Abstract: This study examines the short- and medium-term impacts of the ongoing Russia-Ukraine war on the labor market for Ukrainian workers. Using a unique dataset of 5.4 million online job advertisements for Ukrainian job seekers in Poland and Ukraine over the 2021–2022 period, we show a short-term surge in demand for Ukrainians to work in Poland, while the number of jobs available in Ukraine is relatively stable. Since February 2022, the demand for soft and analytical skills in Ukraine has increased, while the demand for such skills in Poland has remained the same. Moreover, the increase in Polish jobs available to Ukrainian workers is largest for medium/high-skilled jobs and female-oriented jobs. Further analysis suggests a persistent shift (to the left) in wage distribution driven by both the decline of wages within job titles and the change in the composition of jobs across Poland. 

Abstract: This study evaluates the effectiveness of varying levels of human and artificial intelligence (AI) integration in reproducibility assessments of quantitative social science research. We computationally reproduced quantitative results from published articles in the social sciences with 288 researchers, randomly assigned to 103 teams across three groups - human-only teams, AI-assisted teams and teams whose task was to minimally guide an AI to conduct reproducibility checks (the "AI-led" approach). Findings reveal that when working independently, human teams matched the reproducibility success rates of teams using AI assistance, while both groups substantially outperformed AI-led approaches (with human teams achieving 57 percentage points higher success rates than AI-led teams, 𝒑 ﹤ 0.001). Human teams were particularly effective at identifying serious problems in the analysis: they found significantly more major errors compared to both AI-assisted teams (0.7 more errors per team, 𝒑 = 0.017) and AI-led teams (1.1 more errors per team, 𝒑 ﹤ 0.001). AI-assisted teams demonstrated an advantage over more automated approaches, detecting 0.4 more major errors per team than AI-led teams ( 𝒑 = 0.029), though still significantly fewer than human-only teams. Finally, both human and AI-assisted teams significantly outperformed AIled approaches in both proposing (25 percentage points difference, 𝒑 = 0.017) and implementing (33 percentage points difference, 𝒑 = 0.005) comprehensive robustness checks. These results underscore both the strengths and limitations of AI assistance in research reproduction and suggest that despite impressive advancements in AI capability, key aspects of the research publication process still require human substantial human involvement. 

Abstract: Using data from online shopping platforms in China, the United States, and the United Kingdom, we explore how price digits affect price-setting behavior. The estimates for the Chinese sample reveal novel evidence of superstitious price-setting. Chinese sellers frequently use the lucky number “8” in price endings and adjust other endings to include “8”. Prices with the lucky “8” digits are 5-7 percentage points less likely to be updated. The effects of superstition are more pronounced for price increases, higher-priced items, and during the month of Lunar New Year. However, we find no evidence of superstitious pricing or significant impacts of numerology on pricing patterns in the U.S. and U.K. datasets. Our findings provide a novel explanation for price rigidity based on price endings, highlighting the importance of behavioral factors in macroeconomic modeling.

Abstract: Using a unique dataset on menus from more than 5,000 restaurants in the UK, this paper investigates how restaurants react to price adjustments in price leaders. We document three facts on the repricing behaviors of sellers with considerable menu costs. First, chain restaurants change prices more frequently than independent restaurants but by smaller size. The average frequency of price changes in chains is about twice as much as that in locals, but the size of price changes is smaller. Second, the price adjustment decisions of restaurants can be associated with those of huge chains. For example, local burger restaurants adjust prices with large burger chains. Also, chain restaurants are more likely to follow price changes in price leaders than those local restaurants. Third, the reaction to price changes in price leaders is unrelated to distance. This result suggests that the search costs are no longer critical when sellers change their prices.

Abstract: The behavior of food prices has been of particular concern in recent years. To get a more timely picture of food prices, this study develops a weekly web-scraped Food Price Tracker in the UK. This dataset focuses on products in Food and Non-Alcoholic Beverages, Alcohol, and Tobacco, a total of 16.6% in the CPI weight. The data collection started in December 2021, with over 9,000 observations gathered every week. Among the tracked items, 174 correspond to those used in the CPI calculations by the Office for National Statistics (ONS). This paper introduces brand-specific, weekly, and monthly indices to compare with the official figures provided by ONS. We find that the weekly and monthly indices are positively related to the official index but provide greater details. Prices of supermarkets’ own-brand products increase faster than the overall products.