Hi folks. I have been researching whether ShadowStats’s (SGS) Alternate Inflation Rate is more accurate than the CPI, and I’ve found several problems with SGS inflation. I’ve only found a few of these issues partially addressed in the public section of shadowstats.com. I sent these questions to SGS through their contact form but got no reply.
The site is http://www.shadowstats.com/alternate_data/inflation-charts
1) This blog post shows US house prices deflated by CPI-U-Research, which shows a clear housing bubble, and then prices deflated by SGS Alternate Inflation (probably 1980-based, although I’m not sure). With SGS inflation, the graph shows something ridiculous, not just no housing bubble, but real house prices declining by 60% from 1980 to 2010. Is there an error in this analysis?
If the analysis was absolutely right, then as the article says, “Now you can believe there was a housing bubble, or you can believe that Shadow Stats is trustworthy, but if you believe both you're delusional.” The question is, is it correct?
2) I read this interesting article from BLS:
“Addressing misconceptions about the Consumer Price Index”
I’ve read these articles from SGS regarding thas BLS article:
However, there are several points that make more sense in the BLS article:
2.a) Constant standard of living or constant satisfaction? The BLS report makes a point that is more convincing than SGS’ argument for a constant standard of living.
“Suppose that a person buys four candy bars each week: two chocolate bars and two peanut bars. The bars cost $1 each, so her total spending per week on candy bars is $4. Now suppose that, for some reason, the price of chocolate bars quadruples to $4, while peanut bars remain at $1. The goal of the CPI is to measure how much the consumer needs to spend each week to consider herself just as well off as she was before the price increase. A Laspeyres price index calculates the cost of the original purchase quantities: two candy bars of each type. Therefore, the answer according to the Laspeyres formula is that the consumer would need $10 to be as well off as before.”
“With $7, for example, our consumer could afford to buy seven peanut bars, one for every day of the week. Thus, $7 might be sufficient to make her as satisfied at the new prices of candy as she was with $4 at the old prices. Put another way, we can be confident that, for some consumers, the Laspeyres result of $10 would overstate the amount they need to maintain their original level of candy satisfaction.”
I don’t think anyone is going to consider buying dog food for himself just because hamburger prices are rising too fast, but if the price of steak is quintupled and the price of hamburger stays the same, many people will probably need less than 5x the money for steak in order to get the same satisfaction. For example, maybe some will prefer 50% more, buy hamburger and use the 50% extra in some other product to compensate for the satisfaction lost by not buying steak. Economic life is full of compromises and not many things are absolutely necessary at any price.
2.b) If the following is true (from the BLS article)…
“Finally, and most importantly, there is rigorous empirical evidence on the actual quantitative impact of the geometric mean formula, because the BLS has continued to calculate Laspeyres indexes for all CPI basic indexes on an experimental basis for comparison with the official index. These experimental indexes show that the geometric mean led to an overall decrease in CPI growth of about 0.28 percentage point per year over the period from December 1999 to December 2004,24”
… then the following cannot be true too (from one of the SGS articles)…
“Once the system had been shifted fully to geometric weighting, the net effect was to reduce reported CPI on an annual, or year-over-year basis, by 2.7% from what it would have been based on the traditional weighting methodology.”
2.c) Regarding hedonics, SGS’ arguments make sense, but the following paragraphs from the BLS article seem to imply that hedonics cannot be blamed much for that 7% discrepancy in inflation:
“Personal computers, microwave ovens, televisions, and other commodities for which hedonic models were more recently introduced have a combined weight of only about 1 percent in the CPI.
It is also important to emphasize that the BLS makes hedonic adjustments for declines, as well as improvements, in quality. The CPI price indexes for shelter include hedonic adjustments for the gradual aging of the rental housing units in the CPI sample, and those adjustments regularly increase the rate of change of the indexes by at least 0.2 percentage point per year.32 The hedonic adjustments in apparel have had both upward and downward impacts at different points in time and for different categories of clothing.33 As discussed in an article in the Monthly Labor Review,34 the BLS estimates that the hedonic quality adjustments introduced since 1998 have had an upward impact in five item categories and a downward impact in five. The overall impact of these newly introduced hedonic models has been quite modest and in an upward, not downward, direction”
I can't speak to the validity of ShadowStats' calculations, but the BLS explanations show that they are not really measuring anything. They are making qualitative statements and couching it in quantitative terms to give the impression that they are taking measurements.
A price index would compare prices. It would seem that the BLS is trying to compare "satisfaction", which is fine, but it certainly shouldn't be used as a proxy for inflation in GDP calculations or cost-of-living adjustments.
The notion that they can confidently state how much "satisfaction" is inherent in a chocolate bar or hamburger or a microwave oven, and then report it in numbers precise to the hundredths is ludicrous at best. Dishonest would probably be a more accurate way to describe it, in my opinion.
@penski: I can understand that you dislike the concept of “satisfaction” showing up in a measure of “inflation”. However, according to what I’ve quoted above from the BLS report, it seems that the introduction of these changes supposed to account for changes in satisfaction have had only a tiny impact, of much less than 1 percentage point per year. Of course, the BLS could lying about that too.
What I’m concerned with here is basically… Is ShadowStats’ inflation trustworthy? Is inflation anywhere near 10% now?
So I double-checked the results of this page: http://blog.jparsons.net/2011/03/shadow-stats-debunked-part-i.html
I made a Case-Shiller National house prices index adjusted by ShadowStats’ inflation (1980-based).
And I got basically the same results as the blog. The shape of my graph looks pretty much the same, and I got that my house price index adjusted by ShadowStats’ inflation DECLINES 65% from 1987 Q1 to 2010 Q4.
So if you assume that ShadowStats’ inflation is correct, then houses have been getting cheaper and cheaper since 1987, with the “housing bubble” being just a tiny tiny increment of 12% over the entire period of 2000-2005, which in 2006 resumed its long term decline on the way to becoming 3 times as cheap in just 24 years.
If the above scenario seems ridiculous, then you have to conclude that ShadowStats’ inflation is way too high, at least their 1980-based version.
ShadowStats provides 2 measures of inflation, the 1980-based (currently just under 10%) and the 1990-based (currently just over 5%). You might plaussibly argue that maybe the 1980-based version is bunk, but that the 1990-based version is actually a fair representation of real inflation. In that case, we have some issues:
* If the 1980-based version is total bunk, then why show it as an alternate measure of inflation at all? Why not just show the 1990-based version if that’s the correct one? If it’s bunk, then it shouldn’t be there, and no-one should claim inflation is close to 10% based on ShadowStats.
* The key takeaway I get from reading the links posted above from ShadowStats.com is that they claim that the government used to calculate inflation correctly UNTIL they began changing their methodology so as to underestimate inflation. Because the changes started in 1980, they provide the 1980-based version as a measure of what inflation would be like if it was calculated the way it was before the government began “fudging the numbers”. So ShadowStats does seem to imply that the “correct” measure is the 1980-based.
To sum up, no matter how you dice it, it seems to me that ShadowStats’ inflation numbers are out of touch with reality, and so, inflation is very unlikely to be anywhere close to 10%. This doesn’t mean that we can take CPI as the golden measure of inflation. Maybe the BLS is fudging the numbers. Maybe not. In any case, it’s certainly not fudging the numbers by as much as 7 percentage points per year.
If you want to check the data yourself, and I would certainly appreciate if someone tried to independently verify this, here are some tips and links:
Get the file named “U.S. National Index Levels” (http://www.standardandpoors.com/indices/articles/en/us/?articleType=XLS&... ). I got the “Not-Seasonally Adjusted” version, but I suppose seasonal adjustment doesn’t change much.
The Case-Shiller index is not inflation adjusted, so you need to adjust it yourself to either CPI or ShadowStats’s inflation. You can check that by comparing the numbers to this graph: http://www.housingviews.com/2011/09/08/inflation-adjusted-home-prices/re...
I processed the monthly data so as to get quarterly CPI data, but probably you’ll get the same big picture result if you just use annual data.
ShadowStats 1980-based inflation numbers:
The jparsons.net blog post that I mentioned, links to this file: http://www.jparsons.net/antishadowstats/Anti-Shadow%20Stats.xls
The column named “Shadow Stats Index” in the sheet “Inflation Data” is the 1980-based inflation index.
(You can verify that by going to http://www.shadowstats.com/inflation_calculator and inputting Jan 1982 and Jan 2010. The result is shown graphically but not numerically, but the graph has enough precision to allow you to verify the jparsons.net numbers with confidence. Capture a screenshot of the graph, and then count the height in pixels of the vertical bars with a graphics utility such as Paint.NET. Finally, run the numbers and you’ll get a pretty tight estimate of what should be the ratio between the value of the ShadowStats index in 2009 and in 1981, and the actual value is within the estimate’s error rate.)
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