Gross Domestic Product Growth Research Articles

Assessing the economic impact of mobile telecommunications in Egypt: a structural model approach

PurposeThe purpose of this study is to use the structural model to determine the influence of mobile telecommunication on Egypt’s economic growth from 2000 to 2009. By focusing on mobile unique subscribers and mobile broadband-capable device penetration as indicators of telecommunications adoption, the authors seek to understand their overarching effects on the nation’s economic landscape.Design/methodology/approachThe paper uses quarterly time-series data set over the period 2000–2019 and uses a structural econometric model based on an aggregate production function, a demand function, a supply function and an infrastructure function to detect causality and examine long-run relationships between variables.FindingsThe findings of the structural model reveal that both mobile unique subscribers and mobile broadband-capable device penetration significantly contributed to Egypt’s gross domestic product (GDP) growth from 2000 to 2019. Specifically, a 1% increase in mobile unique subscriber penetration and mobile broadband-capable device adoption is estimated to result in an average annual contribution to GDP growth of 0.172% and 0.016%, respectively.Research limitations/implicationsThe scarcity of panel data is the main research limitation for comparative study with other Middle East and North African Region (MENA) countries. Research extensions would include testing the significance of complementarities such as improving governance measures and building human capacity for both households and firms, which are necessary to boost the impact of telecommunication on economic growth in the MENA region.Practical implicationsBased on these findings, the study puts forth policy recommendations aimed at maximizing investment in network utilization, including mobile and internet services, as well as fixed broadband subscriptions. It highlights the crucial role of these investments in promoting social and economic development, not only in Egypt but also across the MENA region as a whole.Social implicationsThe findings of this research emphasize the importance of strategic investments in network utilization, encompassing mobile, internet services and fixed broadband subscriptions. Such investments are pivotal for fostering social and financial inclusion. The study underscores the potential of these investments to drive social and economic progress, not just within Egypt but throughout the entire MENA region.Originality/valueOverall, existing literature generally supports the notion that the telecommunications sector has a positive economic impact. However, there is a gap in the literature when it comes to understanding the specific effects of the Egyptian telecommunications sector on the country’s economy, particularly in relation to the Egypt Vision 2030. The study aims to fill this gap by focusing specifically on Egypt and providing additional insights into the direct and indirect effects of the Egyptian telecommunications sector on the economy. By conducting a thorough analysis of the sector’s role, the authors aim to contribute to the existing literature by providing context-specific findings and recommendations.

THE EFFECT OF CREDIT TO THE PRIVATE SECTOR ON ECONOMIC GROWTH IN SIERRA LEONE

<p>Economic growth is important for poverty reduction, and it is of interest to all policymakers. Also, finance is important for boosting investment and hence growth and it takes various forms. The study therefore investigates the effect of bank credit to the private sector on economic growth in Sierra Leone. The study uses aggregate amount data on real Gross Domestic Product (GDP), credit by banks, and other control variables for the period 1992 to 2022. Variables are tested for the existence of unit roots and the Autoregressive Distributed Lag (ARDL) was used to test for cointegration and estimation of short-run and long-run models of growth. The results show that credit to the private sector has a positive effect on economic growth in Sierra Leone. Other results show that interest rates and inflation harm real GDP growth. The important policy implication is the need for the central bank to continue its financial stability efforts, the need for strengthened macroeconomic stability, and structural reforms that bind investment celebrate for more bank credit to the private sectors, in reducing to enhance growth.</p><p> </p><p><strong>JEL: </strong>O16, G21, E51, O55<strong></strong></p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0728/a.php" alt="Hit counter" /></p>

Savings and growth nexus in the context of Southern African Customs Union countries

Orientation: The primary goal of Southern African Customs Union (SACU) is to promote economic development through regional coordination. Consequently, SACU members have set economic growth targets through various medium- and long-term policies.Research purpose: The article investigates the savings-growth nexus among SACU countries.Motivation for the study: This study is motivated by low economic growth among SACU countries and the gap in the saving-growth literature. Specifically, previous studies assumed linear relationship, thereby ignoring the fact that savings may be related to economic growth in a nonlinear fashion.Research approach/design and method: The study utilised several panel estimation techniques with data over 1990–2021 for the SACU countries.Main findings: Firstly, there is a strong evidence of long run relationship between saving and economic growth in SACU countries. Secondly, domestic saving exhibits a positive and statistically significant effect on economic growth both in the short-and long-term. Thirdly, there is evidence of non-linear relationship between domestic saving and economic growth. Lastly, it is shown that 16% threshold level of domestic savings to gross domestic product (GDP) ratio is consistent with 6% GDP growth target aspired by SACU union.Practical/managerial implications: The findings of this article suggest that domestic saving is a prerequisite for economic growth provided the funds are channelled to productive investments. Consequently, there is a need to design appropriate policies that can help to promote and mobilise savings.Contribution/value-add: This article contributes to the ongoing debate on saving-growth in the context of developing countries. In addition, it addressed the linearity assumption of the previous studies by incorporating nonlinear assumption.

Money Supply, Inflation and Budget Deficit in Russia Compared to the United States

The author examines the causes and sources of the depreciation of money in Russia compared with that in the United States. The subject is causal connections between the budget deficit, money supply, and the depreciation of money. The relevance of the research for Russia is determined by concerns about macroeconomic stability and high inflation. In the case of the United States, an increase in the money supply and an inflation spike occurred because of the debt financing of the federal budget deficit. The scientific novelty of the paper lies in considering the two main options for monetary policy to support the liquidity of public debt: hard and soft, and the analytical methods and results of the research. One of the important scientific results is that the burden of public debt should be measured not as the ratio of public debt to gross domestic product (GDP) but as the share of public debt in a bond market. The second scientific result is very important for the practice: during 2011–2022, in the eight biennial periods, the GDP deflator was approximately equal to the growth of the money supply M2 minus GDP growth. Thus, the depreciation of money was directly caused by monetary policy. In the other three biennial periods, a substantial difference was observed, probably because of external shocks. As the method of the study, the author estimated the effect of interest rates caused by crowding out corporate debt by public debt. It was substantiated that to obtain the effects of soft monetary policy and thus the increase of M2 to GDP deflator, it is essential to use biennial periods. Based on the results of the analysis, it was revealed that, particularly in 2021–2022, the growth of the GDP deflator amounted to 139.8% and was due to the growth of the money supply M2 by 140.5%. At the same time, the effect on GDP growth was insignificant, at 3.4%. The key conclusion is that for the implementation of macroeconomic stability policies, it is necessary to manage the expansion of the M2 money supply, the exchange rate, and to use the GDP deflator as an important indicator in addition to the inflation index — consumer price index. A good way to achieve this is to adopt a special law for controlling inflation, similar to the USA Inflation Reduction Act.

Balance of Payments and Macroeconomic Performance in Nigeria

This study examined the effect of the balance of payments on macroeconomic performance in Nigeria between 1981 and 2021. The specific objectives are to determine the effects of current account balance, capital account, and external reserves on the gross domestic product (GDP) growth rate (the proxy of macroeconomic performance). This study employed secondary data sourced from the United Nations Conference on Trade and Development (UNCTAD), the Central Bank of Nigeria (CBN), and the database associated with Chinn and Ito. The study employed the augmented Dickey-Fuller method to examine the stationarity of the series and tested for cointegration among the variables using the bound test. The relationship between the balance of payments component and the gross domestic product growth rate was analysed using the autoregressive distributed lag (ARDL) method. The study confirmed the long-run relationship between components of the balance of payments and GDP growth. The ARDL shows that in the long run, current account balances had a positive and significant impact on GDP growth. The capital account proved not to be an effective policy for driving economic growth in the long run. It was found that external reserves had a positive and significant impact on GDP growth in the long run. Based on the findings, this study recommended a blend of export promotion policy and import substitution strategy to improve the balance of payments and create more opportunities for economic growth. Again, policymakers should focus on improving the financial depth and strengthening institutions, all of which support the liberalisation of the capital account and foster economic growth.

Understanding the Growth Implications of Debt Servicing in Nigeria

This study examined the effect of external debt servicing on economic growth in Nigeria. The specific objectives are to determine the effects of multilateral debt service, total debt service and external debt stocks on gross domestic product (GDP) growth. Time series data required for the investigation were sourced from the World Development Indicators and International Debt Statistics. The data analysis techniques include descriptive statistics, unit root tests, Johansen cointegration test and parsimonious error correction model (ECM) in addition to the post- estimation tests. The unit root results showed that all the variables are stationary at first difference. In other words, this finding revealed that the variables are integrated into order one [I(1)]. Evidence of two cointegrating equations was established from the Johansen cointegration test results, which implies that GDP growth has a long-run relationship with multilateral debt service, total debt service and external debt stocks. The parsimonious ECM showed that multilateral debt service has a negative and significant effect on GDP growth. This implies that an increase in multilateral debt service is detrimental to economic growth. The results further showed that total debt service and external debt stocks negatively and significantly impacted GDP growth. This finding indicates that Nigeria has not productively utilized the growing stocks of foreign loans to enhance its contributions to economic growth. The error correction parameter (-0.432) is negative and significant, which suggests that short-run disequilibrium can adjust to a long-run equilibrium position at a speed of 43.2 per cent. Based on the findings, this study concludes that debt servicing undermines the growth of the Nigerian economy. Thus, it is recommended that among others the government should gradually reduce its debt stock to reduce the total debt service obligations and make more resources available for economic grow

Forecasting GDP growth: The economic impact of COVID‐19 pandemic

AbstractThe primary goal of this study is to effectively measure the impact of a severe random shock, such as the COVID‐19 pandemic on aggregate economic activity in Greece, seven other euro area economies, three Scandinavian countries, and the United States. The class of linear and quantile predictive regression models is proposed for the analysis of real gross domestic product (GDP) growth, and a Bayesian approach for model selection is developed, by using a computationally flexible Markov chain Monte Carlo stochastic search algorithm that explores the posterior distribution of linear and quantile models, and identifies the relevant predictor variables. Penalized likelihood regression models are also implemented to tackle the issue of model selection. The model confidence set approach is applied and verifies that the selected models identified by the stochastic search algorithm belong to the set of superior models. Our analysis confirms that the outbreak of the pandemic had a profound effect on the economies under study, and reveals that different predictor variables are able to explain different quantiles of the underlying real GDP growth distribution for analyzed countries, suggesting that the quantile modeling approach improves the ability to adequately explain real GDP series compared with the standard conditional mean approach that explains only the average of the relationship between real GDP growth and several predictor variables.

Energy use and CO<sub>2</sub> emissions of the Moroccan transport sector

In this paper, optimized models based on two different machine learning (ML) methods were developed to forecast the transport energy consumption (TEC) and carbon dioxide (CO<sub>2</sub>) emissions in Morocco by 2030. More precisely, artificial neural networks (ANN) and support vector regression (SVR) were used for modelling non-linear TEC and CO<sub>2</sub> emissions data. This study uses data from 1990 to 2020 and employs various independent parameters, including population, gross domestic product, urbanization rate, evolution of the number of vehicles, and the number of electric vehicle introductions. Four statistical metrics are derived to assess the effectiveness of the ML algorithms used. The forecasts for 2030 were based on six scenarios, including three scenarios for the growth of gross domestic product (GDP) and two scenarios for the evolution of electric cars’ introduction into Moroccan vehicle fleet. The ANN model outputs showed that a decrease in TEC and CO<sub>2</sub> emissions is expected until 2030. However, the SVR model predicts outputs values close to those in 2020. The study's results also indicate that: i) TEC and transport CO<sub>2</sub> emissions are positively impacted by economic growth in Morocco and ii) electric vehicles will be essential components enabling substantial reductions in overall CO<sub>2</sub> emissions in future transport systems.

Public spending and economic growth: Evidence from the Western Balkans

The objective of this study is to examine the relationship between public expenditures, foreign investments, and the growth of the Gross Domestic Product (GDP) for the years 2002-2021 in the countries of the Western Balkans (BB6) and Croatia. The analysis includes data on $2.8 trillion of GDP, $668 billion of public expenditures, and $160 billion of FDI for these states. The methodology used in this study is based on a detailed examination of public expenditures and their impact on the Gross Domestic Product. This article investigates two hypotheses, thoroughly assessing their impact on GDP growth. Through the use of the Ordinary Least Squares (OLS) econometric model, concrete results with over 95% reliability have been obtained. The variables are determined based on multiple regressions for the findings we will obtain based on econometric calculations using the fixed effects, standard deviation, mean, and linear regression models. The findings of this study relate directly to the stated aims and objectives of the publication. The results presented in the study are an essential component of the study's conclusions. We found that some independent factors have a uniform impact on GDP growth, while others have a significant impact on real growth. Also, our findings confirm economic theories that argue that an increase in government spending leads to an increase in GDP. The data show that public investment in the Western Balkans has historically been overlooked, a gap in the literature that our research attempts to fill.

Predicting Gross Domestic Product (GDP) using a PC-LSTM-RNN model in urban profiling areas

Gross Domestic Product (GDP) is significant for measuring the strength of national and global economies in urban profiling areas. GDP is significant because it provides information on the size and performance of an economy. The real GDP growth rate is frequently used to indicate the economy’s health. This paper proposes a new model called Pearson Correlation-Long Short-Term Memory-Recurrent Neural Network (PC-LSTM-RNN) for predicting GDP in urban profiling areas. Pearson correlation is used to select the important features strongly correlated with the target feature. This study employs two separate datasets, denoted as Dataset A and Dataset B. Dataset A comprises 227 instances and 20 features, with 70% utilized for training and 30% for testing purposes. On the other hand, Dataset B consists of 61 instances and 4 features, encompassing historical GDP growth data for India from 1961 to 2021. To enhance GDP prediction performance, we implement a parameter transfer approach, fine-tuning the parameters learned from Dataset A on Dataset B. Moreover, in this study, a preprocessing stage that includes median imputation and data normalization is performed. Mean Square Error, Mean Absolute Error, Root Mean Square Error, Mean Absolute Percentage Error, Median Absolute Error, and determination coefficient (R2) evaluation metrics are utilized in this study to demonstrate the performance of the proposed model. The experimental results demonstrated that the proposed model gave better results than other regression models used in this study. Also, the results show that the proposed model achieved the highest results for R2, with 99.99%. This paper addresses a critical research gap in the domain of GDP prediction through artificial intelligence (AI) algorithms. While acknowledging the widespread application of such algorithms in forecasting GDP, the proposed model introduces distinctive advantages over existing approaches. Using PC-LSTM-RNN which achieves high R2 with minimum error rates.

Determinants of the personal savings rate in the Kingdom of Saudi Arabia using time savings deposits, 2012–2022

Personal saving is an important indicator of future economic prosperity. Despite the growth in gross domestic product per capita (GDPPC) from 2012 to 2022 in the Kingdom of Saudi Arabia (KSA), the personal savings rate remains low. Only a few studies have explored savings in KSA, but no study that used time savings deposits (TSD) to measure personal savings exists. Thus, this study aims to investigate the determinants of personal savings employing TSD. Using data from the Saudi Central Bank from 2012 to 2022, this study empirically examines the determinants of TSD. The autoregressive distributed lag cointegration technique determines the long-run relationship between the study's variables. The study finds that GDPPC, deposit interest rates (DIR), consumer loans (CLs), and real estate loans (RELs) significantly impact personal savings. Only GDPPC and RELs have a significant negative impact on personal savings. The study is among the few to examine savings in KSA but, unlike other studies, used TSD as a measure of personal savings. In conclusion, several implications and recommendations for policymakers and financial institutions were presented.

Whether the Chinese provinces have achieved their potential efficiency in economic growth?

PurposeMost economic growth is concentrated in the eastern and coastal provinces of China, while the western and central provinces have not yet experienced the expected economic growth. This study aims to address the following crucial research questions: Do the central and western provinces achieved potential efficiency in economic growth? Have China’s provinces used their resources effectively in implementing economic growth strategies?Design/methodology/approachThe research design concerns the use of a panel dataset on province-specific economic growth in China over the years to 2000–2020. The methodology used was a stochastic frontier gross domestic product (GDP) model with time-varying technical efficiency over time. The approach uses the existing literature to identify the important variables influencing economic growth at the provincial level to model the stochastic frontier GDP model for empirical analysis.FindingsThis study concludes that the central provinces show the highest rate of efficiency in economic growth, though not 100%, followed by the Eastern and Western provinces. By increasing and improving skilled education institutes and intensifying supply chain opportunities through foreign direct investment (FDI), the central provinces achieving 100% growth efficiency may not be ruled out.Research limitations/implicationsThe modes of economic governance and policies to improve GDP growth have been rapidly changing from increasing incentives to improving competition. Thus, more unique avenues and expansion of the horizon for impending research on provincial, national and international macroeconomics would emerge that would make current methodologies of the growth analysis outdated.Practical implicationsThe empirical analysis highlights the importance of improving skilled education institutes and intensifying supply chain opportunities through FDI for achieving sustained economic growth.Social implicationsThe empirical analysis facilitates finding ways to reduce income inequality across provinces in China.Originality/valueTo the authors' knowledge empirical analysis examining the Chinese province-specific economic growth efficiency explicitly has not been carried out using the recent Chinese panel dataset.

Control Chart for Correcting the ARIMA Time Series Model of GDP Growth Cases

The essential prerequisite for attending the G20 conference is a country's GDP because G20 members can significantly boost the economy and preserve the nation's financial stability. Time series data can be thought of as a country's Gross Domestic Product (GDP) at a particular point in time. In this research, the GDP numbers from five Southeast Asian nations that are attending the G20 fulfilling are used. The total was 47 observations made yearly, which extended from 1975 to 2001. A time series analysis was performed on the data gathered. The correctness of time series models is also evaluated using control charts based on this research. The control chart is constructed using the time series model's residuals as observations. After applying the IMR control chart for verification, the results revealed that the residuals, specifically the models for GDP in Malaysia, Singapore, and Thailand, are out of control. The white noise assumption is fulfilled by the time series model obtained for Brunei and Indonesia's GDP, but the residuals are out of control. Whether controlled residuals are used depends on the accuracy with which the time series model predicts the future. If the amount of residuals is under control, then the time series model produced is accurate and good enough for prediction. After using the IMR control chart to verify the residuals, the results indicate that the residuals, namely the models for GDP in Malaysia, Singapore, and Thailand, are not under control. The assumption of white noise is proved correct by the time series model obtained for the GDP of Brunei Darussalam and Indonesia. With that being said, the residuals are entirely out of control. The model must improve its ability to forecast various future periods. It is a consequence of the unmanageable residuals that the model contains. Even if the best available model has been obtained based on the criteria that have been defined, it is anticipated that the research findings will improve the theories that have previously been developed and raise knowledge regarding the usefulness of testing the time series model. In addition to all of that, it is intended that the research will produce a summary of cases of an increase in GDP from five Southeast Asian countries participating in the G20 conference.

Linkage vector autoregressive model

AbstractTo accommodate linkage effects of individuals, we develop a new linkage vector autoregressive (LAR) model for dynamic panel data. A main feature of the LAR model is incorporating dynamic network information in autoregressive time series modeling. The dynamic network can be given, or we can formulate the network links as a function of historical data, where unknown parameters of the function can be estimated from the data. We propose a simulation technique to check the stationarity condition of the LAR model and suggest a Bayesian Markov chain Monte Carlo method for estimation. Empirical results for the quarterly growth rates of gross domestic product (GDP) in 45 countries indicate that (i) the autoregressive (AR) coefficient for the aggregated growth rate is hard to distinguish from zero; (ii) a panel AR model with individual effects has a positive autocorrelation; and (iii) the alternative LAR models are preferred to the panel AR model. Depending on the specification of the linkage variables, the sign and size of the linkage effect can differ. The logistic linkage function has a flexible structure to accommodate the size of the linkage of individual GDP growth rates, and it strengthens the dynamics.

Exploring the Long-Term Relationship between Foreign Direct Investment and GDP: Empirical Insights from Bangladesh

The study's purpose is to examine the long-term correlation between Foreign Direct Investment (FDI) and Gross Domestic Product (GDP) in Bangladesh. The article is mostly based on secondary data collected from Bangladesh Bank’s website covering for the period 1980-2021. Data were processed with the assistance of the Statistical Package of Social Science (SPSS IBM 23 Version). Correlation and regression analyses were used to examine the data in the study. The results suggest that there is a high degree of positive correlation (0.976) between FDI and GDP, along with the implication that FDI has a significant positive impact on GDP in the long run within the Bangladesh economy. The results also suggest that if FDI changes by 1 unit, then the GDP will positively change by 0.92381 at the level of 5% significant statistically. This finding is reinforced by the regression analysis, which indicates a statistically significant relationship between FDI and GDP growth. So, it is understandable that there is a well-built impact of FDI on Gross Domestic Product (GDP) in the long-run in the Bangladeshi economy. These results are further supported by regression analysis, underscoring a statistically significant relationship between FDI and GDP growth. However, it is important to acknowledge certain limitations, such as data availability constraints and potential confounding variables not addressed in the analysis. Future research endeavors could address these limitations and explore additional factors influencing the FDI-GDP relationship in Bangladesh. Overall, the study highlights the substantial impact of FDI on Gross Domestic Product in the long run and discusses policy recommendations to attract FDI inflows to Bangladesh.

A novel modeling and prediction approach using Caputo derivative: An economical review via multi-deep assessment methodology

<p>In this study, we proposed a novel modeling and prediction method employing both fractional calculus and the multi-deep assessment methodology (M-DAM), utilizing multifactor analysis across the entire dataset from 2000 to 2019 for comprehensive data modeling and prediction. We evaluated and reported the performance of M-DAM by modeling various economic factors such as current account balance (% of gross domestic product (GDP)), exports of goods and services (% of GDP), GDP growth (annual %), gross domestic savings (% of GDP), gross fixed capital formation (% of GDP), imports of goods and services (% of GDP), inflation (consumer prices, annual %), overnight interbank rate, and unemployment (total). The dataset used in this study covered the years between 2000 and 2019. The Group of Eight (G-8) countries and Turkey were chosen as the experimental domain. Furthermore, to understand the validity of M-DAM, we compared the modeling performance with multiple linear regression (MLR) and the one-step prediction performance with a recurrent neural network, long short-term memory (LSTM), and MLR. The results showed that in 75.04% of the predictions, M-DAM predicted the factors with less than 10% error. For the order of predictability considering the years 2018 and 2019, Germany was the most predictable country; the second group consisted of Canada, France, the UK, and the USA; the third group included Italy and Japan; and the fourth group comprised Russia. The least predictable country was found to be Turkey. Comparison with LSTM and MLR showed that the three methods behave complementarily.</p>

Factors affecting net interest margin in the banking sector: Evidence from the Arab region

The net interest margin is an important measure for assessing the operational efficiency of the banking sector, and it also evaluates the performance of the bank’s management, as well as the success of its strategies in generating revenues through its core business (Obeid & Adeinat, 2017). In this paper, we examine the determinants of the net interest margin in the banking sector for selected Arab countries, including the cost-income ratio, the bank’s assets, the provisions, the main interest rate of the monetary policy, the real gross domestic product (GDP) growth rate, and the inflation rate, for a sample of 18 commercial banks in six Arab economies during the period 2015–2020. We use panel data models and the Hausman test to select the appropriate model. The results show that there is a significant positive effect of the bank size and the cost-to-income ratio on the net interest margin, while there is a negative impact of inflation, interest rates on monetary policy tools, and the coronavirus pandemic on the net interest margin. The results did not show a significant relationship between real GDP growth and loan provisions on the one hand, and the operational efficiency of the banking sector on the other hand.

ВАЛОВИЙ ВНУТРІШНІЙ ПРОДУКТ ЯК ІНДИКАТОР РІВНЯ ЕКОНОМІЧНОГО РОЗВИТКУ КРАЇНИ (НА ПРИКЛАДІ ЧЕСЬКОЇ РЕСПУБЛІКИ)

The article addresses the current issue of researching and analyzing Gross Domestic Product (GDP) as an indicator of national economic competitiveness on a global scale and its impact on the macroeconomic stability of the Czech Republic. The authors emphasize the importance of GDP analysis for effective economic management, planning, forecasting, and ensuring macroeconomic stability. The study is based on a review of previous research and publications by both Ukrainian and foreign scholars. As a result, the concept of Gross Domestic Product (GDP) is thoroughly analyzed, with three main aspects of the concept elucidated: "gross," "domestic," and "product." Furthermore, the article provides crucial explanations to enhance comprehension of the GDP concept. Moreover, the article extensively analyzes the dynamics of nominal and real Gross Domestic Product (GDP) of the Czech Republic from 2016 to 2022. Special attention is given to the impact of the COVID-19 pandemic on the Czech economy and its adverse effects in 2020. The causes of GDP decline are highlighted, along with data on economic recovery at the end of 2020 and an assessment of GDP dynamics in 2021 and 2022. The significance of evaluating GDP growth rates and their potential implications for the Czech economy are underscored, as well as the importance of GDP per capita as an indicator of Czech economic competitiveness and the country's position in the GDP per capita ranking. Additionally, the article examines the impact of declining household consumption on Czech GDP due to inflation and low investments. The methodology of correlation-regression analysis is employed to identify trends in GDP dynamics, along with projected GDP values for 2024 and 2025. It is noted that the main drivers of Czech economic growth should be the export activities of companies and the recovery of household demand. However, further research is needed to explore the analysis of GDP dynamics as an indicator of macroeconomic stability, its impact on forming global competitiveness rankings, and positioning the Czech Republic in the global economic community.

Balancing Progress and Preservation: The Complex Interplay of Economic Growth and Forest Conservation in Nepal’s Carbon Dioxide Emissions

The intricate relationship between economic growth, environmental quality, and energy consumption has been extensively debated and studied on a global scale. The impacts of ecological quality on economic growth have been observed to be both positive and negative, particularly about human health as a result of pollutant emissions. It is essential to examine the compatibility between economic growth and environmental improvement, particularly through the reduction of emissions. This study aimed to investigate the connection between economic growth in forested areas and the corresponding impact on carbon dioxide (CO2) emissions in Nepal (Rose and Fisher, 1970). The analysis utilized time series data from 1990 to 2020, employing the dynamic ordinary least squares (DOLS) method. The DOLS results demonstrated a positive and statistically significant relationship between economic growth and CO2 emissions (Shafik and Bandyopadhyay, 1992). Specifically, an increase of Rs. 10 million in gross domestic product (GDP) corresponded to a 0.6112 kiloton increase in CO2 emissions. In contrast, the long‐term coefficient for forested areas exhibited a substantial association, indicating that a reduction of one square kilometer of forested area (deforestation) resulted in an increase of 68.37 kilotons in CO2 emissions in Nepal. These findings accentuate the divergent effects of economic progress and deforestation on carbon emissions in Nepal, with GDP growth contributing to a greater increase in emissions. Therefore, the implementation of effective strategies and economic measures, such as afforestation and reforestation, forest protection, sustainable forest management, and mechanisms like REDD+ (reducing emissions from deforestation and forest degradation plus), can play a vital role in mitigating carbon emissions while simultaneously addressing deforestation and ensuring long‐term economic progress in Nepal.

Negative Impact of Income Tax on Economic Growth

In the intricate development of global trends, economic growth is a crucial part shaped by the factors all around from indicators like Gross Domestic Product (GDP), Gross National Income (GNI) to policies for taxation, exportation, social welfare and so on. Among them, taxation is an interesting topic discussed frequently by analysts and economists, which also contributed to wealth redistribution and inequality as important considerations. This article focuses on researching the impact of income tax on economic growth, including individual income tax and corporate income tax. The purpose of this research is to figure out whether cut in tax promotes economic growth in the United States. The results show that income tax rate indeed have a negative relationship with economic growth rate. The research’s data specifically shows how GDP shift up or down with the change of consumption, investment, employment rate, and so on. Cut in taxation somewhat promotes the GDP growth, while people are more willing to consume, invest, and governments are more abundant in funding. Finally, this research suggests the policy maker to consider the lagging effect of taxation policy on economic growth and timely adjustment of taxation structure progressivity, and further research and development.