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Agricultural water salvation is the lifeblood of the national economy and is of great significance to the high-quality development of the region. In order to maximize the economic assistances of agricultural water salvation investment, this article focuses on panel data from 2005 to 2019 in 14 provinces in Eastern China, this research constructs an economic development evaluation index system from five dimensions: innovative development, coordinated development, green development, open development and shared development, and uses dynamic panel model to explore the influence relationship and path of Eastern Agricultural water salvation investment on economic development. The results represent that: there is a significant non-linear effect between agricultural water salvation investment and economic growth, showing an inverted U-shaped relationship. Which means that with the expansion of agricultural water salvation investment; economic growth has risen first and then declined. At present, the impact of agricultural water salvation investment in the Eastern region on economic development is in the promotion stage of positive and sustained growth. The recommendation of this research will help the state control in the amount of agricultural water salvation investment in the Eastern region, improve the efficiency of agricultural water salvation investment, and provide support in decision making. [ABSTRACT FROM AUTHOR]

The increased exposure of pastoralist communities in East Africa to climatic shocks has focused attention on the resilience of these communities. Although many social scientists directly or indirectly infer versions of homo-economic agents, increasing evidence in development behavioral economics, indicates that such assumptions may be misplaced. Despite on-going advances in the science concerning the effects of stress on dynamic changes in short-term cognitive capacity, there remains limited understanding of the effects of changes in cognitive capacity on economic decision making. The present research empirically evaluates the drivers of short-term changes in cognitive capacity–cognitive ability and heuristic use–and its effect on crop and livestock expenditure among predominantly poor Kenyan agro-pastoralists. Three rounds of cognition and survey data from Samburu, Kenya is analysed. The primary data was collected at the end of the 2015–16 East African drought and covers an 11-month period between October 2016 and September 2017. Dynamic panel estimation, employing maximum likelihood, is used on balanced and unbalanced data. Results indicate that fluid intelligence and heuristic use, along with literacy and stressors, affect crop expenditure. Perceptions of scarcity, relative to prior expectations, are also identified as an important determinant of short-term changes in cognitive ability. These results underscore the importance of better understanding the effects of short-term changes in cognitive capacity on economic expenditure among the poor. [ABSTRACT FROM AUTHOR]

Housing value is a major component of the aggregate expenditure used in the analyses of welfare status of households in the development economics literature. Therefore, an accurate estimation of housing services is important to obtain the value of housing in household surveys. Data show that a significant proportion of households in a typical Living Standard Measurement Survey (LSMS), adopted by the Word Bank and others, are self-owned. The standard approach to predict the housing value for such surveys is based on the rental cost of the house. A hedonic pricing applying an Ordinary Least Squares (OLS) method is normally used to predict rental values. The literature shows that Machine Learning (ML) methods, shown to uncover generalizable patterns based on a given data, have better predictive power over OLS applied in other valuation exercises. We examined whether or not a class of ML methods (e.g. Ridge, LASSO, Tree, Bagging, Random Forest, and Boosting) provided superior prediction of rental value of housing over OLS methods accounting for spatial autocorrelations using household level survey data from Uganda, Tanzania, and Malawi, across multiple years. Our results showed that the Machine Learning methods (Boosting, Bagging, Forest, Ridge and LASSO) are the best models in predicting house values using out-of-sample data set for all the countries and all the years. On the other hand, Tree regression underperformed relative to the various OLS models, over the same data sets. With the availability of abundant data and better computing power, ML methods provide viable alternative to predicting housing values in household surveys. [ABSTRACT FROM AUTHOR]

There is few significant attempt to integrate environmental regulation, government financial support, and corporate technological innovation in a methodological framework. Employing the data of the industrial enterprises with an annual turnover of over 20 million yuan from 30 Chinese provinces or municipalities between 2008 and 2016, this paper applies the fixed effect regression model to reveal the relationships between environmental regulation, government financial support, and corporate technological innovation simultaneously. Results show that: (1) there exists a U-shaped relation between environmental regulation intensity and technological innovation of enterprises which declines first and then climbs up, and China is still at the stage of inhibition before the “inflection point”. (2) government financial support does not significantly work on technological innovation directly, but environmental regulation drives this effect to be achieved; when the value of lnER is higher than 3.69, government financial support can significantly facilitate corporate technological innovation. (3) the comparison between regional samples reveals that heterogeneity exists in the influence of environmental regulation intensity and government financial support on corporate technological innovation. The threshold value of enabling effects of environmental regulation in eastern region is higher than that of the central and western region. These results remain consistent after we experiment several robustness checks. Theory and policy implications of our work are discussed. [ABSTRACT FROM AUTHOR]

Noncommunicable diseases (NCDs) are a broad challenge for decision-makers. NCDs account for seven out of every 10 deaths globally, with 42 percent occurring prematurely in individuals under age 70. Despite their heavy toll, NCDs are underfunded, with only around two percent of global funding dedicated to the disease set. Country governments are responsible for funding targeted actions to reduce the NCD burden, but among other priorities, many have yet to invest in the health-system interventions and policy measures that can reduce the burden. This article examines “investment cases” as a potential mechanism for catalyzing attention to—and funding for—NCDs. In Jamaica, using the UN inter-agency OneHealth Tool, we conducted an economic analysis to estimate the return-on-investment from scaling up strategic clinical interventions, and from implementing or intensifying policy measures that target NCD risk factors. In addition, we conducted an institutional and context (ICA) analysis, interviewing stakeholders across sectors to take stock of promising policy pathways (e.g., areas of general consensus, political appetite and opportunity) as well as challenges to implementation. The economic analysis found that scaling up clinical interventions that target CVD, diabetes, and mental health disorders, and policy measures that target tobacco and alcohol use, would save over 6,600 lives between 2017–2032, and avert JMD 81.3 billion (USD 640 million) in direct and indirect economic costs that result from mortality and morbidity linked to NCDs. The ICA uncovered government economic growth targets and social priorities that would be aided by increased attention to NCDs, and it linked these targets and priorities to the economic analysis. [ABSTRACT FROM AUTHOR]

In light of the problem of environmental pollution caused by fossil fuel combustion, and its association with rapid urbanization, China is grappling with the question of how to reduce carbon emissions through more efficient energy consumption while simultaneously advancing its economic development. We applied a directional distance function to estimate the carbon emission performance of 30 provinces in China during the period 2000–2016. We selected an index system to assess urbanization processes in these provinces and conducted a spatial analysis to investigate the relationship between urbanization and carbon emission performance. We obtained the following results. First, the carbon emission performance of the eastern region, valued at 0.853, was relatively higher than the corresponding values of 0.810, 0.804, and 0.843 in the central, western, and northeastern regions, respectively. However, during this period, disparities among provinces increased. Second, the average urbanization value for each province showed an upward trend during the study period, and urbanization assumed a “striped” spatial agglomeration pattern. A third finding was that carbon emission performance and urbanization demonstrated a relationship of positive spatial dependence. The average value of their coordinated coupling indicated an upward trend, with an annual increase of 0.85%. Last, we found that efforts to reduce carbon emissions that are solely based on carbon emission performance do not yield reliable results. Accordingly, measurements of urbanization values can enable more detailed differentiation. In conclusion, reasonable measures should be implemented to improve carbon emission performance and urbanization that are in alignment with the actual situation within a given region. [ABSTRACT FROM AUTHOR]

With green development becoming a global movement, environmental tax has been adopted by many governments to promote green development. This study analyzes the impact of environmental tax on green development by using a four-dimension dynamical system. The establishment of the system is based on the complex and dynamic interactions among economic development, pollution emissions, resources consumption, and environmental tax, where roles of environmental tax are reflected by the linear parameters. A theoretic analysis shows the complexity of the behavior of the system. Mainly, the existence of chaos is inferred by Lyapunov exponent spectrum and bifurcation diagram, then verified by the presence of a chaotic attractor. An empirical study of the green development dynamical system in China demonstrates the particular evolution paths of economic growth, pollution intensity, and resource intensity under different environmental tax parameters. Results indicate a robust beneficial role of environmental tax on green development. Furthermore, when an environmental tax is imposed, a firm government control, an active consumer awareness, an advanced technology level can stimulate economic growth, decrease pollution intensity, and control the resource intensity. But the government control has a stronger effect. This study provides a viable and promising approach to analyze the role of imposing an environmental tax on green development and may have potential application in other areas and countries. [ABSTRACT FROM AUTHOR]

China is facing severe pressure on its water resources and water environments. Calculating the industrial water efficiency of each province is an important index for the central government to evaluate local governments. In the traditional water resources evaluation index, the industrial water use efficiency and pollutant discharge are evaluated separately. In this paper, we collected industrial input data, output data and pollutant discharge data with a four-stage data envelopment analysis to calculate China's industrial water use efficiency with and without considering pollutant discharge, and then analyzed the factors influencing the industrial water use efficiency. The results show that the eastern coastal provinces of China have the highest water use efficiency and are less affected by pollutant discharge than other provinces. The industrial water use efficiency of the central and western provinces is lower than that of the other provinces, and the industrial water use efficiency in the central provinces is greatly affected by pollutant discharge. Factor endowment, economic development level, scientific and technological progress, industrial structure, proportion of foreign investment, water consumption per 10000 yuan of value-added by industry, industrial sewage treatment capacity and educational investment have a significant influence on the industrial water use efficiency of China. We suggest that the government strengthen the construction of sewage plants and other related infrastructure in central provinces when conducting the industrial transfer of heavy polluting enterprises. [ABSTRACT FROM AUTHOR]

Downscaled climate projections need to be linked to downscaled projections of population and economic growth to fully develop implications for land, natural resources, and ecosystems for future scenarios. We develop an empirical spatiotemporal approach for jointly projecting population and income at the county scale in the United States that is consistent with neoclassical economic growth theory and overlapping labor markets and that accounts for labor migration and spatial spillovers. Downscaled projections generated for the five Shared Socioeconomic Pathways used to support global scenario analysis generally show growth focused around relatively few centers especially in the southeast and western regions, with some areas in the Midwest and northeast experiencing population declines. Results are consistent with economic growth theory and with historical trends in population change and convergence of per capita personal income across US counties. [ABSTRACT FROM AUTHOR]

Objective: To develop and validate an interactive nomogram to predict healthcare-associated infections (HCAIs) in the intensive care unit (ICU). Methods: A multicenter retrospective study was conducted to review 2017 data from six hospitals in Guizhou Province, China. A total of 1,782 ICU inpatients were divided into either a training set (n = 1,189) or a validation set (n = 593). The patients’ demographic characteristics, basic clinical features from the previous admission, and their need for bacterial culture during the current admission were extracted from electronic medical records of the hospitals to predict HCAI. Univariate and multivariable analyses were used to identify independent risk factors of HCAI in the training set. The multivariable model’s performance was evaluated in both the training set and the validation set, and an interactive nomogram was constructed according to multivariable regression model. Moreover, the interactive nomogram was used to predict the possibility of a patient developing an HCAI based on their prior admission data. Finally, the clinical usefulness of the interactive nomogram was estimated by decision analysis using the entire dataset. Results: The nomogram model included factor development (local economic development levels), length of stay (LOS; days of hospital stay), fever (days of persistent fever), diabetes (history of diabetes), cancer (history of cancer) and culture (the need for bacterial culture). The model showed good calibration and discrimination in the training set [area under the curve (AUC), 0.871; 95% confidence interval (CI), 0.848–0.894] and in the validation set (AUC, 0.862; 95% CI, 0.829–0.895). The decision curve demonstrated the clinical usefulness of our interactive nomogram. Conclusions: The developed interactive nomogram is a simple and practical instrument for quantifying the individual risk of HCAI and promptly identifying high-risk patients. [ABSTRACT FROM AUTHOR]

National contributions to science are influenced by a number of factors, including economic capacity, national scientific priorities, science policy, and institutional settings and cultures. Nations do not have equal opportunities to access the global scientific market, and therefore, often seek out international partners with complementary resources and expertise. This study aims at investigating national collaboration strategies, with a focus on research leadership—measured through corresponding authorship—and its relationship with scientific impact. Results show that countries with higher R&D investments are more scientifically independent, and confirm that international collaboration is positively related to citation impact. However, leadership in international collaboration is inversely related with a countries’ share of international collaboration and there is a very little relationship between citation impact and international leadership. For instance, most countries—and particularly those that have fewer resources—have higher scientific impact when they are not leading. This suggests that, despite increasing global participation in science, most international collaborations are asymmetrical, and that the research system remains structured around a few dominate nations. [ABSTRACT FROM AUTHOR]

This study scrutinized the asymmetric impact of oil prices on stock returns in Shanghai stock exchange with data (January 2000 to December 2018) by using asymmetric ARDL model. The examined results of asymmetric autoregressive distributed lag model indicate that cointegration exists between the oil prices and the stock returns. Results of asymmetric autoregressive distributed lag model confirm that both in the long run and the short run increase in oil prices have a negative impact on the stock returns of Shanghai stock exchange while decrease in the oil prices has a positive impact on the stock returns. The examined results of this study recommend that oil prices dynamically contribute incompetence in stock prices in such a way that impact the profits of investors in stock market. [ABSTRACT FROM AUTHOR]

Understanding the causality between energy consumption, carbon emissions and economic growth is helpful for policymakers to formulate energy, environmental and economic policies. For the first time, based on nonlinear dynamics, this paper employs multispatial convergent cross mapping (CCM) to revisit the energy-carbon-economy causation for China, India and the G7 countries using both aggregate data and per capita data. The findings indicate that there are significant differences between developing countries and developed countries. A bidirectional nexus between energy consumption, carbon emissions and economic growth is found in China and India, but various causal relationships are identified in the G7 countries, including bidirectional, unidirectional and neutral nexus. The results confirm that the decoupling phenomenon is common in most G7 countries. By leveraging a variety of samples and a new approach, this study provides new evidence for policy authorities to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth. [ABSTRACT FROM AUTHOR]

This paper combines a Granger causality test and a VAR model to investigate the relationships among oil price shocks, global economic policy uncertainty (GEPU), and China’s industrial economic growth. Based on monthly data from 2000 to 2017, we reveal that GEPU and world oil prices jointly Granger cause China's industrial economic growth; world oil prices have a positive effect on China's industrial economic growth, while GEPU has a negative effect. Further analyses investigate the asymmetry effect of oil prices and find that the negative component shows a more significant impact on China's industrial economic growth. The results are robust to different oil price and EPU proxies. [ABSTRACT FROM AUTHOR]

Based on the calculation of the inclusive financial development level of 22 provinces and 4 municipalities in China from 2004 to 2017, this paper uses the Kernel density estimation method to further analyze the evolution of the inclusive financial index. Based on the above analysis, we make empirical analysis of the impact of China's inclusive financial inclusion development index on farmers' entrepreneurship using static panel and dynamic panel estimation method. The empirical conclusions show that there are certain differences in inclusive financial inclusion development level in various provinces in China. Improving the inclusion development level of inclusive finance can better promote farmers' entrepreneurship. Urbanization level, economic openness and regional economic development level have a significant positive effect on farmers' entrepreneurship, while farmers' income and education level have a significant negative effect on farmers' entrepreneurship. It is possible to promote farmers' entrepreneurship by improving the inclusive development level of inclusive finance, combining urbanization, increasing government investment in productive fixed assets, increasing economic openness and improving regional economic development. [ABSTRACT FROM AUTHOR]

The impact of environmental change on internal migration has received wide attention in recent years. Mass internal migration has been a significant economic and social phenomenon in China, and soil erosion is a major environmental problem that impacts sustainable socioeconomic development. This study aims to identify the impact of soil erosion on internal migration in China at the county level based on gravity model by analyzing related data, such as the sixth national population census data and the soil and water conservation survey data. The results of spatial overlay could not identify an obvious relationship between soil erosion and net outmigration in China. The traditional gravity model of migration is modified to analyze the impact of soil erosion on net outmigration while other variables are controlled. The results indicate that only serious soil erosion increases the possibility of outmigration and that the impact is considerably higher in agricultural counties than in non-agricultural counties. In general, the impact of soil erosion on internal migration is far less than the impact of socioeconomic factors. [ABSTRACT FROM AUTHOR]

The changing population age structure has a significant influence on the economy, society, and numerous other aspects of a country. This paper has innovatively applied the method of compositional data forecasting for the prediction of population age changes of the young (aged 0–14), the middle-aged (aged 15–64), and the elderly (aged older than 65) in China, India, and Vietnam by 2030 based on data from 1960 to 2016. To select the best-suited forecasting model, an array of data transformation approaches and forecasting models have been extensively employed, and a large number of comparisons have been made between the aforementioned methods. The best-suited model for each country is identified considering the root mean squared error and mean absolute percent error values from the compositional data. As noted in this study, first and foremost, it is predicted that by the year 2030, China will witness the disappearance of population dividend and get mired in an aging problem far more severe than that of India or Vietnam. Second, Vietnam’s trend of change in population age structure resembles that of China, but the country will sustain its good health as a whole. Finally, the working population of India demonstrates a strong rising trend, indicating that the age structure of the Indian population still remains relatively “young”. Meanwhile, the continuous rise in the proportion of elderly population and the gradual leveling off growth of the young population have nevertheless become serious problems in the world. The present paper attempts to offer crucial insights into the Asian population size, labor market and urbanization, and, moreover, provides suggestions for a sustainable global demographic development. [ABSTRACT FROM AUTHOR]

In this paper, I aim to explore the effect of good governance on equity returns, and empirically investigate if governance at the country level has asset pricing implications and contributes to the idiosyncrasy of price jumps. Jumps are found to be far less systematic than the smooth (non-jump) component of country price indexes. Hence, if jumps are more idiosyncratic, governance should primarily affect the jump risk component. This is good news for international investors, because diversification provides insurance against jumps. Relying on an equilibrium asset-pricing model in an economy under jump diffusion, I decompose the moments of the returns of international stock markets into a diffusive (systematic) risk and a (idiosyncratic) jump risk part. For a balanced panel of 52 countries, my results suggest that governance is an important determinant of (idiosyncratic) jump risk. Stock markets in poorly governed countries are characterized by higher volatility and more negative return asymmetry, primarily driven by the higher jump risk. Regulatory quality, the government effectiveness and the control of corruption appear to be most important. Results are robust to the inclusion of various controls for other country- or market-specific characteristics. [ABSTRACT FROM AUTHOR]

Based on more recent science spending developments in countries such as China, Korea, India and Brazil, there is a growing sense that the world’s scientific deck of cards is in the midst of a major reshuffle. But it is not clear if this reordering is limited to just the top spenders, or, indeed, how these changes have been playing out over the longer term. The new, more comprehensive research and development (R&D) spending estimates presented and discussed here reveal that we are in the midst of a possibly game-changing, albeit partial and perhaps irregular, reshuffle of the global R&D deck. These changes have potentially profound domestic and international economic development implications over the medium to long term. Notably, the fortunes of many of the world’s poorer countries continue to look bleak. Using the evolving structure of past R&D spending to project forward, and absent marked changes in science policies and spending priorities, we foresee a continuing and substantial shift in the geography of R&D towards parts of Asia, along with a continuing large, and in many respects growing, gap between the world’s scientific haves and have-nots. [ABSTRACT FROM AUTHOR]

This study analyzes the core energy consumption among countries’ specific variables by Environmental Kuznets Curve hypothesis (EKC), for a panel data of 29 (14 developed and 15 developing) countries during the period of 1977–2014. By assessing Generalized Method of Moments (GMM) regressions with first generation tests such as common root, individual Augmented Dickey-Fuller (ADF), and individual root-Fisher-PP which have been computed individually, the results confirm the EKC hypothesis in the case of emissions of solid, liquid, gases, manufacturing industries and also construction. Hence, we computed the cointegration test by Pedroni Kao from Engle-Granger based and Fisher. Since the variables are co-integrated, a panel vector error correction model is estimated in GDP per capita, emission from manufacturing industries, arms import, commercial service export, and coal rent, in order to perform Pairwise Granger Causality test and indicate Vector Error Correction (VEC), with co-integration restrictions. Moreover, the statistical finding from VEC short-run unidirectional causality from GDP per capita growth to manufacturing industries and coal rent, as well as the causal link with manufacturing industries and commercial service export. Additionally, there occurred no causal link among economic growth, arm import and coal rent. [ABSTRACT FROM AUTHOR]

Taxation policies can explain the differences in countries' capacity to produce and export more sophisticated products. We develop a theoretical model considering elements from standard models of economic growth to highlight that a country's productive structure is implied by the appropriate fiscal policy that is necessary for the development of sophisticated products. We show that economies that rely less on capital relative to labor taxation tend to produce more complex products, while countries that rely more heavily on capital relative to labor taxation produce simple products. These relationships remain robust across alternative econometric specifications. Furthermore, we demonstrate the differential effect of a country's level of economic development on the nexus between the structure of taxation and economic sophistication. We show that the negative impact of capital taxes on economic sophistication becomes stronger for countries that are more developed. [ABSTRACT FROM AUTHOR]

The accumulation of knowledge required to produce economic value is a process that often relates to nations economic growth. Some decades ago many authors, in the absence of other available indicators, used to rely on certain measures of human capital such as years of schooling, enrollment rates, or literacy. In this paper, we show that the predictive power of years of education as a proxy for human capital started to dwindle in 1990 when the schooling of nations began to be homogenized. We developed a structural equation model that estimates a metric of human capital that is less sensitive than average years of education and remains as a significant predictor of economic growth when tested with both cross-section data and panel data. [ABSTRACT FROM AUTHOR]

As in many nations, air pollution linked to rapid industrialization is a public health and environmental concern in Malaysia, especially in cities. Understanding awareness of air pollution and support for environmental protection from the general public is essential for informing governmental approaches to dealing with this problem. This study presents a cross-sectional survey conducted in the Klang Valley and Iskandar conurbations to examine urban Malaysians’ perception, awareness and opinions of air pollution. The survey was conducted in two languages, English and Malay, and administered through the online survey research software, Qualtrics. The survey consisted of three sections, where we collected sociodemographic information, information on the public perception of air quality and the causes of air pollution, information on public awareness of air pollution and its related impacts, and information on attitudes towards environmental protection. Of 214 respondents, over 60% were positive towards the air quality at both study sites despite the presence of harmful levels of air pollution. The air in the Klang Valley was perceived to be slightly more polluted and causing greater health issues. Overall, the majority of respondents were aware that motor vehicles represent the primary pollution source, yet private transport was still the preferred choice of transportation mode. A generally positive approach towards environmental protection emerged from the data. However, participants showed stronger agreement with protection actions that do not involve individual effort. Nonetheless, we found that certain segments of the sample (people owning more than three vehicles per household and those with relatives who suffered from respiratory diseases) were significantly more willing to personally pay for environmental protection compared to others. Implications point to the need for actions for spreading awareness of air pollution to the overall population, especially with regards to its health risks, as well as strategies for increasing the perception of behavioural control, especially with regards to motor vehicles’ usage. [ABSTRACT FROM AUTHOR]

Connections between interindividual differences and people’s behavior has been widely researched in various contexts, often by using top-down group comparisons to explain interindividual differences. In contrast, in this study, we apply a bottom-up approach in which we identify meaningful clusters in people’s concerns about various areas of life (e.g., their own health, their financial situation, the environment). We apply a novel method, Dirichlet clustering, to large-scale longitudinal data from the German Socioeconomic Panel Study (SOEP) to investigate whether concerns of people living in Germany evaluated in 2010 (t0) cluster participants into robust and separable groups, and whether these groups vary regarding their party identification in 2017 (t0 + 7). Clustering results suggest a range of different groups with specific concern patterns. Some of these notably specific patterns of concerns indicate links to party identification. In particular, some patterns show an increased identification with smaller parties as the ‘Bündnis 90/Die Grünen’ (‘Greens’), the left wing party ‘Die Linke’ (‘The Left’) or the right-wing party ‘Alternative für Deutschland’ (‘Alternative for Germany’, AfD). Considering that we identify as many as 37 clusters in total, among them at least six with clearly different party identification, it can also be concluded that the complexity of political concerns may be larger than has been assumed before. [ABSTRACT FROM AUTHOR]

In this paper, we propose a spatial lag panel smoothing transition regression (SLPSTR) model ty considering spatial correlation of dependent variable in panel smooth transition regression model. This model combines advantages of both smooth transition model and spatial econometric model and can be used to deal with panel data with wide range of heterogeneity and cross-section correlation simultaneously. We also propose a Bayesian estimation approach in which the Metropolis-Hastings algorithm and the method of Gibbs are used for sampling design for SLPSTR model. A simulation study and a real data study are conducted to investigate the performance of the proposed model and the Bayesian estimation approach in practice. The results indicate that our theoretical method is applicable to spatial data with a wide range of spatial structures under finite sample. [ABSTRACT FROM AUTHOR]

The Doha Development Agenda recognizes the central role that international trade can play in the promotion of economic development. In fact, the increase of exports from developing countries to developed nations' markets has been considered a key element for developing countries to realize the potential benefits of globalization. Over the last decades, developed countries have provided preferential access to their markets to developing countries through nonreciprocal trade agreements. Moreover, developing countries have also participated in reciprocal trade agreements. This paper re-examines comparatively the effect of both kinds of trade agreements on exports from developing countries but also from the developed world. In line with other studies, our results across specifications are unstable. However, the results of our preferred specification give additional support to the argument raised by critics of nonreciprocal preference regimes who consider that developing countries should abandon their reliance on one-way trade preferences in favor of reciprocal agreements. [ABSTRACT FROM AUTHOR]

Environmental degradation is causing global warming, which is of the utmost concern to both physical and social scientists. A number of potential determinants of environmental degradation are analysed in the literature. This study examines the role of government expenditure and financial development in environmental degradation in the context of the environmental Kuznets curve (EKC) hypothesis for the Venezuelan economy. Time series data have been analysed for this purpose. The long-term relationship between the variables in this study is established through a bounds test in the presence of an unknown structural break. The results of this study confirm the EKC hypothesis. It is found that energy use is harming the quality of the environment not only in the long run but also in the short run. This study finds a positive impact of government expenditure on environmental degradation, which indicates that the Venezuelan government is not taking its expenditure for a sustainable environment into account. Moreover, this study finds that financial development is hindering environmental degradation. This means that financial institutions in Venezuela can help to develop the concept of sustainable energy in the country and the Venezuelan government can reduce carbon emissions through financial development. [ABSTRACT FROM AUTHOR]

Researchers who analyze data within the framework of null hypothesis significance testing must choose a critical “alpha” level, α, to use as a cutoff for deciding whether a given set of data demonstrates the presence of a particular effect. In most fields, α = 0.05 has traditionally been used as the standard cutoff. Many researchers have recently argued for a change to a more stringent evidence cutoff such as α = 0.01, 0.005, or 0.001, noting that this change would tend to reduce the rate of false positives, which are of growing concern in many research areas. Other researchers oppose this proposed change, however, because it would correspondingly tend to increase the rate of false negatives. We show how a simple statistical model can be used to explore the quantitative tradeoff between reducing false positives and increasing false negatives. In particular, the model shows how the optimal α level depends on numerous characteristics of the research area, and it reveals that although α = 0.05 would indeed be approximately the optimal value in some realistic situations, the optimal α could actually be substantially larger or smaller in other situations. The importance of the model lies in making it clear what characteristics of the research area have to be specified to make a principled argument for using one α level rather than another, and the model thereby provides a blueprint for researchers seeking to justify a particular α level. [ABSTRACT FROM AUTHOR]

Objective: Empirical research that cannot be reproduced using the original dataset and software code (replication files) creates a credibility challenge, as it means those published findings are not verifiable. This study reports the results of a research audit exercise, known as the push button replication project, that tested a sample of studies that use similar empirical methods but span a variety of academic fields. Methods: We developed and piloted a detailed protocol for conducting push button replication and determining the level of comparability of these replication findings to original findings. We drew a sample of articles from the ten journals that published the most impact evaluations from low- and middle-income countries from 2010 through 2012. This set includes health, economics, and development journals. We then selected all articles in these journals published in 2014 that meet the same inclusion criteria and implemented the protocol on the sample. Results: Of the 109 articles in our sample, only 27 are push button replicable, meaning the provided code run on the provided dataset produces comparable findings for the key results in the published article. The authors of 59 of the articles refused to provide replication files. Thirty of these 59 articles were published in journals that had replication file requirements in 2014, meaning these articles are non-compliant with their journal requirements. For the remaining 23 of the 109 articles, we confirmed that three had proprietary data, we received incomplete replication files for 15, and we found minor differences in the replication results for five. Conclusion: The findings presented here reveal that many economics, development, and public health researchers are a long way from adopting the norm of open research. Journals do not appear to be playing a strong role in ensuring the availability of replication files. [ABSTRACT FROM AUTHOR]

Understanding the relationship between carbon dioxide (CO2) emissions and the urbanization of national populations has been a key concern for environmental scholars for several decades. Although sophisticated modeling techniques have been developed to explore the connection between increases in urban populations and CO2 emissions, none has attempted to assess whether declines in urbanization have an effect on emissions that is not symmetrical with that of growth in urbanization. The present study uses panel data on CO2 emissions and the percentage of individuals living in urban areas, as well as a variety of other structural factors, for less-developed countries from 1960–2010, to empirically assess whether the effect of growth in urban populations on emissions is symmetrical with the effect of decline. Findings indicate that the effect of growth/decline in urban populations on CO2 emissions is asymmetrical, where a decline in urbanization reduces emissions to a much greater degree than urbanization increases emissions. We hypothesize that this is at least in part because deurbanization is connected with disruptions to the production and distribution of goods and services and/or access to electricity and other energy sources. Our finding suggests that not only the absolute level of urbanization of nations matters for emissions, but also how the patterns of migration between rural and urban areas change over time. Future research should be mindful of the processes behind deurbanization when exploring socioeconomic drivers of CO2 emissions. [ABSTRACT FROM AUTHOR]

Objectives: This study calculates cigarette affordability for 78 countries worldwide from 2001 to 2014 using the Relative Income Price (RIP) ratio defined as the percentage of per capita GDP required to purchase 100 packs of cigarettes using the lowest price from Economist Intelligence Unit (EIU) database, examine the association between cigarette affordability and cigarette consumption, and calculate the affordability elasticity of demand. Design and methods: RIP (2001–2014) was calculated for 16 low-income economies, 19 lower middle-income economies, 13 upper middle-income economies, and 30 high-income economies. Ordinary least square regressions were used to analyze the association between cigarette affordability and consumption. Results: Per capita consumption continued to rise in low-income countries and decreased slightly in lower middle-income countries as the RIP of cigarette consistently declined in low- and lower middle-income economies from 2001 to 2014. The real cigarette prices continued to decline in low- and lower middle-income countries and continued to rise in upper middle- and high-income countries. Though cigarettes were more expensive in HICs than were in LMICs, cigarettes were more affordable in HICs than were in LMICs. The regression results show a 10% increase in the RIP of cigarettes led to a 2% decrease in per capita consumption. The affordability elasticity of demand differed significantly between HICs and LMICs. However, the effect of cigarette affordability on consumption has not changed over time. Conclusions: To control the smoking epidemic, low- and lower middle-income countries should further increase cigarette prices. The rate of price increase should exceed the rate of economic growth and outpace the inflation rate to make cigarettes less affordable and thereby reducing tobacco use. [ABSTRACT FROM AUTHOR]

The energy consumption-growth nexus has been widely studied in the empirical literature, though results have been inconclusive regarding the direction, or even the existence, of causality. These inconsistent results can be explained by two important limitations of the literature. First, the use of bivariate models, which fail to detect more complex causal relations, or the ad hoc approach to selecting variables in a multivariate framework; and, second, the use of linear causal models, which are unable to capture more complex nonlinear causal relationships. In this paper, we aim to overcome both limitations by analysing the energy consumption-growth nexus using a Flexible Fourier form due to Enders and Jones (2016). The analysis focuses on the US over the period 1949 to 2014. From our results we can conclude that, where the linear methodology supports the neutrality hypothesis (no causality between energy consumption and growth), the Flexible Fourier form points to the existence of causality from energy consumption to growth. This is contrary to the linear analysis, suggesting that lowering energy consumption would adversely affect US economic growth. Thus, by employing the Flexible Fourier form we find the conclusions can be quite different. [ABSTRACT FROM AUTHOR]

Introduction: Both the preventive and curative healthcare provisions accumulate agents’ health stock and stimulate economies’ productivities. However, with limited medical resources, increases in preventive health expenditure crowd out curative expenditure, and vice versa, which in turn impairs the population’s health and deters economic growth. This research aims to provide a empirically rigorous test on the hypothesis that optimally allocating health expenditure between prevention and cures stimulates economic growth within different countries, especially developed countries, and investigates whether health services are luxury goods on the path of economic development. Methods: Based on OECD country experiences, this present study uses the system generalized method of moments (GMM) estimation method to examine the roles of preventive and curative healthcare services over the path of economic development and proves that preventive and curative health spending have non-linear effects on economic performance. Results: For growth maximization, the optimal share of preventive health expenditure to GDP is 0.44% with per capita GDP at US$40,465; the real share is 0.25% with per capita GDP at US$35,230. The optimal share of curative health expenditure to GDP is 10.96% with per capita GDP at US$41,816; the real share is 8.26% with per capita GDP at US$35,230. Accordingly, the estimated optimal provision of health services are currently underprovided. This research further estimates the effects of income on demand for care and shows that the income elasticities of preventive and curative health care are greater than unity. Health services are luxury goods. Conclusions: Economies with higher incomes demand such services more than those with lower incomes. The large positive effects of income on preventive care use exist. [ABSTRACT FROM AUTHOR]

This paper re-examines health-growth relationship using an unbalanced panel of 17 advanced economies for the period 1870–2013 and employs panel generalised method of moments estimator that takes care of endogeneity issues, which arise due to reverse causality. We utilise macroeconomic data corresponding to inflation, government expenditure, trade and schooling in sample countries that takes care of omitted variable bias in growth regression. With alternate model specifications, we show that population health proxied by life expectancy exert a positive and significant effect on both real income per capita as well as growth. Our results are in conformity with the existing empirical evidence on the relationship between health and economic growth, they, however, are more robust due to the presence of long-term data, appropriate econometric procedure and alternate model specifications. We also show a strong role of endogeneity in driving standard results in growth empirics. In addition to life expectancy, other constituent of human capital, education proxied by schooling is also positively associated with real per capita income. Policy implication that follows from this paper is that per capita income can be boosted through focussed policy attention on population health. The results, however, posit differing policy implications for advanced and developing economies. [ABSTRACT FROM AUTHOR]

The new European model stipulates the achievement of an inclusive, sustainable and intelligent economic growth. Increasing the share of renewable energy is one of the factors that improve the quality of economic growth, similar to research, development and investment in human capital. In this paper we tested the correlation between economic growth and renewable energy consumption for ten European Union (EU) member states from Central and Eastern Europe (CEE) in the period 1990–2014, using Auto-regressive and Distributed Lag (ARDL) modeling procedure, a technique that captures causal relationships both on a short run and on a long run. The short run perspective reveals the transition towards a new energy paradigm, while the long run approach corresponds to the long-term equilibrium of the analyzed factors. Our results shows that, in the short run, the Gross Domestic Product (GDP) and Renewable Energy Consumption (REC) dynamics are independent in Romania and Bulgaria, while in Hungary, Lithuania and Slovenia an increasing renewable energy consumption improves the economic growth. The hypothesis of bi-directional causality between renewable energy consumption and economic growth is validated in the long run for both the whole group of analyzed countries as well as in the case of seven CEE states which were studied individually. These results allow us to look into the feasibility of the Europe 2020 goals regarding the increase of energy efficiency and to propose public policies to achieve these goals. [ABSTRACT FROM AUTHOR]

The global trade system can be viewed as a dynamic ecosystem in which exporters struggle for resources: the markets in which they export. We can think that the aim of an exporter is to gain the entirety of a market share (say, car imports from the United States). This is similar to the objective of an organism in its attempt to monopolize a given subset of resources in an ecosystem. In this paper, we adopt a multilayer network approach to describe this struggle. We use longitudinal, multiplex data on trade relations, spanning several decades. We connect two countries with a directed link if the source country’s appearance in a market correlates with the target country’s disappearing, where a market is defined as a country-product combination in a given decade. Each market is a layer in the network. We show that, by analyzing the countries’ network roles in each layer, we are able to classify them as out-competing, transitioning or displaced. This classification is a meaningful one: when testing the future export patterns of these countries, we show that out-competing countries have distinctly stronger growth rates than the other two classes. [ABSTRACT FROM AUTHOR]

Massive Open Online Courses (MOOCs) have the potential to democratize education by providing learners with access to high-quality free online courses. However, evidence supporting this democratization across countries is limited. We explored the question of MOOC democratization by conducting cross-national comparisons of gender differences in the enrollment in and completion of science, technology, engineering, and mathematics (STEM) MOOCs. We found that while females were less likely than males to enroll in STEM MOOCs, they were equally likely to complete them. Further, a higher probability to enroll in STEM MOOCs and smaller gender gaps in STEM MOOC enrollment and completion were found in less gender-equal and less economically developed countries. [ABSTRACT FROM AUTHOR]

In this paper, we revisit the relationship between housing prices and consumption in China by using a continuous wavelet analysis. This method provides an insight into the dynamic nexus in both time and frequency domains. In general, Empirical results show that there is a positive relationship between the two series in China, although it varies across time and frequencies. First, we find that disposable income is the core factor which affects both consumption and housing prices in China. Second, housing prices have a weak wealth effect on consumption in most time. High housing ownership and proportion of housing asset in the total household asset lead to a wealth effect of housing prices on consumption. Third, in the long term, there is a significant wealth effect of housing prices on consumption, but it weakens after 2008, which implies that excessively high housing prices in recent years have partially constrained residents’ consumption. These findings have important implications for seeking housing market regulation and expanding domestic consumption decisions. [ABSTRACT FROM AUTHOR]

Nighttime lights, calculated from weather satellite recordings, are increasingly used by social scientists as a proxy for economic activity or economic development in subnational regions of developing countries where disaggregated data from statistical offices are not available. However, so far, our understanding of what nighttime lights capture in these countries is limited. We use geo-referenced Demographic and Health Surveys (DHS) from 29 African countries to construct indicators of household wealth, education and health for DHS cluster locations as well as for grid cells of roughly 50 × 50 km. We show that nighttime lights are positively associated with these location-specific indicators of human development, and that the variation in nighttime lights can explain a substantial share in the variation in these indicators. We conclude that nighttime lights are a good proxy for human development at the local level. [ABSTRACT FROM AUTHOR]

Family Health Strategy, the primary health care program in Brazil, has been scaled up throughout the country, but its expansion has been heterogeneous across municipalities. We investigate if there are unique municipal characteristics that can explain the timing of uptake and the pattern of expansion of the Family Health Strategy from years 1998 to 2012. We categorized municipalities in six groups based on the relative speed of the Family Health Strategy uptake and the pattern of Family Health Strategy coverage expansion. We assembled data for 11 indicators for years 2000 and 2010, for 5,507 municipalities, and assessed differences in indicators across the six groups, which we mapped to examine spatial heterogeneities. Important factors differentiating early and late adopters of the Family Health Strategy were supply of doctors and population density. Sustained coverage expansion was related mainly to population size, marginal benefits of the program and doctors’ supply. The uptake was widespread nationwide with no distinct patterns among regions, but highly heterogeneous at the state and municipal level. The Brazilian experience of expanding primary health care offers three lessons in relation to factors influencing diffusion of primary health care. First, the funding mechanism is critical for program implementation, and must be accompanied by ways to support the supply of primary care physicians in low density areas. Second, in more developed and bigger areas the main challenge is lack of incentives to pursue universal coverage, especially due to the availability of private insurance. Third, population size is a crucial element to guarantee coverage sustainability over time. [ABSTRACT FROM AUTHOR]

Economic complexity reflects the amount of knowledge that is embedded in the productive structure of an economy. It resides on the premise of hidden capabilities—fundamental endowments underlying the productive structure. In general, measuring the capabilities behind economic complexity directly is difficult, and indirect measures have been suggested which exploit the fact that the presence of the capabilities is expressed in a country’s mix of products. We complement these studies by introducing a probabilistic framework which leverages Bayesian non-parametric techniques to extract the dominant features behind the comparative advantage in exported products. Based on economic evidence and trade data, we place a restricted Indian Buffet Process on the distribution of countries’ capability endowment, appealing to a culinary metaphor to model the process of capability acquisition. The approach comes with a unique level of interpretability, as it produces a concise and economically plausible description of the instantiated capabilities. [ABSTRACT FROM AUTHOR]

A debt-based economy cannot survive without economic growth. However, if private debt consistently grows faster than GDP, the consequences are financial crises and the current unprecedented level of global debt. This policy dilemma is aggravated by the lack of analyses factoring the impact of debt-growth cycles on the environment. What is really the relationship between debt and natural resource sustainability, and what is the role of debt in decoupling economic growth from natural resource availability? Here we present a conceptual Agent-Based Model (ABM) that integrates an environmental system into an ABM representation of Steve Keen’s debt-based economic models. Our model explores the extent to which debt-driven processes, within debt-based economies, enhance the decoupling between economic growth and the availability of natural resources. Interestingly, environmental and economic collapse in our model are not caused by debt growth, or the debt-based nature of the economic system itself (i.e. the ‘what’), but rather, these are due to the inappropriate use of debt by private actors (i.e. the ‘how’). Firms inappropriately use bank credits for speculative goals–rather than production-oriented ones–and for exponentially increasing rates of technological development. This context creates temporal mismatches between natural resource growth and firms’ resource extraction rates, as well as between economic growth and the capacity of the government to effectively implement natural resource conservation policies. This paper discusses the extent to which economic growth and the availability of natural resources can be re-coupled through a more sustainable use of debt, for instance by shifting mainstream banking forces to partially support environmental conservation as well as economic growth. [ABSTRACT FROM AUTHOR]

Manufacturing in China has developed rapidly with the widening and deepening of globalization, but only innovation can industry keep upgrading and enhancing its international competitiveness. This paper combines Global Value Chains (GVCs) and National Value Chains (NVCs) in a unified theory framework, uses Structural Decomposition Analysis (SDA) to explore how innovation capacity, production capacity, and vertical specialization affect innovation performance from the supply and demand sides by examining the case of Electronic Manufacturing of China. We observe that innovation inputs and outputs present strong regional heterogeneity between coastal and inland regions. Although most regions continue to engage in processing trade or assembly manufacturing in GVCs, NVCs are gradually established and led by coastal regions. The results indicate a good chance for cultivating innovation capacity in coastal regions. After assessing the influence of determinants on innovation performance, we observe that from supply-side, innovation capacity has a positive effect on innovation performance, production capacity in coastal regions is improving, and domestic demand for domestic products is increasingly important. From the demand side, innovation capacity continues to have a positive effect on innovation performance, production capacity improves rapidly, and imported intermediate inputs enhance innovation performance more effectively than domestic intermediate inputs. [ABSTRACT FROM AUTHOR]

The present study investigated the relationship between level of education and liberalization values in large, representative samples administered in 96 countries around the world (total N = 139,991). These countries show meaningful variation in terms of the Human Development Index (HDI), ranging from very poor, developing countries to prosperous, developed countries. We found evidence of cross-level interactions, consistently showing that individuals’ level of education was associated with an increase in their liberalization values in higher HDI societies, whereas this relationship was curbed in lower HDI countries. This enhanced liberalization mindset of individuals in high HDI countries, in turn, was related to better scores on national indices of innovation. We conclude that this ‘education amplification effect’ widens the gap between lower and higher HDI countries in terms of liberalized mentality and economic growth potential. Policy implications for how low HDI countries can counter this gap are discussed. [ABSTRACT FROM AUTHOR]

Over the last few decades, public life has taken center stage in urban studies, but that is about to change. At times, indoor activities have been shown to matter more than what is publicly visible (they have been found to be more predictive of future crimes, for example). Until recently, however, data has not been available to study indoor activities at city scale. To that end, we propose a new methodology that relies on tagging information of geo-referenced pictures and unfolds in three main steps. First, we collected and classified a comprehensive set of activity-related words, creating the first dictionary of urban activities. Second, for both London and New York City, we collected geo-referenced Flickr tags and matched them with the words in the dictionary. This step produced both a systematic classification (our activity-related words were best classified in eleven categories) and two city-wide indoor activity maps which, when compared to open data of public amenities and sensory maps of smell and sound matched theoretical expectations. Third, we studied, for the first time, activities happening indoor in relation to neighborhood socio-economic conditions. We found the very same result for both London and New York City. In deprived areas, people focused on any of the activity types (leading to specialization), and it did not matter on which one they did so. By contrast, in well-to-do areas, people engaged not in one type of activity but in a variety of them (leading to diversification). [ABSTRACT FROM AUTHOR]

The energy-growth nexus has important policy implications for economic development. The results from many past studies that investigated the causality direction of this nexus can lead to misleading policy guidance. Using data on China from 1953 to 2013, this study shows that an application of causality test on the time series of energy consumption and national output has masked a lot of information. The Toda-Yamamoto test with bootstrapped critical values and the newly proposed non-linear causality test reveal no causal relationship. However, a further application of these tests using series in different time-frequency domain obtained from wavelet decomposition indicates that while energy consumption Granger causes economic growth in the short run, the reverse is true in the medium term. A bidirectional causal relationship is found for the long run. This approach has proven to be superior in unveiling information on the energy-growth nexus that are useful for policy planning over different time horizons. [ABSTRACT FROM AUTHOR]

This study examines the Environmental Kuznets Curve hypothesis (EKC), considering the primary energy consumption among other country-specific variables, for a panel of the EU-28 countries during the period 1990–2014. By estimating pooled OLS regressions with Driscoll-Kraay standard errors in order to account for cross-sectional dependence, the results confirm the EKC hypothesis in the case of emissions of sulfur oxides and emissions of non-methane volatile organic compounds. In addition to pooled estimations, the output of fixed-effects regressions with Driscoll-Kraay standard errors support the EKC hypothesis for greenhouse gas emissions, greenhouse gas emissions intensity of energy consumption, emissions of nitrogen oxides, emissions of non-methane volatile organic compounds and emissions of ammonia. Additionally, the empirical findings from panel vector error correction model reveal a short-run unidirectional causality from GDP per capita growth to greenhouse gas emissions, as well as a bidirectional causal link between primary energy consumption and greenhouse gas emissions. Furthermore, since there occurred no causal link between economic growth and primary energy consumption, the neo-classical view was confirmed, namely the neutrality hypothesis. [ABSTRACT FROM AUTHOR]

Research on temporal characteristics of human dynamics has attracted much attentions for its contribution to various areas such as communication, medical treatment, finance, etc. Existing studies show that the time intervals between two consecutive events present different non-Poisson characteristics, such as power-law, Pareto, bimodal distribution of power-law, exponential distribution, piecewise power-law, et al. With the occurrences of new services, new types of distributions may arise. In this paper, we study the distributions of the time intervals between two consecutive visits to QQ and WeChat service, the top two popular instant messaging services in China, and present a new finding that when the value of statistical unit T is set to 0.001s, the inter-event time distribution follows a piecewise distribution of exponential and power-law, indicating the heterogeneous character of IM services users’ online behavior in different time scales. We infer that the heterogeneous character is related to the communication mechanism of IM and the habits of users. Then we develop a combination model of exponential model and interest model to characterize the heterogeneity. Furthermore, we find that the exponent of the inter-event time distribution of the same service is different in two cities, which is correlated with the popularity of the services. Our research is useful for the application of information diffusion, prediction of economic development of cities, and so on. [ABSTRACT FROM AUTHOR]

Coastal risks are increasing from both development and climate change. Interest is growing in the protective role that coastal nature-based measures (or green infrastructure), such as reefs and wetlands, can play in adapting to these risks. However, a lack of quantitative information on their relative costs and benefits is one principal factor limiting their use more broadly. Here, we apply a quantitative risk assessment framework to assess coastal flood risk (from climate change and economic exposure growth) across the United States Gulf of Mexico coast to compare the cost effectiveness of different adaptation measures. These include nature-based (e.g. oyster reef restoration), structural or grey (e.g., seawalls) and policy measures (e.g. home elevation). We first find that coastal development will be a critical driver of risk, particularly for major disasters, but climate change will cause more recurrent losses through changes in storms and relative sea level rise. By 2030, flooding will cost $134–176.6 billion (for different economic growth scenarios), but as the effects of climate change, land subsidence and concentration of assets in the coastal zone increase, annualized risk will more than double by 2050 with respect to 2030. However, from the portfolio we studied, the set of cost-effective adaptation measures (with benefit to cost ratios above 1) could prevent up to $57–101 billion in losses, which represents 42.8–57.2% of the total risk. Nature-based adaptation options could avert more than $50 billion of these costs, and do so cost effectively with average benefit to cost ratios above 3.5. Wetland and oyster reef restoration are found to be particularly cost-effective. This study demonstrates that the cost effectiveness of nature-based, grey and policy measures can be compared quantitatively with one another, and that the cost effectiveness of adaptation becomes more attractive as climate change and coastal development intensifies in the future. It also shows that investments in nature-based adaptation could meet multiple objectives for environmental restoration, adaptation and flood risk reduction. [ABSTRACT FROM AUTHOR]

In recent years, entrepreneurship has been gaining more prominence as a potential tool for solving poverty in developing countries. This paper mainly examines the relationship between farmer entrepreneurship and rural poverty alleviation in China by assessing the contribution of farm entrepreneurs towards overcoming poverty. Data were collected from 309 employees of farmer entrepreneurships in Guangxi Province through survey questionnaires. Structural equation modeling was used to conduct an analysis of the effects of three identified capabilities of farm entrepreneurs—economic, educational and knowledge, and socio-cultural capabilities—on attitude towards farmer entrepreneurship growth and the qualitative growth of farmer entrepreneurship and how these in turn affect rural poverty, using AMOS 21. The findings show that socio-cultural capability has the greatest influence on farmer entrepreneurship growth (β = 0.50, p<0.001). The qualitative growth of farmer entrepreneurship also more significantly impacts rural poverty (β = 0.69, p<0.001) than attitude towards farmer entrepreneurship growth. This study suggests that policy makers in China should involve more rural farmers in the targeted poverty alleviation strategies of the government by equipping rural farmers with entrepreneurial skills. This can serve as a sustainable, bottom-up approach to alleviating rural poverty in remote areas of the country. The study also extends the literature on the farmer entrepreneurship-rural poverty alleviation nexus in China, and this can serve as a lesson for other developing countries in the fight against rural poverty. [ABSTRACT FROM AUTHOR]