Vaibhav Scores 770 (Q50, V44)

It has been 3 weeks since completed my GMAT. This community has helped me in preparation since day 1 so I thought it is my duty to share my experience with fellow students. Instead of going the traditional route of explaining how I prepared etc. I thought I will try something different. I am planning to share a few nuggets of experience during the preparation and point out some tips from it. If anyone has any other questions I can answer, please ask here or pm me.
And get ready for a LONG post!  

1) General preparation - So, believe it or not, I ordered the OG (officially beginning my GMAT study) some time around December 2013 (yeah, I know, its been 3 years!). However, I did not even register for the exam until Jan 2016. I started with just the OG and going through tens of forum posts on GMAT Club. I went through the OG material, started solving few random problems here and there. However, every few months, something used to come around and disrupt my preparations. It didnt help that my work was very busy with often 12+ hour days and work spilling over weekends. However, by end of 2014 I was ready, or so I felt. I had planned to take exam around Dec 10th 2014 and then go on a 3 week vacation. However, I realized around November if I do take the exam I wont be putting my best foot forward and decided to take the exam after the vacation. As it turns out, a 3- week vacation is enough for you to even forget your password to login into mba.com and I realized I had simply lost track of all my preparation. From then onward, for a few months I was preparing on and off (mostly off) and then GMAT just kind of took a backseat. Around mid 2015 I re-started the prep, realized I needed some "structure" to the prep, joined e-gmat Verbal Online course and completed it by end of 2015. Even then I did not register for the exam since it felt like I was missing some more preparation - I was getting around 700-720 but I had not exhausted all of my tests materials etc.
Around beginning of 2016, I got email from e-gmat that my subscription was going to end. but if I gave proof that I have registered for GMAT, they can extend it until exam day. This prompted (or rather forced me) to book the exam for early March and the rest is history. 

Tip: My main advice to anyone starting GMAT prep - dont start until you are in a situation where you can study for 2-3 months in such a way that you are not away from prep for more than 1 day. You may study for 1 hour or 10 hours a day but you need to be in a stage in life and with work that you study every single day. Maybe some people are different, but for me even a single day break would mess with the preparations. If you dont feel like studying some day, just browse through GMAT debriefs, go look at univ websites, read some stats from Poets and Quants or some other stuff. But make sure you login into your GMAT-mode every day until you take the test. 

2) Sentence Correction - Of all the time I spent preparing for GMAT, 75% time was spent on Verbal and of that almost 60% was spent on SC. English is not my first language, but I went to a school where English was teaching medium. I would rank myself as an avid reader of English books, novels etc. However, something in the SC section of GMAT just wont 'click' for me. I completed OG problems in all sections - twice!. I still could never get the 700+, 'hard' SC problems. Based on all the discussion on GMATclub, I ordered the Manhattan prep SC guide and completed it. At that point, I realized my accuracy in SC was somewhere close to ~50-60% on 700+ questions. This would bring my Verbal score to somewhere 37-38 on a good day and around 30-32 otherwise. I realized I needed some 'structure' to solving SC going beyond theory. I joined the e-gmat Verbal course after reading few reviews here and attending a couple of their free seminars. I will type a separate review for e-gmat but I must say their Verbal course is worth every dollar spent. It is not great as far as grammar theory is concerned (MGMAT book is excellent in that regard) but e-gmat has nailed what grammar you need for GMAT specifically. One other advantage is that they have interactive video lessons which help in preparation immensely. Anyway, I was able to get a 'method' to solving SC problems, kept following and zoning it in. Towards the end, when I solved GMAT Prep full length tests I was able to get most of SC questions right and kept scoring >40.

Tip: For every section, plan to have strategy to tackle the problems. I feel that GMAT tests an approach to problem more than anything else and some questions are designed such that only those following a known approach will get to the answer in time. Even though you get the answer during a test, go back and practice your approach on the problem. This is more important in SC and CR.

3) Integrated Reasoning - It is almost comical that I was dreading this section as my exam date approached (and feel like I may have gotten little lucky with my score), since most people just dont bother preparing for this section. One reason for this is most prep companies (including GMAT Club and e-gmat) are still not giving enough attention to this section- not as much as they give to Quant or Verbal. However, most recent news suggest that admission offices are planning to consider IR score important. Anyway, I never got a good handle on this section. On one hand, you need to solve a 2-3 part question with paragraph-long descriptions in <2.5 mins; and on other hand, there was no guessing, no skipping which would ultimately reward you. I even posted a plea on GMAT Club about this and found few people in same boat as me. I decided to do the only thing I could do - solve as many IR questions as I can. I solved all the question in GMAT's software, on e-gmat's course and several on GMAT club. I also solved few tests on 800 score which I got through e-gmat subscription. I realized I needed to get the easy questions correct on IR - the one with geometry, graphs or the ones where you need to select 2 answers one in each section etc. Either way, I did get an 8 on GMAC test and in the final exam.

Tip: Nothing specific really - if you dont know what to study in a section, just go and solve whatever problems you can get in that section! 

4) Exam Day - I am going to jump into my exam day now. My exam was starting at 11.15. I got there on time and after almost an airport security type atmosphere, went into the exam hall. (I was not expecting the examiner to ask me to turn my pant pockets out to show I dont have anything in them! ). I finished the essay and IR sections and raised my hand for a break. The very nice lady was just escorting another girl into the exam hall and came to me after around 1 minute. Now, when I took practice tests at home, I always did them timed with 8-min breaks. So I had my sandwich and chocolate bar as always, went to the bathroom across a long hallway and headed back to exam hall. What I didnt realize was I had to do the pull-your-pant-pockets out routine one more time and then the examiner walked me in the hall towards my booth. What this resulted in was that when I started my Quant section, the clock showed 55 seconds past my break-time! The unthinkable had happened! How do I justify to myself that after all this prep I was careless enough to sit outside eating chocolate while my exam seconds were ticking away!! To top it off, in the hurry, I even clicked through the initial description section which lasts for 1 minute. In my excitement I thought if I dont spend time on the information section I can use it towards the problem sets - that is not how it works and ultimately I started the test with only 73:55 mins remaining. I tried to calm myself, told myself Quant is my strong suit, and afterall 1 min is basically just 1 problem I have missed or have to guess. I started being extra careful with time, and by 10th problem I had recovered the lost minute. I think in the end I ended up guessing 1 problem which didnt matter much.
The story is not yet over. I managed to do the same thing in Verbal and was 23 seconds late. This time, I did not jump through the Information section (took full minute to calm myself down) and then started the test. I was again able to recover the lost 30 seconds.

Tip: Well, its kind of obvious but dont be late during the breaks. When practicing tests at home, try to take a 6 or 7 min break. You wont have a wrist watch on your hand when you take exam so try to mentally time the break. In the end it is better to be early and sit for couple of minutes staring at the exam screen after the break than to be late.

5) My exam-day gymnastics didnt end with just being late for both important sections Quant and Verbal. I took a nap during the Verbal section - well almost! 15-20 mins into the Verbal section, I started feeling incredibly sleepy! May be the initial exam time adrenaline had started to wear off. I also wondered if the chocolate bar I ate had some sort of sleep-inducing drug but no matter what I did I just could not control the yawns. I was afraid if I leaned on the chair I might actually fall asleep. I had managed to sleep 7-8 hours previous night. If this was a prep exam and I was studying at home I would have just done a few push-ups or jumped into air but obviously that was not an option. I had to literally fight sleep for few minutes until things got 'normal' again and I completed the exam.
In retrospect (and after my wife pointed out), I realized what happened. Almost every weekend on Saturdays, except when I took full-length tests, I always (and I mean ALWAYS) take a nap after lunch. I started my exam at 11.15 and was in Verbal section around 2pm which coincided with the time. My stupid body didnt know it was exam time and started getting dozy. I am glad I was able to fight that off and get through the 74 min 37secs of Verbal.

Tip: I know many people elsewhere on GMAT Club have mentioned but take an exam at a time of day when you are most active. For me, I had to take exam on Sat and most slots open were around mid-day time (Early morning slot was out of question, since I knew I wouldnt be able to take off from work on Fri and mostly wont get full night's sleep for an 8am exam). My advice would be if you get an exam time, make it a habit to be mentally and physically active at that time of the day/week.

6) Prep Material - Before closing this long (and probably boring) rant, let me list the prep material I used and its merits/de-merits.

a) OG - Obviously a must! I solved all sections of it twice, marked the important questions in each and went back and revised a few of them.
b) MGMAT SC - I got this for 2 reasons, one was obviously to get SC prep but other was also to get the 6 full-length MGMAT tests (more on the tests later). SC section is very detailed, systemmatic and also very boring. I found it really difficult to go through the prep questions in this book more because of the nature of problems. I know a lot of people like the SC book but I didnt find it that useful.
c) Powerscore CR Bible- Another book I got from recommendation from GMATClub members. One of the best, most logical prep books I have encountered. I am not sure how much it helped me because I was not tracking my score back when I went through the book, but I can tell you the book was a joy to go through - with every section neatly detailed with tip and in a logical fashion.
d) E-gmat Verbal Online course - Extremely useful. The course will not teach you what a gerund is or when and how to use a Past Participle in a sentence. What it will tell you, however, is that for every type of problem, what strategy is useful to solve a problem. I will post a separate review of this course elsewhere.
e) GMAT Club and GMAT Club tests - What can I say about the most amazing resource for GMAT on the planet, and that too absolutely free! GMAT Club has done a great service to all MBA aspirants with the detailed lists of everything you need from preparation strategy, experiences of past applicants, do and donts for multiple scenarios and now admission guides! GMAT Club quant tests are really good and I would say at par or slightly tougher than the real ones. Verbal tests are alright and can use some improvement in my opinion. I have also found the members very helpful in general. The kudos system is pretty good and if you spend some time you can get enough kudos to get access to GMAT Club tests.

Practice Tests.
a) I took quite a few 'free tests' initially from almost every Prep course - MGMAT, Veritas, Powerscore, Economist etc. Most of the tests are OK and help build stamina.
b) MGMAT tests - Apart from the GMAC software tests, I think Manhattan tests are the most reliable source of practice with good problems. Their quant is unnecessarily hard, confusing and has long paragraph problems which you wont get on real test, but as an indicator of an ability the MGMAT tests are very good. I did 3 of the test before getting into full gear for prep so I wont list the score here, but these were the scores in final 3 tests.
Exam 1 - 740 (Q47, V45, IR4)
Exam 2 - 700 (Q45, V40, IR5)
Exam 3 - 710 (Q48, V38, IR5)
c) GMAC tests - obviously the best indicator of the real test. My scores were identical to real one.
GMAC 1 - 770 (Q50, V44, IR8)
GMAC 2 - 760 (Q50, V44, IR8 - I got the SAME IR questions in the both GMAC tests)
Real GMAT - 770 (Q50, V44, IR8).

7) Last tip - and IMO most important - GMAT is for most people a long and time-consuming journey. No matter how hard you prepare, what score you get, people around you bear the brunt of it and you take time away from them. So after the exam, thank whoever in your life has supported you through that journey - spouse, partner, parents, kids, colleagues, God, anyone. Take some time to do something nice for them.

That is all from me. Hope this helps someone. Good luck and all the best!

Roland Fryer - Melhor ganhador da Medalha Clark da década

Roland Fryer is an influential applied microeconomist whose work spans labor economics, the economics of education, and social problems and social interactions.  His innovative and creative research contributions have deepened our understanding of the sources, magnitude, and persistence of U.S. racial inequality.  He has made substantial progress in evaluating the policies that work and do not work to improve the educational outcomes and economic opportunities of children from disadvantaged backgrounds.  His theoretical and empirical work on the “acting white” hypothesis of peer effects provides new insights into the difficulties of increasing the educational investments of minorities and the socially excluded.  Fryer is the leading economist working on the economics of race and education, and he has produced the most important work in recent years on combating the racial divide, one of America’s most profound and long-lasting social problems.

He has mastered tools from many disciplines to tackle difficult research topics.  Fryer has developed and implemented compelling randomized field experiments in large U.S. urban school districts to evaluate education interventions.  He founded EdLabs (the Education Innovation Laboratory at Harvard University) in 2008 to facilitate such efforts and continues as its director.  He has incorporated insights from psychology to formulate a new model of discrimination based on categorization, and he has used detailed historical archival research to understand the origins and spread of the Ku Klux Klan. 

The Racial Achievement Gap and Education Policies

Roland Fryer in a series of highly-influential studies has examined the age profile and sources of the U.S. racial achievement gap as measured by standardized test scores for children from 8 months to seventeen years old.  Fryer (with Steven Levitt) has shown the black-white test score gap is quite small in the first year of life, but black children fall behind quickly thereafter (“Testing for Racial Differences in Mental Ability among Young Children,” American Economic Review 2013). The racial test score gap is largely explained by racial differences in socioeconomic status at the start of schooling (“Understanding the Black-White Test Gap in the First Two Years of School,” Review of Economics and Statistics 2004), but observable family background and school variables cannot explain most of the growth of the racial test score gap after kindergarten.  Fryer’s comprehensive chapter in the Handbook of Labor Economics(2011, “Racial Inequality in the 21^st Century: The Declining Significance of Discrimination”) documents that racial differences in social and economic outcomes today are greatly reduced when one accounts for educational achievement gaps.  He concludes that understanding the obstacles facing minority children in K12 schools is essential to addressing racial inequality.  Fryer has taken up this challenge to study the efficacy of education policies to improve the academic achievement and economic outcomes of low-income and minority children.

Roland Fryer’s initial effort at designing and evaluating school-based policies focused on short-term financial incentives for students to improve measured achievement (“Financial Incentives and Student Achievement: Evidence from Randomized Trials,” Quarterly Journal of Economics 2011).  Fryer implemented and analyzed randomized field experiments in over 200 urban schools across three cities where treated students were paid for working hard (reading books in Dallas), doing well on interim standardized assessments (New York City), and earning high grades in class (Chicago).  Although students appeared to be aware of the financial incentives and self-reported to be motivated by then, the findings for all three cities were of zero mean impact of short-term financial incentives on student achievement.  Many low-income students lacked the knowledge of how to improve their performance and did not have the necessary complementary inputs (from parents, teachers, and peers) to respond to the incentives.

In “Teacher Incentives and Student Achievement:  Evidence from New York City” (Journal of Labor Economics 2013), Fryer looks at financial incentives for teachers through randomized control trials (RCTs) in New York City  (NYC) middle schools and high schools.  Fryer finds no systematic effect of traditional teacher incentives on student outcomes. The ineffectiveness of standard U.S. teacher incentive programs motivated work by Fryer (with Steven Levitt, John List, and Sally Sadoff) to try new approaches in a recent working paper.  Fryer implemented a randomized trial in 9 Illinois schools in which teachers were selected for a pay-for-performance program but where the timing and framing of the award differed randomly across teachers. He found that a “Loss” treatment – where teachers are given the bonus initially and lose all or part of it if their students do not meet performance targets -- substantially and significantly raised student math performance. A traditional “Gain” treatment had no detectable impact.  The findings suggest that the structure and faming of teacher incentives are central to their success.

The Harlem Children’s Zone (HCZ), a 97-block area in Harlem that combines charter schools with neighborhood services, has provided Fryer with a testing ground for school-based vs. neighborhood-based interventions.  Fryer and Will Dobbie have exploited the lottery used for admission to the Promise Academy (a charter school that is part of the HCZ) to examine the impacts of the charter school on student outcomes.  They find short-run improvements in math test scores that are large enough to close the racial achievement gap (“Are High-Quality Schools Enough to Increase Achievement among the Poor? Evidence from the Harlem Children’s Zone,” American Economic Journal: Applied Economics 2011). A follow-up study (“The Medium-Term Impacts of High-Achieving Charter Schools,” Journal of Political Economy forthcoming) finds similar substantial positive impacts on medium-term outcomes including college enrollment, high school graduation, and reductions in risky behavior.  Fryer and Dobbie find similar positive impacts of attending the Promise Academy for residents and non-residents of the HCZ indicating high-quality schools alone even without the other HCZ community resources can be effective.

In “Getting Beneath the Veil of Effective Schools: Evidence from New York City” (American Economic Journal: Applied Economics 2013), Fryer and Dobbie collect data on the inner-workings of 39 NYC charter schools from interviews and surveys of principals, teachers, and students, along with administrative data.  They correlate the school policies and characteristics with estimates of school effectiveness in raising student achievement from lottery-based and quasi-experimental matching estimates. They find that a bundle of five school policies suggested by their in-depth qualitative research – frequent teacher feedback, the use of data to guide instruction, high-dosage tutoring, increased instructional time, and high expectations – are strongly positively correlated with improvements in student achievement.

In “Injecting Charter School Best Practices into Traditional Public Schools: Evidence from Field Experiments” (Quarterly Journal of Economics 2014), Roland Fryer examines the impact on student achievement of bringing a bundle of the best-practices from high-performing charter schools into low-performing, traditional public schools in Houston.  Fryer implements both a school-level randomized field experiment among 18 low-performing elementary schools in Houston as well as quasi-experimental comparisons of schools getting the new practices vs. comparable Houston public schools. The findings indicate that injecting best practices from charter schools into traditional Houston public schools significantly increased math achievement in treated schools by 0.15 to 0.18 standard deviations per year (similar to the impacts of high-performing charter schools) but had little effect on reading achievement (as is the case with charter schools as well).  Fryer finds similar positive results from implementing such practices in public schools in Denver and Chicago.

Economics of Social Interactions and Acting White

Roland Fryer has developed new conceptual frameworks and empirical evidence to better understand the role of “cultural capital” in the creation and persistence of racial and ethnic group differences in educational investments and other social outcomes and behaviors.  His early work (“A Model of Social Interactions and Endogenous Poverty Traps,” Rationality and Society 2007) developed an equilibrium model of cultural capital (group-specific investments valuable for future social interactions with a peer or social group) and showed how a trade-off can arise between the accumulation of formal education and such cultural capital.  Fryer extended this framework (with David Austin-Smith, “An Economic Analysis of ‘Acting White’,” Quarterly Journal of Economics 2005) into an elegant model of peer effects and educational investments in which “acting white” (rejecting those who try too hard in school or accumulate too much education) can arise from a two-audience signaling quandary: signals that lead employers to offer high wages can induce peer group rejection.   The paper represents a transparent but rigorous model of educational under-investment as a signal to peers.

In “An Empirical Analysis of Acting White” (Journal of Public Economics 2010), Fryer uses data on friendship networks for high school students and uncovers noticeable racial differences in the relationship of student popularity and grades.  The findings are consistent with Fryer’s two audience signaling model of acting white with a less positive impact of grades on popularity for blacks in schools with more inter-racial contact.  The work adopts measures of the popularity and racial isolation (segregation) of one’s friends based on Fryer’s rigorous and novel work on the measurement of segregation with Frederico Echenique (“A Measure of Segregation based on Social Interactions,”Quarterly Journal of Economics 2007).  Fryer has empirically studied the role of racial identity and cultural capital for other social behaviors. Of particular note is his work with Steven Levitt (“The Causes and Consequences of Distinctively Black Names,” Quarterly Journal of Economics 2004) examining changes in patterns of first names of Black and White children since the 1960s. 

Economics of Discrimination, Anti-Discrimination Policy, and the Racial Divide

Roland Fryer is also a leading scholar of the economics of discrimination, affirmative action, and anti-discrimination policy.  His work (with Matthew Jackson) explores the psychological foundations for racial discrimination in a model of categorization (“A Categorical Model of Cognition and Biased Decision-Making,” The B.E. Journal of Theoretical Economics 2008).  Fryer and Jackson show that specific biases emerge from optimal categorization with a fixed number of categories. Types of experiences and objects that are less frequent in the population tend to be more coarsely categorized potentially leading to discrimination against minority groups that looks like statistical discrimination (treating all members of a minority group as part of one category and not making finer distinctions).

Fryer has done important work with Glenn Loury analyzing the economics and consequences of affirmative action (“Affirmative Action and its Mythology,” Journal of Economic Perspectives 2005; “Valuing Diversity,” Journal of Political Economy 2013).  Fryer and Loury provide a rigorous analysis in the tradition of optimal tax theory and provide close attention to the visibility (sighted vs. unsighted) and the timing (ex ante development assistance or ex post placement advantages) dimensions of affirmative action policies.  They also have shown empirically the potential inefficiencies of “color-blind” (unsighted) affirmative action for increasing racial diversity in university admissions (“An Economic Analysis of Color-Blind Affirmative Action,” Journal of Law, Economics, and Organizations 2008 along with Tolga Yuret). 

Fryer has been a leader in research on other key aspects of the racial divide including the measurement of segregation, the adverse impact of the crack cocaine epidemic of the late 1980s and early 1990s on inner-city communities, long-run trends and the determinants of rate of inter-racial marriage, the changing role of Historically Black Colleges and Universities (HBCUs) in the higher education of U.S. Blacks, and the economics and politics of the Ku Klux Klan in the early 20^th century.  For example, Fryer (along with Steven Levitt, Lisa Kahn, and Jorg Spenkuch in the Review of Economics and Statistics 2012) has empirically examined “The Plight of Mixed Race Kids” documenting that mixed-race children have economic outcomes between blacks and whites, but that mixed-race kids have higher levels of risky behaviors as adolescents.  A Roy model of peer interactions can help explain this pattern with mixed-race kids having less of a predetermined peer group choosing riskier behaviors to gain acceptance.

Roland Fryer has emerged as a leading scholar of the U.S. racial divide and as a major figure in the evaluation of education policies to narrow the racial achievement gap.  He has been bold and fearless in his willingness to use rigorous economic theory, collect new data, and to develop and implement appropriate empirical strategies (including large-scale randomized field experiments) to assess any serious hypothesis that may shed light on racial inequality and may provide policy tools to improve the long-run outcomes of disadvantaged children.  Fryer’s work is marked by a creative and entrepreneurial edge.  His work on testing educational reform policies has led to better models of the education production function and to promising policies for improving schools for disadvantaged U.S. students   Fryer’s research illuminates the role of peer effects, social identity, and economic incentives in the educational and economic outcomes of minority groups in the United States and around the world.

How might a China slowdown affect the world?

By Michael Pettis · December 2, 2014 ·

 Two years ago it was hard to find analysts who expected average GDP growth over the rest of this decade to be less than 8%. The current consensus seems to have dropped to between 6% and 7% on average.

I don’t think Beijing disagrees. After assuring us Tuesday that China’s economy – which is growing a little slower than the 7.5% target and, is expected to slow further over the rest of the year – was nonetheless “operating within a reasonable range”, in his Tianjin speech on Wednesday Premier Li suggested again that the China’s 7.5% growth target is not a hard target, and that there may be “variations” in China’s growth relative to the target.

I think every one knows that variations will only come in one direction, and although his stated expectations are still pretty high, most analysts, correctly I think, interpreted his remarks as a warning that growth rates will drop even more. Here is how the People’s Daily described the speech:

 Premier Li Keqiang on Wednesday said China can meet the major economic goals this year and policymakers will not be distracted by short-term fluctuations of individual indicators. Li downplayed the importance of some economic data from the past two months when delivering his keynote speech to the 2014 Summer Davos, which opened Wednesday in north China’s port city of Tianjin.

…China has targets of GDP growth around 7.5 percent and a consumer price index (CPI) increase of about 3.5 percent in 2014, with 10 million more urban jobs to keep the urban unemployment rate at a maximum of 4.6 percent.

 Inflation is also below target. According to the National Bureau of Statistics Wednesday release, “In July, the consumer price index (CPI) went up by 2.3 percent year-on-year. Prices grew by 2.3 percent in cities and 2.1 percent in rural areas. Food prices went up by 3.6 percent, while non-food prices increased 1.6 percent. Prices of consumer goods went up by 2.2 percent and prices of services grew by 2.5 percent.”

Surprisingly, analysts continue to hail lower-than-expected CPI inflation as giving the PBoC room and encouragement to expand credit – largely I guess because this is what analysts say when US or European CPI inflation numbers are low, and although most of us haven’t thought through the differences between China and the US in the ways prices respond to monetary policy, we don’t want to seem like we don’t know what we are doing. The constraint on monetary and credit growth in China is not CPI inflation and never has been. Monetary and credit growth in China are constrained by the impact of GDP growth on balance sheets.

For me the main information coming out of CPI inflation data is that consumer demand relative to total production continues to be too weak to drive up prices, something confirmed earlier this week by the August trade numbers, which failed to suggest strong growth in domestic demand. According to Xinhua:

China’s exports in August rose 9.4 percent year-on-year to 208.5 billion U.S. dollars, with monthly trade surplus reaching an all-time high of 49.8 billion U.S. dollars, customs data showed on Monday. China’s imports continued to contract last month, with a year-on-year decrease of 2.4 percent, to 158.6 billion U.S. dollars, the General Administration of Customs said in a statement.

Trade surplus in August jumped 77.8 percent year-on-year and hit a record high again, after reaching an all-time high of 47.3 billion U.S. dollars in July, the data showed.

 Although in my opinion the current 6-7% medium-term growth expectations are still far too optimistic, and will almost certainly be disappointed within one or two years, the good news is that most analysts at least recognize that the increasing risk of a “hard landing”, which they mostly seem to define as growth below 6%. The idea that during the rebalancing process Chinese growth can drop as sharply as it has for every other country that has gone through a similar rebalancing is still hard to accept, even though a little digging would make it clear that analysts underestimated the pace of slowdown during each of the previous cases too.

Still, the fact that we have been consistently surprised on the down side since 2010 has alerted most analysts to the possibility that we may continue to be surprised on the down side. A “hard landing” of growth below 6% is still considered unlikely, but no longer possible to ignore.

This worries a lot of people. A hard landing, we are told, would be devastating for the world economy because China is the world’s “growth engine”, and if it falters, growth around the world will also slow. There is also rising concern about a baking crisis within China. An economist at Oxford Economicsrecently told a Sydney audience that “Chinese authorities were understating the extent of bad loans on their banks’ books and faced tough choices in dealing with the potential bank failure.” In that he is certainly right, but he went on to say: “”We don’t know when there will be a China banking crisis and how it will play out but it is almost certain there will be one,”

I am not sure I agree. Insolvency doesn’t necessarily lead to crisis, as countries like Spain have made clear. It takes a collapse in liquidity to create a crisis, and if insolvent borrowers remain liquid, we are likely instead to see a long, difficult period of slow growth in which the losses are painfully ground out of the system (and always turn out to be greater than they would have been had they been recognized immediately). A banking crisis in China is always possible, and several people I respect are quite certain that there will be one, but I think that as long as Beijing implicitly or explicitly guarantees deposits, and as long as Beijing’s credibility with Chinese households is solid, and I believe it is, I think we are more likely to see many years of Japanese-style “zombie banks” than a banking crisis.

What does it mean if growth slows?

At any rate as far as I can understand, most analysts claim that if growth in China fell much below 6%, we would be likely to suffer the following:

1. The rest of the world would slow, perhaps sharply, as a consequence of China’s lower growth.
2. There would be a crisis in the Chinese financial system, which would spread to the global financial system.
3. Political instability would emerge in China as unemployment surges.

I think most analysts may be overestimating the adverse consequences and underestimating the probability of much lower growth. I continue to expect growth rates to fall substantially, probably by 1 percentage point a year or more for the rest of the decade, so that in the best case, during the expected period of President Xi’s administration (2013-32), growth rates are unlikely to average above 3-4%.

Higher growth rates are not impossible, of course, but to get the arithmetic to work for me it would take some fairly implausible assumptions – mainly that Beijing engineers the transfer of 2-3% of GDP every year from the state sector to the household sector – for China to achieve growth rates anywhere near 6% for the next decade. I would make two further points about the consensus:

1. Even though most analysts who now think 6% is the likely lower end of China’s growth trajectory have already had one or more Damascene conversions, they still think of rebalancing largely as a linear process. It isn’t. The longer unbalanced high growth is maintained (and high growth is always unbalanced), the sharper the reversal must ultimately be.

In the best-case orderly adjustment, growth rates will drop every year, more or less smoothly, as credit growth is constrained and investment growth drops with it. As the reforms proposed during the Third Plenum are implemented, ordinary Chinese households will benefit from direct or indirect transfers from the state sector, so that total household wealth will continue to rise more or less in line with the growth in household income during the past decade. In that case, consumption growth will remain in the 5-8% range.

As this occurs, the consumption share of GDP growth will, of course, rise over the next few years so that much slower GDP growth does not imply much slower growth in the rate at which ordinary Chinese see an improvement in their standard of living. The two biggest risks to a smooth adjustment are, first, that the Chinese elite are successfully able to prevent the implicit transfers of wealth to the household second implied by the Third Plenum reforms, and second, that the wealth effect of a collapse in real estate prices, or a high correlation between consumption growth and investment growth, result in much slower than expected consumption growth. The second risk is the focus of a recent blog posting in which JCapital’s Anne Stevenson-Yang’s more pessimistic consumption expectations are contrasted with mine, with a follow up blog posting, and while we disagree, I don’t completely dismiss the JCapital position.

A disorderly adjustment will have a different dynamic. It is likely to occur after another 2-3 years or relatively high (7-8%) GDP growth rates followed by a very ugly contraction once debt capacity is exhausted, which will occur when new loans cannot grow fast enough both to roll over existing bad loans (by which I mean loans that funded projects whose returns were insufficient to liquidate the loans) and to generate economic activity. Average growth rates in the case of a disorderly adjustment will be well under 3-4% but the adjustment will be highly discontinuous.

2. So if GDP growth rates are much lower than current consensus and even much lower than what most analysts would consider a “hard landing”, does this mean – especially if China’s economy is, as the New York Times called it, “the world’s main growth engine in recent years” – that the global economy is dire straits?

It depends on how China adjusts. China is not the world’s growth engine and never has been. It is simply the largest arithmetical component of growth, which is a very different thing. Whether China’s economy slows, and how quickly it does, matters to specific sectors of the global economy – positive to some and negative to others – and this will depend primarily on the evolution of China’s current account surplus. An orderly rebalancing will be good for the world on average and a disorderly one bad.

The same is true about the effect of a Chinese slowdown on social conditions. People do not generally care about GDP growth rates. They care about their own income growth relative to their expectations. Rebalancing in China means by definition that Chinese household income growth will outpace GDP growth, after many years of the opposite. A best-case orderly rebalancing should result in little change in the growth of household income, even as GDP growth drops sharply. This for example is what happened in Japan from 1990 to 2010, when GDP growth dropped close to zero but household income grew at nearly 2%.

A disorderly rebalancing, however, could result in negative growth in both GDP and household income, with the former dropping more than the latter. This, for example, is what happened in the US in the 1930-33 period – with GDP dropping by around 35% and household income dropping by around 19%. In the case of China, in other words, while elites will suffer in both scenarios, in the former case there is no reason for popular discontent.

Is China the world’s growth engine?

When analysts say that China is the world’s growth engine – something they said about Japan in the 1980s, by the way – they are implicitly assuming incorrectly the source of growth. If you multiply China’s GDP growth by its share of global GDP, you will find that Chinese growth over the last few years has comprised a larger share of global GDP growth than that of any other country. But this doesn’t mean it is the engine of growth.

An engine of growth drives growth around the rest of the world. If an economy is simply growing quickly, and especially if it is growing at the expense of other economies, it can hardly be called an engine of growth. In that case its growth actually constrains growth elsewhere.

Consider the colonial relationship between Britain and India 200 years ago. During the middle of the 18^thCentury and well into the beginning of the 19th Century India produced far more textiles – and usually much cheaper and of better quality – than did England, but a number of measures aimed at undermining Indian textile producers and protecting British textile producers (tariffs that almost always exceeded 50%, for example, and by 1813 were as high as 85%) meant that at some point in the first half of the 19^th Century the British textile industry had become the most efficient in the world and was able largely to eliminate the Indian textile industry from global competition.

There is no question that Britain was the largest component of global GDP growth at the time (the US and Germany did not surpass Britain until the 1860s and 1870s), but it would be foolish to say, at least in the Indian context, that the UK was the “engine” of global growth. In the textile industry, its growth came at the expense mainly of India. I am not suggesting that China’s growth relative to the rest of the world is equivalent to Britain’s growth relative to India. My point is only that a country’s contribution to global growth cannot be calculated by measuring its share of global growth.

So what contributes to growth? One of the thornier debates in economics is the debate between supply-siders, who insist that increasing production is the only way to increase growth, and the demand-siders (often Keynesians) who insist that increasing demand is the only way to increase growth, at least it is when resources are underutilized. Each statement is one side of an accounting identity, but causality does not necessarily run only in one direction. Growth can be driven primarily either by supply or by demand, depending on circumstances. When savings are in short supply, it is the latter. When not, it is the former.

To put it more explicitly, when investment is constrained by a lack of savings, the best way to generate growth is to increase investment by forcing up the domestic savings rate, in which case the world’s growth engine is likely to be the country that exports capital to investment-hungry parts of the world. Of course a net exporter of capital is by definition a country that is running a current account surplus.

In the United States during much of the 19^th Century, an erratic and unstable financial system combined with the huge infrastructure needs of a rapidly expanding continental economy meant that the US was almost always in short supply of money and capital*, and so to a large extent its growth rate was constrained mainly by British liquidity. When money poured into the US from Europe, and mainly from England, investments in the US grew apace and the US economy boomed, until some event caused the taps to be turned off (the collapse in silver mining in the 1820s during Latin America’s wars of independence, for example, which was followed by the US crisis of the 1830s and, as a matter of interest to those interested in Chinese history, with the replacement of silver exports with opium to the silver-starved Qing government in China). Whereas Britain may not have been an engine of growth for 18^thCentury India, or at least for the Indian textile industry, it was for much of the 19^th Century the world’s engine of growth because it supplied much of the capital that a savings-starved world needed to fund investment.

But when savings rates are excessive, which is often a consequence of income inequality and a high state share of GDP, as I show in one of my earlier blog posts, the problem the economy faces is insufficient demand, not insufficient savings available for investment. In fact as consumption declines with the rising savings rate, it tends to reduce the need for productive investment, so that both productive investment and consumption tend to drop.

Technically you can never have “excess” savings over investment because savings must always balance investment globally. But as I show in another blog entry, the tendency of rising income inequality to force up the savings rate beyond the needs of productive investment must necessarily be balanced by one, or a combination, of three counterbalancing events:

1. As the savings rate tends to rise (or, which is the same thing, as the consumption rate tends to decline) productive investment opportunities tend also to decline, so that excess savings flow into speculative and non-productive investment, including rising inventories, developing countries, risky technology ventures (which can generate huge positive externalities), real estate, stock markets, etc.

2. Perhaps because rising prices in speculative assets causes a strong wealth effect, ordinary households borrow against their rising wealth to increase consumption faster than their income increases, driving down their savings rate in line with the rise in savings that accompanies rising inequality.

3. Rising speculative investment, rising inventories, and rising debt eventually reach a limit, often followed by a crisis, after which unemployment must rise and, by reducing production faster than it reduces consumption, forces down the savings rate enough once again to maintain the balance between savings and investment.

When the world suffers from too low a level of savings to fund needed productive investment, policies that force up savings are positive for long-term growth. For similar reasons, economies with excess savings create growth abroad by exporting the excess to where it is needed. In that case the supply-side insistence on focusing policy on ways to generate additional savings does result both in more growth and in trickle-down wealth expansion.

However when savings are high enough and mobile enough that balance can only be achieved in the form of high unemployment, the world does not need more savings to fund more productive investment, as the supply-siders argue, but rather more demand, as the Keynesians insist. More sustainable demand (in the form of needed infrastructure or of higher consumption by wealthier workers) will lead to more productive investment by redeploying underutilized resources, including unemployed workers.

If there is such a thing as a global engine of growth, in the latter case, it is the country that is able (or is forced) to import the most amount of capital and export the most amount of demand (i.e. run the largest trade deficit). In that case countries with large trade surpluses that have to export excess savings do not cause growth abroad. As an aside Kenneth Austin recently published in The Journal of Post Keynesian Economics what I think is a very important paper on how capital exports affect the global economy. His paper is summarized in a recent New York Times article.

What will drive China’s contribution to global growth?

So what kind of world are we in – one with excess savings, or one with excess demand? I would be truly surprised if anyone suggested that we are in the latter world and not the former. A world of excess savings is prone to bubbles, and either debt-fueled consumption or high unemployment, and this pretty much describes the world we have been living for the past two decades. For this reason I would argue that countries that are absorbing excess savings – i.e. running current account deficits – are generating growth abroad while countries that are exporting excess savings – i.e. running current account surpluses – are weakening growth abroad.

China, in other words, is not the world’s growth engine. Behind Germany and ahead of some of the oil producers, it runs the largest current account surplus in the world, which means that it is exporting its excess savings in a world that has nowhere to put the money, and so the world must respond either with speculative asset bubbles, unproductive investment, debt-fueled consumption binges or unemployment.

This means that to assume slower growth in China will reduce growth abroad is wrong. As the growth rate of China’s economy drops, the fact that its share of global GDP growth will drop does not presage anything bad for the global economy. What matters is what happens to China’s current account surplus. As long as the world suffers from weak global demand, if China’s current account surplus declines relative to global GDP, China is adding net demand to a world that needs it. This is positive for global growth. If on the other hand China’s current account surplus rises, China will be adding more savings to a world already unable to absorb total savings productively, and the world will be worse off.

This tells us how China’s rebalancing will affect growth abroad. China’s contribution to global growth over the next decade depends on the relative pace at which savings and investment decline. If savings declines faster than investment, China’s excess savings will decline and with it its current account surplus. China in that case, will be adding net demand (or reducing negative net demand, to be more precise) to a world that needs it. If on the other hand China’s investment rate declines faster than its savings rate, its current account surplus will by definition grow, and the world economy will be worse off.

So which will it be? I think it depends on how orderly the rebalancing process will be.

1. In an orderly rebalancing, China will take steps to reduce investment growth. Instead of causing unemployment to surge, however, the reforms proposed during the Third plenum, most of which involve direct and indirect transfers from the state sector to the household sector, should keep consumption growth rates relatively high.

In order to keep the process as stable as possible and to prevent a surge in unemployment, my guess is that investment will decline more slowly than consumption will rise, so that in effect the gap between savings and investment narrows. This is just another way of saying that China’s current accounts surplus will narrow as a share of global GDP and the effect for the world will be positive (this is what occurred during Japan’s rebalancing between 1990 and 2010).

2. A disorderly rebalancing can occur in a number of different ways so it is hard to predict the impact on the current account, but the most likely outcome would be a surge in the current account surplus. Assume, for example, that a disorderly rebalancing occurs because Beijing waits so long to force through the reforms that it runs into debt capacity limits (i.e. the growth in debt cannot exceed the growth in the amount of bad debt that must continually be rolled over). In that case investment will drop quickly. At the same time unemployment will rise, which will partially reduce the savings rate, but worried Chinese households with jobs will cut back on consumption, which will increase the savings rate.

If the combination of the two causes the savings rate to rise, or to fall more slowly than the rapidly declining investment rate, the automatic corollary is a rise in the current account surplus. This would reduce demand in a world already suffering from low demand.

A slowing Chinese economy might be good or bad for the world, depending on how it affects the relationship between domestic savings and domestic investment, and this itself depends on whether Beijing drives the rebalancing process in an orderly way or is forced into a disorderly rebalancing by excess debt. My best guess is that Beijing will drive an orderly rebalancing of the Chinese economy, even as it drives growth rates down to levels that most analysts would find unexpectedly low, and this will be net positive for the global economy.

 This is an abbreviated version of the newsletter that went out ten weeks ago.  Academics, journalists, and government and NGO officials who want to subscribe to the newsletter should write to me atchinfinpettis@yahoo.com, stating your affiliation, please.  Investors who want to buy a subscription should write to me, also at that address.

 * To the point, where counterfeit money was often accepted as real, even though it was known to be counterfeit (Stephn Mihm, A Nation of Counterfeiters: Capitalists, Con Men, and the Making of the United States, Harvard University Press, 2009). This, by the way and for those who find this kind of think interesting, was also true in China during the late Ming Dynasty, and explains China’s huge demand for silver, which was soon to be supplied by Spanish silver discoveries in the Americas.