The goal is to measure constraints for each sector in the country of study and compare these measurements with benchmarks of performance in countries across the world where investments have been successfully made in this same sector. This is expected to provide a revealed measure of whether a constraint is absolutely binding or not for investors in a sector. For example, if a given indicator (e.g. electricity supply) is essential for a sector (e.g. manufacturing), only countries with good electricity supply will witness successful private investment in manufacturing. For other sectors that depend less on electricity supply, such as agriculture, countries with poor electricity supply may still attract successful private sector investment. This benchmarking of constraints thus enables singling out the set of constraints for each sector where the country’s performance is below the minimum level required for successful investment. If constraints are frequently below investment level across different sectors, then this would also reveal constraints that may be binding for the entire economy.

The analysis is based on country-specific performance indicators (163 in total sourced from the World Bank TCdata360)<sup>14</sup> as sub-indicators of 12 categories representing: Demand, Factors (labor, capital), Key Inputs (infrastructures), and Institutions (macroeconomy, governance). The binding nature of the constraints measured by these indicators is then assessed by benchmarking them with a metric of third countries and sector specific score of success. In its current form, this metric is the existence of actual FDI in a sector and country<sup>15</sup> as recorded by the Financial Times' _fDi Markets_ database.

The CBT is designed to guide analysis through a large amount of information and provide an initial indication of where the biggest issues may be. However, the approach comes with limitations. First, it does not provide the user with the information on whether the variables included are associated in a statistically significant way with the success outcome of interest (i.e., attracted FDI or a revealed comparative advantage in a sector). Yet, the ability to understand which variables, among many variables, are the statistically significant (key) binding constraints is of high importance for efficient decision making (both from the investor and policy maker perspective). Second, the benchmarking process (i.e., assigning scores from 1-5 to each indicator for every country/sector pair) considers each indicator in isolation and is based only on the past information about the values of the indicator and the sector-level success performance. The process does not account for the effects of other relevant indicators or of potential associated factors, thereby potentially producing biased estimates.

# Identification of factors associated with trade and investment in a high-dimensional framework

# Objectives

Our approach is based on complementing the work discussed above by addressing some of its limitations. In particular, the objectives of the analysis are the following:

- Reduce the complexity of the universe of indicators associated with trade and investment outcomes success at the sector level.

> 14 Accessible at https://tcdata360.worldbank.org/

> 15In an earlier version of the tool, IFC’s DOTS database has been used. The DOTS database records IFC investments (so not only foreign investments but also domestic ones to which IFC is part of) and their performance. Thus, the tool enabled to benchmark performance against that of profitable investments, offering a more robust benchmark.

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