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This article aims to analyze the effect of Customer Relationship Management on reducing adverse selection within microfinance institutions in Cameroon. This analysis is made possible through the implementation of a questionnaire survey. Carried out on a sample of 522 microfinance clients in the cities of Douala Yaoundé and Bafoussam, the resulting descriptive statistics make it possible to measure the different variables. Data processing carried out using SPSS, which, once the variables have been estimated, facilitates the design of an econometric model using bivariate probit multiple regression. The results of the study indicate that a quality welcome and personalized support have effects on reducing adverse selection. Based on these results, we can recommend that marketing managers in MFIs rely on the future value of the customer at each stage of the customer life cycle in the customer acquisition and retention phases, in order to target the right customers, and therefore reduce adverse selection. [ABSTRACT FROM AUTHOR]

Copyright of Revista Espacios is the property of Talleres de Impresos Oma and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transformations in Business & Economics is the property of Vilnius University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A simple econometric model predicting the effects of key drivers of climate change on the real GDP is constructed. It shows quantitatively how GDP is affected by carbon dioxide emissions and energy produced from renewable sources (excluding hydroelectricity). Moreover, the model also demonstrates that increasing energy consumption using fossil fuels at the expense of renewable sources negatively impacts GDP. [ABSTRACT FROM AUTHOR]

Energy security and international competitiveness are two of the most fiercely discussed topics – especially in the light of the European Union (EU)'s dependence on Russia's gas, oil, and coal. Both mentioned concepts are of special importance for the so-called EU new member states (EU NMS), which are undergoing the energy diversification process. The main goal of this paper is to analyze how energy security influences the international competitiveness of these countries. The study uses trade theories related to productivity differentials (Ricardian hypothesis) and differences in factor endowments (Heckscher–Ohlin hypothesis) as a basis for our econometric modeling. The results show that relative energy supply as well as physical and human capital relative endowments have a statistically significant impact on international competitiveness of the studied economies. [ABSTRACT FROM AUTHOR]

This editorial summarises the papers in issue 18(3) (2023). The first article examines the balloon effect, the shift of production of illicit crops to other areas upon regulatory enforcement. The second paper tests for the existence of innovation spillover effects on firm survival. The third paper analyses the impact of lockdown policy measures on the daily use of mobile phone broadband through a quasi-experimental econometric model with 15 different treatment dummies. The fourth paper examines to what extent the economic effect of lockdowns in different regions and countries interact with each other and the extent to which policy coordination of these interactions influences the overall economic effect. The fifth and sixth papers develop spatial extensions of the autoregressive conditional heteroskedasticity model (ARCH) to explain US house price returns. [ABSTRACT FROM AUTHOR]

One explanation for the increasing number of hectares of coca is that eradication strategies displace coca crops but fail to completely clear affected areas. In the drug policy literature, that dynamic shifting is commonly known as the balloon effect. This study integrates georeferenced agricultural data through spatially explicit econometric models to test the hypothesis that forced eradication displaces coca crops. Using annual data for 1116 contiguous municipalities in Colombia, we estimate a spatial Durbin error model. Our results suggest that, on average, aerial fumigation in a municipality diffuses the benefits of this crime control strategy to neighbouring municipalities. [ABSTRACT FROM AUTHOR]

In his article published in JHET in 2022, Vincent Carret (2022a) criticizes our work. In footnote 19, pages 630–631, he claims that our result "is based on a mistaken interpretation of the paragraph at the bottom of p. 191 of Frisch (1933)." He then states that we "take to mean that the coefficient of each cycle in the general sum of solutions is arbitrary, while ... these coefficients [depended] on initial conditions and the parameters of the system." The present rejoinder aims at rebutting Carret's allegation of mistaken interpretation in our work. We demonstrate that his statements are based on a misunderstanding of Frisch's econometric model and approach. Then, we show that Carret's results are not supported by the demonstration he claims to have made, and that he misrepresents our arguments. [ABSTRACT FROM AUTHOR]

Urbanization, national economic growth, and China's changing population structure have elevated the importance of real estate assessment in various contexts, including mortgage financing, secondary housing market transactions, and real estate tax reform. To address this need, this study employs a time-spatial double-fixed spatial cross-section data model as a mass appraisal tool to analyze the transaction price data of 429 ordinary residential houses in Xixia District, Yinchuan, China on April 1, 2022. Specifically, this study analyzes 7 spatial cross-section data models, discerning their interconnections. It devises an assignment technique that merges distance and characteristic variable rank into a unified indicator. The results explore spatial lag effects in real estate transaction price generation and assess the descriptive capabilities of different spatial cross-section data models. [ABSTRACT FROM AUTHOR]

Prioritizing health technologies requires comparisons of improvements in longevity or quality of life (QoL), or both. For this purpose, value sets are constructed that contain weights assigned to health states based on societal preferences. I show that how this is typically done may distort the results by giving unjustifiably larger impact to individuals who prioritize improvements in QoL over longevity. The problem results from equating the utility differences between being dead and full health across people, ignoring the fact that interpersonal utility comparisons are forbidden (or at least problematic) in economics. I propose another approach: the numerical value of maximal health gain (either in longevity or QoL) is assumed to be equal across individuals, to remove the impact of the range of utilities differing between people. I test this approach using EQ-5D-5L and EQ-5D-3L utilities elicited in Poland for two modeling techniques: a simple econometric model and a Bayesian one that accounts for censoring. The proposed approach increases the utilities of the worst health state: from - 0.41 to - 0.25 in EQ-5D-5L and from about - 0.54 to - 0.36 in EQ-5D-3L. In the Bayesian approach, the impact is greater: from - 0.45 to - 0.11 for EQ-5D-5L and from - 0.54 to - 0.22 for EQ-5D-3L. I discuss some normative arguments why the proposed approach may be more justifiable for aggregating individual preferences for health outcomes. [ABSTRACT FROM AUTHOR]

This paper investigates the economic development within the Guangdong-Hong Kong-Macao Greater Bay Area from two perspectives--spatial pattern and influencing factors--to promote coordinated development across the area. This paper employs Moran's I test and local Getis-Ord G statistic from spatial statistics. Furthermore, it constructs a hierarchical spatial econometric model to facilitate empirical investigation. It is found that the overall economic development of the Guangdong-Hong Kong-Macao Greater Bay Area exhibits a "mountain-shaped" spatial pattern of the high-level homogeneous regions with "high-high correlation" and the low-level homogeneous regions with "low-low correlation." The internal difference in economic density is moderate, with an obvious trend of decrease year by year. Economic density shows a significant spatial positive correlation, with the expansion of the scope of areas exhibiting "high-high correlation." The differences in economic density between hotspots and sub-hotspots have decreased, but the economic density of cold spots has failed to keep up with the development of other regions. The difference in factor input density among the influencing factors explains most of the differences in economic density among different regions. The results from the R&D capital investment coefficient indicate that in recent years, the effect of investments in urban scientific and technological innovation factors has been more extensive and uniform among the regions under its jurisdiction, but the spatial spillover effect of innovation factors at both layers is not significantly positive. Apart from the city's location within the Greater Bay Area, the relative location of the jurisdictions within the city equally influences the economic development configuration of the Greater Bay Area. Although economic density in regions adjacent to cities outside the Greater Bay Area is notably lower than in other regions, their growth rate and production efficiency remain on par with other regions. T-test and model results underscore the rapid development of the areas encircling the bay. The coefficient of location dummy variables in areas adjacent to cities in the Greater Bay Area varies among cities. At a particular factor input density, some cities have higher output efficiency in areas contiguous to cities in the Greater Bay Area. This study uniquely adopts low-level city jurisdictions and high-level cities to shape a two-tiered hierarchical dataset with nested geographic units. This innovative approach fully leverages insights from distinct layers, delving into spatial interdependence and interplay across layers. This paper aims to explore the spatial pattern and influencing factors steering economic development in the Guangdong-Hong Kong-Macao Greater Bay Area. In doing so, it aims to identify problems and present pertinent policy recommendations. [ABSTRACT FROM AUTHOR]

This paper measures the Green Total Factor Productivity (GTFP) of 279 cities in China from 2011 to 2018 based on the Global Malmquist-Luenberger (GML) index and Slacks-based Measure Directional Distance Function (SBM-DDF) method. Through different spatial econometric models, we empirically analyse the spatial convergence of the GTFP and the spatial effect of Digital Inclusive Finance (DIF) on the GTFP convergence. The results show no spatial σ convergence in the GTFP in the Total, Central, Eastern, and Western regions of China, while the gap in green development is the largest in western cities and most balanced among central cities. In China's three regions, absolute spatial β convergence, conditional spatial β convergence, and spatial club convergence exist. The DIF can promote the spatial convergence of the GTFP, and the promotion effect is more significant in the Western than in the Eastern and Central regions. The findings are important for narrowing the regional GTFP gap and promoting regional economic synergistic development. [ABSTRACT FROM AUTHOR]

At present, the rapid development of digital finance is closely related to the economic development of urban agglomerations. An urban agglomeration provides conditions for digital finance to form a spatial relevancy network. Exploring the development of digital finance in the urban agglomeration of the Pearl River Delta (PRD), which is the bellwether of China's economy, can provide important practical experience for the economic construction of coastal areas and even the whole country. In this study, using the urban digital finance index issued by the Guangzhou Institute of International Finance, we measured the intensity and direction of the spatial relevancy of digital finance in the PRD urban agglomeration by applying the gravity model, modified in the calculation of distance between cities. Then, we examined the influencing factors of the spatial network of digital finance through the quadratic assignment procedure (QAP) approach. The achieved results are as follows. First, although the overall density is low, the network is tightly connected and stable. Second, in terms of individual characteristics of the network, Guangzhou, Shenzhen, Foshan still play the leading roles in the spatial network of digital finance. Third, the digital finance network does not have bidirectional spillover block. The links between segments are relatively loose. Fourth, economic level, degree of opening up, Internet level and geographical location are important factors in driving the formation of spatial relevancy of digital finance in the PRD urban agglomeration. [ABSTRACT FROM AUTHOR]

En este estudio se propone utilizar las áreas monetarias óptimas como base teórica para el análisis de la plena dolarización en el Ecuador, considerando al país y a los Estados Unidos como una unión monetaria informal. Se examinan i) las propiedades de convergencia de las tasas de inflación entre el Ecuador y los Estados Unidos (mediante el uso de pruebas de raíces unitarias y de estacionariedad) y ii) el grado de vulnerabilidad de la economía ecuatoriana a los cambios en la política monetaria de los Estados Unidos (mediante modelos estructurales de vectores autorregresivos). Los resultados indican que las tasas de inflación convergen ex post, tras la dolarización plena del Ecuador, y que, por tanto, los cambios de política monetaria de los Estados Unidos afectan las variables macroeconómicas ecuatorianas. Además, se sostiene que la teoría de las áreas monetarias óptimas puede ser útil para estudiar las economías totalmente dolarizadas. [ABSTRACT FROM AUTHOR]

Chile and Korea subscribed a free trade agreement in 2003, which entered into force in 2004. One of the main objectives behind the agreement was to modify the concentration of the Chilean export basket, traditionally dominated by primary products, through preferential access to the country's main export destinations. From here, this paper analyses the achievement of this objective through mixed-methods. Acknowledging that econometric models may not fully explain trade patterns, this article uses both quantitative data to understand the impact of the agreement on export flows, and qualitative information to complement these results. It concludes that Chile has not been capable of achieving the objective stated, due to constrains in the public and private sector. [ABSTRACT FROM AUTHOR]

Understanding children's mobility behaviour and parents escorting practices are important to developing a children-friendly society. But only a few studies concerning children's mobility behaviour have focused on developing countries. In this study, we attempted to develop an econometric model to understand escorting practices in a developing country. A multinomial logit (MNL) model is developed using travel diary data of 398 elementary school-going children, inhabiting in Chattogram City Corporation (CCC) area of Bangladesh. We have considered different combinations of environmental (both school and neighbourhood environment), socio-cultural, household, and personal factors to explain children's independent mobility behaviour for both school and discretionary trip purposes. The findings suggested that children's individual (e.g. education level) and parents' sociodemographic (e.g. income, access to cars, mother's education level) facilities available at school, and built-environmental factors (e.g. commercial density, road density, land use mix and proximity to open spaces) are significantly associated with parent's choice for chauffeuring their children in CCC area. Results will be useful to planners and policy makers for formulating effective measures to promote children's independent mobility and will be a guideline for urban planners to include children's mobility demand for the neighbourhood as well as city design. [ABSTRACT FROM AUTHOR]

This article aims at finding a relationship between the degree of fiscalism and innovation in eleven countries in Central and Eastern Europe (CEE). The article uses clustering algorithms to divide countries into groups, with the most similar features in a multidimensional space generated by values of adopted indices, irrespective of fiscalism and innovation. Econometric modelling based on panel data was used to identify directions and the strength of the relationship between different variables. The article finds that fiscalism and innovation performance are closely interrelated. The article uses selected (limited) indices to exhibit the relation between fiscalism and innovation. The impact of tax competition may be used to give a broader perspective on this relation. The implication for the public policy is that high value of tax-to-GDP (gross domestic product) coexists with low labour costs and entrepreneurs' attitude to investment in innovation. It is among the first articles to exhibit a relation between innovation and fiscalism in the CEE countries. In addition, the article uniquely uses clustering methods combined with the econometric panel model. [ABSTRACT FROM AUTHOR]

Promoting the agricultural sustainable development is one of the core objectives of agricultural comprehensive development (ACD), and the core of agricultural sustainable development lies in enhancing agro-ecological efficiency (AEE). Based on inter-provincial panel data from 2003-2017, the AEE was measured by a unexpected super-efficient SBM model. From the perspective of investment scale and investment structure, the impact of investment scale in ACD on AEE was examined using a panel econometric model, then characterizing the investment structure by the proportion of government funds in the investment of ACD, examining the non-linear relationship between investment structure of ACD and AEE seeking a reasonable proportion of government expenditure. Finally, a spatial econometric model was constructed to test the spatial spillover effect of the scale and structure of investment in ACD on AEE. Results showed that: (i) AEE of China is on the rise overall, but the efficiency level is still low and there is large scope for improvement. (ii) Due to the inefficient use of funds and the lag in the transformation of agricultural benefits, the scale of investment in ACD has a significant negative impact on AEE in the current period. (iii) The impact of investment structure of ACD on AEE presents a significant “inverted N” relationship, and the optimal proportion of government fund investment structure is 76.71%. The reasonable structure of investment in ACD at different food functional areas shows differences. (iv) After considering the spatial effect, the impact of ACD remains robust, but the spatial spillover effect prolongs the time lag of this impact of investment scale and starts to have a positive impact in the 2nd year after the investment. Guarantee the investment scale in ACD, reduce financial redundancy, establish a cooperation mechanism between ACD and agricultural ecological protection in neighboring areas, and increase the introduction of private capital can achieve sustainable development of agricultural economy. [ABSTRACT FROM AUTHOR]

Urban agglomeration (UA) is an advanced spatial economic form formed and developed in the process of rapid industrialization and urbanization, and an important carrier of urbanization and economic development. The economy has developed rapidly in the recent decades of China, and the UAs have also developed rapidly. However, as a large population country, the population distribution and changes of UAs in China has unique characteristics. Using the fifth, sixth and seventh population census data, spatial auto-correlation and spatial econometric models, we analyzed the spatial-temporal evolution characteristics and influencing factors of population agglomeration in China's UAs. Results revealed that: 1) from 2000 to 2020, the population gradually converged into UAs, and the characteristics of population agglomeration in different development degree of UAs differ. The higher the development degree of UA, the higher the population agglomeration degree. Besides, UAs are the main area with the most significant population agglomeration degree, and the spatial autocorrelation show that the cities with similar degree tend to be concentrated in space. The urban population gathering in UAs has a certain positive spillover effect on population size of neighboring cities. 2) Economic development and social conditions factors are important factors affecting population agglomeration degree in UAs. The main factors of population gather into UAs are similar with the outside UAs, but the positive promotion of urbanization rate and proportion of tertiary industry in GDP on population agglomeration of UAs in China are enhancing from 2000 to 2020. Meanwhile, the other factors, such as high-quality public services, good urban living environment conditions, high-quality medical and educational resources, are also important factors to promote urban population gather into UAs. This study provides a basis for formulating the development planning of UAs in China, and enriches the relevant theoretical research of population evolution and influencing factors of UAs. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Physical Education Institute / Shanghai Tiyu Xueyuan Xuebao is the property of Shanghai Physical Education Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Tourism demand nowcasting is generally carried out using econometric models that incorporate either macroeconomic variables or search query data as explanatory variables. Nowcasting model accuracy is normally evaluated by traditional loss functions. This study proposes a novel statistical method, the monotonicity test, to assess whether the nowcasting errors obtained from the ordinary least squares, generalised dynamic factor model and generalised dynamic factor model combined with mixed data sampling model are monotonically decreasing when new data on explanatory variables become available, based on the mixed frequency data between 1 January 2011 and 31 December 2019. The results of the empirical analysis show that nowcasts generated results based on two data sources combined are superior to that based on a single data source. Compared with traditional loss functions, the monotonicity test leads to a more objective and convincing nowcasting model performance. This study is the first attempt to evaluate tourism demand nowcasting performance using a monotonicity test. [ABSTRACT FROM AUTHOR]

In this article, we develop the Nerlove models that give the area of cacao and cashew nuts in terms of the area, the price and the rainfall. These models are estimated using the methods of ordinary least square and likelihood maximum and are used to analyze the link in a short time between the agricultural determinants. The results showed that the anticipation elasticity had an effect on the price practiced and forecast model. In a short time, the price delayed by one year, and the area delayed by one and two years, had decreasing returns to scale for the current area. [ABSTRACT FROM AUTHOR]

Energy is the key driver of economic growth; however, the economic leadership position of G7 countries and the rising global manufacturing hub status of the ASEAN-5 countries have yet to achieve the Sustainable Development Goals. Thus, this paper aims to examine the effects of real GDP per capita, urban population, the number of individuals using the internet, carbon dioxide emissions, total trade and net foreign direct investment (FDI) inflows on the renewable energy consumption (REC) of G7 and ASEAN-5 countries from 1990 to 2021 yearly data. Using Studenmund's and Gujarati and Porter's procedures of the panel data model, the panel fixed-effect econometric modelling held the best outcome for both G7's and ASEAN-5 countries' REC models. Based on the findings, urban population highly and positively affects REC in G7 countries. However, there is also a positive and strong relationship between net FDI inflows and REC in ASEAN-5 countries. The empirical findings prove the importance of macroeconomic, socioeconomic and environmental variables for the outcomes of REC policies across both developed and developing countries. [ABSTRACT FROM AUTHOR]

Climate plays a significant role in shaping ecosystem-level carbon sinks. Research on the mechanisms of climate impacts on carbon sinks can contribute to the achievement of carbon neutrality. Investigating the mechanisms by which climate impact on carbon sinks in ecological spaces in the Beijing–Tianjin–Hebei region, one of the most important urban clusters in China, is of great significance. This study employed spatial autocorrelation and econometric models to explore how various climatic factors impact net primary productivity (which is used to represent carbon sink capacity) on a spatial scale. We found an increasing trend in NPP across the Beijing–Tianjin–Hebei urban agglomeration from 2000 to 2020, with marked spatial clustering. Climatic factors exhibited the best fit with the spatial Durbin model, except for average annual precipitation. The remaining factors had significant effects on NPP, showing spatial spillover effects. Results also showed that the average annual temperature, evaporation, and relative humidity had positive impacts on NPP at a local scale but adverse effects at a regional scale. Average annual sunshine duration and the ground temperature had negative effects on NPP locally but promoted effects regionally. Furthermore, the average annual wind speed negatively impacted both local- and regional-scale NPP. This research provides insights into how climate affects carbon sinks on a small spatial scale, offering important references for making policy decisions and improving the accuracy of carbon cycling simulations. [ABSTRACT FROM AUTHOR]

Copyright of Realidad Economica is the property of Realidad Economica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Systematic risk, or beta, measures stock price variability in the overall stock market. A considerable body of literature focuses on estimating beta. To the best of our knowledge, there is, however, a lack of definitive research on the impact of income elasticity of demand on stock market beta. This study is the first to examine this relationship using 659 publicly traded firms from 47 industries in South Korea from 2001 to 2020. To estimate the value of the stock market beta, we employ an econometric model with a fixed effects‐two stage least squares approach and use industry concentration as an instrumental variable to deal with the endogeneity problem in the estimation. The overall objective of this study is to investigate the influence of income elasticity of demand on stock market beta. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Forest ecological security is an important guarantee for national security and the healthy development of forestry. Existing research has been limited to the comprehensive evaluation and obstruction factors of forest ecological security, and this study innovatively analyzes internal coordination of forest ecological security and its spatial influencing factors in order to enhance the internal coordination of the forest ecosystem and promote the coordinated improvement of regional forest ecological security. Firstly, the forest ecological security in China from 2006 to 2020 was evaluated. On this basis, the coupling coordination degree of forest ecological security (FESD) was calculated, and its influencing factors and spatial spillover effects were analyzed using the spatial econometric model. The results show that: (1) most of China's provincial forest ecological security is at a critical and relatively safe level, and shows a trend of gradual improvement; (2) FESD in 25 provinces, represented by Guangxi, is in the acceptable range and is constantly improving; and (3) annual mean temperature, urbanization rate, completed forestry investment, and forest pest control have been positive influences on FESD. Forest population density, per capita GDP, and investment in environmental governance have significant negative influences. In addition, completed forestry investment, annual mean temperature, urbanization rate, forest population density, and forest pest control have significant spillover effects on FESD. Therefore, in the process of forest ecological management, it is necessary to further strengthen investments in forestry and pest control, and to pay more attention to the interaction between regions. [ABSTRACT FROM AUTHOR]

With numerous aging societies worldwide, the world is facing a rapidly growing and already large elderly population. Elderly care facilities have become an important topic. Hence, it is urgent to examine the layouts of public elderly care service facilities, conduct rational planning, and promote the efficient utilization of facility resources. By constructing a Service Demand Equality-Frame Model and performing visualizations based on Geographic Information Systems (GISs), we assessed the degrees of spatial equilibrium between the service capacities of public elderly care services and the demand for them. The spatial accessibility and equality of hospitals, communities, and elderly care facilities in Guangzhou’s four main urban districts (Yuexiu, Liwan, Haizhu, and Tianhe) were subjected to scientific evaluation. The results have validated the effectiveness of the econometric model. According to GIS-based visualization, the spatial accessibility distributions of these public facilities are uneven with large gaps between subdistricts. Accessibility peaked in Yuexiu but gradually declined from the city center and Yuexiu to the surrounding areas. We investigated the best quantitative approaches for measuring the spatial accessibility distributions of public facilities such as hospitals and communities to improve spatial layout monitoring and optimization of elderly care facilities. [ABSTRACT FROM AUTHOR]

Sustainable development can be mainly achieved by promoting the green transformation and development of the world economy and by improving the efficiency of regional green development, which often receive extensive attention from the academia. This paper uses a spatial econometric model to estimate the impact of manufacturing agglomeration on green development efficiency based on the panel data of China's Yangtze River Economic Belt (YREB). The results show an overall large gap of green development efficiency between regions in the Yangtze River Economic Zone, mostly due to the extremely uneven development of green development efficiency in the upper reaches. Opposite to the middle and lower reaches, manufacturing agglomeration in the upper reaches of the YREB improves green development efficiency. Manufacturing agglomeration is conducive to the improvement of green development efficiency in adjacent areas. Nonetheless, it may hinder green development efficiency by inhibiting green technological innovation. This paper provides empirical evidence and policy implications for applying manufacturing agglomeration to promote green development efficiency in accordance with local conditions. [ABSTRACT FROM AUTHOR]

The article raises issues regarding the consumption of energy from both fossil and renewable sources in households. The research was carried out on the basis of data obtained from the Eurostat database, which covered the period from 1995 to 2021 and concerned the European Union countries. Increasing energy consumption and, thus, increasing household expenses affect their standard of living. The purpose of the analysis was to construct two econometric models for electricity consumption. The first model referred to the consumption of energy from fossil sources and the second from renewable sources. A forecast of energy consumption in households was also constructed on the basis of estimated models. Econometric modelling methods (multiple regression) and time-series forecasting methods (linear regression method, exponential smoothing models) were applied for the study. Research shows that the main factor that models energy consumption in households, both from fossil and renewable sources, is the final consumption expenditure of households (Euro per capita). The set of indicators for the models varies depending on the type of energy source. The forecast shows that the share of energy consumption obtained from fossil sources will decrease systematically, while the share of energy consumption from renewable sources will continue to increase systematically. [ABSTRACT FROM AUTHOR]

In regard to the comprehensive promotion of rural revitalization, the construction of digital villages is a crucial development. Because the construction of digital villages is considerably novel, the existing studies mainly focus on the theoretical aspects pertaining to the rational and practical robustness of digital villages, and with regard to regional unevenness, the number of studies that consider the current characteristics, absolute gaps, and impact mechanisms pertaining to the construction of digital villages is insufficient. Based on the regional unevenness that characterizes digital village construction, this study proposes a research framework for digital technology-enabled village construction, which integrates three major factors, namely technology, institutions, and human resources; thus, the comprehensive assessment pertaining to the level of digital village construction is enhanced. This study, which applies the aforementioned research framework, constructs an index system for evaluating the construction level of digital villages, and to reveal the characteristics pertaining to regional heterogeneity and the main influencing factors pertaining to the construction level of digital villages in China (study period; 2015–2020), it utilizes the Dagum Gini coefficient method and the spatial econometric model. Consequently, the researchers observe the following: First, the level of digital village construction in China exhibits a "W-shaped" recovery growth. Second, with respect to the regional level, the eastern region exhibits the highest level of digital village construction, followed by central and western regions; furthermore, we observe that the eastern and western regions account for the greatest intra-regional variation, and that with regard to the overall difference, the inter-regional gap represents the main causative factor. Finally, with regard to influencing factors, technology and innovation capabilities, occupational differentiation of farmers, economic development significantly contribute to the level of digital village construction, whereas fiscal autonomy exerts a significant inhibiting effect. In regard to the level of digital village construction, the research framework and results may provide a novel analytical framework for examining the main sources of regional unevenness, and it may also provide a reference for decision-making, which can influence the construction of digital villages in China as well as in other countries. [ABSTRACT FROM AUTHOR]

Economic growth characterizes the quantitative changes that occur in economic variables and attributed to overall increase in production per capital. This study examined the economic impact of exchange rate, foreign direct investment, inflation rate and the trade balance on Nigeria GDP over the period of 1970-2022. The dynamic causal association among the selected macroeconomic variables and economic growth in Nigeria was evaluated via the implementation of vector error correction model (VECM) procedures and impulse response functions. The VECM estimates and the impulse response shows that the response of GDP to inflation and exchange rates is positive while the response of GDP to a one period shock to the trade balance yields a marginal negative depreciation. The result justifies that the place of Exchange rate, Inflation and Trade Balance to Nigeria economic growth cannot be overstated. The results of the work suggest that to promote stable and sustainable economic growth, policy makers should lay more emphasis on encouraging stable and reasonable exchange rate. Also, the work recommends that to promote economic growth and keep inflation low in Nigeria, Anti-inflationary policies should be accompanied to attract foreign investors and frustrate capital fleeing from the country. [ABSTRACT FROM AUTHOR]

The main objective of this article is to discuss and estimate the relationship between Induced Investment (II) and the Gross Domestic Product (GDP) cycle of the Brazilian economy, based on the theoretical foundations of John Maynard Keynes and Hyman Philip Minsky. In addition, the methodology for carrying out the econometric modeling involves the use of unit root and cointegration tests of the Induced Investment and GDP series in Brazil between 1990 and 2019. The results of the econometric models confirm Keynes-Minsky's economic foundations on business cycles. Therefore, it is up to economic agents, especially the government and the business sector, to observe the best method of employing them, in order to guarantee a more effective recovery of the economy, not only focusing on growth speed, but in medium and long term stabilization in order to avoid new outbreaks of crisis in the short term. [ABSTRACT FROM AUTHOR]

The digitisation of the transportation sector and data availability have opened up new opportunities to implement data-driven methods for improving company performance. This article analyses demand and freight rate forecasting techniques in the context of the road freight transportation company. The European market was analysed in this research, and direction from the Netherlands to Italy was selected for the case study. Performed investigation showed that econometric models such as Auto-Regressive Integrated Moving Average (ARIMA) used for demand prognosis provide good results. Freight rate forecasting is different; econometric models, including multivariate models ARIMA with exogenous variables (ARIMAX) and Seasonal ARIMAX (SARIMAX), do not perform satisfactorily under specified time intervals, therefore MultiLayer Perceptron (MLP) was used as a solution. It can be seen that Artificial Intelligence (AI) based methods provide better results. Despite its success, the AI-based approach alone is not recommended for practical implementation since forecasted input parameters are neces)sary. Lastly, the study uncovers a valuable insight. A strong correlation (0.86) between spot and contract rates was found, and the article shows how current spot rates can be used for contract rate forecasting. [ABSTRACT FROM AUTHOR]

The objective of this research in to analyze the incidence of the economic and social indicators of Mexico and China on the flows of direct foreign investment. For this purpose, it is analyzed first the behavior of the main macroeconomic variables of these economies. Subsequently, the theories of foreign direct investment are reviewed in order to understand its nature, motivations, and ways in which it is presented. From which the methodological features of the econometric models applied to each country are addressed. The results establish that in the Mexican case, the value added in the manufacturing industry and intentional homicides determined the flow of direct foreign investment to the country. While salaries, public spending on education and intentional homicides motivated foreign direct investment in the case of China. [ABSTRACT FROM AUTHOR]

In the context of carbon neutralization and carbon peak, carbon reduction in key industries has become a central topic in our country. As an important part of technological progress, it is necessary to study the effect of technology import on carbon emission reduction in key industries. Based on the panel data of 30 provinces. from 2011 to 2020, this paper used the fixed-effect model to analyze the emission reduction effect in key industries on the development status of technology import. The spatial econometric model was used to analyze the spatial characteristics of carbon emissions of technology import and key industries. Then, the mediating effect model was used to bring industrial technological innovations into the research category to analyze the mediating role of technology imports on the carbon emissions of key industries. Finally, a robustness test proved the reliability of the model. The findings were as follows: (1) Technology import significantly promoted carbon emission reduction in key industries; (2) In terms of the spatial relationship, technology import and carbon dioxide emissions had significant spillover effects, and there were trends of high and high aggregation and low and low aggregation, with the impact of technology import on carbon dioxide emissions having a siphon effect; (3) Industrial technological innovation played an intermediary role in this path, but it was a negative role, which was not, in general, conducive to the reduction of carbon emissions of key industries. On this basis, the paper puts forward several policy suggestions. [ABSTRACT FROM AUTHOR]

In this paper, the spatial dynamic panel data (SDPD) model with fixed effects is extended to a non-parametric form by relaxing the linear or nonlinear parameter structure of explanatory variables. The non-parametric spatial dynamic panel data (NSDPD) model with fixed effects not only retains the advantages of the SDPD model which can deal with spatial and/or temporal individual characteristics and spatio-temporal dependencies but also solves the limitation that may lead to specification errors. It also enhances the flexibility and practicability of the spatial econometric model. Since the model to be estimated contains unknown functions, we propose this profile maximum likelihood (PML) method to solve the problem of the incidental parameters in the estimation. Under the assumption that the spatial coefficients are known, we first eliminate the influence of the time effect by substitution and then use the local polynomial estimation to preliminarily estimate the unknown function so as to transform the model into the parametric form for solving. We derive the asymptotic properties of PMLEs and find that under certain regularity conditions, both parametric and non-parametric estimators are consistent. The Monte Carlo results show that the estimators have good finite sample performance. We illustrate the empirical relevance of the model by applying it to examine the impact of tourism dynamics on economic development in the Yangtze River Delta region of China. [ABSTRACT FROM AUTHOR]

The objective of the study was to estimate the effect of possession of university degrees (sheepskin effect) on the salaries of university professionals in the Huánuco region, Peru for the year 2014. The theoretical framework is based on the theoretical model of academic degrees. Proposed by Hungerford and Solon, this model establishes a relationship between the possession of academic degrees and people's salaries. Regarding the methodology, the study is characterized by being of a quantitative approach and of an applied type, with an explanatory level and a non-experimental cross-sectional design. In this sense, data from the 2014 National Survey of University and Universities Graduates carried out by the National Institute of Statistics and Informatics (INEI) were used to estimate a multivariate linear regression econometric model. The econometric model estimation results indicate that possession of academic degrees has a direct and significant effect on wages; In particular, it is found that the academic degree of Master and Doctor have a greater effect on the salaries of professionals compared to professionals who do not have said degrees, evidencing the sheepskin effect in the Huánuco region. [ABSTRACT FROM AUTHOR]

Thermal power is the main source of China's electricity supply. Improving total‐factor generation performance (TFGP) is essential for the development of this industry in the current deteriorating operating environment. This study adopts the meta‐frontier nonradial direction distance function approach to measure the static and dynamic TFGPs of the thermal power industry in China's 30 provinces in 2011–2019, and then discusses the regional distribution characteristics and the impact factors using spatial econometric model and Tobit regression method, respectively. Empirical results show that: (I) The TFGPs in central and west China are relatively close, but both are remarkably lower than that in east China. (II) The TFGPs in central and west China have generally remained stable since 2011, whereas that in west China has declined mainly because this region is more susceptible to the situation of electricity supply‐demand. (III) A significant spatial positive correlation exists among provincial TFGPs. High TFGP provinces are mostly in the eastern seaboard region and low TFGP provinces are in southwest China. (IV) Economic development, power structure, fuel prices, and environmental regulation have positive impacts on China's TFGP, while the impacts of technological innovation and energy endowment are not significant. [ABSTRACT FROM AUTHOR]

The aim of this study is to present the consequences of the COVID-19 crisis in the long-distance coach market in Europe. Firstly, the literature review depicts the dynamic situation of European long-distance transport service providers. It is reiterated that the disruptions to long-distance coach transport triggered by the COVID-19 pandemic are multidimensional. Secondly, 10 econometric panel models, including one spatial and two dynamic panel models, were constructed for 505 or 495 regions (depending on the model) of 26 European countries. The analysis allowed us to draw conclusions about the impact of excess mortality, public sentiment, population density, and infrastructure quality on the number of long-distance FlixBus coach departures. Models indicate that increased anxiety associated with COVID-19 leads to a drop in the number of departures even when mortality anomaly is accounted for. Moreover, the number of departures changed more significantly in response to an increased infection rate in 2021 compared to 2020. This may indicate that long-distance coach companies were encouraged to implement new policies aiming at a lower frequency of trips, thereby increasing certainty that planned departures would not be canceled at the last minute. This can serve as an evidence of a shift in companies' focus towards greater flexibility of their offers. [ABSTRACT FROM AUTHOR]

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Copyright of Revista de Economia e Sociologia Rural is the property of Sociedade Brasileira de Economia e Sociologia Rural and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: Demonetization was one of the macroeconomic shocks that occurred in India on 8th November 2016, leading to an impact on liquidity for informal laborers. The income of informal laborers declined, which increased poverty and inequality among the informal workers. Therefore, the study aims to comprehend how demonetization affected the informal labor segment of the Faridabad district of Haryana. Furthermore, skill development in this setting is crucial in addressing poverty because it increases laborer's "employability", "productivity", and promotes "equitable growth." Thus, another objective of the study is to understand how the laborer's productivity and employability are related to the enhancement of the skill of informal workers, which can thereafter address the SDGs 1 (Zero Poverty), 5 (Gender Equality), 8 (Economic Growth & Decent Work), 10 (Zero Inequality). Method: Regression analysis has been used to assess the causal relationship between the money supply, income creation, and gross domestic savings based on secondary data. This was supported by primary data collected through surveys from informal laborers in a particular Faridabad industrial cluster. Further, the descriptive research (ANOVA) and econometric model will show how skill development among informal workers promotes employability and productivity, and primary data will show how gender, education, and skill affect productivity, respectively. This may further reduce the poverty levels complemented by a national, state-level policy analysis. Results: The study revealed a decrease in average income (from INR 10,340 to INR 7,075) and savings (from INR 1,330 to INR -2,092) of informal workers after demonetization. The study also shows that male salaries improve when they receive formal skill development training, that is, by INR 1096.944 (INR 11429) from INR 10332. On the other hand, the average income of female informal workers who have informal training and no primary education comes to be at INR 10332.79. Originality: The research is an original mixed-method approach to determine the intuitive and positive links between changes in the Gross Domestic Product (GDP), Money Supply (M3), and household Gross Domestic Savings. It is further supported by primary data that show how demonetization affected informal workers' savings and the effect of skill on their earnings (a proxy variable for labor productivity). [ABSTRACT FROM AUTHOR]

Copyright of Ensayos - Revista de Economía is the property of Ensayos Revista de Economia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Copyright of Les Cahiers du CREAD is the property of Centre de Rrecherche en Economie Appliquee pour Developpement and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: The paper's primary purpose is to assess macroeconomic conditions' impact on the sustainable development of transport companies in France, Germany and Poland from 2008 to 2020. The study is important for the stable development of the transport sector and for ensuring a balance between socioeconomic and environmental development. Design/methodology/approach: The research goal was achieved thanks to creating sustainable development indicators using the normalization method of variables; additionally, econometric models were developed using the Ordinary Least Square (OLS) and the Seemingly Unrelated Regression (SUR) methods. Findings: The analysis results indicate that in France, Germany and Poland, there is a positive trend in the sustainable development of transport companies. What is more, its high rates also remain at the time of the outbreak of the Covid-19 pandemic. Economic growth is an essential macroeconomic condition which positively affects sustainable development and its pillars. Research limitations/implications: The research limitations are related to data availability at the level of sectors, the selected research period, the selection of variables, and the normalization method. Moreover, the econometric methods were selected for estimating equations. Practical implications: The empirical implications include that the research results can help those in power (formulation of specific legal regulations and conditions for sustainable development of enterprises). Furthermore, those managing enterprises should focus not only on the company's internal situation but also on analyzing macroeconomic factors continuously. Social implications: Social development is crucial for the sustainable development of enterprises. Therefore it is necessary to take measures to develop human capital. Originality/value: The study's novelty is the comparative assessment of the sustainable development of the transport sector in France, Germany and Poland. In addition, it should be noted that modern statistical methods were used for the analyses. [ABSTRACT FROM AUTHOR]

Electronic word of mouth (eWOM) has been gaining popularity pertaining to its numerous benefits and ability to be applied in various fields. It helps consumers in making informed decisions and aids service providers in delivering an enhanced service or product. Despite all these benefits, dealing with the huge amounts of eWOM is a consistent problem. eWOM helpfulness comes handy in order to address this issue. In this study, we utilize 16699 hotels related eWOM written by 1099 reviewers which are collected from TripAdvisor.com. Our main objective is to analyze which factors impact eWOM helpfulness and how. For this purpose, eight unique variables belonging to three different categories are selected (eWOM length, eWOM subjectivity, eWOM polarity, eWOM readability, eWOM recency, hotel rating, reviewer badge and reviewer helpfulness) and are analyzed using econometric modelling. Our findings show that hotel rating as well as reviewer badge and helpfulness enjoy a positive significant relationship with eWOM helpfulness. It also suggests that eWOM length, readability and subjectivity positively influences eWOM helpfulness though eWOM polarity and recency are found to have an inverse relationship with the helpfulness of eWOM. Thus, our study reports that review, hotel and reviewer characteristics impact eWOM helpfulness in different ways. This study is summarized with the discussion of theoretical and practical implications. [ABSTRACT FROM AUTHOR]