to your HTML Add class="sortable" to any table you'd like to make sortable Click on the headers to sort Thanks to many, many people for contributions and suggestions. Licenced as X11: http://www.kryogenix.org/code/browser/licence.html This basically means: do what you want with it. */ var stIsIE = /*@cc_on!@*/false; sorttable = { init: function() { // quit if this function has already been called if (arguments.callee.done) return; // flag this function so we don't do the same thing twice arguments.callee.done = true; // kill the timer if (_timer) clearInterval(_timer); if (!document.createElement || !document.getElementsByTagName) return; sorttable.DATE_RE = /^(\d\d?)[\/\.-](\d\d?)[\/\.-]((\d\d)?\d\d)$/; forEach(document.getElementsByTagName('table'), function(table) { if (table.className.search(/\bsortable\b/) != -1) { sorttable.makeSortable(table); } }); }, makeSortable: function(table) { if (table.getElementsByTagName('thead').length == 0) { // table doesn't have a tHead. Since it should have, create one and // put the first table row in it. the = document.createElement('thead'); the.appendChild(table.rows[0]); table.insertBefore(the,table.firstChild); } // Safari doesn't support table.tHead, sigh if (table.tHead == null) table.tHead = table.getElementsByTagName('thead')[0]; if (table.tHead.rows.length != 1) return; // can't cope with two header rows // Sorttable v1 put rows with a class of "sortbottom" at the bottom (as // "total" rows, for example). This is B&R, since what you're supposed // to do is put them in a tfoot. So, if there are sortbottom rows, // for backwards compatibility, move them to tfoot (creating it if needed). sortbottomrows = []; for (var i=0; i
Just over a decade ago, we discovered the U.S. Bureau of Economic Analysis' resources for digging deeper into GDP, including applications that could break the nation's GDP down by both industry and state.
Back then, the state-level Gross Domestic Product data went by the name of "Gross State Product", or GSP, which had a major deficiency, as updates for the state level data for a given quarter were released many quarters after which they actually occurred.
That began to change in 2012, as the BEA began developing more timely updates for state-level GDP data by industry, where they seek to release data within 30 days of the release of the third estimate of national-level GDP after the end of a given quarter.
The BEA is still working toward that goal, with the new state-level GDP data, now identified as "Quarterly Gross Domestic Product By State", coming out within 2-to-3 quarters of the end of the quarter to which it applies. The most recently available data at this writing spans the period from the first quarter of 2005 through the fourth quarter of 2014, with the next data release covering the period through the second quarter of 2015 expected to be released in December 2015.
To show what kind of analysis is possible with GDP data detailed to the state level, we're going to compare the performance of the entire U.S. economy, covering all industries, with that of the state of Kansas for the period from the first quarter of 2006 through the fourth quarter of 2014.
Given the difference in the sizes of the respective economies of the entire U.S. and the state of Kansas, the way we'll do that is to compare the real, inflation-adjusted growth rates of GDP at both levels. Our first chart shows each quarter's annualized growth rate over our chosen period of interest, which allows us to fully cover a period of time spanning two full years before the onset of the so-called "Great Recession" with the available data.
In the chart above, we've indicated the quarters in which Kansas' economy experienced negative real GDP growth with the red-shaded vertical bands. The U.S.' real economic growth is shown as the dotted line, while Kansas' is shown as the solid blue line.
Overall, we see that Kansas' economy generally outperformed the economy of the U.S. in the period preceding the Great recession. Beginning with the Great Recession however, we see that Kansas' economy has generally followed the overall trend of the entire U.S. economy, with some notable exceptions.
The most significant deviation between the two occurred in 2012, where Kansas' real economic growth significantly lagged behind that of the U.S. economy as a whole.
Using the state's GDP data broken down by major industry, we quickly determined that the state's agricultural output was very negatively impacted during this period. A simple search of contemporary news sources quickly confirmed why: a multiyear drought that began in earnest in the fourth quarter of 2010 sharply intensified in 2012.
The chart below shows how Kansas' real economic growth was impacted by the drought, where we calculated the state's real GDP growth rate without the contribution of its agricultural sector, shown as the light blue line.
The BEA's state-level GDP data confirms that Kansas' economy was negatively impacted by drought in 2012. Believe it or not, the National Weather Service also recognized the drought's negative economic impact contemporaneously:
The drought has had a detrimental impact on agriculture and crops across the region. Due to a very dry fall, the winter wheat crop is already suffering. According to the Kansas Agricultural Statistics Service from late November and early December, 25% of the winter wheat across the state was in poor to very poor condition, 46% in fair condition, and only 28% in good condition; only 1% was rated excellent.
Of course, livestock suffered terribly. Livestock producers were forced to move their animals off of pasture early because the grass was gone and the water supply was depleted. As of September 10th, farmers and ranchers with cow/calf operations had been feeding hay for a couple of months. They were also forced to either deplete part of their herds or purchase high-priced feed. No doubt, the economic ramifications were significant. Cash flows on almost all livestock operations were severely impacted and in many cases operators with cattle were forced to sell livestock early which, in turn, resulted in less income. Those who held on to their cattle had to buy expensive feed which also resulted in lost revenue. Furthermore, the drought has not only had a negative impact on agriculture and crops, but also has greatly reduced water levels on reservoirs and rivers, with many areas reporting very low and in some cases record low stream flows. This has adversely affected recreational boating.
The effects of extreme drought that year would also negatively impact the state's non-durable goods manufacturing sector, as mills in the state would have less grain to process into flour, particularly in the quarters following the main harvest, which is also evident in the detailed state-level GDP data.
But we also noticed that durable goods manufacturing also experienced a downturn in that period. As it happens, Kansas' economy was also negatively affected in 2012 and 2013 by a downturn in its aerospace and defense industrial sector, which resulted in significant layoffs within the state. In our chart below, we've shown what Kansas' real GDP growth rate was for all its other industries, less its agricultural and manufacturing industries:
What we find is that after accounting for the negative economic contributions of just these two industrial sectors, the gap between Kansas' real economic growth rate and that of the U.S. as a whole narrows to fall within a range that might be expected from simple statistical noise.
As for what prompted the contraction in Kansas' manufacturing industry, we can directly identify the influence of a significant reduction in aircraft orders and deliveries to the industry's worldwide customers that disproportionately affected Kansas' aviation industry and also a reduction in defense spending on the part of the U.S. federal government, which came as part of the budget sequester that President Obama proposed for the Budget Control Act of 2011, making the downturn for aerospace and defense industries actually national in scope.
The remainder of the downturn in Kansas' economic growth in 2012 can otherwise be attributed to two very short term factors that took place in the first quarter of 2012. First, the first quarter of 2012 in Kansas was unusually warm, which reduced the contribution of utilities to the state's GDP that quarter, which was confirmed by one of the state's leading power companies in their financial statements.
The other very short term factor was a downturn in the state's real estate sector, which turned down after having peaked in real terms in the fourth quarter of 2011, thanks to the recovery of housing prices in Kansas, which had boosted the contribution of real estate to the state's economy in 2011, but less so afterward, in part because of the negative shocks experienced in the state's agricultural and manufacturing sectors.
In our final chart, we'll consider the counterfactual of how Kansas' state economy would have grown with respect to the overall U.S. economy, in which we'll show how the state's economy would have grown if its overall real economic growth had not been negatively affected by extreme drought and the results of the recession in its aerospace and defense manufacturing industries. In this chart, we've indexed the growth of both the U.S. and Kansas' economies to the fourth quarter of 2010 (2010:IV = 1.00, or 100% if you prefer), which corresponds to the beginning of Kansas' multiyear period of drought. We've also animated the chart to emphasize the difference that the fortunes of the state's agricultural and manufacturing industries make to its economic performance.
Basically, we've nearly completely accounted for the differences in overall performance between the U.S.' economy and Kansas' economy, substantiating that both severe drought on the state's agriculture and non-durable goods manufacturers and also a national recession for the state's aviation and defense manufacturers negatively impacted the state's actual GDP.
Which we point out because at least one professor at a large public university who claims to be competent in the field of economics was unable to do so. But then, that may be because they are completely unfamiliar with the detailed data on actual state-level GDP that the BEA makes freely available. Then again, based on what we've observed of their analytical ability, we believe that they would be hard pressed to discover their own ass, even if equipped with both hands and a flashlight.
Speaking of which, the only reason we're even discussing this topic today is because of a really bizarre pattern we've observed in our site traffic in recent months, extending back to at least July of this year, with the most recent episode taking place earlier this week, late at night (the timestamps shown below reflect Pacific Standard Time).
While we appreciate the repetitive site traffic, we can't help but think that the ongoing visits represent a level of knowing guilt on the part of our frequent site visitor, where the fear of our potential exposure of what could be described as blithering incompetence at best, or perhaps even purposeful deceit at worst, is keeping them from sleeping soundly at night, driving their frequent visits to our site where they hope to still find that we haven't yet addressed the matter.
We will address the matter in greater detail in a future post. When we do, will be at our leisurely convenience....
Update 6 September 2016: Talk about leisurely convenience! We didn't get back to addressing the matter in greater detail until 8 July 2016, so if you've come to this post by way of Econbrowser, hopefully following this link will help describe why the particular author who pointed you to this post is so put out. If you'd rather not click through, the short story is that we caught them engaged in a practice that some would describe as "academic fraud" and called them out on it - it's so bad that they don't even dispute their bad actions, but instead appear to be engaged in a campaign of misdirection, where they've systematically engaged in some spectacularly unprofessional and unscholarly behavior.
But even in their campaign of pseudoscience, they did raise an interesting point regarding the counterfactual analysis we presented in this post. Let's quote them from their most recent attempt at a smear attack:
Unfortunately, in his calculation of Kansas GDP excluding agriculture and manufacturing, he made an error by simply subtracting (chain weighted) real agricultural output and real manufacturing from real GDP (as discussed in the addendum to this post).
We love the title of the post he linked - at least he's being up front about what he's doing! More seriously, let's compare the results of what you get when you actually add up the subcomponents of the real GDP data that we used to produce our counterfactual in this post and compare it with the BEA's total real GDP estimate for the state.
As you can see, adding up the subcomponents of the state's real GDP would slightly overstate real GDP in the period from 2005Q1 through 2008Q3, and again briefly in 2012-Q3. At the same time, we also see that we get nearly matching results in the period from 2008-Q4 through 2012-Q3, and then we see that the results of adding together all the subcomponents of real GDP slightly understates total real GDP from 2013-Q1 through 2014-Q4. All results are within 0.6% of the total GDP reported for each quarter, with half of the results falling within half that maximum margin of error (recorded in 2007-Q4). As you would expect for data baselined in 2009, the further away you get in time with respect to the baseline period, the typically greater the error.
Looking over the entire span of data, if we calculate the compound GDP growth rate over the full 10 years from 2005-Q1 through 2014-Q4 from the results of adding up its subcomponents, the resulting 1.47% annualized rate of growth indicates a slightly slower rate of growth than what we get when we perform that math with the state's total GDP, where we get a result of 1.57%.
In other words, our counterfactual falls well within any reasonable margin of error that would be expected arising the inherent statistical errors in the underlying data that the BEA used in its reported estimates throughout this entire period of time.
That also means that our counterfactual that was based on adding up the subcomponents of the industries that contribute to the state's GDP and excluding the contributions from the agricultural and manufacturing sectors of the state's economy slightly understates the amount of GDP growth that would have occurred in the absence of drought and the state's aerospace industry microrecession that ran from 2012 through 2013, which offset the minor recovery from extreme drought in 2013..
We therefore see no need to revise the analysis to reflect the slightly higher rate of growth, because as a counterfactual, we only need it to be reasonably close to a more precise calculation, where we're on very firm ground in erring on the side of understating the amount of growth that would have occurred if the state's agriculture and manufacturing sectors had grown at rates similar to that recorded by all the other sectors of the state's economy throughout this period of time.
That also means that our spiteful critic's repeated attempts at a smear attack on this point also qualifies as junk science. Here's the applicable category from our junk science checklist:
How to Distinguish "Good" Science from "Junk" or "Pseudo" Science | |||
---|---|---|---|
Aspect | Science | Pseudoscience | Comments |
Precision | If numbers are presented in support of a scientific explanation, they must be stated with the precision and accuracy required by their level of significance as determined by known measurement error in the data from which are derived, neither more nor less. | Pseudoscience practitioners will often present numbers with a level of precision and accuracy that exceeds that supported by the known accuracy of real world data in order to give the appearance of greater validity for their claims. | A recent example of pseudoscientific deception by precision include certain economists suggesting that "a Keynesian multiplier of 1.57" specifically applies for government stimulus spending, when a wide range of studies suggest the actual multiplier may be "anywhere from 0 to 1.5" (note the difference in the number of decimal places and potential range of values!) |
We're pretty sure that it's only a coincidence that 1.57 figure keeps showing up with respect to junk science in economics!
U.S. Bureau of Economic Analysis. Quarterly Gross Domestic Product by State, 2005-2014 (Prototype Statistics).
Table: Real GDP by Stgate, 2005-2014. Excel Spreadsheet]. 2 September 2015. Accessed 19 November 2015.
General Aviation Manufacturers Association. 2013 General Aviation Statistical Databook & 2014 Industry Outlook. [PDF Document]. 18 February 2014.
Kansas Department of Labor. 2013 Kansas Economic Report. [PDF Document]. 28 August 2013.
Kiser, Becky. "'3rd Worst Drought for Kansas' According to Local Research". Hays Post. [Online Article]. 21 May 2014.
National Weather Service. Wichita, Kansas Record Breaking Heat and Drought in 2012. [Online Article]. Accessed 19 November 2015.
Said, Hashem. Map: US Struggles Through Five years of Drought. Al Jazeera America. [Online Article]. 9 July 2015.
Southwest Farm Press. Kansas October Moisture a Third of Normal. [Online Article]. 11 November 2010.
Strassner, Erich H. and Wasshouser, David B. BEA Briefing: Prototype Quarterly Statistics on U.S. Gross Domestic Product by Industry, 2007-2011. [PDF Document]. June 2012.
Westar Energy. "Westar Energy announces 1st quarter 2012 results; 1st quarter was warmest in more than 50 years." PDF Document]. 9 May 2012.
Labels: economics
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