Research
2020
Abstract: We characterize inflation dynamics during the Great Lockdown using scanner data covering millions of transactions for fast-moving consumer goods in the United Kingdom. We show that there was a significant and widespread spike in inflation. First, aggregate month-to-month inflation was 2.4% in the first month of lockdown, a rate over 10 times higher than in preceding months. Over half of this increase stems from reduced frequency of promotions. Consumers' purchasing power was further eroded by a reduction in product variety. Second, 96% of households have experienced inflation in 2020, while in prior years around half of households experienced deflation. Third, there was inflation in most product categories, including those that experienced output falls. Only 13% of product categories experienced deflation, compared with over half in previous years. While market-based measures of inflation expectations point to disinflation or deflation, these findings indicate a risk of stagflation should not be ruled out. We hope our approach can serve as a template to facilitate rapid diagnosis of inflation risks during economic crises, leveraging scanner data and appropriate price indices in real-time.
Abstract: How do price dynamics affect inequality worldwide? Despite extensive research, this question remains debated due to potential biases in existing measures of prices and expenditure patterns across countries. To address this issue, this paper introduces a new global scanner database. 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 consumer packaged goods in thirty-four countries, including developing (e.g., Brazil, China, India, and South Africa) and developed countries (e.g., the United States, Russia, and most European countries). The first part of the analysis focuses on the relationship between prices and inequality within countries over time. We find that inflation inequality has been a worldwide phenomenon in recent years. In most countries, inflation has been lower and product variety has increased faster in product categories catering to higher-income households. The second part of the paper builds purchasing power parity (PPP) indices using millions of identical barcodes across countries. We find that standard biases in the calculation of price indices (including quality bias, new goods bias, and substitution bias) do not vary significantly with the level of economic development. But we show that PPP indices between countries vary widely depending on which household income serves as the reference level. For example, the PPP index between Italy and Germany is below one for low-income households but above one for high-income households. Consequently, we develop non-homothetic PPP indices to characterize differences in purchasing power along the household income distribution in all countries. To address the limitation that only a subset of total expenditures is observed, we use shifts in Engel curves (extending the Hamilton (2001) method and building on recent work by Almas et al. (2019) and Atkin et al. (2020)). To directly check the external validity of our findings, we supplement the scanner data with more aggregate data on prices and expenditures from national statistical agencies covering the full consumption basket of consumers. Overall, the findings indicate that using microdata on prices and expenditures is crucial to accurately describe patterns of inclusive growth worldwide. We provide publicly available statistics on a companion website, which other research teams can use to build on and extend our analysis.
2019
Abstract: How do price dynamics affect inequality worldwide? Despite extensive research, this question remains debated due to potential biases in existing measures of prices and expenditure patterns across countries. To address this issue, this paper introduces a new global scanner database. 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 consumer packaged goods in thirty four countries, including developing (e.g., Brazil, China, India, and South Africa) and developed countries (e.g., the United States, Russia, and most European countries). The first part of the analysis focuses on the relationship between prices and inequality within countries over time. We find that inflation inequality has been a worldwide phenomenon in recent years. In most countries, inflation has been lower and product variety has increased faster in product categories catering to higher-income households. The second part of the paper builds purchasing power parity (PPP) indices using millions of identical barcodes across countries. We find that standard biases in the calculation of price indices (including quality bias, new goods bias and substitution bias) do not vary significantly with the level of economic development. But we show that PPP indices between countries vary widely depending on which household income serves as the reference level. For example, the PPP index between Italy and Germany is below one for low-income households but above one for high-income households. Consequently, we develop non-homothetic PPP indices to characterize differences in purchasing power along the household income distribution in all countries. To address the limitation that only a subset of total expenditures is observed, we use shifts in Engel curves (extending the Hamilton (2001) method and building on recent work by Almas et al. (2019) and Atkin et al. (2020)). To directly check the external validity of our findings, we supplement the scanner data with more aggregate data on prices and expenditures from national statistical agencies covering the full consumption basket of consumers. Overall, the findings indicate that using micro data on prices and expenditures is crucial to accurately describe patterns of inclusive growth worldwide. We provide publicly available statistics on a companion website, which other research teams can use to build on and extend our analysis.
Abstract: How do price dynamics affect inequality worldwide? Despite extensive research, this question remains debated due to potential biases in existing measures of prices and expenditure patterns across countries. To address this issue, this paper introduces a new global scanner database. 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 consumer packaged goods in thirty four countries, including developing (e.g., Brazil, China, India, and South Africa) and developed countries (e.g., the United States, Russia, and most European countries). The first part of the analysis focuses on the relationship between prices and inequality within countries over time. We find that inflation inequality has been a worldwide phenomenon in recent years. In most countries, inflation has been lower and product variety has increased faster in product categories catering to higher-income households. The second part of the paper builds purchasing power parity (PPP) indices using millions of identical barcodes across countries. We find that standard biases in the calculation of price indices (including quality bias, new goods bias and substitution bias) do not vary significantly with the level of economic development. But we show that PPP indices between countries vary widely depending on which household income serves as the reference level. For example, the PPP index between Italy and Germany is below one for low-income households but above one for high-income households. Consequently, we develop non-homothetic PPP indices to characterize differences in purchasing power along the household income distribution in all countries. To address the limitation that only a subset of total expenditures is observed, we use shifts in Engel curves (extending the Hamilton (2001) method and building on recent work by Almas et al. (2019) and Atkin et al. (2020)). To directly check the external validity of our findings, we supplement the scanner data with more aggregate data on prices and expenditures from national statistical agencies covering the full consumption basket of consumers. Overall, the findings indicate that using micro data on prices and expenditures is crucial to accurately describe patterns of inclusive growth worldwide. We provide publicly available statistics on a companion website, which other research teams can use to build on and extend our analysis.