Consumer Price Index Data Research Articles

Presidential Address: Macroeconomics and Online Prices

Presidential Address:Macroeconomics and Online Prices Roberto Rigobón (bio) The availability of microeconomic pricing data has produced an empirical revolution in macroeconomics. Two events were the main culprits: First, national statistical offices allowed economists to study the data underlying the construction of the consumer price index (CPI), which gave our profession the chance to tackle many questions that have been open for decades. Second, scanner data from several supermarkets and merchandising companies were made available as well, offering another great opportunity for research. The earlier literature used aggregate price indexes to address questions of price rigidity, the law of one price, cost and exchange rate pass-through, international market segmentation, and so on. The aggregation and the procedures behind the construction of those indexes mask several economic phenomena. The availability of more detailed data has allowed the profession to take a closer look at old questions.1 The microeconomic CPI data has several advantages. The first and most important is its representativeness. Statistical offices invest in the design of the data to make sure they include a representative set of prices for the consumption basket. The second advantage is the long history. When the micro-economic price data are released, researchers generally have access to several years and sometimes decades. This feature is quite important for evaluating pass-through and relative price equilibrium deviations. The disadvantages are many, including the one indicated by Alberto Cavallo in his thesis: micro-economic CPI prices are plagued with unit values.2 Although unit values are [End Page 199] conceivably a very good piece of information for the computation of inflation, they are terrible for understanding price-setting dynamics, especially when evaluating price stickiness. The second disadvantage is that even though the data are representative, CPIs tend to have very few items in each sector, which means that the heterogeneity within sectors is disguised by small samples. The scanner data resolved some of the issues in the CPI data and worsened others. The scope was clearly much bigger, and the extensive product variety allowed researchers to deal with heterogeneity much better. In addition, several scanner data sets have information on cost and quantities, as well as on the prices, which facilitates addressing questions on pass-through. The disadvantages, however, are several. First, scanner data are not representative. The data characteristics vary greatly depending on the data provider, the location, and the time period when the data were collected. Databases available for research are usually from a single retailer, which makes generalization even harder. Furthermore, the quantity data captured by scanner data can be biased. The reason is simple: a supermarket that sells milk at an unusually low price will experience unusually large sales of milk. Using the quantities to determine aggregate implications produces a massive bias. Second, scanner data also has unit values, with prices reported as a ratio of sales over quantities and averaged over a week. Not all scanner data suffer from this problem, but most of the data sets that have been used in the macroeconomic and international literature do. Observing the average price is not necessarily wrong if the question asked is about pass-through or inflation. It is, however, the incorrect data point when addressing questions of price stickiness and price dynamics.3 Alberto Cavallo and I started the Billion Prices Project at MIT (BPP) almost a decade ago to explore how using web methods can improve the collection of prices.4 We use web scraping to download millions of prices every day, from hundreds of retailers in more than seventy countries. The purpose is to collect all the products sold by a store, identify the posted prices every day, and also detect information about sales, promotions, and the like, in which case we collect all prices available. There are some advantages and disadvantages to these data. First, they are not as representative as census [End Page 200] data, but they are more representative than data from a single store, which is the typical source of scanner data. In particular, every U.S. supermarket selling products through an online web page is probably in our data set, not just Safeway. Second, the data are daily and have no...

Whether Inflation Hampers Economic Growth in Nepal

Present paper seeks to examine whether inflation hampers economic growth in Nepal or not with the help of Distributed Lag Models using the annual data of GDP and Consumer Price Index (CPI). The nominal GDP is converted into real terms and transformed into logarithmic form and the first difference of the real GDP in logarithmic form is taken as the proxy for economic growth. The CPI data is converted into logarithmic form and its first difference is taken as the proxy for inflation. While using the distributed lag models, the economic growth of Nepal at current time is adversely affected by inflation of the same time, whereas the current economic growth is favorably affected by the inflation of preceding time. The estimated regression of economic growth on inflation up to lag one is found to be robust and stable as indicated by residuals diagnostic test ( serial correlation, heteroscedasticity and normality tests) and Ramsey's RESET test. The findings of the study throw light in policy point of view. The present study suggests that the rate of inflation would automatically be adjusted with increasing output if rate of investment in increased.

City Relative Price Dynamics in Australia: Are Structural Breaks Important?*

This paper examines the dynamic behaviour of relative prices across seven Australian cities by applying panel unit root test procedures with structural breaks to quarterly consumer price index data for 1972 Q1–2011 Q4. We find overwhelming evidence of convergence in city relative prices. Three common structural breaks are endogenously determined at 1985, 1995, and 2007. Further, correcting for two potential biases, namely Nickell bias and time aggregation bias, we obtain half-life estimates of 2.3–3.8 quarters that are much shorter than those reported by previous research. Thus, we conclude that both structural breaks and bias corrections are important to obtain shorter half-life estimates.

Seasonal ARIMA model to Nigerian consumer price index data

Time series analysis of Nigerian Consumer Price Index (NCPI) Data is done. It is observed that it is seasonal. A multiplicative seasonal autoregressive integrated moving average (ARIMA) model , (0, 1, 1)x(0, 1, 1)12, is fitted to the series. A visual inspection of the actual and the fitted time plots reveals a close agreement between the two.

Inflation-Based Adjustments in Federal Civil Monetary Penalties

Civil monetary penalties play a vital role in federal law. The Federal Civil Penalties Inflation Adjustment Act of 1990, Pub. L. No. 101-410, prescribes rules for the regular adjustment of federal civil monetary penalties in response to inflation. Three statutory defects have undermined the Inflation Adjustment Act. First, the Act's 10 percent cap on initial adjustments creates an inflation gap relative to the level that would properly reflect inflation. Second, the Act directs federal agencies to use Consumer Price Index data that are at least 7 months and as many as 18 months out of date. This creates CPI lag in the adjustment of civil monetary penalties. Third, the Act's rounding rules can force some agencies to wait 15 years or more between adjustments.Originally prepared as a report for the Administrative Conference of the United States, this article examines the Inflation Adjustment Act and recommends possible legislative remedies for the Act's defects.

Switching from Originator Brand Medicines to Generic Equivalents in Selected Developing Countries: How Much Could Be Saved?

ObjectivesIn low- and middle-income countries, patients and reimbursement agencies that purchase medicines in the private sector pay more for originator brands when generic equivalents exist. We estimated the savings that could be obtained from a hypothetical switch in medicine consumption from originator brands to lowest-priced generic equivalents for a selection of medicines in 17 countries. MethodsIn this cost minimization analysis, the prices of originator brands and their lowest-priced generic equivalents were obtained from facility-based surveys conducted by using a standard methodology. Fourteen medicines most commonly included in the surveys, plus three statins, were included in the analysis. For each medicine, the volume of private sector consumption of the originator brand product was obtained from IMS Health, Inc. Volumes were applied to the median unit prices for both originator brands and their lowest-priced generics to estimate cost savings. Prices were adjusted to 2008 by using consumer price index data and were adjusted for purchasing power parity. ResultsFor the medicines studied, an average of 9% to 89% could be saved by an individual country from a switch in private sector purchases from originator brands to lowest-priced generics. In public hospitals in China, US $ 370 million could be saved from switching only four medicines, saving an average of 65%. Across individual medicines, average potential savings ranged from 11% for beclometasone inhaler to 73% for ceftriaxone injection. ConclusionsSubstantial savings could be achieved by switching private sector purchases from originator brand medicines to lowest-priced generic equivalents. Strategies to promote generic uptake, such as generic substitution by pharmacists and increasing confidence in generics by professionals and the public, should be included in national medicines policies.

소비자물가지수의 시계열모형 연구

소비자물가지수는 국가의 중요한 경제 척도 중의 하나이다. 본 연구에서는 4개 도시, 서울, 부산, 대구, 광주지역의 소비자물가지수를 연구하였다. 자료는 모두 통계청에서 발췌하였고, 기간은 1998년-2011년 월별자료이며, 시계열분석 기법인 자기회귀오차모형으로 분석하였다. 소비자물가 분석을 위한 설명변수는 9가지 경제변수인 경기동행지수, 미국환욜, 생산자물가지수, 원유수입단가, 원유수입물량, 국제경상수지, 수입물가지수, 실업율, 화폐통화량을 사용하였다. 분석 결과, 자기회귀오차모형으로 각 지역별 소비자물가지수를 46%-52% 정도 설명할 수 있다. The consumer price index (CPI) data is one of the important economic measurement of the country. In this article, the Autoregressive Error (ARE) model has been considered for analyzing the monthly CPI data at Seoul, Pusan, Daegu, and Gwangju Cities in Korea, In the ARE model, nine economic variables are used as the explanatory variables for the CPI data set. The nine explanatory variables are CCI (coincident composite index), won-dollar rate, producer price index, oil import price, oil import volume, international current account, import price index, unemployment rate, and amount of currency. The result showed that the monthly ARE models explained about 46-52% for describing the CPI.

Do disaggregated CPI data improve the accuracy of inflation forecasts?

In this paper, we evaluate the role of using consumer price index (CPI) disaggregated data to improve the accuracy of inflation forecasts. Our forecasting approach is based on extracting the factors from the subcomponents of the CPI at the highest degree of disaggregation. The data set contains 54 macroeconomic series and 243 CPI subcomponents from 1992 to 2009 for Mexico. We find that the factor models that include disaggregated data outperform the benchmark autoregressive model and the factor models containing alternative groups of macroeconomic variables. We provide evidence that using disaggregated price data improves forecasting performance. The forecasts of the factor models that extract the information from the CPI disaggregated data are as accurate as the forecasts from the survey of experts.

Does Quality Adjustment Matter for Technologically Stable Products? An Application to the CPI for Food

Most indexes in the Consumer Price Index (CPI) use a form of the “matched-model” approach. It is frequently assumed that this approach accurately reflects inflation for items that have no major trend in quality. In this paper we investigate that hypothesis using CPI data for retail food items. We find that CPI analysts may be correct on average when they decide that new and replacement items are similar in quality. We also find, however, that when sample items are replaced by items of significantly different quality the CPI imputation procedures may underestimate price change and overstate quality change.

Discussion

Discussion

The Relative City Price Convergence in Pakistan: Empirical Evidence from Spatial GLS

It is evident from general experience that price of same good may differ considerably among countries, regions, cities in same country and even adjacent shopping malls and outlets. It is also common knowledge that stronger competitive forces and information about market price tend to ensure convergence of prices. In the presence of these forces price differentials cannot be persistent and are hence short lived. The recent literature on price convergence has focused on country studies using regional commodity prices and Consumer Price Index (CPI) data.1 The analysis of relative prices or real exchange rates between regions or cities in a country has certain advantages in estimating Purchasing Power Parity (PPP) puzzle. There are no trade barriers and non tradable goods in a single country. Krugman and Obstfeld (2007) consider transportation costs, trade barriers and goods market segmentations as obstacles to hold international Ppp.Furthermore they mention that countries have different endowments, baskets of goods and consumption weights in their inflation index. So PPP may not hold even if there are no non tradable goods and barriers. The PPP theory is related to the law of one price through arbitrage of international goods. The estimation of real exchange rates among countries shows that the convergence towards PPP is very slow.2 This study attempts to use overall Consumer Price Index (CPI) data on 35 Pakistani cities from July 2001 to June 2008 to estimate relative city price convergence with Karachi and Lahore, two numeraire cities. The case of Pakistan is interesting primarily due to the following reasons.

Regional Consumer Price Differences Within Germany

Summary Every month the Consumer Price Index for Germany (CPI) provides comprehensive and detailed information regarding the price development over time. However, when differences in the price level across regions in Germany have to be analysed at a given point in time, sufficient information is not available at present. Interest in regional consumer price data is shown by both scientists and policy makers. Currently, this information demand is not met as regional consumer prices or regional price comparisons are not provided by the Federal Statistical Office in Germany. Data available from the German Consumer Price Index is suitable to follow the price development over time but cannot be used directly to compare price levels of different regions because the goods tracked may be different from region to region. The article first considers the information demand and gives an overview of existing price data. Its main part refers to an empirical study which was conducted to check if existing Consumer Price Index data can be used to calculate regional consumer price comparisons by ex-post selecting comparable products.

Deviations from the Law of One Price across Cities: Testing for a Border Effect in Persistence and Volatility

In this paper, we test for border effects in deviations from the law of one price. With respect to the AR(p) representation of deviations from the law of one price, we test for a border effect in both the sum of the autoregressive coefficients (persistence) and the variance of the disturbance term (volatility). Using consumer price index data for a large number of categories of consumer goods and services for Canadian and U.S. cities from Engel and Rogers (1996), we first use the Hansen (1999) grid-bootstrap procedure to generate median-unbiased estimates of the persistence and volatility in deviations from the law of one price for every city pair and CPI category. We then estimate cross-section regression models across city pairs for the estimates of persistence and volatility for each CPI category, and we find that (after controlling for the distance between cities) crossing the Canadian-U.S. border leads to significant increases in both persistence and volatility for nearly all of the CPI categories. We also document a border effect in both persistence and volatility using the aggregate consumer price index data for European cities from Engel and Rogers (2001).

Multi-horizon inflation forecasts using disaggregated data

In this paper we use multi-horizon evaluation techniques to produce monthly inflation forecasts for up to twelve months ahead. The forecasts are based on individual seasonal time series models that consider both, deterministic and stochastic seasonality, and on disaggregated Consumer Price Index (CPI) data. After selecting the best forecasting model for each index, we compare the individual forecasts to forecasts produced using two methods that aggregate hierarchical time series, the bottom-up method and an optimal combination approach. Applying these techniques to 16 indices of the Mexican CPI, we find that the best forecasts for headline inflation are able to compete with those taken from surveys of experts.

Relative price convergence among US cities: Does the choice of numeraire city matter?

Using annual consumer price index (CPI) data for 17 US cities between 1918 and 2007, this paper examines the implications of the choice of numeraire city for the behavior of relative prices across cities. A common factor representation of relative price is used to understand the nature of the dynamic behavior of relative prices. This paper finds overwhelming evidence of convergence in relative prices with Atlanta, Chicago, and Los Angeles as the numeraire city. Further, with Boston, Cincinnati, Houston, San Francisco, Seattle, and St. Louis, the lack of convergence in relative prices is found to be driven by the nonstationarity of the common factor. In contrast, with New York, Philadelphia, and Portland, while the common factor is stationary, the idiosyncratic components are unit root processes. This paper further investigates the implications of the choice of numeraire city by estimating the half-life with different numeraire cities, after correcting for the small-sample and the time aggregation bias. These half-life estimates are smaller than those reported in previous studies and they vary depending on the choice of numeraire city. The relative price volatility seems to hold some promise for explaining why the choice of numeraire city matters for the unit root results or the half-life estimates.

A self-tuning model for inflation rate dynamics

A regime-switching model is proposed to capture the structural changes in inflation dynamics. We apply a special version of the EM algorithm to find optimal parameter estimates of the model within the framework of a discrete-time finite state Markov chain that governs the switching of regimes from one state to another. The model is implemented to Canada’s consumer price index (CPI) data series and its performance is assessed by comparing its one-step ahead predictions with the actual data. We found that, within the dataset studied, a two-state Markov-switching model is sufficient to capture the dynamics of Canadian CPI series. The model being proposed is adaptive as parameters are updated upon the arrival of a new set of information. A description of how to calculate the standard errors for parameter estimates using the Fisher information matrix is provided. We also determine the optimal number of states for the Markov chain within the dataset considered via the AIC analysis.

CPI vs. PPI: Which drives which?

The consumer price index (CPI) and producer price index (PPI) are interrelated but significantly different concepts. Relationships between the two indices may be that of causality or non-causality. The paper conducts a Granger-causality test on China’s CPI and PPI data for the period from January 2001 to August 2008, and finds that CPI Granger causes the change in PPI, and the latter reacts to the former with a time lag of 1–3 months. The result may suggest that in contemporary Chinese economy, demand-side factors have played a more important role than supply-side factors, although the two sides both have influences on domestic inflation trend which is measured by CPI.

Do Producer Prices Cause Consumer Prices? Some Empirical Evidence

The main purpose of this paper is to examine the relationship between consumer price index (CPI) and producer price index (PPI) in Malaysia. This research considers monthly data of consumer price index and producer price index from January 1986 to April 2007. The Johansen cointegration method suggests that there is long-run equilibrium relationship between these two variables. Both Engle Granger and Toda-Yamamoto causality tests find that there is uni-directional causality running from PPI to CPI.

Purchasing power parity in Korean city panels with disaggregate price indices

We examine whether the purchasing power parity holds between Korean major cities. We use the disaggregated consumer price index data for Korean cities including 13 tradable or nontradable goods. We apply panel unit root tests of Maddala and Wu (1999), Choi (2001) and Im et al. (2003). From the empirical result, we are able to reject the nonstationary null hypothesis for six of eight tradable goods and for two of five nontradable goods at the 10% level. Thus we could conclude that the theory holds between Korean major cities. Also, it holds more for tradable goods than nontradable goods.

The Minimum Wage, Restaurant Prices, and Labor Market Structure

Using store-level and aggregated Consumer Price Index data, we show that restaurant prices rise in response to minimum wage increases under several sources of identifying variation. We introduce a general model of employment determination that implies minimum wage hikes cause prices to rise in competitive labor markets but potentially fall in monopsonistic environments. Furthermore, the model implies employment and prices are always negatively related. Therefore, our empirical results provide evidence against the importance of monopsony power for understanding small observed employment responses to minimum wage changes. Our estimated price responses challenge other explanations of the small employment response, too.