Master Theses Topics

Master Theses Topics

Here is a list of possible topics to write a Master thesis under the supervision of NoCeT’s researchers:

  • Dividend taxation, Cum-Cum Trading and Ex-Dividend Pricing

    Dividend taxation, Cum-Cum Trading and Ex-Dividend Pricing

    A common tax planning strategy among investors is to sell their stocks the day before dividends are due, and buy them back on the ex-dividend day. This strategy, known as cum-cum trading, allows investors to avoid paying dividend taxes. The Norwegian tax authorities are considering to implement policies that make cum-cum trading less attractive in order to generate more dividend tax revenue.

    Your task will be to see how cum-cum trading relates to taxation and other policy variables, using international stock market data. Questions that you could answer in this topic are: Do stock market experience excess trade around the dividend day? Does excess trade relate to the dividend tax rate? Do stock prices reflect the level of the dividend tax? Are policies aimed at combating cum-cum trading effective in other countries?

    Cum-cum trading strategies have been detected in Europe. Are they present in the Asian and South-American market? Are these trades a global problem that contributes to rising inequality?

    Supervisor: Floris Zoutman and Evelina Gavrilova-Zoutman

  • Dividend taxation, abusive stock swap and loan transactions

    Dividend taxation, abusive stock swap and loan transactions

    A tax strategy among investors is to recast a dividend payment as a swap payment in order to take advantage of favoured tax treatment given to swap agreements involving non-US persons in the US. US stock dividents paid to non-US persons are subject to the dividend tax, whereas “dividend equivalents” paid to non-US persons as part of a swap agreement are not subject to any US tax.

    Since a 2009 Senate hearing identified the tax evasion nature of these transactions, there has been little research on the topic. These transactions are likely the origin from which cum fraud schemes have arisen. Since 2009 the US has had reforms in their dividend tax and in the legislation surrounding the claiming of these dividend equivalents. What is the impact of these reforms on stock lending of US stocks?

    Supervisor: Floris Zoutman and Evelina Gavrilova-Zoutman

  • How did the US Tax Bill affect M&As?

    How did the US Tax Bill affect M&As?

    The 2017 TCJA may significantly change the pattern of corporate M&As. For instance, it has lifted the original use requirement for immediate depreciation of acquired assets. That makes it much more attractive to structure deals as asset purchases rather than stock acquisitions.

    Furthermore, net operating losses before and after January 1, 2018 are treated differently. An empirical analysis could use either Zephyr or SDC Platinum to explore early signs of these changes. 

    Supervisor: Maximilian Todtenhaupt.

  • Common ownership and tax avoidance

    Common ownership and tax avoidance

    Corporate tax planning is high on the agenda of both tax practitioners and policy makers. While some firms certainly try to avoid paying taxes, we know very little about how firms learn about different tax avoidance mechanisms. An important channel may be via common owners. Do firms engage in similar levels of tax avoidance if they are owned by the same investors? This project will investigate this question using balance sheet information and ownership details of large corporations.

    Supervisor: Maximilian Todtenhaupt.

  • Inventors and tax havens

    Inventors and tax havens

    Inventors are an important source of innovation for any country. At the same time they are highly mobile and respond to tax incentives. Furthermore, the intellectual property they create (e.g. patents) can be used shift income to tax havens. How many inventors are involved in such tax avoidance behavior? This project will assess the importance of inventors in tax havens by combining data on international inventors with the Panama papers which have recently become available.

    Supervisor: Maximilian Todtenhaupt.

  • The Tax Haven Call

    The Tax Haven Call

    In political and institutional economy we think of countries as having extractive and inclusive institutions. Institutions are loosely defined as informal norms of behaviour. In an influential (but controversial) paper by Acemoglu et al. (2001) the type of institutions are shown to impact economic development. However, it is unclear whether what aspect of these informal norms have influenced countries like the Netherlands, Ireland and Bermuda to become tax havens?

    Dharmapala and Hines (2009) have found that governance is an important factor that separates tax havens from non-tax havens. Better-governed small countries are more likely to be successful tax havens than badly governed small countries. Governance and institutions are closely related, but the link is not explored in this article.

    In addition, the list of tax havens has expanded since 2009 and now we have continuous measures of secrecy and tax haven status, which can give better identification in re-examining the question: What makes a tax haven?

    Starting point: Dharmapala, D. and Hines Jr, J.R., 2009. Which countries become tax havens?. Journal of Public Economics, 93(9-10), pp.1058-1068.

    Supervisor: Evelina Gavrilova-Zoutman.

  • Wealth Taxation in Norway

    Wealth Taxation in Norway

    The wealth tax is one of the most controversial aspects of the Norwegian tax system. Detractors believe that the wealth tax hurts economic growth by disincentivizing entrepreneurial activity and risk taking, and taking away a source of liquidity for business owners. Proponents argue that the wealth tax is a great instrument to reduce inequality.

    In this project you will use data on Norwegian tax payers to evaluate the arguments of the detractors. Specifically, the goal is to understand i.) whether the arguments are valid empirically, ii.) how large the concerns are quantitatively. Specific research questions could be i.) does the wealth tax discourage individuals/business owners from taking risk, ii.) does the wealth tax reduce liquidity for small businesses, iii.) does the wealth tax reduce innovation or iv). does the wealth tax discourage savings. The answer of each of these four questions is of great practical relevance to policy makers that have to make a trade-off between the efficiency cost and the equity gain associated with the wealth tax.

    Data: Individual tax return data

    Literature:

    • Berzins, Janis, Øyvind Bøhren and Bodan Stacesu (2019). Illiquid Shareholders and real firm effects: the personal wealth tax and financial constraints. Working Paper BI.
    • Akcigit, U., Grigsby, J., Nicholas, T., & Stantcheva, S. (2018). Taxation and Innovation in the 20th Century. NBER Working Paper.

    Supervisor: Floris Zoutman

  • Literature review on the effects school facilities have on student and teacher outcomes

    Literature review on the effects school facilities have on student and teacher outcomes

    Supervisor: Arnt-Ove Hopland

  • Correcting witness reports through Machine Learning

    Correcting witness reports through Machine Learning

    It is well known that witness accounts on crime are often unreliable. The effects of stress or poor light on the victim can create a skewed perception of how the perpetrator looked. This, coupled with an unconscious discriminatory bias, leads to the victim reporting that the perpetrator was unknown or from the black racial minority. Often the witness report is based on an estimate – e.g. “ the perpetrator looked black, around 25 years”.

    Comparing actual arrests to reports, we can try to put a number on the amount of witness error. By training a machine learning model on a subsample, we can try to predict the gender, race and age of unobserved criminals. This can impact the computation of statistics on black/white, male/female and young/old crime gaps. What if blacks are actually responsible for a very small fraction of crimes? What if females are responsible for more crimes? This could lead us to rethink current racial profiling strategies in crime detection.

    Data: National Incident Based Reporting System, US

    Starting point: Imbens, G.W. and Lemieux, T., 2008. Regression discontinuity designs: A guide to practice. Journal of econometrics, 142(2), pp.615-635.
    Fryer Jr, R.G., 2016. An empirical analysis of racial differences in police use of force (No. w22399). National Bureau of Economic Research

    Supervisor: Evelina Gavrilova-Zoutman.

  • When the police is cheating

    When the police is cheating

    Police agencies get funding based on the amount of crime in their jurisdiction. This gives them the incentive to manipulate crime statistics. This can mean that for e.g. aggravated assaults are downgraded to simple assaults, or simple crimes are elevated to felonies. The police can add drug charges, in order to appear as being successful against organized crime. All this behaviour is hidden behind crime statistics.

    Through a combination of machine learning and local linear estimates we can try to determine how police agencies cheat. With the use of election outcomes as instrumental variables, we can try to find a causal effect. The findings of this project could have a strong impact on how crime figures are viewed. With corrected crime figures we can replicate previous analyses and determine whether well known policies actually impact crime or not.

    A separate question would be how do policing incentives influence police cheating in reporting statistics? E.g. federal grants that increase the police labor force vs. militarization donations that increase police capital. Both of these types of policies expect a crime decrease as a result and this is what we find in the literature, but is this finding warranted? Do we observe more crime downgrading after the policies than before?

    Data: National Incident Based Reporting System, US

    Supervisor: Evelina Gavrilova-Zoutman.

  • Smuggling and money laundering

    Smuggling and money laundering

    It is well known that laundered money change their form from cash to other goods such as jewellery, antique objects or other collectible items. Do we observe abnormal flows of such good to/from tax havens? Do these flows shift with the signing of information exchange agreements between two countries?

    Methods: Regressions, machine learning.

    Supervisor: Evelina Gavrilova-Zoutman.

  • Using Textual Analysis to identify whether there is a gender gap in financial white collar crime

    Using Textual Analysis to identify whether there is a gender gap in financial white collar crime

    There is very little systematic evidence on the gender gap in crime. In particular, it is difficult to quantify it for financial white collar crime, as they do not find their way into police statistics and as there is little female presence on the top levels of companies.

    In this project, we can use textual analysis tools to collect data from the Securities and Exchange Commission (SEC) on insider trading and other frauds. We can match the name of the defendant to a gender, and quantify what is the difference between males and females.

    Then, we can correlate the gap, as well as the fraud itself, to past financial statements of involved companies in terms of gender representation in the board of the company and other indicators of company culture. Finally, we can compare the gap to other measures of female participation in the boardroom and determine whether white collar females seem more or less likely to commit crimes than white collar males. We can provide a partial answer to the question: Are companies going to become more responsible (do less criminal rule-breaking) if there are more females on the board?

    Methods: Textual analysis, web crawling, R

    Supervisor: Evelina Gavrilova-Zoutman.

  • Detecting Corruption in the Oil-For-Food Program

    Detecting Corruption in the Oil-For-Food Program

    The Oil for Food Program (OFFP) was a relief effort orchestrated by the United Nations to help the people of Iraq after the Gulf War. It lasted from 1995 to 2003. Leaks from classified reports reveal that there has been rampant corruption, from the bank that handled the Iraq escrow account, to the trucking company that was supposed to handle the logistics of food transport. Even the then UN General Secretary Kofi Annan has been implicated in this corruption scandal. By looking at important events that influence the survival of the OFFP and stock prices of companies bidding for contracts, by virtue of insider trading, we can find an indirect proof for corruption.

    The methodology for this thesis is the same as in DellaVigna, S. and La Ferrara, E., 2010. Detecting illegal arms trade. American Economic Journal: Economic Policy, 2(4), pp.26-57.

    Supervisor: Evelina Gavrilova-Zoutman.

  • How do schools adapt to their physical infrastructure?

    How do schools adapt to their physical infrastructure?

    Does it matter for teaching practice whether the school is new, old, well maintained, run down, a permanent building or temporary modules ("barracks")?

    Supervisor: Arnt-Ove Hopland

  • The disintegration of institutions and the smuggling of antiquities

    The disintegration of institutions and the smuggling of antiquities

    Countries that enter a period of internal strife such as a civil war experience a disintegration of institutions. When factions are battling for control, who would protect the property rights of victims? This creates an excellent climate to export antique objects with little oversight. Can we link export flows to civil war status? Can we flip this, and use flows of antiquities to flag countries where rule of law is disintegrating?

    Starting Point: Fisman, R., & Wei, S. J. (2009). The smuggling of art, and the art of smuggling: Uncovering the illicit trade in cultural property and antiques. American Economic Journal: Applied Economics, 1(3), 82-96.

    Supervisor: Evelina Gavrilova-Zoutman