Although the Chinese government regularly publishes statistics on income distribution, a new study by Wang Xiaolu, deputy director and senior research fellow of the National Economic Research Institute of the China Reform Foundation, an independent nongovernmental research organization, suggests this data may not be accurate.


One look around China’s streets, he says, shows that consumer trends — such as soaring housing prices, skyrocketing new car sales and strong domestic demand for luxury goods — are confirmation that incomes are much higher than what the government’s statisticians say they are. As for Wang, his statistics — based on a different methodology than what the National Bureau of Statistics of China (NBSC) uses — indicate that not only are average incomes increasing rapidly, but also the income gap between the rich and poor in China has been underestimated.


According to his work, the government’s statistics omit roughly RMB 9.26 trillion (US$1.36 trillion) in “invisible” income — that is, money earned illegally and under the table or not declared to tax authorities.


That China’s mainstream media immediately jumped on Wang’s findings shows that uneven income distribution has been a growing concern domestically. “The attention I got recently was more than expected,” says Wang. Observers worry that the increasing disparity in income may hinder the growth of the world’s second-largest economy. “If distorted income distribution is not dealt with, we may be heading toward a social crisis,” warns Wang.


Why do official statistics underplay the disparity? And what needs to happen to address the growing gap, while also tackling the “invisible” and “grey economy?” There are no easy answers, says Wang in this interview with China Knowledge at Wharton.


The following is an edited translation from Chinese of the conversation.


China Knowledge at Wharton: Your research shows that there is a discrepancy between official data on per-capita income and what we see on the streets. Why is that?


Wang Xiaolu: The NBSC draws random samples from urban and rural households when compiling statistics. The method is not the problem, but it’s the sample groups that cause certain deviations.


First, participation in the sample group is voluntary, and a considerable number of people with high incomes choose not to participate. Excluding these high earners seriously skews the results. Second, many participants do not tell the truth about their real incomes. They may be honest about their wages, but off-payroll income is another issue entirely. This unofficial “grey income” is not included in the survey data.


Even the NBSC admits that its methods of gathering samples can lead to incomes being underestimated. For example, according to official data, per-capita annual income of the top 10% of urban households in 2008 was RMB 43,614 (US$6,347), a number that is completely incompatible with general observations of consumer behavior.


China Knowledge at Wharton: Your research is also based on household surveys. How do you ensure that your data is reliable?


Wang: Our survey draws samples from 64 cities and 14 counties of varying sizes across 19 provinces in China, including municipalities. We surveyed 4,909 families, and after a strict screening process, compiled statistics using 4,195 of the samples.


We employed professional surveyors to gather the primary data from people they were familiar with, such as friends, family, colleagues and neighbors, based on different groups of income and careers, rather than choosing them randomly. And there were some supporting measures to ensure the authenticity of the data. The personal connection in the survey process creates an atmosphere of mutual trust, and this fosters more honest answers, and more reliable data.


China Knowledge at Wharton: Since your 4,195 samples were not randomly selected, how can they form an accurate snapshot of the nation?


Wang: Our purpose in conducting the survey was to calculate the statistical relationship between the disposable income levels and several consumption parameters … and test the results against official figures, rather than directly infer the aggregate income distribution from the samples.


For example, the Engel coefficient is a parameter related to income levels [measuring the income elasticity of demand for food]. It decreases as incomes increase, which is widely acknowledged in academic circles.


In 2008, the NBSC divided urban sample households into seven groups according to income levels. The lowest income group had an Engel coefficient of 0.4814, with a per capita income of RMB 4,754. Beginning with our own lowest income sample group, which we believe to be the most credible, we added in samples until the group’s average Engel coefficient was as close as possible to 0.4814. We found that the average income of this group was RMB 5,685. The difference between the two results is RMB 931.


Of course, the Engel coefficient is influenced by a number of factors, such as food prices and eating habits, so we applied an econometrics model to eliminate the effects of these factors. We arrived at an average income of RMB 5,350 with an Engel coefficient of 0.481.


According to my research, the total amount of disposable income in China in 2008 was roughly RMB 23.2 trillion (US$3.41 trillion), while the NBSC’s figure was about RMB 14 trillion (US$2.1 trillion). This suggests that there was about RMB 9.26 trillion in invisible income that year.


On a per capita level, our data shows that annual income in urban households in 2008 was around RMB 32,154 (US$4,729), which was almost double the official RMB 15,781 (US$2,321).


China Knowledge at Wharton: Do any organizations, such as the NBSC, question your results?


Wang: NBSC officials pay close attention to the results. We have discussed the matter in private. They generally think the official figures might have deviations, but not as much as what I get and they are not sure how much the deviation should be.


China Knowledge at Wharton: Were you surprised by the results?


Wang: No. Our results may sound frightening, but there are many social phenomena that can’t be explained by NBSC statistics. For example, according to international standards, the average cost of buying a house should be between three and five times the average annual household income. If the number exceeds five, it is an indication of an unsustainable real estate market. According to the NBSC, in 2008, the average house cost 10 times the average annual salary. But the real estate market remained hot throughout 2009, with revenue from house sales reaching RMB 3.8 trillion that year. How is it that so many people can afford to buy houses under these circumstances? One possible explanation is that their incomes have been underestimated….


We did similar research several years ago on income levels in 2005. Although the two pieces of research were based on different data samples, the result and the extent of the discrepancy from the official data is very similar in terms of population distribution and total income, which [helps to increase] the credibility of the results.


China Knowledge at Wharton: According to your research, invisible money exists across all income groups. Does this mean that both urban and rural residents have more money than widely believed?


Wang: That’s one side of the coin. The other would be that the income gap between the rich and the poor is much wider than we previously thought. In fact, we found that most of the overall grey income was going into the pockets of the wealthiest.


Among the income groups, we discovered that the lowest 10% of urban earners made RMB 5,350, 1.1 times higher than the official RMB 4,754, but those in the top 10% income bracket made RMB 139,000 annually, 3.2 times the official level [of RMB 44,000]. So the income disparity in urban areas is 26 times greater, rather than nine times as estimated by the NBSC. Furthermore, if you compare the highest urban income with the lowest average in rural areas, the gap will be 65 times, while the official estimate is 23 times.


Although our findings couldn’t directly calculate [the measure of income inequality in a particular population known as] the “Gini coefficient,” I would estimate it to be much higher than 0.5 — a dangerous level. We still have a long way to go in achieving what the government calls an “Oliver Society” [in which there is a large middle class and small lower and upper classes].


China Knowledge at Wharton: Your research found that the average per-capita income of the top 10% urban households is RMB 139,000 (US$ 20,000). Would it be fair to say that a large number of Chinese are earning incomes similar to those in developed countries?


Wang: According to our samples, members of this group owned both real estate and private vehicles. It means that at least 60 million people share a similar income to their counterparts in developed countries. This number is equal to the population of a big European country. If we look at it from a purchasing power parity perspective, this means that the quality of life may on average [be the same as] in developed countries. Companies with ambition to explore the consumer market in China may need to look at the data with a fresh eye before they hone their marketing strategies.


China Knowledge at Wharton: Who comprised the top group of your sample?


Wang: Entrepreneurs, private business owners, senior professionals (doctors, lawyers and artists). Without a doubt, the incomes of some government officials were much higher than they claimed. But my sample wasn’t a reflection of the overall situation in China in this regard.


China Knowledge at Wharton: How would you define invisible and grey income?


Wang: Some of the invisible money is composed of income not declared during government data collection, which interviewees omit for various psychological reasons.


However, mid- to high-income earners have a much higher level of invisible money, perhaps because of some profound systematic reasons. This is especially true for top earners, whose average income is several times more than official statistics suggest.


The term “grey income” mainly refers to two sources of income. The first is money acquired in ways that fall between legal and illegal, such as gifts. Accepting money and gifts from friends and relatives is legal in China. But when a government official takes advantage of this to amass a significant amount of money, then it is a different matter altogether. Is it bribery? Who broke the law if the official’s family members accepted the gifts? This lack of clarity is due to a lack of legislation.


The second is income acquired from sources that are legal, but via means that are possibly illegal. For example, insider trading, fake land auctions, and stock and futures market manipulation are all illegal….


China Knowledge at Wharton: According to your figures, what is the total size of China’s grey income?


Wang: Outside the random sample survey, the NBSC uses another set of statistical standards that are primarily based on economic census data coming from companies. Based on trend projections, this data shows that in 2008, disposable income in China was RMB 17.87 trillion (US$2.63 trillion). I believe this figure is more accurate than the NBSC household survey data [of RMB 14 trillion, or US$2.1 trillion].


In my study, I define grey income as the difference between this [RMB 17.9 trillion] and my calculation of disposable income [of RMB 23.2 trillion], which is about RMB 5.4 trillion.