STATISTICAL ANALYSIS OF MODERN WORLD MARKETS: PRINCIPLES, METHODOLOGY, CHALLENGES

Clustering is a technique used to classify objects or cases into groups based on their similarity, called clusters or groups. Objects in each group tend to resemble each other and differ greatly (not the same) with objects from other clusters. Public welfare is a condition of fulfilling the material, spiritual and social needs of citizens in order to be able to live properly. Fuzzy Subtractive Clustering (FSC) method is a clustering algorithm that can form the number and centroid of clusters in accordance with data conditions. This study aims to determine the FSC results in grouping the level of welfare of the Indonesian people in 2017. The testing results of the cluster validity index show 2 values of Partition Entropy and Classification Entropy forming into 2 clusters that have the best value, indicating that the provincial group has a high welfare level and the provincial group has a low welfare level.

This is qualitative research that uses a descriptive approach focuses on knowing the level of welfare of athletes with special needs in national training centers. Primary data was obtained by using interviews addressed to 20 athletes who were willing to be resource persons. Interviews were conducted based on the welfare level instrument used by the Central Bureau of Statistics of Indonesia with indicators in the form of income, expenses, living conditions, housing facilities, ease of obtaining health services, and ease of obtaining transportation facilities. In addition, researchers also took information in the form of monthly salary receipt data obtained by athletes as secondary data from this study. The data was then analyzed using the NVivo 12 Pro. The search results using the word cloud feature in the NVivo 12 Pro application program that comes from all research data, the sentence "has fulfilled" is a sentence that often appears as evidenced by the percentage of 57.53%. Based on the data analysis that has been done, it can be seen that the majority of athletes with special needs have a high level of welfare.

The use of modern chicken genotypes with high egg or meat performance results in the ethically unacceptable practice of culling day-old male layer chicks because of their inefficient fattening performance. Dual-purpose genotypes with a balanced performance profile for both eggs and meat are one option to avoid this practice. In this study, four chicken crosses of a layer breed (White Rock or New Hampshire) and the meat breed Bresse Gauloise were compared under the conditions of organic agriculture. Purebred Bresse Gauloise and the layer hybrid Lohmann Sandy served as controls. Part 1 of this study focused on the fattening performance of the cockerels, which were reared together with the pullets. The birds were housed in a floor system (9.9–20.7 kg live weight per m2 at the end of week 15) with access to a green outdoor run. Live weight of the crosses before slaughter at the age of 15 weeks ranged between 2355 and 2447 g and did not differ significantly between the genotypes. With average daily gains of 22.1–22.8 g, the crosses grew slower than Bresse Gauloise males (26.1 g) but faster than Lohmann Sandy males (15.9 g). Welfare assessment indicated a generally high level of welfare with no foot pad lesions or hock burns on any of the cockerels. Fattening dual-purpose cockerels can therefore be an ethically desirable option with a high level of animal welfare and a better fattening performance than in male layer chicks, but still requires more resources than the fattening of specialised broilers.

By connecting the post-Keynesian view of financialization with Comparative Political Economy, we suggest some elements for an updated interpretation of the existing models of welfare. As a main element of novelty, we consider how high-income countries are reacting to the pressures of finance-dominated capitalism, namely by extending, keeping, or retrenching their welfare systems. The contribution of the article is threefold. First, we elaborate on the nexus between welfare and financialization. Second, we introduce a multidimensional index aimed at assessing the degree of welfare of 32 OECD countries for the period 1990–2015. Third, we compare our index with the socio-economic models identified in the literature and with the patterns of financialization. Two trajectories emerge from our exploration: on the one side, Scandinavian and Continental European countries moved toward relatively higher levels of welfare; on the other side, lower levels of welfare feature Anglo-Saxon, Asian, Mediterranean, and Central and Eastern European countries. Besides such divergence, we find that the process of financialization was more intense in countries with stronger welfare, which likely opted for a compensation strategy. Our work highlights the relevance of policies and institutions in shaping different welfare systems and coping with the challenges of the current phase of capitalism.

The need for precise stock price evaluation and projection is highlighted by the stock market’s increasing importance in the national economy, a topic that has attracted a lot of scholarly attention. Predictive modelling faces a very dynamic and difficult task when it comes to stock price movements, which are impacted by a variety of elements, including macroeconomic policy, industry news, capital flows, market sentiment, and corporate fundamentals. Rising volatility and increasing complexity are making themselves felt on the global stock markets; hence, there is a need for advanced prediction models that may incorporate financial, macroeconomic, and sustainability variables. This paper has therefore suggested a hybrid Long Short-Term Memory (LSTM) model that combines sentiment analysis of financial news and Principal Component Analysis (PCA) choice of features to predict stock market movements based on the aspect of economic sustainability. Historical stock price data, macroeconomic variables, and ESG (Environmental, Social, and Governance) scores for several global indexes between 2010 to 2024 are fed into the algorithm. The experimental results prove that in consideration of factors such as directional accuracy and predictive accuracy, the suggested LSTM-Hybrid framework performs better than any traditional LSTM or ARIMA model. Informed investment strategies can thus drive investors and policymakers toward economic sustainability in the long run.

This study aims to classify regencies/municipalities in South Sulawesi Province based on welfare indicators using cluster analysis. Cluster analysis is a technique for grouping objects according to the similarity of their characteristics. The method employed is hierarchical agglomerative clustering with the average linkage approach, which is a stepwise clustering procedure that merges two objects with the shortest distance until a single cluster is formed. The average linkage method defines the distance between clusters as the average distance between all objects in one cluster and all objects in another cluster. Prior to clustering, a sampling adequacy test, correlation test, and Principal Component Analysis (PCA) were conducted to address multicollinearity. Subsequently, the Euclidean distance matrix was calculated, a dendrogram was constructed, and the optimal number of clusters was determined by cutting the dendrogram at the largest difference between successive fusion distances, which indicates a significant change in the cluster structure. The results show that two clusters were obtained. Cluster 1, representing regions with lower welfare levels, consists of Selayar, Bulukumba, Bantaeng, Jeneponto, Takalar, Gowa, Sinjai, Maros, Pangkep, Barru, Bone, Soppeng, Wajo, Sidrap, Pinrang, Enrekang, Luwu, Tana Toraja, Luwu Utara, Luwu Timur, Toraja Utara, Parepare, and Palopo. Cluster 2, representing regions with higher welfare levels, consists of Makassar.

BackgroundThe health area being greatest impacted by coronavirus disease 2019 (COVID-19) and residents’ perspective to better prepare for future pandemic remain unknown. We aimed to assess and make cross-country and cross-region comparisons of the global impacts of COVID-19 and preparation preferences of pandemic.MethodsWe recruited adults in 30 countries covering all World Health Organization (WHO) regions from July 2020 to August 2021. 5 Likert-point scales were used to measure their perceived change in 32 aspects due to COVID-19 (-2 = substantially reduced to 2 = substantially increased) and perceived importance of 13 preparations (1 = not important to 5 = extremely important). Samples were stratified by age and gender in the corresponding countries. Multidimensional preference analysis displays disparities between 30 countries, WHO regions, economic development levels, and COVID-19 severity levels.Results16 512 adults participated, with 10 351 females. Among 32 aspects of impact, the most affected were having a meal at home (mean (m) = 0.84, standard error (SE) = 0.01), cooking at home (m = 0.78, SE = 0.01), social activities (m = -0.68, SE = 0.01), duration of screen time (m = 0.67, SE = 0.01), and duration of sitting (m = 0.59, SE = 0.01). Alcohol (m = -0.36, SE = 0.01) and tobacco (m = -0.38, SE = 0.01) consumption declined moderately. Among 13 preparations, respondents rated medicine delivery (m = 3.50, SE = 0.01), getting prescribed medicine in a hospital visit / follow-up in a community pharmacy (m = 3.37, SE = 0.01), and online shopping (m = 3.33, SE = 0.02) as the most important. The multidimensional preference analysis showed the European Region, Region of the Americas, Western Pacific Region and countries with a high-income level or medium to high COVID-19 severity were more adversely impacted on sitting and screen time duration and social activities, whereas other regions and countries experienced more cooking and eating at home. Countries with a high-income level or medium to high COVID-19 severity reported higher perceived mental burden and emotional distress. Except for low- and lower-middle-income countries, medicine delivery was always prioritised.ConclusionsGlobal increasing sitting and screen time and limiting social activities deserve as much attention as mental health. Besides, the pandemic has ushered in a notable enhancement in lifestyle of home cooking and eating, while simultaneously reducing the consumption of tobacco and alcohol. A health care system and technological infrastructure that facilitate medicine delivery, medicine prescription, and online shopping are priorities for coping with future pandemics.

Summary. The paper considers the determinacy of the equilibrium price level in the cash-in-advance monetary economy of Lucas and Stokey (1983, 1987), in the case of deterministic fundamentals. The possibilities both of a multiplicity of perfect foresight and of equilibria are considered. Two types of monetary policy regimes are considered and compared, one in which the money supply grows at a given exogenous rate (that may be positive or negative), and one in which the nominal interest rate on one-period government debt is pegged at a given non-negative level. In the case of constant money growth rate regimes, it is shown that one can easily have both indeterminacy of perfect foresight equilibrium and existence of equilibria; indeed, in the case of negative rates of money growth (as called for by Friedman (1969)), both types of indeterminacy necessarily occur. On the other hand, sufficient conditions for uniqueness of equilibrium (and non-existence of other than a deterministic steady state) are also given, and a class of cases is identified in which a sufficiently high rate of money growth guarantees this. Thus there may be a conflict between the aims of choosing a rate of money growth that results in a high level of welfare in the steady state equilibrium and choosing a rate that makes this steady state the unique equilibrium.) In the case of the interest rate pegging regimes, sufficient conditions are given for uniqueness of equilibrium (and impossibility of equilibria), and it is shown that these necessarily hold in the case of any low enough nominal interest rate. Thus the nominal interest rate peg allows simultaneous achievement of price level determinacy and a high level of welfare in the unique (steady state) equilibrium. In this paper I consider the consequences of alternative choices of the monetary policy regime for the determinacy of the rational expectations equilibrium value of money, and in particular for the existence or not of sunspot equilibria, i.e., rational

This study evaluates the effectiveness of Machine Learning (ML) models in forecasting the EUR/USD exchange rate from January 2014 to December 2024, focusing on the relationship between forecast errors and key macroeconomic indicators, including interest rates, inflation, unemployment, and GDP growth. The forecasting framework integrates three widely used architectures—Multilayer Perceptron (MLP), Random Forest (RF), and Long Short-Term Memory (LSTM) networks—applied to monthly exchange rate and macroeconomic data drawn from Yahoo Finance, the World Bank, and the International Monetary Fund. The findings indicate that the LSTM model outperforms both MLP and RF in predictive accuracy, achieving an R-squared value of 0.9234. While all models demonstrate strong short-term forecasting performance, macroeconomic variables have limited explanatory power regarding forecast error, with only Eurozone interest rates showing weak statistical significance. These results suggest that ML models can effectively model exchange rate dynamics even when macroeconomic indicators provide limited statistical relevance. The study contributes to the literature on AI in financial forecasting by highlighting the comparative strengths of deep learning and ensemble methods and identifying persistent challenges in integrating economic fundamentals, underscoring the value of hybrid and interpretable AI frameworks that bridge macroeconomic theory and data-driven learning for improved financial forecasting.

Youth unemployment remains one of the most persistent and structurally sensitive challenges in emerging economies, particularly in environments characterized by macroeconomic volatility and frequent shocks. This study investigates the dynamics and forecasting performance of youth unemployment in Turkey by adopting a symmetry-based multivariate framework that explicitly contrasts equilibrium-oriented and asymmetric temporal behaviors. Using monthly data covering the period 2009–2024, youth unemployment is modeled jointly with key macroeconomic indicators, including economic growth, inflation, overall unemployment, labor force participation, migration, exchange rates, and consumer confidence. The empirical strategy integrates traditional econometric models and modern machine learning approaches under a unified and leakage-free evaluation protocol. Stationarity and long-run properties of the series are examined using unit root tests and the Bayer–Hanck cointegration approach, followed by long-run coefficient estimation via FMOLS and DOLS. Forecasting performance is then compared across VARIMA, Prophet, and deep learning models (RNN, LSTM, and GRU), including both vanilla and hyperparameter-tuned specifications. The results reveal a clear performance hierarchy. VARIMA models, particularly the VARIMA (p = 2, q = 0) specification, consistently outperform all alternatives by a wide margin, achieving exceptionally low forecast errors. This finding indicates that youth unemployment in Türkiye is predominantly governed by symmetric co-movements and long-run equilibrium relationships among macroeconomic variables. Prophet and GRU models capture short-term and regime-sensitive fluctuations more flexibly, reflecting asymmetric temporal responses, but at the cost of higher forecast dispersion. In contrast, RNN and LSTM models exhibit limited generalization capability and are prone to overfitting in the small-sample macroeconomic context. As a result, this study positions the estimation of youth unemployment as both an econometric challenge and a symmetry-based analytical problem, offering new methodological and conceptual insights consistent with a fresh perspective.

This article examines the development of mortgage lending in Kazakhstan, focusing on its dynamics and its relationship with key macroeconomic indicators. Special attention is given to the role of government programs and the integration of ESG (Environmental, Social, and Governance) principles to promote sustainability in the sector. While ESG standards are widely adopted in international financial systems, this study analyzes Kazakhstan’s unique economic and institutional context. Additionally, Uzbekistan is considered a country where certain effective financial and regulatory tools applied in Kazakhstan could potentially be adapted to local conditions. The analysis compares selected mortgage lending indicators between Kazakhstan and Uzbekistan and employs correlation and regression modeling to evaluate how macroeconomic variables such as GDP, interest rates, and the share of overdue loans impact mortgage lending volumes. Drawing on data from The Global Economy (2023), the study explores how mortgage programs in developed countries affect the ratio of banking sector assets to GDP, providing a global benchmark. A detailed analysis of mortgage trends from 2007 to 2023 reveals important patterns and correlations between macroeconomic factors and mortgage loan dynamics in both countries. Time series and correlation methods allowed the authors to establish statistically significant relationships, particularly in the case of Kazakhstan. As a result, a forecasting model was developed, incorporating GDP growth, lending interest rates, and the level of non-performing loans as independent variables. The article also discusses the integration of ESG standards into Kazakhstan’s mortgage finance system, highlighting their potential to foster green construction and sustainable housing development. These initiatives support broader sustainable development objectives and could be relevant for Uzbekistan as well. The authors argue that implementing green financial instruments such as green mortgages and funding programs for energy-efficient housing can reduce environmental harm and improve housing affordability in Kazakhstan, Uzbekistan, and other emerging economies. Key words: mortgage lending, sustainable development goals (SDGs), ESG standards, GDP, socio-economic development, Kazakhstan.

China’s energy revolution strategy serves as both a driving force and a hindrance to the rise of central China. Based on the six-dimensional data of GDP, industrial structure, urbanization, energy efficiency, per capita income and energy consumption of the five central provinces, this research sets three levels of growth rate, namely high, medium and low growth rates. With GDP growth as the key sub-scenario, a total of 13 rising models from SE11 to SE34 are established to simulate the high-quality rise of the five central provinces against the background of energy revolution. The results indicate that the path of high-quality rise of central China varies from SE11 to SE25, that is, from high-speed economic growth to benchmark growth model. For the model of rapid economic development, the industrial structure will be upgraded and the energy efficiency will be maximized. With the energy revolution, the emission of carbon dioxide will reach its peak in 2020. However, the adjustment of industrial structure promoting energy efficiency will be challenging, which will also cost a huge amount of energy. For the benchmark growth model, GDP growth rate is lower than that of the rapid development model, but the energy consumption is reduced, and the adjustment of industrial structure and the improvement of energy efficiency is less challenging. Improving energy efficiency has a higher effect on energy saving than upgrading industrial structure. Through energy revolution, the proportion of renewable energy will reach 23.06% in 2035, and consequently the emission of carbon dioxide will reach its peak two years ahead of schedule.

This paper examines the assertion that economic globalization has led to the decline of welfare spending in recent decades. Although it is often argued that the increasing intensity of globalization has led to such a decline in the industrialized states, the paper finds that there has been little, if any, downturn in either levels of state expenditure in general or in levels of welfare spending in particular. However, the experience of the developing states has been rather different. In their case, the last few decades indicate that stagnation or a decline in welfare spending has occurred, particularly during the period of structural adjustment implementation. It is argued that the OECD countries still manage to provide a high level of social welfare to their populations that closely resembles the compensatory state model. In contradistinction, many of the states in the South have struggled to maintain their levels of social expenditure and therefore most resemble Cerny's competitive state model. In order to explain these two divergent outcomes, the paper examines the way in which the behaviour of certain key international financial actors (investors, multinational companies, international financial institutions) differs with regard to these two sets of countries.

The article studies the key prerequisites for the formation of the scientific school “Theory and practice of sovereign social economy”, conditioned by the historical experience in the formation of elements of sovereign and socially oriented systems. It highlights the stages of the evolution of economic knowledge in Russian economic history, which had a decisive influence on theory and practice. It also reveals the main reasons for the dismantling of an open raw materials-based economy and identifies the main result of which was the formation of a model of “growth without development”, the criterion features of the emerging model of the economy of modern Russia, which sets the contours of a new paradigm of economic knowledge. There is an analysis of previous theoretical and methodological developments formed within the framework of various scientific schools. The overall result boils down to the justification that, given the complexity of modern global processes and the challenges facing national economies, it becomes obvious that there is a need to move from fragmented solutions to a holistic concept of a sovereign social economy that reflects the logic of building an architecture and a clear definition of goals and objectives. The goals of building and implementing a sovereign social economy as a concept are aimed at systematically ensuring national development that is sustainable to external and internal challenges by forming a balanced model of socio-economic relations that prioritizes both strengthening economic sovereignty and achieving a high level of social justice and public welfare. The concept focuses on creating an economic environment that can effectively mobilize internal resources, stimulate the development of domestic production, science and technology, reduce dependence on external economic and political factors, and provide institutional support for basic industries that are critical to national security.

当前及即将到来的“十三五”是我国新型城镇化建设的关键时期，深入研究综合交通运输与国民经济的内在关联规律，通过建立关联指标体系更科学合理的指导“十三五”综合交通基础设施建设对于落实新型城镇化战略具有重要意义。本文从综合交通运输与国民经济内在关联本质入手，提出城镇化率、产业结构是把握二者规律及表现的两大关键指标，在此基础上构建综合交通运输与国民经济关联指标体系研究框架，并初步拟定关联指标体系。 In the key period of China’s new pattern urbanization, it has great significance to implement the new urbanization strategy which could precisely reflect the rules of internal connection between comprehensive transportation and national economy, and establish an supportive associated index system to guide the development of comprehensive traffic infrastructure in the “13th Five Year” period. This paper studies the inherent relationship between comprehensive transportation and national economy, points out that “urbanization rate” and “industrial structure” are the two key indicators of the relationship, complies a research framework of associated index system of comprehensive transportation and national economy, then further provides a preliminary asso-ciated index system.