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Hitoshi Tsujiyama, Ph.D.

Goethe University Frankfurt, Germany

Authors: Jonathan Heathcote and Hitoshi Tsujiyama

Abstract: What is the optimal shape of the income tax schedule? This paper compares the optimal (Mirrlees) tax and transfer policy to various simple parametric (Ramsey) alternatives. The environment features distinct roles for public and private insurance. We explore a flexible class of social welfare functions, one special case of which captures the taste for redistribution reflected in the current tax system. Optimal marginal tax rates increase in income in our baseline calibration to the United States, and the optimal tax schedule can be well approximated by a simple two parameter function. We show that the shape of the optimal schedule is sensitive to the amount of fiscal pressure the government faces to raise revenue. As fiscal pressure increases, the optimal schedule becomes first flatter, and then U-shaped, reconciling various findings in the literature.

Keywords: Optimal income taxation; Mirrlees taxation; Ramsey taxation; Tax progressivity; Flat tax; Private insurance; Social welfare functions

Full Text:  “Optimal Income Taxation: Mirrlees Meets Ramsey”

Still not using Excel effectively? Join our short course where in four lessons you will learn the basics of Excel and master the tools necessary for its efficient usage.

Thursdays, 18:30-21:00
Starting date: 20 October, 2016
Finishing date: 10 November, 2016

About the facilitator: Petar Buha
Petar is an MA in Applied Economics graduate from 2015 and currently works as an Analyst at Accenture. He is interested in analysis, innovation, and IT; it was due to these interests that he worked at Social Bakers prior to his studies and why he joined Accenture after graduation. He used Excel considerably during his studies, especially on the practical Financial Modeling course, and he also uses it extensively in his current role, where he has developed complex models for an insurance provider's regulatory reporting and is administering reporting capabilities for a data migration stream, analyzing and forecasting the productivity of developers and their deliverables. In his free time, Petar likes to do kick-boxing, watch sci-fi movies and actively socialize.

Curriculum

Lecture 1:

• Basic information
• Keyboard shortcuts
• Formatting (& conditional, pt.1)
• Visuals, help (comments, cell borders, ...)
• Column/cell hide, size, group, merge cells
• Introduction to formulas (basic math, SUM, COUNT, AVERAGE)
• IFs, AND, OR, NOT

Lecture 2:

• Conditional formatting, pt. 2
• Anchoring cells
• SUMIF, COUNTIF
• Freeze panes, rows & columns
• Filters
• IFERROR, ISBLANK
• INDEX, MATCH, VLOOKUP

Lecture 3:

• SUMPRODUCT, SUMIFS
• DATE
• Text functions
• RAND, RANDBETWEEN
• Calculation options
• Pivot tables

Lecture 4:

• Data validation (esp. lists)
• Text to columns
• OFFSET, INDIRECT
• (Dynamic) named ranges
• Paste special
• Other formats
• Formula auditing (F9, tracing)
• Etiquette in Excel

Participants who attend at least 75% of the sessions will obtain a Certificate of Attendance issued by CERGE-EI.

Participants need to bring their own laptops with  Excel 2007 or later installed, ideally 2013 or 2016.

Course curriculum 

Would you like to learn to use R to develop dashboards like these? 
https://www.rstudio.com/products/shiny/shiny-user-showcase/
https://mbienz.shinyapps.io/tourism_dashboard_prod/
https://gallery.shinyapps.io/086-bus-dashboard/

If yes, this is the right course for you. If you already have some knowledge of R, it is an advantage. However, you are welcome to join without any prior knowledge, basics of R will be covered during the first session and with some additional homework, you should be able to catch up. Attending this course will be very useful if you want to join our Datathon, as you can utilize what you learn in the course immediately!

Thursdays, 19:00-20:30
Starting date: 20 October, 2016
Finishing date: 10 November, 2016

About the facilitator: Juan Pablo Maldonado López
Pablo earned his PhD in Applied Mathematics at Université Paris VI - Pierre at Marie Curie. He was an adjunct professor at Universidad Michoacana de San Nicolás de Hidalgo and Instituto Tecnológico de Estudios Superiores de Monterrey. For the past two years he has worked as a Data Scientist in the Czech Republic for O2 Czech Republic and PricewaterhouseCoopers.  

Curriculum

Session 1: R and dplyr (data manipulation and basic operations)

Session 2: Introduction to Shiny and ggplot

Session 3: Acquiring data from external sources

Session 4: Leaflet package (visualizing maps, geographical data) 

Dana Sisak, Ph.D.

Erasmus University Rotterdam, The Netherlands

Authors: Philipp Denter, John Morgan, and Dana Sisak

Abstract: We study a situation where a newbie with potentially unknown talent enters into competition with an established competitor of known talent. Assuming the newbie is aware of his talent, we first study his incentive to show off and reveal his type through costly signaling to his competitor. We find that whether he reveals his type in equilibrium, depends on his as well as the incumbent's talent. When the incumbent is relatively weak, strong newbie types show off in equilibrium. Otherwise, showing off does not occur. We then study whether the incumbent is hurt by the newbie's showing off behavior. Interestingly, we find that both competitors benefit from showing off if it happens, to the detriment of the principal. Thus, a principal interested in maximizing aggregate effort prefers a firm culture where showing off is not possible. We also show that this result may be reversed when the newbie exhibits overconfidence.

Full Text:  WILL BE AVAILABLE LATER