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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Number of Results 31

WP(31/2025)494. Hybrid or Hands On? Students’ Economic Preferences over Study Design and Labor Market Payoffs

Authors: Zawadzki Wojciech, Czajkowski Mikołaj, Skrzypek Katarzyna, Jędrzejewska Matylda, Żmijewska Maja, Ryłow Jakub, Gadowska-dos Santos Dominika, Grotkowska Gabriela, Różycka Agnieszka, Filip Arkadiusz, Gruszczynski Marcin, Kałamucka Agata, Kowalski Tadeusz, Kozioł Waldemar, Olender-Skorek Magdalena, Opolski Krzysztof, Saczuk Katarzyna, Szczurek Mateusz, Sztandar-Sztanderska Urszula, Wańczyk Kacper, Wiśniewska Aleksandra, Zabarina Kateryna, Żoch Piotr
We study how university students trade off the design and demands of study against expected labor market returns. We conducted a Discrete Choice Experiment (DCE) with students of the Economics Department at the University of Warsaw. Choice alternativ…

WP494. Hybrid or Hands On? Students’ Economic Preferences over Study Design and Labor Market Payoffs

We study how university students trade off the design and demands of study against expected labor market returns. We conducted a Discrete Choice Experiment (DCE) with students of the Economics Department at the University of Warsaw. Choice alternatives varied the share of in person teaching, weekly class hours, weekly preparation time, language mix (Polish vs. English), net monthly study cost (tuition minus stipends), and expected net salary after graduation. The DCE was embedded in a broader survey measuring study experience, time use, work during studies, scheduling preferences, and perceptions of quality and reputation. The instrument and framings follow state of the art DCE guidance and are publicly documentable. Using multinomial logit and mixed logit models, we estimate compensating differentials students require to accept (i) more online teaching, (ii) more weekly effort (classes/prep), or (iii) English medium instruction in Polish language curricula. The results show large, precise utility gains from higher expected salary, disutility from higher weekly preparation time, and strong (non linear) preferences over delivery mode and language. We then simulate policy scenarios (e.g., introducing 50% online, adjusting effort) and quantify the cost equivalent or salary equivalent levers needed to maintain program attractiveness. We position our results in the international literature on DCEs in higher education and discuss external validity with respect to a large national DCE that emphasized earnings over prestige. We conclude with program design implications for universities worldwide navigating hybridization, workload calibration, and language policy in light of students’ revealed economic preferences.


DOI: https://doi.org/10.33138/2957-0506.2025.31.494
Zawadzki Wojciech, Czajkowski Mikołaj, Skrzypek Katarzyna, Jędrzejewska Matylda, Żmijewska Maja, Ryłow Jakub, Gadowska-dos Santos Dominika, Grotkowska Gabriela, Różycka Agnieszka, Filip Arkadiusz, Gruszczynski Marcin, Kałamucka Agata, Kowalski Tadeusz, Kozioł Waldemar, Olender-Skorek Magdalena, Opolski Krzysztof, Saczuk Katarzyna, Szczurek Mateusz, Sztandar-Sztanderska Urszula, Wańczyk Kacper, Wiśniewska Aleksandra, Zabarina Kateryna, Żoch Piotr
discrete choice experiment higher education hybrid/online vs. in-person language of instruction student workload willingness-to-pay

WP(30/2025)493. Is smooth Energiewende possible? Improving the performance of climate policies in Germany by optimizing the risk of electricity delivery

Authors: Bandurski Jakub, Hałatek Eliza, Łaziński Adam, Künstler Michał
The Energiewende is a deep-rooted notion in the German economy. The main goal is to achieve climate neutrality by transitioning to renewable energy sources. However, the feasibility of this transition is partially hindered by power grid congestion, w…

WP493. Is smooth Energiewende possible? Improving the performance of climate policies in Germany by optimizing the risk of electricity delivery

The Energiewende is a deep-rooted notion in the German economy. The main goal is to achieve climate neutrality by transitioning to renewable energy sources. However, the feasibility of this transition is partially hindered by power grid congestion, which undermines system efficiency and leads to both economic and environmental costs. We address this issue by making a prediction of the likelihood of congestion occurrence within the German TenneT DE electricity network in the years 2020-2023. We propose a twofold approach offering a combination of advanced econometric models and state-of-the-art machine learning methods. We offer separate solutions for up congestion when additional energy needs to be pushed to the network as well as down congestion when energy needs to be pulled away from the network. Analyzing the CatBoost with XAI, we identify factors that play a significant role in driving redispatch events within the German electricity network.


DOI: https://doi.org/10.33138/2957-0506.2025.30.493
Bandurski Jakub, Hałatek Eliza, Łaziński Adam, Künstler Michał
energiewende econometrics machine learning climate policy catboost

WP(29/2025)492. Childbearing in the Knowledge-Based Society: Job-Related Learning Demands and the Transition to Parenthood in Germany

Authors: Luo Chen, Jarosz Ewa, Matysiak Anna
This study investigates the relationship between learning demands at work and the transition to parenthood in Germany. As a consequence of technological progress and intensifying global competition, workplace learning is no longer an optional path to…

WP492. Childbearing in the Knowledge-Based Society: Job-Related Learning Demands and the Transition to Parenthood in Germany

This study investigates the relationship between learning demands at work and the transition to parenthood in Germany. As a consequence of technological progress and intensifying global competition, workplace learning is no longer an optional path to career advancement but has become an essential job demand. Consequently, it absorbs time and energy that could otherwise be devoted to family formation, prompting individuals to postpone childbearing or have fewer children. Yet, the fertility implications of this structural change have not been systematically examined. This study addresses this gap by analysing how job-related high learning demands relate to the transition to the first birth. The results indicate that individuals in jobs with high learning demands, both men and women, tend to delay the transition to the first birth. However, these delays do not appear to preclude them from becoming parents later, suggesting a postponement rather than a withdrawal from parenthood.


DOI: https://doi.org/10.33138/2957-0506.2025.29.492
Luo Chen, Jarosz Ewa, Matysiak Anna
fertility childbearing learning demands labour market transformation work-family conflict

WP(28/2025)491. Working-Time flexibility and Union Dissolutions: Evidence for couples in Germany

Authors: Kałamucka Agata, Matysiak Anna, Osiewalska Beata
Objective: This study examines the relationship between men's and women's working-time flexibility and relationship dissolutions (cohabitating and married couples) in Germany Background: Globalisation and technological advancements have popu…

WP491. Working-Time flexibility and Union Dissolutions: Evidence for couples in Germany

Objective: This study examines the relationship between men's and women's working-time flexibility and relationship dissolutions (cohabitating and married couples) in Germany
Background: Globalisation and technological advancements have popularised flexible working hours, necessitating a deeper understanding of their implications on family dynamics and relationship stability. Employee-oriented flexibility, which allows workers to adjust their schedules to meet family needs, generally supports work-family balance and reduces conflict, yet it can also blur the boundaries between work and personal life and may reduce family time. On the other hand, employer-oriented flexibility, characterised by unpredictable hours, can heighten marital strain and increase the risk of relationship dissolution.
Method: Using data from the German Socio-Economic Panel (SOEP), the final sample consists of 15,519 cohabiting and married couples, and the number of relationship dissolutions during the analysed time period is 1,463. The study employs event history analysis to explore the relationship between working-time flexibility and relationship dissolutions, differentiating by gender, parental status and the age of the youngest child. 
Results: Preliminary results indicated that employee-oriented flexibility of men tends to lower the risk of dissolution among couples with more than 2 children, especially when they are young, highlighting its benefits in facilitating family responsibilities. Any significant results on employer-oriented flexibility have not been found in comparison to fixed schedules.
Conclusion: Fathers’ more than mothers’ working-time flexibility relates to lowering the risk of relationship dissolutions, especially when children are young and in families with two or more kids, suggesting that men’s control over their schedules may facilitate greater involvement at home and alleviate care burdens on women.


DOI: https://doi.org/10.33138/2957-0506.2025.28.491
Kałamucka Agata, Matysiak Anna, Osiewalska Beata
working-time flexibility couples flexible hours dissolutions Germany

WP(27/2025)490. Employers’ Discrimination against Fathers and Mothers Taking Parental Leave: Evidence from a Choice Experiment

Authors: Cukrowska-Torzewska Ewa, Matysiak Anna, Kasperska Agnieszka, Kaufman Gayle
This study provides causal evidence on the hiring and pay penalties associated with taking parental leave of varying lengths. We investigate how deviations from prevailing social norms, in the form of non-standard leave-taking behavior by mothers and…

WP490. Employers’ Discrimination against Fathers and Mothers Taking Parental Leave: Evidence from a Choice Experiment

This study provides causal evidence on the hiring and pay penalties associated with taking parental leave of varying lengths. We investigate how deviations from prevailing social norms, in the form of non-standard leave-taking behavior by mothers and fathers, affect their employment outcomes. We also compare the parental leave penalties with those linked to unemployment to disentangle the determinants of these penalties and to identify the mechanisms through which they operate. To this end, we conducted a discrete choice experiment with 997 managers, who evaluated hypothetical job candidates differing in the length of employment interruptions due to parental leave. Using a conditional logit model, we find that both mothers and fathers face disadvantages in hiring and remuneration when taking longer parental leave. Notably, fathers are penalized for taking any parental leave, though the penalties are more severe for longer leave. These poorer employability prospects stem from managers perceiving such fathers as less available for work. Meanwhile, mothers receive hiring and pay bonuses for taking shorter leaves, stemming from employer perceptions of such mothers as more available, competent, and motivated.


DOI: https://doi.org/10.33138/2957-0506.2025.27.490
Cukrowska-Torzewska Ewa, Matysiak Anna, Kasperska Agnieszka, Kaufman Gayle
parental leave family policies employment wages gender norms ideal worker norms

WP(26/2025)489. How Effective are Energy Labels? Evidence from the 2021 EU Reform

Authors: Toker Doganoglu, Grzybowski Łukasz, Frank Verboven
Energy labels are often used to promote the adoption of more energy-efficient domestic appliances. This paper provides evidence on the impact of the 2021 revision of the EU energy labeling regulation using product-level sales data on refrigerators in…

WP489. How Effective are Energy Labels? Evidence from the 2021 EU Reform

Energy labels are often used to promote the adoption of more energy-efficient domestic appliances. This paper provides evidence on the impact of the 2021 revision of the EU energy labeling regulation using product-level sales data on refrigerators in four European countries (Belgium, France, Germany, and Poland). We first document substantial cross-country differences in sales-weighted energy consumption, reflecting differences in product portfolios and consumer preferences. Controlling for product characteristics, average energy consumption declines by between 3.3% in France and 4.2% in Belgium following the reform. We subsequently estimate a product-level demand model that incorporates energy labels in utility either directly or through their associated 15-year electricity costs. The results indicate that consumers undervalue future energy costs under both labeling regimes, although the degree of undervaluation declines under the new labels. Counterfactual simulations suggest that the labeling reform generated only modest energy efficiency gains. Larger gains could be achieved through alternative policies: stricter minimum standards (banning the least efficient appliances) or fiscal incentives (a feebate scheme subsidizing efficient appliances while taxing inefficient ones).


DOI: https://doi.org/10.33138/2957-0506.2025.26.489
Toker Doganoglu, Grzybowski Łukasz, Frank Verboven
Energy Efficiency EU Energy Label Nested Logit

WP(25/2025)488. Application of Deep Reinforcement Learning to At-the-Money S&P 500 Options Hedging

Authors: Bracha Zofia, Michańków Jakub, Sakowski Paweł
This paper explores the application of deep Q-learning to hedging at-the-money options on the S&P 500 index. We develop an agent based on the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, trained to simulate hedging decisions w…

WP488. Application of Deep Reinforcement Learning to At-the-Money S&P 500 Options Hedging

This paper explores the application of deep Q-learning to hedging at-the-money options on the S&P 500 index. We develop an agent based on the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, trained to simulate hedging decisions without making explicit model assumptions on price dynamics. The agent was trained on historical intraday prices of S&P 500 call options across years 2004 to 2024, using a single time series of six predictor variables: option price, underlying asset price, moneyness, time to maturity, realized volatility, and current hedge position. A walk-forward procedure was applied for training, which lead to nearly 17 years of out-of-sample evaluation. The performance of the deep reinforcement learning (DRL) agent is benchmarked against the Black–Scholes delta hedging strategy over the same time period. We assess both approaches using metrics such as annualized return, volatility, information ratio, and Sharpe ratio. To test models’ adaptability, we performed simulations across varying market conditions and added constraints such as transaction costs and risk-awareness penalties. Our results show that the DRL agent can outperform traditional hedging methods, particularly in volatile or high-cost environments, highlighting its robustness and flexibility in practical trading contexts. While the agent consistently outperforms delta hedging, its performance deteriorates when the risk-awareness parameter is higher. We also observed that the longer the time interval used for volatility estimation, the more stable the results.


DOI: https://doi.org/10.33138/2957-0506.2025.25.488
Bracha Zofia, Michańków Jakub, Sakowski Paweł
Deep learning Reinforcement learning Double Deep Q-netwoorks options market options hedging deep hedging

WP(24/2025)487. State Aid for Broadband and Crowding Out of Private Investment: Evidence from the French Market

Authors: Bourreau Marc, Grzybowski Łukasz, Muñoz-Acevedo Ángela
In this paper, we investigate the potential crowding out of private investment by public subsidies in the deployment of broadband fiber networks. We estimate a model of fiber entry using a rich dataset on fiber deployment for more than 34,000 municip…

WP487. State Aid for Broadband and Crowding Out of Private Investment: Evidence from the French Market

In this paper, we investigate the potential crowding out of private investment by public subsidies in the deployment of broadband fiber networks. We estimate a model of fiber entry using a rich dataset on fiber deployment for more than 34,000 municipalities in mainland France from 2014 to 2019. We then assess whether private investment would have occurred in subsidized municipalities in the absence of state aid. We find that in 36% of cases, public subsidies were allocated to municipalities where private entry would have occurred within three years. We estimate that about 902 million euros of the total 2,203 million euros in total subsidies disbursed by the end of 2019 may have crowded out private investment. However, we also show that the French broadband plan accelerated fiber coverage in subsidized municipalities in the early stages of deployment.


DOI: https://doi.org/10.33138/2957-0506.2025.24.487
Bourreau Marc, Grzybowski Łukasz, Muñoz-Acevedo Ángela
State Aid; Ex-Post Evaluation; Broadband; Entry; Coverage; Crowding Out

WP(23/2025)486. Does Pair Trading Still Work During Extreme Events? A Comprehensive Empirical Evidence from Chinese Stock Market

Authors: Sun Yufei
This study evaluates the performance of pairs trading strategies in the Chinese stock market across extreme market environments, including the Financial Crisis, Bull and Bear phases, and the COVID-19 period. Using a comprehensive stock dataset and in…

WP486. Does Pair Trading Still Work During Extreme Events? A Comprehensive Empirical Evidence from Chinese Stock Market

This study evaluates the performance of pairs trading strategies in the Chinese stock market across extreme market environments, including the Financial Crisis, Bull and Bear phases, and the COVID-19 period. Using a comprehensive stock dataset and incorporating transaction costs, we find that most portfolios deliver near-zero excess returns after costs. However, in volatile conditions—especially during the Financial Crisis—top-performing portfolios achieved monthly returns up to 156 basis points. The strategy underperforms in stable or bullish markets with fewer mean-reversion opportunities. COVID-19 introduced challenges that further reduced profitability. Results highlight the critical role of transaction costs and the importance of advanced pair selection methods, such as combining the Sum of Squared Deviations (SSD), Hurst exponent, and the Number of Zero Crossings (NZC), which consistently outperform traditional approaches. While generally unprofitable, pairs trading can succeed under specific market regimes, offering insights into risk management and strategy adaptation.


DOI: https://doi.org/10.33138/2957-0506.2025.23.486
Sun Yufei
Pairs Trading Statistical Arbitrage Sum of Squared Deviations Hurst Exponent Chinese Stock Market

WP(22/2025)485. A survey of statistical arbitrage pair trading with machine learning, deep learning, and reinforcement learning methods

Authors: Sun Yufei
Pair trading remains a cornerstone strategy in quantitative finance, having consistently attracted scholarly attention from both economists and computer scientists. Over recent decades, research has expanded beyond traditional linear frameworks&mdash…

WP485. A survey of statistical arbitrage pair trading with machine learning, deep learning, and reinforcement learning methods

Pair trading remains a cornerstone strategy in quantitative finance, having consistently attracted scholarly attention from both economists and computer scientists. Over recent decades, research has expanded beyond traditional linear frameworks—such as regression- and cointegration-based models—to embrace advanced methodologies, including machine learning (ML), deep learning (DL), reinforcement learning (RL), and deep reinforcement learning (DRL). These techniques have demonstrated superior capacity to capture nonlinear dependencies and complex dynamics in financial data, thereby enhancing predictive performance and strategy design.
Building on these academic developments, practitioners are increasingly deploying DL models to forecast asset price movements and volatility in equity and foreign exchange markets, leveraging the advantages of artificial intelligence (AI) for trading. In parallel, DRL has gained prominence in algorithmic trading, where agents can autonomously learn optimal trading policies by interacting with market environments, enabling systems that move beyond price prediction to dynamic signal generation and portfolio allocation.
This paper provides a comprehensive survey of ML-, DL-, RL-, and DRL-based approaches to pair trading within quantitative finance. By systematically reviewing existing studies and highlighting their methodological contributions, it offers researchers a structured foundation for replication and further development. In addition, the paper outlines promising avenues for future research that extend the application of AI-driven methods in statistical arbitrage and market microstructure analysis.


DOI: https://doi.org/10.33138/2957-0506.2025.22.485
Sun Yufei
Pair Trading Machine Learning Deep Learning Reinforcement Learning Deep Reinforcement Learning Artificial Intelligence Quantitative Trading