Measuring business uncertainty in developing and transition economies

Edgar Avalos, Jose Maria Barrero, Alvin Davis, Leonardo Iacovone, Jessica Torres

Uncertainty about business prospects is a fact of life for any business. When deciding whether to hire new workers or invest in new technology, businesses don’t know whether it will lead to increased sales and profits, due to factors beyond their control. Instead, they forecast future sales revenues (and other performance measures) and account for the uncertainty of those forecasts. They think of situations where things could turn out worse than predicted, leaving too many workers and unemployed investments, or, conversely, when things could go better. Only by weighing these scenarios can firms decide whether to hire these workers or invest in this technology.

When faced with a high degree of uncertainty, firms usually also have the option to wait and see to avoid mistakes. This option is most attractive when the business environment is highly unpredictable and reversal is costly, such as when laying off workers or reselling machinery and equipment is costly. But it is also costly in itself: waiting means delaying or canceling some projects that would be profitable. In theory, such delays can have serious economic consequences. They can reduce a country’s productivity if many businesses end up operating at sub-optimal scales or with sub-optimal technologies. This problem is potentially more serious in developing and emerging market economies, where inadequate business investment and technology adoption often stifle productivity and economic growth.

Measurement of uncertainty

On practiceHowever, economists are struggling to understand how uncertainty affects business and macroeconomics. Part of the reason is that standard measures of uncertainty, such as stock market volatility and forecaster disagreement, do not reflect uncertainty at the enterprise level; i.e. managers of uncertainty enterprises understand around their projections of future sales and performance. Only recently have researchers made significant progress in directly measuring this subjective uncertainty at the firm level. A modern methodology uses surveys of business managers that identify a number of scenarios about the future performance of their own firm and the likelihood for each scenario. This combination of scenarios and probabilities allows researchers to construct business metrics. forecasts and business uncertainty in the minds of each individual manager.

So far, most efforts to measure subjective forecasts as well as uncertainty were limited to a handful of high-income countries such as the US and the UK. But new data compiled by the World Bank shows that a simplified version of this modern methodology also works well in developing and transition countries. This is an important development as many researchers felt that it would be difficult to conduct this type of survey in developing countries, where businesses and their managers may be less experienced. New World Bank data refutes these concerns and reveals systematic differences in how business managers perceive uncertainty across income levels.

The data in question comes from Business Pulse and World Bank Business Surveys, which were created to track the impact of the coronavirus pandemic on the private sector. Both surveys include a module that identifies the main, optimistic, and pessimistic scenarios for future sales of one’s own firm, as well as the probabilities for each scenario. Between April 2020 and March 2022, more than 23,000 enterprises from 41 countries in Eastern Europe, Asia, Africa and Latin America took part in it. The countries covered cover a wide range of income levels, from Madagascar at the bottom to Poland at the top.

Stylized facts

As it turns out, business sales forecasts and uncertainty metrics built from this World Bank data capture a lot of business outlook information that managers have access to, as the following stylized facts show.

First, future sales forecasts predict actual future sales. as reported in the interview followed by the survey (Fig. 1). Second, managers who express higher uncertainty at the time of forecasting tend to make larger forecast errors (Figure 2). This second finding suggests that a survey-based measure of business uncertainty reflects the degree of unpredictability or volatility in firms’ sales and reflects similar findings from studies conducted in advanced economies.

Figure 1. Sales forecasts predict actual sales

Sales forecasts predict actual salesNotes: Scatter plot of realized sales in the follow-up interview against sales expectations (forecast) for the next six months on the horizontal axis. Realized and expected sales are expressed relative to 2019 levels.

Figure 2. Companies reporting higher levels of uncertainty make more severe forecasting errorsFirms reporting higher uncertainty make more severe forecasting errors.Notes: Scatter plot of the absolute error between sales expectations (i.e., six-month-ahead forecasts) and realized sales in a subsequent interview versus subjective uncertainty about six-month-ahead sales. Realized and expected sales are expressed relative to 2019 levels.

Second, there are systematic differences in business uncertainty across countries with different levels of development.— a new stylized fact. Firms in poorer countries, i.e. those with lower GDP per capita, tend to have higher levels of uncertainty on average (Figure 3). Previous research has shown that employment, sales and investment data are more volatile in low-income countries. But now it is clear that this is not due to poor quality or noisy data. Instead, business managers actually perceive insecurity about being three to six times higher in these low- and middle-income countries than in the US or the UK. Thus, high levels of business uncertainty are likely to distort investment and employment patterns in low-income countries. This discovery brings researchers one step closer to showing that some countries may indeed not develop and grow because their unpredictable business environment encourages firms to wait and wait too much rather than invest and increase their productivity.

Third, the negative relationship between uncertainty and GDP per capita is not easy to explain. This does not seem to be due to differences in the composition of the business sector in different countries. It is also not systematically related to the volatility of exchange rates or business cycles, which are often higher in developing and emerging market economies. Instead, there appears to be a strong link between economic development and the degree of risk and unpredictability (i.e., uncertainty) that businesses perceive in their economic environment.

Figure 3. Employment-weighted business uncertainty declines as GDP per capita grows.

Employment-weighted business uncertainty declines as GDP per capita rises.Notes. This figure shows employment-weighted subjective uncertainty in each country, averaged over the World Bank’s Business Pulse and Enterprise Survey waves, compared to the country’s GDP per capita in 2019 on the horizontal axis. We weigh firms by employment in each country. UK and US values ​​are taken as averages for April 2020-December 2021 and April 2020-March 2022, respectively.

Policy implications

The data from these World Bank surveys has at least two policy implications. First, central banks and governments in low- and middle-income countries can collect forecast and uncertainty data as part of their routine business surveys and thus obtain timely information about business prospects. Such data can be useful for policy makers and researchers interested in macroeconomic fluctuations and firm dynamics in these countries. In addition, country-specific surveys can also collect projections and uncertainty about prices, employment, or investment that can be useful for monetary, fiscal, and business development policies.

Second, removing and reducing the degree of uncertainty that enterprises perceive through specific policies can play an important role in supporting investment and growth of companies in developing countries, with a positive impact on the macro economy. And the economic benefits of making business uncertainty a higher policy priority can also bring greater political and social stability, which in turn matters to the business environment.