The effect of inflation on economic growth in Ghana, 1995-2019: Post democratic analysis

Background: One of the fundamental goals of macroeconomic policy in many nations, both developed and developing, is to foster economic development while keeping inflation low. There has been a debate as to whether inflation impacts negatively on economic growth or rather promotes economic growth. The study is motivated by this controversy and used time-series data from 1995 to 2019 in Ghana to examine the relationship between inflation and economic growth, establish the long-run effect and also test whether there exists a causal effect between inflation and economic growth. Method: The review utilized Ordinary Least Square (OLS) regression examination to inspect the impact of inflation on economic growth and while long run co-integration relationship was additionally decide utilizing Fully Modified (FM-OLS) regression analysis. Granger causality was investigated to see if there is a causal impact among inflation and economic growth. Model diagnoses were performed to discover the strength of the discoveries where autocorrelation, multicollinearity, normality test and heteroscedasticity were tested. Results: The review uncovered that, inflation has a negative measurably irrelevant impact on economic growth at 5% basic level. The concentrate likewise uncovered that there was co-integration relationship between inflation and economic growth during the time of viable 1995-2019. There was no causal impact among inflation and economic growth, in this way neither inflation nor economic growth Granger-Causes the other. The study suggest that inflation targeting ought to be the best financial approach measure for economic growth by keeping up with the rate at 8+/-2%.

Stock Market Reactions during Different Phases of the COVID-19 Pandemic: Cases of Italy and Spain

The COVID-19 pandemic and pandemic-induced lockdowns and quarantine establishments have inevitably affected individuals, businesses, and governments. At the same time, the spread of the COVID-19 pandemic had a dramatic impact on financial markets all over the world and caused an increased level of uncertainty; the stock markets were no exception either. Most of the studies on the impact of the COVID-19 pandemic on stock markets are based either on the analysis of a relatively short period (the beginning of pandemic) or a longer period, which, in turn, is very heterogeneous in terms of both the information available on the COVID-19 virus and the measures taken to contain the virus and address the consequences of the pandemic. However, it is very important to assess the impact not only at the beginning of the pandemic but also in the subsequent periods and to compare the nature of this impact; the studies of this type are still fragmentary. Therefore, this research aims to investigate the impact of the COVID-19 pandemic on stock markets of two of the most severely affected European countries—Italy and Spain. To reach the aim of the research OLS regression models, heteroscedasticity-corrected models, GARCH (1,1) models, and VAR-based impulse response functions are employed. The results reveal that the stock market reaction to the spread of the COVID-19 pandemic differs depending on the country and period analyzed: OLS regression and heteroscedasticity-corrected models have not revealed the statistically significant impact of the spread of the COVID-19 pandemic, while impulse response functions demonstrated the non-zero primary response of analyzed markets to the COVID-19 shock, and GARCH models (in the case of Spain) confirmed that the COVID-19 pandemic increased the volatility of stock market return. This research contributes to the literature by providing a comprehensive impact assessment both during the whole pre-vaccination period of the pandemic and during different stages of this period.

A model proposal for estimating banks’ future value: Evidence from Turkey

Investors make solid decisions when evaluating their investments based on positive indicators the firm may show in the future, rather than based on its past performance. Accordingly, this study aims to investigate the relationship between performance criteria and the most significant value-based criterion; Economic Value Added (EVA). Further, it evaluates the impact of future EVA values on the bank value. Panel Data Analysis and the OLS Regression model are used to estimate the regression equation. The analysis is performed using data of 10 banks on the BIST Banks Index over the period 2011 to 2020. Furthermore, the EVA criterion was converted into standardized EVA(SEVA) by dividing EVA by total assets. The OLS regression analysis results revealed that the model’s explanatory power for the SEVA variable is 71.92%. The three variables that have positive correlation with SEVA are earnings per share (EPS) and TOBINQ rates at the 1% significance level and the price to sales growth rate with a degree of significance at 10%. Regarding the Panel Data Analysis results, while the explanatory power of the SEVA variable is 72.14%, its association with the EPS and TOBINQ criteria was found to be significant at the 1% significance level. The empirical investigations reveal that the model developed using the future SEVA as a proxy for bank value is found to be promising, and it is accepted that the SEVA variable can be used instead of the bank value.

COVID-19 Pandemic and the Performance of Financial Firms in Nigeria

The impact of the COVID-19 pandemic on the performance and capital adequacy of Nigerian banks is explored in this article. The aim of the study was to see how the virus outbreak affects the performance and capital adequacy of Nigerian banks. For the purposes of this study, an actual post-research budget was used. The number of confirmed positive cases in Nigeria since 2020 is used as an indicator of the virus, with capital adequacy measured by capital adequacy ratio (CAR) and bank financial performance measured by the performance of assets (ROA). In one model, positive cases of the Covid virus were linked to the banks' CAR, while in the other, positive Covid cases were linked to the banks' ROA. Secondary statistics are included in CBN's annual report for the year ended 2020, to be released in 2021. Conventional least squares (OLS) regression estimates were used to analyze the data. . According to the results, the Covid pandemic has had a positive and significant effect on the capital adequacy of Nigerian banks. This can be seen in CBN’s announcement of a higher equity level for 2020 of 15.2%, up from 14.6% in 2019

Determinants of tourists’ length of stay

This paper aims to identify the determinants of the length of stay (LoS) of international tourists in Norway. The paper reassesses the standard assumption related to tourists’ LoS; it refers to the travel industry’s current trends, and it postulates a more sustainable approach to analyzing tourists’ LoS at the destination level. The paper concludes with a series of recommendations. The data for this study were collected during 153 data collection days and among 5,300 travelers in Norway. The determinants of LoS were analyzed by means of an ordinary least squares (OLS) regression. The results indicate that tourists’ LoS is positively related to their age, interests (nature-based tourists), origin (German, Dutch tourists) and mode of travel organization (package tourists). A negative and significant effect on tourists’ LoS was found for tourists’ interests (urban-based tourists), spending, and origin (home market, long-haul tourists). No significant results were revealed for two covariates, namely, gender and repeat visitation.

The impact of Islamic portfolio on risk and return

The purpose of this study is to investigate the comparative impact of conventional and Islamic bonds over returns. It provides useful insights to investors to diversify investment by lowering the risk to the optimum level. This study examines the impact of the conventional and Islamic portfolios on returns through simple OLS regression, suggesting that Sukuk returns are positive and significant. Simultaneously, conventional bonds show a negative trend, but in the long run, the returns are significant. It indicates that the market is volatile due to macroeconomic factors that can reduce risks through portfolio diversification. Thus, this research suggests that investment can be secured by taking a rational portfolio decision that confirms robustness. Therefore, it is a good opportunity for the investors to get high margins over the investment tenure.

Impact of Covid-19 on the Financial Sector Indices

This study is an attempt to assess the impact of Covid-19 and the lockdown pronounced thereof on the Nifty sectoral indices with specific reference to the financial sector indices owing to their significance in the economy. The OLS regression, Granger Causality and Impulse Response Function were estimated to measure the changes in the future responses of Nifty 50 to the changes in the select sectoral indices, namely, Nifty Bank, Nifty Financial Services and Nifty Private Banks and Nifty PSU Banks for the period consisting two sub-periods, i.e., the first sub-period from April 2019 to March 2020 are assumed as the preCovid-19 period and the second sub-period from April 2020 to March 2021 is assumed as the period during Covid-19. The results indicated that the shock of the Covid-19 had an impact on the financial sector indices in India during the Covid-19 period.

The Role of Industrial Parks Entrepreneurial Ecosystem in Strengthening Ventures' Capability: Evidence From Ethiopian Small Manufacturing Enterprises

Small scale enterprises sector has been recognized as an integral component of economic development and it is advisable and indispensable to integrate the enterprises with Industrial parks for sustainable business operation. IPs plays a crucial role in organizing the resources and innovation of manufacturing operation through business advising, infrastructure provision, technology transfer, and R&D support which advances firms’ capability. In this sense, the objective of this was to investigate the role IPs entrepreneurial ecosystem towards improving the capability of small ventures. Data were obtained from a sample of 245 small manufacturing enterprise owners selected through simple random sampling and analysed using descriptive, multi-level regression analysis and OLS regression analysis. From this, the presence of better and suitable entrepreneurial ecosystem which consists of provision of training, market information, adequate finance, and government commitment positively contributes for improvement of small firm’s capability. Despite of this, the study also found that there are many barriers hindered the development of strong entrepreneurial ecosystem in Ethiopia, such as, human capital, institutional, financial, market, policies and legal procedures, cultural and resource barriers. The entrepreneurial ecosystem influences the resources capability more when academia-industry linkage exists. The OLS regression result also shows that the entrepreneurial skill mediates the influence of entrepreneurial ecosystem on technological capability, while managerial knowledge mediates the influence of entrepreneurial ecosystem on the firm’s resource capability. The implication for policymakers is to develop a policy that supports incorporating small firms in industrial parks entrepreneurial ecosystem and link with academia. The study also forwarded a clue for managers of small firms in improving their firms technological and resource capabilities through building managerial knowledge and entrepreneurial skills.

The Determinants of Fish Catch: A Quantile Regression Approach

The goal of this study is to use quantile regression (QR) to find predictors of fishers’ catch and compare it with OLS regression. The heterogeneous association across the different quantiles of the catch distribution was investigated using QR analysis. The findings reveal that the effect changes depending on where a fisher is in the catch distribution. In the OLS, there are several non-significant predictors that appear to be significant in quantile regression. By OLS regression, demographic variables have little effect on fishers’ catch; but, in quantile regression, marital status, fishing hours, and use of motorized boats appeared to have a relatively high impact at the top of the distribution.

Impact of Storage Conditions on Equine Fecal Inoculum for Estimating In Vitro Digestibility

This study evaluated the effect of storage conditions of equine fecal material on the viability of microbial inoculum used for in vitro equine digestibility trials. Pooled fecal material from three mature Quarter Horse geldings was stored at 39 °C anaerobically for 15 min (control), while aerobic samples were stored at 22 °C for 6 h (SC1), 3 °C for 6 h (SC2), and −18 °C for 24 h (SC3). Following storage, the feces were utilized to prepare microbial inoculum for the digestion of six different forages using the Daisy II Incubator. After incubation, DM, NDF, and ADF compositions were determined and used to calculate DMD, NDFD, and ADFD. Analysis using the OLS regression model for differences in DMD, NDFD, and ADFD across the storage conditions found significant interactions between the forage sample and the storage condition (p < 0.05). The results between the control and SC1, SC2, and SC3 were not different (p < 0.8). Fecal material stored aerobically for six hours at 22 °C provided similar digestibility estimates compared to the control, while DMD decreased by 3.86% in SC2 and by 4.08% in SC3.