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The paper reports analysis of data from a household survey concerning water conservation behaviour in Kuwait. Econometric models were used for nine conservation measures, The models were estimated for nationals and expatriates. The results revealed that households made efforts to conserve water by changing habits/practices. The results failed to support the theory of planned behaviour as water conservation campaign had no effect on households' water conservation. Awareness about environment and water conservation did not result in pro-conservation behaviour. [ABSTRACT FROM AUTHOR]

Resource-based cities often face problems such as resource scarcity and insufficient electricity to achieve complex high-quality growth. At present, there is relatively little research on the impact on the high-quality development of such cities. To study the key variables that affect the high-quality growth of resource-based cities, we adopt entropy weighted TOPSIS technology, spatial correlation analysis, and spatial econometric models. The main conclusions are as follows: (1) The overall high-quality development of resource-based cities in China is on the rise year by year; The cities with the highest growth rates are those that are mature, rejuvenated, growing, and declining. (2) Resource-based cities have a positive geographical correlation in high-quality development, and different numbers of clusters are displayed by changing the Moran I index score. (3) High quality development is strongly influenced by human capital, urbanization, technological innovation, and global market openness. There are significant differences in the ways in which these variables affect various types of resource-based cities. Policy makers who strive to reduce regional inequality and encourage high-quality growth in resource-based communities may benefit greatly from the insights provided by this study. [ABSTRACT FROM AUTHOR]

This paper employs a unique data set to analyze the trading behavior of wealthy individual investors across Mainland China and their impact on Chinese stock markets' tail risk. Results show that the wealthy individual investors' trading behavior can explain Chinese stock markets' tail risk, and the daily investment portfolios based on the network density of wealthy individual investors have significant excess returns. This paper also investigates the determinants of wealthy individual investors' trading behavior with the social network method and the spatial econometric model, and reveals that wealthy individuals benefit from the spillover effect of their trading behavior through the investor networks. The results of this paper not only reveal micro evidence for the formation mechanism of asset prices, but also provide insight into the behavior of wealthy individual investors. [ABSTRACT FROM AUTHOR]

This research focused on the relationships among 34 major airports in China, analyzing how these relationships are influenced by spatial dependence and heterogeneity. Using a spatial econometric model, it found that passenger traffic in China's airports displays a mutually driven aggregation effect. Furthermore, the study revealed that the airport relationship changes from complementarity to competition as the geographic distance between them decreases. The study also classified the main airports in China into three hierarchical levels and found significant complementarity and competition among those within the hub-and-spoke network structure. Specifically, this study identified a complementary relationship among regional trunk and local branch airports, as-well-as significant competition among hub airports. Crucially, the study suggests that the absence of a hub airport weakens the collaborative interactions between different types of airports, emphasizing the critical importance of hub airports for the connectivity and operational efficiency of China's airport network. [ABSTRACT FROM AUTHOR]

An extensive and profound investigation into the dynamic interactions between High-Quality Urbanization (HQU) and Ecosystem Service Value are of utmost importance for the coordinated development of the region. Diverging from traditional macro-level analysis, this study is grounded on county-scale data, measuring HQU and ecosystem service value from a multidimensional perspective. On the basis of the research framework of "phenomena-relationships-mechanisms", we expect to delve deeper into the spatiotemporal evolutionary characteristics of ecosystem service value and HQU and their integrated interactions. Additionally, we utilize econometric models to rigorously evaluate the impact of HQU on ecosystem service value, with the goal of filling the current research gaps. The research results are as follows: (1) From 2000 to 2020, the ecosystem service value in Shandong Province exhibit an overall decreasing and then increasing trend, and shows a spatial posture of high east and low west. HQU generally maintains a steady upward trend, and its spatio-temporal evolution has apparent heterogeneity. (2) The Coupled Coordination Degree (CCD) between HQU and ecosystem service value has a gradual rising trend, and there is an increasing level of consistency between them. (3) HQU has a negative effect on ecosystem service value, and the direction and degree of the effect on segmented ecosystem service value types vary greatly. (4) The effect of HQU on ecosystem service value is heterogenous, and the attenuating effect is mainly found in grain-producing counties, inland counties, and counties with a lower index of high-quality urbanization. In conclusion, our results are expected to provide targeted recommendations for sustainable development and ecological balance in Shandong Province. [ABSTRACT FROM AUTHOR]

The purpose of this article is to analyze the association between board remuneration and the probability of disclosure of non-GAAP earnings measures by Brazilian companies listed in Brazil, Bolsa, Balcão - [B]3, in the period from 2010 to 2020. The analyzed sample is composed of 271 companies, with 2,093 firm-year observations. To achieve the proposed objective, two econometric procedures were used. Initially, to analyze the probability of EBITDA disclosure, a model with Logit estimation was used. Then, to give robustness to the results, the data were rotated using Ordinary Least Squares with fixed effects and sector control. The variables used in the study were collected from documents filed with the CVM, and Refinitv Eikon? was also used. To identify the disclosure or not of EBITDA by the companies, the press releases published and filed on the IR website or at the CVM were analyzed. The results of the econometric models showed that the remuneration of the board of directors increases, on average, the probability of the firm disclosing the non-GAAP EBITDA measure by 26%. However, the probability of EBITDA disclosure is reduced by 41% when the firm has a loss for the year and this loss is greater than the loss of the previous year. The other GAAP variables were not statistically significant, so it can be concluded that the increase in earnings did not directly influence the EBITDA disclosure. In addition, quantitatively, there is a reduction in the disclosure of EBITDA in the years 2019 and 2020. In this way, this study contributes to the various users of accounting information, in particular, it takes a look at the agency problem, by providing evidence related to the agent's remuneration and the disclosure of information - reduction of information asymmetry, to the principal. In addition, it provides evidence on non-GAAP measures for accounting standards bodies, nationally and internationally. [ABSTRACT FROM AUTHOR]

Globalization opens up economies and encourages the free movement of persons and factors of production. Diaspora investors and workers earn income in the process and make remittances to the migrating countries. We examine the impact of the remittance inflow on the macroeconomic performance of top emigrating countries, which comprise nine emerging and two advanced economies. We conduct group and individual country analyses with distinct econometric models (Feasible Quasi Generalized Least Squares and Dynamic Common Correlated Effects) using data between 1987 and 2021. The results reveal positive impact of remittance inflows on nominal GDP and nominal GDP per capita and on real GDP and real GDP per capita, although evidence on the latter is weaker. In all, the emigrating countries can benefit from diaspora remittance in terms of improved productivity and macroeconomic performance. We therefore recommend better systems to facilitate remittance receipt and policies to channel such flows more into investment activities. [ABSTRACT FROM AUTHOR]

In the context of the rapid development of the digital economy, it's an important topic how to play the role of digital technology in improving innovation efficiency. Employing the spatial econometric model with province-level panel data during 2006–2018, the article explores the impact of the development of the digital economy on innovation efficiency in China. The analysis unveils three major findings. First, the innovation efficiency has significant positive spatial externalities and the digital economy has significantly positive direct effects and spatial spillover effects on innovation efficiency, but the above effects are heterogeneous for different regions and innovation subjects. Second, the impact of digital economy development on innovation efficiency has characteristics of a certain degree of lag effect and continuity. Third, the threshold effect analysis reveals the non-linear characteristic of the increasing marginal effect of the digital economy on innovation efficiency. Altogether, the development of the digital economy has become an important driving force for promoting China's innovation efficiency. The findings of this paper provide empirical evidence for understanding the relationship between the digital economy development and innovation efficiency, giving significant implications for the innovative development of developing countries. [ABSTRACT FROM AUTHOR]

The effectiveness of the policies implemented during the COVID-19 pandemic is relevant both for assessing the impact caused and for deriving policy lessons in case such phenomena recur. The main objective here is to determine the relationship between human activity and reported COVID-19 cases. To measure human activity, a metric of nighttime lights is generated using satellite images. Conducting cointegration tests we found a long-term equilibrium relationship between the two variables, and through causality tests we confirmed that it is feasible to predict COVID-19 infections from changes in nighttime lights. Using econometric models for time series, it is shown that COVID-19 infections respond to changes in nighttime lights with high statistical significance and with a lag of up to two weeks, implying that the intensity of human activity that was happening now would have been useful for planning the resources that would be necessary two weeks later. [ABSTRACT FROM AUTHOR]

The green transformation of the manufacturing industry is an important segment in high-quality development, and the vigorous development of the digital economy has provided a new impetus. Taking the balanced panel data of 277 cities in China from 2011 to 2021 as the sample, this study used the super-efficient SBM model containing unexpected output to measure the effects of the green transformation of the manufacturing industry at the city level, measured the digital economy index at the city level based on the entropy weight method, and then used the general nesting spatial model to empirically analyze the impact of the digital economy on the green transformation of the manufacturing industry. After drawing the basic conclusions, this study further applied the mediation effect model and the two-zone spatial econometric model to analyze the mediation and moderation factors of the digital economy on the green transformation of the manufacturing industry. The results indicated that: (1) The green transformation of manufacturing industry among Chinese cities presented a spatial clustering feature, specifically manifested as the siphon effect, which means that the green transformation of manufacturing industry in a city was not conducive to the green transformation of manufacturing industry in its surrounding cities. (2) The digital economy not only significantly promoted the green transformation of the manufacturing industry in this city, but also in the surrounding cities. This conclusion remained valid after a series of endogeneity and robustness tests. (3) Mediation analysis found that the promotion of the digital economy in the green transformation of the manufacturing industry occurred through three channels: promoting green technology innovation, optimizing resource allocation efficiency, and improving green credit. (4) Moderation analysis indicated that the relationship between the digital economy and the green transformation of the manufacturing industry was affected by energy efficiency, and lower energy efficiency weakened the role of the digital economy. Compared to existing research, this study improves the theoretical mechanism of the digital economy-manufacturing green transformation relationship from the perspectives of resources and credit and explores the moderation factors in this relationship from the energy perspective. The spatial econometric model in this study also comprehensively considers the spatial correlation caused by geographical and economic factors, which is progress compared to previous studies that only considered geographical spatial correlation. Based on the research results, this study proposes relevant implications to accelerate the development of the digital economy, improve energy efficiency, accelerate green technology innovation, improve resource allocation efficiency, and optimize green credit. [ABSTRACT FROM AUTHOR]

Purpose: the aim of the work is to study the impact of selected economic factors on the level of gross salaries in the industry sector in Poland in the years 2005-2020. Design/methodology/approach: in the first stage of the research, the Pearson linear correlation between the average gross salary in industry and the adopted variables was examined. Then, a multiple regression model was created, which aims to indicate which of the adopted variables best explain the development of the average gross salary in industry. Findings: the construction of the econometric model allowed us to indicate that the factors that best explain the average gross salary in industry are the average gross salary in the economy and the volume of domestic demand. Research limitations/implications: there are many alternative models that may lead to different results by subsequent authors of scientific papers. Therefore, it is recommended to conduct further research to identify the factors shaping gross salaries in industry. Originality/value: the article raises an important topic regarding economic factors affecting the level of salaries in industry. The existing literature lacks research specifically focused on salaries in the industry. [ABSTRACT FROM AUTHOR]

Carbon emission issues are becoming increasingly severe, and the carbon emissions in shrinking cities, primarily characterized by population loss, are often overlooked and insufficiently studied. This paper focuses on the carbon emissions from county-level administrative units in China's three northeastern provinces from 2001 to 2017. The study scientifically identified shrinking cities and measured the differences in carbon emission characteristics between growing and shrinking cities using the Theil index. Ultimately, the paper constructs a panel spatial econometric model to analyze the factors influencing them and explore their spatial effects. (1) The total carbon emissions in the Three Northeastern Provinces exhibited an inverted U-shaped trend, increasing from 734.21 million tons in 2001 to 1731.73 million tons in 2017, with the Mann–Kendall trend test showing a significant increase; spatially, this manifests as a significant positive spatial autocorrelation. (2) The region has 138 shrinking cities, accounting for over 50%; regarding carbon emission characteristics, the Theil index has consistently remained above 0.18, indicating significant differences between the carbon emissions of growing and shrinking cities. (3) The panel spatial econometric model results show that the influencing factors of carbon emissions in shrinking cities have unique directions, intensities, and spatial effects. In shrinking cities, aside from localized GDP effects and per-capita GDP acting as a suppressant, the population size has a pronounced inhibitory effect on local and surrounding carbon emissions. The analysis reveals significant differences in the carbon emission patterns and mechanisms between growing and shrinking cities; based on these results, the paper proposes differentiated carbon control strategies. [ABSTRACT FROM AUTHOR]

Logistics land is the spatial carrier for the development of logistics enterprises. Its evolution mode and driving mechanism determine the level of high-quality development of the logistics industry, and serve as an important basis for urban planning and territorial spatial planning. This study introduced a Boston consulting group (BCG) matrix and geographically weighted regression (GWR) spatial econometric models to carry out empirical research on the Yangtze River Delta (YRD), in an effort to provide scientific information for evidence-based decision-making by governments and enterprises. The scale and ratio of logistics land (LLS and LLR) in the YRD showed significant spatial heterogeneity and autocorrelation, cities with large logistics land use converging from clusters to belts from 2000 to 2020, and agglomerations with high logistics land ratio (LLR) migrating from inland to coastal areas. Diversified models of logistics land evolution also emerged, such as high scale–high speed cities, low scale–low speed cities, high scale–low speed cities, and low scale–high speed cities. In addition, the driving mechanism of LLS and LLR was very complex, with a great difference in the intensity, nature and spatial effects of the influence of different factors. The inspiration from empirical case studies is urgent to revise the planning norms and clarify the LLS and LLR control standards for logistics land use. Meanwhile, the synergistic development target of the logistics industry in the new era is changing from the manufacturing industry to the commerce and trade industry; the establishment of planning zoning and the designing of differentiated management policies significantly improve the planning applicability. [ABSTRACT FROM AUTHOR]

This paper proposes a nonlinear teaching approach, based on learning theories in cognitive psychology, with a special focus on large-cohort economics modules. The fundamental rationale is to match the features of teaching with the nature of learning. This approach was implemented in an undergraduate economics module, which received qualitative feedback and quantitative evaluation. Formal econometric models with both binary and continuous treatment effects were developed and estimated to quantify the effects of the proposed approach. Evidence shows that the nonlinear teaching approach significantly improves the effectiveness and efficiency of the learning-teaching process but does not promote student attendance. [ABSTRACT FROM AUTHOR]

Purpose: Managers engage in marketing efforts to boost sales and in setting marketing budgets based on current or historical sales. Past studies have overlooked the reciprocal relationship between marketing spending and sales. This study aims to examine the nature of the relationship between sales and marketing expenses in the B2B market. Design/methodology/approach: Five hypotheses on the relationship between sales and marketing expenditures were framed. A total of 30 of India's dyeing firms provided data on revenues, sales (in units) and marketing expenditures over time. The structural vector auto-regressive model and the vector error correction model were fitted to the data. Findings: The results show that marketing expenses and sales are related bidirectionally in a sequential way. Furthermore, sales drive the long-term equilibrium relationship to a greater extent than marketing expenditures. Practical implications: The findings of this study should assist managers in predicting sales and marketing budgets simultaneously and devising precise marketing strategies and tactics. Originality/value: Using econometric models in data-driven research is not a frequent practice in marketing. This study adds value to the body of marketing literature by advancing the theory of the relationship between sales and marketing spending using real-world data and econometric models in the B2B sector. [ABSTRACT FROM AUTHOR]

The paper analysed the input costs on the sunflower production at Mkalama district in Singida region using variables prices of fertilizer, plough, pesticide, land hired per acre, labour hired, hoe, improved seed (50kg) and Local seed (50kg). For this aim, descriptive statistics and an econometric analysis was conducted in 120 randomly selected sunflower farmers in Mkalama district. Descriptive statistics and OLS regression model were used to analyze the extent of input costs on the sunflower production by respondents. The results revealed that fertilizer, plough, labour hired and Local seed (50kg) inputs had the highest average total cost of inputs. The results of econometric model showed that fertilizers, ploughs, pesticides, land hired per acre, hoes and improved seed (50kg) were the most important inputs, significantly contributed to total production of sunflower seeds; While, the use of labour hired and Local seed (50kg) has negative relationship with output of sunflower. The paper found out that price per bag of fertilizer, price per plough, price per pesticide and price per acre of land hired are positive and statistically significant influence on the sunflower production (Beta= 0.535, 0.302, 0.502, 0.197, P>0.001). The paper concluded that major problems confronting sunflower production were found to be inputs cost which always affects the yield of sunflower. This paper recommended that the Government of Tanzania should enhance the productivity of the agricultural sector through the subsidies provision of the required inputs, which would minimize the total cost of production and speed up the productivity process of sunflower in Tanzania. [ABSTRACT FROM AUTHOR]

Openness to international trade is often conducive to long-term economic development. Indeed, thanks to trade instruments based on an effective and selective policy of openness, and to human capital that is both qualified and specialised, trade liberalisation is a key determinant of healthy and progressive economic growth. The aim of this article is to study the nature and direction of causal relationships in a dynamic framework, between the variable to be explained (trade openness) measured by the volume of exports and imports as well as by human capital, and the variable to be explained (economic growth) measured by GDP at the level of Morocco. In this respect, we will attempt to examine this causal relationship in the Moroccan context. From this perspective, our question, which remains important, can be formulated as follows: To what extent does trade openness promote economic growth in Morocco? In order to find more relevant answers to our question, we carried out a mixed analysis (both theoretical and empirical) based on mortgagedeductive reasoning derived from a purely positivist posture, on the one hand, and, on the other, we applied econometric modeling to the case of Morocco, based on the ARDL approach. The data collected is annual and covers a period from 1985 to 2020. It was gathered from the HCP and World Bank databases. To do this, we used the ARDL method. The results received by the econometric modeling and the tests that verify the relationship and the direction of causality indicate that trade openness have a positive influence on Moroccan economic growth. [ABSTRACT FROM AUTHOR]

Economists have hypothesized that currency appreciation resulting from oil production in oil-rich countries can suppress the production of tradable goods, a phenomenon known as Dutch disease, often assessed using econometric models. This study leverages sanctions on Iranian oil exports, employing a quasi-experimental design with two distinct periods (1959–2020): one marked by sanctions (oil revenue recession) and the other by non-sanctions (oil revenue boom). The result shows a reversal of the Dutch disease effect during sanctions, leading to a real depreciation of the national currency and heightened production of tradable goods over non-tradable ones. The observed pattern of the real exchange rate aligns with Dutch disease dynamics, depreciating during sanctions and appreciating during non-sanction periods. Furthermore, the tradable sector exhibited increased share and real output growth compared to the non-tradable sector during the sanction period. [ABSTRACT FROM AUTHOR]

This study investigates the corporate social responsibility disclosure (CSRD) practices of multinational corporations (MNCs) operating in the Libyan oil industry, particularly amidst significant political transformations within the host‐country (HSC). By examining these insights, we aim to shed light on how these corporations navigate and address CSRD considerations in a dynamic and politically evolving environment. To analyse these aspects, we employ various econometric models, including two‐stage least squares (2SLS) and propensity score matching (PSM). Our examination covers a dataset of 6000 data points representing 35 multinational oil corporations headquartered in 18 different home countries (HMCs) across five continents, spanning the years from 2008 to 2015. Our findings indicated that the level of institutional quality convergence between MNCs' HMCs and HSC significantly determines the extent of HSC‐related CSRD by MNCs. Additionally, the study emphasised that MNCs' internationalisation and business horizon within the HSC are critical factors influencing their CSRD in that country. The findings furthermore suggested that MNCs with a higher CSRD might exert an influence on the political decisions of their HMCs' governments concerning the political crisis in the HSC. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to study the impact of economic freedom and some key macroeconomic variables on the foreign direct investment (FDI) inflow in Brazil. Design/methodology/approach: An econometric model is developed that includes FDI inflow as the dependent variable and macroeconomic variables such as the output, current account balance, the real exchange rate, openness and economic freedom as explanatory variables. Annual time series data from 1995 to 2022 is used. Before carrying out the estimation, the time series properties of the data are diagnosed using unit root tests and cointegration tests. Since the data series were found to be stationary in the first difference form and the variables in the model were cointegrated, an error correction model is developed and estimated. Findings: The findings demonstrate that the size of the market (gross domestic product), current account balance and the economic freedom index significantly influence FDI inflow to Brazil. Although the signs of openness and the real exchange rate align with theoretical expectations, they do not attain statistical significance. Originality/value: To the best of the authors' knowledge, this is the first formal study on the impact of economic freedom on the FDI inflow in Brazil. The finding of this study adds value to the understanding of FDI dynamics in Brazil, highlighting the critical role of economic freedom and market size in attracting foreign investment. [ABSTRACT FROM AUTHOR]

This paper addresses the question of whether self-esteem affects women's intra-household bargaining power by using the National Survey on Women's Social Status of China (NSWSS). While providing a conceptual framework, the study employs econometric models to show that self-esteem positively affects women's intra-household bargaining power. The analyses, using an instrument-variable approach, and using different indicators of household bargaining power, further collaborate the robustness of our conclusion. Overall, the empirical study provides important insights on future academic research and policy measures in women's empowerment. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the impact of foreign direct investment (FDI) on national digital capability, specifically differentiating the impact between FDI greenfield and mergers and acquisitions (M&A). The research also investigates factors shaping digital capabilities, encompassing government transparency and absorptive capability, while exploring the mediating influence of absorptive capability in the FDI–digital capability relationship. Design/methodology/approach: An econometric model has been developed to examine the interrelationship between national digital capability, FDI inflows, national absorptive capability and government transparency. The data set encompasses 55 countries over a period of nine years (2013–2021). National digital capability data is derived from the well-established index published by the World Competitive Centre (WCC). The sources of the explanatory variables align with standard practices, drawing from reputable institutions (UNCTAD and the World Bank, among others). Findings: The findings reveal a significant positive impact of FDI, particularly in greenfield investments, on national digital capability. Government transparency and research and development (R&D) investment are crucial factors contributing to digital capabilities. Additionally, the absorptive capacity, reflected by R&D investment, also emerges as a potential moderating factor, influencing the impact of FDI inflows on digital capabilities. Practical implications: The results recommend that policymakers and stakeholders should carefully consider the role of FDI, especially in greenfield investments, as a catalyst for enhancing national digital capability. The findings also underscore the significance of promoting government transparency and directing investments towards R&D to nurture digital capabilities. Moreover, understanding the mediating role of absorptive capability can inform strategies aimed at optimizing the impact of FDI on digital capabilities. Originality/value: This study contributes uniquely to the existing literature by being the first to systematically explore the influence of FDI on national digital capability. Furthermore, it presents innovative empirical findings on the role of absorptive capability in enhancing the FDI impact on national digital capability, an area that remains relatively uncharted in current literature. [ABSTRACT FROM AUTHOR]

Nowcasting can play a key role in giving policymakers timelier insight to data published with a significant time lag, such as final GDP figures. Currently, there are a plethora of methodologies and approaches for practitioners to choose from. However, there lacks a comprehensive comparison of these disparate approaches in terms of predictive performance and characteristics. This paper addresses that deficiency by examining the performance of 17 different methodologies in nowcasting US quarterly GDP growth, including all the methods most commonly employed in nowcasting, as well as some of the most popular traditional machine learning approaches. Performance was assessed over a 20-year period, from 2002 to 2022. This span encompassed two crises, the 2008 financial crisis and the COVID crisis, as well as extended tranquil periods. The two best-performing methodologies in the analysis were long short-term memory artificial neural networks (LSTM) and Bayesian vector autoregression (Bayesian VAR). To facilitate further application and testing of each of the examined methodologies, an open-source repository containing boilerplate code that can be applied to different datasets is published alongside the paper, available at: github.com/dhopp1/nowcasting_benchmark [ABSTRACT FROM AUTHOR]

Sub-Saharan Africa (SSA) is seeing exceptional urbanization and economic expansion rates. Therefore, the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) parameters and the spatial econometric framework are used in this work to examine the influence of economic growth and urbanization on SSA's CO2 emissions. Likewise, to determine the spatial effect and understand how factors influence the spatial dependence of carbon emissions, the study builds a spatial Durbin model (SDM). In line with the findings, the spatial correlation test revealed the spatial correlations across various countries. This indicates that the changes in sub-Saharan African country's CO2 emissions impacted nearby countries and the countries themselves. Additionally, the findings reveal that, in the SSA's countries, urbanization, economic growth, industrial structure, trade, and population, excluding energy intensity, which failed the significant test, all positively influence CO2 outflows, in line with the spatial econometric model's findings. Thus, energy intensity shares an adverse impact on carbon emissions. As an outcome, energy intensity reduces carbon dioxide emissions in nearby nations and the entire region. Thus, the study recommends that policymakers account for the effects of spatial spillover when establishing low-carbon policies, encouraging a low-carbon lifestyle, promoting environmentally friendly technologies, and improving regional collaboration. [ABSTRACT FROM AUTHOR]

This study investigates the dynamics of inflation and unemployment in Ecuador using econometric models. The research is framed within the theory of the Phillips Curve and employs statistical techniques to analyze historical data. The results reveal a significant relationship between the inflation rate and the unemployment rate in the country. Additionally, ARIMA models were applied to identify patterns and trends in inflation. These findings have important implications for economic policy formulation and strategic decision-making. The need for considering multidimensional approaches and integrating multiple data sources for a comprehensive understanding of economic dynamics is emphasized. In conclusion, this study contributes to the knowledge of the Ecuadorian economy and provides valuable insights for addressing the country's economic challenges. [ABSTRACT FROM AUTHOR]

The relationship between fiscal decentralization and the extraction of income by private agents is a constant element in the debates on territorial institutional design. Theoretical literature makes ambiguous predictions about this relationship, and it has been little studied empirically. An econometric model is estimated for a panel of data from 73 developing countries for the years 1996-2019. In general, the evidence found regarding the role of spending decentralization in a lower perception of corruption is consistent. However, a decentralization of income is related to greater corruption. In this way, possible accountability systems appear independent of the generation of own resources and transfer systems are highlighted in the control of public spending. [ABSTRACT FROM AUTHOR]

Este estudio tiene por objeto medir los efectos de la participación en las cadenas globales de valor sobre la productividad total de los factores de la economía brasileña utilizando modelos de paneles dinámicos heterogéneos y métodos que permiten diagnosticar efectos a corto y largo plazo. El estudio innova en dos aspectos: se estima el impacto de las cadenas globales de valor en la productividad total de los factores sectorial brasileña, desagregando los indicadores de participación en cadenas simples y complejas desarrollados por Wang y otros (2017), y se usa una metodología inédita en el análisis entre participación en las cadenas globales de valor y productividad total de los factores sectorial brasileña. A largo plazo, esta participación parece generar ganancias de productividad con cualquier indicador considerado. Además, los mayores efectos a largo plazo se producen cuando las actividades se desarrollan en cadenas complejas. Se encuentran efectos positivos en 15 de los 31 sectores analizados. [ABSTRACT FROM AUTHOR]

The pandemic in 2020 addressed different challenges for Mexican households, especially those where some members had the disease. This article analyzes the survival strategies developed by households and communities living in the historic center of Mexico City and the municipality of Nezahualcóyotl. Three variables were established to analyze said strategies: social cohesion, neighbor intervention in collective actions, and community participation. Using data collected from the survey "Citizen Empowerment to Improve Public Security and Rule of Law in Mexico City" and econometric models, it was evident that both communities were outlined for their cohesion and neighborhood participation. In Nezahualcóyotl, family and neighborhood relations were essential, whereas in the historic center, solidarity among neighbors prevailed. [ABSTRACT FROM AUTHOR]

This paper analyses the winemaking sector in the Republic of Moldova using econometric models. The use of econometric models in agriculture involves the application of statistical methods and economic theory to analyze and model relationships in the agricultural sector. These models help researchers, policy makers and practitioners to understand the factors that influence agricultural outcomes and make informed decisions. The article presents the results of regression estimations in which the endogenous factor is the volume of overall production in agriculture, but also the volume of production in the wine sector. On the basis of official statistical data of the Republic of Moldova, the Cobb-Douglas production function was estimated, whereas exogenous factors are labor and capital used in agriculture, but also technical and scientific progress observed in agriculture. The function is used for both short-term and long-term forecasts. [ABSTRACT FROM AUTHOR]

This study aimed to analyze the factors affecting the size of nongovernmental organizations (NGOs) from a multinational perspective. Empirical analyses were conducted through econometric modeling, and the data of the 17 countries from 2003 to 2019 were used. The data was obtained from the World Bank and OECD database. We used advanced panel data estimation techniques (CUP-FM and CUP-BC) to obtain long-run coefficients. GDP per capita, general government final consumption expenditure, adult education at tertiary level, and Gini index growth declined grants by private agencies and NGOs' contribution to GDP (GinGDP) initially but after a threshold level, GinGDP increased with growth at later stages of these variables. Urban population growth, employment, and foreign population have reducing effect on the size of NGOs. The size of NGOs has bidirectional causality relationship between GDP per capita, adult population at tertiary education level, employment to population ratio, and Gini index; and unidirectional causality between urban population growth, general government final consumption expenditure, and foreign population. [ABSTRACT FROM AUTHOR]

The upgrade of industrial structure is one type of momentum for improving urban ecological efficiency, and exploring the nexus between them can help implement the concept of green development. Using data from 284 cities in China between 2004 and 2019, this research employs a series of econometric models to examine how improving industrial structure contributes to the growth of urban ecological efficiency. The research results reveal that urban ecological efficiency can be significantly improved by industrial structure upgrade, while ecological efficiency is inhibited by low-quality GDP and financial development models and insignificantly decreased by industrial structure rationalization. In addition, industrial structure upgrading has failed to play a mediating role in promoting eco-efficiency through technological innovation and the reduction of pollutant emission intensity. Moreover, officials' turnover plays a negative moderating influence on the role of industrial upgrading in increasing ecological efficiency, while environmental regulation plays the opposite role. This study further conducts triple heterogeneity tests including city size, resource endowment, and regional heterogeneity, which provide a feasible way for further implementation of relevant policies. [ABSTRACT FROM AUTHOR]

This paper focuses on returns comovements in global stock portfolios including the US Dollar as a defensive asset. The main contribution is the selection of a large set of macroeconomic and financial variables as potential drivers of these comovements and the emphasis on the predictive accuracy of proposed econometric models. One-year US Expected Inflation stands out as the most important predictor, while models including a larger number of variables yield significant predictive gains. Larger forecast errors, due to parameters instabilities, are documented during major financial crises and the COVID-19 pandemic period. Some research directions to improve the forecasting power of econometric models are discussed in the concluding section. [ABSTRACT FROM AUTHOR]

This study examines the relationships between Greek macroeconomic variables, examining before and after the euro's introduction as a currency. We conducted an extensive analysis from 1980 to 2019, examining various economic indicators such as government expenditure, unemployment rates, taxation, inflation, and national debt, employing causal and correlation analysis and econometric modeling with and without time-varying effects. The results revealed a significant correlation between the introduction of the euro and a tighter relationship between government spending and unemployment levels, while one more remarkable point was that higher government spending or debt reduction initiatives appeared to positively impact joblessness, particularly in the context of the euro. Our research underscored the correlation between national debt and government spending as increased debt led to reduced government expenditure and vice versa. Unemployment cited an increased impact on government spending right after the euro adoption, and on the other hand, the effect of unemployment on government spending decreased. The debt–government spending nexus was decreasing for many years before the euro adoption, while just before the euro adoption, the relationship between debt and government spending was rather stable. Finally, during the euro adoption, the effect of inflation on tax increased, while the corresponding inflation tax remained stable. Our findings have significant implications for policymakers shaping the economic strategies in Greece as they point out the necessity for stable and balanced approaches that manage government spending and debt to address unemployment effectively. [ABSTRACT FROM AUTHOR]

With the active promotion of the "carbon peaking and carbon neutrality" goals, science and technology finance (STF) is the important driving force of low-carbon development, and financial networks facilitate the aggregation and transformation of resources in space, so it is of great theoretical and practical significance to investigate the impact of science and technology finance networks (STFN) on carbon emissions (CE). Based on the 30 provinces of China from 2011 to 2019, this article used the STF development level in each province as the main indicator to construct the STFN. The complex network analysis and econometric models are combined, with the weighted degree values and betweenness centrality selected as typical network structure indicators incorporating into the econometric model to explore their impact on CE. Then, the Geographically and Temporally Weighted Regression (GTWR) model is applied to analyse the spatio-temporal heterogeneity of influencing factors. The results show the following: (1) From 2011 to 2019, the spatial structure of China's STFN has changed significantly, and the status of the triangle structure consisting of Beijing–Tianjin–Hebei (BTH)–Yangtze River Delta (YRD)–Pearl River Delta (PRD) is gradually consolidated in the overall network, and the network structure tends to be stable. (2) The results of the benchmark regression show that the weighted degree value of the STFN has a significant inhibitory effect on CE, while betweenness centrality shows a certain positive effect on CE. (3) The weighted degree value has a more significant effect on CE reduction in the eastern region, while the betweenness centrality has a more significant effect on CE reduction in the central and western regions, but shows a significant promotion effect in the eastern region. (4) There is spatio-temporal heterogeneity in the effects of residents' affluence, energy consumption, industrial structure, and environmental pollution on CE. [ABSTRACT FROM AUTHOR]

The impact of urbanization on the environmental quality of ecologically fragile areas has long been ambiguous. With a focus on the human–environment interaction in 95 counties of Hengduan Mountain, an ecologically fragile region in southwestern China, in this study, we clarify the impact and mechanism of urbanization on environmental quality through the environmental regulation effect, using econometric models and county-level panel data from 2010 to 2019. The results of this study show that: (1) urbanization and environmental regulation have increased over this 10-year period within the study area and regional differences in environmental quality have decreased; (2) urbanization significantly contributes to environmental quality, with heterogenous effects on different environmental elements—increasing the proportion of wetlands and green areas per capita but suppressing vegetation coverage and production efficiency; and (3) environmental regulation is an important mechanism for urbanization to improve environmental quality; however, there are negative externalities on neighboring areas. The results of this study show that urbanization and environmental quality are not always mutually exclusive, thus providing a reference for the development of pro-environmental urbanization to improve sustainable development in ecologically fragile areas. [ABSTRACT FROM AUTHOR]

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In this research, we assess the international trade implications of Ukraine's pursuit of self‐determination through the lens of the EU–Ukraine Association Agreement and the contemporaneous war with Russia in the years preceding the 2022 Russian Invasion. To do so, we construct a dataset with annual, bilateral export and import flows for Ukraine and a set of comparator countries at the 6‐digit level of the Harmonised Tariff Schedule (HS) for years 2000–2019. Using this data, we nest a difference‐in‐difference design within a series of econometric gravity models to estimate the effects on the sectoral and geographic composition of Ukrainian trade. Our results indicate a major re‐direction of exports towards the EU and away from Russia. Trade outcomes are one of many considerations that led to Ukraine's pursuit of EU integration. [ABSTRACT FROM AUTHOR]

Copyright of Economics & Environment / Ekonomia i Środowisko is the property of Fundacja Ekonomistow Srodowiska i Zasobow Naturalnych 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.)

Using firm-level data from public listed large non-financial corporations (NFC) this paper studies the impact of financialization on productive investment in Latin America in the last two decades. After considering the main stylized facts on investment, profits and financial incomes from balance sheet information, we estimate an econometric model of investment determinants to measure the impact of financialization over large NFC. Similar to developed economies, evidence suggest that dividends payments and financial income has negative affect investment. But, in Latin America, restricted only for large and very large firms. Besides this, we also registered that non-current financial assets holding negatively affects productive investment. This seems to be especially relevant in the context of the carry trade boom in the region after 2009. These findings provide new insights on the negative effects of the international dimension of financialization on emerging countries productive investment. [ABSTRACT FROM AUTHOR]

Copyright of Izmir Journal of Economics is the property of Dokuz Eylul University, Faculty of Economics & Administrative Sciences 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.)

This paper provides a review of the development of the non‐fungible tokens (NFTs) market, with a particular focus on its pricing determinants, its current applications, and its future opportunities. We investigate the current state of the NFT markets and highlight the perception and expectations of investors toward these products. We summarize and compare the financial and econometric models that have been used in the literature for the pricing of non‐fungible tokens with a special focus on their predictive performance. We design a framework that can help to understand the price formation of NFTs. We further aim to shed light on the value‐creating determinants of NFTs in order to better understand investors' behavior on the blockchain. [ABSTRACT FROM AUTHOR]

Based on a multisector general equilibrium framework, we show that the sectoral elasticity of substitution plays the key role in the evolution of asymmetric tails of macroeconomic fluctuations and the establishment of robustness against productivity shocks. A non-unitary elasticity of substitution renders a nonlinear Domar aggregation, where normal sectoral productivity shocks translate into non-normal aggregated shocks with variable expected output growth. We empirically estimate 100 sectoral elasticities of substitution, using the time-series linked input-output tables for Japan and find that the production economy is elastic overall, relative to a Cobb-Douglas economy with unitary elasticity. In addition to the previous assessment of an inelastic production economy for the USA, the contrasting tail asymmetry of the distribution of aggregated shocks between the USA and Japan is explained. Moreover, the robustness of an economy is assessed by expected output growth, the level of which is led by the sectoral elasticities of substitution under zero-mean productivity shocks. [ABSTRACT FROM AUTHOR]

Generative adversarial networks (GANs) have been extremely successful in generating samples, from seemingly high‐dimensional probability measures. However, these methods struggle to capture the temporal dependence of joint probability distributions induced by time‐series data. Furthermore, long time‐series data streams hugely increase the dimension of the target space, which may render generative modeling infeasible. To overcome these challenges, motivated by the autoregressive models in econometric, we are interested in the conditional distribution of future time series given the past information. We propose the generic conditional Sig‐WGAN framework by integrating Wasserstein‐GANs (WGANs) with mathematically principled and efficient path feature extraction called the signature of a path. The signature of a path is a graded sequence of statistics that provides a universal description for a stream of data, and its expected value characterizes the law of the time‐series model. In particular, we develop the conditional Sig‐W1$W_1$ metric that captures the conditional joint law of time series models and use it as a discriminator. The signature feature space enables the explicit representation of the proposed discriminators, which alleviates the need for expensive training. We validate our method on both synthetic and empirical dataset and observe that our method consistently and significantly outperforms state‐of‐the‐art benchmarks with respect to measures of similarity and predictive ability. [ABSTRACT FROM AUTHOR]

Copyright of Religación: Revista de Ciencias Sociales y Humanidades is the property of Religacion: Revista de Ciencias Sociales y Humanidades 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.)

With the acceleration of urbanization in recent years, China has witnessed large-scale construction across its provinces, generating massive amounts of construction waste that pose challenges to environmental protection and sustainable development. This study evaluated the impact of construction waste policy intensity on its environmental efficiency. Firstly, the content analysis method was used to analyze the construction waste policy text quantitatively. Second, this study constructed a slack-based measure (SBM) model based on data envelopment analysis (DEA), considering resource input and construction waste output to measure environmental efficiency. Finally, we built and tested an econometric model of how policies affect environmental efficiency using the system generalized method of moments (SYS-GMM). The findings indicate a non-linear U-shaped link between policy intensity and environmental efficiency. Among all five control variables, population density, urbanization level, and technological innovation enhance environmental efficiency, while economic development and highway density will lower it. This study advances the research on construction waste policies and offers some insights for the construction industry to pursue sustainable development. [ABSTRACT FROM AUTHOR]

As the main body that unites farmers internally and connects with markets externally, professional farmer cooperatives are playing an increasingly important role around the world. In order to investigate the significant factors influencing this subject in agricultural socialization services, 487 cooperatives in Heilongjiang Province were selected for investigation. The field survey found that many of the better-developed cooperatives have a certain degree of inadequacy in the performance of their service functions. This paper proposes that viability and government support are important factors influencing the realization of the service function of farmer professional cooperatives. Based on the empirical analysis of sample survey data and econometric models, it was demonstrated that the experience of the chairman, the number of board members, the distribution of members, the scale of land operation, profitability, and the institutional arrangement of the cooperatives are an important embodiment of the viability of the cooperatives. These factors significantly influence the service function of cooperatives in different sections, including pre-production, mid-production, and post-production. Moreover, obtaining external support from the government is necessary for cooperatives at their primary stage of development, especially regarding relevant training, which can facilitate the realization of the service functions of cooperatives in all aspects. [ABSTRACT FROM AUTHOR]

In Italy, productivity had a turning point in the second half of the 1990s, when it went into decline. During the last few years, productivity in Italy has been sluggish, with an even more marked decreasing trend. Studies on companies' performances, regarding productivity growth, have highlighted different aspects and various concomitant factors. Many analyses focused on the lack of investment and productivity differentials related to export activity. Indeed, productivity growth is a multidimensional problem that can be approached by following the evolution of various factors, such as profitability, labor costs, growth of aggregate demand, and investment. This work aims at identifying and analyzing, at the microlevel, the determinants of labor productivity over the whole period 2004–2013, and in the two sub-periods before and after the 2007 crisis. The goal is to determine the factors that have most influenced the change in the productivity of manufacturing companies in the period considered. Moreover, we focus on those elements that permit firms to survive a crisis, and on the presence of other factors that can, instead, accelerate a crisis. To carry out this analysis, firms have to be tracked over time, so a panel of companies' financial reports was used to create a transition matrix, and econometric models are proposed to estimate productivity determinants. We highlight the centrality of the labor market in explaining the main economic evolution, also in recent years, and the factors that have pushed Italy's move towards a labor-intensive development model. [ABSTRACT FROM AUTHOR]

The subject of this study is the insider trading behaviors within the US financial markets, with a focus on transactions by politicians and public officials, and their implications for global economic stability. The purpose is to investigate and analyze these transactions for ethical and legal challenges, and to evaluate their potential impact on market integrity and investor trust. The relevance of this research arises from the substantial influence these figures have on market dynamics, the legal nuances involved in their financial activities, and the broader implications for market transparency and fairness. The scientific novelty is established using econometric modeling and data analytics, particularly the analysis of trading behavior that potentially circumvents the Stop Trading on Congressional Knowledge (STOCK) Act. The methods employed include a Python tool to extract data from financial disclosures and ordinary least squares (OLS) regression to analyze key indicators of insider behavior. The results indicate a significant proportion of trades, approximately 86.67%, were conducted by politicians with noted STOCK Act violations, highlighting a potential gap in the enforcement of current laws and reporting standards. The authors concluded that the findings call for stricter law enforcement, a reevaluation of reporting standards, and comprehensive financial disclosures to maintain market integrity, alongside an urgent need for improved regulatory measures and enhanced transparency mechanisms to mitigate the risks associated with insider trading by individuals in positions of power.