In-work benefits for married couples: an ex-ante evaluation of EITC and WTC policies in Italy

2.1 Design of the EITC and WTC programs

A common feature of the EITC in the US and the WTC in the UK is that low-income households are entitled to a refundable tax credit (or benefit) provided that at least one adult member works and other eligibility criteria are satisfied.

To be eligible for the EITC, the taxpayer needs to meet two conditions: (i) positive earned income from employment or self-employment, and (ii) earned income, adjusted gross income and investment income below certain thresholds. Conditional on eligibility, the credit entitlement depends on family earned income according to separate schedules by filing status and number of eligible children. Each schedule includes a phase-in region where the credit is initially increased at a certain subsidy rate, a flat region where the credit is kept constant at the maximum amount, and a phase-out region where the credit is tapered away to zero. Subsidy rate, maximum credit amount, and taper rate vary with the number of eligible children leading to a more generous welfare program in favor of large households¹.

To be eligible for the WTC, the claimant needs to work a minimum number of hours per week and fulfil other conditions related to either age, disability, responsibility for children or previous periods of unemployment benefits. The credit entitlement is equal to its maximum amount if gross annual income (jointly assessed in the case of couples) does not exceed a fixed disregard and is reduced at a certain taper rate above it. Compared to the EITC, an important difference is the lack of a phase-in region. Moreover, if the claimant works 30 hours or more per week, the maximum credit entitlement is shifted upward by the 30 hour element of the WTC schedule².

2.2 Disincentives on secondary earners

The key insight from both economic theory and earlier empirical evaluations is that family-based in-work benefits like EITC and WTC are effective for some population groups like lone-parents and primary earners of married couples, but they lead to perverse effects on secondary earners of married couples whose labor supply decisions are known to be sensitive to financial incentives from the tax-benefit system. Despite its importance, this issue has received little attention compared with other problems such as the role of childcare, the problem of benefit take-up and stigma effects, and the evaluation of possible spillover effects with other parts of tax-benefit system. The use of family-based in-work benefits with extra credits for secondary earners has been recommended by Brewer et al. (2010) based on implications from the optimal taxation theory. To our knowledge, however, formalized policy designs and simulation results for the impact of such reforms are still lacking.

Notice that in the UK and the US, the focus on lone parents may be partly justified by the large share of two-earner households with children. In Italy, however, this population group amounts to 45% due to the low labor market participation of married women. Thus, potential disincentives on secondary earners must be considered a more serious concern than in the US and the UK.

3.1 The Italian FA program

The FA program provides family-based benefits that are exempt from taxation and means-tested against the number of eligible household members, household composition and gross household income. Its schedule distinguishes among 15 household groups, but our attention shall be focused on four groups only consisting of married couples with no disabled member and (i) no children, (ii) one child, (iii) two children, and (iv) three children, respectively. Eligibility is restricted to employees, temporary workers, unemployed covered by unemployment benefits, and former-employee pensioners. Self-employed are not eligible since at least 70% of gross household income is required to be from wages, salaries, and former-employee pensions. As shown in Figure 1, FA are strictly increasing with household size and non-increasing with gross household income. With the exception of childless couples, each household group faces an initial flat region of maximum benefits and three subsequent phase-out regions. Although it is usually considered a welfare program to alleviate poverty, FA expire at rather generous income cut-off points (about 90th percentile of the gross income distribution for households with children). As discussed below, our in-work benefit reforms impose lower income cut-off points to collect resources from the right-hand-side of the household income distribution and then use these resources to finance a set of additional incentives for two-earner households with low income.

3.2 The EITC reform

where $E_c^{\ast }$ is the maximum benefit of the flat region, $t_{1c}=E_c^{\ast }/G_{1c}$ is the subsidy rate of the phase-in region, $t_{2c}=E_c^{\ast }/(G_{3c}-G_{2c})$ is the taper rate of the phase-out region, $G_{\mathit{\text{tc}}}$, t=1,2,3, are the income cut-off points, and G is gross household income. The schedule for two-earner households presents two differences. First, there is a higher maximum benefit ${Ē}_c^{\ast }=(1+p_c)E_c^{\ast }$, where $p_c\ge 0$ is the benefit premium for two-earner households. Second, there are larger phase-in and phase-out regions to avoid that the benefit expires as secondary earners enter the labor market.

Imposing that length of the flat region, subsidy rate and taper rate do not change, the income cut-off points of the schedule for two-earner households are equal to ${\bar{G}}_{1c}=(1+p_c)G_{1c}$, ${\bar{G}}_{2c}=G_{2c}+p_c{G}_{1c}$ and ${\bar{G}}_{3c}=(1+p_c)G_{3c}-p_c(G_{2c}-G_{1c})$.

Figure 2 focuses on households with one and two children to illustrate FA and two different EITC schedules against gross earnings of the secondary earner, with gross earnings of the primary earner fixed to 15,000 Euros. The two EITC schedules differ only in the size of the benefit premium for two-earner households, which is fixed to p _c =0 in the standard schedule and p _c =1 in the new schedule. In both schedules, the income cut-off points G_1c,G_2c, and G_3c are fixed to 50%, 100% and 150% of the poverty line in the baseline tax-benefit system and vary across household groups according to coefficients of the Carbonaro equivalence scale. As noticed above, the benefits from the two EITC schedules expire at lower income cut-off points with respect to FA, and the new EITC schedule has alarger phase-out region than the standard EITC schedule. One-earner households receive higher benefits under the standard EITC schedule. However, as the second-earner enters the labor market, the new EITC schedule provides considerably higher benefits over a wider range of the gross earnings distribution.

3.3 The WTC reform

where $W_c^{\ast }=W_{1c}^{\ast }$ is the maximum benefit of the flat region, $t_c=W_c^{\ast }/(G_{3c}-G_{2c})$ is the taper rate of the phase-out region, and $G_{2c}$ and $G_{3c}$ are the income cut-off points delimiting the phase-out region. Here, the first income cut-off point of the flat region is defined implicitly by the eligibility condition placed on hours of work, and it varies across households according to hourly wages of both spouses and non-labor household income. Two-earner households who are entitled to the second adult element face a similar schedule with maximum benefit ${\bar{W}}_c^{\ast }=W_{1c}^{\ast }+W_{2c}^{\ast }$, income cut-off points ${\bar{G}}_{2c}=G_{2c}$ and ${\bar{G}}_{3c}=G_{3c}+p_c(G_{3c}-G_{2c})$. If both spouses work full-time, then the maximum benefit is shifted upward to ${\tilde{W}}_c^{\ast }=W_{1c}^{\ast }+W_{2c}^{\ast }+W_{3c}^{\ast }$, and the income cut-off points are increased to ${\tilde{G}}_{2c}=G_{2c}$ and ${\tilde{G}}_{3c}=G_{3c}+(p_c+q_c)(G_{3c}-G_{2c})$. Thus, two-earner households are entitled to a higher maximum benefit and face a larger phase-out region.

Figure 3 illustrates FA and two different WTC schedules against gross earnings of the secondary earner for households with one and two children. For comparability with the EITC schedules illustrated in Figure 2, common policy coefficients are set as before, and the benefit premium for full-time work is fixed at q _c =0.5 for all household groups. Compared to the EITC, this system of in-work benefits is particularly targeted to households with low hourly wages. Further, it provides additional incentives to encourage full-time work.

4.1 Tax-benefit calculator and survey data

The tax-benefit calculator used in this study is EconLav, an Italian microsimulation model that covers social security contributions, taxes and public transfers. EconLav is applied to a subsample of married couples from the 2008 wave of the SHIW to approximate the budget sets of each sample unit under both the baseline tax-benefit schedule in the year of data collection and the hypothetical schedules resulting from our in-work benefit reforms. Our working sample consists of 1,926 married couples in which the husband and the wife are both aged between 20 and 65 years, and neither of them is disabled, retired, in education, nor engaged in self-employment activities. We also trimmed 1% of outliers from the observed hourly wage distribution of each spouse. Descriptive statistics on the key variables are presented in the Additional file 1.

4.2 Behavioral model of labor supply

For the behavioral model of labor supply, we extend to married couples the multi-sectoral discrete choice model for single decision makers developed by Dagsvik and Strøm (2006). Like other models based on a discrete choice approach, labor supply is treated as the outcome of agents’ choices from a finite set of job opportunities. Thus, utility maximization is performed by finding the best alternative in this finite set, and it becomes simple handling nonlinear and nonconvex budget sets while also accounting for other important issues faced in the estimation of labor supply models (e.g. flexible specifications of preferences, observed and unobserved heterogeneity, unobserved wages, and quantity constraints on the choice set).

The multi-sectoral framework of Dagsvik and Strøm (2006) extends the standard setup for this class of models by accommodating the separation of jobs in different sectors. Within this framework, each job is characterized by fixed hours of work, a sector-specific hourly wage, and other nonpecuniary and unobservable job attributes. Thus, the hourly wage of each agent can vary across jobs of different sectors, and the set of available jobs is allowed to be individual-specific to capture quantity constraints that are determined by market equilibrium conditions and negotiations between unions and employers within each sector.

Our generalization of this framework to married couples is presented in Appendix A: A multi-sector model of labor supply for married couples. A key assumption of this model is that it relies on a unitary approach where husband and wife maximize a common household utility function. As argued by Chiappori and Donni (2009); Vermeulen (2002); and Bargain et al. (2010), the income pooling assumption made in this approach is not exempt from criticisms, and it has been rejected in some empirical studies. A more attractive approach would be a collective model where the two spouses are involved in an intra-household bargaining process to maximize their own preferences (see, for example, Vermeulen 2006 and Francesconi et al. 2009). Earlier studies by Beninger et al. (2006); Beninger et al. (2007); Beninger and Laisney (2002); and Chiuri and Longobardi (2002), among others, suggest that imposing a unitary framework when the data-generating process is a collective framework may lead to downward biased estimates of labor supply responses for wives and upward biased estimates of labor supply responses for husbands. In this paper, we shall not follow this more general approach because full estimation of a collective and multi-sectoral labor supply model with taxes like ours has not been achieved yet.

In the empirical analysis, we focus on a two-sector model that distinguishes between jobs in the public and private sectors to capture the non-negligible differences existing in the labor market conditions and the hourly wage structures of these two sectors in the Italian economy (see, for example, Giordano et al. 2011). The predetermined choice set of each agent includes non-participation plus 6 job opportunities for each sector, yielding 169 job combinations for each couple. In modeling quantity constraints on the choice set, we assume that the number of sector-specific jobs available for each spouse depends on education and regional unemployment rates. Further, we assume that their hours of work distributions are uniform apart from two peaks at full-time jobs with 35 and 40 weekly hours of work, respectively, and one peak at part-time jobs with 20−30 weekly hours of work.

The hourly wage of each agent is allowed to vary among jobs in the public and private sectors but not across jobs within the same sector. This amounts to assuming that hourly wages are independent from hours of work. Since sector-specific hourly wages of the two spouses can never be observed jointly, we estimate a system of four hourly wage equations in an early stage. As described in Appendix B: Estimation of sector-specific hourly wage equations of husbands and wives, this estimation stage is based on a three-step control function procedure that simultaneously accounts for sector-specific selection effects, endogeneity of experience, and correlations among hourly wages of the husband and the wife.

In addition to the bias correction terms that control for selection in each equation of the system and the reduced form residuals that control for endogeneity of experience, the covariates in the hourly wage equations include a third-order polynomial in experience, two indicators for education attainment, gender-specific regional unemployment rates, and two indicators for living in the center and the south of Italy. Identification of the hourly wage equations is attained through a set of exclusion restrictions: second-order polynomials in age and non-labor income, number of children, and indicators for children aged less than 3 years and occupational status of the parents. In other words, we assume that this set of variables help explain the reduced form equation for experience and the selection equations for the choice of the sector, but not the sector-specific hourly wages of the two spouses. Hourly wage predictions also incorporate prediction errors drawn from a multivariate normal distribution with zero means and a variance-covariance matrixequal to the estimates resulting from our three-step procedure.

The utility function includes a systematic component, which takes the form of a quadratic polynomial expansion in disposable household income, leisure of the husband and leisure of the wife, and a random taste-shifter which is identically and independently distributed across households, sectors and jobs according to an extreme value distribution.

Preference variation across couples is taken into account by modeling the marginal utility of each spouse’s leisure in terms of a second-order polynomial in age, number of children, an indicator for children aged less than 3 years, and a random error for unobserved heterogeneity in preferences. The random errors for unobserved heterogeneity in the preferences of husbands and wives are assumed to be mutually independent, independent of prediction errors in the hourly wages, and normally distributed with mean zero and constant variance.

Due to the distributional assumption on the random taste-shifter, the reduced form of the model is equivalent to a multinomial mixed logit model with 169 alternatives and six random errors, two of which account for unobserved heterogeneity in preferences of the two spouses, and four account for prediction errors in their sector-specific hourly wages. Model parameters are estimated via simulated maximum likelihood (SML) to integrate out of the likelihood these unobservable random errors. Provided that the number of draws used in SML goes to infinity faster than the square root of the number of observations, the resulting estimator is known to asymptotically equivalent to the exact maximum likelihood estimator (Hajivassiliou and Ruud 1994).

4.3 Labor supply predictions

The SML estimates of our model can be used to predict potential adjustments in labor supply due to changes in the tax-benefit system. In our analysis, these predictions are computed through the procedure of Creedy and Duncan (2002). For each couple, we first draw up to 750 realizations from the extreme value distribution and the estimated asymptotic distribution of the parameter estimates, such that under the baseline tax-benefit system, the observed alternative in the choice set has the highest utility. This gives us one set of draws of the random taste-shifter and the parameters estimates which rationalizesthe observed labor supply choices of the two spouses under the baseline tax-benefit system. Only for couples where none of the 750 realizations yields maximum utility at the observed alternative, labor supply of the two spouses is considered to be invariant. Through repeated applications of this process, we construct 250 sets of draws for all random components of the model, and for each of them we predict labor supply choices of the two spouses under a reform scenario to obtain 250 predictions of labor supply transitions. Finally, we average over the sample and report the mean and the fifth and ninety-fifth percentiles of the distribution of transitions. These percentiles are the bounds of a two sided confidence interval of about 90 percent.