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The principal aim of this paper is to review three basic theoretical growth models, namely the Harrod-Domar model, the Solow model and the Ramsey model, and examine their implications for economic policies.

The paper utilizes a positivist research framework that emphasizes the causal relationships between the variables in each of the three models. Mathematical methods are employed to formulate and examine the three models under study. Since the paper is theoretical, it does not use any empirical data although numerical illustrations are provided whenever they are appropriate.

The Harrod-Domar model explains why countries with high rates of saving may also enjoy high rate of economic growth. Both the Solow and Ramsey models can be used to explain the medium-income trap. The paper examines the impact of Covid shocks on the macroeconomy. While the growth rate can be recovered, it may not always possible to recover the output level.

For the Harrod-Domar model, the public spending decreases the private consumption at the period 1, but there is no change in the capital stock and hence the production in subsequent periods. For the Ramsey model with AK production function, both the private consumption and the outputs will be lowered. In both the Harrod-Domar and Ramsey models with Cobb-Douglas production function, if the debt is not high and the interest rate is sufficiently low, it is better to use public debt for production rather than for consumption. If the country borrows to recover the Total Factor Productivity after the Covid pandemic, both the Harrod-Domar and Ramsey models with Cobb-Douglas production function show that the rate of growth is higher for the year just after the pandemic but is the same as before the pandemic.

The economy can recover the growth rate after a Covid shock, but the recovery process will generally take many periods.

This paper focuses on economic implications and does not aim to examine social implications of policy changes or Covid-type shock.

The paper provides a comparison of three basic growth models with respect to public spending, public debts and repayments and Covid-type shocks.

EU countries, including those in Central and Eastern Europe, seem to have increasingly similar economies, allowing for the study of real convergence as a process of equalising income levels (measured by GDP per capita). Studies of income convergence in the European Union also have a regional dimension and often focus on convergence at the NUTS2 or NUTS3 regional level. The level of development and income in Polish regions differ significantly. The regional policy implemented at the national and EU level focuses on reducing these differences.

The main aim of the chapter is to analyse the income convergence process among regions in Poland and verify the effectiveness of regional policy implemented at the national and EU level.

The study uses Barro type regression for panel data, log t convergence test, and club clustering algorithm introduced by Phillips and Sul to identify patterns of club convergence in Polish regions. The data used for the study is the Local Data Bank provided by Statistics Poland, which includes gross domestic product per capita at the NUTS-3 level for 73 Polish regions over the period of 2000–2020.

The results of the study indicate a very weak convergence process for all Polish NUTS-3 regions and suggest a club convergence. The club convergence is characterised by regions with similar income levels clustering together. The regional distribution of clubs is similar to the regional distribution of income. The study's findings provide important insights into the effectiveness of regional policy in Poland and suggest that policymakers need to focus on policies that promote catch-up growth in less developed regions. The study also highlights the importance of supporting the most developed regions in the country as they can play a crucial role in driving the country's economic growth and prosperity.

This study aims to examine the antecedents of purchase intention toward energy efficient air conditioners by incorporating the theory of planned behavior (TPB) with two additional constructs, i.e. environmental concern and personal norms. TPB is one of the most widely used theoretical framework to study consumer behavior.

The study applied a quantitative technique using a survey method by distributing self-administered questionnaires among the Indian households who have purchased energy efficient air conditioners in the past six months or had enquired to do so. The study collected data from three select regions: Delhi and NCR, Punjab and Tri-city. The collected data of 424 respondents have been analyzed using confirmatory factor analysis and structural equation modeling.

The study posits that normative factors such as subjective norms and personal norms have a relatively higher influence on purchase intention. Despite the significant existence of environmental concern, the study did not find environmental concern directly influencing purchase intention.

The sample size of the study is too small and pertains to specific regions. Thus, it could hinder the generalizability of the results. Advertisement appeals should be related with enhancement of self-esteem in terms of making responsible and valuable contribution to environment protection through the purchase of energy efficient air conditioner.

There are a few studies in the Indian context studying consumer’s purchase intention toward energy efficient air conditioners to which this study adds. The study provides an important contribution to marketers in developing strategies for increasing purchase intention toward energy efficient air conditioners in view of their stage in the product life cycle, diffusion of product and influence of normative factors.

The purpose of this study is twofold. First, to estimate an optimal inflation rate for Ghana and second, to investigate factors that account for the differences between observed and target inflation.

The paper explored the questions within two econometric frameworks, the Autoregressive Distributed Lag (ARDL) and Threshold Regression Models using data spanning the period 1965–2019.

The study estimated a range of 5–7% optimal inflation for Ghana. While this confirms the single-digit inflation targeting by the Bank of Ghana, the range is lower than the central bank's band of 6–10%. The combined behaviours of the central bank, banks and external outlook influence inflation target misses.

The study urges the central bank to continue pursuing its single-digit inflation targeting. However, it implies that there is still room for the Bank to further lower the current inflation band to achieve an optimal outcome on growth and welfare. Again, the Bank should commit to increased transparency and accountability to enhance its credibility in attaining the targeted inflation.

The study is one of the first attempts in Africa in Ghana to estimate an optimal inflation target and investigate the underlying factors for deviation from the targets.

This chapter focuses on testing optimal capital structure theory: The role of intervening variable debt to equity ratio (DER) on the influence of the financial performance, Ownership Structure of Independent Board of Commissioners (IBCO), Audit Committee (ACO), and Institutional Ownership on Firm Value. The research design was explanatory research using path analysis. Using purposive sampling, 61 manufacturing companies, observation period from 2014 to 2018 with 286 N samples. The research novelty empirically can prove the role of intervening variable DER on the effect of return on assets (ROA) on firm value and shows the market response to the ROA is fully reflected by DER, indicating the existence of an optimal capital structure. The role of DER on the effect of ROE and IBCO on firm value is a partial mediation with the inverse direction. This phenomenon shows that the mechanism of forming a balance between the responses of investors and creditors relates to debt financing.

This chapter examines the influence of external public borrowing resources on economic progress in Tunisia. The study focuses on two stages: First, the influence is studied in a direct sense and then in an indirect sense, i.e., through a transmission channel of this influence. By applying the autoregressive distributed technique with staggered lags (ARDL), over a period ranging from 1986 to 2019, the results showed that the influence of external borrowing resources on growth seems to be unfavorable in the short term but positive in the long term, hence the importance of the empirical technique chosen. Second, three interaction variables were tested, namely total government expenditure, government investment expenditure, and the real effective exchange rate. The results obtained call for better attention to the channels identified to maximize the positive influence of external public debt on the country's economic progress.

This paper provides a structural model to value startup companies and determine the optimal level of research and development (R&D) spending by these companies.

This paper describes a new variant of float-the-money options, which can act as a financial instrument for financing R&D expenses for a specific time horizon or development stage, allowing the investor to share in the startup's value appreciation over that duration. Another innovation of this paper is that it develops a structural model for evaluating optimal level of R&D spending over a given time horizon. The paper deploys the Gompertz-Cox model for the R&D project outcomes, which facilitates investigation of how increased level of R&D input can enhance the company's value growth.

The author first introduces a time-varying drift term into standard Black-Scholes model to account for the varying growth rates of the startup at different stages, and the author interprets venture capital's investment in the startup as a “float-the-money” option. The author then incorporates the probabilities of startup failures at multiple stages into their financial valuation. The author gets a closed-form pricing formula for the contingent option of value appreciation. Finally, the author utilizes Cox proportional hazards model to analyze the optimal level of R&D input that maximizes the return on investment.

The integrated contingent claims model links the change in the financial valuation of startups with the incremental R&D spending. The Gompertz-Cox contingency model for R&D success rate is used to quantify the optimal level of R&D input. This model assumption may be simplistic, but nevertheless illustrative.

Once supplemented with actual transaction data, the model can serve as a reference benchmark valuation of new project deals and previously invested projects seeking exit.

The integrated structural model can potentially have much wider applications beyond valuation of startup companies. For instance, in valuing a company's risk management, the level of R&D spending in the model can be replaced by the company's budget for risk management. As another promising application, in evaluating a country's economic growth rate in the face of rising climate risks, the level of R&D spending in this paper can be replaced by a country's investment in addressing climate risks.

This paper is the first to develop an integrated valuation model for startups by combining the real-world R&D project contingencies with risk-neutral valuation of the potential payoffs.

The purpose of this study is to investigate the nonlinear effects of renewable energy (RE) consumption and economic growth on per capita CO₂ emissions during the time span from 1980 to 2020.

The study uses the logistic smooth transition autoregression (STAR) model to decipher the nonlinear relationship between RE consumption, economic growth and CO₂ emissions in the Indian economy.

The estimated results confirm a nonlinear relationship between India’s economic growth, RE consumption and CO₂ emissions. The authors found that economic growth positively impacts CO₂ emissions until it reaches a specific threshold of 1.81 (per capita growth). Beyond this point, further economic growth leads to a reduction in CO₂ emissions. Similarly, RE consumption positively affects CO₂ emissions until economic growth reaches the same threshold level, after which an increase in RE consumption negatively impacts CO₂ emissions.

The study suggests that India should optimize the balance between economic growth and RE consumption to mitigate CO₂ emissions. Policymakers should prioritize the adoption of RE during the early stages of economic growth. As economic growth reaches the specific threshold of 1.81 per capita, the economy should shift to more sustainable and energy-efficient practices to limit the effect of further CO₂ emissions on further economic growth.

To the best of the authors’ knowledge, this study represents the first-ever endeavor to reexamine the nonlinear relationship between RE consumption, economic growth and CO₂ emissions in India, using the STAR model.

Our paper studies a central issue with a long history in economics: the relationship between population and economic growth. We analyze the joint dynamics of economic and demographic growth in 111 countries during the period 1960–2019.

Using the concept of economic regime, the paper introduces the notion of distance between the dynamical paths of different countries. Then, a minimal spanning tree (MST) and a hierarchical tree (HT) are constructed to detect groups of countries sharing similar dynamic performance.

The methodology confirms the existence of three country clubs, each of which exhibits a different dynamic behavior pattern. The analysis also shows that the clusters clearly differ with respect to the evolution of other fundamental variables not previously considered [gross domestic product (GDP) per capita, human capital and life expectancy, among others].

Our results indirectly suggest the existence of dynamic interdependence in the trajectories of economic growth and population change between countries. It also provides evidence against single-model approaches to explain the interdependence between demographic change and economic growth.

We introduce a methodology that allows for a model-free topological and hierarchical description of the interplay between economic growth and population.

Today, the increasing use of fossil fuels, energy security, concerns and the great importance of achieving sustainable economic growth underscore the urgent need to transition to a green energy system as soon as possible. To shed light on the relationship between the economy and renewable energy, this study assesses the nonlinear relationship between renewable energy consumption and economic growth for 24 OECD countries between 1990 and 2015.

The authors apply two nonlinear models: panel threshold regression (PTR) and panel smooth transition regression (PSTR).

The results show that the positive effect of renewable energy consumption on economic growth is conditional. On the one hand, the results of the nonlinear PTR model yielded a threshold value for renewable energy consumption of about 251.17. Below this threshold, the authors find a negative impact of renewable energy consumption on economic growth. However, above this threshold, renewable energy consumption becomes a favorable source of economic growth. Using the nonlinear PSTR model based on the gamma transition parameter of 2.014, the transition from low renewable energy consumption regime to higher is abrupt.

Referring to previous studies analyzing linear causality between renewable energy and economic growth, most of the results show various mixed and non-stable effects over the study period. The contributions of this study consist in conduct a series of empirical tests of the nonlinear effects of renewable energy use on economic growth using two nonlinear approaches such as the PTR and PSTR models. If the authors show that such a relationship is nonlinear, it is essential to check whether the transition from one weak regime to another strong regime is abrupt or smooth, using the PSTR approach.