Aggregate non-tradable production is estimated through a minimal opportunity-cost framework in which the annual output of an individual is proxied by the income the worker would have earned if she had been allocated to the traditional sector of the labor market. The cumulative value of the non-tradable production is given by the yearly number of hours devoted to the domestic chores and housework activities by gender. The approach applies the average traditional-sector wage, as not doing so would transfer the gender wage inequities from the market to the valuated output (Chadeau, 1985). The model does not predict or impute the wages respective to earning-related characteristics such as the employment status or age-group of the different shares of the population partaking in non-tradable activities as this is deemed problematic for an aggregate standpoint (Hill, 2009). Instead, the alternative that is adopted ascribes the traditional-sector wage as the single and minimum remuneration with which the non-tradable production is valued by the economy.

# **4 Parameterization**

## **4.1 Data Sources**

A wide range of data are used to calibrate the model. In following the CKW 2017 approach, the demographic module is comprised of total fertility rates (TFR) and projected quinquennial population by five-year age group that are gathered from the World Population Prospects of the United Nations (2010). The module of two-sector production is divided between modern sector and the traditional sector. The data on sectoral share of labor is taken by the Liberian Labor Force Survey (LFS) of 2010 and the sectoral share of GDP are taken from the 2007-2013 estimated average of Abid (2016). The amount of arable land and the value rendered by the natural resources are likewise inputted into the production module and taken from the World Development Indicators (WDI) database. The capital stock estimates and the Gross Domestic Product (GDP) statistics are drawn from the Penn World Tables (Feenstra, Inklaar, & Timmer, 2015).

Baseline data on labor force participation rates (LFPR) by sex and five-years age groups are obtained from the ILOSTAT repository (ILO, 2020). The earnings by sex which are taken for the parametrization of wages are taken by the Household Income and Expenditure Survey (HIES) 2014 data (Liberia Institute for Statistics and Geo-Information Services, 2015). Baseline data on human capital is composed of the average educational attainment (in years) by sex and five-years age groups, obtained from the Barro-Lee dataset (Barro & Lee, 2013), and the average height (in meters) by sex and five-years age groups, obtained from the Demographic and Health Survey (DHS) by the Liberia Institute of Statistics and Geo-Information Services, The Ministry of Health and Social Welfare/Liberia, National AIDS Control Program/Liberia, and ICF International (2014). Baseline estimates of age-specific savings rates are gathered from Bloom, Canning, Mansfield, & Moore (2007).

The non-tradable production module is composed of the average time (in hours) allocated to housework and domestic chores by sex, obtained at baseline from the United Nations Global SDG Database of the United Nations Statistics Division (2020) and UN Women (2019). To these measures, the time allocated to fetching water or firewood are added and obtained at baselined from the HIES 2014 from LISGIS (2015). Appendix 1 describes each source of data.

## **4.2 Calibration and Convergence**

We use parameters generated in CKW 2017 and impute additional parameters for our extension to the model. The CKW 2017 model parametrizes the reduction in labor market participation due to an additional child, the endogenous response of fertility to changes in education, the impact of fertility on 11