Measuring Price Changes Research Articles

Food prices in the United States during COVID-19: generalized facts on price inflation and volatility

PurposeThe COVID-19 pandemic was a shock to the food supply chain without modern precedent. Challenges in production, manufacturing, distribution and retailing led to the highest rates of food price inflation in the US since the 1970s. The major goal of this paper is to describe statistically the impact of the pandemic of food price inflation and volatility in the US and to discuss implications for industry and for policymakers.Design/methodology/approachWe use Bureau of Labor Statistics data to investigate food prices in the US, 2020–2021. We apply 16 statistical approaches to measure price changes and volatility and three regression approaches to measure counterfactuals of food prices, had the pandemic not occurred.FindingsFood price inflation and volatility increased substantially during the early months of the pandemic, with a great deal of heterogeneity across food products and geographic regions. Food price inflation was most pronounced for meats, and contrary to expectations, highest in the western US Forecasting approaches demonstrate that grocery prices were about 7% higher than they would have been without the pandemic as of the end of 2021.Originality/valueThe research on COVID-19 and the food system remains in its nascent stage. As findings on food loss and waste, employment and wages, food insecurity and more proliferate, it is vital to understand how food prices were connected to these phenomena and affected. We also motivate several ideas for future work.

Trend Behavior of Malaysia Consumer Price Index: Evidence from National Database (2003–2022)

The Consumer Price Index (CPI) is a general indicator used to measure price changes over time. The Malaysia CPI is published using a base year of 2010. This study aimed to identify the significant trend behavior in the Malaysia CPI series for the period 2003–2022. The main question of the paper is whether there exists any difference in trends between the main and overall CPI variables? If so, is the difference significant? If so, how strong or weak is the magnitude of its trend? This is analyzed empirically through five statistical analysis methods involving the serial correlation analysis, Mann–Kendall test, Mann–Kendall sequential test, Sen’s-T test, and Sen’s estimator. Overall, we conclude that there is a significant upward trend for 11 of the 13 variables, while two variables, which are Transportation and Communication, showed no significant monotonic trend. The results of this study provide insight into a better understanding of the behavioral trends of the CPI in Malaysia. This study can help policymakers to understand the importance of increasing expenditure into certain sectors in order to have better production and with this implementation, the trend of inflation rate can be better understood.

A Machine Learning Approach to Price Indices: Applications in Commercial Real Estate

This article presents a model agnostic methodology for producing property price indices. The motivation to develop this methodology is to include non-linear and non-parametric models, such as Machine Learning (ML), in the pool of algorithms to produce price indices. The key innovation is the use of individual out-of-time prediction errors to measure price changes. The data used in this study consist of 29,998 commercial real estate transactions in New York, in the period 2000–2019. The results indicate that the prediction accuracy is higher for the ML models compared to linear models. On the other hand, ML algorithms depend more on the data used for calibration; they produce less stable results when applied to small samples and may exhibit estimation bias. Hence, measures to reduce or eliminate bias need to be implemented, taking into consideration the bias and variance trade-off.

A Comparison of Deflators for Telecommunications Services Output

La consommation de donnees a augmente de pres de 2 300 % entre 2010 et 2017 au Royaume‑Uni, et pourtant la valeur ajoutee brute reelle du secteur des services de telecommunications a diminue de 8 % entre 2010 et 2016 alors que le secteur affichait l’un des taux de croissance de la productivite les plus bas de son histoire. Ce decalage entre l’amelioration rapide des technologies et la performance economique mesuree vient en grande partie des deflateurs appliques a la production nominale. Nous comparons deux options methodologiques : premierement, une amelioration de l’indice existant des prix a la production des services de telecommunications ; deuxiemement, une methode de mesure des variations de prix fondee sur le prix moyen par unite de donnees pour differents services de telecommunications. La principale difference entre ces deux options est que le premier indice est pondere par les revenus tandis que le deuxieme peut etre considere comme etant pondere par les volumes. En utilisant ces deux methodes, nous concluons que les services de telecommunications ont enregistre une baisse de prix comprise entre 37 % et 96 % de 2010 a 2017, bien au‑dela du deflateur actuel. La production reelle du secteur est donc largement superieure a ce que les statistiques actuelles suggerent.

Disintegration of Price Ordered Probit Model: An Application to Prices of Cereal Crops in Nigeria

Swindling in prices of comestible cereal crops positively or negatively has effect on incomes and earnings, because they are the most consumable farm harvests. The instability in prices of cereal crops undoubtedly affects consumers' demands and purchasing power; producers' profitability margin. The higher their prices, the more profit accrued by farmers and the panicky effect on both domestic markets and international prices, especially to depending countries. Due to this, the Price Ordered Probit model was considered due to its ability to measure price changes of commodities. We estimated the parameters embedded in the Price Ordered Probit model via Generalized Linear Method, thereafter disintegrated the model into three components with associated estimated parameters for adequate measurement of unsteadiness in prices

Price changes of antibiotics and perceived substitutes in the context of OTC policy changes in Mexico and Brazil

Methods Study design: Quasi-experimental. Time period: January 2008-March 2013. Setting: IMS Health retail quarterly trade prices from the private sectors in Mexico and Brazil. Groups studied were: antibiotics, cough-and-cold medicines, non-steroidal antiinflammatory drugs (NSAIDs), and analgesics. The latter two groups were combined in the analysis of median price per defined daily dose (DDD). All prices were adjusted for inflation rate and converted to US Dollars. Interventions: Interrupted time series analysis to measure price changes (level and slope) after the OTC sales regulation of antibiotics and seasonal price changes. Stationarity and autocorrelation corrected using ARIMA models.

The Role of Contagion in the American Housing Boom

This paper investigates whether price spillovers across metropolitan areas were an important factor in the spreading of the last housing boom. We estimate the magnitude of those spillovers by measuring price changes in a focal market following positive shocks to neighboring markets. To identify shocks to neighboring markets, we exploit sharp structural breaks in house price growth rates. There is strong evidence of spillovers following such shocks. These effects arise mostly from very close neighbors and imply an elasticity of focal market price changes to nearest neighbor price changes of 0.15-0.33. Changes in local fundamentals cannot explain these spillovers.

Effects of the National Essential Medicine System in reducing drug prices: an empirical study in four Chinese provinces.

ObjectivesThe rapid increase in drug expenditure has become a major source of public criticism in China. In 2009, the National Essential Medicine System (NEMS) was launched in China to control drug prices and improve access to medicines. This study investigated whether and to what extent the prices of essential medicines were reduced after the introduction of NEMS.MethodsData were obtained from 149 public primary healthcare centers (PHCs) in four Chinese provinces (Shandong, Zhejiang, Anhui and Ningxia) using a facility-based survey. In total, 10,988 essential medicines were investigated. Individual price differences and a price index were used to measure price changes for three different lists: 2009–2010, 2010–2011, and 2009–2011.ResultsIn the comparison between 2009 and 2010, a median decrease of 34.4% [95% confidence interval: 30.4%–39.1%] was observed in drug prices and the number of drug sales increased by 1.5%. The higher the retail price in 2010, the more the drug sales increased compared with 2009 (χ2 = 75.9, p < 0.01). The drug revenues in 100 of the 149 surveyed PHCs decreased by an average of 39%. Where the available data allowed price changes for 2009–2011 to be assessed, drug prices were reduced significantly in 2010, but a modest decrease was seen in 2011. The Laspeyres index was less than 100 and the Paasche index was larger than the Laspeyres index in 2010 and 2011, which indicated that the frequently prescribed drugs usually had higher prices and any price reduction was milder.ConclusionsThe introduction of NEMS in PHCs in China led to price reductions in essential medicines. However, more-expensive drugs were preferred in the postreform period. Most PHCs had less drug revenue and could encounter financing dilemmas after the implementation of NEMS. Policy options such as improving the compensation mechanism and rational use of drugs should be further promoted in PHCs.

The Effect of the Hedge Horizon on Optimal Hedge Size and Effectiveness When Prices are Cointegrated

This study compares two alternative regression specifications for sizing hedge positions and measuring hedge effectiveness: a simple regression on price changes and an error correction model (ECM). We show that, when the prices of the hedged item and the hedging instrument are cointegrated, both specifications yield similar results which depend on the hedge horizon (i.e., the time frame for measuring price changes). In particular, the estimated hedge ratio and regression R2 will both be small when price changes are measured over short intervals, but as the hedge horizon is lengthened both measures will converge toward one. These results imply that, when prices are cointegrated, a longer hedge horizon will yield an optimal hedge ratio closer to one, while at the same time enhancing the ability to qualify for hedge accounting. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark 32:837–876, 2012

Evidence of a modest price decline in US broadband services

In this paper, we construct a consumer price index for broadband services in the United States using over 1500 service contracts offered by DSL and cable providers from 2004 through 2009. This exercise frames a range of open questions about measuring price changes in a manner that informs policy discussions about US broadband services. We employ approaches used commonly for constructing a consumer price index by using a mix of matched-model methods and hedonic price index estimations to adjust for qualitative improvements. We find a quality-adjusted price decline, but the evidence points towards a modest decline at most. Our estimates of the price decline range from 3% to 10% in quality-adjusted terms for the 5-years period, which is faster than the BLS estimates for the last 3 years. In contrast to other innovative industries that experience rapid price declines, such as computers or integrated circuits, the modest price decline for broadband services raises many questions.

The Effect of Mergers on Consumer Prices: Evidence from Five Mergers on the Enforcement Margin

In this paper we propose a method to evaluate the effectiveness of U.S. horizontal merger policy and apply it to the study of five recently consummated consumer products mergers. We select the mergers from those that, from the public record, seem most likely to be problematic. Thus, we estimate an upper bound on the likely price effect of completed mergers. Our study employs retail scanner data and uses familiar panel data program evaluation procedures to measure price changes. Our results indicate that four of the five mergers resulted in some increases in consumer prices, while the fifth merger had little effect.

A Wavelet Analysis of Scaling Laws and Long-Memory in Stock Market Volatility

This paper investigates the dependence of average stock market volatility on the timescale or on the time interval used to measure price changes, which dependence is often referred to as the scaling law. Scaling factor, on the other hand, refers to the elasticity of the volatility measure with respect to the timescale. This paper studies, in particular, whether the scaling factor differs from the one in a simple random walk model and whether it has remained stable over time. It also explores possible underlying reasons for the observed behaviour of volatility in terms of heterogeneity of stock market players and periodicity of intraday volatility. The data consist of volatility series of Nokia Oyj at the Helsinki Stock Exchange at five minute frequency over the period from January 4, 1999 to December 30, 2002. The paper uses wavelet methods to decompose stock market volatility at different timescales. Wavelet methods are particularly well motivated in the present context due to their superior ability to describe local properties of times series. The results are, in general, consistent with multiscaling in Finnish stock markets. Furthermore, the scaling factor and the long-memory parameters of the volatility series are not constant over time, nor consistent with a random walk model. Interestingly, the evidence also suggests that, for a significant part, the behaviour of volatility is accounted for by an intraday volatility cycle referred to as the New York effect. Long-memory features emerge more clearly in the data over the period around the burst of the IT bubble and may, consequently, be an indication of irrational exuberance on the part of investors.

CONSTANT‐QUALITY PRICE INDICES FOR AGRICULTURAL INPUTS: TRACTORS AND FERTILISERS REVISITED

This paper employs the hedonic regression technique to construct constant‐quality price indices and quality change indices for two agricultural inputs ‐ tractors and fertilisers ‐ over the period since World War II in the UK. The technique is described and related to productivity measurement in order to show its relevance for measuring price changes for inputs subject to technological improvement. Problems of application are discussed with reference to the two inputs. The constant‐quality price indices derived for tractors and fertilisers are briefly compared with available ‘official’ price series

Cost of living indices based on demand functions

In the theory of price index numbers we observe two mainlines of research. One is the so-called mechanistic approach. It takes prices and quantities as independent variables and derives price index formulas which have certain desirable properties. The other stream argues for economic cost of living indices that depend on prices and reference levels of utility. These indices ask for the expenditure necessary to reach the corresponding degree of satisfaction. In this paper we are proposing economic cost of living indices PR and PR' that are based on revealed preference considerations. We will build a bridge to mechanistic price indices by showing that several of the properties formulated in E i c h h o r n / V o e l l e r [1976] hold (slightly changed) for PR as well. S a m u e l s o n / S w a m y [1974] have shown similar results for the standard economic approach. We thereby extend results of F u c h s S e l i g e r [1984a]. In recent articles by V a r i a n [1982, 1983] and V a r t i a [1983] progress has been made in applying revealed preference theory to index number problems. By V a r i a n [1982] a utility function compatible with observed data can be approximated. If one is not interested in the utility function itself but only in measuring price changes, then one may, according to V a r t i a [1983, p. 92], proceed more directly. This is also the mainline the present paper pursues: Based on revealed preferences the income compensation function is calculated. It can be used to define price and welfare indices as well as serving as an (indirect) utility function. Hence it turns out

Consumer prices and private consumption in Poland and Austria

Starting from a bilateral comparison of consumption levels in Poland and Austria in 1964, 1973, and 1978, the authors calculate the implicit price indexes for both countries. The confrontation of the implicit and official price indexes seems to prove that official data grossly understate price inflation and overstate real growth of consumption in Poland. The causes of this discrepancy are mainly seen in the systemic difficulty of properly measuring price changes in Poland's “shortage economy.” This problem may arise in all international comparison between centrally planned and market economies when official price indices are used.

PURCHASING POWER PARITIES IN INTERNATIONAL COMPARISONS: QUANTITY vs. PRICE COMPARISONS

Just as intertemporal price indices have two functions, to measure price changes and to deflate current values to constant values, this is true also for interspatial price indices, purchasing power parities (PPPs). In practice these two functions of PPPs, for conversion and for comparing price levels, are not always distinguished, and this may have some disadvantages since in a number of cases the differences between the two PPPs might be considerable. The authors review the differences in content of the two types of PPPs, and make some suggestions for making the distinction more explicitly.

Use of Price Indexes in MRO Buying

Use of Price Indexes in MRO Buying Commodity price forecasts can be used as an effective tool in identifying potential inflation opportunities and in measuring purchasing performance for MRO materials. The use of such forecasts at the General Motors Corporation's regional purchasing operations in Detroit helps reduce cost increases by alerting buyers to potential price changes for indirect materials. The same forecasts are also used by management to provide an independent measurement of purchasing performance. Most of the commodity price forecasts are based primarily on projections made by an independent econometric forecasting firm.1 This firm forecasts price changes for approximately 150 disaggregated producer price indexes (PPI) as well as consumer price indexes and other broad-based aggregate indexes. These PPI forecasts are generated by a complex set of mathematical models that reflect the composition and interaction of specific sectors of the economy. PPI forecasts indicate anticipated price changes in the major commodity categories tracked by the U.S. Department of Labor, Bureau of Labor Statistics (BLS). Hence, since the index series used in the forecasting activity corresponds with the widely published BLS indexes, both the forecasted and historical data are compatible with numerous other data series published by the BLS and other governmental agencies. This continuity can be helpful when attempting to relate developments in indirect material price movements to other economic conditions and trends (e.g., industrial production and real growth in GNP). In order to be useful in buying and purchasing management activities, the producer price indexes must be compared with internal commodity price data based on actual purchases. The relative movement of the two series provides a basis for forecasting and measuring purchasing performance. DEVELOPMENT OF THE INTERNAL INDEX FOR PRICES PAID (IPP) Since it is impractical to track prices for each of the thousands of individual items purchased, a group of items must be selected carefully to represent a general commodity group. In actual practice, the nature and number of items selected to represent a commodity group should be based on dollar volume, consistency of item usage, and the ability to track price changes. In the example that follows, certain paper products have been selected because their dollar volumes are large, they are purchased repetitively, and their precise product specifications enable the buyer to track prices. In order to track the prices paid by GM for paper products, the IPP shown in Exhibit 1 was constructed. A review of all paper purchases during a four-month test period identified sixty items which accounted for over two-thirds of the total dollars expended for paper products. January, 1979, was selected as the base month from which to measure price changes, because price data were readily available from that time forward and the data provided an adequate historical pattern for analytical purposes. Prices for each of the sixty items were tracked from January, 1979, through April, 1980. The price for each item was then weighted to reflect the number of dollars expended for each one. This step was necessary since there was a wide variation in the amount of money spent by type of paper product. Thus, expenditures for one type of paper called offset accounted for .25 percent of the total sample, compared with 9.43 percent for groundwood, another type of paper (see Exhibit 1). The weighted value was calculated by multiplying the unit purchase price by the appropriate percent of total dollar purchases. In the case of offset, the weighted value of 8.21 was found by multiplying $32.84 by .25. The example in Exhibit 1 shows only the weighted values for January, 1979, and April, 1980, although values were calculated for each interim month. After the weighted values for each item were calculated, the values for a given month were totaled. …

BLS Consumers' Price Index and the AMS Index of Prices Paid by Farmers for Family Living. A Juxtaposition

T IS only natural that in a desire to evaluate changes in the purchasing power of farmers and of wage and salaried workers, resort should be made to the two price-deflator series published respectively by the Agricultural Marketing Service and the Bureau of Labor Statistics. Not infrequently the two series are assumed by their users to be quasi-homogeneous and this in turn tends to provoke controversy when the movements of the two indexes digress. It is proposed in this paper to examine a few selected basic characteristics of the two indexes. It is hoped that by contrasting their frameworks of reference, the techniques used in their compilation and the approaches used by their compilers to measure price changes that a better understanding of the two series may be attained. It is also hoped that the insights obtained from such analysis will be of help in the evaluation of the two series. At the outset, note should be taken of the fact that in describing what each of the two series tends to measure, their compilers rely on substantially similar language. BLS speaks of its Consumers' Price Index as a measure of the "average change in retail prices of goods, rents, and services customarily purchased by city wage-earner and clerical worker families."' In a similar vein, AMS refers to its Index of Prices Paid by Farmers, Including Interest, Taxes and Farm Wage Rates (known, for short, as the Parity Index) as a measure of "changes in the prices of goods and services bought by farm families for use in living and production."2 The Index of Prices Paid by Farmers for Family Living is, of course, one of the five subindexes of the Parity Index. Specifically, the latter is defined as measuring "average changes in prices paid by farmers on a nation-wide basis for consumers' goods."3 These definitions thus make it appear as though BLS and AMS consumer price series seek to measure the same thing-the average changes in retail prices paid, although by two different segments of the American population. Even if the methodology and techniques used to measure price movements were identical in the case of the BLS and the AMS series, some