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.
We establish five facts about prices in the U.S. economy: (1) For consumer prices, the median frequency of nonsale price change is roughly half of what it is including sales (9-12% per month versus ...19-20% per month for identical items; 11-13% per month versus 21-22% per month including product substitutions). The median frequency of price change for finished-goods producer prices is comparable to that of consumer prices excluding sales. (2) One-third of nonsale price changes are price decreases. (3) The frequency of price increases covaries strongly with inflation, whereas the frequency of price decreases and the size of price increases and price decreases do not. (4) The frequency of price change is highly seasonal: it is highest in the first quarter and then declines. (5) We find no evidence of upwardsloping hazard functions of price changes for individual products. We show that the first, second, and third facts are consistent with a benchmark menu-cost model, whereas the fourth and fifth facts are not.
Imperfect information about product attributes inhibits efficiency in many choice settings, but can be overcome by providing simple, lowcost information. We use a randomized control trial to test the ...effect of high-frequency information about residential electricity usage on the price elasticity of demand. Informed households are three standard deviations more responsive to temporary price increases, an effect that is not attributable to price salience. Conservation extends beyond pricing events in the short and medium run, providing evidence of habit formation and implying that the intervention leads to greenhouse gas abatement. Survey evidence suggests that information facilitates learning.
It is widely believed that oil prices impact food prices in developing countries. Yet rigorous evidence on this relationship is scarce. Using maize and petrol price data from east Africa, we show ...that global oil prices do affect food prices but primarily through transport costs, rather than through biofuel or production cost channels. We find that global oil prices transmit much more rapidly to the pump and then to local maize prices than do global maize prices, suggesting that the immediate effects of correlated commodity price shocks on local food prices are driven more by transport costs than by the prices of the grains themselves. Furthermore, we present suggestive evidence that, for markets furthest inland, changes in world oil prices have larger effects on local maize prices than do changes in world maize prices.
This paper assesses the impact of oil price changes on Spanish and euro area consumer price inflation. We find that the inflationary effect of oil price changes in both economies is limited, even ...though crude oil price fluctuations are a major driver of inflation variability. The impact on Spanish inflation is found to be somewhat higher than in the euro area. In both economies, direct effects have increased in the last decade, reflecting the higher expenditure share of households on refined oil products, whereas indirect and second-round effects seem to be losing importance.
A considerable body of economic literature shows the adverse economic impacts of oil-price shocks for the developed economies. However, there has been a lack of similar empirical study on China and ...other developing countries. This paper attempts to fill this gap by answering how and to what extent oil-price shocks impact China's economy, emphasizing on the price transmission mechanisms. To that end, we develop a structural vector auto-regressive model. Our results show that an oil-price increase negatively affects output and investment, but positively affects inflation rate and interest rate. However, with price control policies in China, the impact on real economy, represented by real output and real investment, lasts much longer than that to price/monetary variables. Our decomposition results also show that the short-term impact, namely output decrease induced by the cut in capacity–utilization rate, is greater in the first 6 periods (namely half a year), but the portion of the long-term impact, defined as the impact realized through an investment change, increases steadily and exceeds that of short-term impact in the 7th period. Afterwards, the long-term impact dominates, and maintains for quite some time.
This paper investigates how explicit structural shocks that characterize the endogenous character of oil price changes affect stock-market returns in a sample of eight countries — Australia, Canada, ...France, Germany, Italy, Japan, the United Kingdom, and the United States. For each country, the analysis proceeds in two steps. First, modifying the procedure of Kilian
Kilian, L., (forthcoming). Not All Oil Price Shocks are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market. American Economic Review., we employ a vector error–correction or vector autoregressive model to decompose oil-price changes into three components: oil-supply shocks, global aggregate-demand shocks, and global oil-demand shocks. The last component relates to specific idiosyncratic features of the oil market, such as changes in the precautionary demand concerning the uncertainty about the availability of future oil supplies. Second, recovering the oil-supply shocks, global aggregate-demand shocks, and global oil-demand shocks from the first analysis, we then employ a vector autoregressive model to determine the effects of these structural shocks on the stock market returns in our sample of eight countries. We find that international stock market returns do not respond in a large way to oil market shocks. That is, the significant effects that exist prove small in magnitude.
How have house prices evolved over the long run? This paper presents annual house prices for 14 advanced economies since 1870. We show that real house prices stayed constant from the nineteenth to ...the mid-twentieth century, but rose strongly and with substantial cross-country variation in the second half of the twentieth century. Land prices, not replacement costs, are the key to understanding the trajectory of house prices. Rising land prices explain about 80 percent of the global house price boom that has taken place since World War II. Our findings have implications for the evolution of wealth-to-income ratios, the growth effects of agglomeration, and the price elasticity of housing supply.
Using time-varying BVARs, we find a substantial decline in the shortrun price elasticity of oil demand since the mid-1980s. This finding helps explain why an oil production shortfall of the same ...magnitude is associated with a stronger response of oil prices and more severe macroeconomic consequences over time, while a similar oil price increase is associated with smaller output effects. Oil supply shocks also account for a smaller fraction of real oil price variability in more recent periods, in contrast to oil demand shocks. The overall effects of oil supply disruptions on the US economy have, however, been modest.
This study examines volatility transmission between oil and selected agricultural commodity prices (wheat, corn, soybeans, and sugar). We apply the newly developed causality in variance test and ...impulse response functions to daily data from 01 January 1986 to 21 March 2011. In order to identify the impact of the food price crisis, the data are divided into two sub-periods: the pre-crisis period (01 January 1986 to 31 December 2005) and the post-crisis period (01 January 2006–21 March 2011). The variance causality test shows that while there is no risk transmission between oil and agricultural commodity markets in the pre-crisis period, oil market volatility spills on the agricultural markets —with the exception of sugar —in the post-crisis period. The impulse response analysis also indicates that a shock to oil price volatility is transmitted to agricultural markets only in the post-crisis period. This paper thereby shows that the dynamics of volatility transmission changes significantly following the food price crisis. After the crisis, risk transmission emerges as another dimension of the dynamic interrelationships between energy and agricultural markets.
► We find that there is no volatility spillover between oil and agricultural commodity markets before food price crisis. ► We find that oil volatility transmits to wheat, corn, and soybeans markets after the food price crisis ► We find that sugar is neutral to oil market risk both before and after the crisis.
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