Uncertainty about business prospects is a fact of life for any company. When deciding whether to hire new workers or invest in new technology, companies don’t know if this will result in more sales and profits, due to factors beyond their control. Instead, they predict future sales revenue (and other performance metrics) and take into account the uncertainty around those forecasts. They think of situations where things could go worse than expected, leaving them with too many workers and idle investments, or the other way around when things get better. Only after weighing these scenarios can companies decide whether to hire those workers or invest in that technology.
Faced with high uncertainty, companies usually also have the ability to wait and see to avoid making mistakes. This option is particularly attractive when the business environment is highly unpredictable and the decision to reverse is costly, for example when it is expensive to lay off workers or resell machinery and equipment. But it’s also expensive in itself: waiting means postponing or canceling some projects that would have been profitable. In theory, such delays can have serious economic consequences. They could reduce a country’s productivity if many companies end up operating on a suboptimal scale or with suboptimal technology. This problem is potentially more serious in developing and emerging economies, where corporate investment and the adoption of inadequate technologies often reduce productivity and economic growth.
Practicallyhowever, economists struggle to understand how uncertainty affects businesses and the macroeconomy. Part of the reason is that standard measures of uncertainty such as stock market volatility and disagreement among forecasters do not capture uncertainty at the individual asset level; that is, business managers of uncertainty feel around their forecast of future sales and performance. Only recently have researchers made substantial progress in directly measuring this subjective uncertainty at the firm level. The state-of-the-art methodology uses surveys of business executives that elicit a series of scenarios about their company’s future results and a probability for each scenario. This combination of scenarios and probabilities allows researchers to build business measures forecasts and business uncertainty as perceived by each individual manager.
So far, most of the efforts to measure the subjective business forecasts And uncertainty have been limited to a handful of high-income countries like the United States and the United Kingdom, but new data collected by the World Bank shows that a simplified version of this cutting-edge methodology also works well in developing and emerging economies . This is an important development because many researchers believe it would be difficult to conduct this type of survey in developing countries, where companies and their managers may be less sophisticated. New data from the World Bank refutes these concerns and reveals systematic differences in how corporate executives perceive uncertainty in countries that have different income levels.
The data in question comes from the World Bank’s Business Pulse and Enterprise Surveys, created to track the impact of the coronavirus pandemic on the private sector. Both surveys include a module that elicits a central, optimistic and pessimistic scenario for your businesses’ future sales along with the probabilities for each scenario. Between April 2020 and March 2022, over 23,000 companies participated in 41 countries in Eastern Europe, Asia, Africa and Latin America. The countries covered cover a wide range of income levels, from Madagascar on the low end to Poland on the high end.
Apparently, the sales forecast and uncertainty measures constructed from these World Bank data gain a lot of insight into the business outlook that managers are aware of, as the following stylized facts show.
First, forecasts for future sales predict actual future sales as reported in the follow-up survey interviews (Figure 1). Second, managers who express greater uncertainty at the time of forecasting tend to make larger forecasting errors (Figure 2). This second fact states that the survey-based measure of business uncertainty captures the degree of unpredictability or volatility of business sales and reflects similar findings from survey efforts in advanced economies.
Figure 1. Sales forecasts predict actual sales
Notes: Grouped scatter plot of sales made in the follow-up interview versus sales expectations (forecast) for the next six months on the horizontal axis. Both realized and expected sales are expressed with respect to 2019 levels.
Figure 2. Firms reporting greater uncertainty make larger forecasting errorsNotes: Bound scatter plot of the absolute error between sales expectations (i.e., forecasts looking six months ahead) and sales made in the follow-up interview, versus the subjective six-month sales uncertainty in advance. Both realized and expected sales are expressed with respect to 2019 levels.
Second, there are systematic differences in business uncertainty between countries at different levels of development—A new stylized fact. Firms in poorer countries, that is, those with lower per capita GDP levels, tend to have higher levels of uncertainty on average (Figure 3). Previous research had shown that employment, sales and investment data are more erratic in low-income countries. But now it is clear that this is not due to low quality or noisy data. Instead, business leaders actually perceive uncertainty of being three to six times higher in those low- and middle-income countries than in the United States or the United Kingdom Therefore, high levels of business uncertainty are likely to distort investment and hiring patterns in low-income countries. This discovery takes researchers one step closer to demonstrating that, indeed, some countries may fail to develop and grow because their unpredictable business environment encourages companies to wait and see too much, rather than investing and improving their productivity.
Third, the negative relationship between uncertainty and GDP per capita is not easily explained. It does not appear to result from differences in the composition of the business sector between countries. It is also not systematically related to the volatility of exchange rates or economic cycles, which are often higher in developing and emerging countries. On the contrary, there appears to be a solid relationship between economic development and the amount of risk and unpredictability (i.e. uncertainty) that firms perceive in their economic environment.
Figure 3. Employment-weighted business uncertainty decreases with per capita GDP.
Notes: This figure plots the employment-weighted subjective uncertainty in each country, averaged across waves of World Bank business and enterprise surveys relative to the country’s GDP per capita in 2019 on the horizontal axis. We weigh companies based on employment within each country. UK and US values taken as averages for April 2020 – December 2021 and April 2020 – March 2022 respectively.
The evidence from these World Bank polls has at least two political implications. First, central banks and governments in low- and middle-income countries can collect forecasting and uncertainty data as part of their routine business surveys and thus obtain timely information on business prospects. Such data could be a boon to policy makers and researchers interested in macroeconomic fluctuations and business dynamics in these countries. In addition, country-specific surveys could also collect forecasts and uncertainty data on prices, employment or investments that could be useful for the conduct of monetary, fiscal and business development policy.
Second, addressing and reducing the amount of uncertainty perceived by businesses through specific policy interventions could play an important role in supporting business investment and growth in developing countries, generating positive effects for the macroeconomy. And the economic benefits of making business uncertainty a higher political priority could also bring greater stability to the political and social spheres, which in turn are important to the business environment.