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Currencies, commodities and consumption : measurement and the world economy
\"Currency values, prices, consumption and incomes are at the heart of the economic performance of all countries. In order to make a meaningful comparison between one economy and another, economists routinely make use of purchasing power parity (PPP) exchange rates, but whilst PPP rates are widely used and well understood they take a lot of effort to produce and suffer from publication delays. Currencies, Commodities and Consumption analyses the strengths and weaknesses of two alternatives to PPP. Firstly, the so-called 'Big Mac Index' which uses hamburger prices as a standard of measurement and secondly, a less well known technique which infers incomes across countries based on the proportion of consumption devoted to food. Kenneth Clements uses international macroeconomics, microeconomic theory and econometrics to provide researchers and policy makers with insights into alternatives to PPP rates and make sense of the ongoing instability of exchange rates and commodity prices\"-- Provided by publisher.
Book
World pandemic uncertainty and German stock market: evidence from Markov regime-switching and Fourier based approaches
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.
Journal Article
The Billion Prices Project: Using Online Prices for Measurement and Research
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.
Journal Article
Predictions of steel price indices through machine learning for the regional northeast Chinese market
Projections of commodity prices have long been a significant source of dependence for investors and the government. This study investigates the challenging topic of forecasting the daily regional steel price index in the northeast Chinese market from January 1, 2010, to April 15, 2021. The projection of this significant commodity price indication has not received enough attention in the literature. The forecasting model that is used is Gaussian process regressions, which are trained using a mix of cross-validation and Bayesian optimizations. The models that were built precisely predicted the price indices between January 8, 2019, and April 15, 2021, with an out-of-sample relative root mean square error of 0.5432%. Investors and government officials can use the established models to study pricing and make judgments. Forecasting results can help create comparable commodity price indices when reference data on the price trends suggested by these models are used.
Journal Article
How Government Statistics Adjust for Potential Biases from Quality Change and New Goods in an Age of Digital Technologies: A View from the Trenches
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.
Journal Article
Globalization and the Gains From Variety
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.
Journal Article
Improving quality of the scanner CPI: proposition of new multilateral methods
Scanner data can be obtained from a wide variety of retailers (supermarkets, home electronics, Internet shops, etc.) and provide information at the level of the barcode, i.e. the Global Trade Item Number or its European version: European Article Number. One of advantages of using scanner data in the Consumer Price Index measurement is the fact that they contain complete transaction information, i.e. prices and quantities for every sold item. One of new challenges connected with scanner data is the choice of the index formula which should be able to reduce the chain drift bias and the substitution bias. Multilateral index methods seem to be the best choice in the case of dynamic scanner data sets. These indices work on a whole time window and are transitive, which is a key property in eliminating the chain drift effect. Following the so-called identity test, however, one may expect that even when only prices return to their original values, the index becomes one. Unfortunately, the commonly used multilateral indices (GEKS, CCDI, GK, TPD, TDH) do not meet the identity test. The paper discusses the proposal of two multilateral indices, the idea of which resembles the GEKS index, but which meet the identity test and most of other tests. In an empirical study, these indices are compared, inter alia, with the SPQ index, which is relatively new and also meets the identity test. Analytical considerations as well as empirical study confirm the high usefulness of the proposed indices.
Journal Article
The Cyclically of Sales, Regular and Effective Prices: Business Cycle and Policy Implications
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.
Journal Article
ARE POOR CITIES CHEAP FOR EVERYONE? NON-HOMOTHETICITY AND THE COST OF LIVING ACROSS U.S. CITIES
This paper shows that the products and prices offered in markets are correlated with local income-specific tastes. To quantify the welfare impact of this variation, I calculate local price indexes micro-founded by a model of non-homothetic demand over thousands of grocery products. These indexes reveal large differences in how wealthy and poor households perceive the choice sets available in wealthy and poor cities. Relative to low-income households, high-income households enjoy 40 percent higher utility per dollar expenditure in wealthy cities, relative to poor cities. Similar patterns are observed across stores in different neighborhoods. Most of this variation is explained by differences in the product assortment offered, rather than the relative prices charged, by chains that operate in different markets.
Journal Article
The dynamic volatility nexus of geo-political risks, stocks, bond, bitcoin, gold and oil during COVID-19 and Russian-Ukraine war
We investigate the dynamic volatility connectedness of geopolitical risk, stocks, bonds, bitcoin, gold, and oil from January 2018 to April 2022 in this study. We look at connectivity during the Pre-COVID, COVID, and Russian-Ukraine war subsamples. During the COVID-19 and Russian-Ukraine war periods, we find that conventional, Islamic, and sustainable stock indices are net volatility transmitters, whereas gold, US bonds, GPR, oil, and bitcoin are net volatility receivers. During the Russian-Ukraine war, the commodity index (DJCI) shifted from being a net recipient of volatility to a net transmitter of volatility. Furthermore, we discover that bilateral intercorrelations are strong within stock indices (DJWI, DJIM, and DJSI) but weak across all other financial assets. Our study has important implications for policymakers, regulators, investors, and financial market participants who want to improve their existing strategies for avoiding financial losses.
Journal Article