Growth Modeling Framework Research Articles

Commodity price volatility, institutions and economic growth: An empirical investigation

AbstractThis article investigates the role of institutional quality in transmitting effects of commodity price volatility to economic growth. To do so, we collect data on 107 primary commodity exporting countries in both developing and developed ones over the period 1976–2015. Our empirical approach is based on Solow growth model framework (Solow, R. M. (1956). The Quarterly Journal of Economics, 70(1), 65) and consists of estimating a dynamic panel model using the two‐step system GMM estimator. Our results show evidence that commodity price booms are associated with good economic performances that are unfortunately wiped out by the negative effects of price volatility in developing commodity‐dependent countries (CDCs). The main channel through which this volatility affects economic growth turns out to be through factor productivity. Finally, we have formally established that the negative effect of price volatility in CDCs is mainly due to the poor quality of institutions in these countries. These results suggest that it is important for commodity‐exporting economies, especially developing CDCs, to work on building strong economic and political institutions to guard against the risk of commodity price volatility.

Measuring academic resilience of socioeconomically disadvantaged students in Taiwan 2011-2017: Two-part latent class growth modeling based on IRT scores

Academic resilience is a critical topic that has been around for decades and contains a variety of theoretical models and research approaches. In this current study, we adopted the developmental view of resilience. We combined the person-focused (classification and trajectory) and variable-focused (regression) methods to analyze the longitudinal data of 744 students from the TDCYP 2011-2017. We conducted item response theory (IRT) models and a latent class growth modeling framework. First, we measured each person’s latent trait level by IRT and simultaneously identified the classes by positive outcome (academic self-concept) and risk factors. Eventually, to explain the class membership and growth factors by adding covariates. The finding of this study as follows, (1) the four-class model was selected, and they are the competent group (17%), the resilient group (34%), the vulnerable group (31%), and the maladaptive group (18%). (2) The developmental hypothesis of academic resilience was not confirmed because the slope factors of academic self-concept and two groups of risk factors showed no significance. (3) Moreover, we found gender, mental health (illness), and teacher support play critical roles in this study, and they could explain the growth trends and even the membership classifying. The family support and poverty factors were lack of influence might due to the data properties. Importantly, this study can advise educators that it is worth further studying and practicing that school-based context on how to support a student, especially the socioeconomically disadvantaged. Keywords: Academic resilience, socioeconomically disadvantaged, latent class growth modeling, longitudinal IRT schools, Taiwan Database of Children and Youth in Poverty (TDCYP)

Feasibility of Carbon Dioxide Storage Resource Use within Climate Change Mitigation Scenarios for the United States.

To progress decarbonization in the United States, numerous techno-economic models that project CO2 storage deployment at annual injection rates of 0.3-1.7 Gt year-1 by 2050 have been built. However, these models do not consider many geological, technical, or socio-economic factors that could impede the growth of geological storage resource use, and there is uncertainty about the feasibility of the resulting projections. Here, we evaluate storage scenarios across four major modeling efforts. We apply a growth modeling framework using logistic curves to analyze the feasibility of growth trajectories under constraints imposed by the associated storage resource availability. We show that storage resources are abundant, and resources of the Gulf Coast alone would be sufficient to meet national demand were it not for transport limitations. On the contrary, deployment trajectories require sustained average annual (exponential) growth at rates of >10% nationally for two of the three reports and between 3% and 20% regionally across four storage hubs projected in both reports with regional resolution. These rates are high relative to historical rates of growth in analogous large scale energy infrastructure in the United States. Projections for California appear to be particularly infeasible. Future modeling efforts should be constrained to more realistic deployment trajectories, which could be done with simple constraints from the type of modeling framework presented here.

The impact of climate change on economic growth: Evidence from a panel of Asian countries

Asia is recognized as one of the most vulnerable regions. This research aims to identify climate change effects on economic growth. It proposes a new and comprehensive perspective to examine the climate-economy nexus in this region and provides an underpinning for assessing the pathway of the growing Asian economy under the SSP climate scenario (CMIP6). We apply a macroeconomic-climate modeling approach with a climate damage function. The damage function, which is based on the temperature anomaly, was examined under three classes of damage severity. The climate change effect has been examined by including the direct effect on the output as the level effect and two more channels, including capital depreciation and productivity growth reduction. The augmented Solow growth model framework that considers different types of capital, including physical, human, social, and environmental capital, was applied. The labor productivity or technology is assumed to depend on trade-related variables, including trade openness, financial development, and foreign aid inflows. Also, in order to test the constant returns to scale assumption, the CES production function, which is the flexible production technology, was used. The study relied on the country-year panel of GDP per capita and other macroeconomic variables such as labor force, capital formation, financial development index, trade openness, and foreign aid gleaned for 1994–2017 to estimate production functions using the GMM estimation method. The climate data on the annual mean temperature and projections of future temperature are based on ICMP6 by 2100 for Asian countries. Based on the CES estimation results, constant returns to scale or Cobb-Douglas production function was adopted. The estimation results show that physical and environmental capital account for the highest contribution to the output per worker. However, the contribution of trade-related variables was found to be insignificant. The projected pathway by 2100 establishes that climate change would significantly reduce Asian output per worker, especially if severe damage function is examined, and climate change stays on the SSP scenario-anticipated trajectory. The output elasticity with respect to temperature under the most severe scenario was obtained −22.80, corresponding to the output per worker reduction of 46.7 percent in 2100. Among the three channels of the climate effect, productivity growth reduction showed the most adverse effect on output. The lower flexibility of the production function that restricts the environmental replacement with other inputs, may lead to a more binding role under growing scarcity conditions. It was also found that labor and technology could contribute dampening the capital damage induced by higher temperatures. From the research results, the findings suggest measures aiming at providing flexible production technology, development of capital-embodied technologies, and lower dependence on environmental capital.

“Data, data, data” – post-Brexit data governance and its relation to the UK’s economic model

ABSTRACT This paper studies the UK’s post-Brexit turn toward softening data protection standards. It uses this case to develop a perspective on data governance that is rooted in the growth model framework. With this approach, it illustrates how incentives to ease data-based value creation can be tied to certain macroeconomic conditions. The studied data protection reform serves as a crucial event at which links between macroeconomic conditions and policy action promise to become particularly visible. As the analysis shows, the UK government’s policy discourse and actions reflect various facets of the country’s data economy that have special weight in the UK’s growth model: the importance of data markets and advertising, the role of tech and data in attracting foreign investments, and the general importance of tech and data-intense service industries. The case study therefore points to important analytical dimensions that are relevant more generally for the study of evolving growth regimes.

On a finite strain modeling of growth in budding yeast.

Cell's ability to proliferate constitutes one of the most defining features of life. The proliferation occurs through a succession of events; the cell cycle, whereby the cell grows and divides. In this paper, focus is made on the growth step and we deal specifically with Saccharomyces cerevisiae yeast that reproduces by budding. For this, we develop a theoretical model to predict the growth powered by the turgor pressure. This cell is herein considered as a thin-walled structure with almost axisymmetrical shape. Due to its soft nature, the large deformation range is a priori assumed through a finite growth modeling framework. The used kinematics is based on the multiplicative decomposition of the deformation gradient into an elastically reversible part and a growth part. Constitutive equations are proposed where use is made of hyperelasticity together with a local evolution equation, this latter to describe the way growth takes place. In particular, two essential parameters are involved: a stress-like threshold, and a characteristic time. The developed model is extended to a shell approach as well. In a finite element context, representative numerical simulations examining stress-dependent growth are given and a parametric study is conducted to show the sensitivity with respect to the above mentioned parameters. Finally, a suggestion for natural contractile ring modeling closes this study.

The Impact of Reform on the Economic Growth Trajectory of Sub-Saharan Africa

The research examines why sub-Saharan African (SSA) nations have seen unsatisfactory economic development by assessing the reform programmes implemented during the last three decades. Based on an enhanced neoclassical growth model framework generated from a dynamic panel for 12 African nations from 1995 to 2019 using data from the LSDCV dynamic panel. The findings revealed that insufficient changes, particularly in governance and the institutional environment, had been implemented. Stability in the macroeconomic environment, structural reform, and physical infrastructure are all necessary for an efficient reform process and development of the developing world's growth prospects. Reform implies that it is political, social, and economical simultaneously. Political and economic reform should be carried out in tandem.

From revolutions to institutions: the experience of Arab reform

PurposeThe purpose of this study is to outline the reasons for the 2011 Arab Spring and why the Arab states failed to achieve sustainability and inclusive growth over the past three decades.Design/methodology/approachThis study used the augmented growth model framework derived from a production function and a dynamic panel LSDCV estimation, which incorporates aggregated economic and political reform indicators generated by principal component analysis. The empirical analysis is a comparative assessment of the Arab region as a whole and the Gulf countries and emerging Arab countries. This study is based on several panel data models for the Arab region’s reform programmes from 1995 to 2018.FindingsThe absence of robust economic and institutional reforms was the main reason for the uprising. Structural reforms in Gulf countries have been insufficient and more difficult to address than macroeconomic stability. By contrast, Arab emerging economies have achieved strong progress in structural reform but with weak progress in economic stability. Critically, governance indicator reforms enhance growth, with different items of governance based on the type of each group of countries. The results of this study confirm that reform is simultaneously political, social and economical.Practical implicationsEconomic reform should not be seen in a vacuum or in isolation from the political and social choices that society makes. Looking forward, the Arab reform agenda must address critical governance issues that hinder the effectiveness of reform policies.Originality/valueTheoretically, this study reappraises governance’s role in economic growth using a unified mathematical model. Methodologically, this study analyses economic, social and political reform components in the Arab region using econometric analysis. Empirically, this study investigates regional socioeconomic reform programmes. Existing studies have failed to recognise the economic and institutional policy reform patterns in the Arab world.

Modelling of NHPP Based Software Reliability Growth Model from the Perspective of Testing Coverage, Error Propagation and Fault Withdrawal Efficiency

This paper presents a software reliability growth model framework modeled from a non-homogenous poisson process (NHPP). Invariably, software testing continues to be a paramount measure for validating the standard of software. Test coverage measures appraise and estimate the proportion and gradation of testing in software. Therefore, presenting a correct picture of the test coverage becomes a prime requisite to guarantee software reliability. As an enhancement over the existing models, the proposed model integrates testing coverage (TC), error propagation, and fault withdrawal efficiency while keeping the number of parameters restrained to make the framework more reliable for parameter estimation. A relative analysis to assess the efficacy of the proposed model and some existing models has been carried out on the failure data obtained from three real-world software applications using six comparison criteria. Finally, the weighted criteria rank method has been used to rank the models and assess their performance. In addition, sensitivity analysis has been carried out to demonstrate the effect of the parameters of the proposed model on the mean value function.

Does environmentally friendly energy consumption spur economic progress: empirical evidence from the Nordic countries?

Exploring energy use-growth nexus can proffer valuable clues to policymakers and stakeholders on both economic and environmental sustainability targets. Unlike extant studies, this study focuses on the effects of renewable energy consumption on the economic progress of the Nordic countries including Denmark, Sweden, Norway, Finland, and Iceland. The empirical analysis encompasses two distinctive renewable energy consumption indicators while accounting for influential factors like research and development (R&D) expenditures, and both human and physical capital components within the traditional growth model framework. The DCCE estimator was deployed for the empirical analysis covering the available sample data between 1995 and 2020. From the results, the estimated impact of renewable energy consumption on economic progress varies according to its measurement vis-à-vis the utilized indicator 1 (renewable as % of total energy use) and indicator 2 (distinctive renewable power sources and biofuels). In the case of the former indicator, the impacts were insignificant while a positive significant impact on growth was seen across all model evaluations using both the GDP and per capita income levels of the Nordic countries in the latter indicator. Furthermore, both R&D expenditures and human capital component are essential significant long-run drivers of both economic growth and income levels in the bloc while physical capital formation produced contrary evidence on economic progress in the bloc. As such, policy implications and recommendations to enhance economic progress were suggested in the main text for the Nordic countries in view of renewable energy development and the bloc's environmental sustainability drive. Notably, strategic policy implementation should be geared towards encouraging more R&D expenditures, especially in renewable energy developments to facilitate economic growth and income levels while further positioning the Nordic bloc on environmental sustainability path.

Remote Work and Gender Differences in Absenteeism and Presenteeism Behavior

This study aims to examine whether the transition from working in an office to working remotely, forced by the Covid-19 pandemic, impacts employee absenteeism and presenteeism over time. Based on conservation of resources theory, we hypothesize that changing from an office to a remote work setting leads to decreased absenteeism and increased presenteeism among employees. We further assume that these relationships differ between gender subgroups as women experience the boundaries between the work and life area as more permeable, take over more domestic responsibilities, and, thus, have fewer resources available to cope with work tasks. We investigated how absenteeism and presenteeism developed using a sample of 514 white-collar workers tracked over two years. In a discontinuity growth model framework, zero-inflated negative binomial regressions showed decreased absenteeism and increased presenteeism after the transition to remote work. Contrary to our assumptions, subgroup analyses revealed that women showed a stronger decrease in absenteeism than men and a similar level of presenteeism. We discuss our contributions and the implications for corporate leadership and occupational health management.

Does energy intensity matter in the nexus between energy consumption and economic growth regarding capital-energy substitution?

This article investigates how the non-linear connection between energy consumption and economic development is influenced by energy intensity level in the context of energy-capital substitution. We firstly analyze the substitutability/complementarity between energy and capital by estimating VES production function within the standard Solow growth model framework for 58 countries over the period of 1975-2017. The selected countries are classified into four groups according to their relative energy intensity levels and their accessibility to energy. The estimation findings reveal that energy and capital are complements in the final output for each country group. Hence, in this paper, as further analysis, the study examines whether or not energy consumption always fosters economic growth. We investigate the non-linear link between energy consumption and economic development by constructing a panel smooth transition regression (PSTR) model for each country group and looking at the impact of energy intensity in this relationship. The empirical results provide that for each country group, there is a threshold level for energy intensity. Regardless of whether a country is a net energy exporter or net energy importer, it needs to use energy efficiently and not exceed the ideal energy intensity level in both production and consumption to maintain long-term economic growth.

Credit, banking fragility, and economic performance

Abstract This article explores the role of banking fragility for the relationship between private credit and economic growth and bridges two literatures, one on the link between credit and economic growth and the other on the effects of banking fragility on credit dynamics. We consider two types of banking fragility on both the asset and liability sides: nonperforming loans and the ratio of bank capital to assets. Using a standard growth model framework and a dynamic generalized method of moment panel estimator on data for European Union countries, we find that banking fragility has a negative effect on economic growth. A consequence of considering banking fragility is that credit appears to have a positive effect on economic growth only when banking fragility is relatively low.

A comparison of methods for evaluating schools with respect to growth of students in subpopulations in three-level models

ABSTRACT Although there is recognition that there may be differential outcomes for groups of students within schools, examination of outcomes for subgroups presents challenges to researchers and policymakers. It complicates analytic procedures, particularly when the number of students per school in the subgroup is small. We explored five alternatives for applying a three-level multilevel growth modeling framework to examine school-level achievement for a select subgroup of students (students with disabilities) using a large longitudinal database tracking reading achievement. The alternatives vary in terms of use of subgroup only or all student data, use of student-level predictors, and method of linking student or school-level outcomes to school effectiveness indices. Correlations from .57 to .99 among alternatives suggest the choice of how to derive school-level outcomes for a subgroup has consequences for inferences about the school’s effectiveness with the subgroup. Researchers’ assumptions and data available should guide the selection of an approach.

Shaky Student Growth? A Comparison of Robust Bayesian Learning Progress Estimation Methods.

Monitoring the progress of student learning is an important part of teachers’ data-based decision making. One such tool that can equip teachers with information about students’ learning progress throughout the school year and thus facilitate monitoring and instructional decision making is learning progress assessments. In practical contexts and research, estimating learning progress has relied on approaches that seek to estimate progress either for each student separately or within overarching model frameworks, such as latent growth modeling. Two recently emerging lines of research for separately estimating student growth have examined robust estimation (to account for outliers) and Bayesian approaches (as opposed to commonly used frequentist methods). The aim of this work was to combine these approaches (i.e., robust Bayesian estimation) and extend these lines of research to the framework of linear latent growth models. In a sample of N = 4970 second-grade students who worked on the quop-L2 test battery (to assess reading comprehension) at eight measurement points, we compared three Bayesian linear latent growth models: (a) a Gaussian model, (b) a model based on Student’s t-distribution (i.e., a robust model), and (c) an asymmetric Laplace model (i.e., Bayesian quantile regression and an alternative robust model). Based on leave-one-out cross-validation and posterior predictive model checking, we found that both robust models outperformed the Gaussian model, and both robust models performed comparably well. While the Student’s t model performed statistically slightly better (yet not substantially so), the asymmetric Laplace model yielded somewhat more realistic posterior predictive samples and a higher degree of measurement precision (i.e., for those estimates that were either associated with the lowest or highest degree of measurement precision). The findings are discussed for the context of learning progress assessment.

Growth Modeling for Quantitative, Spatially Resolved Geographic Atrophy Lesion Kinetics.

PurposeTo demonstrate the applicability of a growth modeling framework for quantifying spatial variations in geographic atrophy (GA) lesion kinetics.MethodsThirty-eight eyes from 27 patients with GA secondary to age-related macular degeneration were imaged with a commercial swept source optical coherence tomography instrument at two visits separated by 1 year. Local GA growth rates were computed at 6-µm intervals along each lesion margin using a previously described growth model. Corresponding margin eccentricities, margin angles, and growth angles were also computed. The average GA growth rates conditioned on margin eccentricity, margin angle, growth angle, and fundus position were estimated via kernel regression.ResultsA total of 88,356 GA margin points were analyzed. The average GA growth rates exhibited a hill-shaped dependency on eccentricity, being highest in the 0.5 mm to 1.6 mm range and lower on either side of that range. Average growth rates were also found to be higher for growth trajectories oriented away from (smaller growth angle), rather than toward (larger growth angle), the foveal center. The dependency of average growth rate on margin angle was less pronounced, although lesion segments in the superior and nasal aspects tended to grow faster.ConclusionsOur proposed growth modeling framework seems to be well-suited for generating accurate, spatially resolved GA growth rate atlases and should be confirmed on larger datasets.Translational RelevanceOur proposed growth modeling framework may enable more accurate measurements of spatial variations in GA growth rates.

Estimating dynamic interactive linkages among urban agglomeration, economic performance, carbon emissions, and health expenditures across developmental disparities

This work analyzed the dynamic interactive causal links among urban agglomeration, economic performance, carbon emissions, and health expenditures across developmental disparities in China. To this end, this work developed a health expenditures-augmented growth model to introduce health expenditures and carbon emissions as a shift factor of total factor productivity. A block of simultaneous equations is developed based on the health expenditures-augmented growth modeling framework. The System-variant/Difference-variant Generalized Method of Moments is employed to estimate the block of simultaneous equations in order to deal with the potential endogeneity of the variables used. Based on empirical results, the core findings are as follows: first, a Pendroni cointegration-based long-run stable association is verified. Second, the urban agglomeration exhibited a bidirectional positive causal linkage with the gross domestic product (GDP) growth and health expenditures growth. Third, the health expenditures growth demonstrated a bidirectional positive causal linkage with carbon emissions growth and GDP growth. Fourth, a unidirectional mixed causal linkage—positive (negative) for linear form (squared form) of urban agglomeration—existed from urban agglomeration to carbon emissions growth. Fifth, there is a negative causal linkage operating from carbon emissions growth to GDP growth. However, there is mixed causal linkage—positive for a linear form of GDP growth, and negative for the squared form of GDP—operating from GDP growth to carbon emissions growth. These findings exhibited consistency in the type of causal linkages across the developmental disparities and hence showed robustness. Nevertheless, the findings showed disparities in the degree of impact across the developmental disparities. In this regard, the strength of causal linkage is the largest (moderate/lowest) for highly (moderately/least) developed regions of China. Based on empirical results, inferences are extracted and discussed.

Foreign Direct Investment and Total Factor Productivity: Any Nexus?

This study examines the impact of foreign direct investment (FDI) on the total factor productivity (TFP) of host countries. Extensions of the new growth theory provide a framework in which FDI increases the growth rate of a host country through technology transfer, diffusion and spillover effects. We construct four new series of TFP using the framework of neoclassical growth models. We also address the issue of endogeneity using the generalized method of moments. Our estimations using a balanced panel of 77 low- and middle-income countries suggest that FDI could not promote TFP in the countries studied. Our sensitivity analysis, in terms of alternative estimation methods, data, models and time period, reinforces the findings. We observe that the lack of absorptive capacity is likely to be an important reason for not having a direct relationship between FDI and TFP. JEL Classification: F21, F23, O33, F43, C33

Cultural Political Economy: An Alternative Approach to Understanding the Divergences between Italian and German Positions during the Euro Crisis

AbstractSo far, the Euro crisis has been analysed using the ‘varieties of capitalism’ concept, the growth model framework or ideational accounts. These approaches have generally been applied in isolation or in opposition to one another. There has been little cross‐fertilization, due to the different epistemological points of departure that emphasize either institutional rational efficiency, material driving forces or ideational motives for the political economies during the crisis. This article instead applies the concept of cultural political economy to today's socioeconomic tensions between northern and southern member states. Cultural political economy offers a historical evolutionary perspective showing how institutional, material and ideational motivations have co‐evolved in European member states since the 1950s, contributing to the discrepancies that we witness today between the northern and southern EU countries. The article exemplifies the cultural political economy approach against the background of the German–Italian irritations that have sparked through the crisis.

A heterogeneous single changepoint software reliability growth model framework

SummaryMany non‐homogeneous Poisson process software reliability growth models (SRGM) are characterized by a single continuous curve. However, failures are driven by factors such as the testing strategy and environment, integration testing and resource allocation, which can introduce one or more changepoint into the fault detection process. Some researchers have proposed non‐homogeneous Poisson process SRGM, but only consider a common failure distribution before and after changepoints. This paper proposes a heterogeneous single changepoint framework for SRGM, which can exhibit different failure distributions before and after the changepoint. Combinations of two simple and distinct curves including an exponential and S‐shaped curve are employed to illustrate the concept. Ten data sets are used to compare these heterogeneous models against their homogeneous counterparts. Experimental results indicate that heterogeneous changepoint models achieve better goodness‐of‐fit measures on 60% and 80% of the data sets with respect to the Akaike information criterion and predictive sum of squares measures.