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This paper analyses whether jersey sponsorship has an effect on team performance at FIFA World Cup matches, taking team qualities into account. Team qualities are measured by the Elo-ratings of national soccer teams. We measure the performance of sponsors by comparing the Elo-ratings at the start and the end of World Cup tournaments. The Elo-ratings are used to calculate the expected probabilities of a win during knockout matches and to compare them with the actual outcomes. The results show that in the knockout stages of the World Cup tournaments, national teams sponsored by Adidas perform significantly better than expected, while teams sponsored by other companies, such as Puma or Nike, perform worse. The average advantage per knockout match for the Adidas teams is to raise the probability of winning by 10 percentage points.

The purpose of this paper is to review studies focusing on the magnitude of money laundering and their effects on a country’s economy. The relevant concepts are identified on the basis of discussions in the literature by prominent scholars and policy makers. There are three main objectives in this review: first, to discuss the effects of money laundering on a country’s macro-economy; second, to seek measurements from other scholars; and finally, to seek previous findings about the magnitude and the flows of money laundering.

In the first part, this paper outlines the effects of money laundering on macroeconomic conditions of a country, and then the second part reviews the literature that measures the magnitude of money laundering from an economic perspective.

Money laundering affects a country’s economy by increasing shadow economy and criminal activities, illicit flows and impeding tax collection. To minimise these negative effects, it is necessary to quantify the magnitude of money laundering relative to economic conditions to identify the most vulnerable aspects of money laundering in a country. Two approaches are used in this study: the first is the capital flight approach, as money laundering will cause flows of money between countries; the second is the economic approach for measuring money laundering through economic variables (e.g. tax revenue, underground economy and income generated by criminals) separately from tax evasion.

The paper offers new insights for the measurement of money laundering, especially for developing countries. Most methods in quantifying money laundering have focused on developed countries, which are less applicable to developing countries.

The purpose of this paper is to interrogate if the legal status of a cannabis affects money laundering activity. The legal status of cannabis continues to evolve globally; at the same time, its market remains enormous. Much of this market represents dirty money from criminal acts, which often requires laundering. In the context of changing cannabis regulations, legislation, and policies, the authors propose the possible implications such changes may have on the extent of money laundering.

This paper proposes the implications of the evolution of cannabis regulations on money laundering activities, using the theoretical underpinning of rational choice. Using Australia as a replicable critical case study, the paper, using the Walker gravity model and using United Nations Office on Drugs and Crime-reported prices of cannabis from 2003 to 2017 and Australian Criminal Intelligence Commission reports empirically validates the effects of cannabis regulations on the proceeds available for laundering.

This study finds support for the argument that prohibitive measures toward cannabis use contribute to increases in the need to launder generated proceeds.

The findings can be replicated in other countries and may contribute to novel propositions within the debate on the legalization of cannabis use, which has, thus, far primarily focused on the areas of health, crime, taxation and education.

To the best of the authors’ knowledge, no study has yet attempted to provide an economic analysis of the effects of cannabis policy changes on money laundering.

This paper aims to determine the preferable destinations of money laundered from Pakistan by using the Walker’s Gravity Model and to estimate the amount of money laundered through 156 countries. The research aims to facilitate policymakers and regulators to provide more efficient guidelines to counter the problem of money laundering.

This study uses a descriptive and quantitative approach. This study uses the Walker’s Gravity Model updated by Unger et al. (2006) to measure money laundering in Pakistan; Walker’s Gravity Model was first developed by John Walker in 1994.

The results indicate that Pakistani money launderers preferred countries having large financial sectors and political stability to hide their illegal money. In addition, the study estimates the amount of money laundered and shows that Pakistan has lost bulk of funds.

The major limitation is the non-availability of reliable data as the activity is hidden. Reliable data is either not available officially or scattered. Available data only reflect aspects that are reported. Non-availability of statistics for all years and countries resulted in the omission of some countries.

The study helps legislators and policymakers, including the Ministry of Finance, State Bank of Pakistan, Securities and Exchange Commission Pakistan, and other regulators, including law enforcement agencies and financial institutions, in formulating effective policies, regulations and internal control.

The study helps to identify the need of estimating the amount of money laundered to fight the problem effectively. Very few efforts have made to determine the size and the amount of money laundered, and this is the first study to determine the amount of money flowing out of Pakistan with the purpose of laundering.