The Consumer Price Index
Consumer Price Index is defined as the average change in consumer goods and prices that occurs over time in the prices that urban consumers pay for goods and services. In other words, the goal of the CPI, when prices change, is to measure the percentage change if the spending by the consumers to be as well off as they were before. For example, suppose the prices of all the goods went up by 5%. Consumers would have to increases the spending by 5% for keeping themselves on the same living standard, assuming everything else constant (Greenlees, J. S. & McClelland, R.B 4).
CPI as Inflation Gauge
Inflation is often defined as the trend rate of change in the prices. The change rate of prices of products, excluding energy and food prices, is common proxy for this basic definition of inflation. This definition reflects the idea that energy and food prices have more volatility than the other goods. Therefore, we can conclude that such prices show less signal of the trend rate of inflation. With regard to these findings, two trend rates are utilized to measure inflation. The two are overall consumer prices and consumer prices. It is notable that energy and food prices are not included (Dye, R. A. & Sutherland, C. 2009).
The CPI and perceived inflation
There has been criticism on CPI from a writer’s perspective in the words that the CPI is inconsistent with the research. There have been complaints for the many commentators have shown the concern that measured inflation is lower in the U.S. than another country. This shows the evidence that the growth rate of U.S. CPI is understated. One important point to remember is that one can easily gauge the accurate values of the U.S. CPI with inflation rates in the other countries is wrong as each nation has its own inflation experience. It is result of its unique economic conditions.
CPI is the most widely used measure of price level in the U.S.; however, it implicitly assumes that the expenditure function is related to a static expenditure minimization problem. The research has shown that the assumption, mentioned above, has some problems. If the consumer is active for more than that particular period, the price index should reflect the prices of future goods too, along with the prices of today. Researchers have been trying to solve the problem. A Dynamic Price Index has been proposed the recognizes the monetary cost of goods included in the cost of both, the future good and current goods (Shuhei, A. & Minoru, K, p. 959).
Among all the criticisms on CPI, the most understood and mischaracterized is its use of the geometric mean formula. Economists are agree to the fact that the price index formula of basic CPIs, used before 1999, has been overstated the changes in the cost of living, particularly the change in taxpayers index. It predates the decision of BLS to switch off to geometric means formula for the computation of most to basic CPIs (Greenlees, J. S. & McClelland, R.B, p. 6).
It has to be released in a timely manner and Bauru of Labor Statistics uses it. The CPI is used as a parameter for consumer cost of living demographics. Inflation is an upward movement in prices. Often it is observed as rather a movement in the prices of goods and services. Moreover, the CPI is a fixed weight index and overestimates the changes in cost of living. When comparing both models the Personal Consumption Expenditure Price index (PCEPI) suffers less stress from the overestimation. In fact, Consumption Expenditure Price index (PCEPI) is favored by changes in consumer prices (Richard, D, p. 2).
In short, the use of CPI as indicator of inflation has been source of controversy and misconceptions. Journals and other interested observers have been questioning the use of CPI as the operational guide and trend measures of inflation. Some countries have experienced that the core inflation trend deviat4e persistently from total CPI inflation and, therefore, is not reliable measure of inflation pressure.
Does the CPI understate Inflation?
The criticisms on CPI have been believed to be a result of misunderstanding of the methods used for the construction of the index. The attempts to make improvements are asked on the sound economic theory and research by academicians and BLS economists. The outside commissions have been reviewing the methods and statistical agency has been using them. Some writes have attributed to the changes in the methodology of CPI. A widely cited alternative is the estimate that is based on the change to CPI since 1983. This development has resulted in the lowering growth rate o inflation, by addition 4%, approximately (Greenlees, J. S. & McClelland, R.B., p. 14).
Many writers have contributed to the changes fin methodology of CPI. The use of geometric mean is one of the proposed models. It has lowered the CPI growth by 3% points. Furthermore, the use of hedonic models and OER knave lowered the growth rate of CPI by 4% points. However, it is important to note that these proposed models have been inconsistent with empirical evidence, according to BLS. The indexes computed by BLS show that the use of the geometric mean has reduced the growth rate of inflation by only -0.28% point per annum. We can also make a number of other points. Industry experts single out size and effects of the changes implemented by BLS as overestimates. The introduction to geometric mean formula has resulted in the decrease in the rate of change by 0.3 percentage points per year. On the other hand, some critics have proposed it to be 3-percentage point. Second, the changes that have been implemented by BLS have been considered the result of analysis and recommendations made over a decade, and are consistent with the international standards of statistics. It is being widely used by OECD countries and Euro stat. Third, the BLS has been publishing the details about its methods and changes to the models. In ‘Handbook of Methods’ of BLS the chapter on CPI contains information about the methods of construction of index and its history, uses, perceptions and related topics. In addition to these facts, the CPI website has included a wide variety of specialized information, for example, articles on hedonic regression models, new vehicle quality adjustment methods, fact sheet of the methods utilized in the generation of selected CPI components. The use of intervention analysis in the seasonal adjustment and the comparison of the CPI and PCE price index, are also included. The BLs also maintains the information at the both national and regional offices to respond to the questions from people (Greenlees, J. S. & McClelland, R.B, p. 16).
Basic statistical model of inflation
Empirical exercises to evaluate CPI as a measurement of inflation have been developed in the recent past. For example, Dye, R. A. & Sutherland, C. (2009) has presented the same with quietly data for prices and consumer prices without energy and food prices. The study utilized two measures of consumer prices: the Personal Consumption expenditure Price index (PCE) and the consumer price index (CPI). Both measures differ from each other in various ways. How the model aggregates the construction of an aggregate price level differs with each model and this should be noted. Trend inflation = expected value of inflation. However, the value is measurable over the next four quarters.
Dye, R. A. & Sutherland, C. 92009) have used the univariate IMA model of inflation to a bivariate model of inflation in consumer prices excluding food and energy prices and consumer prices. Consumer data, collected to pitch credible differences between both methods, the outcomes show that the relationship among overall consumer prices and consumer prices without energy and food over time has changed. To evaluate this trend properly, gauging it using recent data on price trends and consumer reaction becomes principal. The analysis is based on prices excluding energy and food price.
In short, we can conclude the simple CPI can be best utilized if the food and energy prices are excluded.
Alternative Inflation Gauge
Dye, R. A. & Sutherland, C. have presented an improvement on the CPI index that has been used to quantify the economic stress of households that they have been feeling in the days of high inflation. In the stress days of present economic situation, most of the economic stress of households is the result of decline in the household wealth. The reason for this decline is the fall in prices of housing sector. Therefore, it is appropriate to use the housing prices change in addition to CPI index. The first three quarters of 2008 have seen the bad economic conditions in most of the U.S. regions. As such, deterioration of economic condition has a down ward effect. Macroeconomics suffers a depression that is replicated on households. This is how the Household Economic Stress Index has increased. The rate of unemployment across a range of set clusters/areas is a parameter vital in context. Rate of change in the consumer price index is one parameter. Rate of unemployment act also is a parameter and work well when used along the latter. Both are core data sources. Rate in change of house prices is used as a parameter of Stress index. The study concluded that the Stress Index is useful for the analysis of the mortgage delinquencies, regionally and nationally.
Researchers have proposed a new price index ‘Dynamic Price Index’ (DPI). The DPI recognizes that the products’ monetary cost includes the cost of current goods as well as the cost of future goods. Shuhei, A. & Minoru, K. has argued that how DPI presents the inflation rate that is more volatile than CPI (p. 959). They ignored durable and multiple goods and focused on the two modifications: a focus on the Epstein-Zip utility and considering total wealth that include both human as well as financial components. These modifications resulted in more stable measures of inflation than those of the previous research.
An Integrated System of Accounts for Measuring Inflation
At present, the discussions of public, about inflation, are centered towards a very few indexes. Important among them are CPI, the index of producer prices and GDP defaulter. There is need for integration of eh system in order to measure inflation. The set of indexes, mentioned above, must b most informative. The CPI, for example, must show annual rates of inflation. Another account is to present the corresponding price levels that start from a value of some base year unity. This will show the cumulative amount of inflation and allow a quick comparison of the price levels of two periods. All price levels would deflated with a general price level system of relative prices accounts would be a genuine novelty and increase in economically meaningful information (Hillinger, C, p. 24).
Roger, M. & Zheng, D. (2010), has presented another model, recently. This model is renowned as ‘regime-switching model.’ The objective of the model is to capture the structural changes of inflation dynamics to get valid estimates. Using an advanced EM algorithm can help identify optimal parameter estimates of the model of the discrete time finite Markov chain. This governs the switching of regimes from one form to another. They implemented the model to measure the CPI data of Canada. Comparing real data with predictions helps estimate performance. They found that the used data set was sufficient to capture the dynamics of CPI series of Canada.
Works Cited
- Anderson, Magnus. “Using Intraday Data to Gauge Financial Market Responses to Federal Reserve and ECB Monetary Policy Decisions.” International journal of Central Banking (2010): 117-146.
- Dye, Ryan. & Sutherland, Ian. “A New Metric to Gauge Household Economic stress: Improving on the Misery Index.” Business Economics 44 (2009): 109-113.
- Greenlees, John. & McClelland, Robert. “Addressing misconceptions about the consumer price index.” Monthly Labor Review 13. 8 (2008): 3-19.
- Hillinger, Claude. “Measuring Real Value and Inflation.” Economics 2 (2008): 1-26.
- Kiley, Michael. “Estimating the common trend rates of inflation for consumer prices and consumer prices excluding food and energy prices.” Finance and Economics Discussion Series.
- Richard, Dennis. “The ‘inflation’ in Inflation Targeting.” FRBSF Economic Letter 17 (2010): 1-5.
- Roger, Enoka & Zheng, Daniel. “A Self-tuning model for inflation rate dynamics.” Communication in Nonlinear Science & Numerical Simulation 15. 9 (2010): 2521-2528.
- Shuhei, Aoiki. & Kitahara, Minoru. “Measuring a Dynamic Price Index Using Consumption Data” 42 (5): 959-964