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n a sense of the economic significance consider the us experience between 2004 and 2007 labour productivity grew by 1 2 per year but labour reallocations made a negative 0 3 percentage point contribution over the same period private credit to gdp grew by 4 5 per year taking the estimates at face value if credit to gdp had grown by only 1 5 the drag on productivity growth would have been eliminated they re saying we used too much credit bis one bank to rule them all bis says private credit use was excessive bis says private debt was excessive bis this is big posted by the arthurian at 4 00 am 0 comments monday august 22 2016 debt service and labor productivity projections here s the graph i couldn t get right for yesterday s post x axis was messed up the blue line shows household debt service 1980 thru 2015 the black line is a debt service trend line showing the future debt service that i anticipate same as yesterday the brown line shows labor productivity 1980 thru q2 2016 the bright red line shows my general expectation for future productivity q2 2016 thru q4 2020 also bright red the productivity data for q4 1993 thru q2 1998 the data i copied and showed again as future productivity graph 1 debt service and labor productivity projections by the time we get to 2020 the economy will be great the person we elect president in 2016 will be easily re elected in 2020 and we ll all be happy again for a while until debt goes too high once again and we have another financial disaster anything else the excel file posted by the arthurian at 4 00 am 0 comments sunday august 21 2016 potential productivity since 2007 the rate of productivity growth has been disappointing john cassidy writes in the new yorker since 2010 it has been extremely disappointing here s a close up of productivity growth since the start of 2011 graph 1 productivity growth 2011 q1 thru 2016 q2 the linear trend line is very flat at 0 5 percent productivity is low and not improving what s more the last few readings show a downward trend extremely disappointing as john cassidy says but we do not know where the red line will go next it was lower in mid 2013 than it is now and it went low more quickly then it turned around and went up even faster so you never know here s a close up of productivity growth in the quiet time before the goldilocks years of the 1990s graph 2 productivity growth 1993 q1 thru 1995 q1 the linear trend line is very flat at 0 5 percent productivity low and not improving the last few readings show a downward trend productivity growth was disappointing just like the first graph here s a close up that picks up where graph 2 leaves off graph 3 productivity growth 1995 q1 thru 1997 q1 the linear trend rises from 0 5 percent to nearly 3 in two years you never know to my way of thinking graph 1 our time is very much the same as graph 2 the early 1990s but i think we are at the end of graph 2 and ready to start graph 3 that makes all the difference oh come on you are saying graph 2 shows only a couple years graph 1 shows almost six years there s no comparison the slump is endless this time it s not endless that s the point the quiet time before the vigor is longer this time about 2½ times as long my guess i m telling you we are at the end of the quiet period soon we will see productivity start to climb just as on graph 3 on friday i showed productivity growth with bright red circles around the two quiet times the recent years and the early 1990s our low productivity has lasted much longer than that of the 1990s graph 4 productivity and debt service yes and it shows that the bottom in the dull red debt service curve has also lasted much longer this time but you can see from the shape of that curve that it wants to go up and you can see from the early 1990s that when the debt service curve goes up it goes up quickly and productivity goes up with it and the economy becomes vigorous i expect that debt service will soon rise sharply productivity will improve just as happened in the mid 1990s and the economy will again be vigorous graph 5 the recent years if we want to understand the productivity problem we have to look at it in context what context i suggest we use household debt service for context the recent years of debt service show a remarkable drop from the late 2007 peak debt service fell rapidly to a sharp down spike at the end of 2012 after the bounce back from that down spike the path of debt service was different the rapid decline had ended it had reached a bottom it was running flat if you look you can see that debt service since the beginning of 2013 shows a fairly smooth curve the curve bottoms out just at the end of 2014 then starts to rise to my eye debt service drifted downward less quickly in 2014 than 2013 then turned and started drifting upward in 2015 started drifting upward last year curse the luck the debt service data ends with 2015 we don t have first and second quarter 2016 numbers that let us see what s really happening but i think 2016 will drift upward a little more than 2015 continuing the pattern that began at the start of 2013 and i think that after 2016 debt service will rise even faster that s when we ll start to feel the vigor that s when we ll see the improved productivity here i mirrored the curve on this next graph to show the kind of future i expect graph 6 our near future just to give you an idea i should say though that if debt service rises as far and as fast as this graph suggests then the recession bar after 2025 will be even wider than what the graph shows and the recession more severe than the last one but you take my point if the debt service curve is going down then going down more slowly then going up instead of down then going up more quickly this is what the graph must look like and if debt service goes up and up productivity will improve and the economy will show vigor for a while at least i took the eight data values for 2014 and 2015 the slowly down and slowly up drift in the curve and used those eight values to create a trend line in excel the trend line runs into the past and future to show where debt service will be and where it would have been if those eight values determined the path of debt service graph 7 household debt service and the 2014 2015 trend the original eight values are shown in red at the end of the blue line just at the bottom of the u shaped trend line going forward the u shaped trend provides an estimate of the future path of the blue line the future path of household debt service going backward the u shaped line is not an exact match to the blue line during its rapid 2007 2013 fall but the lines are close enough to make you stop and think and that means the right side of the u curve the side that imagines the future is likely also a pretty good estimate time will tell in the meanwhile i have to look i have to see if i understand what s going on i have to see if i understand the economy i made a screen capture of household debt service in the 1990s so we can look at the dip bottom and recovery dbr of that time it is shown here in place in the 1990s as a dotted green line in a black box overlaid on the original blue line graph 8 capturing the dip bottom and recovery of the 1990s i took that image of the 1990s with the green dots there took that image and scaled it up by a factor of 2 5 that is 2 5 times as tall and 2 5 times as wide then i moved it so that the dip of the 1990s lines up with the 2007 2013 dip on the blue line graph 9 looking at current conditions as 2½ times the size of the 1990s conditions the green dots the 1990s data scaled up by a factor of 2 5 the green dots make a very good match to the 2007 2013 downtrend of the blue line a very good match the green dots also suggest that the debt service recovery will happen sooner than excel s u curve says this makes me stop and think excel s u curve is based on the most recent two years of debt service data only two years of it but the most recent two years perhaps the debt service recovery will not come as quickly this time as it did in the 1990s that seems a reasonable conjecture excel s u curve seems to me a better bet than my scaled up green dots from the 1990s so i grabbed the image of the 1990s again and stretched it still 2 5 times as tall but this time 3 times as wide three times the duration i fitted the green overlay to the blue line as before graph 10 looking at current conditions as 3 times the duration of the 1990s conditions the scaled up green dots from the 1990s align with the 2007 2013 fall of the blue line as before and this time the green dots of the 1990s recovery align quite nicely with excel s u curve what does it mean really really it means nothing it s a prediction still if the prediction turns out to have been correct it means maybe i do have a pretty good handle on the economy time will tell it all comes down to prediction on my part you don t expect the economy to pick up you don t expect vigor you don t expect productivity to rise i look at debt service in the 90s and say that pattern is being repeated right now no you say the economy is different since the crisis and you are right different it is maybe things won t pick up this time maybe the economy will stay as flat as my recent blogger stats but everything i read tells me that people are tired of this washed out recovery which is less a recovery than a continuing depression people are tired of it people are ready for recovery nobody believes me when i say vigor but everybody s ready for it it will happen it won t happen because of my charm and wit but it will happen it will happen because people are ready for it nobody was ready yet in 2010 everybody wanted it but everybody knew vigor was unrealistic today people don t say vigor is realistic but everybody wants it we re not saying vigor is possible but we re hungry for it you know what that is that s expectations expectations have turned can vigor be far behind the excel file for the first three graphs makes use of the fred series ophnfb_pc1 nonfarm business sector real output per hour of all persons percent change from year ago quarterly seasonally adjusted posted by the arthurian at 4 00 am 0 comments friday august 19 2016 productivity and debt service this graph shows productivity i have circled the low productivity of the past few years and also the low productivity of the 1990s in the years before goldilocks graph 1 productivity when i take that graph and add household debt service to it you can see that the circled years of low productivity are quite obviously related to the lows in debt service graph 2 productivity and debt service need i say more posted by the arthurian at 4 00 am 2 comments thursday august 18 2016 low debt service plus growing debt equals productivity the red line is productivity shown as percent change from year ago graph 1 household debt debt service blue and productivity red the blue line combines the household debt service ratio and the growth of household debt the two lines don t always match mostly because of the big spike in productivity that we typically get after recessions but set those spikes aside and the lines do at least hint at similarity the red oval mid graph highlights productivity and debt conditions during the goldilocks years the red oval on the right shows debt conditions even lower now than during 1993 1995 so there is plenty of room for things to go up productivity has been low since 2011 as the graph shows but productivity was also low after debt conditions bottomed out in the early 1990s just before the goldilocks years productivity is going to pick up soon posted by the arthurian at 5 11 am 4 comments wednesday august 17 2016 illicit use of the hodrick prescott the hodrick and prescott 1980 1997 filter hereafter the hp filter has become a standard method for removing trend movements in the business cycle literature i m reading notes on adjusting the hodrick prescott filter for the frequency of observations a short pdf by morten o ravn and harald uhlig the paper is 2002 by the president and fellows of harvard college and the massachusetts institute of technology so they re probably right most applications of this filter have been to quarterly data but data is often available only at the annual frequency whereas in other cases monthly data might be published this raises the question of how one can adjust the hp filter to the frequency of the observations so that the main properties of the results are conserved across alternative sampling frequencies their topic is tweaking the hp calculation to allow for different data frequencies i use kurt annen s vba code in excel to do the hp calculation the code creates a function named hp that does all the work all you have to give it is the range of source data and a constant the constant is how you allow for different data frequencies changing the constant changes the amount of smoothing you get when you graph the results the trick is to use the right value for the constant i ve always used the values 100 for annual data 1600 for quarterly data and 14400 for monthly data something i picked up from the eviews user forum a while back i have some old notes on it i shouldn t say i always use those values i always start with those values sometimes i change them for examples of how changing the value of the smoothing constant affects the results see this old post in this recent post i show why for one graph of monthly data i abandoned my usual monthly constant of 14400 in favor of my default annual value 100 the larger value smoothed all the information out of the result like kruger smoothing the head off a statue on seinfeld for quarterly data ravn and uhlig say the value 1600 is commonly used it seems 1600 is the value mr hodrick and mr prescott used in the article that introduced the hp filter but for annual data ravn and uhlig note four different values 100 400 10 and their own personal favorite 6 25 we then show that our recommendations work extremely well on u s gdp data using a value of the smoothing parameter of 6 25 for annual data and 1600 for quarterly data produces almost exactly the same trend this leads us to reconsider the business cycle facts reported in earlier studies as an example we cast doubt on a finding by backus and kehoe 1992 using a constant of 6 25 rather than 100 for annual data the authors produce almost exactly the same trend that they get for quarterly data with a constant of 1600 sounds good but let me ask do you really want to get the same hp trend for the two series on this graph graph 1 quarterly blue and annual red rgdp i don t think so the quarterly trend should show more detail maybe if i m looking at 50 years of data i d want to think of the trend for the data and it should be the same for both annual and quarterly but if i m focused on only a few years of data it s probably because i m looking for more subtle differences and i d want to see more wiggle in th...
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