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AbstractThe paper examines the relationship between health and economic growth using a dynamic panel with threshold effect and endogeneity. The study uses a sample of 136 countries over the period of 1965–2015 and the results indicate that the relationship between health and economic growth is nonlinear. The findings suggest that the impact of health on economic growth is only positive in countries that have attained minimum benchmarks of health improvement. These findings carry significant policy implications. Low-income countries need a comprehensive approach, encompassing multiple factors, such as education enhancement, productivity boost, and entrepreneurship promotion, that go beyond health promotion to foster substantial economic growth. In countries already attaining satisfactory health outcomes, policies prioritizing improved health outcomes, through directing investments towards Research and Development can serve as an effective means to promote sustainable economic growth.

Abstract Key message We have examined thermal control for embryo growth and seed germination in European ash. Using historical data (span of 36 years) of embryo index in matured seeds, we showed that maturation is not influenced by the annual average temperature. Secondary dormancy in ash’s seeds is easily induced, and the thermal window for both embryo growth and seed germination was between 10 and 20 °C. Context Seed germination plays a crucial role in establishing plant communities. Ash seeds are characterized by deep morphophysiological dormancy, usually overcome by 32 weeks of stratification. Observed climate changes might disrupt ash’s thermal window for embryo growth and seed germination. Thus, proper examination of seed adaptability can be important for forest management. Aims We investigated the effect of temperature on the embryo index (ratio between embryo and seed length) as well as embryo growth and germination of European ash (Fraxinus excelsior L.) seeds under different thermal conditions. Methods We used seeds collected at the same site in Poland between 1985 and 2021 to first analyze the influence of the growing season on the initial embryo index in mature seeds. Subsequently, we examined embryo growth and germination of seeds at constant temperatures of 3°, 10°, 15°, 20°, 25°, and 30 °C from seeds collected in 2021. Using the modeled rate of embryo growth and germination, we predicted the cardinal temperatures for those processes in ash seeds. Results The embryo index of ash seeds varied; however, there was no relationship between the index and year of seed collection. The base temperature for embryo growth was 1.4 ± 1.1 °C, with a ceiling temperature of 29.9 ± 2.0 °C and an optimal temperature of 15.7 ± 0.3 °C. The base temperature for germination was at − 1.8 ± 0.3 °C. Due to the induction of secondary dormancy, the ceiling temperature of germination was impossible to establish. Conclusions The initial embryo index of mature ash seeds seems to be an individual trait and was not affected by local average annual temperatures. The most effective temperature ranges for embryo growth and germination were similar, however narrow (between 10 and 15 °C). Temperatures above 20 °C inducted secondary dormancy, hampering embryo growth as well as germination. Such a narrow thermal window for embryo growth can potentially act as a limiting factor for the natural regeneration of ash seeds.

In this paper, the relationship between energy consumption and total factor productivity (TFP) in the industrial sector in Iran has been investigated using threshold-type nonlinear relationships. The results of estimating a two-threshold model in a sample including data related to 110 industrial branches during the years 2002-2019 show that the effect of energy consumption on the TFP in the industry sector is state-dependent on the energy consumption state or regime and the energy consumption variable coefficients in all regimes has a negative and significant effect on the TFP. If the energy consumption in Iran's industrial sector exceeds a certain threshold, the negative effect of energy consumption on the TFP will intensify. Also, the effect of energy consumption on the TFP in the industry sector is a state dependent on the TFP state or regime, so in low TFP regimes or states, the effect of energy consumption on the TFP of industries is considerable, but in high TFP regimes, industries with higher TFP have a much lower negative impact of energy consumption on their TFP.

The aim of this study is to test the possible non-linear effect of environmental policy stringency on carbon emissions and thus make policy recommendations for emission reduction. For this purpose data for the period 1995–2015 for selected emerging countries were used. According to the findings obtained from fixed-effects panel threshold regressions environmental policy stringency has no significant effect on the relationship between gross domestic product per capita and carbon dioxide emissions. However, it has statistically significant effect if the share of the service sector and the foreign direct investment are taken as regime-dependent variables. Accordingly, in the high policy stringency regime an increase in the share of the service sector and the foreign direct investment reduce emission levels. In the case of using market-based environmental regulations the threshold effect faced by foreign direct investment is much more pronounced. In order to reduce carbon emissions it is recommended to increase environmental policy stringency, especially in market-based tools.

Background: Litter size at birth (LSB) is one of the most important economic traits in sheep and could be used in genetic improvement schemes for meat production. LSB is inherently a categorical trait and should be analysed with threshold models. Objective: Bayesian threshold models were used to analyze sheep LSB to estimate genetic parameters. Methods: Data was based on 7,901 LSB records from 14,968 dams and 682 sires collected from 1986 to 2012 at Makouie Sheep Breeding Station in Iran. Means of posterior distributions (MPDs) of LSB's genetic parameters were estimated, and the best-fitted models were selected using the deviance information criterion. Results: In the repeated measurement analysis, the estimated direct and maternal heritabilities, and permanent environmental effect (±SE), according to the best-fitted model (model 5), were 0.01 (0.010), 0.02 (0.014), and 0.01 (0.011), respectively. In the univariate analysis, the best estimates of direct and maternal heritabilities were 0.12 (0.064) and 0.08 (0.045), respectively. An increasing trend for direct and maternal heritabilities was observed in parity 2 (0.15 (0.082) and 0.25 (0.083), respectively). In the bivariate analysis, the best estimates of direct and maternal heritabilities for LSB were 0.03 (0.027) and 0.22 (0.041), respectively. The direct and maternal genetic correlations among parities were 0.25 (0.054) and 0.12 (0.021), respectively. Conclusions: The results showed a considerable influence of environmental factors on LSB in each parity of sheep; also, statistically different genetic parameters (p

Abstract According to innovation diffusion theories, the adoption of a new product is the result of a dynamic process whereby individuals become likelier to adopt as others do. Agent-based modelling has emerged as a useful technique to model and study processes of innovation diffusion within artificial societies, as it allows to easily programme and simulate the interaction of multiple agents among them and with their environment. Despite a large body of literature dealing with innovation of diffusions, including the use of agent-based modelling, there has been little to no consideration of two elements that are important features of consumption: the presence of multiple characteristics of goods, and that of price-premiums on the presence of added characteristics. We propose an agent-based model of the diffusion of such goods, and study its emerging properties when compared to standard ones. Our goal is to try and understand how social interaction affects the consumption of goods that are complex rather than uni-dimensional, and whose prices depend on the number of dimensions (characteristics) that are present. Testing the model for different parameters shows that as goods become more complex, social interaction becomes an increasingly important explanatory variable for purchases. This opens up interesting avenues of discussion for those seeking to bring together innovation diffusion theories and goods’ complexity, and can be linked with a number of issues in the social and sustainability sciences.

Objective The objective of the study was to investigate the possibility of utilizing an early litter size trait as an indirect selection trait for longevity and to estimate genetic parameters between sow stayability and litter size at different parities using a linear-threshold model for longevity in Thai Large White (LW) and Landrace (LR) populations. Methods The data included litter size at first, second, and third parities (NBA1, NBA2, and NBA3) and sow stayability from first to fourth farrowings (STAY14). The data was obtained from 10,794 LR and 9,475 LW sows. Genetic parameters were estimated using the multiple-trait animal model. A linear-threshold model was used in which NBA1, NBA2, and NBA3 were continuous traits, while STAY14 was considered a binary trait. Results Heritabilities for litter size were low and ranged from 0.01 to 0.06 for both LR and LW breeds. Similarly, heritabilities for stayability were low for both breeds. Genetic associations between litter size and stayability ranged from 0.43 to 0.65 for LR populations and 0.12 to 0.55 for LW populations. The genetic correlation between NBA1 and STAY14 was moderate and in a favorable direction for both LR and LW breeds (0.65 and 0.55, respectively). Conclusion A linear-threshold model could be utilized to analyze litter size and sow stayability traits. Furthermore, selection for litter size at first parity, which was the genetic trait correlated with longevity, is possible when one attempts to improve lifetime productivity in Thai swine populations.

Abstract Loss and degradation of grasslands in the Great Plains region have resulted in major declines in abundance of grassland bird species. To ensure future viability of grassland bird populations, it is crucial to evaluate specific effects of environmental factors among species to determine drivers of population decline and develop effective conservation strategies. We used threshold models to quantify the effects of land cover and weather changes in "lesser prairie‐chicken" and "greater prairie‐chicken" (Tympanuchus pallidicinctus and T. cupido, respectively), northern bobwhites (Colinus virginianus), and ring‐necked pheasants (Phasianus colchicus). We demonstrated a novel approach for estimating landscape conditions needed to optimize abundance across multiple species at a variety of spatial scales. Abundance of all four species was highest following wet summers and dry winters. Prairie chicken and ring‐necked pheasant abundance was highest following cool winters, while northern bobwhite abundance was highest following warm winters. Greater prairie chicken and northern bobwhite abundance was also highest following cooler summers. Optimal abundance of each species occurred in landscapes that represented a grassland and cropland mosaic, though prairie chicken abundance was optimized in landscapes with more grassland and less edge habitat than northern bobwhites and ring‐necked pheasants. Because these effects differed among species, managing for an optimal landscape for multiple species may not be the optimal scenario for any one species.

According to the recognition heuristic (RH), for decision domains where recognition is a valid predictor of a choice criterion, recognition alone is used to make inferences whenever one object is recognized and the other is not, irrespective of further knowledge. Erdfelder, Küpper-Tetzel, and Mattern (2011) questioned whether the recognition judgment itself affects decisions or rather the memory strength underlying it. Specifically, they proposed to extend the RH to the memory state heuristic (MSH), which assumes a third memory state of uncertainty in addition to recognition certainty and rejection certainty. While the MSH already gathered significant support, one of its basic and more counterintuitive predictions has not been tested so far: In guessing pairs (none of the objects recognized), the object more slowly judged as unrecognized should be preferred, since it is more likely to be in a higher memory state. In this paper, we test this prediction along with other recognition latency predictions of the MSH, thereby adding to the body of research supporting the MSH.

According to the recognition heuristic (RH), for decision domains where recognition is a valid predictor of a choice criterion, recognition alone is used to make inferences whenever one object is recognized and the other is not, irrespective of further knowledge. Erdfelder, Küpper-Tetzel, and Mattern (2011) questioned whether the recognition judgment itself affects decisions or rather the memory strength underlying it. Specifically, they proposed to extend the RH to the memory state heuristic (MSH), which assumes a third memory state of uncertainty in addition to recognition certainty and rejection certainty. While the MSH already gathered significant support, one of its basic and more counterintuitive predictions has not been tested so far: In guessing pairs (none of the objects recognized), the object more slowly judged as unrecognized should be preferred, since it is more likely to be in a higher memory state. In this paper, we test this prediction along with other recognition latency predictions of the MSH, thereby adding to the body of research supporting the MSH.

It has been well stated that high values of blood pressure constitute a risk factor for cardiovascular diseases [20], with the latter being the number one death cause in Portugal. The main interest of the present study is to model the high values of systolic blood pressure in the individuals of the population who are most at risk, i.e., the elderly. This group frequently suffers from a specific type of hypertension pathology, known as isolated systolic hypertension. With that purpose the Peaks Over Threshold methodology was applied, which consists in fitting a generalized Pareto distribution to the excesses above a sufficiently high threshold. The model will be able to estimate extreme quantiles and tail probabilities.

The study seeks to investigate whether non-linear patterns are present in the returns of two indices on the stock markets in Ghana and Nigeria between the period of 2011 and 2015.The results of applying four linearity tests on the returns concluded that the null of linearity is rejected on all four tests for the Ghanaian index but mixed for the Nigerian index. We modelled the indices under the non-linear self-exciting threshold autoregressive (SETAR) model. We compared the modelling performance of the non-linear SETAR model with that of the standard AR (1) and AR (2) by analyzing AIC values of the respective models. Our results show that the SETAR model fits the data well. Hence, modelling stock market returns from Ghana and Nigeria using linear models might lead to spurious conclusions.

Habitat loss and degradation compound the effects of climate change on wildlife, yet responses to climate and land cover change are often quantified independently. The interaction between climate and land cover change could be intensified in the Great Plains region where grasslands are being converted to row-crop agriculture concurrent with increased frequency of extreme drought events. We quantified the combined effects of land cover and climate change on a species of conservation concern in the Great Plains, the Lesser Prairie-Chicken (Tympanuchus pallidicinctus). We combined extreme drought events and land cover change with lek count surveys in a Bayesian hierarchical model to quantify changes in abundance of male Lesser Prairie-Chickens from 1978 to 2014 in Kansas, the core of their species range. Our estimates of abundance indicate a gradually decreasing population through 2010 corresponding to drought events and reduced grassland areas. Decreases in Lesser Prairie-Chicken abundance were greatest in areas with increasing row-crop to grassland land cover ratio during extreme drought events, and decreased grassland reduces the resilience of Lesser Prairie-Chicken populations to extreme drought events. A threshold exists for Lesser Prairie-Chickens in response to the gradient of cropland:grassland land cover. When moving across the gradient of grassland to cropland, abundance initially increased in response to more cropland on the landscape, but declined in response to more cropland after the threshold (δ=0.096, or 9.6% cropland). Preservation of intact grasslands and continued implementation of initiatives to revert cropland to grassland should increase Lesser Prairie-Chicken resilience to extreme drought events due to climate change.

This article follows the main contributions brought to the nonlinear modeling literature. We investigate and review a series of parametric initiatives, focusing on the evolution of TAR and ARCH – GARCH model families in econometric and forecasting applications.

The efficacy of the entry price policy in the European fresh fruits and vegetables sector is not well understood. We investigate econometrically the efficacy of the import policy. The analysis estimates a threshold vector autoregressive model using data on imports the main competing country on the European Union domestic markets. Our results allow concluding on the insulating effects induced by the entry price system. We argue that the quota restrictions are likely to provide larger contribution to the domestic market stabilization. Policy implications are provided.

This paper investigates the possibility to obtain better GDP forecasts in the early stages of Great Recession. Here, predictive performance refers to exclusively out-of-sample forecasts. Based on exploratory data analysis and general-to-specific modelling, this paper proposes a univariate predictive threshold model for the small open economy that outperforms its linear counterparts and correctly determines the course of events. This model does not explain any causal links; however, based on a set of economic arguments, it sets forward an idea regarding how a forecaster can act when principal determinant factors, responsible for a sudden, yet lasting change, are unknown, unmeasurable or cannot be influenced by national policy makers. A major dissimilarity between usual threshold models and the model presented in this paper is that while variables act differently under different conditions in the former, in this model, due to economic reasons, errors act differently. Alternatively, this paper can be viewed as a comparative GDP prediction study.

Judgments and decisions under uncertainty are frequently linked to a prior sequential search for relevant information. In such cases, the subject has to decide when to stop the search for information. Evidence accumulation models from social and cognitive psychology assume an active and sequential information search until enough evidence has been accumulated to pass a decision threshold. In line with such theories, we conceptualize the evidence threshold as the “desired level of confidence” (DLC) of a person. This model is tested against a fixed stopping rule (one-reason decision making) and against the class of multi-attribute information integrating models. A series of experiments using an information board for horse race betting demonstrates an advantage of the proposed model by measuring the individual DLC of each subject and confirming its correctness in two separate stages. In addition to a better understanding of the stopping rule (within the narrow framework of simple heuristics), the results indicate that individual aspiration levels might be a relevant factor when modelling decision making by task analysis of statistical environments.

Judgments and decisions under uncertainty are frequently linked to a prior sequential search for relevant information. In such cases, the subject has to decide when to stop the search for information. Evidence accumulation models from social and cognitive psychology assume an active and sequential information search until enough evidence has been accumulated to pass a decision threshold. In line with such theories, we conceptualize the evidence threshold as the ``desired level of confidence'' (DLC) of a person. This model is tested against a fixed stopping rule (one-reason decision making) and against the class of multi-attribute information integrating models. A series of experiments using an information board for horse race betting demonstrates an advantage of the proposed model by measuring the individual DLC of each subject and confirming its correctness in two separate stages. In addition to a better understanding of the stopping rule (within the narrow framework of simple heuristics), the results indicate that individual aspiration levels might be a relevant factor when modelling decision making by task analysis of statistical environments.

Data from 2032 Uruguayan Aberdeen Angus cows under extensive management and recording practices were analysed with Bayesian threshold-liability sire models, to assess genetic variability in calving success (CS), defined as a different binary trait for each of the second (CS2), third (CS3) and fourth (CS4) calving opportunities. Sire (herd) variances ranged from 0.08 to 0.11 (0.10 to 0.20) and heritability from 0.27 to 0.35, with large credibility intervals. Correlations between herd effects on CS at different calving opportunities were positive. Genetic correlation between CS2 and CS4 was positive (0.68), whereas those involving adjacent calving opportunities (CS2–CS3 and CS3–CS4) were negative, at −0.39 and −0.54, respectively. The residual correlation CS2–CS3 was negative (−0.32). The extent of uncertainty associated with the posterior estimates of the parameters was further evaluated through simulation, assuming different true values (−0.4, −0.2, +0.2 and +0.4) for the genetic correlations and changes in the degree of belief parameters of the inverse Wishart priors for the sire covariance matrix. Although inferences were not sharp enough, CS appears to be moderately heritable. The quality of data recording should be improved, in order to effect genetic improvement in female fertility.

Previous studies showed that the influence of meteorological variables and concentrations of other air pollutants on O3 concentrations changes at different O3 concentration levels. In this study, threshold models with artificial neural networks (ANNs) were applied to characterize the O3 behavior at an urban site (Porto, Portugal), describing the effect of environmental and meteorological variables on O3 concentrations. ANN characteristics, and the threshold variable and value, were defined by genetic algorithms (GAs). The considered predictors were hourly average concentrations of NO, NO2, and O3, and meteorological variables (temperature, relative humidity, and wind speed) measured from January 2012 to December 2013. Seven simulations were performed and the achieved models considered wind speed (at 4.9 m·s−1), temperature (at 17.5 °C) and NO2 (at 26.6 μg·m−3) as the variables that determine the change of O3 behavior. All the achieved models presented a similar fitting performance: R2 = 0.71–0.72, RMSE = 14.5–14.7 μg·m−3, and the index of agreement of the second order of 0.91. The combined effect of these variables on O3 concentration was also analyzed. This statistical model was shown to be a powerful tool for interpreting O3 behavior, which is useful for defining policy strategies for human health protection concerning this air pollutant.

This paper presents a single hysteresis model for limited-availability group that are offered Erlang, Engset and Pascal traffic streams. The occupancy distribution in the system is approximated by a weighted sum of occupancy distributions in multi-threshold systems. Distribution weights are obtained on the basis of a specially constructed Markovian switching process. The results of the calculations of radio interfaces in which the single hysteresis mechanism has been implemented are compared with the results of the simulation experiments. The study demonstrates high accuracy of the proposed model.