Working Papers

Seria wydawnicza WNE WORKING PAPERS prowadzona jest przez WNE UW od 2008 r. i jak dotąd opublikowano w niej ponad 400 prac.

Seria WNE Working Papers służy szybkiemu upowszechnianiu wyników badań prowadzonych na Wydziale Nauk Ekonomicznych UW. Publikowane tu teksty mają charakter wersji roboczych (pre-printów): mogą być uzupełniane lub poprawiane w miarę postępu prac nad tekstem i procesu wydawniczego. Prezentujemy aktualną wersję udostępnioną przez autorów, opatrzoną datą oraz identyfikatorami DOI/ISSN – co ułatwia jej cytowanie i śledzenie kolejnych iteracji. Każdy dokument zachowuje pełne prawa autorskie swoich twórców, a w przypadku późniejszych zmian, autorzy mogą w dowolnym momencie zamieścić zaktualizowany plik lub wskazać miejsce ostatecznego wydania.

Do serii WORKING PAPERS przyjmowane są artykuły pracowników naukowych WNE UW oraz publikacje z konferencji organizowanych na WNE UW. Artykuły powinny dotyczyć ekonomii, mieć charakter oryginalnych prac badawczych, nie być wcześniej publikowane. Przyjmowane są wyłącznie teksty w języku angielskim.

Prace prosimy przesyłać e-mailem na adres: sF\$ytr2^oGTj9@]Cl-f_Mg7n'{]#[k2OlccZ}@`&G^T4L!u}^h/L-wsh

Prosimy przesyłać dwa pliki:

(1) główny tekst bez podania tytułu artykułu oraz autorów (plik DOC/DOCX) oraz

(2) stronę tytułową zawierającą: tytuł opracowania, autorów oraz ich afiliację (plik DOC/DOCX). 

Przed przesłaniem tekstu prosimy zapoznać się z szczegółowymi wymogami edycyjnymi.

Redaktorem wydawniczym serii Working Papers jest dr Maciej Bukowski.

Ilość wyników 3

WP(18/2024)454. Explaining and forecasting abnormal returns and volume by investor sentiment indicators

Autorzy: Lis Szymon, Ślepaczuk Robert, Sakowski Paweł
This study investigates the impact of investor sentiment on stock returns and trading volume, challenging the efficient market hypothesis. Using CRSP data from May 1998 to March 2022, methods like Fama-MacBeth and quantile regression were applied to …

WP454. Explaining and forecasting abnormal returns and volume by investor sentiment indicators

This study investigates the impact of investor sentiment on stock returns and trading volume, challenging the efficient market hypothesis. Using CRSP data from May 1998 to March 2022, methods like Fama-MacBeth and quantile regression were applied to analyze sentiment indicators such as the VIX, AAII Investor Sentiment Survey, Consumer Confidence, and Baker-Wurgler Index. The findings reveal that investor sentiment significantly influences stock returns and trading volume, especially during uncertain times. Sentiment also affects financial metrics like SMB, HML, RMW, and CMA uniquely. This research provides new insights and practical implications for investors and analysts, emphasizing the importance of considering sentiment in investment strategies to better anticipate market movements and manage risks.


Lis Szymon, Ślepaczuk Robert, Sakowski Paweł
market sentiment factor models stock returns EMH Fama-MacBeth model quantile regression Baker-Wurgler index VIX index

WP(30/2022)406. Quantile regression analysis to predict GDP distribution using data from the US and UK

Autorzy: Tran Thi Huyen, Ślepaczuk Robert
This paper aims to find the best models to forecast one-quarter-ahead and one-year-ahead US and UK real GDP growth distributions by employing quantile regression with skewed-t distribution on different sets of relevant near-term predictors. The resea…

WP406. Quantile regression analysis to predict GDP distribution using data from the US and UK

This paper aims to find the best models to forecast one-quarter-ahead and one-year-ahead US and UK real GDP growth distributions by employing quantile regression with skewed-t distribution on different sets of relevant near-term predictors. The research data period starts in 1947Q1/1955Q1 for US/UK data and ends in 2021Q3/2020Q4 for one-quarter-ahead/one-year-ahead prediction. The out-of-sample period ranges from 1996Q3 to 2021Q3 for one-quarter-ahead prediction and to 2020Q4 for one-year-ahead forecasting. The author applies a two-step testing procedure, in which models with the lowest average error in out-of-sample period are selected to the next step where the cumulative distribution functions of probability integral transforms are computed for the out-of-sample period, to select the best models. The improvement in the final forecasts of the tested models results, among others, from the use of new macroeconomic data with a higher frequency and focusing on the specific properties of the tested models separately for the US and UK. The chosen best models indicate that there exist better models than the model proposed by Adrian et al. (2016) to predict US growth distributions and that near-term predictors can produce good UK growth forecasts. Additionally, some simplified models associated with significantly lower portion of model risk are detected to produce meaningful forecasts for both US and UK case. For the US data, there exist several models that can produce timely predicted results.


Tran Thi Huyen, Ślepaczuk Robert
GDP growth density forecast quantile regression US GDP UK GDP cumulative distribution function probability integral transform out-of-sample forecasting

WP(13/2016)204. Evolution of the public-sector wage premium in Poland

Autorzy: Grotkowska Gabriela, Wincenciak Leszek, Gajderowicz Tomasz
The aim of this paper is to estimate the adjusted sectoral wage gap in Poland in the period 1999–2012. We use a set of individual data from the survey on the structure of earnings by occupations (SEO) carried out by Central Statistical Office i…

WP204. Evolution of the public-sector wage premium in Poland

The aim of this paper is to estimate the adjusted sectoral wage gap in Poland in the period 1999–2012. We use a set of individual data from the survey on the structure of earnings by occupations (SEO) carried out by Central Statistical Office in Poland (CSO) every two years for entities with more than nine employees. We apply quantile regression and the Ñopo decomposition method to address several methodological problems of wage differential analysis. We show that, after controlling for structural differences in employment, there is no clear trend in the evolution of the adjusted public-sector wage premium in Poland in recent years. The parametric approach indicates a positive and growing premium, with significant variations across different parts of wage distribution. The non-parametric approach yields different results, indicating a negative premium with no clear trend in the period 1999–2012, with a declining public-sector wage penalty in recent years.


Grotkowska Gabriela, Wincenciak Leszek, Gajderowicz Tomasz
wage differentials public sector wages quantile regression Ñopo decomposition Poland
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