GDP Growth Rate Research Articles

ECONOMIC SECURITY CHALLENGES TO PAKISTAN DURING POST PANDEMIC ERA

Pakistan’s economy has faced many challenges since the inception of Pakistan as an independent state. The economy of country was largely dependent on agrarian resources during the initial decades and then industrial bases afterwards. During the past three decades it the economy of Pakistan depends on loans and financial aids from international financial institutions such as, IMF along the industrial growth. The world economy slowed down after the pandemic and it also had consequences on Pakistan economy. Covid-19 caused major disruption in Pakistan economy. As, Before pandemic the GDP growth rate was 2.50% in 2019 and it fell in negative point -1.27% during the fiscal year 2020. The economic challenges to Pakistan raised during pandemic era such as its GDP growth rate decreased in negative points, its fiscal debt increased to 12.74% in 2020 as compare to 2019. Unemployment, shut down of small businesses, increase in job displacement, fiscal deficit, decline in foreign direct investment are the few challenges to name. Therefore, the economic security of Pakistan had faced many challenges during the post pandemic era. The drastic impact of covid-19 forced government to take immediate steps to counter economic challenges. The first national security policy of Pakistan in this regard made economic indicators as a challenge and made economic security a part of national policy.

Sacrificing sustainability for a higher GDP growth rate

Striving for positive GDP growth often comes at the expense of sustainability indicators, highlighting a crucial dilemma in modern economic development. This empirical study delves into the intricate relationship between sovereign sustainability indicators and GDP growth by using panel data that spans across 15 years for 100 countries and sheds light on the complexities of economic progress in the context of sustainability. Analysis reveals a negative bidirectional relationship between SDG scores and GDP growth rate, prompting further exploration into the determinants of these variables. Notably, GDP growth tends to rise following deteriorations in sustainability, while improvements in certain sustainability indicators, such as quality education and renewable energy consumption, correspond to enhanced GDP growth. However, the interplay between GDP growth factors and SDG scores unveils nuanced patterns, with both positive and negative associations observed across various determinants. These findings underscore the multifaceted nature of the relationship between sustainability and economic growth, challenging the notion that GDP growth alone signifies economic well-being. Considering these insights, policymakers are urged to adopt a holistic approach to sustainable development, integrating diverse econometric metrics, decoupling economic growth from environmental degradation, and bolstering data collection and analysis efforts. By embracing comprehensive strategies that prioritize sustainability alongside economic prosperity, policymakers can pave the way for inclusive and resilient development pathways.

Time management as the growth factor of small manufacturing enterprises

The article deals with small manufacturing enterprises as a point of an industry economic growth which potentially outpaces the average growth rate of the industry and the GDP growth rate that makes it possible to increase the share of gross production product in the general structure of small business of Russia. As one of the reserves of growth of such enterprises the author presents implementation of corporate time management technologies which allow the administration of the enterprises to increase the time for solving the tasks facilitating the economic growth: working with the major clients and contracts, searching for new financial sources, introduction of new capacities, development of new products, formation and development of new management teams. The author suggests the structure of a corporate time management standard which regulates the issues of managing meetings, calendars, operational tasks, work communications. The article contains description of the method of implementation of corporate time management at the example of a small manufacturing enterprise of the instrumentation industry.

Monetary and fiscal policy impacts under alternative trilemma regimes

Using a new set of trilemma indexes for exchange rate stability, financial market openness, and monetary policy independence, this paper first locates more than one hundred economies in the trilemma triangle over time. Second, the paper depicts individual economies’ trilemma regimes, defined by combinations of the three indexes, in the global map. Third, the paper tests econometrically the impact of monetary and fiscal policies on key macroeconomic variables (i.e., the real GDP growth rate gap, inflation, and their variability/volatility) under alternative trilemma regimes. Fourth, it examines the roles of trilemma regimes in influencing the macroeconomic variables. Econometric analysis uses a sample of 61 emerging market & developing economies over the period 1971–2020. The two-stage least squares estimation results largely support the Mundell-Fleming predictions made for three “corner” regimes. Monetary policy is effective in raising the real GDP growth rate gap and its variability under the “flexible exchange rate” corner regime, but not under the “financially open fixed rate” regime. Monetary policy is most effective in stimulating inflation and inflation volatility under the “flexible rate” regime. Fiscal policy has a positive impact on the GDP growth rate gap under the “flexible rate” regime and positive impacts on inflation and variability/volatility measures under the “financially closed fixed rate” regime, while it has no such impact under the “financially open fixed rate” regime, a somewhat surprising finding. The “financially open fixed rate” regime has a role of achieving price stability in a financially open economy.

THE DIGITAL ENTERPRISE LANDSCAP: HOW DESI METRICS SHAPE ECONOMIC GROWTH IN THE EU

The European Union’s (EU) economic growth is increasingly driven by digitalization across all areas, including the digital transformation of businesses. This paper explores how the digital transformation of enterprises could influence economic growth in the EU by analyzing data from the Digital Economy and Society Index (DESI) and economic metrics from Eurostat for the post-pandemic period (2021-2022). This paper uses econometric techniques like Panel Corrected Standard Errors (PCSEs) and Robust Regression with Huber Iteration (RRHI) to investigate the cause-and-effect relationships between digitalization and economic factors such as GDP growth rate and real GDP per capita growth. The results show that different digital strategies have varying effects on economic performance. The paper also emphasizes the critical role of real labor productivity in connecting digital transformation with economic performance. The implications of this paper highlight the need for nuanced policy strategies that foster digital skills, improve technological infrastructure and support the Small and Medium Enterprises (SMEs) in their digitalization efforts in order to achieve the ambitious objectives of the EUs Digital Decade. The results also propose a strategic focus on specific technologies that offer immediate economic advantages and enable a stronger incorporation of digital progress across various business operations in the member states.

Multi-factor fuzzy sets decision system forecasting consumer insolvency risk

The objective of this study is to develop a multi-factor decision system predicting insolvency risk for natural persons with the use of fuzzy sets. Considering that the financial situation of households is affected by various endogenous and exogenous factors, the main assumption of this study is that the system for predicting financial difficulties should not be limited to the use of only a few financial variables concerning consumers, but also include variables describing the environment. The author proposes a system consisting of three different forecasting models that connect the macroeconomic and microeconomic environments. It monitors the economic situation of households by also identifying those environmental variables, which may directly, or indirectly, endanger the consumer, such as unemployment rate (job market situation), inflation and interest rates, exchange rates, or economic situation in the country (GDP growth rate, the dynamics of retail sales, etc.). Moreover, the created cause-and-effect tool is in the form of a flexible application that can be easily adapted to changing economic conditions. Another unique feature of the study is the proposed use of newly developed ratios in household finance, similar to that in financial ratio analysis, which is commonly used in corporate finance. The proposed ratios demonstrated high predictive abilities. The paper also identifies the predictive capabilities of selected macroeconomic variables from the perspective of their impact on the risk of consumer insolvency. The research relies on four samples consisting of a total of 2400 consumers from Taiwan and Poland. The author created three forecasting models separately for the South-East Asian and Central European regions, and two multi-factor systems, each consisting of 1260 decision rules. The findings clearly showed that fuzzy logic is a significantly more effective method compared to traditional models based on classical logic.

Circular economy efficiency in the context of waste management in the selected Central and Eastern European countries – evidence from DEA and fractional regression analysis

Sustainability and optimizing waste management efficiency through circular economy principles have become significant trends in recent research. This study aims to compare the circular economy efficiency within the waste management framework in selected Central and East European countries. To achieve this, the research employs Data Envelopment Analysis (DEA) and Fractional Regression Analysis, specifically using the Slack-Based Measurement model. This model measures efficiency by referencing the inefficient Decision-Making Units (DMUs) rather than the origin of the coordinate system. Key variables such as GDP per capita, GDP growth rate, and circular economy indicators were selected and analyzed using Eurostat data from 2010 to 2022. The findings reveal varying potentials for improving the efficiency of hazardous and non-hazardous waste management in the countries investigated. Additionally, differences in the mutual influence of selected variable indicators on waste efficiency are identified using Fractional Regression Analysis. These insights emphasize the pivotal role of waste management in advancing circular economy policies.

Digital transition in a turbulent world: European regional growth opportunities in 17 years' time

ABSTRACT Recently, the digital transition has been highlighted as a strategy fostering economic competitiveness. How the advantages from the digital transition will distribute over time and space is still unclear. This paper builds scenarios comparing the effects of a digital transition. Technological assumptions are consistently related to the assumptions on other structural changes. The internal coherence among assumptions is guaranteed by a larger overarching framework based on how the geopolitical context will evolve. A deeper within-EU integration and global cooperation, or a fragmented Europe torn in a world polarized in two blocs, enhance the digital transition and the main structural changes in different ways. Qualitative assumptions, validated through a Delphi analysis, are translated into quantitative ones and included in our MAcroeconometric, Social, Sectoral, Territorial 5 (MASST5) model, a regional macro-econometric forecasting model, through which simulations of GDP growth rates at regional (NUTS2) level are simulated for the period 2021–2038. Results show that if the digital investment plans stimulate growth, they only partially reverse regional growth divergence trends caused by advantages stemming from an integrated market, even if distributed with the aim of closing the digital gap among European countries.

Do Foreign Buyer Taxes Affect House Prices?

This paper studies the impact of foreign buyer taxes on house prices using recent law changes in Canada, Australia, and New Zealand. Counterfactual house prices are estimated for each treated location, combining prediction techniques from machine learning with inference methods from the synthetic control method literature. In general, the foreign buyer taxes we studied had negative, large, and persistent effects on house price growth. We found bigger effects in locations with higher taxes and with larger immigrant shares. Alternative outcome variables, including population growth, GDP growth, and unemployment rates, were either unaffected or slightly affected in ways that do not confound our results.

The blue economy effects on EUROMED tourism: forecasting approach

This study examines the factors that influence the blue economy in EUROMED, aiming at promoting economic growth in line with the UN Sustainable Development Goals. EUROMED was chosen because all of its nations have fisheries and marine tourism, which are the two key indicators of the blue economy. Blue economy contributes to sustainable development in the fisheries and marine tourism sectors. A commitment to sustainability has sped up national and regional blue economy policy development. The study uses secondary qualitative data and literature review to analyse the synergies and conflicts between EUROMED blue economy strategies and the UN Sustainable Development Goals. The findings suggest that GDP growth, aqua production, open trade, CO2 emissions, and inflation rate influence the blue economy, and that ecotourism that considers education, society, and the environment may generate sustainable fisheries and marine tourism. Only 21 countries gave the ARDL test between 2000 and 2019. This study analyses synergies and conflicts between EUROMED blue economy strategies and UN Sustainable Development Goals. Location-based contextual development of blue economies that suit all players' requirements is essential to maintain sustainability objectives. Ensure resilience against future environmental and political shocks, preserve the ecological underpinning for vibrant blue economies, and create capacity at all levels to promote effective and fair governance. This study tries to make good use of ocean conservation and aquaculture within the context of the blue economy. This is the first EUROMED blue economy study and contributes to the theoretical and methodological development of blue economy research.

How Much Government Debt Is Now Acceptable for Russia?

The period of near-zero interest rates is over, and the recent noticeable growth in the debt burden, as well as in the cost of interest payments to service that debt, has made it more challenging for national and global financial regulators to strike a balance between keeping budgetary parameters stable and spurring economic development. This article proposes a “safe” threshold for the debt burden such that the ac-cumulated debt would not diminish prospects for growth and degrade fiscal sustainability. A significant negative linear effect of government debt on GDP growth rates from 1980 to 2021 has been observed for a total sample of 57 countries. According to the Hansen test, there are relatively safe thresholds for high- and middle-income countries at 56% and 24% of GDP, respectively. An assessment of the impact of government debt on the dynamics of interest expense indicates that there is a stable positive relationship between them. The conclusion drawn is that the thresholds beyond which an acceleration in the growth of interest payments would produce an increase in the debt burden stand at 51% and 29% of GDP, respectively, for the same groups of countries. However, the current conditions of unprecedented sanctions that restrict access to foreign borrowing together with a double-digit key interest rate were not taken into account for calculations based on the retrospective data. When those factors are included, the authors’ projections indicate that Russia’s safe level of debt should not exceed 20% of GDP.

Does ambition work? The effectiveness of local climate pledges in China

ABSTRACT This study employs a mixed research design to examine the effectiveness of local climate ambitions in China and identify the factors influencing their performance. The empirical results indicate that local governments’ ambitious climate pledges do not necessarily lead to better performance in low-carbon development compared to cities without such pledges. This conclusion is supported by various indices, including the low-carbon status index, the carbon emissions reduction trend index, the carbon peaking trend, and the decoupling degree of carbon emissions growth rate and GDP growth rate. By integrating the principal-agent theory, the study reveals that local governments often make climate pledges passively, driven by central government mandates rather than genuine ambition. This lack of true commitment is attributable to weak incentives and constraints, significant pressure to transition to low-carbon development, and the absence of robust monitoring and accounting systems.

Բյուջետային ծախսերի կառուցվածքի ազդեցությունը տնտեսական աճի վրա (ՀՀ օրինակով) / The impact of the public expenditures structure on economic growth: Case of Armenia

The public budget is an important lever for the state regulation of the economy: it reflects the main directions and priorities of the state economic policy. In this context, there is a lot of discussion about the dynamics of the public expenditure multiplier, as well as the interaction between the structure of these expenditures and economic growth. The study of the dynamics of the multiplier of budgetary expenditures of Armenia over the last 15 years shows that it was higher than 1, making an average of 4.5 points. As a result of the research, we evaluated the impact of Armenia's budgetary expenditures on economic growth using an econometric model, based on quarterly data from 2008-2023. The results of the research show that the increase in the productive expenditures of the state budget in Armenia, such as those spent on education, healthcare and the national economy, contribute to the GDP growth rate, while the allocation of public funds to non-productive expenditures, such as defense and social sector expenditures, has a negative impact on the GDP growth rate.

Predicting determinants of industrial firms’ loan payment default: Logit model versus probit model

Appropriate control and management of credit risk has become the main concern of financial institutions, which are constantly developing models for analyzing, assessing and predicting this risk, particularly in view of the prudential standards required by central banks. The current research paper aims to specify the determinants of payment defaults in Tunisian companies in the industrial sector so as to develop a model with the optimal predictive precision of forecasting payment default when it relates to industrial firms functioning in the Tunisian environment. Within this framework, we compared two generalized linear models which correspond to the logit and probit models based on a sample of Tunisian industrial companies. The results revealed that debt ratio is the most important variable that increases the probability of default payment, while the solvency ratio reduces the probability of default payment. This study highlights the vital contribution of macroeconomic agents, such as GDP growth rate and inflation rate, in terms of the prediction of default payment.

THE DYNAMICS OF EXCHANGE RATES, INFLATION, AND TRADE BALANCE IN A SMALL OPEN ECONOMY (CASE STUDY OF SIERRA LEONE)

Sierra Leone experiences a persistent trade deficit problem. Currently, there is a vacuum in the literature employing recent data and suitable approaches to address the issue of non-stationarity and dynamic interaction between macroeconomic variables in influencing the trade deficit in Sierra Leone. This study examines the relationship between Sierra Leone's trade balance, inflation, and exchange rate using quarterly data from 2005 Q1 to 2023 Q3. The focus is on understanding how the exchange rate and inflation impact Sierra Leone's trade balance in both the short and long term. To achieve this, the study utilizes the VAR/VECM model to depict the dynamic interaction between the trade balance, exchange rate, and inflation. It also employs Granger Causality analysis to determine the most appropriate ordering among the macroeconomic variables in the model and Impulse Response Function (IRF) analysis to test the hypotheses regarding the trade balance response to exchange rate shocks and inflation. The empirical results confirm the existence of cointegration, indicating a long-term balance between the trade balance, exchange rate, inflation, and other macroeconomic variables such as GDP growth and interest rate differentials. Moreover, the dynamic prediction analysis using the IRF method supports the J-curve hypothesis in Sierra Leone and suggests that inflation can reduce the performance of the trade balance. These findings highlight the need for Sierra Leone to implement a comprehensive strategy to adjust the exchange rate and curb inflation to improve the trade balance and enhance external economic stability.

Does Islamic Mutual Fund Bear Higher Risk than Conventional Mutual Funds? An Empirical Analysis from Bangladesh

This study aims to identify whether Islamic mutual funds bear higher risk exposure than conventional mutual funds due to implementing their shariah screening criteria to select assets on the portfolio. For this purpose, monthly closing price data of Islamic and conventional funds operated in Bangladesh are collected from January 2016 to August 2023. A total of 2320 observations of each risk measure (e.g., standard deviation, semi-standard deviation, semi-standard deviation, and beta) are computed using a 12-month rolling window method to compare risk exposure between Islamic and conventional funds using univariable and multivariate analysis. The univariate analysis is conducted by performing an independent samples t-test, which confirms that overall, Islamic funds bear lower risk exposure than conventional funds. In multivariate analysis, the Feasible Generalized Least Square (FGLS) method, a dynamic panel data analysis model, is applied where the effects of macroeconomic variables such as deposit rate, GDP growth rate, exports, imports, broad money, and remittances are controlled. The results of the multivariate analysis also confirm that Islamic mutual fund risk exposure is lower than that of conventional mutual funds. This study will be helpful for practitioners and institutional investors in decision-making.

Effect of Macroeconomic Factors on Mutual Funds Risk and Return: An Empirical Study from Bangladesh

This study aims to identify the influence of macroeconomic factors on the risk and return of mutual funds in Bangladesh. Monthly closing price data of 27 mutual funds from Bangladesh are collected from December 2015 to December 2022. Additionally, monthly data of 6 macroeconomic variables, i.e., deposit rate, export, import payments, remittance, broad money (M2) and GDP growth rate, are gathered for this study. This study utilized standard deviation and beta as risk measures, and the Sharpe and Treynor ratios are applied as risk-adjusted return (RAR) measures. All the risk and risk-adjusted return measures are computed using 12-months rolling window method. The random effect model of panel data analysis is applied to find the influence of macroeconomic variables on the risk and return of mutual funds. Overall findings indicate that macroeconomic factors significantly influence mutual fund risk exposure. On the other hand, risk-adjusted return (RAR) is also significantly influenced by the macroeconomic variables. This empirical evidence helps practitioners and institutional investors in their decision-making in the situation of market asymmetric. Keywords: Risk-Adjusted Return, Bangladesh, Mutual Fund, Standard Deviation, Beta, Sharpe Ratio, Treynor Ratio

Carbon Kuznets curve in China: Nighttime light analysis in prefecture-level cities

Analysing the relationship between economic growth and carbon emissions may help China to determine how to reduce carbon emissions. This study examined 221 Chinese prefecture-level cities using data from 2003 to 2018 to investigate the possible inverted U-shaped relationship between carbon emissions and economic growth, based on per capita nighttime light brightness. This revealed a significant inverted U-shaped relationship between per capita nighttime and carbon emissions with a per capita GDP of 139.8 thousand Yuan corresponding to the turning point. For China to achieve its carbon emissions peak before 2030, the per capita GDP growth rate would need to be at least 6.6 %. Therefore, for help prefecture-level cities to achieve peak carbon, they must strive towards high-quality economic growth and accelerate transformation of economic growth modes to improve low-carbon pilot policies, and such projects should be implemented in more cities. Efforts to achieve peak should be accelerated first in eastern cities and later in western cities.

Forecasting US GDP growth rates in a rich environment of macroeconomic data

Forecasting GDP growth rates is a formidable challenge, compounded by the inherent volatility, the complexity of the economic landscape, and the presence of a multitude of economic indicators at varying data frequencies. This study employs the MIDAS-LASSO model, which represents a penalized approach designed for mixed-frequency data, to forecast US GDP growth rates, while considering a vast array of macroeconomic indicators, including the Macroeconomic Attention Index (MAI) of Fisher et al. (2022). The empirical analysis demonstrates that both macroeconomic indicators and MAI exhibit considerable power for forecasting US GDP growth rates. The MIDAS-LASSO model outperforms its competitors in terms of forecasting efficacy, particularly in scenarios involving a plethora of predictors. Further analysis scrutinizes the model's efficacy across business cycles and during significant economic downturns, and the pathways through which macroeconomic risks influence US GDP growth rates. These insights offer valuable contributions to the field of economic forecasting and present novel avenues for policymakers and analysts.

Can the improvements in human capital quality mitigate the negative impact of ageing on growth? Evidence from selected EU countries

AbstractMost long‐term GDP projections in developed countries expect a substantial decline in GDP growth rates over time. The main factor behind it is demographic changes, especially the decreasing working‐age population. We argue that these projections do not consider improvements in the quality of the human capital, which may, at least to some extent, mitigate the effects of the negative demographic shock. We start with a simple observation—the skills of younger age cohorts are higher than of older cohorts. Assuming that the current level of skills will be obtained also by the generations which will enter the labour market in the future, the average level of skills among the working‐age population will increase. Trying to catch this effect, we use the Programme for the International Assessment of Adult Competencies standardised test results to create an aggregate human capital measure, the average skill level of the work force, for 18 European Union countries and project it until 2040. We show that on average at least one sixth of the negative impact of the shrinking of the working‐age population can be offset by the increase in the quality of human capital and that this number can increase to three quarters in a less conservative scenario.