Working Papers

The WNE Working Papers series has been published by the Faculty of Economic Sciences at the University of Warsaw since 2008.

The WNE Working Papers series provides a fast, open channel for disseminating research conducted at the Faculty of Economic Sciences, University of Warsaw. The papers hosted here are working versions (pre-prints) and may evolve as authors refine their analyses, incorporate feedback, or progress through formal peer-review. What you read is the current version released by the authors, timestamped and assigned DOI/ISSN identifiers to ensure precise citation and version tracking. Copyright remains with the authors, who may, at any time, upload a revised file or add a note directing readers to a later, peer-reviewed publication.

The Working Papers series accepts articles by research employees of the Faculty and publications from conferences organised at the Faculty of Economic Sciences at the University of Warsaw. Articles should be original research papers which have not been previously published, on the subject of economics.

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(1) the main text without the title of the article and the authors (DOC/DOCX file) and

(2) the title page including: the title of the paper, the authors and their affiliation (DOC/DOCX file).

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Number of Results 4

WP(16/2026)510. Two Blind Walls: A Transferable Pedagogical Design for Art-Market Literacy Across Art and Economics Education

Authors: Kopczewski Tomasz, Laskowska-Lisicka Justyna, Lisicki Jan, Okhrimenko Kostiantyn, Potocki Tomasz
This article presents an ongoing pedagogical project at the intersection of economics and art education. It starts from a double blind wall: economics rarely uses the art market as a eaching laboratory, while art education often protects aesthetic ju…

WP510. Two Blind Walls: A Transferable Pedagogical Design for Art-Market Literacy Across Art and Economics Education

This article presents an ongoing pedagogical project at the intersection of economics and art education. It starts from a double blind wall: economics rarely uses the art market as a eaching laboratory, while art education often protects aesthetic judgement from market reductionism. We propose a transferable protocol combining diagnostic questions, valuation tasks, anchoring and signalling treatments, public-art perception probes, and dashboard feedback. Its first implementation uses Wojciech Fangor in Warsaw. The aim is not representative measurement, but a replicable design through which students observe how attention, information, narrative, and market signals shape the encounter with art.


DOI: https://doi.org/10.33138/2957-0506.2026.16.510
Kopczewski Tomasz, Laskowska-Lisicka Justyna, Lisicki Jan, Okhrimenko Kostiantyn, Potocki Tomasz
art valuation economics education art education anchoring signalling asymmetric information pedagogical narrative laboratory Know Thyself Wojciech Fangor replication

WP(14/2026)508. Know Thyself: A Methodological Manifesto for Teaching Microeconomics Through Epistemic Provocation

Authors: Kopczewski Tomasz
This paper documents and formalises the Know Thyself method, a teaching approach developed through more than thirty years of university teaching practice. Its starting diagnosis is that students often learn economic models without experiencing the as…

WP508. Know Thyself: A Methodological Manifesto for Teaching Microeconomics Through Epistemic Provocation

This paper documents and formalises the Know Thyself method, a teaching approach developed through more than thirty years of university teaching practice. Its starting diagnosis is that students often learn economic models without experiencing the assumptions that make those models necessary. The method reverses the usual sequence: experience before theory, data as a mirror before abstraction, and questions before answers. Its empirical core is not the experiment narrowly understood, but ad hoc research: classroom experiments, surveys, simulations, valuation tasks, and replication laboratories that make learners’ own assumptions visible. Four case studies — expected value, ergodicity, market equilibrium, and the rationality of altruism — illustrate how the method converts declarative knowledge into reflective practice. Artificial intelligence gives the method scale by lowering the cost of surveys, dashboards, simulations, and replication protocols. The paper’s practical conclusion is simple: change the order. Ask first. Teach later.


DOI: https://doi.org/10.33138/2957-0506.2026.14.508
Kopczewski Tomasz
economics education epistemic provocation experiential learning replication expected value ergodicity market equilibrium AI in education science curiosity

WP(18/2021)366. Enhanced Index Replication Based on Smart Beta and Tail-Risk Asset Allocation

Authors: Korzeń Kamil, Ślepaczuk Robert
The following research paper’s main goal is to create an algorithmically managed ETF, which tracks the SPX index and provides a Smart Beta exposure. Authors apply the following simple index replication methods: partial correlation, non-negative…

WP366. Enhanced Index Replication Based on Smart Beta and Tail-Risk Asset Allocation

The following research paper’s main goal is to create an algorithmically managed ETF, which tracks the SPX index and provides a Smart Beta exposure. Authors apply the following simple index replication methods: partial correlation, non-negative least squares, beta coefficient, and dynamic time warping. First, authors are trying to reverse engineer the Index Tracking process in an automated and fair manner - taking into account e.g. transaction costs. Additionally, authors apply a constraint to the total number of assets used in the replication process, which is limited to the certain N. Then, authors develop a Smart Beta framework based on limiting the negative tail-risk. The positive excess return (alpha) is captured and used to compensate for the underperformance of the replicated Index or paid in a form of a dividend. Moreover, with the enhancement methods applied (Kurtosis/Skewness and Excess Return Cushion (ERC) enhancements), the authors’ main goal is to keep the Tracking Error (TE) on a fixed level, although with a significant overweight on the Positive TE and underweight on the Negative TE. In the research paper, the data from 04-Jan-2016 to 31-Dec-2020 is used as the training window, while the first quarter of the year 2021 (Q1 2021) is used as an out-of-sample and out-of-time testing period. Additionally, the authors measure the replicated Index’s performance compared to the SPY, VOO, and IVV ETFs. Authors find a piece of empirical evidence that it is possible to track the SPX Index within the limits of 4-5% TE with the limited number of assets. Moreover, after the implementation of alpha accumulation, the authors outperform the benchmark ETFs in terms of minimizing the TE but did not succeed in providing statistically significant returns better than the SPX Index.


Korzeń Kamil, Ślepaczuk Robert
exchange-traded funds enhanced index replication methods smart beta asset allocation partial correlation non-negative least squares dynamic time warping

WP(4/2013)89. Relative risk aversion and power-law distribution of macroeconomic disasters

Authors: Brzeziński Michał
The coefficient of relative risk aversion (CRRA) is notoriously difficult to estimate. Recently, Barro and Jin (On the size distribution of macroeconomic disasters, Econometrica 2011; 79(3): 434-455) have come up with a new estimation approach that f…

WP89. Relative risk aversion and power-law distribution of macroeconomic disasters

The coefficient of relative risk aversion (CRRA) is notoriously difficult to estimate. Recently, Barro and Jin (On the size distribution of macroeconomic disasters, Econometrica 2011; 79(3): 434-455) have come up with a new estimation approach that fits a power-law model to the tail of distribution of macroeconomic disasters. We show that their results can be successfully replicated using a more refined power-law fitting methodology and a more comprehensive data set.


Brzeziński Michał
coefficient of relative risk aversion power-law modelling macroeconomic disasters replication robust statistics
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