Phillips-Perron Research Articles

Evaluating the Effectiveness of Macroeconomic Determinants on the Performance of the Dhaka Stock Exchange: A Time Series Approach

The present study examines the causal relationships between selected macroeconomic factors and the Dhaka Stock Exchange Broad Index (DSEX) performance from January 2014 to December 2023. Time series econometric techniques include Dickey-Fuller (ADF) and Phillips-Perron (PP) tests to verify stationarity, Granger causality to investigate short-term dynamics, and Johansen's co-integration test to evaluate long-term relationships. The results show that while there is no long-term cointegration, there are significant short-term relationships between macroeconomic variables and the DSEX broad index. GDP growth and unemployment significantly impact stock performance, with two-way causality. While interest rates and the money supply have little impact on the index, inflation forecasts trends in inflation even if it doesn't directly influence it. Overall, the DSEX broad index shows how important it is to Bangladesh's macroeconomic dynamics by accurately predicting changes in GDP growth, unemployment, and inflation. The researcher provides unique insights into the mechanics of the Bangladeshi stock market, filling a vacuum in the literature on emerging countries. It analyzes how macroeconomic conditions affect the DSEX index over time, including the COVID-19 pandemic. The study investigates the influence of several macroeconomic variables on DSEX Index performance, providing significant information for Bangladeshi investors and policymakers looking to increase profits, inform policy choices, and promote economic stability. To have a better knowledge of stock market dynamics, future studies should include other macroeconomic aspects and regional markets.

Macroeconomic Drivers of Inflation in Ethiopia: Evidence from ARDL Modelling

Purpose: This study identifies the macroeconomic determinants of inflation in Ethiopia from 2012 to 2023, a period marked by reforms and liberalization efforts. Despite these measures, inflation remains a critical challenge impacting Ethiopia's economic stability.Method: Utilizing the ARDL model, this study examines the relationship between inflation and various macroeconomic indicators. Data are drawn from sources such as the National Bank of Ethiopia (NBE), Ethiopian Economic Association (EEA), International Monetary Fund (IMF), and World Bank (WB). The Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests are employed to assess data stationarity.Findings: Results indicate that money supply growth, import-to-GDP ratio, budget deficit, and public expenditure have a significant positive effect on inflation in both the long and short term. Conversely, lending interest rates exhibit inflationary effects in the short term but are deflationary in the long term. Additionally, external debt-to-GDP ratio, official exchange rate, and real GDP growth rate demonstrate negative long-term impacts on inflation.Novelty: This research uniquely integrates key macroeconomic variables, analyzing their divergent impacts on inflation across short- and long-term frameworks in Ethiopia's context.Implications: The findings underscore the importance of balanced fiscal and monetary policies to curb inflation, offering critical insights for Ethiopian policymakers aiming to foster economic stability.

Bio-inspired MXene membranes for enhanced separation and anti-fouling in oil-in-water emulsions: SHAP explainability ML

Optimizing membrane performance for efficient water treatment is crucial for sustainable development and environmental protection, aligning with UN SDGs. This study involves experimental design, statistical reliability of small data, and explainable machine learning (ML) using SHAP (Shapley Additive Explanations). The research uses ML models and statistical tests to ensure data reliability and stationarity and investigate various membranes’ fouling and separation efficiency (MX-CM, PDMX-CM, and SPDMX-CM). Stationarity tests, including the Augmented Dickey–Fuller (ADF) and Phillips–Perron (PP) tests, revealed that MX-CM is stationary at level (I(0)), while PDMX-CM and SPDMX-CM required first differencing (I(1)) to achieve stationarity. SHAP analysis showed that in the fouling study, higher values of PDMX-CM and MX-CM positively influenced model predictions, with SHAP values of +0.09 for Cycle, −0.06 for PDMX-CM, and −0.06 for MX-CM. In the separation efficiency study, Cycle had a neutral impact (0.00), PDMX-CM had a slight positive effect, and MX-CM had a slight negative impact. These findings highlight the importance of ensuring data stationarity and utilizing SHAP for model explainability in predicting membrane performance. Accurate preprocessing and model interpretation enhance decision-making and optimization in membrane fouling and separation efficiency studies, ensuring robust and reliable ML models.

Impulse Response of External Debt Stock and Gross Capital Formation on Economic Growth in Bangladesh: Var Model, Granger Causality and Variance Decomposition Analysis

Purpose: This study employs an annual time series data set from 1987 to 2018 gathered from the World Development Indicators (WDI), 2021 to analyze the properties of external debt stock on financial progress(proxied by economic growth) in Bangladesh. Methodology: The objectives are determined using a variety of econometric techniques, including the Phillips-Perron (PP) unit root test, Var model, Johansen co integration test, Impulse Response Function (IRF), Variance decomposition function, and Granger causality test. The get the result of the Phillips-Perron (PP) unit root test which indicates the stationarity of all the variables at the initial difference. Findings: There is an expectant impact on financial progress (proxied by Gross Domestic Product Per capita) in Bangladesh, according to the short run Var model with the two independent variables External Debt Stock (proxied by public debt) and second lag of Gross Fixed Capital. Block Exogeneity/ Wald Tests and Johansen Co-integration test show that both lnEDS and lnGCF have a strong constructive impact on Bangladesh's financial progress in the short as well as long run. Pairwise, Granger Causality also indulgence the Bi-directional causality between lnGDPPC and lnEDS and Uni-directional causality from lnGCF to lnGDPPC. The influences of lnEDS and lnGCF on lnGDPPC are rising in the long term, showing that both variables are significantly exogenous on the dependent variable. Practical Implication: Bangladesh is now a fast-growing economy with several mega projects for infrastructural, human, and technological advancements such as roads, train, power, education, health, information technology, gas, and energy. External debt service and gross capital formation are crucial for Bangladeshi economic growth. The government should establish a priority aim for long-term economic growth by implementing suitable measures to control, maintain, regulate, and stabilize inflation at a reasonable level. Originality/Value: In a developing country, Savings within the country are insufficient to support investment for financial progress, according to the dual-gap theory and the Keynesian theory of public debt. As a result, bridging this gap for the required level of investment and achieving targeted economic growth will necessitate a bigger inflow of foreign aid or external borrowings. That’s why this study is very important. Limitations: Some limitations of this study include the absence of recent data with the factors. Also numerous factors can influence Bangladesh economic growth for instances, remittances, exchange rates and foreign direct investment all have a crucial impact on GDP growth.

Towards a Sustainable Future: Examining the Symmetric and Asymmetric Effect of Unstable Macroeconomic Factors on Initial Public Offerings Variability

The research seeks to explore the symmetric and asymmetric effects of renewable energy, technological innovation, and ecological footprint on the variability of initial public offerings in the unique institutional setting of the Pakistani IPO market. The study used yearly data on the Pakistani IPO market and the macroeconomic variables from January 1992 to December 2020. Further, the study employed the linear and Non-Linear ARDL to investigate the symmetric and asymmetric nexus among variables. For that purpose, the stationarity of the variables was predetermined using Augmented Dicker Fuller (ADF) and Phillips Perron (PP) unit root tests. Additionally, the F-bound test verifies that IPO issuance and macroeconomic drivers are co-integrated. The findings show a symmetric and asymmetric relationship between IPO variability and macroeconomic variables under study. Renewable energy and technological innovation have statistically positive effects on IPO variability. On the contrary, the ecological footprint has a significantly negative impact on IPO variability. The weak condition of the Pakistani IPO market could be attributed to the slow adoption of technological innovation, the transition to renewable energy, and a high ecological footprint that attracts stringent regulatory and environmental compliance costs of going public.

Empirical Analysis of Relationship Between Inflation and the Rate of Interest on GDP in Ethiopia

This study has examined the influence of real rates of interest and inflation on the economic development of Ethiopia. The study used analysis of time series data and chose to collect samples of 42 years, covering the period from 1981 to 2022. The research used data gathered from the World Bank's archive as well as the International Monetary Fund’s (IMF) Global Economic Outlook database. In addition, the research used an econometric analysis methodology by using the auto-regressive distributed lag (ARDL) model and its related Error Correction (ECM) Model to determine the long-run and short-run correlations between the variables. The study used the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests to determine the stationarity or non-stationarity of the time series data variables in the research, as well as their integration levels. The research used economic growth (GDP) as the dependent variable. The E-Views 12th edition software package facilitated the use of various time series data analysis methodologies and tests. The research has identified both short and long-term cointegration links among all the variables examined in this study. The findings revealed a statistically significant inverse correlation amongst real rates of interest and Ethiopia's growth in economy over time, seen in both the long term and the short term. In the long term, inflation has a clear and substantial impact on Ethiopia's economic development.

Spatiotemporal variability identification and analysis for non-stationary climatic trends for a tropical river basin of India

The non-stationary behavior of climatic variables has been increasingly recognized as a challenge that disrupts the equilibrium of human-defined climate-based stationary processes, including hydrological and agricultural practices, and irrigation systems. This study aims to investigate long-term trends and non-stationarity in climatic variables across 23 stations of the Krishna River basin, India. Prominent trends in rainfall, temperature, and their extreme indices were identified using the Modified Mann-Kendall (MMK), Bootstrapped Mann-Kendall (BMK), and Sen's Slope Estimator tests, while the Innovative Trend Analysis (ITA) test uncovered hidden trends and potential shifts in climatic patterns. This study addresses a critical research gap by exploring both significant and hidden trends in climatic variables, providing a better understanding of future dynamics. Traditional methods like MMK and Sen's Slope were insufficient to reveal these hidden trends, but ITA offered a more comprehensive analysis. The findings revealed an increase in total annual rainfall for almost 50% of the basin, which aligns with rising maximum temperatures, suggesting enhanced evaporation rates and subsequent fluctuations in rainfall patterns. Seasonal analysis indicated a shift towards decreased rainfall during winter and pre-monsoon seasons, contrasted by increased precipitation during the monsoon and post-monsoon periods, highlighting a clear alteration in rainfall distribution. The Simple Daily Intensity Index (SDII) and other indices suggest intensified rainfall events despite a decrease in the number of rainy days, indicating fewer but more intense events. Temperature analysis showed an overall increase in maximum temperatures, with the Diurnal Temperature Range (DTR) significantly increasing across all stations, implying greater daily temperature variations and potential for intensified water cycles and extreme climatic events. Furthermore, the study simplifies these trends by classifying them into two attributes: intensity and frequency, aiding policymakers in site-specific management of water resources and planning for future climatic scenarios. The presence of non-stationarity in extreme rainfall was confirmed by the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests. These findings are significant as they conclude how climate change is altering hydrological patterns at each station. The study emphasizes the necessity for adaptive management strategies to mitigate the adverse impacts on agriculture, infrastructure, and human safety.

Indirect Tax Reform And Market Efficiency: An Empirical Study of Indian Stock Market

The biggest tax reform of the Indian Government in this present decade is the Goods and Services Tax (GST), which was passed in parliament on 8th September 2016 and was enforced from 1st July 2017. Eight years of data from the Bombay Stock Exchange Sensex and the National Stock Exchange Nifty50 index is studied. The data is divided into two sub-periods before GST was passed from parliament period - I and after GST was passed from the parliament of India period - II. The study intends to test the market efficiency in its weak form. To check the time series data for normality, stationarity, random walk, and autocorrelation function, Kolmogorov-Smirnov (KS) test, Augmented Dickey-Fuller (ADF) test, Phillips Perron (PP) test is used for the analyse of the time-series data. The study found that returns are not normally distributed and the market is inefficient in a weak form for both periods under study.

The Impact of Economic Growth on the Ecological Environment and Renewable Energy Production: Evidence from Azerbaijan and Hungary

This article reflects on the necessity of employing renewable energy sources in the modern era to mitigate the negative environmental impact caused by traditional energy sources and address environmental pollution. Through research conducted in Azerbaijan and Hungary, it analyses the influence of economic growth on the ecological environment and renewable energy production. Due to limitations in the general dataset, the study considers the period of 1997–2022 for CO2 emissions causing environmental pollution, 2007–2022 for renewable energy production in Azerbaijan, and 2000–2021 for the same in Hungary. Information regarding wind and solar energy in Azerbaijan has been available since 2013. Temporal sequences have been utilised in the research, employing Augmented Dickey–Fuller and Phillips–Perron (PP) unit root tests to examine the stationarity of the time series. An Autoregressive Distributed Lag (ARDL) model has been constructed, and the credibility of the model has been verified using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegrating Regression (CCR) models. The findings reveal that in Azerbaijan, the long-term impact of economic growth on hydro-energy has been negative, while dependence on biomass and waste has been insignificant but positive. The influence on wind and solar energy production has also been negative and insignificant, akin to hydro-energy production. However, energy supply from renewable sources has been positively affected by the aggregate indicator of economic growth, albeit insignificantly. The impact of economic growth on carbon dioxide has been significant in two magnitudes, whereas in other cases, it has been insignificant but positive. In Hungary, economic growth has positively affected renewable energy production. However, the impact on carbon dioxide has been negative, meaning that this indicator has decreased as economic growth has increased. The study concludes that the impact of economic growth on indicators of both countries has been more effective in Hungary, which can be attributed to economic development.

Environmental Degradation and its Effects on Health in Bangladesh

This study aims to analyze the impact of environmental degradation on health using the Autoregressive Distributed Lag (ARDL) method with data from 1976 to 2020. The primary focus is on the influence of CO2 emissions on life expectancy in Bangladesh, evaluating the short-term and long-term relationships among key variables such as CO2 emissions, urban population growth (UPG), money supply (M2), and renewable energy consumption (REC). The study employs unit root tests, including the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests, to determine the stationarity of the time-series data. Results indicate mixed integration orders, necessitating the use of the ARDL bounds testing approach to confirm cointegration. The findings reveal that CO2 emissions have a significant negative effect on life expectancy, while M2 and REC exhibit varying impacts. The ARDL model confirms a long-term relationship between the variables, with a significant speed of adjustment towards equilibrium. Diagnostic tests validate the model’s robustness, ensuring no issues with heteroskedasticity, autocorrelation, or model misspecification. The study underscores the importance of effective governance in mitigating the adverse effects of environmental degradation on health, advocating for stricter environmental regulations and improved public health policies. These findings have significant implications for policymakers aiming to enhance public health outcomes amidst growing environmental challenges..

Tehran Stock Market efficiency: A quantile autoregression approach

The purpose of this paper is to evaluate the price efficiency of the Tehran Stock Market. For this aim, we used daily stock prices of 30 large companies on the Stock Exchange. In the first stage, a unit root test with the endogenous break and without a structural break was performed using augmented dickey-fuller test (ADF) tests and Phillips-perron (PP) tests. The results indicate that the price of 9 companies has a random walk process with intercept and 21 companies follow a random walk without intercept and trend component process which is known as the pure random walk process. Thus, considering the ADF and PP tests, most companies’ stock prices are efficient. Quantile autoregression results in the second stage show that the stock prices in the middle price deciles have weak efficiency, but in the lower and upper price deciles, the stock price does not follow the weak efficiency conditions. So, if the stock price deviates (up or down) from the long-term mean, the market becomes inefficient, but when the stock price is at the median level, the market is efficient. The general conclusion is that median prices are the long-term average prices that change over time, and stock prices tend to move toward that price.

Revisiting the environmental Kuznets curve hypothesis in the context of renewable and non-renewable energy in China

This research paper attempts to determine the effect of fossil fuel, renewable energy, and economic growth on carbon dioxide emissions and revisits China's Environmental Kuznets curve (EKC) hypothesis. The time series analysis will be performed for the years 1990 to 2020. To begin, Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) tests will be performed to verify the series' stationarity. Second, the cointegration test will be utilized to determine the validity of a cointegration vector before performing the Fully Modified Least Square approach to conduct long- and short-term estimation. The empirical analysis illustrates that renewable energy negatively and significantly affects short- and long-run carbon dioxide emissions. However, fossil fuel consumption only positively and significantly affects carbon dioxide emissions in the short run. The empirical evidence supports the Environment Kuznets Curve's hypothesis in China. Fossil fuel consumption has a considerably higher effect on carbon dioxide emissions than renewable energy. To avoid ecological damage in China, authorities must pay more consideration to encouraging the use of energy from renewable sources. This demonstrates that China's overall environmental performance first deteriorates before gradually improving with economic growth.

An Assessment of Purchasing Power Parity in the Long-Run: Evidence from India and its four Major Trading Partners

The present study focuses on evaluating the validity of the Relative Purchasing Power Parity (RPPP) theory for India and its four major trading partner nations namely the United States, China, the United Arab Emirates, and Saudi Arabia using monthly time series spanning January 2001 to March 2021. For the purpose of empirical analysis, standard Augmented Dickey Fuller (ADF) and Phillips-Perron (PP) unit root tests, as well as the Johansen-Juselius cointegration technique, have been applied. Firstly, the stationarity of the real exchange rate has been investigated using standard unit root tests. The findings indicate that each country’s real exchange rate is nonstationary signifying the absence of strong PPP. Thereafter, the weak form of PPP was tested in the second stage using the Johansen cointegration test. The findings of the cointegration test confirm the presence of a long-run relationship among bilateral exchange rates, domestic price levels, and foreign price levels for all countries undertaken except for the UAE. Since three economies from among the total four trading partners’ country-pair support the existence of PPP, it can be said that PPP holds for the Indian rupee exchange rate for the economies so considered. The study further signals that India’s trade with the UAE could lead to arbitrage opportunities.

THE RELATIONSHIP BETWEEN BIST BANK INDEX AND INFLATION, EXCHANGE RATE, INTEREST RATE, GOLD AND OIL PRICES: EVIDENCE FROM THE ARDL BOUND TEST

The aim of this study is to investigate the effects of inflation, exchange rate, interest rates, gold and oil prices on the BIST bank index between January 2005 - October 2023. For this purpose, firstly, the stationarity levels of the data were tested by the Augmented Dickey-Fuller (ADF) and Phillips- Perron (PP) tests. Then, since the series became stationary at different levels, ARDL bounds test, one of the cointegration tests, was applied. In the study, it is concluded that the BIST bank index and its independent variables are cointegrated in the long-run in the relevant period. According to the short-term asymmetric relationship results, a 1% increase in gold prices by 0.036%, a 1% increase in interest rates by 0.33%, and a 1% increase in the dollar exchange rate by 1.03% decreased the BIST Bank index. On the other hand, a 1% increase in CPI has a positive effect on the BIST Bank Index. No statistical relationship was found between oil prices and BIST Bank Index.

Empirical Approach to Modelling and Forecasting Inflation using ARIMA Model: Evidence from Tanzania

This study investigates the dynamics of the inflation rate (INFL) in Tanzania spanning from 1990 to 2021 using advanced time series analysis techniques. The dataset sourced from the World Bank online database serves as the basis for analytical exploration. Initially, the Autoregressive Integrated Moving Average (ARIMA) model is applied to understand underlying patterns in the INFL data. Transitioning to Seasonal ARIMA (SARIMA) modeling encounters challenges due to the absence of pronounced seasonality or clear trends. Unit root tests, including the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests, assess the stationarity of the data. Following the identification of non-stationarity, differencing is employed to achieve stationarity. Estimation of ARIMA models (ARIMA (1,1,1) and ARIMA (2,1,1)) is conducted, with diagnostic checks confirming the suitability of the ARIMA (1,1,1) model. The study contributes to the understanding of inflation dynamics and facilitates evidence-based economic policymaking in Tanzania.

Financial Development and Income Inequality in Nigeria: Testing the Financial Kuznets Curve Hypothesis

This study aims to investigate the link between financial development and income inequality in Nigeria, considering the potential existence of a financial Kuznets curve in Nigeria from 1986 to 2022. The study uses datasets from the World Bank and International Monetary Fund Database. It employs the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), Zivot-Andrews (ZA), ARDL bounds testing approach, and the Toda-Yamamoto causality test to determine the direction of causality between the two variables. The study finds evidence of an inverted U-shaped relationship between financial development and income inequality, potentially supporting the Financial Kuznets curve hypothesis in Nigeria. Additionally, the results of the Toda-Yamamoto causality test show a unidirectional causality running from financial development to income inequality. The findings have significant implications for economic development and social stability in Nigeria, emphasizing the need for targeted policies to mitigate the potential adverse effects of financial development on income inequality. This study fills a gap in existing research by examining the financial Kuznets curve in Nigeria and accounting for structural breaks, thus contributing valuable insights to the ongoing debate on finance and inequality.

Economic Environment and Entrepreneurial Development in North Central, Nigeria

This work sought to determine the impact of Economic Environment (EE) and Entrepreneurial development in North central, Nigeria. The unprecedented factors arising from inconsistencies, to lack of continuity of policies and programmes implementation constitute a lot of constraints that impede on the establishment, growth and development of Small and Medium Enterprises (SMEs) in the North central, Nigeria. The specific objectives of the study were to: (i) Ascertain the extent to which unemployment rate effects start-up business and entrepreneurial development in North central, Nigeria. (ii) Evaluate the extent to which total tax rate effects the growth of business enterprises in North central, Nigeria. (iii) Assess the extent to which domestic interest rate by banks to private sector impact on entrepreneurship development in North central, Nigeria. The study adopted survey research design, and ex-post facto, the population of the study was 18,173 staff made of owner-founder and management staff, from 2,178 private enterprises that registered with the respective state ministries of trade, commerce, industry and tourism in North central, Nigeria. A sample size of 377 was drawn from the population using Krejcie and Morgan (1970), sample size determination. The instrument used for data collection was mixed method: Quantitative method (structured questionnaire) and Ex-post facto (secondary data). The hypothesis were tested using Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) to ascertain the time series properties of the variable for hypothesis one. Hypotheses two and three were tested using simple linear regression. The findings revealed that, to a large extent the listed Economic factors had significant negative relationship with entrepreneurial development in North central, Nigeria. Based on the findings of the study it was recommended that, there should be strategic policy by government and individual put in place to ensure substantive numbers of work force engaged in both private and public sectors; government should encouraged entrepreneurial development by enforcing on financial institutions to issue one-digit interest rate loan to entrepreneurs and business concern to boost business activities in the region. More so the issue of double taxation on entrepreneurial activities should be minimized or avoided to provide a level plane ground for business enterprises to strive, grow and develop in North central, Nigeria.

Exploring the Nexus between CO2 Emissions, Trade, and Sustainable Economic Growth: A Novel NARDL Approach

This study investigates the nexus between CO2 emission, trade, Gross domestic product (GDP), and tourism in Pakistan during 1990-2019. We examined the asymmetric relationship between CO2 emission, international trade, Gross domestic product (GDP), and international tourism number of arrivals in Pakistan. Data Stationarity has been tested using the Augmented Dicky Fuller (ADF), Kwiatkowski-Phillips-Schmidt-Shin (KPSS), and Phillips-Perron (PP) tests for unit roots. We used the NARDL technique. Then a Granger Causality helped estimate the relationship between these environmental variables. If there is an asymmetric association between these variables, we estimate the non-linear auto-regressive distributed lag, which is the most applicable econometric estimate. The ARDL technique can potentially explore the dynamic nexus between CO2 emission, tourism, GDP, and trade. Our findings suggest a dynamic relationship between tourism, trade, CO2 emission, and GDP from Pakistan's perspective. The outcomes reveal that negative and positive shocks to trade, GDP, and tourism affect CO2 emissions in the short and long term. The Granger Causality findings also determined that causality is directed from Tourism toward CO2 emission, while unidirectional causality was found between CO2 emission and tourism. In this study, the graphs of the CUSUM and CUSUMQ determined the functional stability of the established relationship. This indicates that this model is a suitable and valuable strategy tool. Therefore, an increase or decrease in the macroeconomic series will cause variation in carbon emissions in Pakistan in the long -term. The finding benefits macro-level policymakers and will provide important insight for the relevant stakeholders.

Investigation of Causal Linkages Between Financial Development and Economic Growth: Evidence from Pakistan

Financial development is a driving factor for economic growth and is important in fostering growth. An efficient and effective financial system contributes to economic growth and fosters the performance of other economic measures. This study aims to investigate the influence of financial innovation on economic expansion to understand the correspondence between financial development and economic growth in Pakistan. Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) are used for stationarity. Auto Regressive Distributed Lag (ARDL) and Error Correction Model are employed to analyze the correlation between economic growth and financial development. The finding shows that financial development stimulates economic growth. The research explains that foreign direct investment and personal remittances adversely affect GDP growth. These understandings recommend that although financial development generally promotes, its results can vary extensively and depend on specific context-dependent conditions. Furthermore, applying CUSUM AND CUSUM of square tests to measure model stability convincingly confirms a long-term relation between financial development and economic expansion, disproving the null hypothesis of no co-integration and reinforcing that financial development is essential to domestic economies. Policymakers need to practice these understandings in actionable plans by highlighting financial innovations that advance access to credit and efficiently allocate resources so investment in education and agriculture can maximize economic growth.

The Intricate Impression of Tourism, Patent, And Renewable Energy on Environmental Sustainability

The growing global attention to indicating climate conversion and plummeting carbon dioxide (CO2) emanations has spurred researchers to examine the influence of several factors on promoting environmental sustainability. This research examines the intricate role of tourism, patent applications, rent from natural resources, and utilization of renewable power in carbon dioxide secretions in Bangladesh. For this purpose, data has been collected from 1995 to 2019 from World Development Indicators (WDI). Augmented Dickey-Fuller (ADF) and the Phillips-Perron (PP) and the ARDL bound cointegration procedures are employed to determine the existence of stationary data and cointegration among variables respectively. The Autoregressive Distributive Lag (ARDL) procedure is used to consider the effects of the chosen variables on CO2 emissions over the short and long run. VIF test, White's test, and the Breusch-Godfrey test are employed to check multicolinearity, homoscedasticity, and autocorrelation respectively. The research discloses that it is vital to expand the usage of renewable energy sources while simultaneously decreasing natural resource rent by limiting natural resource extraction for a sustainable environment. Although the statistical insignificance of the long-term coefficient of tourism has been observed, the study reveals a negative coefficient for tourism, suggesting the possible efficacy of sustainable tourism practices for mitigating CO2 emissions. The findings also demonstrate the long-term contribution of innovation activities to environmental degradation through the positive coefficient of patent applications. The research results offer significant insights for policymakers and stakeholders involved in the pursuit of a sustainable and ecologically conscious future in Bangladesh.