scholarly journals Using Scanner Data to Improve the Quality of Measurement in the Consumer Price Index

2013 ◽  
pp. 17-38 ◽  
Author(s):  
William J. Hawkes ◽  
Frank W. Piotrowski
Keyword(s):  
Price Index ◽  
Consumer Price Index ◽  
Scanner Data

scholarly journals How Frequent Are Small Price Changes?

2014 ◽  
Vol 6 (2) ◽  
pp. 137-155 ◽  
Author(s):  
Martin Eichenbaum ◽  
Nir Jaimovich ◽  
Sergio Rebelo ◽  
Josephine Smith
Keyword(s):  
Price Index ◽  
Consumer Price Index ◽  
Empirical Work ◽  
Cost Models ◽  
Scanner Data ◽  
Micro Data ◽  
Price Changes ◽  
Nominal Rigidity ◽  
Menu Cost ◽  
Litmus Test

Recent empirical work suggests that small price changes are relatively common. This evidence has been used to criticize classic menu-cost models. In this paper, we use scanner data from a national supermarket chain and micro data from the Consumer Price Index to reassess the importance of small price changes. We argue that the vast majority of these changes are due to measurement error. We conclude that the evidence on the prevalence of small price changes is much too weak to be used as a litmus test of nominal rigidity models. (JEL C82, E31, L11, L81)

scholarly journals Tests for Price Indices in a Dynamic Item Universe

2019 ◽  
Vol 35 (3) ◽  
pp. 683-697
Author(s):  
Li-Chun Zhang ◽  
Ingvild Johansen ◽  
Ragnhild Nygaard
Keyword(s):  
Price Index ◽  
Consumer Price Index ◽  
Scanner Data ◽  
Price Indices ◽  
Cost Of Living ◽  
Quality Change ◽  
Large Index ◽  
New Goods ◽  
Cost Of Living Index ◽  
Index Family

Abstract There is generally a need to deal with quality change and new goods in the consumer price index due to the underlying dynamic item universe. Traditionally axiomatic tests are defined for a fixed universe. We propose five tests explicitly formulated for a dynamic item universe, and motivate them both from the perspectives of a cost-of-goods index and a cost-of-living index. None of the indices that are currently available for making use of scanner data satisfies all the tests at the same time. The set of tests provides a rigorous diagnostic for whether an index is completely appropriate in a dynamic item universe, as well as pointing towards the directions of possible remedies. We thus outline a large index family that potentially can satisfy all the tests.

scholarly journals Price Statistics Compilation in 196 Economies

2019 ◽  
Vol 19 (163) ◽  
Author(s):  
Francien Berry ◽  
Brian Graf ◽  
Michael Stanger ◽  
Mari Ylä-Jarkko
Keyword(s):  
Policy Analysis ◽  
Price Index ◽  
Consumer Price Index ◽  
Economic Indicator ◽  
International Standards ◽  
Social Benefits ◽  
Scanner Data ◽  
Producer Prices

The consumer price index (CPI) is a key economic indicator used to gauge inflation, adjust wages, pensions, and social benefits. The producer prices index (PPI) is used for forecasting and deflating GDP estimates. Both indexes are used by the Fund, policymakers, and researchers for global, regional, and domestic surveillance. In this context, the paper evaluates the soundness of the indexes by assessing four major criteria: frequency of updating the weights, the index coverage, timeliness, and the use of international classifications. We discuss online and scanner data as frontier issues. The study shows that the CPI is universally and frequently compiled, timely, and fairly-well aligned with international standards. However, the weights used to compile the index are updated in only 45 percent of economies and have national coverage in 76 percent. PPIs, compiled by only 126 economies are timely, but there is scope for continued improvement as only 36 percent of economies have updated PPI weights and approximately 67 percent maintain the recommended coverage. Outdated weights impact the reliability of the indexes for policy analysis. Frequently updated weights and well-represented coverage mitigate against biases and ensure that the indexes properly measure the price evolution in the economy.

scholarly journals Temporary Price Changes, Inflation Regimes, and the Propagation of Monetary Shocks

2020 ◽  
Vol 12 (1) ◽  
pp. 104-152
Author(s):  
Fernando Alvarez ◽  
Francesco Lippi
Keyword(s):  
Price Index ◽  
Price Level ◽  
Consumer Price Index ◽  
Monetary Shocks ◽  
Scanner Data ◽  
Optimal Plan ◽  
Price Changes ◽  
Inflation Rates ◽  
Wide Range ◽  
Menu Cost

We present a sticky price model that features the coexistence of many price changes, most of which are temporary, with a modest flexibility of the aggregate price level. Stickiness is introduced in the form of a price plan, namely a set of two prices: either price can be charged at any moment but changing the plan entails a menu cost. We analytically solve for the optimal plan and for the aggregate output response to a monetary shock. We present evidence consistent with the model implications using scanner data, as well as Consumer Price Index data across a wide range of inflation rates. (JEL D22, E31, E52, L11, O11, O23)

scholarly journals Sources of Bias and Solutions to Bias in the Consumer Price Index

2003 ◽  
Vol 17 (1) ◽  
pp. 23-44 ◽  
Author(s):  
Jerry Hausman
Keyword(s):  
Price Index ◽  
Consumer Price Index ◽  
Second Order ◽  
Order Effects ◽  
Scanner Data ◽  
Cost Of Living ◽  
First Order ◽  
Consumer Prices ◽  
Substitution Bias ◽  
Cost Of Living Index

Four sources of bias in the Consumer Prices Index (CPI) have been identified. The most discussed is substitution bias, which creates a second order bias in the CPI. Three other changes besides prices changes create first order effects on a correctly measured cost of living index (COLI). I explain in this paper that a “pure price” based approach of surveying prices to estimate a COLI cannot succeed in solving the 3 problems of first order bias. I discuss economic and econometric approaches to measuring the first order bias effects as well as the availability of scanner data that would permit implementation of the techniques.

P3814An analysis of Medicare reimbursement rates in cardiology from 2000 to 2018

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
S Bhatt ◽  
J Haglin ◽  
A S Tseng ◽  
K Mishark
Keyword(s):  
Price Index ◽  
Consumer Price Index ◽  
The United States ◽  
Medicare Reimbursement ◽  
Reimbursement Rate ◽  
Policy Makers ◽  
Total Percentage ◽  
Cardiology Department ◽  
Fee Schedule

Abstract Background There is a paucity of data regarding financial trends for procedural reimbursement in the field of cardiology. A comprehensive understanding of such trends is important as continued progress is made to advance agreeable reimbursement models in cardiology while maintaining quality of care. Purpose To evaluate monetary trends in Medicare reimbursement rates for 10 commonly utilized cardiology procedures from 2000 to 2018. Methods Reimbursement data was extracted using The Physician Fee Schedule Look-Up Tool from the Centers for Medicare & Medicaid Services of the 10 included Current Procedural Terminology (CPT) codes in cardiology. The utilized CPT codes included each of the top two most frequently billed codes in the echocardiology, catheterization, pacemaker, electrophysiology, and device integrations divisions of our local cardiology department during the 2017 calendar year. All monetary data for each code was adjusted for inflation to 2018 US dollars (USD) utilizing changes to the United States consumer price index (CPI). If the code was redefined throughout the study period, the correct replacement code was utilized for each year as defined by the procedure. The R-squared and both the average annual and the total percentage change in reimbursement were calculated based on these adjusted trends for all included procedures. Results After adjusting for inflation, the average reimbursement for all procedures decreased by 38.2% from 2000 to 2018. The greatest mean decrease was observed in transthoracic echocardiogram (−64.4%). The only procedure with an increased adjusted reimbursement rate throughout the study period was biopsy of heart lining (+60.4%). From 2000 to 2018, the adjusted reimbursement rate for all included procedures decreased by an average of 2.8% each year, with an average R-squared value of 0.81, indicating a stable decline throughout the study period. Conclusion This is the first study to evaluate trends in procedural Medicare reimbursement for cardiology. When adjusted for inflation, Medicare reimbursement for included procedures has steadily decreased from 2000 to 2018. Increased awareness and consideration of these trends will be important for policy-makers, hospitals, and surgeons in order to assure continued access to meaningful cardiology care both at the local and global level.

scholarly journals DETERMINANTS OF LIFE EXPECTANCY: ANALYSIS OF SOUTHEASTERN EUROPEAN COUNTRIES

2019 ◽  
Vol 31 (1) ◽  
pp. 193-198
Author(s):  
Marija Trpkova-Nestorovska ◽  
Nikola Levkov
Keyword(s):  
Life Expectancy ◽  
Price Index ◽  
Consumer Price Index ◽  
National Income ◽  
Gross National Income ◽  
European Countries ◽  
Life Expectancy At Birth ◽  
Quality Of Living ◽  
Per Capita

Political, social or economic factors can significantly influence the life expectancy at birth. This is important since life expectancy is an indicator of both the quality of life and one country’s development. Governments should create strategies in order to improve the quality of life, nevertheless, they should first know the main factors that determine it. Consequently, the main purpose of this analysis is to identify the key determinants of life expectancy at birth by using the cointegrated panel regression model for twelve Southeastern European countries. The research includes annual data for period 2000-2015, for twelve countries. The countries included in this analysis are Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Greece, Macedonia, Moldova, Romania, Serbia, Slovenia and Turkey. Kosovo and Montenegro are not included in the analysis due to the insufficient data for the observed period. The total number of observations is 192. The analysis examines the possible statistically significant impact that the six explanatory variables (consumer price index, employment, food production index, gross national income per capita, health expenditure per capita and immunization) may have on the life expectancy. Before the regression model is estimated, variables are tested for stationarity and cointegration. The results from the cointegrated panel regression confirm that the consumer price index, employment and gross national income per capita are statistically significant determinants that influence the life expectancy at birth in the Southeastern European countries. Consumer price index has positive impact of the life expectancy, as the life expectancy continues to increase, the demand for food also increases and so does its prices. Employment to population ratio has negative and statistically significant impact, where decline in employment is mostly due to the emigration of the active work force. While the employment rate is declining, the life expectancy, partly due to the other factors, is constantly increasing, thus the negative dependence. Gross national income has positive and statistically significant effect on the life expectancy. The result is in accordance with the expectations because greater the gross national impact per capita means better standard of living with quality housing, education, health providers, quality food. Solid economy is precondition for improvement of life expectancy and thus quality of living. Having economic factors as key determinants of life expectancy is important input while creating government policies and measures that could contribute to better quality of living.

Dampak Penerapan Perbankan Syari’ah Terhadap Pertumbuhan Ekonomi Negara: Kajian Perbandingan Malaysia dan Indonesia

2017 ◽  
Vol 1 (1) ◽  
pp. 37
Author(s):  
Hansen Rusliani
Keyword(s):  
Gross Domestic Product ◽  
Response Function ◽  
Price Index ◽  
Vector Autoregression ◽  
Consumer Price Index ◽  
Domestic Product

Penelitian ini bertujuan untuk mengetahui dampak perbankan syari’ah terhadap pertumbuhan ekonomi di Indonesia dan Malaysia. Data yang digunakan dalam penelitian ini merupakan data primer (interview) dan data sekunder dalam bentuk bulanan yang diperoleh dari Badan Pusat Statistik Ekonomi dan Keuangan Indonesia Bank Indonesia (SEKI-BI) dan Statistik Perbankan Syari’ah Bank Indonesia (SPS-BI) serta data dari Bank Negara Malaysia dan Departemen Statistik Malaysia dalam periode waktu kurun waktu 16 tahun, 2000 sampai dengan 2015. Observasi penelitian dilakukan di Indonesia dan Malaysia untuk memperkaya analisis. Penelitian ini menggunakan Vector Autoregression (VAR), Uji Kointegrasi serta dikombinasikan dengan Response Function (IRF) dan Decomposition (FEVD) untuk melihat interaksi antara faktor makro ekonomi dengan pembiayaan dalam jangka panjang. Adapun variabel yang digunakan adalah total pembiayan syari’ah (Total Syari’ah Financing) dan Gross Domestic Product (GDP) sebagai representasi pertumbuhan ekonomi. Untuk tambahan variabel digunakan Consumer Price Index (CPI) sebagai representasi tingkat inflasi. Hipotesis penelitian yaitu terdapat pertumbuhan ekonomi setiap tahunnya dikedua negara tersebut pasca krisis moneter.

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