# 3.3. Application to Bhutan

## **_Modeling of Market Income_**

The most challenging part of the fiscal incidence analysis for Bhutan is the lack of information on labor and nonlabor income. Previous studies have dealt with this in several different ways. A popular approach is to use the survey-to-survey imputation to match the consumption survey with an income survey—this was done in Argentina (Lopez Del Valle et al. 2021), Ecuador (Llerena Pinto et al. 2015) and Paraguay (Canavire et al. 2021), for example. The feasibility and success of this approach depends on a number of factors, including the availability of income and consumption surveys that were conducted not too far apart in time and the existence of a sufficient number of common variables. While Labour Force Surveys are conducted annually in Bhutan, the questions are less suited to capture the earnings from the agriculture sector which is the most important source of livelihoods for the rural poor.

Another approach is to impute market income by assuming disposable income equals consumption aggregates, which is a reasonable assumption in a lower-middle-income country as it may be rather uncommon to have large savings, when information on direct transfers and taxes is available, . However, using this approach directly for Bhutan is challenging since there is no information in the BLSS on direct taxes and social security. Moreover, it is difficult to attribute aggregate household consumption into individual-level consumption unless some simplifying assumptions are made, such as dividing household consumption or income by the number of workers to get an estimate of average individual income (see Lara Ibarra et al. 2019 for the Arab Republic of Egypt and Hill et al. 2017 for Ethiopia). Since this method would not reflect income differences between household members, it could lead to an imprecise estimate of income tax liabilities.

We develop a more sophisticated approach for Bhutan by adopting a consumption-based approach to modeling market income. Specifically, we employ a Mincer earnings model to estimate individual net labor income and then recover gross income using information on the prevailing income tax structure in Bhutan. The approach is consistent with the recommendation in Lustig et al. (2018), which suggests working backwards to impute market income from disposable income. Compared to other methods, this approach allows for the modeling of fiscal interventions that target individuals, such as social security schemes or personal income taxes. In sum, this approach combines a consumption-based model with a Mincer earnings model to derive estimates of individual income.

The estimation of individual market income is performed in two stages. In the first stage, a Mincer earnings model is estimated on households with a single earner—in this case, net market income equals disposable income (or consumption). The coefficient estimates from the Mincer model are then applied to predict net income for households with multiple earners. In the second stage, we estimate individual gross market income from net labor income by using prevailing rules about personal income taxation and social security contributions. The rest of this section describes the detailed set-up of the model.

The model starts with an identity of household consumption, as shown in equation (1): Where Cj is household _j_ ’s consumption, Aj is the demand for assets of household _j_ , YjN is total net labor income for household j (for example, gross wages minus direct taxes), and πj is other non-labor income for 10