Future Growth Rates Research Articles

Time budget of a mallard duck population residing in an urban park in northern Portugal during courtship and nesting period

Behavioural observations were used to investigate the temporal dynamics events and associated variation in the daily activities of a sedentary population of mallard duck (Anas platyrhynchos) inhabiting an urban park in northern Portugal. Data was collected at Porto City Park from December to April, during the species’ courtship and early nesting periods. The most frequent activities for this population were locomotion, resting and feeding. Statistical analysis revealed that male and female behaviours differed significantly throughout the courtship period, as males exhibited more displays and aggressive behaviour while females were more prone to feed in order to meet their increased nutritional and energetic needs. Temporal analyses showed that courtship reached a peak in intensity in February, since it was in this month that the highest values for mating, aggressive behaviour in males and defensive behaviour in females were observed. Behavioural differences were found for this population, with higher feeding rates compared to those of wild populations as well as lower defensive behaviour rates. This paper sheds light on how synanthropized populations, as well as those from Southwestern Europe, show different behavioural responses from other populations. Additional extensive monitoring of population dynamics and factors such as latitudinal differences, habituation to humans and climate change will help to predict future growth and expansion rates.

Markov equilibrium of social security: An analytic solution under CRRA utility and the future of social security

The politico-economic sustainability of pay-as-you-go social security has been studied with the help of two-period overlapping generation models under Markovian equilibrium concepts. The literature has mostly used logarithmic utility for tractability, whereas versions under the more general isoelastic CRRA utility have only been analyzed computationally. This paper demonstrates that a prototypical social security model under CRRA utility has a closed-form solution; it revisits previously obtained computational conclusions and presents new findings and extensions. Quantitatively, the model can explain the observed path of payroll tax rates in the USA and predicts increased tax rates as the equilibrium response to lower future population growth rates. The model predicts a gradual increase in tax rates, from the current 12.4% to about 15% or so in 2060, and then staying at that level. Benefits are expected to decrease slowly, by about 2% (or less) per decade, starting in 2030.

Uncertainty reduction for precipitation prediction in North America.

Large differences in projected future annual precipitation increases in North America exists across 27 CMIP6 models under four emission scenarios. These differences partly arise from weak representations of land-atmosphere interactions. Here we demonstrate an emergent constraint relationship between annual growth rates of future precipitation and growth rates of historical temperature. The original CMIP6 projections show 0.49% (SSP126), 0.98% (SSP245), 1.45% (SSP370) and 1.92% (SSP585) increases in precipitation per decade. Combining observed warming trends, the constrained results show that the best estimates of future precipitation increases are more likely to reach 0.40-0.48%, 0.83-0.93%, 1.29-1.45% and 1.70-1.87% respectively, implying an overestimated future precipitation increases across North America. The constrained results also are narrow the corresponding uncertainties (standard deviations) by 13.8-31.1%. The overestimated precipitation growth rates also reveal an overvalued annual growth rates in temperature (6.0-13.2% or 0.12-0.37°C) and in total evaporation (4.8-14.5%) by the original models' predictions. These findings highlight the important role of temperature for accurate climate predictions, which is important as temperature from current climate models' simulations often still have systematic errors.

Opportunities and challenges in single‐cell protein production using lignocellulosic material

AbstractThe increase in world population has led to an increase in global food demand, which is estimated to grow by 35–56% from 2010 to 2050. As a result, the risk of hunger is also expected to rise. Protein consumption between 2000 and 2018 rose by 40% worldwide and is expected to increase at 9.3% cumulative annual growth rate in the near future. Hence, there is a huge demand and potential market available for human and animal protein. Therefore, newer and more protein sources will be required to meet the longer food value chains. Hence, a microbial protein produced using waste biomass could offer socio‐economic benefits and consumer acceptance owing to its vegetarian nature. Moreover, waste biomass‐based proteins are environmentally benign and very good ingredients in food and feed. Dry microbial protein, described as single‐cell protein, grown on agricultural residue, has been considered as a potent source of protein for both humans and animals. Thus, single‐cell protein will open up new opportunities to meet the growing protein demands for humans and animals. Microbially produced beer, cheese and yogurt are all examples of microbial protein sources for humans and animals. The feedstock, like agriculture residue, is relatively cheap and could be a potential source for large‐scale protein production in the future.

Integrating climate change induced flood risk into future population projections

Flood exposure has been linked to shifts in population sizes and composition. Traditionally, these changes have been observed at a local level providing insight to local dynamics but not general trends, or at a coarse resolution that does not capture localized shifts. Using historic flood data between 2000-2023 across the Contiguous United States (CONUS), we identify the relationships between flood exposure and population change. We demonstrate that observed declines in population are statistically associated with higher levels of historic flood exposure, which may be subsequently coupled with future population projections. Several locations have already begun to see population responses to observed flood exposure and are forecasted to have decreased future growth rates as a result. Finally, we find that exposure to high frequency flooding (5 and 20-year return periods) results in 2-7% lower growth rates than baseline projections. This is exacerbated in areas with relatively high exposure to frequent flooding where growth is expected to decline over the next 30 years.

Collusion or governance? Common ownership and corporate risk‐taking

AbstractResearch QuestionDisputes over the corporate governance impacts of common ownership continue. Differentiating from existing studies, we focus on the Chinese stock market, exploiting the Top 10 Shareholding File, which includes various investors besides institutional investors, to study the impact of common ownership built through blockholders on corporate risk‐taking behavior.Research FindingsWe find that firms with higher common ownership are less likely to engage in corporate risk‐taking, with concomitant decreases in future growth rates. Mechanism analysis shows that blockholders' common ownership exerts its influence through increasing market concentration, with concomitant lessening of market competition. Interestingly, further analyses indicate that, in contrast to blockholders, ownership connectedness built by mutual fund families significantly raises corporate risk‐taking along with growth. However, individual investors' common ownership does not show the significant statistical relationship with corporate risk‐taking.Theoretical ImplicationsWe add to the debate on common ownership on corporate governance. Consistent with the anti‐competition stream of literature, the risk‐taking‐reduction role we identify for blockholder common ownership supports the theory of anti‐competition. Our results highlight the need to consider the heterogeneity of common ownership.Policy ImplicationsWhile blockholder common ownership is evidenced to have a negative effect on corporate risk‐taking, with, by extension, a negative impact on economic development, our results also suggest that efficient monitoring mitigates these effects. We also document an interesting heterogeneity in investor types. Mutual fund common ownership, in contrast to blockholder common ownership, is associated with higher risk‐taking and more robust firm growth. This suggests the positive role of institutions in corporate governance and the necessity of considering the heterogeneity of common ownership.

Leadership in Agriculture: Artificial Intelligence for Modelling and Forecasting Growth in the Industry

The paper investigates the growth rates of agriculture as one of the leading industries, which serves as a catalyst for economic development and is intended to provide the population with food products and industry with raw materials. The main aim of the conducted research is to analyze the impact of agricultural reforms on the agricultural growth rates in Algeria. The systematic analysis of literary sources and methods of addressing the problem of agricultural growth indicates the existence of socio-economic, political, and institutional inhibitors of effective agricultural reclamation of the agricultural sector. Five inputs were used as parameters characterizing the development of the agricultural industry. These are the volume of agricultural financing, the volume of exploited agricultural area, the volume of developed agricultural machinery, the volume of agricultural labor, and the rural level of agricultural growth. Forecasting indicators of the development of the agricultural industry was carried out using the methods of min max scaler tool, ReLU, and RMSE. A machine learning model from the Python language built the artificial neural network model. The statistical data of the Ministry of Finance and Agriculture and the World Bank served as the information base for the study of the relationship between the amount of adopted and implemented agrarian reforms. The link between the number of agrarian reforms adopted and expressed was investigated using data from several areas of statistics, the Ministry of Finance and Agriculture, and the World Bank. The modelling results proved the positive influence of bank financing, the volume of exploited agricultural areas and the number of the population employed in agriculture on the growth rates of agriculture in Algeria in the long term. An increase in agricultural mechanization by one unit (tractors and agricultural equipment per 100 km2) contributes to the growth of indicators of agricultural development by 0.21%, and an increase in the number of people employed in agriculture per million will lead to a rise in the level of agricultural development by 12 %. Thus, the results of econometric modelling proved the positive impact of agricultural reforms on the development of agriculture after 2022. It contributes to the increase in the level of employment of the population and, ultimately, will have a positive effect on the future rate of economic growth in Algeria.

Consumer Preference on Food Delivery Services Before and After the COVID-19 Outbreak

The sustainability of the food delivery services industry remains questionable as time finally reaches the end of the COVID-19 pandemic. People are no longer forced to decide on any dining options. Therefore, it is significant to identify how consumer preference changes over the pandemic to predict better the future growth rate of the food delivery services industry. This study aims to identify the leading factors that affect consumers decision-making in choosing food delivery services and to explore how the consumer preference toward food delivery services has changed before and after the the COVID-19 pandemic. This study also examines how consumer behaviors change according to the environmental change in their living status. The study uses data and an empirical approach to purposefully and methodically determine the causal relationship between the conditions and phenomena provided in the above research subject, consumer preference for food delivery services. The study suggests that consumer preference is enhanced through the pandemic and is unlikely to slow down after the outbreak ends because other dining options' experiential values from the service's features are irreplaceable. By analyzing the data obtained from other literature resources and statistical evidence, it is sure to conclude that consumer behavior toward prioritizing food delivery services is unlikely to change due to the attractiveness of the service still maintained after the pandemic.

Proactive Fiscal Policy: The New Logic of China’s Practice

China’s proactive fiscal policy adheres to the development ideology centered around the people and differs from the traditional Western logic of macro-fiscal policy. It bears distinct Chinese characteristics and represents a significant macroeconomic governance policy innovation in China’s process of modernization. Despite the considerable differences between the perspectives of the Keynesian tradition and the non-Keynesian tradition, their policy objectives and methodological foundations are broadly similar, constituting the traditional Western logic of macro-fiscal policy. Currently, this logic is facing increasing practical challenges. In contrast, China’s proactive fiscal policy not only aims to restore supply-demand balance and potential growth levels but also emphasizes enhancing future potential growth rates, marking a transformation from the traditional Western logic to a new logic. It is essential to emphasize that under this new logic, forming a new fiscal policy paradigm requires a reevaluation of the nature and appropriate scale of fiscal deficits, the role and risk measurement standards of government debt, the space and effectiveness of reduction of taxes and administrative fees, demand management methods and priorities, as well as policy costs and efficiency, among other fundamental categories.

The effects of debt liquidity risk on firms' growth rate

PurposeIn theory, the impact of debt liquidity risk (DLR) on the firm's future growth is ambiguous. This study aims to examine the empirical relationship between the DLR and firms' growth rate using annual data for USA companies from 1976 to 2020.Design/methodology/approachGiven the longitudinal nature of the data, the author uses OLS (ordinary least squares) regression methodology with fixed effects to control for unobserved characteristics that might affect the dependent variable. Instrument variable regression is also used to address the potential endogeneity problem.FindingsThe results show that firms having higher DLR, as proxied by more short-term debt, experience lower growth rate. An increase in firms' short-term debt decreases the firms' future growth rate as evidenced by lower assets, revenue and employee growth rate. Moreover, the authors' results show that small firms or firms with more investment opportunities grow fast if the firms take higher DLR. Finally, cyclical firms with higher DLR exhibit lower growth rate during the credit tighten period. The authors' results hold for both the pre-zero lower bound (ZLB) era and ZLB period.Originality/valueTo the authors' best knowledge, this is one of the earliest studies to carefully examine the effects of DLR on firms' growth rate. While prior research finds that firms with higher growth potential, measured by market-to-book (MTB) ratio, use more short-term debt, the authors' research directly addresses whether DLR affects firms' future growth rate. The authors’ findings also help explain why firms with high growth potential use more short-term debt.

Analysis of economic growth forecast based on regression model

In this paper, the population growth retardation model, the unitary linear regression model and the multiple linear regression model are established to solve the problem. After considering the year and population relationship, the total population and the future labor population are predicted by the growth retardation model, and the future education investment and the investment in fixed assets of the whole society are predicted by the unitary linear regression model. After considering such factors as education investment, total population, labor force population, and investment in fixed assets of the whole society, establish a linear relationship between the economy and these factors, and then solve the change of GDP under the joint influence of these factors through multiple regression analysis, and then predict that the economic growth rate in the next 20 years will be 4.71%, 4.49%, 4.29%, 4.10%, 3.93%, 3.78%, 3.64%, 3.51% 3.39%, 3.28%, 3.18%, 3.08%, 2.99% 2.91%, 2.83%, 2.75%, 2.68%, 2.61%, 2.55%, 2.48%. It can be seen that the future economic growth rate shows a downward trend. The growth rate of GDP per capita in the next 20 years will be 4.26%, 4.05%, 3.86%, 3.69%, 3.54%, 3.40%, 3.27%, 3.15%, 3.05%, 2.95%, 2.86%, 2.77%, 2.69%, 2.62%, 2.54%, 2.48%, 2.42%, 2.36%, 2.30%, 2.25%, showing a decreasing trend. Finally, it is concluded that the average annual growth rate of GDP per capita in the next 20 years will be 7%.

Renewable energy consumption and per capita income: An empirical analysis in Finland

Over the past decade, population growth and industrialization have been the driving force behind the increase in greenhouse gas emissions. The implementation of modern technologies capable of producing energy from renewable sources is insufficient to meet the demand for energy, which is experiencing a strong growth trend. In the last decade, it has been possible to observe a decrease in the use of oil and a significant increase in renewables, the inconsistency and unmanageability of which make it impossible to balance supply and demand. However, these have a positive impact not only on the environment, but also on the development in the economic field and employment. This study aims to examine the current relationship between economic growth and renewable energy consumption, for the period 1990–2019, on the territory of Finland, through a Granger causality test. The variables used for this work are renewable energy consumption, GDP, trade, and gross capital formation. The results are significant and lead to important policy implications; in fact, the analysis shows a feedback effect between renewable energy consumption and economic growth, and, through the Granger causality test, it is shown how renewable energy consumption can affect the rate of future growth.

RNA Expression Signatures of Intracranial Aneurysm Growth Trajectory Identified in Circulating Whole Blood.

After detection, identifying which intracranial aneurysms (IAs) will rupture is imperative. We hypothesized that RNA expression in circulating blood reflects IA growth rate as a surrogate of instability and rupture risk. To this end, we performed RNA sequencing on 66 blood samples from IA patients, for which we also calculated the predicted aneurysm trajectory (PAT), a metric quantifying an IA's future growth rate. We dichotomized dataset using the median PAT score into IAs that were either more stable and more likely to grow quickly. The dataset was then randomly divided into training (n = 46) and testing cohorts (n = 20). In training, differentially expressed protein-coding genes were identified as those with expression (TPM > 0.5) in at least 50% of the samples, a q-value < 0.05 (based on modified F-statistics with Benjamini-Hochberg correction), and an absolute fold-change ≥ 1.5. Ingenuity Pathway Analysis was used to construct networks of gene associations and to perform ontology term enrichment analysis. The MATLAB Classification Learner was then employed to assess modeling capability of the differentially expressed genes, using a 5-fold cross validation in training. Finally, the model was applied to the withheld, independent testing cohort (n = 20) to assess its predictive ability. In all, we examined transcriptomes of 66 IA patients, of which 33 IAs were "growing" (PAT ≥ 4.6) and 33 were more "stable". After dividing dataset into training and testing, we identified 39 genes in training as differentially expressed (11 with decreased expression in "growing" and 28 with increased expression). Model genes largely reflected organismal injury and abnormalities and cell to cell signaling and interaction. Preliminary modeling using a subspace discriminant ensemble model achieved a training AUC of 0.85 and a testing AUC of 0.86. In conclusion, transcriptomic expression in circulating blood indeed can distinguish "growing" and "stable" IA cases. The predictive model constructed from these differentially expressed genes could be used to assess IA stability and rupture potential.

Chinese Economic Growth Projections Based on Mixed Data of Carbon Emissions under the COVID-19 Pandemic

Current research on carbon emissions and economic development has tended to apply more homogeneous low-frequency data to construct VAR models with impulse responses, ignoring some of the sample information in high-frequency data. This study constructs a MIDAS model to forecast GDP growth rate based on monthly carbon emission data and quarterly GDP data in the context of the COVID-19 pandemic. The results show that: (1) The MIDAS model has smaller RMSE than the VAR model in short-term forecasting, and provides more stable real-time forecasts and short-term forecasts of quarterly GDP growth rates, which can provide more accurate reference intervals; (2) China’s future macroeconomic growth rate has recently declined due to the impact of the sudden epidemic, but the trend is generally optimistic. By improving urban planning and other methods, the authorities can achieve the two-carbon goal of carbon capping and carbon neutrality at an early date. In the context of the impact of COVID-19 on China’s economic development, we need to strike a balance between ensuring stable economic growth and ecological protection, and build environmentally friendly cities, so as to achieve sustainable economic and ecological development and enhance human well-being.

Developing a Decision Support System for Evaluating an Investment in Fare Collection Systems in Transit

This article presents the initial development of a decision support system (DSS) to assess cost impacts of upgrading or replacing a transit ticketing and fare collection (TFC) system. Assessment of these costs, typically, requires extensive calculations and involves estimation of unknown parameters such as future ridership growth rate, equipment utilization rate, and interest rate on debt financing. This DSS is developed with two categories of policy- and decision-makers in mind—transit agency managers and transit industry researchers and policy-makers.With the aid of this DSS, a transit manager or analyst is able to specify current TFC system characteristics, select desirable options for a new TFC system, and in a matter of minutes estimate capital costs, forecast operating costs, perform net present value and payback period analyses for alternative TFC systems. This article also presents a prototype TFC DSS including a model base, database, knowledge base, and the Microsoft Excel-based graphical user interface.

The abundance and persistence of Caprinae populations

Stable or growing populations may go extinct when their sizes cannot withstand large swings in temporal variation and stochastic forces. Hence, the minimum abundance threshold defining when populations can persist without human intervention forms a key conservation parameter. We identify this threshold for many populations of Caprinae, typically threatened species lacking demographic data. Doing so helps triage conservation and management actions for threatened or harvested populations. Methodologically, we used population projection matrices and simulations, with starting abundance, recruitment, and adult female survival predicting future abundance, growth rate (λ), and population trend. We incorporated mean demographic rates representative of Caprinae populations and corresponding variances from desert bighorn sheep (Ovis canadensis nelsoni), as a proxy for Caprinae sharing similar life histories. We found a population’s minimum abundance resulting in ≤ 0.01 chance of quasi-extinction (QE; population ≤ 5 adult females) in 10 years and ≤ 0.10 QE in 30 years as 50 adult females, or 70 were translocation (removals) pursued. Discovering the threshold required 3 demographic parameters. We show, however, that monitoring populations’ relationships to this threshold requires only abundance and recruitment data. This applied approach avoids the logistical and cost hurdles in measuring female survival, making assays of population persistence more practical.

Organic and Acquisitive Growth: Replicating and Extending Lockett, Wiklund, Davidsson, Girma (2011)

We replicate and extend the work from Lockett, Wiklund, Davidsson, and Girma (2011), investigating how organic and acquisitive growth strategies influence future organic growth rates. Analysing a panel of Dutch firms over the period 2011-2016, we confirm Lockett et al.’s finding that past organic growth exerts a restraining effect on current organic growth. Unlike the original paper, we also find that acquisitive growth hinders rather than sustains subsequent organic growth. We therefore extend Lockett et al.’s framework by explicitly accounting for how the relatedness and complementarity of acquisitions moderate this effect. We observe that this negative effect is less pronounced when acquisitive growth is less related and complementary. Finally, we refine the identification strategy further developing the empirical analysis.

Looking for ecological sustainability: A dynamic evaluation and prediction on the ecological environment of the belt and road region

Since its inauguration, the Belt and Road (B&R) Initiative has gained tremendous popularity and become one of great potential international cooperation platforms. Sustainable development is a central issue of this vast project, but current research is insufficient in this regard. This paper evaluated the status of B&R's ecological sustainability and resource utilization efficiency (RUE) from 1991 to 2017, analyzed the driving factors behind ecological footprint (EF) per capita, predicted the ecological sustainability trend for the next 10 years, and compared them with the globe. The results show that EF per capita in the B&R and global regions were always higher than the biocapacity (BC) per capita, and ecological deficit always existed and kept growing. But both the EF and BC per capita of the B&R countries were lower than the global average, with the EF had increased more rapidly and the BC had decreased even less, indicating that B&R had a relatively more resilient eco-environmental background to support its development. For RUE, the improvement in the B&R region was significantly faster than the globe, with the gap between B&R and the globe rapidly narrowing, indicating that there is still considerable room for RUE to improve in this region. For the driving factors, which have a great impact on EF per capita, nevertheless the main factors of each country are different, and the driving direction of each factor also varies among countries. The prediction results show that under the current development model, the future EF growth rate of the B&R region will still be relatively higher, but the decline rate in BC will be obviously lower than that of globe, indicating that the region is still facing huge ecological pressure, substantial improvement potential, and needs to adopt a development model that reduces its EF more effectively. Finally, combined with the analysis of coordinated development and driving factors, we outlined some crucial policy implications for B&R's sustainable development.

MARKET CAPITALIZATION OF THE STOCK IN BIRTH - DEATH PROCESSES

In this article the inability to predict the future growth rates and earnings of growth stocks leads to the high volatility of share prices and difficulty in applying the traditional valuation methods. To demonstrate that the high volatility of share prices can nevertheless be used in building a model that leads to a particular cross-sectional size distribution. The model focuses on both transient and steady-state behavior of the market capitalization of the stock, which in turn is modeled as a birth-death process.

Optimal solution of the liquidation problem under execution and price impact risks

We consider an investor that trades continuously and wants to liquidate an initial asset position within a prescribed time interval. As a consequence of his trading activity, during the execution of the liquidation order, the investor has no guarantees that the placed order is executed immediately; it may go unfilled, partially filled or filled in excess. The uncertainty in the execution affects the trading activity of the investor and the asset share price dynamics generating additional sources of noise: the execution risk and the price impact risk, respectively. Assuming the two sources of noise correlated and driven by the cumulative effect of the investor trading strategy, we study the problem of finding the optimal liquidation strategy adopted by the investor in order to maximize the expected revenue resulting from the liquidation. The mathematical model of the liquidation problem presented here extends the model of Almgren and Chriss [Optimal execution of portfolio transactions. J. Risk, 2000, 3(2), 5–39] to include execution and price impact risks. The liquidation problem is modeled as a linear quadratic stochastic optimal control problem with the finite horizon and, under some assumptions about the functional form for the magnitude of execution and price impact risks, is solved explicitly. The derived solution coincides with the optimal trading strategy obtained in the absence of execution uncertainty for an asset price with a modified growth rate. This suggests that the uncertainty in the execution modifies the directional view of the investor about the future growth rate of the asset price.