Large Economies Research Articles

Improving Irrigation Management of Cotton with Small Unmanned Aerial Vehicle (UAV) in Texas High Plains

The rapid decline in water availability for irrigation on the Texas High Plains (THP) is a significant problem affecting crop production and the viability of a large regional economy worth approximately USD 7 billion annually. This region is the largest continuous cotton-producing area in the United States, and the timely delivery and efficient use of irrigation water are critical to the sustainability and profitability of cotton production in this region. Current irrigation scheduling must be improved to reduce water consumption without compromising crop production. Presently, irrigation scheduling based on reference evapotranspiration (ETo) is limited due to the lack of reliable and readily available in-field weather data and updated crop coefficients. Additionally, in-field variability in crop water demand is often overlooked, leading to lower irrigation efficiency. To address these challenges, we explored the potential use of an unmanned aerial vehicle (UAV)-based crop monitoring system to support irrigation management decisions. This study was conducted in Lubbock, Texas, in 2022, where high temporal and spatial resolution images were acquired using a UAV from a cotton field experiment with four irrigation levels. Soil moisture and canopy temperature sensors were deployed to monitor crop response to irrigation and rainfall. The results indicated a significant effect of water stress on crop growth (revealed by UAV-based canopy cover (CC) measurements), yield, and fiber quality. Strong correlations between multi-temporal CC and lint yield (R2 = 0.68 to 0.88) emphasized a clear trend: rainfed treatments with lower yields exhibited reduced CC, while irrigated plots with higher CC displayed increased yields. Furthermore, irrigated plots produced more mature and uniform fibers. This study also explored various evapotranspiration calculation approaches indicating that site-specific CC measurements obtained from a UAV could significantly reduce irrigation application. A regression model linking evapotranspiration to canopy cover demonstrated promising potential for estimating water demand in crops with an R2 as high as 0.68. The findings highlight the efficacy of UAV-based canopy features in assessing drought effects and managing irrigation water in water-limited production regions like the THP.

AN OVERVIEW OF CORPORATE SOCIAL RESPONSIBILITY ACTIVITIES IN COIMBATORE DISTRICTS

The concept of Corporate Social Responsibility is a very broad one, encompassing the various dimensions of the business world. Social responsibility in marketing involves focusing efforts on stake holders who want to make a positive difference with their requirements. Social responsibility has a great impact in the performance of various organizations. The CSR strategies may vary in accordance with company nature(size), Type, Form of Industry. The CSR ambit is getting bigger and for upcoming years it would turn as a unique knowledge base for analysing and achieving sustainability goals as among various large economies. India is a country which has assured by mandating CSR through its legislative action. This study focus on companies CSR efforts from their practices to broad societal impacts, be explained by the Classical model, Stakeholder model, Sustainability model, Concentric Circle model, or by a combination of all four.

Changes in Surface Runoff and Temporal Dispersion in a Restored Montane Watershed on the Qinghai–Tibetan Plateau

Surface runoff is a major component of the hydrological cycle, and it is essential for supporting the ecosystem services provided by grassland and forest ecosystems. It is of practical importance to understand the mechanisms and the dynamic processes of runoff in a river’s basin, and in this study, we focused on the restored montane Pailugou Basin in the Qilian Mountains, Gansu Province, China, since its water status is extremely important for the large arid area and local economies therein. Our purpose was to determine the annual variation in the surface runoff in the Pailugou Basin because it is important to understand the influence of climate fluctuations on surface water resources and the economy of the basin. In addition, little is known about the annual variations in precipitation and runoff in this region of the world. Daily atmospheric precipitation, air temperature and runoff data from 2000 to 2019 were analyzed by the calculation of the uneven annual distribution of surface runoff, the calculation of the complete adjustment coefficient, and the vector accumulation expressed by the concentration degree. We also used the cumulative anomaly approach to determine the interannual variation trend of runoff, while the change trend was quantified by the sliding average method. Finally, we used the Mann–Kendall mutation test method and regression analysis to establish the time-series trend for precipitation and runoff and to determine the period of abrupt runoff changes. The results indicated concentrated and positive distributions of surface runoff on an annual basis, with a small degree of dispersion, and an explicit concentration of extreme flows. The relative variation ranges exhibited a decreasing trend, and the distribution of the surface runoff gradually was uniform over the year. The runoff was highest from July to September (85% of the annual total). We also determined that annual surface runoff in the basin fluctuated over the 20-year period but showed an overall increasing trend, increasing by 3.94 × 105 m3, with an average increase rate of 0.42 × 105 m3 every ten years. From 2005 to 2014, the annual runoff and the proportion of runoff in the flood season (July to September) to the annual runoff fluctuated greatly. The correlation between the runoff and precipitation was significant (r = 0.839, p < 0.05), whereas the correlation between air temperature and surface runoff was low (r = 0.421, p < 0.05).

The effects of conventional and unconventional monetary policies of the US, EU, and China on global green investment

This study investigates how the monetary policies of the USA, EU, and China affect global green investment differently by using the dynamic autoregressive distributive lag (DARDL) model and kernel-based regularized least squares (KRLS). DARDL's results show that US monetary policy is not conducive to global green investment in the short and long term. The EU's conventional monetary policy negatively impacts global green investment, but only in the short term. However, China's conventional monetary policy boosts global green investment in the long term. The inference from the response simulations implies that the conventional monetary easing policy of the US, EU, and China positively influences global green investment in the long and short run. However, the magnitude of the response of the EU is greater than that of the US and China. Unconventional monetary policy easing of the US negatively influences global green investments in the short run, whereas China and EU policies affect it positively. However, in the long run, global green investment is unaffected by unconventional monetary policy easing in the case of the US. In contrast, China's and the EU's unconventional monetary policies easing have had a positive impact. In the case of financial development, a negative impact on global green investment is more strongly evident for China than for the US and the EU. Overall, the empirical results of this study recommend that a significant change in the monetary policies of large economies is required to promote global green investment for ecological transition.

Quantifying provincial in-use stocks of rare earth to identify urban mining potentials in the Chinese mainland

Recycling of rare earth elements (REE) can help to offset the increasing demand for REE minerals and enhance the diversification of the REE supply chain. The development of low-carbon technologies, such as new energy vehicles and wind turbines has expedited the accumulation of REE as “urban mines”. This trend offers prospects for the progress of REE recycling initiatives targeting end-of-life products. This study conducts a dynamic material flow analysis (combined top-down and bottom-up method) of nine products containing NdFeB permanent magnets (their scrap is regarded as the most important secondary resource of rare earth) in the Chinese mainland at a provincial level to identify end-of-life products and provinces with high urban mining potentials. Results indicate that e-bikes, wind turbines, and air conditioners have the most significant REE recycling potentials in the Chinese mainland. Provinces with large populations and robust economies, such as Guangdong and Jiangsu, exhibit greater potential for REE recycling. This study illustrates significant provincial disparities in the end-of-life recycling potentials of REEs in the Chinese mainland and highlights the significance of provincial-level assessments of urban mining potential in the planning of the REE recycling industry.

On the continuity of the Walras correspondence in distributional economies with an infinite-dimensional commodity space

Distributional economies are defined by a probability distribution in the space of characteristics where the commodity space is an ordered separable Banach space. We characterize the continuity of the equilibrium correspondence and an associated stability concept which allows us to give a positive answer to an open question about the continuity of the Walras correspondence in infinite-dimensional spaces. As a byproduct, we study a stability concept where differentiability assumptions are not required, as is usual in the literature on regularity. Moreover, since distributional economies do not specify a space of agents, our setting encompasses several results in the literature on large economies.

An index of static resilience in interindustry economics

We introduce a novel static indicator of economy-wide resilience that assesses an economy’s ability to adapt and recover from negative shocks originating from either the demand or supply side. This metric is counterfactual and, through simulation, reveals the extent of adjustments required to maintain total income at or above the initial pre-shock level while preserving the initial economic structure. The larger the scale of adjustments needed in response to the shock, the lower the resilience of the economic system. The methodology we propose for this assessment relies on the concept of constrained input–output multipliers embedded within a linear programming problem. We demonstrate the applicability of our approach by calculating and comparing demand and supply resilience indices for a group of ten large OECD economies. In all these economies, the results indicate that manufacturing industries exhibit higher resilience to demand shocks than service sectors and that economic resilience regarding negative supply shocks is higher than that of demand shocks.

Star help and knowledge transfer: an event study analysis of star interactions observed from acknowledgement texts

AbstractThis paper contributes to the growing literature on the impact of connections to star scientists on the productivity of academic scientists. The existing literature generally focuses on larger economies and specific scientific fields in evaluating star-connection effects. It has rarely examined the particular channels through which stars have their effects. Using natural language processing (NLP) techniques to explore the acknowledgement texts of a broad corpus of published papers from three small open economies, we examine the effects of star help revealed by the acknowledgement texts published in articles. Using an event-study framework with matched data, we find evidence of an economically and statistically significant effect on scientist productivity in the year of acknowledgement of star help. However, there is only evidence of an enduring productivity effect if scientists maintain their acknowledgement of ties to the star over time. A similar pattern is evident across different types of acknowledgements, except for acknowledgements of star help with access to materials, which shows an enduring effect even after a single acknowledgement. The largest estimated star-help effects are found for authors in lower quartiles of the field-specific productivity distribution measured in the year before the help is acknowledged. The results are robust to using a raw-publications-based measure of scientist productivity in place of our preferred citation-weighted publications measure of productivity, suggesting that the observed productivity effect is unlikely to be due to a pure signalling effect. We discuss the implications of these findings for the design of star recruitment and integration policies.

Collective decision through an informed mediator

An imperfectly informed mediator (or mechanism designer) must make a decision on behalf of a group of agents, who are privately informed about their valuations attached to the decision. The mediator chooses a mechanism before observing a signal about the agents' valuations and commits to truthfully using this information in the mechanism. We give a necessary and sufficient condition on the mediator's information under which the ex post efficient decision rule can be implemented by an ex ante budget balanced, dominant strategy incentive-compatible and ex post individually rational mechanism. In a large economy, we show that the amount of information that the mediator needs to know about each agent to achieve ex post efficiency is bounded as the number of agents grows to infinity.

Knowledge Production in a Territorial Network of Organizations: Identifying the Determinants in the Case of Moroccan Technopole

Globalization has led to a geographical concentration of economic activities, known as territorialized networks of organizations, especially technopoles. That is why the knowledge process takes on new dimensions and requires a multidimensional and dynamic approach. This study aims to analyze factors of knowledge production dynamics in technopoles based on a conceptual model that is elaborated based on the literature review and tested in a technopole’s environment, knowledge creation, knowledge transfer, and knowledge utilization processes. We used partial least squares structural equation modeling confirmatory composite analysis techniques to test the validity and reliability of the model. The technopole actors’ heterogeneous nature allowed us to use a stratified sampling technique. The data were collected from 303 respondents from four technopoles in Morocco. Our findings indicate the existence of a strong influence of the factors presented in the research model on knowledge production dynamics in technopoles. Moreover, the technopole actors’ contribution to the creation, transfer, and utilization of knowledge is more likely to be effective in increasing knowledge production dynamics within the network. The technopoles are likely to be more successful in regions that have the properties of a large, diversified, and well-established metropolitan economy, a robust research base, and an entrepreneurial culture where stakeholders are actively engaged. Our study is the first to analyze the dynamics of knowledge production in Moroccan territorialized networks of organizations (i.e., technopoles). This study provides insights to managers in formulating efficient knowledge production strategies in technopoles and offers suggestions at three levels: actors of technopoles, technopoles, and regional actors.

Impacts of Monetary Policy Shocks on Inflation and Output in New Zealand*

We identify monetary policy shocks in New Zealand as 1‐day changes in the whole yield curve around monetary policy announcements. The impacts of these shocks on inflation and output are estimated using functional local projections. We find that the effects of monetary policy shocks are standard in the short run but might be different in the long run. Monetary policy shocks in a small open economy have similar effects as in a large economy, except that unconventional monetary policy announcements have limited impact on long‐term interest rates. Accounting for forward guidance, used in New Zealand since 1997, is important.

The asymmetric impact of oil market shocks on the time-varying connectedness and spillover of financial stress

ABSTRACT Applying a novel time-varying parameter VAR (TVP-VAR) extended joint connectedness approach this study first examines the connectedness and spillover of financial stress among twelve large Asian economies. The finding shows that the usually high connectedness of the financial stress among these economies was further elevated during the Asian financial crisis and global financial crisis but not significantly during COVID-19 pandemic. The direction of spillover depends on the level of economic development. Developed economies such as South Korea, Singapore and Hong Kong are significantly net transmitters of financial stress to other Asian economies whereas countries such as Pakistan and Indonesia are significantly net receivers. Applying linear and non-linear Markov-switching models this study further examines the impact of oil-supply, and consumption- and speculation-led oil-demand shocks on the dynamic connectedness of financial stress indexes. In the linear model only a speculation-led increase in demand for oil increases the connectedness. However, the Markov-switching model reveals that in the high-volatility regime all types of oil shocks influence the connectedness of the financial stress among these economies. This emphasizes the elevated role of oil market in transmitting financial stress across economies during the time of economic turmoil.

Techno-Economic Sustainability Potential of Large-Scale Systems: Forecasting Intermodal Freight Transportation Volumes

The sustainability of large economies is one of the most important challenges in today’s world. As the world strives to create a greener and more efficient future, it becomes necessary to accurately analyze and forecast freight volumes. By developing a reliable freight transportation forecasting model, the authors will be able to gain valuable insights into the trends and patterns that determine the development of economic systems. This will enable informed decisions on resource allocation, infrastructure development, and environmental impact mitigation. Such a model takes into account various factors such as market demand, logistical capabilities, fuel consumption, and emissions. Understanding these dynamics allows us to optimize supply chains, reduce waste, minimize our carbon footprint, and, ultimately, create more sustainable economic systems. The ability to accurately forecast freight volumes not only benefits businesses by enabling better planning and cost optimization but also contributes to the overall sustainable development goals of society. It can identify opportunities to shift to more sustainable modes of transportation, such as rail or water, and reduce dependence on carbon-intensive modes, such as road or air. In conclusion, the development and implementation of a robust freight forecasting model is critical to the sustainability of large-scale economic systems. Thus, by utilizing data and making informed decisions based on these forecasts, it is possible to work toward a more sustainable future for future generations.

Planning the “Ruralopolis” in India: Circular Migration, Survival Entrepreneurship, and the Subversive Non-Farm Economy

Urban research has scarcely investigated the planning context of the “ruralopolis”—poor and predominantly agrarian regions of the Global South with very high population densities. Today, some of these regions are urbanizing, in the sense that elements of urbanism beyond density, such as a large non-farm economy, are emerging. This paper uses a case study of an Indian district in Bihar to investigate urbanizing ruralopolis settlements. I identify and discuss the planning implications of three distinctive features of their urbanization: circular out-migration, a non-farm economy rooted in consumption and survival entrepreneurship, and shifts in agrarian social hierarchies that present progressive possibilities.

Analysis of pros and cons of quantitive easing

From the financial crisis in 2008 to the impact of the COVID-19 in recent years, quantitative easing, an unconventional economic policy, has become a means for many large economies to alleviate economic recession and stimulate economic growth. QE can not only help overcome the downward pressure of the economy, but also maximize the avoidance of unemployment, inflation and other issues caused by more severe economic crises. This paper focuses on the practical process and effects of the four QEs in the United States, analyzes the pros and cons of QE, and pays attention to the consequences of the current interest rate hike in the United States. It is concluded that QE has a significant effect on stimulating economic growth and boosting the stock market in the short term, but may lead to a long-term slowdown in economic growth and inflation. This analysis enriches the explanation of the QE operation process and is conducive to the more appropriate application of this policy.

Economic Effect and Disparity of Airport Economic Zones Utilizing the Synthetic Control Method

This study investigates the economic impact of an airport economic zone (AEZ) on a city using the synthetic control method (SCM). It is an important issue for small-sized and medium-sized cities to make effective strategic plans for AEZs according to their own characteristics. Cities have begun to imitate the successful experiences of AEZs in cities with larger economies, but they often fail to replicate the same path. Moreover, the current methods are likely to reduce the reliability of the causality argument because of the lack of random sampling and random allocation of treatment. The SCM can solve this problem. In this research, the SCM was used to investigate panel data for 37 small- and medium-sized cities in China for the period 2000–2016. The results showed that the presence of an airport had a significant positive economic effect on cities with a higher economic strength and a weak positive effect on cities with a lower economic strength in our treatment group sample. In investigating the causal mechanism for this disparity, we found that the higher the match between the types of industries laid out in the AEZ and the city’s dominant industries, the better the economic development from a long-term development perspective. In addition, since AEZs are embedded in specific socio-economic contexts, it is sometimes difficult to apply successful experiences to AEZs in less developed cities. Our research utilized a new policy evaluation method and has significant implications for decision-makers.

Export Market Size Matters: The Effect of the Market Size of Export Destinations on Manufacturing Growth

Literature contends that the manufacturing sector is crucial for economic development, and it is conventional wisdom that exports drive manufacturing growth. However, it has yet to be established empirically whether the market size of export destinations is an essential factor in explaining diverging regional and sectoral manufacturing growth patterns. This article argues that accessing a few large external markets reduces entry costs, increases expectations of economies of scale, and fosters capital formation. To test this hypothesis, we construct a novel Relative Export Market Size (REMS) index that measures whether the share of sectoral exports destined to large economies in one region is higher than in other regions. Using a PVAR model with fixed effects, we verify the impact of the REMS index on value added, employment, and capital accumulation of 129 manufacturing sectors in 23 regions in Colombia from 1992 to 2017. The obtained results show that exporting to larger markets positively impacts employment, capital formation, and value added per capita of manufacturing sectors at a regional level. This finding indicates that exporting to the world’s largest market helps develop competitive manufacturing sectors.

Распространение финансового заражения в странах Европы под воздействием глобальных шоков

This article examines the impact of global shocks of various nature on the development of the European economy within the framework of the theory and methodology of financial contagion. The content of the concept of “financial contagion” is revealed. The variety of methods of its detection is considered. It is shown that the methodology of financial contagion is useful in the study of financial crises. Based on data on local crises, the crisis burden indicator for the European region is calculated for the period from 1960 to 2019. In Europe, compared with other regions, this indicator takes on the lowest values, so the European economy is more resilient to crises. At the same time, the analysis of some empirical studies shows numerous episodes of financial contagion in the European zone. The results of original investigation which is based on large scale array of empirical data on stock indices and international trade are presented in the article. An advanced dynamic financial contagion test is used for analysis in this study. For situations caused by four global shocks contagion estimates are calculated which show different susceptibility levels of European countries to these shocks. On the other hand, the results of the analysis suggest that the COVID‑19 pandemic has the strongest impact on European countries because the calculated values of test statistics more often and significantly exceed the threshold level during this period (compared with other shocks such as the global financial crisis, BREXIT and the energy crisis). The main channel of contagion is the stock market, not trading. In addition, it can be noted that large European economies are not immune to financial contagion. They are as much its recipients as the weaker countries of the region. At the same time, they play the role of a damper, i. e. they do not transmit financial contagion within the European zone. Finally, the study identifies some directions of financial contagion counteractions in European countries that are linked to its transmission channels. Examples of the transformation of European economic policy caused by the impact of global shocks, contagion effects and stressful situations are given.

Pakistan’s Trade Insight in Terms of Gravity Model: An Empirical Evidence

This study is intended to analyze the determinants of the trade potential of Pakistan. For the said purpose, the study employed an augmented gravity model over the data of 12 trading partner countries of Pakistan for the period of 20 years from 2002 to 2022. The dependent variable is merchandise trade, while the independent variables consist of core variables i.e., GDP & bilateral distance, and explanatory variables like population, common border, and preferential trade agreement. Breusch-Pegan and Hausman's tests were used for model selection, which proposes that the Random effect model is appropriate for estimation. The results confirm that distance among trading states hurts trade between them. Although the GDP of Pakistan shows a positive effect on trade the relation is inconsequential. However, the impact of GDP on trading associates of Pakistan is positive and highly substantial. The population of trading allies of Pakistan is showing a significant positive impact on trade. Common border and preferential trade agreements between the trading partners have a significant negative influence on trade. The study concludes that for Pakistan, the larger the distance with its trading associate country the smaller the trade among them and Pakistan has greater trading potential with larger economies as compared to smaller ones.

The Development of the Russian Economy in the Paradigm of the Formation of Digital Ecosystems

In the article, the authors give answers to such questions as: what is a digital ecosystem? How is a digital ecosystem different from a digital platform? Why are platforms scaling so quickly? Why are platforms beating traditional products? Why do platforms have a high market capitalization but employ a limited number of employees? What impact do ecosystems have on the multilateral market? How do digital ecosystems differ from traditional ecosystems? The signs of digital ecosystems are analyzed, as well as the network interaction of participants in the digital ecosystem. The authors analyze the degree of influence of the dominant platform of the ecosystem on the development of internal competition, it is also revealed that from the point of view of the digital economy, the competitive development of ecosystems can be facilitated by large economies of scale in product development due to the modular design of digital products and services, and the synergy of consumption that is formed due to technological connection between ecosystem products, increasing the complementarity between them. The authors present the components of the successful development of the ecosystem within the digital economy, as well as analyze the ecosystems that have gained the most popularity today. As a result of the analysis, the authors conclude that entering the ecosystem market is always associated with the risk of competition, which is due to the attraction of new consumers. If the market is dominated by one ecosystem or the number of ecosystems is small, then competition between them may be less intense than competition between specialized companies. Ecosystem companies benefit most from supply and demand synergies, which can be enhanced through complementary products and services.