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Should the Japanese tax system be more progressive? An evaluation using the simulated SMCFs based on the discrete choice model of labor supply

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Abstract

This study proposes a method to obtain the social marginal costs of public funds (SMCF) that allows for heterogeneity on a household basis as well as labor supply responses along both the extensive and the intensive margins. To demonstrate our methodology, we take the example of the 1999 national income tax reform in Japan and evaluate it by estimating the SMCFs for changing marginal tax rates in different income brackets. We estimate the discrete choice model (DCM) of labor supply using a 1997 data set of Japanese households, and we use the estimates to generate the SMCFs with a DCM micro-simulation. We evaluate the simulated SMCFs with various distributional weights and find that the value of the SMCF for a 1 % increase in the marginal tax rate in any given income bracket decreases as we move across brackets from the bottom to the top. This finding suggests that the national government should have made the Japanese income tax system more progressive rather than less progressive as carried out in the 1999 reform. Our method is readily transferrable to tax reforms in other countries as well.

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Notes

  1. This is a tax reform exercise, not a tax design exercise. A tax reform analysis is more practical than a tax design analysis, as it evaluates piecemeal changes from the existing system. On the other hand, tax design calls for an entirely new system by quantifying the optimal value for every tax rate (cf., Feldstein 1976).

  2. We follow Dahlby (1998) to set aside the revenue effect of public services. We therefore fix the level of public services in our analysis such that it does not appear in our expression of the utility function.

  3. Dodgson (1980, 1983) used household income after all taxes and benefits normalized by corresponding average quantity and further adjusted with the equivalent scales. Poapongsakorn et al. (2000) used after-tax income normalized by the corresponding quantity for the highest income group. Creedy et al. (2011) used what they called “full income” (see footnote 7).

  4. We can derive \(\beta _i =y_i^{-\theta }\) from (11) if the preferences are homothetic and households face identical prices. However, if progressive taxation is in place, the weight is no longer justifiable, as leisure prices are no longer identical, except when the BS-SWF is Nash (\(\theta = 1\)). See Bessho and Hayashi (2013) for more details.

  5. We then define \(M_i \equiv W_i T+A_i -R_i \) for a single-member household, and \(M_i \equiv ({W_i^m+W_i^f})\cdot T+A_i -R_i ^C\) for a couple, where \(A_{i}\) is nonlabor income.

  6. Fleurbaey et al. (2013) originally applied this valuation to the health policy. In this study, we propose an application of their metric to the leisure-consumption choice, which coincides with the Rente criterion of Decoster and Haan (2010) and the intercept income of Preston and Walker (1999).

  7. Vermeulen (2006) and Shalhoub (2011) also allowed the random coefficient on the squared value of leisure.

  8. Duncan and Harris (2002), Brewer et al. (2005), and Callan et al. (2009) also considered unobserved heterogeneity in fixed cost (20c).

  9. When calculating the simulated maximum likelihood, we set the number of replications as 100 and assumed a normal distribution of the random coefficients for the mixed logit estimation.

  10. See Van Soest (1995), Van Soest and Das (2001), Duncan and Harris (2002), Brewer et al. (2005, 2006), Vermeulen (2006), Baldini and Pacifico (2009), Shalhoub (2011). Note that Brewer et al. (2005, 2006) did find that the unobserved heterogeneity in the fixed cost term is statistically significant.

  11. For example, see Aaberge et al. (2004), Steiner and Wrohlich (2004, 2005), Bargain and Orsini (2006), Creedy and Kalb (2006), Fuest et al. (2008), Decoster and Haan (2010), Dagsvik et al. (2011), Peichl and Siegloch (2012), and Aaberge and Colombino (2013).

  12. While we only consider national income taxes, we do allow for other income taxes, such as local income taxes and social security premiums, in order to calculate the effective marginal tax rates and brackets (as explained in Sect. 3.2). As such, there are more than five effective income brackets when all the taxes are considered. Note also that we excluded a small number of observations (.7 %) with anomalous data rendering negative values of \(\partial c_i^*/\partial c_i \).

  13. We use the labor supply elasticity of .4 as the “normal” degree of labor response based on the survey by Bargain et al. (2012).

  14. While calculating the SMCFs, we obtain the equivalent effect of this multiplication by placing an additional weight \(\phi _{i}\) on \(\beta _{i}\), which takes \(\phi _i = 13/[13N^*+(N-N^*)]\) if household \(i\) reduces labor supply and \(\phi _{i} = 13/[13N^{*}+(N-N^{*})\)] otherwise. Note that \(N\) is the total number of households, and \(N^{*}\) is the number of households that increased their labor supply.

  15. These results might not be so surprising since the qualitative conclusion depends on the relative sizes of the SMCFs across income brackets. Multiplying the responsive households by the same number should not change such relative comparisons since it would not change their relative proportions over the income brackets either.

  16. The upper and lower adjacent values are given as upper quartile + 1.5 \(\times \) (upper quartile \(-\) lower quartile) and lower quartile \(-\) 1.5 \(\times \) (upper quartile \(-\) lower quartile), respectively.

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Acknowledgments

We are grateful to Eckhard Janeba and two anonymous reviewers for their helpful comments and constructive suggestions. We also thank Robin Boadway, Bev Dahlby, Toshihiro Ihori, Shigeki Kunieda, and Yukihiro Nishimura for their valuable advice and help in the preliminary stages of this project. We would like to acknowledge the Research Centre for Information and Statistics of Social Science at the Institute of Economic Research at Hitotsubashi University for providing micro-level data from the Employment Status Survey for 1997. Bessho is financially supported by the Grant-in-Aid for Scientific Research (Grant-in-Aid for Young Scientists B-19730215). Hayashi acknowledges financial support from the Nomura Foundation, the Seimei Foundation, and the Center for International Research on the Japanese Economy at the University of Tokyo.

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Correspondence to Shun-ichiro Bessho.

Appendices

Appendix 1

Appendix 1 explains the method of obtaining each of the components in (9) and (10). After we estimate parameters in \(U(\cdot )\), we calibrate the random component \(e_{ij}\) in (2) as follows.

  1. [1

    ] Draw a vector of \(J\) random numbers that follow the I-EV distribution. Let \(e_i^q\equiv [e_{i1}^q\), \(e_{i2}^{q}\),..., \(e_{iJ}^{q}\)]’ be the \(q\)-th draw of such a vector. This yields a set of utility levels \(U_i^q\equiv \left[ {U_{i1}^q,U_{i2}^q,\ldots ,U_{iJ}^q} \right] \)’, where \(U_{ij}^q\equiv V(h_{ij} ,\varvec{Z}_i ,\varvec{\tau } )\,+e_{ij}^q\). If observed labor choice \(h_{i}\) coincides with the choice among the \(J\) alternatives that picks up the maximum value in \(U_i^q\), store \(e_i^q\) vas a “successful” draw. Repeat this process to obtain \(K\) successful draws \(\left\{ {e_i^1,\ldots ,e_i^k,\ldots , e_i^K} \right\} \).

  2. [2

    ] For a given successful vector draw \({\varvec{e}}_{i}^{k}\), we can construct pairs of utility level

    $$\begin{aligned} U_i^{0k} =V(h_i ,{\varvec{Z}}_i ,{\varvec{\tau }})+e_{i*}^k \end{aligned}$$
    (21)

    and individual tax liability

    $$\begin{aligned} R_i^0 =R(W_i h_i ,{\varvec{Z}}_i ,{\varvec{\tau }}) \end{aligned}$$
    (22)

    where “\(j\) = *” in (21) indicates that the choice * is optimal for a vector of \({\varvec{e}}_{i}^{k}\). Since observed choice \(h_{i}\) is the optimal choice by construction, different \({\varvec{e}}_{i}^{k}\) does not affect the optimal choice and the values of \(V(h_i ,\varvec{Z}_i ,\varvec{\tau } )\hbox { and}\;R(W_i h_i ,\varvec{Z}_i ,\varvec{\tau } )\).

  3. [3

    ] Change the tax parameters “slightly,” from \(\varvec{\tau }\) to \(\varvec{\tau }^{1}\). This will change the deterministic part of utility in (2) from \(V(h_{ij}, \varvec{Z}_i, \varvec{\tau } )\;\hbox { to}\;V(h_{ij}, \varvec{Z}_i, \varvec{\tau }^1)\). Using \({\varvec{e}}_{i}^{k}\) above, we can predict a new labor choice \(h_{i**}^{k}\) by selecting the choice that yields the maximum values among \(\left\{ {U_{i1}^{1k},U_{i2}^{1k},\ldots ,U_{iJ}^{1k}} \right\} \), where \(U_{ij}^{1k}\equiv V(h_{ij} ,\varvec{Z}_i ,\varvec{\tau }^1)\,+e_{ij}^k\). The new utility and tax liability are

    $$\begin{aligned} U_i^{1k}&= V( {h_{i**}^k,{\varvec{Z}}_i ,{\varvec{\tau }}^1})+e_{i**}^k\; {\hbox {and}} \end{aligned}$$
    (23)
    $$\begin{aligned} R_i^{1k}&= R(W_i h_{i**}^k ,{\varvec{Z}}_i ,{\varvec{\tau }}^1). \end{aligned}$$
    (24)
  4. [4

    ] Simulate the “marginal” utility of income with a “small” lump-sum increase in nonlabor income \(\Delta \), which yields \(V^\lambda (\cdot )\). Using \({\varvec{e}}_{i}^{k}\) again, select \(U_{i*}^{\lambda k}=\hbox { max}\{U_{i1}^{\lambda k},U_{i2}^{\lambda k},\ldots ,U_{iJ}^{\lambda k}\}\), where \(U_{ij}^{\lambda k}\equiv V^\lambda (h_{ij}, \varvec{Z}_i ,\varvec{\tau } )\,+e_{ij}^k\), which yields an estimate for \(\lambda _i^k\) as

    $$\begin{aligned} \lambda _i^k =\frac{U_{i*}^{\lambda k} -U_i^{0k} }{\Delta }. \end{aligned}$$
    (25)

Appendix 2

Appendix 2 explains our method of calculating tax liabilities and cash transfer benefits. Personal income tax liabilities consist of income tax imposed by the central government, inhabitant tax levied by local governments (prefectures and municipalities), and social insurance premiums for public pensions, health insurance, and unemployment insurance. The tax codes for FY 1997 are shown in Table 8. In calculating the tax liabilities, we make the following compromises due to data limitations. First, while local governments base their taxes on income in the previous year, we use the current income as a surrogate. Second, while local governments can change their tax rates, we use the standard uniform local tax rates as set by the national law, since most local governments adhere to the standard rates. Third, while public insurance premiums differ by place of work, we assume that combined premium rates for the three public insurances—those employed by firms with less than 1,000 employees, firms with 1,000 employees or more, and the public sector—are 13.3, 14.3, and 12.9 %, respectively, with specified ceilings on premium payments. Fourth, for deductions and exemptions, we consider employment income deduction, basic exemption, spousal exemptions, exemptions for dependents, and social insurance premium deductions, with the additional assumption that 20 % of nonlabor income is deductible.

Table 8 Outline of Japan’s income tax system, 1997 (thousands of yen)

For cash benefits, we consider child allowance. If households with children have annual earnings that are less than certain levels of income, they are entitled to child allowance. The eligibility depends on the level of household income as well as the number of children at specific ages. The income threshold varies as family size changes. In FY 1997, families with children aged three years or younger were eligible if their annual income was below 3.25 million yen (US$ 32,500), with the income threshold increasing with the number of dependents within the household. The 1997 monthly benefits per child depended on the number and composition of the children: 5,000 yen each for the first and second children and 10,000 yen each for the third and subsequent children.

The government also offers another type of child allowance called the child rearing allowance. However, since this targets single mothers only, we do not consider it here. Public assistance (PA) benefits may also be worth considering. PA benefits compensate for the difference between the minimum cost of living and the maximum possible earnings of a household. However, it is impossible to obtain individual PA benefits from the observed income data, as income is not the only variable used to determine eligibility for benefits. The means tests consider multiple characteristics of the applicants. The applicants have to exhaust all of their financial assets and prove that they have no support from their family and relatives. If the authority considers that the applicants are able to work, their chances for receiving benefits become quite slim. Fortunately, the proportion of households receiving PA in our samples is negligible; in 1997, the ratio of the number of households receiving PA to the total number of households was 1.41 %. In addition, the heads of 93.3 % of households receiving PA were the elderly (\(\ge 65\) years if male and \(\ge 60\) years if female), single mothers, the injured, the sick, and the disabled, all of whom are excluded from our samples. Therefore, the share of households receiving PA in our sample should be less than \(.095\,{\%} [= .0141 \times (1 - .933)]\), and plausibly, even less. See Hayashi (2010) for a general explanation about Japan’s social protection system.

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Bessho, Si., Hayashi, M. Should the Japanese tax system be more progressive? An evaluation using the simulated SMCFs based on the discrete choice model of labor supply. Int Tax Public Finance 22, 144–175 (2015). https://doi.org/10.1007/s10797-014-9303-6

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