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I am an Assistant Professor (Juniorprofessor) of Quantitative Macroeconomics at the University of Mannheim. I completed my Ph.D. at the European University Institute in Florence.

My research focuses on how differences across households and frictions in retail markets shape household decisions and, ultimately, macroeconomic outcomes. To study these dynamics, I combine large-scale microeconomic data with a macroeconomic perspective, using structural modeling and machine learning techniques.

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Krzysztof Pytka and Kuki-Muki on a bike ride

Me (on the right) and Kuki-Muki.

Miscellanea

If you're curious about the pronounciation of my given name it goes by [kʂɨʂt̪ɔf] in IPA. But Christoph is totally fine with me.

Research

Looking into the Consumption Black Box: Evidence from Scanner Data

(jointly with Daniel Runge)

[PDF] [Slides] [BibTeX]
This paper examines the heterogeneity and persistence of household non-durable consumption. We address three questions: (i) Do different consumer groups buy different products? (ii) How persistent are individual choices? (iii) What are the implications for structural models? We find minimal differences in basket composition between rich and poor households and high individual instability, with only 38% of products repurchased annually. To explain this, we propose a "shopping spree" model where products are perfect substitutes and baskets result from random sampling. Our findings serve as a cautionary note for structural models that emphasize product and consumer sorting.

Shopping Frictions with Household Heterogeneity: Theory & Empirics

[PDF] [Slides] [BibTeX]
Revise & Resubmit at the Review of Economic Studies
This paper examines the impact of price dispersion on household consumption, highlighting the role of economic status in shaping purchasing behaviors. Leveraging detailed scanner data, I document high-earning employees pay 1.5 to 7% more than lower-earning ones for the same or similar goods. A causal link between income and the prices is established using the Economic Stimulus Act of 2008. The findings indicate that 8 to 22% of the increase in household spending following a transitory income shock is due to higher prices paid. Despite a broader variety in the consumption baskets of wealthier households, very few goods are tailored to specific income groups. Integrating consumer search with the savings problem, I propose a new model to reconcile the observed patterns and quantify the impact of retail-market frictions on consumption. Counterfactual analysis shows that over two-thirds of households face higher prices due to a price externality.

Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach

(jointly with Andreas Gulyas)

[PDF] [BibTeX]
Conditionally Accepted at the Journal of Labor Economics
Using generalized random forests in a difference-in-differences framework, we analyze heterogeneity in earnings losses following job displacement. We find substantial variation in short-term losses ranging 20-70%. While all workers face long-term losses, employment rather than wage changes primarily drives heterogeneity. The most important predictor for employment losses is worker's age, while the firm wage premium is the most important one for wage losses. We predict similar loss patterns for the population excluded by the typical sample restrictions in the literature. We further show how to create simple decision rules to target active labor market programs to high-loss individuals.

Additional Resources:

  • General-audience presentation about using the GRF for estimation of heterogeneous treatment effects. [Slides]
  • Presentation about using the GRF in business analytics. [Slides]

The Consequences of the Covid-19 Job Losses: Who Will Suffer Most and by How Much?

(jointly with Andreas Gulyas)

[PDF] [BibTeX]
CEPR Covid Economics (47)
Using the universe of Austrian unemployment insurance records until May 2020, we document that the composition of UI claimants during the Covid-19 outbreak is substantially different compared to past times. Using a machine-learning algorithm from Gulyas and Pytka (2020), we identify individual earnings losses conditional on worker and job characteristics. Covid-19-related job terminations are associated with lower losses in earnings and wages compared to the Great Recession, but similar employment losses. We further derive an accurate but simple policy rule targeting individuals vulnerable to long-term wage losses.

Teaching

Courses at Mannheim

I’m proud to teach a wide range of courses at Mannheim, working with talented students across different levels and backgrounds.

1. Quantitative Macroeconomics with Heterogeneous Households

[Ph.D. course]

[Julia Tutorial]
2. Advanced Macroeconomics

[M.Sc. course]

3. Introduction to Predictive Analytics and Machine Learning in R

[B.A. + M.Sc. block seminar]

[Prerecorded Materials]

Featured Interview

I talk about how big data and machine learning are changing the way we do economic research, what it’s like to teach at Mannheim, and how I tinker with a Raspberry Pi to generate valuation reports for my own investment portfolio.

[VWL Lounge Interview]

Student Feedback

I'm grateful for the thoughtful feedback I've received from my students over the years:

"Very entertaining lectures and a sympathetic Professor. You were always very interested that we learn something and understand everything... Furthermore it was never boring to listen to your lectures. I could easily handle listening for 90 minutes without even looking at my mobile phone."
"Different from all other courses we have this semester, the instructor really makes efforts to bring the theory to life using examples/adding stories from real life. They really help to understand material, connect everything in one's head."
"I love this course—definitely my favorite. Very interesting, nice and varied, good evaluation style, really feel like I learned a lot and enjoyed class."
"Overall this course was the best in the first Master semester. Prof. Pytka gave really good intuitions for the calculations and explained difficult topics in an understandable manner."
"Out of all the 3 subjects, Macroeconomics is the only one that I am quite comfortable with and this is only because of Professor Pytka."

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i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';

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