Corruption has become endemic in many African countries and is difficult to eradicate completely; therefore, reducing corruption to a tolerable level that will not deter foreign investors must be the aspiration of all political leaders and stakeholders. This study tries to identify the level of corruption that is tolerable to foreign investors, which is referred to as the Tolerable Level of Corruption for Investment (TLCI). The study proposes that below the TLCI, corruption plays the role of “sand in the wheels of commerce” and thus has a negative impact on FDI inflows, but above the TLCI, corruption functions to “grease the wheels” and has a positive impact on FDI inflows. The study is based on secondary data collected from the World Bank World Development Indicators. Using a dynamic panel data estimation technique while controlling for other variables, the estimated TLCI in Africa is -0.27 on the control of corruption scale, which ranges from approximately -2.5 (weak) to 2.5 (strong). Therefore, all African leaders and stakeholders, especially in countries that fall below the TLCI, should intensify their efforts in the fight against corruption to reduce corruption in their respective countries to at least the TLCI to attract foreign investors.

There has been a marked increase in the magnitude of Foreign Institutional Investments (FIIs) into India since the 1990s, resulting in increased forex reserves and liquidity and a higher-valued Indian capital market. However, such investment is more volatile than other types of flows, causing disruptive effects in the form of sudden stops (for example, the crash of the Indian stock market on January 21, 2008). This study empirically examines the dynamic relationship between FIIs and Indian stock market returns. It also analyses the effects of FIIs on Indian capital market returns, using data from January, 2004 through September, 2012. The analysis employs a Cross Correlation Function (CCF) approach, a Granger Causality Test and Vector Auto Regression after dividing the data into two parts: Pre Global financial crisis and Post Global financial crisis periods. The results of the CCF suggest bi-directional causality between FIIs and Nifty returns, whereas the Granger Causality Test and the VAR analysis suggest uni-directional causality running Nifty returns to FIIs.

In this paper, we examine the causal relationship between aid inflows and economic growth for Ghana during the period from 1970-2013, taking into account structural breaks. To better reflect causality, corruption and trade are included as control variables. To test for causality in the face of cointegration, a vector error correction model (VECM) is used in place of a vector autoregressive (VAR) model. This approach is complemented with Toda and Yamamoto’s method to indicate the causal direction. Our estimation results suggest GDP growth has one cointegrating vector relationship with corruption, EU aid inflows and trade in both the short and long runs. There is a long-run unidirectional causal relationship from EU aid inflows to GDP growth and a short-run unidirectional causal relationship from trade to GDP growth. Corruption (which is a governance issue) was ineffective in inducing GDP growth. The error correction terms are the source of causation in the long run. The results indeed confirm the popular conjecture that corruption in Ghana is endemic and stifles development. Therefore, the decision by the government to launch a national anti-corruption campaign in 2011, though long overdue, was justifiable. We urge all stakeholders to work together to deepen good governance to promote sustainable growth and serve as inducement for continued aid inflows from multilateral donors to sustain efforts at achieving the national development thrust of poverty reduction and sustainable development in Ghana.

In this paper, we derive a small textbook New Keynesian DSGE model to evaluate Polish and Romanian business cycles during the 2003-2014 period. Given the similarities between the two economies, we use an identical calibration procedure for certain coefficients and marginal prior distributions for the others, rendering the resulting cross-country differences as primarily data-driven. The estimated structural coefficients for the two countries have comparable values, implying similar qualitative macroeconomic transmission mechanisms. However, the Romanian shocks display much more variability, and the impulse response functions have similar shapes but deeper trajectories. The model-simulated theoretical moments for the output growth, the inflation rate and the nominal interest rate (means, standard deviations and cross-correlations) are close to their actual data counterparts, demonstrating the models’ ability to match and replicate statistical properties of the observed variables. Shock decompositions of the output and the inflation rate revealed the driving forces of the business cycles; demand shocks explain much of the GDP growth dynamics (persistent positive contributions before the crisis and negative thereafter), whereas prices were also driven by supply and monetary policy shocks, the latter being more important for Poland.

The aim of this paper is to investigate the degree of susceptibility to behavioral biases (the certainty effect, the sunk cost fallacy, and mental accounting) among people of various levels of expertise in market investments and to determine whether this susceptibility is correlated with certain personality traits (impulsivity, venturesomeness, and empathy). The study included 200 participants: 100 retail investors who regularly invest in the Warsaw Stock Exchange and 100 students of the Warsaw School of Economics who are casually involved in investing. In this study, employing a survey methodology, we conducted a laboratory experiment that allowed us to isolate behavioral biases and personality traits and measure their influence on investors’ decision-making processes. The participants filled out questionnaires containing two parts: 1) three situational exercises, which assessed susceptibility to behavioral biases, and 2) the Impulsivity, Venturesomeness, Empathy Questionnaire (IVE) Questionnaire which measures three personality traits (impulsivity, venturesomeness, and empathy). Statistical analyses demonstrated that susceptibility to behavioral biases depends on the level of expertise in market investing such that expertise increases susceptibility to behavioral biases. Some personality traits influenced the participants’ likelihood of displaying these biases.

For many years, the air travel market has been the most regulated sector of the economy. Within the last few decades, it has undergone profound change, which is largely a consequence of changes in the law. Another factor that exerted influence on the market was the popularization of new information and communication technologies that affected the interaction between service providers and clients. Due to the application of modern technologies, it is easier for tradesmen to implement pricing policies to maximize profits or minimize losses. In turn, customers acquired a tool for comparing prices, which aids them in selecting the most advantageous offer from their point of view. This study aims to provide an answer to the following questions: how does flight duration affect the price dispersion of airline tickets and does price dispersion increase as the date of departure approaches. To answer these questions, airline ticket prices for flights on the route: Warsaw-London-Warsaw and the route: Warsaw-New York-Warsaw were observed between August 14 and November 14, 2014. Price dispersion increased on both routes as the date of departure approached. Analysis of price variation over time has revealed that longer flights (WAW-ZYP-WAW vs WAW-LHR-WAW) were less dispersed in terms of prices in the period under analysis.

This paper describes and evaluates “shadow” sovereign credit ratings, which represent the credit ratings of countries that are not rated by credit rating agencies. Credit ratings represent the creditworthiness of companies or governments. They are important in attracting foreign capital. Countries without credit ratings can face greater difficulties than countries with low credit ratings, for example paying a higher price for capital. This paper has two objectives. The primary objective of this paper was to estimate a rating prediction model to the assess credit ratings of countries that are not yet rated. Large numbers of potential determinants were tested, and nine variables were selected that play a key role in assessing credit ratings. According to the chosen determinants, a highly precise model was calculated (80% of the estimated ratings were identical to the corresponding actual ratings or only one notch different). The purpose of this analysis was to estimate credit ratings for a sample of 31 unrated countries. The results are statistically significant and explained in detail. The second objective of this paper was to demonstrate that countries that are not ranked would not necessarily receive the lowest rating, and the results supported that hypothesis.