# 4. Applying the Macro-Micro Simulations to Potential Trade Policy Reforms in Sri Lanka

**To illustrate the use of this methodology, the CGE-GIDD approach is used to assess a set of ex-ante trade policy simulations for the case of Sri Lanka.** Sri Lanka is a country that has some key characteristics that make the country a good candidate to showcase the methodology. First, it is a small open economy and effectively a price taker in international markets. Second, as other developing countries, its export basket is dominated by a primary commodity – in this case exports of tea. Lastly, after a period of political instability that ended in 2009, the economy grew at an average 5.8 percent during the period of 2010-2017. This reflects a determined policy momentum towards reconstruction and rapid structural transformation, despite signs of a slowdown in the last few years. This paper studies the impacts of stylized policy scenarios including assessments of unilateral para-tariff liberalization, free trade agreements with China and India, and a full reform scenario (para-tariffs + FTAs). Section 3.1 discusses the current structure of the labor market in Sri Lanka while Section 3.2 describes the details of the baseline and trade policy scenarios. Simulation results are discussed in Section 4, first focusing on the sectoral level and then on the sub-national distribution of those effects.

**The model can be used to assess the sub-national, localized effects of trade** . The impact of reforms is differentiated across types of households and workers. Such heterogeneity is key in determining the welfare (consumption, poverty, inequality, etc.) and distributional impacts of any reforms to be undertaken. The GIDD distributes the macroeconomic results of the CGE model to households in line with the Sri Lanka Household Income and Expenditure Survey (HIES 2016). The microeconomic model distributes shocks while keeping the consistency with the aggregate results obtained from the macro CGE model.

# 4.1.Employment and skills profile

**The Sri Lanka Household Income and Expenditure Survey (HIES) 2016 was utilized to examine the characteristics of workers at the sectoral and district levels.**<sup>15</sup> The HIES 2016 data set consists of approximately 21,755 households and 82,935 individuals found within these households. We focus on profiling workers in each sector according to the localized Sri Lanka official version of the 1-digit and 4-digit International Standard Industrial Classification (ISIC),<sup>16,17</sup> the province in which they live, median wage and skill level proxied by educational attainment.

**Women account for one-third of employment of 7.7 million workers and they are primarily employed in the agriculture (incl. vegetables and fruits) sector.** Male workers comprise 5.07 million (66 percent) and female workers comprise of 2.63 million (34 percent). Agriculture (25 percent), manufacturing (18 percent), trade and commerce (18 percent), and social services and others (12 percent) sectors are the four largest employers in Sri Lanka according to estimates from HIES 2016 (Table 1).<sup>18</sup>

> 15The survey was conducted by the Department of Census and Statistics (DCS) under the National Household Survey Programme (NHSP) of Sri Lanka. The survey is nationally representative, and the unit of analysis is the household with details on all the individuals comprising the household. The sampling frame consists of two-stage stratified sampling – area of residence (urban and rural) and the estate sectors in each district of the country were the selection domains. This makes our results representative at the district level too, which is essential for the results of the CGE-GIDD at the regional level.

> 16 <u>http://www.statistics.gov.lk/industry/ASI_2016_Report.pdf.</u>

> 17 Sri Lanka HIES 2016 is utilized for the descriptive analysis of workers section, despite that wage information is more reliable in the Sri Lanka Labor Force Survey (LFS 2015).

> 18 Analysis presented in this section relies on the 1-digit ISIC industry classification (10 sectors).

8