In answering this question, Annette Alstadsæter, Niels Johannesen, and Gabriel Zucman (2017) conduct a detailed study by using data from Scandinavian countries. Scandinavians are arguably one of the places where the data quality is excellent. They are able to collect data from randomized audit results, provided by Scandinavian tax authorities (because the transparency policy there also grants easier access).
Despite the trove of quality data, they still theorize that audit can potentially fail to capture sophisticated tax evasion scheme done by the rich. So it is still possible that the resulting income in the tax assessment is understated. Thus, they combine the audit data with leaked data from offshore financial institutions (Swiss Leaks and Panama Papers). They also supplement it with information from recent tax amnesties (again, provided by Scandinavian tax authorities).
Based on Swiss Leaks, Panama Papers, and amnesties, Alstadsæter, et al. found that the top 0.01% richest households evade about 25% of the taxes they owe by concealing assets and investment income abroad. Adding the result from the tax evasion detected in random audits, the total evasion in the top 0.01% reaches 25-30%, versus 3% on average in the population.
The State of Inequality in Indonesia
In 2017, Indonesian Statistic Agency (Badan Pusat Statistik/BPS) reported that the Indonesia's Gini index is 39.1. But you've probably heard/read the Oxfam-INFID paper in 2017. Combining the data from Credit Suisse Global Wealth Databook 2016 and the list of richest people in Forbes, the paper shows shows how the 4 richest Indonesians have more wealth ($25bn) than the combined wealth of 100 million Indonesians in the bottom 40% ($24bn). The same report also suggest that Indonesia is the 6th most unequal countries in the world, after Russia, Denmark, India, United States, and Thailand.
By using the similar data from Credit Suisse Global Wealth Databook (year 2017), I found out that the inequality in Indonesia is worse than official Gini index calculated by BPS.
74.8% of Indonesian wealth is owned by the top 10% richest. If we "zoom" it in further, 60% of wealth owned by the top 10% population is owned only by the top 1% richest. In other words, the top 1% richest owned almost half of total Indonesian wealth. 45.4% of total wealth to be precise.
If this distribution is correct, then the Gini ratio should be twice as worse at 83.7, instead of 39.1 as reported by Badan Pusat Statistik.*)
If we were to measure the average wealth of each population decile, the inequality is more pronounced.
The top 10% richest are, on average, 7.31 times more wealthy than the average Indonesian. Meanwhile the top 1% richest are, on average, 44 times more wealthy than average Indonesian. We can go further: top 20% are 287 times richer than the bottom 20%; top 10% and top 1% are 748 and 4,540 times richer than the bottom 10%, respectively. Look at how the average wealth of bottom 10% population did not even show up in the graph above. This is indeed staggering.
I compare the analysis by looking at the distribution of saving accounts in Indonesia. In this regard, saving accounts could be construed as a proxy of wealth (at least, financial wealth), similar to the HSBC data contained in the Swiss leaks used by Alstadsæter, et al. Indonesian Deposit Insurance Agency (Lembaga Penjamin Simpanan/LPS) keeps track of account ownership that are subsequently grouped based on the amount of money in those saving accounts. This is the source of the saving data.
In the LPS data, the state of inequality in Indonesia still looks astoundingly bleak. For instance, in 2017, 98.06% of saving accounts in Indonesia contain less than 100 million Rupiah in amount. But those 98.06% cumulatively only own 14.6% of total deposit in Indonesia.
In contrast, only 0.04% of saving accounts that have more than 5 billion Rupiah in it. But these 0.04% cumulatively own 46.17% of total savings.
To make it easier to imagine: if we scale down Indonesians into 10,000 people, then the richest 4 persons have 3 times more money in their bank accounts than the other 9,800 combined.
I then calculate the average amount in each saving group. Below is the result:
Note how similar this is to the distribution based on Credit Suisse data. The average amount in the lowest group barely show up in the graph at all, despite accounting for 98% of account ownership in Indonesia. The top group (account with > 5 billion Rupiah) on average contains 2,268 times more money than the average Indonesian saving account. This is an obscene picture of inequality.
Tax Evasion
Now we go back to the original question: do rich people evade more taxes? If I had a hand on the data as good as Alstadsæter, et al., combined with a more detailed distribution of wealth in Indonesia, I can get a more precise estimate.
In the case of Indonesian data, however, I face several roadblocks.
First, the distributional data in the World Inequality Database for Indonesia is inadequate. It does not have a detailed distribution for each percentile/decile. That being said, I have to make do with the Credit Suisse data. However, Credit Suisse does not report the range in each decile nor the standard deviations. I have to reconstruct the distribution points based on the assumption that the Indonesian wealth has uniform distribution, so it is efficient to compute its L-statistics to find out the range in each decile.
Second, because of the obvious confidentiality reason, I don't have the full amnesty data, only its statistics. Since the statistics are anonymized and aggregated (meaning I don't know who owns what and how much), I cannot cross them with the names in Swiss Leaks or Panama Papers. Similarly, I also do not have the data from tax audit to cross with the amnesty/leaked data.**)
Despite such limitations, I try my best to follow the method as outlined by Alstadsæter, et al. in their appendix. This is the finding of Alstadsæter, et al. in Scandinavian countries:
Using the available statistics and reconstructed distribution points, this is what I find in Indonesia:
If we consider tax amnesty as a sign of the previously undetected tax-related wrongdoings – be it evading, avoiding, or simply filing the tax return not in correct, complete, and clear manner – then the richest Indonesians disproportionately commit more wrongdoings compared to the general population. The top 1% richest of Indonesia is 16 more likely to use amnesty compared to average Indonesian (and 201 times more likely compared to the bottom 10%). This is after considering the fact that tax amnesty is basically open to all, and that there is no special treatment for the rich.
Unfortunately, this is the furthest I can do with the data. Given better access, it may be possible to gauge the post-amnesty compliance as outlined by Alstadsæter, et al., or by using macrodata similar to James Alm's study in post-amnesty Colorado. It is also interesting to combine audit data, leaked data, and amnesty data to paint a complete picture of tax evasion and inequality in Indonesia. But, alas.
In the end, it's likely that rich Indonesians have the means and opportunities to concoct tax-evading schemes. And being richer granted even more means and opportunities. "In the little game of tax demagogy," Piketty once wrote, "the weakest seldom come out winners."
Reference:
Alstadsæter, A, N Johannesen and G Zucman (2017), “Tax evasion and inequality”, NBER Working Paper 23772. Appendix available at http://gabriel-zucman.eu/leaks/
Alstadsæter, A, N Johannesen and G Zucman (2018), “Who owns the wealth in tax havens? Macro evidence and implications for global inequality”, Journal of Public Economics, forthcoming.
Piketty, T (2016), "Chronicles: On Our Troubled Times", Penguin
Oxfam - INFID. (2017), "Towards a More Equal Indonesia", Oxfam International
Data:
Lembaga Penjamin Simpanan - Distribusi Simpanan Bank Umum Desember 2017
Badan Pusat Statistik
World Inequality Database, available at WID.world
Direktorat Jenderal Pajak
Credit Suisse (2017) Global Wealth Databook 2017. Credit Suisse Research Institute
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*) Different methodologies could result in different Gini ratios for the same country. For instance, Badan Pusat Statistik use consumption data based on household surveys, while Credit Suisse combined household surveys with SUR and upward-adjustment based on available financial wealth data. Different bracketing could also affect Gini calculation. If you rank the population in decile (1-10) or percentile (1-100) or by 40-40-20 (poorest 40%-middle 40%-richest 20%), the resulting Gini ratios can be very different. If the wealth range in each distribution point is different, Gini can also be different; etc.
**) To my knowledge, Indonesia has yet to implement nationwide randomized audit program. The national audit program for individual taxpayers is focused on prominent people, corporate owners, and entrepreneurs. The good: rich Indonesians are given more scrutiny. The downside: there is not much information regarding the tax compliance of middle-to-low income class. Even if I have the audit data, it may not be representative to infer from these focused audit targets as samples of the general Indonesian population.
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