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This article examines how activist networks contribute to the spatial diffusion of mining conflicts. We conduct a spatial econometric analysis of 590 geolocated mining properties in five countries of Latin America (Argentina, Brazil, Chile, Mexico, and Peru), using the univariate local joint count test and the spatial autoregressive probit method. Empirically, the analysis provides strong and generalizable evidence for the spatial diffusion of conflicts related to mining, namely that a social conflict in a given mine site can be considered an independent cause of a distinct social conflict in another proximate mine site that is additional to the localized factors considered in the quantitative and qualitative literature to date. Moreover, we show that the diffusion effect is most evident at a territorial level of analysis, which leads us to make the theoretical argument that the diffusion of collective action depends on the geospatial resonance of activist claims and mobilizing frames based on a common territorial experience among otherwise distant groups. The concept of geospatial resonance contributes to contemporary efforts to conceptually and empirically specify the limitations to a relational understanding of scale. [ABSTRACT FROM AUTHOR]

Hallux valgus is a common condition where the subluxation of the first metatarsophalangeal joint and lateral deviation of the hallux at the interphalangeal joint creates difficulty with footwear fit. Footwear and foot orthoses are commonly prescribed nonsurgical treatments for hallux valgus. Do extra-width footwear and foot orthoses influence peak pressure at the medial aspect of the metatarsophalangeal and interphalangeal joints in women with hallux valgus? Community-dwelling women with symptomatic hallux valgus underwent gait testing when wearing their own shoes and when wearing extra-width footwear fitted with three-quarter length, arch-contouring prefabricated foot orthoses. Peak pressure (kPa) on the medial aspect of the metatarsophalangeal and medial interphalangeal joints and on the plantar surface of the foot (hallux, lesser toes, metatarsophalangeal joint 1, metatarsophalangeal joints 2–5, midfoot and heel) were measured using the novel pedar®-X system with the pedar® pad and pedar® insole, respectively (Novel, GmbH, Munich, Germany). Paired samples t -tests were used to calculate the differences between the two conditions, and the magnitude of observed differences was calculated using Cohen's d. We tested 28 participants (aged 44–80 years, mean 60.7, standard deviation 10.7). Compared to their own footwear, wearing the intervention footwear and orthoses was associated with a statistically significant decrease in pressure on the medial aspect of the metatarsophalangeal joint (58.3 ± 32.8 versus 42.6 ± 32.8, p =0.026, d =0.49), increased pressure under the midfoot (70.7 ± 25.7 versus 78.7 ± 23.6, p =0.029, d =0.33) and decreased pressure underneath the heel (137.3 ± 39.0 versus 121.3 ± 34.8, p =0.019, d =0.45). The intervention footwear and orthoses significantly decreased peak pressure on the medial aspect of the first metatarsophalangeal joint but had no significant effect on the interphalangeal joint. Further studies are required to determine whether these changes are associated with improvements in symptoms associated with hallux valgus. • We investigated peak medial and plantar pressure in women with hallux valgus. • The intervention decreased medial pressure at the first metarsophalangeal joint. • The intervention increased midfoot and decreased heel plantar pressure. • Women with hallux valgus may benefit from extra-width footwear and orthoses. [ABSTRACT FROM AUTHOR]

Though the literature largely recognizes adult drug treatment courts (ADCs) as beneficial to participants, with lower rates of recidivism and drug use, the question remains of how ADCs impact communities and how other institutions (e.g., law enforcement) react to their presence. This study extends previous work estimating higher arrests associated with ADCs, particularly for crimes involving higher degrees of law enforcement discretion. Results indicate lower drug possession arrest rates for White residents in rural communities, and higher in urban areas, generally, but especially for Black citizens. Though the exact source of these changes has yet to be determined, current analysis indicates larger effect sizes for arrests scaled per officer, as compared to per population, pointing toward changes in law enforcement behavior. [ABSTRACT FROM AUTHOR]

Quality control charts aim at raising an alarm as soon as sequentially obtained observations of an underlying random process no longer seem to be within stochastic fluctuations prescribed by an in-control scenario. Such random processes can often be modelled using the concept of stationarity, or even independence as in most classical works. An important out-of-control scenario is the changepoint alternative, for which the distribution of the process changes at an unknown point in time. In his seminal 1954 Biometrika paper, E. S. Page introduced the famous cumulative sum control charts for changepoint monitoring. Innovatively, decision rules based on cumulative sum procedures took the full history of the process into account, whereas previous procedures were based only on a fixed and typically small number of the most recent observations. The extreme case of using only the most recent observation, often referred to as the Shewhart chart, is more akin to serial outlier than changepoint detection. Page's cumulative sum approach, introduced seven decades ago, is ubiquitous in modern changepoint analysis, and his original paper has led to a multitude of follow-up papers in different research communities. This review is focused on a particular subfield of this research, namely nonparametric sequential, or online, changepoint tests that are constructed to maintain a desired Type-1 error as opposed to the more traditional approach seeking to minimize the average run length of the procedures. Such tests have originated at the intersection of econometrics and statistics. We trace the development of these tests and highlight their properties, mostly using a simple location model for clarity of exposition, but we also review more complex situations such as regression and time series models. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI)-based applications contribute to monitoring financial transactions and detect fraudulent activity in real-time by analyzing transaction patterns, consumer behavior, and other statistics, making them essential for quickly addressing potential threats in the fight against financial crime dynamics. Leveraging financial crime systems with intelligent supervised neuro-structures exploiting nonlinear autoregressive exogenous networks integrating damped least square (NARX-DLS) optimization methods to achieve an appropriate degree of accuracy and adaptability for the estimation of complex nonlinear financial crime differential systems (NFCDSs). The representative NFCDS for financial crime indicators is expressed as susceptible individuals, financial criminals, individuals under prosecution, imprisoned individuals, and honest individuals. The Adams numerical solver accomplishes the acquisition of synthetic data for the layer structure NARX-DLS algorithm execution to solve NFCDSs for various financial crime parameters, such as recruitment rate, influence rate, conversion rate to honest people, financial criminal prosecution rate per capita, discharge and acquittal rate from prosecutions, percentage of discharge rate from prosecution, transition rate to prison, and freedom rate. A sturdy overlap between the solutions of NARX-DLSs and the reference numerical results of NFCDSs implies that the error value is close to a desirable value of zero. The effectiveness of the NARX-DLSs is evidenced by including a variety of assessment metrics that carefully examine the model’s correctness and efficacy, including mean square error-based convergence arches, adaptive regulating parameters, error distribution, and input-error/cross-correlation analyses. [ABSTRACT FROM AUTHOR]

Is the strength of favoritism from social ties gender-dependent? Collecting election data of the most distinguished Chinese scientific academies over a decade, we find favoritism from some social connections, such as sharing a hometown, college, or employer, between recruiters and candidates, can benefit men more than women. These results are robust to conservative econometrics specifications, alternative measures of social connections, quality of peer candidates, and gender composition of recruitment teams. As a result, women need better objective scientific achievements to succeed; most of this gender disparity is attributed to gender-specific favoritism. These results indicate the existence of gender imparity after controlling for social connections. [ABSTRACT FROM AUTHOR]

This paper conducts a brief survey of spatial unit roots within the context of spatial econometrics. We summarize important concepts and assumptions in this area and study the parameter space of the spatial autoregressive coefficient, which leads to the idea of spatial unit roots. Like the case in time series, the spatial unit roots lead to spurious regression because the system cannot achieve equilibrium. This phenomenon undermines the power of the usual Ordinary Least Squares (OLS) method, so various estimation methods such as Quasi-maximum Likelihood Estimate (QMLE), Two Stage Least Squares (2SLS), and Generalized Spatial Two Stage Least Squares (GS2SLS) are explored. This paper considers the assumptions needed to guarantee the identification and asymptotic properties of these methods. Because of the potential damage of spatial unit roots, we study some test procedures to detect them. Lastly, we offer insights into how to relax the compactness assumption to avoid spatial unit roots, as well as the relationship between spatial unit roots and other models, such as the Spatial Dynamic Panel Data (SDPD) model and Lévy–Brownian motion. [ABSTRACT FROM AUTHOR]

The contribution of this study is to disclose the main determinants of the duration of the U.S. antitrust federal court decisions, an issue that has been nearly overlooked by most related studies. As an indirect measure for the time needed to dispose cases, this study uses the duration of the case from the filing of the complaint to the date of the opinion. Using this metric, we employ parametric and nonparametric panel data techniques on a sample of 613 appellate court proceedings on U.S. antitrust cases during the period 1995–2018. The empirical research reveals spatial heterogeneity in terms of case duration among the circuits of the appellate U.S. courts. The econometric analysis supports that the duration of appellate antitrust court decisions depends on administrative-related factors including the way the case was filed in the circuit, the jurisdiction in the case, the " pro se " representation of the undertakings, and the nature of the final judgment. Lastly, based on the flexible semi-parametric analysis, we argue that the impact of these parameters on case duration is linear, regardless of the specification of the parametric part of the model. [ABSTRACT FROM AUTHOR]

In this paper, we utilize the Chicago Board Option Exchange (CBOE) implied volatility indices to estimate the time-frequency information transmission among financial markets from 01.08.2008 to 31.10.2019. In doing so, we utilize the rolling window wavelet correlation (RWWC), Diebold & Yilmaz (The Economic Journal 119: 158–171, 2012), and Barunik & Krehlik (Journal of Financial Econometrics 16: 271–296, 2018). Our empirical findings suggest short-term and long-term dynamic connectedness between implied volatility indices of alternative assets. The long-term analysis findings suggest potential hedging and diversification opportunities that can be exploited by taking offsetting positions across volatility indices. The findings confirm heterogeneity between short-term and long-term connectedness results. Our findings also show superior out of sample hedging effectiveness of GVZ. The implications of the findings are further discussed in the paper. [ABSTRACT FROM AUTHOR]

In this paper we show how a variant of Stone and Brook's continuum regression criterion may be used to define the least variance ratio estimator of the slope parameters of the simultaneous equations model of econometrics. As a by-product of this approach we identify a family of estimators (distinct from the family of k-class estimators) to which it and two variants of the orthogonal least squares estimator belong. We also take the opportunity to mention several features of linear unbiased scalar residuals omitted from an earlier paper. [ABSTRACT FROM AUTHOR]

Ensemble methods, such as Bagging, Boosting, or Random Forests, often enhance the prediction performance of single learners on both classification and regression tasks. In the context of regression, we propose a gradient boosting‐based algorithm incorporating a diversity term with the aim of constructing different learners that enrich the ensemble while achieving a trade‐off of some individual optimality for global enhancement. Verifying the hypotheses of Biau and Cadre's theorem (2021, Advances in contemporary statistics and econometrics—Festschrift in honour of Christine Thomas‐Agnan, Springer), we present a convergence result ensuring that the associated optimization strategy reaches the global optimum. In the experiments, we consider a variety of different base learners with increasing complexity: stumps, regression trees, Purely Random Forests, and Breiman's Random Forests. Finally, we consider simulated and benchmark datasets and a real‐world electricity demand dataset to show, by means of numerical experiments, the suitability of our procedure by examining the behavior not only of the final or the aggregated predictor but also of the whole generated sequence. [ABSTRACT FROM AUTHOR]

Morocco has integrated the human development paradigm into their country-wide planning goals. The 2004 Moroccan census measured HDI for every commune in Morocco, the smallest spatial unit for which data are available. However, when the 2014 Moroccan census was released HDI values were omitted. To measure the change in HDI over the 10-year period, this article uses spatial econometric models along with the RandomForest algorithm in order to make out-of-sample predictions for 2014 HDI scores at the Moroccan commune level. The article concludes that in certain situations RandomForest can outperform spatial econometric models, and discusses the benefits this approach. [ABSTRACT FROM AUTHOR]

An online changepoint detection procedure based on conditional expectiles is introduced. The key contribution is threefold: nonlinearity of the underlying model improves the overall flexibility while a parametric form of the unknown regression function preserves a simple and straightforward interpretation; The conditional expectiles, well-known in econometrics for being the only coherent and elicitable risk measure, introduce additional robustness—especially with respect to asymmetric error distributions common in various types of data; The proposed statistical test is proved to be consistent and the distribution under the null hypothesis does not depend on the functional form of the underlying model nor the unknown parameters. Empirical properties of the proposed real-time changepoint detection test are investigated in a simulation study and a practical applicability is illustrated using the Covid-19 prevalence data from Prague. [ABSTRACT FROM AUTHOR]

Understanding students’ attitudes towards a subject is crucial for optimising their learning experiences. Exploring the impact of different teaching methods on these attitudes remains an underexplored yet vital aspect. This study delves into the effects of the flipped classroom model on students’ attitudes towards Econometrics. The research focuses on a sample of undergraduate students majoring in Economics and Economics and Tourism, all enrolled in an Econometrics course. It compares traditional teaching methods with the flipped classroom approach. This study investigates the influencing variables on attitudinal dimensions, emphasising the impact of attending a flipped course. The results reveal a significant positive impact of the flipped classroom on most attitudinal dimensions, except for the Effort dimension. The findings suggest that the flipped classroom enhances students’ perception of their capability to learn econometrics. [ABSTRACT FROM AUTHOR]

This paper describes a simple and interesting application of structural equation modeling for a single lecture in an undergraduate econometrics course to introduce students to the concept of using data to recover latent variables. The application centers around using hourly observations on ride wait times at Disney's Magic Kingdom to infer how crowded it is at the theme park. Pedagogically, the material is presented in the context of the linear regression model, so the discussion works to enhance students' understanding of core material, not to introduce new disparate methods. The application provides interesting economic-based insights, like which ride's wait times are categorically most informative about how crowded it is at the park. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate the impact of digital investment transactions on the trading volume and profitability of banks' asset management companies. The observations of the variables in the study are compiled for 9 banks between the 1st quarter of 2015 and the 1st quarter of 2023, and a balanced panel data set containing 297 observations is formed. Panel ARDL model, cointegration analysis and correlation analysis are utilized in the study. According to descriptive statistics and normal distribution statistics, Total Trading Volume variable is normally distributed, while Asset Management Company Profit Amount, Bond Trading Volume, Equity Trading Volume and VIOP Trading Volume variables are not normally distributed but close to normal. According to the findings of the CD Horizontal Cross-Section Dependence Test, it is determined that there is horizontal cross-section dependence for Total Trading Volume and Asset Management Company Profit Amount variables and other variables do not vary across units. According to the findings of the IPS (2003), LLC (2002) and CADF (2007) 2nd generation panel unit root tests for the variables Total Trading Volume and Portfolio Management Company Profit Amount, the dependent variables of the study were found to be non-stationary at the level and stationary at the first cyclical difference (Total Trading Volume, Portfolio Management Company Profit Amount). According to the findings of Breitung (1991) and HarrisTzavalis (1999) unit root tests, which are among the first generation panel unit root tests for variables with unit constant and time variables, the variables with unit constant and time variables in the models, namely Bond Trading Volume, Equity Trading Volume, VIOP Trading Volume and Mutual Fund Trading Volume, are found to be non-stationary in level but stationary in first-cycle difference. According to the findings of the correlation analysis between variables, there is a statistically significant, moderate relationship between Total Trading Volume and Bond Trading Volume, VIOP Trading Volume and Mutual Fund Trading Volume at the 1% significance level. There is no statistically significant relationship between Total Trading Volume and Equity Trading Volume. While there are statistically significant low to medium positive relationships between Asset Management Company Profit Amount variable and Bond Trading Volume, Mutual Fund Trading Volume and Mutual Fund Trading Volume at 1% significance level, there is no statistically significant relationship between Asset Management Company Profit Amount and Equity Trading Volume. When the relationships between independent variables are analyzed, there is a statistically significant and quite high relationship between Bond Trading Volume and VIOP Trading Volume and Mutual Fund Trading Volume at the 1% significance level. [ABSTRACT FROM AUTHOR]

The study undertakes a spatial analysis of the total fertility rate in Hungary. The authors examine the dynamics of the indicator, its basic spatial distribution, and the differences between the periods. They show the districts where the total fertility rate significantly differs from the values of the neighbouring regions. Theoretically, the fertility data of each district should be similar to the values of the neighbouring districts - based on Waldo Tobler's (1970) „First Law of Geography". Where this is not the case, the most important fault lines can be observed. The analysis, presents the spatial pattern deter mined by the total fertility rate using two different spatial statistical methods. Finally, with the help of a spatial econometric model, the authors explain the spatial distribution of the total fertility rate, and present findings that are perhaps worthy of consideration. [ABSTRACT FROM AUTHOR]

This article analyzes the relationship between the services sector and Ecuadorian economic growth using cointegration and causality econometric techniques from 1990-2018. The results indicate that services as a whole, particularly trade and transportation, positively impact economic growth in the long run. However, in the short term, services as a whole have a negative effect, which may be explained by the continuous deterioration of their productivity. Meanwhile, there is a causality effect ranging from trade to economic growth, and from GDP per capita to services as a whole and transportation. [ABSTRACT FROM AUTHOR]

Partially linear models find extensive application in biometrics, econometrics, social sciences, and various other fields due to their versatility in accommodating both parametric and nonparametric elements. This study aims to establish statistical inference for the parametric component effects within these models, employing a nonparametric empirical likelihood approach. The proposed method involves a projection step to eliminate the nuisance nonparametric component and utilizes an empirical-likelihood-based technique, along with the Bartlett correction, to enhance the coverage probability of the confidence interval for the parameter of interest. This method demonstrates robustness in handling normally and non-normally distributed errors. The proposed empirical likelihood ratio statistic converges to a limiting chi-square distribution under certain regulations. Simulation studies demonstrate that this method provides better inference in terms of coverage probabilities compared to the conventional normal-approximation-based method. The proposed method is illustrated by analyzing the Boston housing data from a real study. [ABSTRACT FROM AUTHOR]

The Sharpe ratio function is a commonly used risk/return measure in financial econometrics. To estimate this function, most existing methods take a two-step procedure that first estimates the mean and volatility functions separately and then applies the plug-in method. In this paper, we propose a direct method via local maximum likelihood to simultaneously estimate the Sharpe ratio function and the negative log-volatility function as well as their derivatives. We establish the joint limiting distribution of the proposed estimators, and moreover extend the proposed method to estimate the multivariate Sharpe ratio function. We also evaluate the numerical performance of the proposed estimators through simulation studies, and compare them with existing methods. Finally, we apply the proposed method to the three-month US Treasury bill data and that captures a well-known covariate-dependent effect on the Sharpe ratio. [ABSTRACT FROM AUTHOR]

Pragmatic cancer screening trials mimic real-world scenarios in which patients and doctors are the ultimate arbiters of treatment. Intention-to-screen (ITS) analyses of such trials maintain randomization-based apples-to-apples comparisons, but differential adherence (the failure of subjects assigned to screening to get screened) makes ITS effects hard to compare across trials and sites. We show how instrumental variables (IV) methods address the nonadherence challenge in a comparison of estimates from 17 sites in five randomized trials measuring screening effects on colorectal cancer incidence. While adherence rates and ITS estimates vary widely across and within trials, IV estimates of per-protocol screening effects are remarkably consistent. An application of simple IV tools, including graphical analysis and formal statistical tests, shows how differential adherence explains variation in ITS impact. Screening compliers are also shown to have demographic characteristics similar to those of the full trial study sample. These findings argue for the clinical relevance of IV estimates of cancer screening effects. [ABSTRACT FROM AUTHOR]

In many practical situations, we need to change the spatial distribution of some goods. In such situations, it is desirable to minimize the overall transportation costs. In the 1-D case, the smallest transportation cost of such a change is proportional to what is known as the Wasserstein metric. The same metric can be used to describe the distance between two probability distributions. In the last decades, it turned out that this metric can be successfully used in many economic applications beyond transportation. These successes are somewhat of a mystery: in principle, there are many different metrics on the set of all probability distributions, and it is not immediately clear why namely Wasserstein metric is so successful. In this paper, we show that the Wasserstein metric naturally appears in decision making situations. This fact explains the usefulness of the Wassterstein's metric in economic applications. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine Turkey's position and role in international hen egg trade and, based on the findings, to help policy makers, industry stakeholders and researchers understand the dynamics of the global egg market and identify opportunities for market expansion and sustainable growth. Study is prepared using secondary data obtained from national and international online sources and previous academic studies on the subject. Despite the fluctuations experienced after 2018, Turkey, being the world's 4th largest egg exporter as of 2022 shows its place and importance in the global market. Furthermore, the increase in demand for high-quality table eggs from the Middle East and Arabian Peninsula countries after 2018 reveals the opportunity for Turkey to expand its market share and prove itself as a reliable supplier. In conclusion; Turkey's egg producing sector is a net exporter sector. Even considering the relatively small amount of import of eggs for incubation, it is understood that Turkey is a reliable supplier. In addition, it is known that the current import of eggs for incubation is mostly for the production of broiler chickens rather than table eggs. In order to ensure Turkey's sustainable egg exports; It is important that comprehensive studies be implemented jointly by the private sector and public stakeholders in order to increase the capacity of value-added egg products and to identify alternative target markets and ensure entry into these markets. [ABSTRACT FROM AUTHOR]

In statistical analysis, researchers often perform coordinatewise Gaussianization such that each variable is marginally normal. The normal score transformation is a method for coordinatewise Gaussianization and is widely used in statistics, econometrics, genetics and other areas. However, few studies exist on the theoretical properties of the normal score transformation, especially in high-dimensional problems where the dimension p diverges with the sample size n. In this article, we show that the normal score transformation uniformly converges to its population counterpart even when log p = o (n / log n) . Our result can justify the normal score transformation prior to any downstream statistical method to which the theoretical normal transformation is beneficial. The same results are established for the Winsorized normal transformation, another popular choice for coordinatewise Gaussianization. We demonstrate the benefits of coordinatewise Gaussianization by studying its applications to the Gaussian copula model, the nearest shrunken centroids classifier and distance correlation. The benefits are clearly shown in theory and supported by numerical studies. Moreover, we also point out scenarios where coordinatewise Gaussinization does not help and even causes damages. We offer a general recommendation on how to use coordinatewise Gaussianization in applications. for this article are available online. [ABSTRACT FROM AUTHOR]

We developed a command, csa2sls, that implements the complete subset averaging two-stage least-squares (CSA2SLS) estimator in Lee and Shin (2021, Econometrics Journal 24: 290–314). The CSA2SLS estimator is an alternative to the two-stage least-squares estimator that remedies the bias issue caused by many correlated instruments. We conduct Monte Carlo simulations and confirm that the CSA2SLS estimator reduces both the mean squared error and the estimation bias substantially when instruments are correlated. We illustrate the usage of csa2sls in Stata with an empirical application. [ABSTRACT FROM AUTHOR]

This paper forecasts the energy efficiency coefficients at the Polish province level (NUT-2), based on imperfect and contradictory knowledge. On the one hand, we have information on the aggregated national energy efficiency coefficients in the industrial, transport, household, and service sectors. On the other hand, we also have information on the energy intensity at the Polish province level. Since the two samples are of different natures and known with uncertainty, we are obviously dealing with an inverse stochastic problem whose solution requires particular statistical devices. The applied technique of non-extensive cross-entropy econometrics generalizes the Shannon-Kullback-Leibler approach based on the Gaussian assumptions. Its justification is explained throughout this paper from both methodological and empirical points of view. The model forecasts lead to the high-value energy efficiency estimates from quasi-unstructured sets of information. This constitutes the main contribution of this research. These outputs should provide energy policy units with valuable new devices for the optimization of the energy management processes on a disaggregated local level where, by contrast, different agents and households act decisively. On a global level, the proposed technique can be applied in different EU countries and elsewhere, in the context of experimental official statistics. [ABSTRACT FROM AUTHOR]

The paper has two main objectives: one, to investigate if inter-bank horizontal dispersion in the remuneration of executives has any significant influence on bank performance. And two, to explore various situations with respect to board quality, agency cost, and government ownership under which the dispersion-performance nexus is moderated. The paper employs a two-step system GMM of (Blundell and Bond, Journal of Econometrics 8:115–143, 1998) to account for the possible endogeneity issues, and Driscoll–Kraay's non-parametric matrix estimator to account for cross-sectional dependence. The findings show that horizontal pay dispersion has a negative influence on bank performance. It produces evidence in favor of the "equity fairness theory" that higher pay dispersion would incentivize them to engage in excessive risk-taking for maximizing their personal interests, which emerges to be detrimental to the bank's performance. Further evidence of moderating effect shows that in the presence of effective board oversight, pay dispersion exerts a favorable influence on the performance of Indian banking firms. The research has significant policy ramifications for regulators to apprehend the undesirable implications of pay dispersion on bank performance and initiate quick action to scrutinize the governance practices of higher-paying banks. [ABSTRACT FROM AUTHOR]

Testing density-dependence and path-dependence in long-term population dynamics under differentiated local contexts contributes to delineate the changing role of socioeconomic forces at the base of regional disparities. Despite a millenary settlement history, such issue has been rarely investigated in Europe, and especially in highly divided countries such as those in the Mediterranean region. Using econometric modeling to manage spatial heterogeneity, our study verifies the role of selected drivers of population growth at ten times between 1921 and 2021 in more than 8000 Italian municipalities verifying density-dependent and path-dependent dynamics. Results of global and quantile (spatial) regressions highlight a differential impact of density and (lagged) population growth on demographic dynamics along the urban cycle in Italy. Being weakly significant in the inter-war period (1921–1951), econometric models totalized a high goodness-of-fit in correspondence with compact urbanization (1951–1981). Model's fit declined in the following decades (1981–2021) reflecting suburbanization and counter-urbanization. Density-dependence and path-dependence were found significant and, respectively, positive or negative, with compact urbanization, and much less intense with suburbanization and counter-urbanization. A spatial econometric investigation of density-dependent and path-dependent mechanisms of population dynamics provided an original explanation of metropolitan cycles, delineating the evolution of socioeconomic (local) systems along the urban-rural gradient. [ABSTRACT FROM AUTHOR]

This work considers the impact of the different job quality dimensions on Eurozone job satisfaction through the European Working Conditions Survey-2015. The econometric analysis, using a probit model (marginal effects), reveals that dimensions associated with Social environment, Skills and discretion, Prospects, and Earnings have a positive and significant impact on job satisfaction. The impact of Work intensity is negative and those related to Physical environment and Working time quality do not have a significant impact on job satisfaction. Regarding the differential impact of the different dimensions on the public and private sectors, both Prospects and Social environment are notably higher in the private sector. The greater impact of the first index is not justified, as is the case with the Social environment, by a lower index but, probably, by the greater variability of the index in the private sector. Our work emphasizes the relevance of studying variables associated to job quality when identifying the causes of job satisfaction. Greater understanding of these dimensions in the private sector would improve the situation in the public sector (and vice versa) and, therefore, workers' job satisfaction. Of special interest are the possible improvements in the field of Social environment in the public sector, specifically in relationships between workers and their immediate bosses and in the distribution of work tasks. Plain Language Summary: The Impact of the Different Dimensions of Job Quality on Job Satisfaction in the Public and Private sector This study analyses the impact of the different job quality dimensions on Eurozone job satisfaction. The dimensions "Social environment", "Skills and discretion", "Prospects" and "Earnings" have a positive and significant impact on job satisfaction". The impact of both Prospects and Social environment are notably higher in the private sector. [ABSTRACT FROM AUTHOR]

Export tax rebate (ETR) and inwards foreign direct investment (IFDI) are important driving forces for the steady development of China's export-oriented economy. Based on data from 2004 to 2019, this study puts forward relevant assumptions on constructing a model for empirically analyzing the impact of the ETR on China's IFDI from the perspective of the national and the sub-national. The result demonstrates that there exists a complementary relationship between the ETR and IFDI; the weak lag effect of ETR on IFDI in the eastern, middle, and western regions of China; an explicit impact on the performance in the western region, which lags behind only one period; and no significant lag effect of ETR on IFDI in developed, moderately developed, and underdeveloped regions. On the basis of this evaluation, the conclusion could be achieved that that ETR has a significant effect on IFDI, though there may be differences in the direction and value of the impact. The highlight of this research is to detect the impact of ETR on IFDI by taking China as a case, and achieved that there exist sub-national differences, including the geographical and development-level differences. Plain Language Summary: Export Tax Rebate on IFDI The purpose of this article was to detect the impact of export tax rebates (ETR) on China's Inwards Foreign Direct Investment (IFDI) by considering various types of regional differences. The main methods was to establish econometric model considering of time lag effect and control variable and bring relevant hypothesis, then made panel data model to reveal the impact from perspectives of different regions. The conclusion was that the impact of the ETR on the IFDI generally demonstrated differences in complementarity, lag, and geographical and development levels. The implications was that China should implement different regional ETR policy for achieving larger effect on IFDI. The limitations could be detected from two aspects, which was whether an ETR that lags behind to be adopted being debatable and the adoption of enterprise microdata could effectively examine the impact of ETR on IFDI respectively. [ABSTRACT FROM AUTHOR]

This paper aims to research the relationship between population aging, technological innovation, and high-quality economic development. The study applies the spatial econometric model and the intermediary effect model. The object of investigation is 31 provinces in China from 2013 to 2020. The results show that population aging has a significant effect on technological innovation and high-quality economic development. In addition, population aging promotes technological innovation and is further conducive to high-quality economic development. In addition, the impact of population aging on high-quality economic development is regionally heterogeneous. Thus, population aging in the eastern and central regions stimulates technological innovation to have a positive impact on high-quality economic development. Population aging in the western region inhibits technological innovation and has a negative impact on high-quality economic development. Based on this, the study proposes countermeasures to promote high-quality economic development. [ABSTRACT FROM AUTHOR]

The article discusses "Trust" by Hernan Diaz, emphasizing its exploration of the intersection between finance and fictionality. Topics include the novel's self-reflexive nature in comparing financial and fictional world constructions, its use of multiple narratives to highlight the theme of fictionality, and the ethical implications of wealth accumulation depicted through the characters of Andrew Bevel and Mildred.

The article explores the metafictional form of Hernan Diaz's novel Trust, revealing how it provides insights into the narrative foundations of economics and critiques capitalist structures as exploitative. Topics include the novel's examination of financialized economies, the abstraction of econometric techniques from reality, and the power dynamics shaping narratives in the context of capitalism and historical erasure.

In this work, the nature of the mutual influence of monetary and fiscal policy on one of the key problems of the macroeconomic equilibrium of the economy of the Republic of Armenia and the accuracy of forecasting in the context of the application of policies targeting inflation is investigated. The problem of coordination between the two main macroeconomic pillars of economic policy is studied in the context of behavioral and institutional interactions between the Government and the Central Bank of the Republic of Armenia, which implies mutual adaptation and flexibility of reactions within certain rules of the game. Within the framework of the methodology developed in the article, the mutual influence of monetary and fiscal policy is studied using Markov transition models, taking the ratio of tax revenues to GDP and the interest rate on loans issued in the national currency in the Republic of Armenia as a basis. [ABSTRACT FROM AUTHOR]

This study examines the influence of the State bank of the State of Pará, a development bank, on the socioeconomic growth of municipalities in the State of Pará, Brazil. Unlike commercial banks that often reduce their branch network, Banpará has expanded its presence in almost all municipalities. Using spatial econometrics and impact assessment methodologies, the study measures the impact of Banpará branches on these municipalities. The results demonstrate a positive effect contributing to higher Gross Value Added (GVA) in the services sector and public administration of Pará. Additionally, municipalities that established a Banpará branch between 2010 and 2019 exhibited positive results in salaries and production. These findings highlight the critical role of development banks in prioritizing socioeconomic development and fostering inclusive growth. [ABSTRACT FROM AUTHOR]

Simple Summary: Lemur hunting and consumption is widespread in Madagascar. Understanding what drives this phenomenon is key to conserving lemurs and protecting human livelihoods. Current research shows poverty to be a primary driver of lemur hunting and consumption, but no study has employed a composite poverty metric that includes health, education, and living standards. Our study employs such a metric, along with income, to investigate, for the first time, poverty as a driver of lemur hunting and consumption in and around Kirindy Mitea National Park, Madagascar. We document alarming levels of poverty and lemur hunting and consumption among the study community but find no relationship between the variables. Because nearly all households in the study community were impoverished, possible explanations include the following: (1) poverty is not a driver of lemur hunting and consumption in Kirindy Mitea National Park, or (2) a relationship could not be found due to the socio-economic similarity of households in our study community. We consider both interpretations in light of the current literature and offer recommendations for future research. If human and non-human primates are to continue to co-exist in and around Kirindy Mitea National Park, immediate investment in poverty eradication is required, and conservationists should test the efficacy of livestock interventions locally. The futures of human and nonhuman primates are closely tied in protected areas. Understanding this interconnectedness is especially urgent in Madagascar, one of the world's most impoverished biodiversity hotspots. Yet, no study has evaluated the relationship between poverty and lemur hunting and consumption using a composite poverty metric that includes health, education, and living standards. To address this gap, and to inform primate conservation practice and policy, we administered annual surveys to 81 households over six consecutive months (September 2018 to March 2019) in a village on the border of Kirindy Mitea National Park, Madagascar. We observed extreme deprivation scores across multiple dimensions of poverty and identified ninety-five percent of households as 'impoverished'. Of these, three-quarters (77%) of households were identified as being in 'severe poverty'. One-fifth (19%) of all households hunted lemurs and half (49%) of households consumed lemurs. While poverty eradication is an urgent need in communities around Kirindy Mitea National Park, our findings show no relationship between poverty and lemur hunting and consumption, perhaps due to the lack of variance in poverty. Our results highlight the need to investigate other contributory factors to lemur hunting and consumption locally. Because food insecurity is a known driver of lemur hunting and consumption among the study community, and because domestic meats can be preferred over protected species, we recommend testing the efficacy of livestock interventions near Kirindy Mitea National Park. [ABSTRACT FROM AUTHOR]

The aim of the study is to investigate how social capital and innovation affect regional development. In this direction, a spatial model is developed. Since the model includes both a cross-section and a time series, it is assumed that social capital and innovation affect the gross national product per capita spatially as a regional development indicator, and spatial panel data analysis is utilized in this direction. The data of the study are obtained from the social capital index, innovation index and gross national product per capita of the provinces of TR42 East Marmara Development Region (MARKA) between 2007-2021. In order for the concepts of social capital and innovation to gain quantitative characteristics, firstly their sub-determinants are determined. The determinants of these, which can be reached for the region of study, as well as the social capital and innovation indices are obtained within the relevant years. As a result of the study, spatial dependence is determined both in the region and between the provinces. In addition, when the spatial effect is added to the model, it is accepted to analyze the model with Fixed Effect Spatial Error Panel Data Analysis (SEM). As a result, while the effect of innovation on per capita income is not found significant, the effect of social capital on innovation is found to be significant. It is determined that a one-unit increase in social capital reduces the gross national product per capita as 2,530 dollars. [ABSTRACT FROM AUTHOR]

Leveraging a combination of analytical frameworks and empirical assessments, this study investigates the effects of wait-for-free (WFF) pricing schemes on the monetization of serialized, digital entertainment content, which has become increasingly pervasive on online platforms. WFF pricing is a strategy in which consumers are given the option to either wait a certain amount of time to acquire digital content at no cost or pay to consume it immediately. We evaluate the extent to which habit formation and presentbiased preferences driven by the consumption of addictive stock affect individual consumers' willingness to wait (or pay) for content, which, in turn, determines the efficacy of WFF pricing. We also examine the conditions under which consumers switch from waiting for free content to instantaneously purchasing content. Our findings indicate that WFF pricing increases the sales of serialized digital content, generating new demand from customers who would otherwise forgo participation in the market. In addition, the pricing design effectively generates sustained profits in the long run. We found that most consumers who initiate a purchase either upon initial market entry or upon switching continue to purchase as new episodes become available. Moreover, the results indicate that as a user accumulates free episodes of a specific series, given extended waiting periods, the likelihood of their conversion from a wait-for-free customer to an instant-purchase customer increases. In particular, WFF pricing effectively augments the willingness to pay of low-valuation consumers as habit formation builds up through time with the free consumption of serialized content. One free episode can elevate the likelihood of consumer purchase by up to 13%. However, as the number of free episodes consumed goes beyond a threshold, the likelihood of conversion decreases. We conclude with a discussion of managerial implications that can help content providers monetize their serialized digital content products. [ABSTRACT FROM AUTHOR]

• The critical differences between the level and growth effects of temperature on GDP are identified. • We reveal the mechanisms and spatiotemporal characteristics of climate impacts by reviewing various forms of temperature variables and impact functions. • Application scenarios are matched with climate econometrics model specification. • The channels by which future research combines climate econometrics with integrated assessment modelling are identified. • Hybrid econometric model specification could become the research frontier for investigating the temperature-GDP nexus. Climate econometric analysis of the relationship between temperature and gross domestic product (GDP) is increasingly being used to evaluate climate risks and understand economic impacts caused by climate change. We review the literature on growth and level effects (i.e., temperature rise respectively affects the growth and level of economic output), the setting of temperature variables' forms and functional forms, and the inherent model specification of climate econometrics. Additionally, we introduce an approach for combining empirical findings with climate change integrated assessment models (IAMs) to improve damage modelling. Our findings show that estimates of damage through growth effects are generally much larger than those through level effects. Diverse impact mechanisms and adaptation effects can be revealed by changing the time resolution of temperature variables, introducing non-linearity into econometrics functions, and specifying temperature deviation. Combing the cross-sectional and panel model would enable us to examine the economic impacts at different future times. [ABSTRACT FROM AUTHOR]

In this article, I review Environmental Econometrics Using Stata, by Christopher F. Baum and Stan Hurn (2021, Stata Press). [ABSTRACT FROM AUTHOR]

Despite the resurgence internationally of strikes in recent years, studies on the temporality of strike waves within a long-wave perspective has been marked by silence in the literature. This paper revisits the debate on the veracity of long-wave theory to explain the temporality of upsurges in strike activity and the disputes on the measurement of strike waves from an international perspective. The paper applies long-wave theory to South Africa, which is a new contribution and proposes a new quantitative approach to examine the long-term patterning of strikes. This study finds that the predictive power of long-wave theory—that an escalation of the class struggle unfolds around the peaks and troughs of economic long waves—holds throughout the period 1886–2022. This paper makes a new finding that long waves of strikes display a countercyclical patterning to long waves of capitalist development, providing proof of the relative autonomy of the class struggle from long waves. [ABSTRACT FROM AUTHOR]

Change in structure of production in an economy is one of the factors affecting energy consumption in different economic activities. Therefore, the purpose of this study is to investigate the direct and spillover effects of structural changes in production on natural gas consumption in different provinces of Iran during 2007-2018 using spatial econometrics approach. In this study, two indices of production structure changes including industry share in total output and the structural change index (NAV) were used to measure structural changes in the production of the economy. The results indicate that the direct effects of all variables except natural gas price are positive and significant. The direct effect of natural gas price (LGP) on the consumption of this energy is negative and significant. The direct effect of GDP, industrialization, production structure change and urbanization were positive and significant. Spillover effect of the industrialization and change in production structure were positive and significant on natural gas consumption. [ABSTRACT FROM AUTHOR]

Given that the linear linkage between taxation and income inequality remains unclear, especially in Sub‐Saharan African countries, it is critical to explore how the redistribution channel of the tax system could mitigate income inequality within democratic institutions. Using the instrumental variable approach for robust analysis, this study explores the panel dataset of 42 Sub‐Saharan African countries from 1996–2014. The following findings are documented. First, both unconditional linkages between taxation and democracy overwhelmingly reduce income inequality. Second, harnessing democracy with taxation has a net effect that reduces income inequality. Overall, this study establishes that a strong democratic system strengthens the tax system for an income redistribution strategy to enhance income equality. This study is relevant for the achievement of Sustainable Development Goal (SGD) 1 on poverty reduction, SDG 10 on inequality, and SDG 16 on strong institutions. Related Articles: Gatchair, Sonia D. 2015. "Ideology and Interests in Tax Administration Reform in Jamaica." Politics & Policy 43(6): 887–913. https://doi.org/10.1111/polp.12139. Nchofoung, Tii, Simplice Asongu, Vanessa Tchamyou, and Ofeh Edoh. 2022. "Gender, Political Inclusion, and Democracy in Africa: Some Empirical Evidence." Politics & Policy 51(1): 137–55. https://doi.org/10.1111/polp.12505. Wang, Yingyao. 2017. "Why Tax Policy Is Not Politics in China: Public Finance and China's Changing State‐Society Relations." Politics & Policy 45(2): 194–223. https://doi.org/10.1111/polp.12200. [ABSTRACT FROM AUTHOR]

Pawel Ciompa's original and forgotten conception of econometrics is compared with Ragnar Frisch's interpretation of the term. Ciompa conceived of econometrics as being entirely descriptive, facilitating the conveyance of information in the field of accounting. In contrast, Frisch regarded it as a quantitative and empirical approach to economic theorising. Arguments against Frisch's conception of econometrics have been brought forward among others by Ciompa's countrymen of the Austrian School. Ciompa's own conception is immune to that criticism. It is concluded that modern econometrics should be confined to the narrower descriptive character that Pawel Ciompa originally attached to the term. [ABSTRACT FROM AUTHOR]

This article reflects a comprehensive analysis of the factors affecting the financial result of an agro-industrial enterprise using the example of AsiaAgroFood JSC. The research is based on the experience of international and domestic authors who have researched this area. The purpose of the study is to determine the most significant factors affecting the financial result of the organization of an agro-industrial enterprise. To achieve the goal, 8 hypotheses were put forward, 4 of which were rejected, 4 were accepted. The center of this research is AsiaAgroFood JSC, with a special emphasis on the use of advanced statistical methods, in particular correlation and regression analysis, to create an econometric model. In total, 72 different periods were carefully analyzed, with particular attention being paid to the dependent variable of revenue generated from contracts with customers, combined with four other key independent factors, including cost of sales (cost of goods sold), implementation (selling) costs, general and administrative expenses and other sources of income. The authors concluded that with an increase in cost, the revenue of an agro-industrial enterprise increases; with an increase in sales costs, the revenue of an agro-industrial enterprise increases; with an increase in general and administrative expenses, the revenue of an agro-industrial enterprise increases; with an increase in other income, the revenue of an agro-industrial enterprise increases. Thus, the management of an agro-industrial enterprise, based on the data of a scientific article, can come to conclusions about the dependence of revenue and expenses of the enterprise. The significance of the article lies in the application of its results in practice. One of the options for applying the data of the scientific article is the formation of the budget of an agro-industrial enterprise for subsequent years. [ABSTRACT FROM AUTHOR]

Objective: To analyze the competitiveness of the Mexican tomato in the United States market, Methodology: The normalized revealed comparative advantage index was used, regressions with robust estimators, the Hodrick-Prescott filter was applied to extract the trend and guarantee non-seasonality. Results: Mexico maintains the comparative advantage revealed in the US market, with a growing and consistent competitiveness throughout the period analyzed. This competitiveness is strengthened by belonging to the Trade Agreement, by reinforcing the export process. Limitations: A bilateral Mexico-United States analysis is considerate, which, although it responds to the proposed research objective, favors continuing to investigate specifically the dynamics of the United States market because decrease in the proportion of the market is identified despite the substantial increase in exports. Conclusions: The VCRN estimate shows that, for the study period, the Mexican tomato has positioned itself in the US market, with a growing trend; The Hodrick-Prescott filter was applied to extract the trend and ensure the non-seasonality of the VCRN, which in turn allowed a better fit in the model, the F test determined that the model was globally accepted to explain the phenomenon. [ABSTRACT FROM AUTHOR]

This study applies a spatial econometric model to examine the impact of three-dimensional distance on interprovincial tourism economic spillover effects using panel data from 30 provinces in China from 2010 to 2019. The impacts of technological innovation, ecological environment, informatization level, industrial structure, infrastructure facilities, and location, on the indirect effect of the tourism economy are comparatively analyzed. It explores the regional characteristics and developmental changes of tourism economic spillover. The results show that, first, based on the three spatial matrices, the direct and total effect values of technological innovation are the largest when close to each other, and technological innovation among provinces with higher economic volumes significantly promotes positive interprovincial tourism economic spillover. Second, ecological environment is the main promoting factor of positive tourism economic spillover among neighboring provinces in China's western region. Third, industrial structure optimization shows a significant positive spatial spillover effect. Fourth, with gradual infrastructure improvement, the influence of infrastructure facilities on the spillover effect of interprovincial tourism economy weakens gradually. Fifth, improved information technology levels can effectively promote positive spatial spillover of the tourism economy. Sixth, the influence of location on the positive spatial spillover of the interprovincial tourism economy shows a gradually increasing trend. [ABSTRACT FROM AUTHOR]

The digital economy has led to the diversification of user needs and continuous innovation by firms, and firms are increasingly providing customized services to respond to changing user needs and expect to improve their competitiveness and performance. However, there are few in-depth studies on the mechanisms of the impact of customized services on firm performance and the differences among industries. This study attempts to fill this gap by constructing an econometric model and conducting an empirical study. The results of the analysis of data from firms on Taobao show that: customized services provision has a positive effect on firm performance; differences exist in these positive effects, with the effects ranging from high to low in the raw materials, consumer goods, and industrial goods industries; and customer satisfaction plays a mediating role between customized services and firm performance. This study provides insights for firms to modify, improve, and transform their business strategies in the context of the digital economy. [ABSTRACT FROM AUTHOR]

The article analyses the determinants of acquisition of flamenco albums. Flamenco is a musical genre recognized by UNESCO as intangible heritage of humanity. A methodology divided into three phases has been used for this purpose: firstly, interviews with experts from the Spanish music industry where new variables are identified that can affect flamenco consumption habits; then 586 surveys of flamenco spectators who valued these variables and, finally, the application of econometric models to obtain the coefficients of the variables. The results show how the valuation of the composition, the performer and its virtuosity, of the existing trends, and the sociodemographic characteristics of the spectators directly affect the acquisition of flamenco-recorded music. The article contributes to the scarce empirical literature that relates the determinants of recorded music acquisition with traditional popular genres, by adding never studied before variables, focusing on the case of flamenco. [ABSTRACT FROM AUTHOR]