"Measurement Problems: China's GDP Growth Data and Potential Proxies": A Big Data China Event

hello everyone uh good morning or good evening where wherever you're at um uh I'm in the Far East so it's uh it's evening here Ben but my colleagues uh uh back at csis so it's in the morning back there um and my colleagues at Stanford it's early morning there so but uh thank you for coming on to this very very I think important session uh my name is Scott Roselle I'm a co-director with home being Lee of the Stanford center on China's economy and institutions this is a joint effort of Stanford's Freeman spogly in super National studies and the Stanford Institute of Economic Policy research the objective of our Center is um uh to create an impact program that can pay that conveys policy relevant insights from the best new data-driven research to audiences Beyond Academia to inform important debates about contemporary China and about U.S China relations among other things besides research and teaching uh in our research impact group are are sort of the part of it I like the best we do a lot of things but is we've started Big Data China and that's what we're doing here today uh with um Scott Kennedy and and his very very um uh resourceful and and very informative group um Big Data China is a partnership between sky and the center for strategic and International Studies you guys know in the csis that aims to highlight policy implications of Cutting Edge scholarly work on China for the DC policy community in the U.S business community Through regular multimedia analyzes and events and today is uh another one of one of the most interesting ones that uh I think we've been put out uh this year I'm going to turn you over to Scott now he's going to inform you a little about what's going to happen today and take it Forward Scott okay uh Professor Roselle wonderful to see you and to have this partnership Big Data China uh with you and your colleagues at Stanford uh and it's wonderful to have everyone joining us uh today I'm gonna I have a PowerPoint slide I'm going to put up to uh to to continue on with the conversation here um so uh today's uh topic uh is about China's GDP growth data and potential proxies for measuring the size and direction of China's economy um you've already heard from our collaborator uh Scott Roselle uh today uh myself and my colleague Maya May are going to present uh research that we've done uh here at csis trying to understand the debate about Chinese GDP growth data and the search for additional or alternative metrics to understand the trajectory of China's economy uh uh Maya and I are going to present some of the findings first to put the groundwork uh down for everybody and then we're gonna have commentary from three leading economists on China uh Dan Rosen who's a partner at the rhodium group uh as well as a senior associate at csis in our program Ann Stevenson young who's managing principal at J Capital research and Yao Yang who's the dean of the national school of development at Peking University uh the big question that people often ask about Chinese GDP growth data is can you rely on it uh the data that I've got on the screen in front of you all right now uh is both the real numbers uh the effect if you take inflation into account that's in red and then the uh Blue Line uh I'm sorry the red is nominal and then the blue line is the real data when you take inflation into account and those numbers don't look exactly like each other and a lot of people think that uh there's a lot of water in those numbers so to speak and that for both political reasons and Technical reasons depending on Chinese official data uh is not the wisest thing to do if you really want to understand the true trajectory of China's economy this is something that folks in Washington DC uh and other capitals have worried about a lot for a very very long time particularly as China's economy at least reportedly officially gets bigger and bigger and potentially approaches and may surpass the size of the US this is of increasing interest to people so we went out uh and reviewed the literature uh collected some of our own data and interviewed some experts that literature includes a report uh that uh Dan Rosen who is with us today co-wrote uh in 2015 with one of his colleagues from the rhodium group called broken Abacus which is one of the most detailed uh analyzes of China's GDP data how it's put together how to estimate the size of of China's economy uh Tom orlick and others have also done this kind of research so we went back and reviewed these studies we collected some more data on different elements of the Chinese economy and then I think the funnest part of this project uh that that Maya May and I did was interviewing uh 15 economists uh including three of whom were with us today and we asked them about uh their views about Chinese official data about alternative potential proxies about what's what should one do in terms you know just day to day trying to understand where China's economy uh is headed um and we came up with some really interesting findings from them this group uh like all economists uh don't agree with each other on everything uh but they don't disagree wildly uh there is a weight of opinion in a certain area um that is that I wasn't expecting I thought they'd be a hundred percent all over the map uh and that there is some variation but there's more similarities uh than I expected and we'll we'll get to that uh in a little while so I think this the original source of skepticism about Chinese official data has to do with the political economy of China I think everyone is familiar uh who's watching that China's data is assembled and analyzed and presented by the National Bureau of Statistics uh based in Beijing uh the size of their organization has grown dramatically over time and so has their technical capabilities but China's a very large country a complex economy and also growth is important politically and so there are a variety of constraints on the ability of the National Bureau of Statistics to do the job that people think that they should and so that has been a central concern of of Observers if you look at the official growth data which is in red here and then look at a bunch of other unofficial estimates you'll see that particularly 10 years ago 15 years ago the official data estimates were significantly higher than the unofficial estimates over time some of those unofficial there's been greater consonants between the official data estimates and other estimates but not precise and it's actually really interesting that in 2022 the official number for real GDP growth was lower than just about what everyone expected it to be but there is still significant skepticism about Chinese data one of the measures that people used to raise concerns about Chinese data has to do with provincial officials and local officials and their tendency the incentives that they have to report high growth numbers and so if you took uh the provincial reported GDP growth numbers for each province and added them up and then compared them to the National number for a long time you saw a significant gap which we show here the yellow number is that provincial average the blue number is that what the national uh Bureau of Statistics reports for the country as a whole and you can see up until about 2016 there was a significant Gap despite you know that one year in 2007 where they were closely aligned now they're quite similar and the provincial number is actually even a little bit lower than the official number and maybe that's one indicator that things that Chinese data collection is getting better but we're not sure right so we went and interviewed uh these Scholars and we asked them uh three basic questions about what their views were about the official data about different proxies and about how we ought to proceed and what they do to follow China's economy give us some guidance and suggestions and we did find amongst many people that many of these economists significant concerns about Chinese data now there was some one who was the strongest opinion and said you know no one thinks it's reliable Chinese GDP data both Chinese GDP number and GDP growth numbers are unreliable another said that the GDP data is wildly unreliable and a political figure and another said that China's official data is particularly bad compared to other developing countries even Russia and Pakistan have better data local and provincial governments have incentives to over report their numbers uh to the central government these are things that I've already mentioned to you but I think what we found most surprising in the interviews uh let me say some other types of things that people pointed out is in terms of problems uh they said that although the National Bureau of Statistics has improved it in how it collects data compared to 10 years ago there's increasing concerns increasing concerns about data transparency and in particular people are worried about during the covid period from 2020 on uh significant incentives to hide data there's less data available to Scholars uh and that people are concerned that the 2021 and 2022 uh statistics were particularly inflated and people in terms of what they point to as most challenging is investment data and housing data which are two large drivers of growth over the last uh 30 plus years the other problem that people pointed to isn't whether or not the numbers are too high or too low but whether they flatten out and eliminate and hide the volatility that genuinely exists and so one Economist told us when the economy is bad the NBS tends to inflate the GDP numbers and when the economy is good it they tend to suppress the number and so it's this smoothing as much as whether the number's too high or too low that give people concern that said what we really found particularly interesting in these discussions is how uh more positive people were about Chinese GDP data than we expected uh in terms of improvement not necessarily absolute the best on the planet but significant Improvement uh one person said the official Chinese GDP statistics have improved over the years and are now clearly more reliable than any proxy measure I am familiar with China's GDP number is not highly precise but is not inaccurate said another person and when asked whether or not the Chinese are really trying to fix the numbers one by one uh someone said China doesn't have the skill or effort to massage everything in the data and they pointed to areas in which data collection and Reporting has improved with household consumption and services international trade and so in general people thought you know maybe the numbers aren't exactly right but if you look over time you get a significant progress compared to where things work and that official data can be genuinely helpful in in trying to understand where China's economy is headed that said uh people were not uh people still look for alternatives and one alternative they look for uh is the Lika Chiang index uh China's premier uh in 2007 or eight uh started saying that he himself needed to look at alternative sources of data to try and determine which where China's economy was going and put together what came to be known as the Lika Chang index which is a combination of data on rail Freight volume industrial electricity usage and bank loans and here you can see the combination of the Lee kachang index which is in green here along with the official data on real growth in red and nominal GDP growth in blue and you can see that in certain periods these numbers look relatively similar particularly in the last few years um and some places they look different it was in the knots uh when this was first looked at and people thought this was particularly useful but you can see some significant gaps and differences but it's surprising uh that in the last three years uh these numbers look far more similar than one would expect and maybe that's because to get to address the covid challenge that investment in physical uh production manufacturing new loans has has gone up and that may be the biggest source of growth nevertheless we went and we went and asked our uh economists that we interviewed about the Lee kachang index I had to tell you that although we did find some praise for the Lika Chang index in things that have been written both within China uh and outside China um just about none of our economists that we interviewed thought it was a useful statistic um one said it's useful but most criticized the Lika Chiang index because they thought it can't be any better than the official GDP data because they're still all coming from the same basic source and that as one said the Lika Chiang index can be manipulated too people create too much hype of this index and another person said as soon as an index becomes popular they get manipulated such as this and so I was somewhat surprised that although there's been seen progress in Real GDP in the GDP numbers there was not a lot of support for the Lika Chiang index and so that got us thinking about what other potential metrics about China's economy might people look at and one of the ones that is most interesting that we came across is Night Lights and there's been reporting about the use of Night Lights to analyze economies in other parts of the world and often that finds Distortion somewhere around 35 percent of claimed economic growth uh Maya my uh my my partner in this project uh she went and she got two pictures off of that from NASA uh looking uh at uh parts of of China this is the same place uh about two weeks apart in uh on January significant reduction in lights uh in this part of of China as a result and and so this would be a significant sign of reduced economic activity uh and so if if me if I were reading this I would say oh China's economy slowed down significantly GDP must have dropped if this is the pattern that would extend for a long period of time but this is just one view what I'm going to do now is I'm going to hand things over uh to Maya who's gonna show everybody about some of the other uh metrics uh data that we collected and how uh some conclusions that we might draw from some of those and then we'll go to our commentators uh and get their opinion so so Maya thanks for collaborating on this project uh let me turn the floor over to you foreign thank you hi um here you never see my screen okay yes so um so this is the one uh figure where we put um nominal GDP and other growth metrics side by side and um so I'm starting with the nominal GDP year-over-year growth rate and then that will compare the quantity quality nominal GDP with three groups of other growth metrics to give everybody a sense of the relationship between those metrics and how you can play around with this figure when our feature seven comes out very soon after this event so and then there's an interactive figure so everybody can try so in general there are two kinds of metrics physical and sentiment physical metrics covering uh all the Manufacturing Services and trade Etc whereas sentiment metrics reflect people's uh opinion they're both based on scientific data but they measure economic activity and performance differently so for the first group we'll start with comparing nominal GDP with the official manufacturing PMI and scroll down a menu here as well as official service PMI so PNY is purchasing manager index it provides monthly indications of economic activity through serving hundreds of companies in China about their purchasing activities and Supply situations so when we put those lines together we can see that despite pmis have more volatility since it's a higher frequency index the general trend is very similar to the official nominal GDP until the covet era when you can see a big jump a big drop in early 2020 and then a big jump in early 2021 this can help us understand why some people criticize official GDP data so much since it is unbelievably smooth when other metrics like pmis what you can see in this figure show extreme fluctuations now let's move on to the second group of comparison so we'll start with nominal GDP again and this time I'll add on uh electricity consumptions and real estate investment foreign metrics show more volatility than the official nominal GDP and their Trends we're not really aligned with Nam GDP until covet area where the three lines were moving in the same directions with very similar Trends so so far what we're seeing are actually two possible stories or explanations so if you're confident at the Quality and accuracy of the official GDP growth number you could draw the conclusion saying that those alternative metrics can be added up to form the nominal GDP growth line which is generally in the middle but if you're not that confident at the official nominal GDP growth data the conclusion you can reach you'll reach by reviewing those alternative growth metrics is that they show a more nuanced picture where different parts of economy are actually moving in different directions so both can be correct it depends on how you choose to view the subject and now let's move on to group three where I'll show you an outlier well let's put nominal GDP next to uh I'll tell Mobile sales [Music] here so a lot of people believe that car sales reflect how well the economy is doing but when we actually put it next to GDP growth line the two lines are very different as you can see um not saying that one of them um is false or fake data that you just have to make a decision on how you choose to interpret them when you have so many different metrics you can look at so again it is best to review a broad range of growth metrics instead of just relying on one single index or proxy when you're trying to interpret China's economy or making any important business decisions thank you thank you very much let me uh Maya really appreciate that let me um put my screen back up and go to one last uh slide before we go to our expert panel for for their their take um and let me just uh so some takeaways from from the work that Maya and I have done uh based on interviewing uh these economists including the three that are with us the first is don't obsess about China's GDP data it is important uh but it is not absolutely important and if you focus on the precision as opposed to the trend you you might get uh distracted from really what the value of GDP data is and um this is in in some ways China is is not unique about some of the challenges that it faces with with GDP data the second is that you need to collect and examine other quantitative data beside GDP growth data like the ones that that Maya just showed you and that we'll have in the presentation in the feature when it comes out in the next few days these aren't necessarily proxies of GDP growth but they are more granular views into different components of the economy which may be in fact more useful for observers lastly although uh we're all data Geeks and nerds and we like numbers qualitative data observation is highly valuable going to China to different parts of China to Western China rural China to second third fourth tier cities the coast to factories to stores uh observing in a systematic way not just randomly going around but systematic qualitative observation can tell you a lot that the numbers just reported on the screen from official authorities can't necessarily tell you so not only should you not overly worry about the GDP number you also need to collect other types of quantitative data and you need to in addition supplement that with looking at what China feels like on the ground which we now can do because uh you know we're now traveling and in fact uh several of us who are on the uh will be traveling to China uh next week uh for doing some of this work so let me now turn the floor over to our three commentators and and get their take on this subject we're going to start with uh Dan Rosen uh from the rhodium group uh who's done some amazing work on China's GDP data amongst everything else and then we'll turn to Ann Stevenson young who is my go-to person and has been for decades on trying to understand what China's economy really feels like tangibly uh That You Don't See always in the official data and then we're gonna go to Yao Yang who's one of China's most authoritative economists as dean of the national school of development uh to get his assessment about where we're going I'm not going to ask you all any specific questions I'm going to let you take the ball wherever in whatever Direction you all would like to go uh for you know five six minutes each and then we'll come back and we'll have a group discussion uh with with everybody on the screen at the same time so uh Dan Rosen over to you thank you Scott and um it's great to be together with this group to talk about China GDP uh questions um a perennial topic of interest to economists and businesses and um I dare say policy makers nowadays as well now these offer an overarching comment to begin you know throughout I think all of our careers call it three decades or maybe a little more than three in some of our cases um the the nuances the details like they were really interesting to us but fundamentally the sort of Direction and magnitude of China's growth didn't need a number right like everybody knew that this was a giant and growing chunk of marginal Global growth and almost every industry right uh you know um whether you could put a finer point on it was really important to us as researchers but it was you know obvious enough that this was a huge amount of growth was taking place right bigger than than most companies could imagine really addressing that market today for the first time in essentially 40 or 50 years that is no longer a reliable assumption right um growth may be slowing so much that in certainly already in many Industries it's negative it's contractionary and the so we can't just count on it being big and we're not sure how big and so just throw everything you got at it that is not that has worked more than it hasn't worked in the past it doesn't work from this point going forward and you know to some extent that is a a result of China having gotten to Middle income level where fast growth rates normally slow down right um but we also are concerned looking in the rearview mirror the past 10 years and what that tells us about the policy capacity of leadership in China to manage their wave going forward and through the middle income trap uh period without reliable ability to do GDP analysis policy will have a harder time policy makers will have a harder time and business decision makers have a harder time uh you know continuing to devote so much time to uh to China um we know I mean what we learned rhodium in working with csis in the past and the broken Abacus study that Scott mentioned is that the National Bureau of Statistics did or does understand what is required to do good national income accounting analysis of GDP it's not a question of well we have to learn how to do this they learned they understand very well and when we looked at pre-2014 data uh official Chinese data it actually gave us a very accurate count of what the level of China's GDP growth was looking back to I think 2013-20 uh 12 2013 2014 period if I remember correctly what we're looking at right if anything it understated the size of the Chinese economy a little bit has it understated how big the property bubble had been even in those years right it imputed rent for pro how we value the property sector for example I mean if if China had recognized how much even bigger property bubble had been in those years it would have been even more concerned about slowing down the property sector before it became a problem too big to solve which is kind of the story that we're living through right now in my opinion and that's number one so but while we know that they understood how to do this analysis I think we also have to say with certainty that their ability as statisticians and economists to do that work uh was hampered by political uh uh pressures in the years that followed that when my colleagues and I Logan Wright in particular have looked at GDP growth 2014 to 2019 and the stability uh in in those alliance with both Scott and Maya noted it just doesn't make any statistical sense whatsoever everyone in the world who does statistics understands statistics and math knows that it was ridiculous what was being reported the stability of growth and Chinese officials have never engaged in a reasonable discussion about those problems with the data and so coming into the pandemic period and today we have to say that you know with all the caveats uh Scott and Maya are including there's really nothing reliable in Chinese GDP accounting today to that we can confidently stand on and while it would be great if investors who are the ones that have to make you know fiduciary decisions about millions billions of dollars whether it's it's prudent to deploy it into China it would be great if they could go to China every time they considered making up an investment to travel around the country and see what things are actually going on that's not how the global economy works and it's impossible it's practically impossible to do that and you know coming up with these proxies like Night Lights I mean that has some promise for the future but even the two snapshots um that you guys are showed us there right um one of them was a week before Chinese New Year and the other was a couple days after Chinese New Year so that change in light pattern and to me like when I consider what the date was of Chinese New Year in 2020 is almost certainly to be explained um by holiday effects and all these kind of con confounding factors so you know even if I can be aware of that I I can't expect investors to be able to think all that come through what finally and then I look forward to other folks observations here um you know what what at rhodium why I think what we find most predictive of how things are going is actually neither the physical nor the sentiment approaches but credit Dynamics there's actually better more reliable data on credit volumes and pricing than there is reliable information on physical activity or sentiment both of which are highly suspect in my opinion whereas there is pretty powerful information to be found in credit market dynamics if you know how to use it and that's what's given us the best ability to look ahead and anticipate how we think economic performance is going to play through up to a year or in some cases three years ahead of time such as in the case of the credit and credibility study Scott that we did with you also back in 2018 and ended up being extraordinarily accurate in predicting when the real estate uh uh bubble was going to start to collapse um like within a month we called it I think so three years out anyway look forward to my colleagues comments and thank you for doing this work well thank you Dan super super duper helpful and over to you thanks Scott so let's see I I think that which number you look at really depends a lot on what kind of thing you're looking for um I would disagree with the idea that in the past China was was growing so much that nobody really cared I think that that's true that that's what happened but I don't think it was necessarily a good idea and therefore you find a lot of particularly consumer products companies and luxury companies that are now uh International companies as well as domestic companies that are now over invested in tier three tier four cities because they thought that this uh this this growth was just unbridled and that that the growth was was due to economic growth rather than to uh capital investment I think that there are fundamentally two problems with uh with China's statistics and I don't think it particularly matters the capability of the statisticians which I think is you know we can all agree is very high I I think there are two problems one problem is that it's not their job to report data without without uh you know just this straight up report data their job is to Target a particular number and see whether the data can can be twisted a little bit to meet that number how that number is agreed upon is is a you know sort of complex issue and has something to do with uh GDP growth but it's not the fundamental the fundamental driver of GDP analysis is not to find the real number the the fundamental driver is is a target the second problem is that the rural economy is more or less left out uh in a whole lot of areas uh employment consumption household wealth um and every time a number is sort of uh sort of sort of becomes becomes useful by mistake such as flow of funds accounting or something like that then then it gets whisked away uh because the the increasing gap between the rural and urban economies is uncomfortable and also really the the urban economy is the only one that's of of real interest to uh China China's bureaucracy and statisticians So within these problems you get nested all sorts of other problems one of them is is uh bureaucratic conflict so in real estate numbers in particular you have uh two two different streams of of data that are reported one comes from uh state-owned companies and another one comes from localities and those two streams of data are totally different and the localities have uh have all sorts of incentives to distort and and misreport as as everybody does and you find that in uh in consumption numbers in um in retail sales in a whole lot of different areas so I think that the um you know obviously I haven't haven't studied uh GDP in other countries but I do find or suspect that GDP top line numbers in China are whether accurate or inaccurate uh less useful to investors because because they're much more based on Urban uh investment than on uh on on measures of real uh wealth or well-being and so you know maybe wealth and well-being doesn't really matter if your buildings let's say an ethylene cracker if you're building a a set of retail stores to sell coffee then it really does matter um and I've got lots more that I can always say but let's stop there that's super helpful I'm going to reveal a little secret here right now which is uh one of the reasons we want to do this project is because of a dinner that I had in Beijing last September uh when I was at Bay dog giving a talk uh about some research that we did uh uh Yao Yang was kind enough to host the talk uh and the Gathering and it's not his fault that we got down this pathway but he was a facilitator of us thinking about this issue and really appreciate uh your your good offices uh for helping us interact with people in China understand what's going on uh really uh value uh your views and look forward to your comments today yeah yeah over to you first of all I really want to congratulate you and your team finishing this wonderful research um I think you have collected a lot of data and they have made usual comparisons between the DVD figures and the other figures um my sense is that particularly by looking at your figures a data quality is improving particularly when we compare code period and the 2014 2015. we see much more you know the the official data are much more aligned ways are they indicators right particularly index uh actually in 2014 2015 I had a huge doubt about the official data because I looked at the index they were huge discrepancies between the official numbers and the index right now we see more alignment between official data and the liquidation index so that's a good sign I think the major course is that uh the central leaders now emphasize more on data quality that started from several years ago when the top leaders realized and there were manipulations at the local level particularly without changing you know and the onion right so there and you know Mongolia those are three places rewind that TDP quite a lot particularly changing the official number Kenji used to be the richest city in China right but that was impossible everyone knew it but now the changing numbers are more or less correct so I think that's the most important reason Central leaders demand for higher quality of statistics but of course we cannot route manipulation from local levels and particularly this year I and password and last a year when the economy was um it's kind of you know downturn right so local leaders are still having them a little bit of data so in this case probably other indicators are useful to guard the real numbers in China I mean I have the factor with those so-called market economies and they look at the official data but in the meantime they also look at the high frequency data so with those data they try to reach kind of uh so-called correct estimate for China's GDP growth but at the Manco level I still believe the decision index is still useful if you look at the consumption electricity with some adjustments like today right the conceptual electricity is really high because it's so hard for people use air conditioners but overall I still believe is a useful index to estimate the real growth in China I don't know if uh night nice are reliable and there is a paper operation in AR you know using light data to estimate the over Report with GDP numbers and of course the paper found in non-democracy but there is a larger overstay over reporting of the GDP data but for us we actually don't believe in live data a lot because you know a lot of variations in the area like the hours you right for a certain image and other things putting together we actually don't [Music] find line data uh kind of accurate or reflected local growth okay let me stop terrific thank you so much uh wonderful comments from from all of you I think now uh CSS can put us all up on the screen the uh for a group discussion and uh really appreciate the comments that that everybody everybody gave so I want to ask a little bit more about a few things one is about proxies one is about not is about efficiency uh and and then also about data collection uh the audience has been submitting questions online and sending them uh to me I want to thank my my team in addition to Maya doing the research map rocus our program coordinator uh and others at csis who've helped again thanks to to to Skye and Scott Rosell um so I guess the first thing I want to go back to is is uh the alternative metrics and and Dan mentioned credit uh Yao young the Lika Chiang index uh I didn't think I heard from Anne yet what her alternative favorite metrics might be but I'd be curious maybe Anne if you could start uh ex with other types of numbers that you go to and then maybe if Dan and Yaya could explain why they rely on the type of things that they did mention already or things that they don't uh rely on so Ann uh I would say that uh that that I I prefer data sets that come from independent organizations such as my steel or you steal if you still still exists um I like uh high frequency data on the top level I look at um at Road Freight I think that rail Freight is of limited value because there's been such a shift toward Trucking from from trains over the last 20 years really a very dramatic shift over 20 years so I look at um at Road Freight I look at passenger traffic um and and I think Dan is correct that that credit is a good you know you want to look at numbers that um that come from the government because the government has more ability to collect those and in China Bank credit is 90 of investment uh unlike other economies where it comes from you know bonds and Equity investment and you know all sorts of private capital in China it's 90 from the bank so you can pretty much look at the banks and see how much credit they're issuing and understand a lot about the economy that's helpful so Dan maybe you could go into a little bit more about uh Bank credit you know as a as a measure of of where you think things really are is is it again because of the comprehensiveness as Ann just mentioned in terms of its dominance in the financial system um I mean I think a lot of people outside the economics World think that China doesn't have uh you know genuinely Commercial Banking and so the amount of credit that companies use um only reflects maybe government incentives or and then maybe they don't have to pay back their loans so tell us why if you may be in a little more detail why credit is such a valuable tool to understand where you think China's economy is going well first of all it's important because it is the predominant Factor input that determines China's overall growth and performance this is an investment-led system make no mistake about it right and it has been for a very long time and there are other considerations in the mix in the aggregate demographic dividends in the past and the end of those dividends today is a big consideration right and it relates to investment but investment as a factory input and the growth equation right is the independent variable right really in making sense out of what's what's happening there I think and it explains the difference between China and say India or Nigeria and other developing countries over the years China's ability through a command and control uh political economy to um uh a mass well to create Capital formation and to direct where it's going right that that explains China's growth to a considerable extent uh but in terms of what you know we think is most valuable in looking at um to to kind of to understand what government's intention is in terms of economic outcomes you have to yes look at bank credit because Bank credit is such a large value and it is determined by government policy right which sets rates for Bank credit but to get a sense of productivity in the economy and thus um the ability and with the other big variable in the growth equation right total Factor productivity that residual you don't want to look at bad credit because Bank credit is as I said as we know basically determined by Government rate setting right um instead we look at non-bank uh credit of all sorts and types Shadow banking uh credits um uh Bankers uh acceptances there there's a wide variety of um different markets for credit money and swaps and all sorts of things outside of normal Commercial Banking uh channels and for those all those other kinds of credit there is data available and that data is actually much more interesting and reflective of short-term conditions high frequency conditions than the bank uh lending rates are and the Aggregates in the banking system are and so if you really want to see if there's a squeeze on money or if uh suddenly people are losing changing their their confidence and staying keeping their money in like if people start to think that the rimminbee has nowhere to go but down against the US dollar as this happened this year to date you see that show up in various prices as people try to find ways to move out of room and B exposure into dollar exposure right and that is visible to us in credit um data of various sorts and it tells us something really powerful about which of these competing narratives that the world wants to go along China versus the world as Ann said is a little over invested and wants to hedge back on that China exposure a bit that is that that's not something that is obscured to people in the markets who know how to um track that sort of thing so it's a powerful very very powerful lens on what's what's really happening yeah let me get Yao Young's take on this and then also yeah since you mentioned the Lika Chang index we we know that Lee kachang index measures uh industry and and commerce uh production but not Services activities and apparently Services activity is a increasing part of China's economy yet you see greater alignment recently and not the data that Maya showed uh did so is it ironic that the Lika Chang index is more closely aligned with macro Trends even though uh the things that it measures are a decreasing share of the economy um of first of all is say the the two two uh indexes index uh why electricity the other one is the fruit uh volume yes uh connected by uh different uh agencies right they're not collected by MBS electricity actually is reported by the National Grid okay all the state degree uh transportation is collected by the Ministry of Transportation I don't think there is a coordination among those common agencies and so if you want to really go to the accuracy of MBS data you know you want to use the data from different resources okay so that's why I believe the coaching index is a good indicator but I want to give some carriers to backgrounds uh you know when the economy is good bank loans probably are a good indicator for economic growth in China but when time is bad like today backgrounds probably are not a good indicator uh for two reasons why is that soes get a lot of Bank credits and so is a don't invest all their capital of norms they actually divert uh you know money obtained from the bank to other Financial activities so when things are bad that you see Financial results and bank loans are circulating just the amount of financial institutions that's one another one is a local government local governments through their financial companies like local Financial vehicles borrow heavily from Banks and when things are bad local governments can easily divert backlogs for consumption not foreign investment but like today I believe right uh how big is the share no one knows right that when you pack a privately with government officials they are going to tell you right so when things are bad backgrounds I'm going to replace bank loans by uh housing sales that's actually more accurate okay interesting interesting um and let's go to uh Maya since you collected a bunch of this data for us um you looked at all these different metrics what Stan what stands out to you as a useful way to understand the trajectory of China's economy so um I think well they're all like very important but my personal favorite has to be PMI um one it reflects the sentiment uh and then the Enterprises business performance and also kind of um allows you to look into a private Enterprise business business decision as well um and then it's more like a leading um index because it's um it's monthly and then it can show a timely changes in um the business conditions and the business environment uh uh because it covers like new orders inventory production Supply Supply employment it's like a very broad comprehensive um uh information that they collect and also PMI has a service actor version which is very valuable since they're on that many good metrics for the service sector so and then also you get the official pmis and then it's heisen pmis they cover different kinds of um companies but when you look at them together I think they provide very useful information thanks a bunch hey let me ask two final questions because we're running up uh close to the hour here and these are two very different ones and folks feel free to pick whichever question that you want to as as part of your your closing uh reactions to to today's discussion the first is we've talked about measuring economic growth uh but for economists oftentimes what's less what's more important than economic growth is productivity is whether growth is achieved just by throwing more stuff that stuff or whether you're more efficient total Factor productivity and I you know China doesn't clearly report total Factor productivity data um and we're not sure how efficient China's economy is you could you can look at a variety of different metrics and and it seems to be uh that productivity is now almost irrelevant to Chinese growth based on um certain kinds of of data uh so how to crack the productivity not to understand whether it's just more investment or whether we're seeing greater productivity in terms of the use of capital or Chinese workers second question is uh China just recently issued um you know uh some new laws uh related to uh collecting data analysis account or Espionage law uh everybody knows that the environment in China is is seems to be more restrictive uh than it used to be is it going to be harder for us going forward to collect the type of data necessary to understand the trajectory of China's economy or is it it already the genie out of the bottle and we've got the credit data and other types of things and we shouldn't expect it to be more difficult um you know where how worried are you about uh your jobs as economists to tell the story of where China is going so productivity uh and uh doing research collecting data uh feel free to take either of these two uh maybe we'll start with with Ann and then why don't we start then we'll go to Yao Yang and then end with Dan Rosen gosh I'm the least qualified to answer this this is why though I like the uh the the the bank credit numbers and the official GDP number because I think you just take a proportion between those two things and you look at productivity there are economists who do much you know very deep studies on total Factor productivity but as a very very rough estimate that's that's a decent one and it shows a decline um as for whether the numbers are becoming more or less reliable well yeah I I look at I do micro analysis of particular companies and companies are having having trouble there I think that the key issue is that you can no longer just ride into China on on the assumption that uh investment is a great thing um because the you have to look at return on investment not at gross numbers Yaya um at first I I actually don't worry a lot about productivity I really don't believe many uh you know the the outcomes many studies because over the last detectives China has invested heavily into infrastructure but much of the infrastructure is just a consumption to me right like a high speed rail I swear rail does not create any [Music] production outputs but it increased the people's a welfare tremendously and we commonly haven't you went to the message to Mary in a welfare improvements are out of the high-speare Rails uh first of your second equation um you know much of the statistics uh uh are published by the Chinese official agencies right yeah usually we just get data outer like a pboc Ministry or Finance you know ministerial Transportation you just rename it so I don't think the law is going to affect the data macro analysis in China Dan you get the final word thank you Scott it's such a good discussion um look I think um the most importantly for the next phase of China's growth going forward I think we all agree that we're at a turning point Beyond which um a lot of growth as we've known it can't be taken for granted any longer it is crucial for China that it have the best possible understanding of its own GDP performance so that better policy choices can be made and they're going to be really hard ones that are very different than the kind of choices that had to be made in the past equally crucial to the rest of the world where I can say with confidence that governments I speak to in Germany and Brussels and Paris and Tokyo in uh in Washington and Canberra elsewhere are really really concerned about whether they have a enough accurate GDP information to make their policies based on economics not just based on security and political considerations of uncertainty and so this is really important good news is China I think has a terrific bunch of national income economists and professionals who are up to the job uh once there's political room for them to uh put put data back in charge of the narrative well today uh Secretary of the Treasury from the United States Janet Yellen is is on her way to Beijing and she's going to be talking with the Chinese about a lot of different issues uh uh the trajectory of the global economy uh debt relief in developing countries climate finance a bunch of things one hopes that perhaps the topic that we've discussed today about trying to really understand where China's economy is headed uh overall and in different Industries Etc might be a part of the conversation and just the expanding diplomatic dialogue can also help economists and others better understand where China is going it's in China's self-interest I think as Dan just said as as the worlds that we all have a much better that we all have as clear an idea about where uh China's economy is going as possible I want to thank Ann Dan yayang for uh offering their feedback on our feature and this topic and the work that you all do every single day to uh Scott Roselle and his colleagues at Sky for the partnership on Big Data China and to Maya for her partnership on this feature uh it's been great working with you all with you we will be publishing the feature in the next few days to the rest of my team at csis in the trustee chair and at csis Central the broadcast team who put together today's events thanks to all of you wherever you are uh morning afternoon evening thank you for joining and everyone take care cheers foreign [Music]

Channel: Center for Strategic & International Studies

Views: 16,025

Keywords: Center for Strategic and International Studies, CSIS, bipartisan, policy, foreign relations, national security, think tank, politics, Asia, China, Asian Economics, #TrusteeChair, #Event, #Virtual

Id: GA_G-6K_Kbo

Length: 64min 30sec (3870 seconds)

Published: Wed Jul 05 2023