Uncertainty about business prospects is a fact of life for any business. When deciding whether to hire new employees or invest in a new technology, companies do not know whether it will lead to increased sales and profits due to factors beyond their control. Instead, they forecast future sales revenue (and other performance metrics) and factor in the uncertainty surrounding those forecasts. They think through situations where things could turn out worse than forecast, leaving them with too many employees and useless investments – or the opposite when things turn out better. Only after considering these scenarios can companies decide whether to hire those employees or invest in that technology.
When there is great uncertainty, companies usually also have the option of waiting to avoid mistakes. This option is most attractive when the business environment is highly unpredictable and the decision to roll back is costly, such as when it is expensive to lay off employees or to resell machinery and equipment. But it’s also costly in itself: waiting means postponing or canceling projects that would have been profitable. In theory, such delays can have major economic consequences. They can lower a country’s productivity if many companies start operating on a sub-optimal scale or with sub-optimal technology. This problem is potentially more serious in developing countries and emerging economies, where inadequate business investment and technology adoption often slow productivity and economic growth.
In practiceHowever, economists struggle to understand how uncertainty affects businesses and the macro economy. Part of the reason is that standard measures of uncertainty, such as stock market volatility and disagreement with forecasters, do not reflect uncertainty at the level of individual companies; that is, the uncertainty business managers watch around their forecasts of future sales and performance. Only recently have researchers made substantial progress by directly measuring this subjective uncertainty at company level. The state-of-the-art methodology uses surveys of business managers that elicit a series of scenarios about future results of the own company and a probability for each scenario. This combination of scenarios and probabilities allows researchers to construct business measures predictions and business insecurity as perceived by each individual manager.
So far, most attempts to measure subjective things predictions and insecurity are limited to a handful of high-income countries, such as the US and UK. But new data collected by the World Bank shows that a simplified version of this advanced method also works well in developing countries and emerging economies. This is an important development because many researchers thought it would be difficult to conduct these types of surveys in developing countries, where companies and their managers may be less sophisticated. The new data from the World Bank refutes these concerns, revealing systematic differences in how corporate managers perceive uncertainty between countries with different income levels.
The data in question comes from the World Bank Business Pulse and Enterprise Surveys, which were established to monitor the impact of the coronavirus pandemic on the private sector. Both surveys contain a module that evokes a central, optimistic and pessimistic scenario for future sales of own companies, as well as opportunities for each scenario. More than 23,000 companies in 41 countries in Eastern Europe, Asia, Africa and Latin America participated between April 2020 and March 2022. The countries involved span a wide range of income levels, from Madagascar at the bottom to Poland at the top.
It turns out that measurements of business sales forecasts and uncertainty constructed from this data from the World Bank contain a lot of information about the business prospects that managers are aware of, as the following stylized facts show.
First, forecasts for future sales predict actual future sales as reported in follow-up survey interviews (Figure 1). Second, managers who express higher uncertainty at the time of forecasting tend to make greater forecasting errors (Figure 2). This second fact says that the survey-based measure of business uncertainty reflects the degree of unpredictability or volatility of company sales, and reflects similar results from survey efforts in advanced economies.
Figure 1. Sales Forecasts Predict Actual Sales
Explanation: Binned scatterplot 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 both expressed relative to 2019 levels.
Figure 2. Companies reporting higher uncertainty make larger prediction errorsNotes: Binned scatterplot of the absolute error between sales expectations (ie forecasts looking six months ahead) and sales realized in the follow-up interview, against subjective uncertainty about six months of presales. Realized and expected sales are both expressed relative to 2019 levels.
Second, there are systematic differences in business insecurity between countries at different levels of development– a newly stylized fact. Companies in poorer countries, ie countries with a lower GDP per capita, have more uncertainty on average (Figure 3). Previous research had shown that employment, sales and investment data are more erratic in lower-income countries. But now it is clear that this is not due to low quality data or noise. Instead, business managers actually perceive insecurity to be three to six times higher in those low- and middle-income countries than in the US or the UK. High levels of business uncertainty are thus likely to disrupt investment and hiring patterns in low-income countries. This finding brings researchers one step closer to demonstrating that indeed some countries cannot develop and grow because their unpredictable business environment encourages companies to wait too much, rather than invest and improve their productivity.
Third, the negative relationship between uncertainty and GDP per capita is not easily explained. It does not seem to stem from differences in corporate composition between countries. Nor is it systematically related to the volatility of exchange rates or business cycles, which are often higher in developing and emerging countries. Instead, there seems to be a strong relationship between economic development and the amount of risk and unpredictability (i.e. uncertainty) that companies perceive in their economic environment.
Figure 3. Employment-weighted uncertainty in firms decreases with GDP per capita.
Notes: This figure plots the employment-weighted subjective uncertainty in each country averaged over waves from the World Bank Business Pulse and Enterprise Surveys against the country’s 2019 GDP per capita on the horizontal axis. Within each country, we weigh companies on employment. UK and US values taken as averages for April 2020 – December 2021 and April 2020 – March 2022, respectively.
The evidence from these World Bank surveys has at least two policy 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, providing timely information on business prospects. Such data could be a boon to policymakers and researchers interested in macroeconomic fluctuations and business dynamics in these countries. In addition, country-specific surveys could also collect forecasts and uncertainty data about prices, employment or investment that could be useful for the conduct of monetary, fiscal and business development policies.
Second, addressing and reducing the uncertainty experienced by companies through specific policy interventions could play an important role in supporting business investment and growth in developing countries, with positive effects on the macro economy. And the economic benefits of making business uncertainty a higher policy priority can also bring greater stability in the political and social spheres, which in turn is important for the business environment.