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The purpose of this study was to investigate the dynamic interactive link between housing prices, stock market price and effective exchange rate in the Iranian economy for a monthly period from April, 2004, to March, 2019. In addition, for a more accurate analysis, three control and determinates variables including real interest rate, real GDP and FDI have been added to the base model.

For this purpose, we will consider this issue by developing the study of Lean & Smyth (2014), Ali & Zaman (2017) and Coskun et al (2017) in the framework of ADRL and NARDL models. Also, this study analyzed the asymmetric/non-linear impact of stock market indexes and effective exchange rate on Iran’s housing inflation. Asymmetries imply to both positive and negative changes in the variables.

The results obtained from the ADRL and NARDL models suggest that the existence of cointegration relationship between housing market price and its determinants. From linear model, we found that the exchange rate and stock market price have a positive effect on the real estate inflation in the short run; this relationship is also confirmed in the long run. Other empirical results indicate that the GDP stimulates housing price in both long and short run cases, while FDI and real interest rate have an opposite effect. In addition, the results provided by the asymmetric model lead to the rejection of the null hypothesis of no co-integration between the variables. In addition, we found that the effect of stock price in the short and long term are asymmetric and there also is an asymmetric long-run effect of real exchange rate on the real estate price.

Finally, to analyze the sensitivity, we entered two explanatory variables of inflation and money supply to the baseline equation. The finding represented that in both linear and nonlinear framework, a positive correlation between these two variables with housing prices have been proved.

This paper aims to examine the effect of corruption on foreign direct investment (FDI) inflow in Ghana. This provides answers to the call for further empirical examination of the contextual impact of corruption on FDI inflow.

The study uses a non-linear ADRL time series econometric model to estimate data from the World Bank and the international country risk guide (1984–2019).

The study confirms the sand in the wheel and the grabbing hand hypothesis of the impact of control of corruption (CoC) on FDI both in the short and long run. However, degradation on the CoC index has a significant and more than a proportionate constraint on FDI inflows, while an improvement in CoC has no significant impact on improving FDI inflows. An explanation for this outcome was proposed after comparing this finding to a similar prior study with a Nigerian data set (Zangina and Hassan, 2020). The proposed explanation relied mainly on the rational expectation hypothesis and drawing elements of the efficient market hypothesis. FDI inflows do not react to outcomes or trajectories reasonably expected because such rationally expected future outcomes will have been modelled into existing FDI movement decisions. Instead, FDI flows react to “surprises” and often respond in a more than proportional manner.

Political leadership in Ghana should be conscious of the severe adverse effects of inaction or ineffective action in curbing corruption, leading to slippering in CoC rankings. In the case of Ghana, the dependence of FDI on CoC is even more pronounced as the other variables within the specified model show an insignificant impact on FDI. Additionally, admittedly aggregated cross-country data in econometric modelling is appealing and has some empirical basis, but these must not erode the relevance of country-specific studies as both are needed to support theorization.

The paper is among the first to test for the asymmetric relationship between corruption or its control thereof and FDI with a time series approach, and hence, the findings offer new insight.

The main objective of this study is to examine how political institutions affect economic performance in Ethiopia over the 1980–2019 time periods.

Mainly, the impact of political institution indicators including, level of democracy, political violence, democratic accountability and regime durability have been examined using auto regressive distributed lag (ARDL) bound test approach to co-integration and the error correction model.

This study confirms that level of democracy and democratic accountability has an adverse long effect on the economic performance of Ethiopia. On the other hand, political violence has a negative short-run causal effect on economic performance in Ethiopia. The study concluded that the deterioration of political institutions harmfully affected economic performance in Ethiopia.

Government policymakers should primarily pay attention to promoting and changing those political institutions that harm economic performance. Additionally, better management of political violence has important implications for fostering the economic performance of Ethiopia.

This study provides some valuable evidence on the nexuses between political institutions and economic performance in Ethiopia. Likely, this is the first investigation on the subject under the consideration to use time analysis and will vigorously contribute to the literature as well by employing the ADRL bound test. Previous studies have examined the impact of the institution on economic growth on a cross-country basis. Further analysis is required to understand the effects of institutions such as level of democracy, political violence and democratic accountability on economic development.

This paper aims to investigate opportunities of the short- and long-run international portfolio diversification (IPD) benefits by investing in the Middle Eastern oil-producing countries. Over the past decades, IPD has been the integral feature of global capital markets. Several potential benefits like increasing returns and/or reducing risk have made investors to internationalize their portfolios. Solnik’s theory (1974) approved that gains can be achieved through IPD if returns in the different markets are not perfectly correlated. This may attribute to low correlations of equity returns among different economies. In this regards, there would be a large potential of diversification benefits for investors that diversify into new emerging group of economies such as equity markets of the main oil-producing countries. These markets are often segmented and they may ensure a superior return rate for a given risk level.

In most of the previous studies, Pearson’s correlation test is used to analyze the short-run relationship of market prices. However, recent empirical studies indicate that correlations between equity returns vary over the time. To examine the time-varying conditional correlation, this paper used the dynamic conditional correlation (DCC) model to investigate opportunities of the short-run IPD benefits. In addition, for the long-run linkage analysis, the autoregressive distributed lag (ADRL) approach introduced by Pesaran et al. (2001) is applied.

It is found that, the market returns of the sampled countries are not definitely correlated in the short- and long-term. So, international portfolio investors may get the short- and long-term diversification benefits by diversifying their portfolios among the Middle Eastern equity markets, namely, Iran, Bahrain, Qatar, Kuwait, Oman, Saudi Arabia and UAE.

This paper departs from earlier studies by focusing on the dynamic characteristics of correlation. Two main issues are pursued in this paper. First, instead of modeling the correlation by methods like Pearson correlation coefficient that consider the constant-correlation assumption, this paper directly uses the DCC model. Second, to empirically estimate the long-run relationship among stock markets in the Middle Eastern oil-producing countries, the ARDL approach is utilized. The ARDL approach is more robust and performs well for small sample sizes than other co-integration techniques.

Over the last decade, investments in green energy companies have witnessed noticeable growth rates. However, the glacial pace of the world economic restoration due to COVID-19 pandemic placed a high degree of uncertainty over this market. Therefore, this study investigates the short- and long-term relationships between COVID-19 new cases and WilderHill New Energy Global Innovation Index (NEX) using daily data over the period from January 23, 2020 to February 1, 2023.

The authors utilize an autoregressive distributed lag bounds testing estimation technique.

The results show a significant positive impact of COVID-19 new cases on the returns of NEX index in the short run, whereas it has a significant negative impact in the long run. It is also found that the S&P Global Clean Energy Index has a significant positive impact on the returns of NEX index. Although oil has an influential effect on stock returns, the results show insignificant impact.

Governments have the chance to flip this trend by including investment in green energy in their economic growth stimulation policies. Governments should highlight the fundamental advantages of investing in this type of energy such as creating job vacancies while reducing emissions and promoting innovation.

First, as far as the authors are aware, the authors are the first to examine the effect of oil prices on clean energy stocks during COVID-19. Second, the authors contribute to studies on the relationship between oil prices and renewable energy. Third, the authors add to the emerging strand of literature on the impact of COVID-19 on various sectors of the economy. Fourth, the findings of the paper can add to the growing literature on sustainable development goals, in specific the papers related to energy sustainability.

The goal of this study is to look into the connection between Sri Lanka’s fiscal deficit and inflation. Sri Lanka is currently experiencing one of its worst inflation crises in its history, necessitating an investigation into how fiscal deficit affects inflation, as it has been experiencing an ever-increasing fiscal deficit for the last four decades. The quantitative methodology is employed in this study using annual data from 1977 to 2019 following the ARDL technique in the analysis. The findings showed that both in the long run and the near term, Sri Lanka’s fiscal deficit had a positive and significant link with inflation. The policymakers should increase the revenue through the taxes in order to bridge the fiscal deficit. As a developing country, it cannot afford to continue with the ever-increasing fiscal deficit which has become a burden to country. Also, it is the responsibility of each government to think carefully to reduce its massive expenditure which has become a common feature in the country for the last four decades. Cutting down government expenditure can improve the economic growth and well-being of the citizens too. The government should therefore concentrate on short-term investment programmes that will benefit the country while doing the same in the long run.

The aim of this chapter is to show the limits of the European policy model and to support the existence, through straightforward empirical analysis, of an inverse relationship both in the short run and in the long run between trust in institutions and unemployment. The empirical methodology relies on dynamic panel data techniques allowing measuring in a single equation both the long-run relationship and the short-run speed of adjustment among variables. This connection appears to be valid both in the Eurozone considered as a whole and in particular in peripheral countries, where the macroeconomic dynamics have been, under this respect, much more divergent from the average. This outcome allows proofing that to consolidate the European process of integration in the long run, institutions should have as main objective not only inflation but especially unemployment.

Purpose: This study analyses how investments and specific financial factors affect the financial performance of businesses in Kosovo. Exploring the relationship between investments and financial performance and their impact on performance volatility, performance is assessed using return on assets (ROA) and return on equity (ROE) investments.

Methodology: Quantitative methods using secondary data from audited financial statements of Kosova manufacturing and commercial enterprises cover a 3-year period (2019–2021), involving 40 enterprises with 120 observations. Statistical tests such as descriptive statistics, correlation analysis, linear regression, Hausman–Taylor regression, fixed effects, random effects, and generalised estimating equations (GEE) model are applied. The study also utilises ARCH–GARCH analysis to assess the relationship between investments and performance volatility.

Findings: Investments positively impact the financial performance of Kosova businesses and significantly reduce performance volatility. Long-term liabilities, retained earnings, and short-term liabilities also play a role in reducing asset return volatility, while cash flow from financial activities increases it. Investments, cash flows from financial activities, long-term liabilities, short-term liabilities, retained earnings, and solvency affect equity return volatility.

Practical Implications: The study sheds light on how investments and financial factors influence the financial performance and volatility of Kosova businesses. Policymakers can use these insights to create policies that foster the development of commercial and manufacturing enterprises, given their importance in Kosovo’s economy.

Significance: This research provides valuable insights for business managers to enhance investment strategies and improve financial performance. Policymakers can rely on this academic study to enhance the economic environment and promote the growth of businesses in Kosovo.

This study aims to investigate the asymmetric impact of daily announcements regarding COVID-19 on investor sentiment in the stock market.

This study uses a Non-Linear Autoregressive Distribution Lag (NARDL) model that relies on positive and negative partial sum decompositions of the Coronavirus indicators. Five investor sentiments had been used and the analysis is conducted on the full sample period from 24th February 2020 to 25th March 2021.

The results show that new cases have a greater impact on investor sentiment compared to daily announcements of new deaths related to COVID-19. In addition to revealing a significant impact of new COVID-19 new cases and new death announcements on a daily basis on investor sentiment over the short- and long-term, this paper also highlights the nonlinearity and asymmetry of this relationship in the short and long run. Investors' sentiments are more affected by negative news regarding Covid 19 than positive news.

Financial markets have been severely affected by COVID-19 pandemic. This study is the first to measure the extent of reaction of investors to positive and negative announcements of COVID-19. Interestingly, this study examines the asymmetric effect of daily announcements on new cases and new deaths by COVID-19 on investor sentiments and derive many implications for portfolio managers.