Business Dynamics Laboratory (Laboratorio de Dinámica Laboral y Empresarial [LDLE]), is constructed by INEC using information from IESS, SRI, and other government institutions. It contains worker-level data for over 70,000 firms that meet two criteria: reported sales to SRI and registered employment with IESS (formal employment). Combining these three data sources yields a rich employer-employee database useful for analyzing firm dynamics, aggregate productivity, and labor demand patterns for the 2012–2020 period.<sup>1</sup> The main firm performance variable of interest in this paper is firm revenue based TFP. The control function approach developed by Ackerberg et al. (2015) is used to estimate revenue TFP. The variables necessary for estimating revenue TFP are value-added, capital, labor, and materials (which is used as the proxy variable for the control function approach) at the firm-level. The paper follows the methodology of Avellan and Ferro (2017) to construct these variables using the Ecuadorian firm administrative data, adhering to standard measurements in the literature. Value-added is calculated as firm gross output (sales adjusted for product inventories) minus intermediate consumption of materials and services. Intermediate consumption comprises operational expenditures and production costs. Capital is measured based on the value of fixed assets reported in firms' financial statements, lagged by one year. Labor is measured as the number of workers employed by a firm. Materials are computed as the sum of raw materials, transport costs, gasoline costs, and utilities costs. Monetary variables are transformed into constant prices using sector deflators from the Ecuadorian input-output matrix. Consequently, firm gross production, intermediate consumption, and value-added are deflated using their respective sector deflator indexes. Similarly, materials are deflated using the sector deflators for intermediate consumption, while capital is deflated using the sector deflators for gross fixed capital formation. Lastly, there are two significant firm characteristic variables relevant in the analyses of the paper: sector and age. The firm's sector of activity corresponds to the International Standard Industrial Classification (ISIC) sector classification. The age of a firm is calculated as the difference between the observation year and the year of the firm's commencement of operations.

Variables pertaining to workers are measured in a standard manner to facilitate the wage inequality analyses. Worker-level information is available at a monthly frequency in the LDLE. Following relevant papers in the literature (Barth et. al., Criscuolo et al. [2020, 2021, 2022]), only workers that are fully employed for a calendar year are kept in the estimation sample. Wages are constructed as a worker’s daily wage rate from reported monthly wages and the number of days worked in a month. These are deflated by the consumer price index to obtain real wages. To match to the firm-level data, which is at an annual frequency, yearly real wage rates are estimated as the average across months of the real daily wage rate. The paper also utilizes the following variables associated with workers’ job characteristics and human capital: part-time employment, education, age, gender, and ethnicity. A dummy for part-time employment is constructed using the number of days worked in a month. Workers with less than 15 days of employment per month are classified as having part-time employment.<sup>2</sup> For education, a bivariate variable is created to identify if a worker has obtained at least a high school diploma. Last, workers’ age, gender, and ethnicity are provided by the LDLE.

# **3 Motivation Facts: Aggregate Productivity and Inequality Trends in Ecuador**

A concern in Latin American economies is that growth has been unsatisfactory and driven by poor productivity performance, as documented by Busso et al. (2013). Ecuador is no exception to this trend. As depicted in Figure 1, between 2003 and 2014, Ecuador's GDP grew at an average annual rate of 4.7 percent, largely driven by the growth of physical capital stock. However, economic growth has been slightly

> 1 It is important to acknowledge certain limitations of the data sources employed in this paper. Firstly, the universe of firms and workers considered only pertains to formal economic activity. Additionally, due to variations in regulations governing the submission of tax returns by firms, many entities do not report information necessary for measuring relevant variables for the paper. Given this, the sample size can vary across the exercises carried out in this paper, as the number of observations is maximized in relation to the variable of interest in each exercise. To mitigate sample attrition, values are imputed for observations with missing data for the variables used in the productivity estimation method.

> 2 To transform number of days worked per month to an annual measure, the paper considers a worker's most frequently reported number of days worked per month within a year as their annualized measure.

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