Short-run Causal Relationship Research Articles

RETHINKING THE PHILLIPS CURVE IN TÜRKİYE: NEW EVIDENCE FROM THE FREQUENCY DOMAIN

This study aims to investigate the short- and long-run relationship between the inflation rate, which has come to the fore after a long break all over the world, and the unemployment rate for the Turkish economy. For this purpose, the relationship between the two variables is analyzed using a causality test in the frequency domain, with monthly data for the period 2005:01-2023:03. The symmetric findings of the test indicate the existence of a unidirectional and short-run causal relationship from unemployment to inflation. The asymmetric findings of the test provide two important pieces of evidence. The first of these is the existence of a unidirectional and long-run causal relationship from the positive component of unemployment to the negative component of inflation. The second is the existence of a unidirectional, short- and long-run causal relationship from the negative component of unemployment to the positive component of inflation. These findings confirm the trade-off predicted by the Phillips Curve. It is also important for policymakers to try to increase productivity by making structural and institutional reforms in the labor market, as far as settling for a moderate inflation rate while struggling with inflation and unemployment problems.

Economic expansion and innovation: A comprehensive analysis of Pakistan's path to technological excellence.

To encourage technological and industrial innovation, nations worldwide implement "re-industrialization" and "manufacturing return." This study investigates the relationship between GDP growth, expenditure on research and development, and medium- to high-tech as a percentage of manufactured exports on technological innovation in Pakistan. We evaluated long-run and short-run causal relationships using the ARDL, bound-F test, and ECM regression. The study found a positive relationship between GDP growth and technological innovation in the short and long run. In the short run, with a one-year lag, the analysis reveals a positive and statistically significant relationship between technological innovation, medium-high-tech exports, and GDP growth. In the long run, R&D is positive and significant, while economic growth and technological innovation are positive but not statistically significant. There is a 0.38 percent chance that exogenous shocks will eventually lead to equilibrium in the long run. Based on the findings of this study, it is recommended to allocate resources to research and development, promoting collaborative initiatives, ensuring intellectual property rights, and developing a skilled workforce.

Does Wagner’s Hypothesis Explain the Dynamics of Health Expenditures in Transition Countries?

The purpose of this study is to analyze the short and long run causal relationship between public health expenditure and GDP per capita in transition economies within the context of the Wagner hypothesis. For the period 2000-2020, the empirical analysis was conducted using a dataset covering 22 transition countries: Latvia, Belarus, Czechia, Georgia, Bulgaria, Hungary, Estonia, Croatia, Moldova, Bosnia and Herzegovina, Slovenia, Ukraine, Armenia, Lithuania, Russian Federation, Slovak Republic, Romania, Turkmenistan, Uzbekistan, Tajikistan, Kyrgyz Republic, and Kazakhstan. Wagner emphasizes that increases in government expenditure, considered an endogenous variable, do not drive GDP growth. In essence, Wagner argues that a rise in GDP leads to an increase in government expenditures. The study assessed the validity of Wagner’s hypothesis by applying the Panel Cross-Sectionally Augmented Autoregressive Distributed Lag model (CS-ARDL), developed by Chudik et al. (2016), using annual data. For the empirical analysis, panel data from selected transition countries underwent causality tests proposed by Juodis, Karavias and Sarafidis (2021) and Dumitrescu and Hurlin (2012). The stationarity of the series was assessed using a panel unit root test. Subsequently, the panel cointegration test developed by Westerlund (2007) was employed to ascertain the long run cointegration of the variables in the subsequent phase. The results suggest that the Wagner hypothesis holds true within the context of transition countries, as indicated by the outcomes of the CS-ARDL model. The causality test revealed a one-way causal linkage between GDP per capita and health expenditure. Recommendations for those who make policy decisions were made in light of the findings.

The nexus among CO2 emission, health expenditure and economic development in the OECD countries: New insights from a cross-sectional ARDL model.

To find a way to realize sustainable development, this paper applied a cross-sectional ARDL (CS-ARDL) method to explore the interaction between carbon emissions, economic development, and health care expenditure for OECD countries. Firstly, we conduct a cross-sectional test to check whether the data is confronted with this issue. Secondly, we conduct a panel unit root test and cointegration test to confirm whether the ARDL-based method is suitable for our data. Thirdly, we analyze the results and provide possible explanations. Lastly, we conduct a short-term causality test to detect the connection between different variables. The main conclusion of our study includes: 1) Health care is a necessity in OECD countries. 2) Environmental deterioration places a heavy burden on health care expenditure in OECD countries. 3) Health care expenditure of last year negatively affects health care expenditure. 4) There is a short-run causality relationship from CO2, economic development, and dependency rate of youth to health care expenditure in OECD countries. Related policy proposals are provided according to our analysis of the results.

Examining the relationship between bitcoin and altcoins

Purpose- The purpose of this study is to examine the long and short-term relationship between Bitcoin and altcoins selected based on their market capitalization through an empirical analysis. For this purpose, the daily data of Bitcoin and nine altcoins consisting of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin for the period 07/08/2015-08/01/2020 were used. Methodology- The long-run relationship between Bitcoin and altcoins is first analyzed by Vector Autoregression (VAR) analysis. Granger causality test was utilized to determine the short-run causality relationship between the variables. The tests were conducted with the Eviews program. Findings- According to the results of the VAR analysis conducted to investigate the long-run relationship, there is a long-run relationship between Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple and Bitcoin. After determining the long-run relationship between the variables, the relationships between the variables were analyzed with the help of impulse response functions. Impulse response function shows the effect of a one-unit shock to one variable on the other variable. Accordingly, when the results of impulse response functions are analyzed; it is seen that a one-unit random shock in Bitcoin has a negative effect on Ripple, Nem, Litecoin, Dash, Litecoin, Dogecoin in the first two periods, the effect decreases in the second period, and this effect disappears in the third period. A random shock to Bitcoin causes a positive effect on Stellar that lasts for two periods. This positive effect ends in the third period. After analyzing the relationship between Bitcoin and altcoins with impulse response functions, the source of the changes in the variance of the variables is analyzed through variance decomposition. According to the variance decomposition results, the effect of Bitcoin on Dogecoin is 25% in the first period and 22% in the other periods. The variance decomposition of Dash shows that approximately 18% of the change in standard deviation was caused by Bitcoin in the first period and this percentage increased to 25.5% in the following periods. Litecoin's variance decomposition results show that 33% of the change in standard deviation from the first period to the last period was caused by Bitcoin. It is observed that approximately 8% of the change in Nem's standard deviation in the first period was caused by Bitcoin, while this rate increased to 21.5% in the last period. From the first period to the last period, 13.5% of the change in Stellar's standard deviation was caused by Bitcoin. When the variance decomposition of Ripple is analyzed, it is observed that 10% of the difference in the standard deviation is due to Bitcoin. This situation continued similarly from the first period to the last period. Following the VAR analysis, Granger causality test was conducted to explain the short-term relationship between the variables. According to the test results, there is a bidirectional Granger causality between Bitcoin and all altcoins. Accordingly, when Bitcoin is taken as the dependent variable, it is the Granger cause of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin. When the Granger causality relationship between altcoins is analyzed, a causality relationship was observed from Tether to Stellar, while no causality was found from Stellar to Tether. Similarly, while Granger causality is observed from Tether to Ripple, there is no causality from Ripple to Tether. The variance decomposition of Stellar and Ripple shows that Tether does not contribute to the change in standard deviation. The variance decomposition test supports the Granger test results. All altcoin variables except these are Granger causes of each other. Conclusion- At the end of the study, according to the results of the VAR analysis to determine the long-run relationship, there is a long-run relationship between Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple and Bitcoin. There is no long-run relationship between Tether, Monero, Ether and Bitcoin. According to the Granger causality analysis test results conducted to observe the short-term relationship, there is a bidirectional Granger causality between Bitcoin and all altcoins. Accordingly, when Bitcoin is taken as the dependent variable, it is the Granger cause of Ether, Ripple, Tether, Litecoin, Monero, Stellar, Dash, Nem, Dogecoin. As a result, it is observed that Bitcoin has a short-term relationship with all 9 altcoins subject to the study, and a long-term relationship with Dogecoin, Dash, Litecoin, Nem, Stellar and Ripple. These results show that the price movements in Bitcoin have an impact on altcoins. Keywords: Bitcoin, altcoin, cryptocurrency, causality analysis, VAR analysis. JEL Codes: G17, G10, C58

Banking regulation and bank credit delivery in selected Sub-Saharan African countries: Symmetric and asymmetric causal linkages

This study aimed to empirically determine the symmetric and asymmetric causal relationship between banking regulation and bank credit delivery using a context of 23 sub-Saharan African countries from 1995 to 2017. The estimated symmetric and asymmetric error correction-based multivariate panel Granger-causality models allowed for both long-run and short-run causal relationships. The results generally supported the existence of long-run symmetric and asymmetric causality between banking regulatory measures, bank credit delivery and two intermittent variables, namely, economic growth and inflation. In the short run, bidirectional symmetric causality existed between banking entry barriers and bank credit delivery, as well as a one-way symmetric causal flow running from bank credit delivery to banking capital regulations. Moreover, positive shocks to bank credit delivery Granger caused negative shocks to banking entry barriers, activity restrictions or capital regulations, while negative shocks to mixing of banking and commerce restrictions Granger caused positive or negative shocks to bank credit delivery. The findings highlight that policymakers should take into consideration not only the symmetric but also the asymmetric causal effects of reforms aimed at enhancing banking regulation and such reforms should be well-targeted and well-designed for them to stimulate bank credit delivery.

A Study on the Interrelationship between the Stock Markets and the Foreign Exchange Market in India

This study aims at examining the short-run and long-run dynamic linkages among exchange rates and stock market index in India through a structured cointegration and Granger causality tests. Daily exchange rates of USD, EUR, JPY, and GBP to INR along with the daily movement of NSE NIFTY and BSE SENSEX for a period spanning 20 years from 1 January 2003 to 23 November 2022 were used for the analysis. The results reveal that there is no evidence for a stable long-run relationship between stock market index and the exchange rates under study. However, the VAR-based Granger causality test shows that USD and EURO have short-run causal relationship with NSE NIFTY and BSE SENSEX. The NSE NIFTY and BSE SENSEX also seemed to have an influence on USD and JPY expressed in terms of Indian rupee.

Poverty Reduction, Economic Growth, and Mobile Money Proliferation in Ghana

The study analysed the impact of poverty reduction, economic growth, on proliferation of mobile money in Ghana. Using data from the world development indicators and factor analysis, an index measuring mobile money, economic growth, and poverty reduction in Ghana was developed. The data ranged from 1980 to 2021, and a convenience sampling method was used to select the series from world development indicators (WDI) and indexes created to measure the primary variables. The Johansen cointegration method revealed that cointegration exists between the variables, indicating that the variables have long-term relationships. The results of Vector error correction indicated that there is both a long-term and a short-term relationship between the proliferation of mobile money, economic growth, and poverty reduction in Ghana. The findings indicated the existence of a short-term relationship between the variables. Granger causality test also confirmed that mobile money proliferation, economic growth, and poverty reduction in Ghana have a short-run causal relationship. Given the significant role that mobile money service plays in Ghana's economic growth, the study concluded that policymakers in Ghana would do well to pay attention to mobile money service. In order to reduce mobile money and cyber fraud, policymakers are also encouraged to make mobile money and banking services accessible, including financial literacy education, and to strengthen internal controls. Future research could examine the relationship between the proliferation of mobile money, credit assessment, employment, and investment in Africa.

Relation Between Inflation and Capital Market in India

Capital market has significant influence on the inflationary situation in an economy both in the short run and in the long run. The general determinants which affect capital market are share indices, stock prices, prices of gold and silver, interest rate, exchange rate and even money supply can be treated as influencing variable when money is treated as capital. In this paper the author examined the impact of capital market on inflation in India during 1980-2022 taking CPI and WPI as the indicators of inflation and gold price, silver price, BSE index, BSE market capitalization, money supply and rupee dollar nominal exchange rate are considered as the indicators of capital market. Augmented Dickey-Fuller test was applied to verify unit root for all variables including break unit roots and the author calculated growth rates during 1980 – 2022 using the simple semi-log linear trend model. Author applied Johansen cointegration test and vector error correction models among the variables in both the cases of CPI and WPI and calculated short run causality through Wald test and long run causality through cointegrating equation. In VECM, the paper found one significant cointegrating equation in case of CPI and found three significant cointegrating equations in WPI. The paper found that CPI has long run causal relationships with BSE index, BSE market capitalisation, money supply and rupee dollar exchange rate and WPI has long run cointegrating relationships with BSE market capitalisation, money supply and rupee dollar exchange rate respectively. Rupee dollar exchange rate has short run causal relationships with CPI and again CPI and BSE index has bidirectional short run causality. According to impulse response functions, the responses of CPI to gold price, BSE market capitalization and money supply have been approaching towards equilibrium but finally diverged away from equilibrium. There are significant short run causalities from BSE index and money supply to WPI. The impulse response of WPI to gold price, silver price, BSE index, BSE market capitalisation and exchange rate of rupee have been converging towards equilibrium many times although diverged finally. The model can be modified by including interest rate, share prices, bond prices under monthly data analysis.

The Determinants of Capital Adequacy in the Jordanian Banking Sector: An Autoregressive Distributed Lag-Bound Testing Approach

The current study aims to examine the determinants of the capital adequacy ratio (CAR) in the context of Jordanian banks through a literature review and analysis of empirical evidence. The aggregate data were obtained from Globaleconomy.com, the Financial Soundness Indicators, the Central Bank of Jordan, and World Bank Data covering the period from 2003 to 2021. The aggregate data were analyzed using autoregressive distributed lag (ARDL), utilizing Econometric Views (EViews) software. The empirical results suggest a short-run causality relationship running from banks’ credit-to-deposits ratio, banks’ leverage ratio, banks’ liquidity ratio, and one-year-lagged ROE to the CAR. The results also suggest the existence of short-run causality running from the capital-to-assets ratio, one-year-lagged capital-to-asset ratio, liquid-assets-to-deposits ratio, and coverage ratio to CAR. In addition, the results show the leverage ratio and liquidity ratio as having positive long-run associations with CAR. A positive and significant long-run association was also found between CAR, on the one hand, and the capital-to-assets ratio and the liquid assets to deposits ratio; the coverage ratio, on the other hand, showed a negative and statistically significant long-run association with CAR. The pairwise Granger causality test results reveal that liquid asset to deposits, money supply, profitability, and the capital-to-assets ratio Granger cause CAR. The study findings emphasize the importance of understanding the factors impacting CAR, the direction of the influence, the magnitude of the influence of the determinants of CAR in emerging economies such as Jordan and taking appropriate measures to safeguard the stability and resilience of the banking industry.

Investigation of the Causal Relationships between Economic Development and Combustible Renewables and Waste Consumption in Central Asian Countries

This study examines the relationships between Foreign direct investment (FDI), Gross domestic product (GDP), Trade, Inflation, Labor force, Population density, Combustible renewables and waste consumption for the case of Central Asia, spanning the period 1990 to 2020. The combustible renewables and wastes consumption in Central Asia are based on the long run and short run relationship between economic development with the Error Correction Model (ECM) based Panel Cointegration tests and Panel Vector Error Correction Model (VECM) Granger causality test tried to explain using the causality test, spanning the period 1990 to 2020. An empirical analysis uses the Im, Pesaran, and Shin (CIPS) Panel Unit Root test and Westerlund ECM to test the basics of the data unit based on this information. The Panel Vector Autoregression (PVAR) specification was based on the results of the Lag-order selection criteria, and the stability of the PVAR model was checked through the observation of the Hausman test and Eigenvalue stability condition. It performs tests to verify the existence of the long run relationships among the variables and examines short and long run causal relationships. It finds that increased combustible renewables and waste consumption use is the main cause of increased economic growth.

Determinants of the investments: a case study of Côte d Ivoire

Purpose- Based on the importance of investments in supporting the economic growth in the country, the main objective of this study is to investigate the determinants of the investment in Cote d’Ivoire over the period 1980-2020. In order to achieve the objective, this study examines the interactive effect of external debt, communication infrastructures, imports and inflation on the investments in Cote d’Ivoire. Methodology- Annual time series data over the period 1980-2020 were employed in this study. The data are obtained from the World Bank. The ADF unit root test, Johansen cointegration test, OLS model, Granger causality test, and CUSUM test were applied to analyze the data. Ordinary Least Squares (OLS) model has been used in this study to estimate the coefficient of the variables, and it has been subjected to a number of statistical diagnostic tests, namely, the normality, serial correlation, and heteroscedasticity tests to ascertain its statistical adequacy. Findings- The ADF unit root test results indicated that all variables in the model are not stationary at the level but became stationary after first differencing. The Cointegration test pointed to a significant long-run relationship among the variables. Besides, the results of OLS model showed that investment is positively and significantly related with communication infrastructures, importing and inflation, but it is related negatively and insignificantly with external debt. Imports have the biggest effect on the investment. The Granger causality test shows that there are no short-run causality relationships between the variables. However, there are bidirectional long-run causality relationships between investment, external debt and importing, and unidirectional long-run causality relationships running from communication infrastructures and inflation to investment. Lastly, CUSUM test indicated that there are no structural changes in the model. Conclusion- The study therefore recommends that the government should use external debt more efficiently, reduce corruption, improve the infrastructure and create an attractive investment climate, as well as reducing most tariff and nontariff barriers, which will support the investment in the country.

The relationships between domestic investment, country risk, governance and economic development: A comparison, Kazakhstan versus Poland

Domestic investment is one of the key drivers for economic growth and development. But domestic investment does not happen automatically. It requires a positive governance and economic environment. The primary aim of this paper was to test the impact and relationship between domestic investment and some of the determinants of domestic investment, including country risk, governance indicators, and economic development. Kazakhstan and Poland were selected as the study regions in this comparative analysis. A quantitative econometric modelling methodology was utilised to determine the relationships between the selected variables by estimating an ARDL model. In the analysis, long-run relationships and short-run causality relationships were estimated. The study and literature review results confirm that domestic investment is crucial in achieving accelerated economic growth and development. In policy development, all effects should be made to ensure an enabling environment to attract investment. Domestic investment leads to increased production and more competitive productivity. Good governance, including quality institutions and policy, is also required for increased investment.

The Main Determinants of the Government Expenditure: A Case Study of Côte D’ivoire

Abstract Based on the importance of government expenditure in supporting economic growth in the country, the main objective of this study is to investigate the determinants of government expenditure in Cote d’Ivoire over the period 1980-2020. To achieve the objective, this study examines the effect of external debt, national income, inflation, and population on government expenditure, by using the ADF unit root test, Johansen cointegration test, Granger causality test, and CUSUM test. Results from the Johansen cointegration test indicated that there are long-run relationships among the variables. Government expenditure is positively related to external debt, national income, and population, but it is negatively related to inflation. The population has the biggest effect on government expenditure. The Granger causality test shows that there is a unidirectional short-run causality relationship running from external debt to government expenditure, but there is no evidence of any short-run causality relationship between national income, inflation, population, and government expenditure. On the other hand, there are bidirectional long-run causality relationships between inflation, population, and government expenditure, and unidirectional long-run causality relationships running from external debt and national income to government expenditure in Côte d’Ivoire. Lastly, the CUSUM test indicated that there are no structural changes in the model. The study recommends that the government should use government expenditure more efficiently in improving the infrastructure and creating an attractive investment climate, as well as upgrading the quality of human capital by improving the education system, health services, and the standard of living.

Optimal governance for economic growth and environment: evidence from the United Kingdom

ABSTRACT It has now been more significant than ever to understand the consequences of environmental policies given the unsustainability of enduring environmental challenges. This study aims to examine the nexus between economic growth, industrialisation and the environment in the United Kingdom, using time series data for the period 1948–2018. Gross Domestic Per Capita (GDPC) is used as a proxy for economic growth, energy consumption as measures for industrialisation and carbon dioxide emissions (Co2) or environmental pollution to test if the Environmental Kuznets Curve (EKC) holds for the UK. Autoregressive distributed lag (ARDL) and vector error correction model (VECM) have been employed to investigate the long-run and short-run causal relationships among variables, respectively. The paper concludes that the EKC hypothesis holds for the UK as the long-run relationship between CO2 emissions and GDPC is found. Further, energy consumption and imports of goods are found to have insignificant effects on the environment in both the short-run and long-run. The paper further concludes that environmental policies such as limiting energy consumption and controlling carbon emissions have no unfavourable effect on the real output growth in the UK.

The Causal Nexus between Economic Growth, Investment and Saving using Vector Error Correction Model in Ethiopia

Investment and saving are critical for a country's economic development. The primary goal of this research was to determine whether there is a long-run or short-run causal relationship between saving, investment, and economic growth(GDP). We used Vector Error Correction Model and Augmented Dickey-Fulle and Phillips-Perron tests were used to verify the Unit root test. The Johansen Cointegration Test shows that economic growth, savings, and investment are reconciled and are in long-run equilibrium. Vector error correction tests show that there is a unidirectional causal relationship between saving and investment to economic growth in the short-term as well as long-term. There is a bidirectional causal relationship from total domestic savings to total domestic investment. In other words, savings and investment lead to economic growth. Therefore, for this purpose, policymakers need to formulate and implement policies that promote economic growth. Such policies lead to higher growth in savings and investment.

Asymmetric Link between Unemployment, Inflation and GDP growth rate in the United Kingdom Economy: An ARDL Bounds Approach

This paper investigates the relationships between unemployment, inflation, and economic growth in the UK. Quarterly data for the period 1990: Q1 to 2020: Q4. The ARDL bounds test model, Vector Error Correction Model (VECM), and Granger causality test are applied to examine the variables' short-run and long-run causal relationship. Unemployment rate (UR), inflation rate (INFR) and GDP growth rate (GDPGR) as a proxy of economic growth have been taken to study the relationships among unemployment, inflation, and economic growth. The short-run ARDL model in the study suggests that the entire variables (GDPGR, DUR and INFR) have a short-run causal relationship with each other. It follows the economic theories of Okun’s Law and the short-run Philips curve that there is an interrelationship among economic growth, unemployment, and inflation. The ARDL bounds test and VECM findings suggest strong evidence of cointegration between the three variables, which indicates a long-run equilibrium relationship. The pairwise Granger Causality test suggests a bi-directional relationship between economic growth and unemployment and a unidirectional relationship between inflation and economic growth (INFR→GDPGR) and between inflation and unemployment (INFR→DUR). In this case, monetary and fiscal policies may no longer effectively achieve policymakers’ economic growth and development goals.

Stock market development and economic growth in sub-Saharan Africa (1990–2020): an ARDL approach

PurposeThe purpose of this paper is to investigate the short and long run causal relationship between stock market development and economic growth in sub-Saharan Africa within the period 1990 and 2020.Design/methodology/approachUsing panel data from 1990–2020 obtained from the World Bank development indicators, the study makes use of the autoregressive distributed lag model and the Granger causality and cointegration to analyze the long and short run causal relationship between stock market development and economic growth in sub-Saharan Africa.FindingsThe findings unveiled that stock market capitalization had a positive and significant effect on economic growth in the long run and a negative insignificant effect in the short run within the period of 1990–2020 while stock market liquidity measured through total value of shares traded and turnover ratio had a negative and significant effect on economic growth in sub-Saharan Africa within the period of 1990–2020. The Granger causality test showed an inconclusive result between stock market development and economic growth; implying that the authors cannot say if it is stock market development that causes economic growth or it is economic growth that causes stock market development within the period of 1990–2020.Practical implicationsThe findings suggest that governments of sub-Saharan African countries should encourage stock market development by implementing favorable rules for companies listing on their stock market, promote stock market integration with world markets to diversify risk, increase public awareness on stock markets, increase investors' confidence level and finally, remove stock market impediments like high taxes, legal and regulatory barriers to its development.Originality/valueThis study contributes to the existing literature by offering a whole new perspective on stock market development and economic growth since its conception in sub-Saharan Africa. Again, contrary to other papers, the study show how stock market development can contribute to the growth of sub-Saharan Africans’ economy.

Existence of Cointegration between the Public and Private Bank Index: Evidence from Indian Capital Market

Purpose: The study aims to examine both long-run and short-run causal relationships among the public and private bank indices of the Indian capital market. Design/methodology/approach: The paper employs Johansen's cointegration approach and Granger Causality test, which allows measuring long-run relationships and causality among the public and private bank indices. Findings: The empirical analysis indicates that long-run cointegrating relationships exist between public and private bank indices. On the other hand, Granger Causality reveals that the private bank index plays a dominant role; Granger causes public bank index. So, long-run diversification may not be possible due to common factors; however, short-run portfolio diversification is possible due to unidirectional causality running from private bank index to public bank index. Originality/value: Investors often create portfolios by allocating funds to public and private bank stocks based on the performance and projected development of the bank. In recent decades, there has been a surge in interest in banking sector unification. So, the transfer of information between private and public banks witnessed a boom. To fill this research gap, the study contributes to the literature by investigating the cointegration and causality between Nifty PSU Bank and Nifty PVT Bank indices in the Indian capital market. Implications: The study's findings have implications for investors while maximizing return on investment when diversifying capital among public and private bank stocks. The findings significantly impact traders' judgments when using hedging and arbitration strategies, guide portfolio managers when managing risk, and help policymakers assess the market stability. Keywords: Public Bank Index, Private Bank Index, Johansen's Cointegration Test, Granger Causality Test JEL Classification: C58 N25 O16

Ready-made Garments, FDI and Total Exports of Bangladesh: A Time Series Analysis

This study examines the long-run and short-run causal relationships among readymade garments export, total export earnings, and net foreign direct investment inflows utilizing data from the financial year 1996-97 to 2019-20. The autoregressive distributed lag bounds test discloses the existence of a long-run relationship among the variables. This study also employed the Johansen cointegration test to supplement the results of the ARDL approach. This cointegration test confirms the presence of two cointegration equations. In addition, the Toda-Yamamoto test is performed to demonstrate the existence of short-run and long-run relationships among the variables. The results indicate that there is bidirectional causality between RMG exports and total exports in the short run as well as in the long run. Another important aspect of this study is that there is bidirectional causality between FDI and total export earnings in the short run but there is a unidirectional causality in the long run. The analysis also gives insights like single sector dominance, problems that existed in the RMG sector, and problems and prospects of FDI inflow. Further, keeping in view with these problems, the study urges pragmatic feasible measures for sustainable export growth.