The principal caveat of the data sources used in this paper is that the universe of firms and workers corresponds to only formal economic activity and specifically the subset of formal firms and workers that pay into CIT and PAYE, respectively. Thus, informal firms and workers are necessarily excluded, as are formal firms and workers not meeting or complying with the filing thresholds for CIT. Given statutory thresholds for tax filing and firm- and worker-specific drivers of tax compliance, firms and workers in the CIT and PAYE databases are likely to be quite different from excluded firms and workers. However, the firms and workers in the datasets constitute an economically significant portion of the Zambian economy. For 2021, the CIT dataset covers over 5,000 firms, which collectively account for ZMK 329 billion in sales, ZMK 118 billion in value added (equivalent to 27 percent of GDP), and 527,000 estimated workers. For the same year, the PAYE dataset covers over 800,000 unique workers, filing over 6.3 million monthly returns. Beyond their collective size, formal firms, and workers—as proxied through these datasets—are especially critical to economic transformation as they are likely to constitute the most productive segment of the economy and most likely to export (Amin, Ohnsorge and Okou 2019).

# 4. Firm dynamics and productivity

## 4.1. Methodology for productivity analyses

Leveraging these data, productivity-related analyses in this paper focus on labor productivity (LP) rather than total factor productivity (TFP). LP and TFP are two ways of computing firms’ efficiency in converting inputs (capital, labor, etc.) to produce goods or services (output). Conceptually, LP measures output per worker and therefore looks only at how labor is converted into output, while TFP incorporates adjustments in other production factors (e.g., capital stock and intermediate inputs) as well as technology, innovation, management practices, and other ways of augmenting firm output with the same input endowment (Syverson 2011). Although TFP presents a more complete view of productivity, this analysis relies on LP given the lack of reliable data measuring capital or investment, which is a key prerequisite for TFP estimation. As no data on firm-level prices or quantities are available for Zambia, this paper calculates LP in revenue terms rather than in terms of physical quantity. LP calculated in revenue terms reflects not only firm physical efficiency in production but also prices that reflect product quality and marketing in addition to input costs (Cusolito and Maloney 2018). This analysis is unfortunately unable to capture these price-related dimensions and thus cannot definitively conclude that phenomena such as productivity dispersion are the result of allocative efficiency (or lack thereof), quality, or markups. The specific analytical implications of this limitation are further discussed in the subsequent discussion of the results.

Labor productivity is defined as value added per worker for the purposes of this paper. Value added is defined as sales less non-labor cost of sales. The number of workers is estimated by dividing firms’ total wages bills by average annual wages at the ISIC A*38 level (calculated from the PAYE database). Value added is deflated in line with sectoral deflators obtained from ZamStat, which are roughly in line with the ISIC A*38 level of aggregation.

The methodology for decomposing labor productivity growth is drawn from Olley and Pakes (1996), Melitz and Polanec (2015) and Patiño Peña and Ferro (Forthcoming). Labor productivity is estimated and decomposed at the ISIC 1-digit level given the low number of observations per sector at the ISIC 2-digit 5