Research
Ongoing Research
Nowcasting consumer price inflation using high-frequency scanner data: evidence from Germany (with Kai Carstensen, Jan-Oliver Menz, Richard Schnorrenberger, and Elisabeth Wieland)
Abstract
We study how millions of granular and weekly household scanner data combined with machine learning can help to improve the real-time nowcast of German inflation. Our nowcasting exercise targets three hierarchy levels of inflation: individual products, product groups, and headline inflation. At the individual product level, we construct a large set of weekly scanner-based price indices that closely match their official counterparts, such as butter and coffee beans. Within a mixed-frequency setup, these indices significantly improve inflation nowcasts already after the first seven days of a month. For nowcasting product groups such as processed and unprocessed food, we apply shrinkage estimators to exploit the large set of scanner-based price indices, resulting in substantial predictive gains over autoregressive time series models. Finally, by adding high-frequency information on energy and travel services, we construct competitive nowcasting models for headline inflation that are on par with, or even outperform, survey-based inflation expectations.
Available as ECB working paper at: https://www.ecb.europa.eu/pub/pdf/scpwps/ecb.wp2930~05cff276eb.en.pdf?fe0a072f86258f7c499e7a397d88db61
Nowcasting consumer price inflation using high-frequency scanner data: evidence from Germany (with Kai Carstensen, Jan-Oliver Menz, Richard Schnorrenberger, and Elisabeth Wieland)
Abstract
We study how millions of granular and weekly household scanner data combined with machine learning can help to improve the real-time nowcast of German inflation. Our nowcasting exercise targets three hierarchy levels of inflation: individual products, product groups, and headline inflation. At the individual product level, we construct a large set of weekly scanner-based price indices that closely match their official counterparts, such as butter and coffee beans. Within a mixed-frequency setup, these indices significantly improve inflation nowcasts already after the first seven days of a month. For nowcasting product groups such as processed and unprocessed food, we apply shrinkage estimators to exploit the large set of scanner-based price indices, resulting in substantial predictive gains over autoregressive time series models. Finally, by adding high-frequency information on energy and travel services, we construct competitive nowcasting models for headline inflation that are on par with, or even outperform, survey-based inflation expectations.
Available as ECB working paper at: https://www.ecb.europa.eu/pub/pdf/scpwps/ecb.wp2930~05cff276eb.en.pdf?fe0a072f86258f7c499e7a397d88db61
Published Research
Prices and global inequality: New evidence from worldwide scanner data (with Xavier Jaravel and Liuxiu Liu)
Abstract
How do prices a ect inequality and living standards worldwide? To address existing biases in the measurement of prices and expenditure patterns across countries, this paper introduces a new global scanner database. This dataset provides harmonized barcode-level data on expenditures and prices for fast-moving and slow-moving consumer goods during the last decade in thirty four countries, which include both developing (e.g., Brazil, China, India, and South Africa) and developed countries (e.g., the United States, Russia, and most European countries) and represent 70% of world GDP and 60% of world population. We rst quantify the importance of several common biases stemming from substitution, product variety, and taste shocks, and we characterize how these biases vary with the level of economic development. We then build purchasing power parity indices using identical barcodes across countries. We find that adjustments for product variety, non-homotheticities, and taste heterogeneity are quantitatively important. Overall, these findings indicate that using micro data on prices and expenditures is crucial to accurately describe patterns of inclusive growth worldwide.
An older version of the paper is available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3671980
Pass-through of local corporate taxes to consumer prices: Evidence from German micro data (with Sebastian Kessing, Sebastian Siegloch and Malte Zoubek).
Abstract
Tax incidence, i.e. the question who bears the burden of a particular tax, has been a classic topic in public finance, and it is intricately linked to tax pass-through- Our paper quantitiatvely evaluates whether, and to what extent, firms can shift corporate taxes to prices. Conceptually, this requires a setting of imperfect competition. This is empirically plausible, but has been somewhat neglected in most of the modern literature on corporate tax incidence building on Harberger’s (1962) seminal analysis. Recent studies have shown empirically that workers bear a substantial share of the burden of corporate taxes (approximately 30-50%, see Fuest et al. (2018), and Suarez Serrato and Zidar (2016)). This raises the question, whether the remaining burden will be borne by capital, or whether this burden may be shifted upstream to suppliers or downstream to customers and final consumers. The project focuses on the latter channel, i.e. the pass-through rate of corporate taxes to prices, for which no convincing empirical evidence exists.
Prices and global inequality: New evidence from worldwide scanner data (with Xavier Jaravel and Liuxiu Liu)
Abstract
How do prices a ect inequality and living standards worldwide? To address existing biases in the measurement of prices and expenditure patterns across countries, this paper introduces a new global scanner database. This dataset provides harmonized barcode-level data on expenditures and prices for fast-moving and slow-moving consumer goods during the last decade in thirty four countries, which include both developing (e.g., Brazil, China, India, and South Africa) and developed countries (e.g., the United States, Russia, and most European countries) and represent 70% of world GDP and 60% of world population. We rst quantify the importance of several common biases stemming from substitution, product variety, and taste shocks, and we characterize how these biases vary with the level of economic development. We then build purchasing power parity indices using identical barcodes across countries. We find that adjustments for product variety, non-homotheticities, and taste heterogeneity are quantitatively important. Overall, these findings indicate that using micro data on prices and expenditures is crucial to accurately describe patterns of inclusive growth worldwide.
An older version of the paper is available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3671980
Pass-through of local corporate taxes to consumer prices: Evidence from German micro data (with Sebastian Kessing, Sebastian Siegloch and Malte Zoubek).
Abstract
Tax incidence, i.e. the question who bears the burden of a particular tax, has been a classic topic in public finance, and it is intricately linked to tax pass-through- Our paper quantitiatvely evaluates whether, and to what extent, firms can shift corporate taxes to prices. Conceptually, this requires a setting of imperfect competition. This is empirically plausible, but has been somewhat neglected in most of the modern literature on corporate tax incidence building on Harberger’s (1962) seminal analysis. Recent studies have shown empirically that workers bear a substantial share of the burden of corporate taxes (approximately 30-50%, see Fuest et al. (2018), and Suarez Serrato and Zidar (2016)). This raises the question, whether the remaining burden will be borne by capital, or whether this burden may be shifted upstream to suppliers or downstream to customers and final consumers. The project focuses on the latter channel, i.e. the pass-through rate of corporate taxes to prices, for which no convincing empirical evidence exists.