These findings highlight the relevance of political ideology for predicting biodiversity outcomes at a national scale and illustrate opportunities to tailor policies and advocacy to promote biodiversity conservation more effectively. By targeting appropriate messaging and political advocacy, conservationists can improve the likelihood that politicians and their nations will participate in positive biodiversity actions. [ABSTRACT FROM AUTHOR]

This study investigates the asymmetric effects of remittance on economic growth (EG) and environmental quality in the purview of energy use, regulatory quality (REQ), and financial development (FD) in the top 20 remittance‐earning countries. It employs panel data from 1996 to 2020 and utilizes the generalized least square (GLS) estimation and the Dumitrescu–Hurlin causality test. The GLS result shows that remittance inflow has an asymmetric effect on EG as well as environmental quality, validated by a long run asymmetric test. Remittance shocks are beneficial for both EG and maintaining environmental quality in the context of the Environmental Kuznets Curve framework. Energy use; FD, and REQ all positively affect EG, whereas FD, REQ, and gross domestic product (GDP) are favorable for the environment except for energy use. According to a supplemented analysis, remittance and regulatory quality's combined influence on EG and CO2 are favorable, but regulatory quality's impact on the former is detrimental for both models. The results of the GLS estimation are endorsed by the causality analysis, which affirms their reliability. Positive remittance shock and financial development have bidirectional causality with EG, and both shocks of remittance and financial expansion have a two‐way association with CO2 emissions. Only REQ is affected by CO2 emissions. The outcomes have important policy implications for enhancing remittance inflow, ensuring smooth energy availability, a prudential financial system, and improving REQ to influence EG and control CO2 emissions effectively. [ABSTRACT FROM AUTHOR]

Summary: This paper examines the impact of data rescaling and measurement error on scoring rules for distribution forecast. First, I show that all commonly used scoring rules for distribution forecasts are robust to rescaling the data. Second, the forecast ranking based on the continuous ranked probability score is less sensitive to gross measurement error than the ranking based on the log score. The theoretical results are complemented by a simulation study aligned with frequently revised quarterly US gross domestic product (GDP) growth data, a simulation study aligned with financial market volatility, and an empirical application forecasting realized variances of S&P 100 constituents. [ABSTRACT FROM AUTHOR]

Currently, most academic research involving the mortality modeling of multiple populations mainly focuses on factor‐based approaches. Increasingly, these models are enriched with socio‐economic determinants. Yet these emerging mortality models come with little attention to interpretable spatial model features. Such features could be highly valuable to demographers and old‐age benefit providers in need of a comprehensive understanding of the impact of economic growth on mortality across space. To address this, we propose and investigate a family of models that extend the seminal Li‐Lee factor‐based stochastic mortality modeling framework to include both economic growth, as measured by the real gross domestic product (GDP), and spatial patterns of the contiguous United States mortality. Model selection performed on the introduced new class of spatial models shows that based on the AIC criteria, the introduced spatial lag of GDP with GDP (SLGG) model had the best fit. The out‐of‐sample forecast performance of SLGG model is shown to be more accurate than the well‐known Li–Lee model. When it comes to model implications, a comparison of annuity pricing across space revealed that the SLGG model admits more regional pricing differences compared to the Li‐Lee model. [ABSTRACT FROM AUTHOR]

Hybrid electric vehicles are increasingly recognized as a promising solution for reducing carbon dioxide emissions in the transportation sector. The current study examines the nexus between innovation in hybrid electric vehicle‐related technologies and transportation sector‐based carbon dioxide emissions from 1990 to 2019 using a variety of econometric techniques such as the structural breaks unit root test, Maki cointegration test, fully modified ordinary least squares, and dynamic ordinary least squares. The results show that innovation in hybrid electric vehicle‐related technologies, renewable energy consumption, information and communication technologies, and international collaboration in technology development could help reduce transportation sector‐based carbon emissions levels. By contrast, the findings indicate that gross domestic product, trade openness, and financial development have a positive nexus with transportation sector‐based carbon emissions. Higher trade openness encourages economic expansion, and foreign trade may lead to more manufacturing, shipping, and transportation sector‐based carbon emissions. Similarly, when gross domestic product and financial development rise, the need for highly energy‐intensive items and services increases transportation sector‐based carbon emissions. To minimize Japan's transportation sector‐based carbon emissions, governments should emphasize innovation and adoption of hybrid electric vehicle‐related technologies, boost renewable energy consumption, and prohibit emissions‐intensive imports and exports. [ABSTRACT FROM AUTHOR]

Although the potential of the health tourism to support economic growth can be based on strong theoretical foundations, it is also argued that this tourism type may hinder economic growth by weakening labor productivity. On this basis, the present study aims to examine the effect of health tourism on economic growth. The study uses panel data fixed effects method with Driscoll–Kraay standard errors and dataset of 72 countries. The findings strongly supported that health tourism boosts economic growth. To be more precise, it was estimated that a one‐point increase in health tourism revenues, expressed as a percentage of gross domestic product (GDP) of personal health travel exports, causes an increase of 4.9345 in GDP growth rate and 4.2558 in per capita GDP growth rate. Furthermore, the negative growth effect of health tourism through labor productivity, which is theoretically proposed and expressed as crowding‐out effect, was not supported by the findings. [ABSTRACT FROM AUTHOR]

Recent research shows that populist governments in general depress countries' economic growth and fail to improve income distribution. We study the short‐term macroeconomic consequences of populist policies implemented in Poland since 2015. Using the augmented synthetic control method, we find that the populists boosted the gross domestic product per capita by almost 8% between 2016 and 2019. We do not find any effect of populism on inflation and estimate only small labor market impacts. The populists improved tax revenue collection and reduced public debt. A generous child benefit program and other redistributive policies introduced by the populists significantly reduced overall poverty and almost eradicated absolute child poverty. Our results suggest that antiestablishment populists may have macroeconomic viability, at least in the short term. [ABSTRACT FROM AUTHOR]