WInteresting new paper by Tørsløv, Wier, and Zucman (2018) that came out few days ago intrigued me to revisit the question about missing profits. As you may know, corporation is driven by profits. Taxes cut the profits. So it is economically rational to try to reduce tax. One of the usual

In previous post, I have tried to estimate this loss in macroeconomic setting. Now depending on the condition (whether companies also consider market size or proximity) Indonesia may gain 2% or loss up to 5% of GDP due to tax base spillover. In this post, inspired by an equation mentioned by Tørsløv, et al. I will try to use a much more granular data.

Numbers of research concerning profit shifting used commercial database to extract the relevant information from the companies' financial report (mainly from income statement and balance-sheet). These are then entered into some equation. One of the equation mentioned in Tørsløv, et al. is:

where log(πic) denotes natural logarithm of pre-tax profits booked by company i in country c; τp is the tax rate in the parent company; τc is the domestic tax rate; and Firm and Country denote firm- and country-specific fixed effects.

I managed to collect the data for 904 companies for the years of 2012-2017. However, I have to modify the above equation in some ways. First, since I only concern about what happen in Indonesia, I have no use for Country fixed effect. Second, I change the tax differential to include all the subsidiaries in the multinational entities group, instead of the simple parent-subsidiary relationship. The reason is that an Indonesian company (even though it is a subsidiary, for instance) does not necessarily shift the profit to its parent. The profit can be shifted to another subsidiary within its MNE group that is a resident in low tax jurisdiction. The profit can also be "pooled" somewhere and remains unrepatriated to the parent's jurisdiction as in the case of many US companies.

Further, since the logarithmic operation can only be applied to positive numbers, then I must exclude some companies in some years because they booked 0 or loss (negative profit). This makes my panel data unbalanced and the observations are reduced. In the end only 695 companies remain with N = 3,113.

Because of the exclusion too firms may enter and leave the time series. For example, company A booked profit in 2012, 2013, 2015, and 2017 but had zero/negative profit in 2014 and 2016. Due to the log operation, company A is included in the sample for year 2012, 2013, 2015, and 2017, but it is excluded in 2014 and 2016. As a consequence, I cannot apply firm fixed effect and the model essentially turns into random-effect model. This is also confirmed by the results of Hausman and Lagrange Multiplier tests.

That being said, the model turns into:

where log(πi) denotes natural logarithm of pre-tax profits booked by company i in Indonesia; τavg is the unweighted average tax rate of the MNE group following Johansson et al. (2017); τc is the Indonesian corporate tax rate (25%); the rests are errors.

From a theoretical standpoint, choosing only companies that booked profits still has a benefit. You won't have to pay tax if you suffer loss or you have zero profit, so there is not much use to further avoid tax. Moreover, this allows the model to test whether agency theory is at play here: whether the manager tries to reduce tax without sacrificing much of the shareholder values by having zero profit or even booking loss.

Difference in tax rate negatively correlated with pre-tax profitability (p-value 0.033). If the tax rate of Indonesia is higher than the average tax rate of the MNE group, the pre-tax profit of Indonesian company belonging to said group becomes lower. For every percentage of tax rate difference, the pre-tax profit of the company drops by 4.37%. This means an Indonesian company whose other MNE group members are located in Singapore (tax rate 17%) and Vietnam (tax rate 20%) will have 18.93% less pre-tax profit than a non-MNE Indonesian company.

Extending the result to include all the companies in the sample, this is how much pre-tax profit is loss on average:

Again, we see evidence of tax avoidance in the samples included in this study. Of course this is not a comprehensive view of tax avoidance behavior. Loss-making companies and those who have zero profit are not covered here, although it is very likely that they engage in tax avoidance behaviors (via transfer pricing or excessive interest expense, for instance).

There are also other, more comprehensive methods to detect profit shifting explored in Tørsløv, Wier, and Zucman (2018). I suggest you read their paper if you want to know about the missing profit of nations. Indonesia, sadly, is not covered there.

Johansson, A, Ø. B. Skeie, S. Sorbe, and C. Menon (2017), “Tax Planning by Multinational Firms: Firm-Level Evidence from a Cross-Country Database”, OECD Economics Department working paper 1355.

Tørsløv, T, L. Wier, and G. Zucman (2018), “The Missing Profits of Nations”, NBER Working Paper 24701.

*modus operandi*is to establish subsidiary in low tax jurisdiction and divert the profit to it.In previous post, I have tried to estimate this loss in macroeconomic setting. Now depending on the condition (whether companies also consider market size or proximity) Indonesia may gain 2% or loss up to 5% of GDP due to tax base spillover. In this post, inspired by an equation mentioned by Tørsløv, et al. I will try to use a much more granular data.

**The Setup**Numbers of research concerning profit shifting used commercial database to extract the relevant information from the companies' financial report (mainly from income statement and balance-sheet). These are then entered into some equation. One of the equation mentioned in Tørsløv, et al. is:

where log(πic) denotes natural logarithm of pre-tax profits booked by company i in country c; τp is the tax rate in the parent company; τc is the domestic tax rate; and Firm and Country denote firm- and country-specific fixed effects.

I managed to collect the data for 904 companies for the years of 2012-2017. However, I have to modify the above equation in some ways. First, since I only concern about what happen in Indonesia, I have no use for Country fixed effect. Second, I change the tax differential to include all the subsidiaries in the multinational entities group, instead of the simple parent-subsidiary relationship. The reason is that an Indonesian company (even though it is a subsidiary, for instance) does not necessarily shift the profit to its parent. The profit can be shifted to another subsidiary within its MNE group that is a resident in low tax jurisdiction. The profit can also be "pooled" somewhere and remains unrepatriated to the parent's jurisdiction as in the case of many US companies.

Further, since the logarithmic operation can only be applied to positive numbers, then I must exclude some companies in some years because they booked 0 or loss (negative profit). This makes my panel data unbalanced and the observations are reduced. In the end only 695 companies remain with N = 3,113.

Because of the exclusion too firms may enter and leave the time series. For example, company A booked profit in 2012, 2013, 2015, and 2017 but had zero/negative profit in 2014 and 2016. Due to the log operation, company A is included in the sample for year 2012, 2013, 2015, and 2017, but it is excluded in 2014 and 2016. As a consequence, I cannot apply firm fixed effect and the model essentially turns into random-effect model. This is also confirmed by the results of Hausman and Lagrange Multiplier tests.

That being said, the model turns into:

where log(πi) denotes natural logarithm of pre-tax profits booked by company i in Indonesia; τavg is the unweighted average tax rate of the MNE group following Johansson et al. (2017); τc is the Indonesian corporate tax rate (25%); the rests are errors.

From a theoretical standpoint, choosing only companies that booked profits still has a benefit. You won't have to pay tax if you suffer loss or you have zero profit, so there is not much use to further avoid tax. Moreover, this allows the model to test whether agency theory is at play here: whether the manager tries to reduce tax without sacrificing much of the shareholder values by having zero profit or even booking loss.

The ResultThe Result

Difference in tax rate negatively correlated with pre-tax profitability (p-value 0.033). If the tax rate of Indonesia is higher than the average tax rate of the MNE group, the pre-tax profit of Indonesian company belonging to said group becomes lower. For every percentage of tax rate difference, the pre-tax profit of the company drops by 4.37%. This means an Indonesian company whose other MNE group members are located in Singapore (tax rate 17%) and Vietnam (tax rate 20%) will have 18.93% less pre-tax profit than a non-MNE Indonesian company.

Extending the result to include all the companies in the sample, this is how much pre-tax profit is loss on average:

**Conclusion**Again, we see evidence of tax avoidance in the samples included in this study. Of course this is not a comprehensive view of tax avoidance behavior. Loss-making companies and those who have zero profit are not covered here, although it is very likely that they engage in tax avoidance behaviors (via transfer pricing or excessive interest expense, for instance).

There are also other, more comprehensive methods to detect profit shifting explored in Tørsløv, Wier, and Zucman (2018). I suggest you read their paper if you want to know about the missing profit of nations. Indonesia, sadly, is not covered there.

**References**

Johansson, A, Ø. B. Skeie, S. Sorbe, and C. Menon (2017), “Tax Planning by Multinational Firms: Firm-Level Evidence from a Cross-Country Database”, OECD Economics Department working paper 1355.

Tørsløv, T, L. Wier, and G. Zucman (2018), “The Missing Profits of Nations”, NBER Working Paper 24701.