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A large and growing share of retail prices all over the world are posted online on the websites of retailers. This is a massive and (until recently) untapped source of retail price information. Our objective with the Billion Prices Project, created at MIT in 2008, is to experiment with these new sources of information to improve the computation of traditional economic indicators, starting with the Consumer Price Index. We also seek to understand whether online prices have distinct dynamics, their advantages and disadvantages, and whether they can serve as reliable source of information for economic research. The word “billion” in Billion Prices Project was simply meant to express our desire to collect a massive amount of prices, though we in fact reached that number of observations in less than two years. By 2010, we were collecting 5 million prices every day from over 300 retailers in 50 countries. We describe the methodology used to compute online price indexes and show how they co-move with consumer price indexes in most countries. We also use our price data to study price stickiness, and to investigate the “law of one price” in international economics. Finally we describe how the Billion Prices Project data are publicly shared and discuss why data collection is an important endeavor that macro- and international economists should pursue more often.

Since the seminal work of Krugman, product variety has played a central role in models of trade and growth. In spite ofthe general use oflove-of-variety models, there has been no systematic study of how the import of new varieties has contributed to national welfare gains in the United States. In this paper we show that the unmeasured growth in product variety from U. S. imports has been an important source of gains from trade over the last three decades (1972–2001). Using extremely disaggregated data, we show that the number of imported product varieties has increased by a factor of three. We also estimate the elasticities of substitution for each available category at the same level of aggregation, and describe their behavior across time and SITC industries. Using these estimates, we develop an exact aggregate price index and find that the upward bias in the conventional import price index over this time period was 28 percent or 1.2 percentage points per year. We estimate the value to U. S. consumers of the expanded import varieties between 1972 and 2001 to be 2.6 percent of GDP.

A key economic indicator is real output. To get this right, we need to measure accurately both the value of nominal GDP (done by Bureau of Economic Analaysis) and key price indexes (done mostly by Bureau of Labor Statisticcs). All of us have worked on these measurements while at the BLS and the BEA. In this article, we explore some of the thorny statistical and conceptual issues related to measuring a dynamic economy. An often-stated concern is that the national economic accounts miss some of the value of some goods and services arising from the growing digital economy. We agree that measurement problems related to quality changes and new goods have likely caused growth of real output and productivity to be understated. Nevertheless, these measurement issues are far from new, and, based on the magnitude and timing of recent changes, we conclude that it is unlikely that they can account for the pattern of slower growth in recent years. First we discuss how the Bureau of Labor Statistics currently adjusts price indexes to reduce the bias from quality changes and the introduction of new goods, along with some alternative methods that have been proposed. We then present estimates of the extent of remaining bias in real GDP growth that stem from potential biases in growth of consumption and investment. And we take a look at potential biases that could result from challenges in measuring nominal GDP, including those involving the digital economy. Finally, we review ongoing work at BLS and BEA to reduce potential biases and further improve measurement.

We develop a method for decomposing countries' observed export prices into quality versus quality-adjusted components using information contained in trade balances. Holding observed export prices constant, countries with trade surpluses are inferred to offer higher quality than countries running trade deficits. We account for variation in trade balances induced by horizontal and vertical differentiation, and we estimate the evolution of manufacturing quality for top exporters from 1989 to 2003. We find that observed unit value ratios can be a poor approximation for relative quality differences, countries' quality is converging more rapidly than their income, and countries appear to vary in terms of displaying \"high-quality\" versus \"low-price\" growth strategies.

This paper describes the extent of product creation and destruction in a large sector of the US economy. We find four times more entry and exit in product markets than is found in labor markets because most product turnover happens within firms. Net product creation is strongly procyclical and primarily driven by creation rather than destruction. We find that a cost-of-living index that takes product turnover into account is 0.8 percentage points per year lower than a \"fixed goods\" price index like the CPI. The procyclicality of the bias implies that business cycles are more volatile than indicated by official statistics.

We study the cyclical properties of sales, regular price changes, and average prices paid by consumers (\"effective\" prices) using data on prices and quantities sold for numerous retailers across many US metropolitan areas. Inflation in the effective prices paid by consumers declines significantly with higher unemployment while little change occurs in the inflation rate of prices posted by retailers. This difference reflects the reallocation of household expenditures across retailers, a feature of the data which we document and quantify, rather than sales. We propose a simple model with household store-switching and assess its implications for business cycles and policymakers.

Purpose Understandings of house prices and their interrelationships have undoubtedly drawn a great amount of attention from various market participants. This study aims to investigate the monthly newly-built residential house price indices of seventy Chinese cities during a 10-year period spanning January 2011–December 2020 for understandings of issues related to their interdependence and synchronizations. Design/methodology/approach Analysis here is facilitated through network analysis together with topological and hierarchical characterizations of price comovements. Findings This study determines eight sectoral groups of cities whose house price indices are directly connected and the price synchronization within each group is higher than that at the national level, although each shows rather idiosyncratic patterns. Degrees of house price comovements are generally lower starting from 2018 at the national level and for the eight sectoral groups. Similarly, this study finds that the synchronization intensity associated with the house price index of each city generally switches to a lower level starting from early 2019. Originality/value Results here should be of use to policy design and analysis aiming at housing market evaluations and monitoring.

This study aims to examine the impact of the world pandemic uncertainty index on the German stock market index (DAX index) for the 1996Q1 to 2020Q3 period while controlling real effective exchange rate, industrial production index, and consumer price index. The present study performs the Fourier Augmented Dickey-Fulle Unit Root, Fourier Engle-Granger Cointegration, Bayer-Hanck Cointegration, and Markov switching regression tests. The outcomes disclose that there is a long-run cointegration association between the stock market index and world pandemic uncertainty index, real effective exchange rate, industrial production index, and consumer price index in Germany, indicating that the combination of these factors significantly affects the German stock market index in the long-run. Moreover, in both high and low volatile regimes, the world pandemic uncertainty index and real effective exchange rate negatively affect the German stock market index while industrial production and consumer price indices impact positively.

In this paper, we show that the substitution of imported for domestically produced goods and services—often known as offshoring—can lead to overestimates of U.S. productivity growth and value added. We explore how the measurement of productivity and value added in manufacturing has been affected by the dramatic rise in imports of manufactured goods, which more than doubled from 1997 to 2007. We argue that, analogous to the widely discussed problem of outlet substitution bias in the literature on the Consumer Price Index, the price declines associated with the shift to low-cost foreign suppliers are generally not captured in existing price indexes. Just as the CPI fails to capture fully the lower prices for consumers due to the entry and expansion of big-box retailers like Wal-Mart, import price indexes and the intermediate input price indexes based on them do not capture the price drops associated with a shift to new low-cost suppliers in China and other developing countries. As a result, the real growth of imported inputs has been understated. And if input growth is understated, it follows that the growth in multifactor productivity and real value added in the manufacturing sector have been overstated. We estimate that average annual multifactor productivity growth in manufacturing was overstated by 0.1 to 0.2 percentage points and real value added growth by 0.2 to 0.5 percentage points from 1997 to 2007. Moreover, this bias may have accounted for a fifth to a half of the growth in real value added in manufacturing output excluding the computer and electronics industry.

We study the impact of large exchange rate devaluations on the cost of living at different points on the income distribution. Poor households spend relatively more on tradeable product categories and consume lower-priced varieties within categories. Changes in the relative price of tradeables and of lower-priced varieties affect the cost of living of low-income relative to high-income households. We quantify these effects following the 1994 Mexican devaluation and show that they can have large distributional consequences. Two years post-devaluation, the cost of living for the bottom income decile rose 1.48 to 1.62 times more than for the top income decile.