• Economic Policy Uncertainty and Stock Market Participation , with Dimitris Georgarakos.

Does economic policy uncertainty affect household stockholding? To answer this question we create a novel measure of household exposure to economic policy uncertainty news by combining survey information on the hours a household spends in reading newspapers and the frequency of such news in the popular press during a household’s pre-interview period. After controlling for household fixed effects, month-year fixed effects and time-varying cognitive skills, we find that households with more exposure to economic policy uncertainty news are less likely to invest in stocks directly or through mutual funds. This effect is independent from the VIX and household stock-price expectations.

•  The Relative Importance of Taste Shocks and Price Movements in the Variation of Cost-of-Living: Evidence From Scanner Data, with Philip Vermuelen.

Intertemporal consumer preference shifts, although common in modern macro-economic models as drivers of demand shocks, have important but largely unexplored implications for price index theory and thus, for empirically measured price changes. The current practice of inflation measurement basically ignores taste changes and this study aims to fill this gap. We derive a cost-of-living index in the presence of intertemporal preference shifts and show that such taste changes tend to lower the cost-of-living. Using a large barcode level dataset that covers 331 product groups and ten countries, we then uncover the importance of taste changes in explaining consumer demand shifts across close substitutes. We also analyze how measured consumer price inflation alters after allowing for taste adjustment over time and under CES preferences. To do so, we estimate the elasticity of substitution between varieties of the same good and use those to calculate goods price indexes. Our results show that the median elasticity of substitution is around 4 and find that measured average annual goods price inflation is on average about 1.1 percent lower when taking into account consumer taste shifts compared to standard goods price indexes. Our results indicate that taste changes are an important hitherto ignored factor in the measurement of cost-of-living changes.​

• A model of trade in used durables

This chapter examines the role of secondary markets in durable goods in cross-country trade dynamics, with a special focus on the car industry. Empirically, it documents patterns in new and used car trade flows for a sample of European Union countries. Further, it develops a two-country general equilibrium model of trade in which countries can trade on the various vintages of a single durable good. Countries can differ in their initial endowment, growth rate in the car sector and the representative household's preference for new versus older vintages. Adjustment in the level and age composition of the car stock can occur by new car production or international trade as supply of used cars is fixed by past new production. This relationship is responsible for the dynamics of the model. Trade patterns are determined by comparative advantages. The model predicts that the country that experiences a high growth rate in new car production has comparative advantage in new cars and becomes a new car exporter when trade is introduced. Further, the country that dislikes old cars relatively less will consume used cars and export new cars.  Cross-country  differences in tastes and growth rate in new car production influence cross-country trade dynamics. A sudden negative supply shock triggers stock adjustment in the country hit by the shock which generates large initial trade flows and muted but persistent trade flows thereafter. The chapter presents a numerical example and simulation results for the model that uses parameters calibrated to the primary and secondary car market in Germany and Hungary.

​The panel on household finances (phf)–microdata on household wealth in Germany, with Kristina Altmann , René Bernard , Julia Le Blanc , Eniko Gábor-Tóth , Malik Hebbat , Lisa Kothmayr , Tobias Schmidt   , Panagiota Tzamourani , Daniel Werner and Junyi Zhu.

The Panel on Household Finances (PHF) has established itself as one of the leading sources of microdata on households’ wealth in Germany since its inception in 2010. Over the last ten years, more than 7,583 households have participated in the surveys in 2010–11, 2014 and 2017, many of them taking part more than once (3,734 households). This paper provides an overview of the contents, main methodological aspects and use of the PHF data. It also highlights differences to other surveys and addresses how the survey may develop in the future.

​Elementary Index Bias: Evidence for the Euro Area from a Large Scanner Dataset, with Philip Vermuelen.

We provide evidence on the effect of elementary index choice on inflation measurement in the euro area. Using scanner data for 15,844 individual items from 42 product categories and 10 euro area countries, we compute product category level elementary price indexes using eight different elementary index formulas. Measured inflation outcomes of the different index formulas are compared with the Fisher ideal index to quantify elementary index bias. We have three main findings. First, elementary index bias is quite variable across product categories, countries and index formulas. Second, a comparison of elementary index formulas with and without expenditure weights shows that a shift from price only indexes to expenditure weighted indexes would entail at the product level multiple percentage points differences in measured price changes. And finally, we show that elementary index bias is quantitatively more important than upper level substitution bias.​

Other publications

• Linking Deutsche Bundesbank Company Data

We present a method of automatically linking several data sets on companies based on supervised machine learning. We employ this method to perform a record linkage of several company datasets used for research and analytical purposes at the Deutsche Bundesbank. The record linkage process involves comprehensive data pre-processing, blocking/indexing, construction of comparison features, training and testing of a supervised match classification model as well as post-processing to produce a company identifier mapping table for all internal and public company identifiers found in the data. The evaluation of our linkage method shows that the process yields precise match predictions with a sufficiently high coverage/recall to make full automation of company data linkage feasible for typical use cases in research and analytics

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• Understanding Overlaps between Different Company Data

We analyze overlaps between various company datasets, building on the results of the company data record linkage by Gabor-Toth, Schild, and Walter (2023) and Gabor-Toth and Schild (2023). To better understand the data overlaps, we also briefly describe the input data for this linkage, in particular with respect to data universes and time periods covered by the data. We report descriptive statistics that characterize the overlaps found between the company data. The overlaps are discussed and interpreted with reference to properties of the input data and of the record linkage process.

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