Measuring business volatility in emerging and developing economies

Uncertainty about business prospects is a fact of life for any business. When deciding whether to hire new employees or invest in new technology, businesses don’t know if this will result in higher sales and profits because of factors beyond their control. Instead, they forecast future sales revenue (and other performance measures) and take into account the uncertainty surrounding those forecasts. They think that things could be worse than predicted, leaving many workers and idled investments – or vice versa when things get better. Only after weighing these factors can companies decide whether to hire those workers or invest in that technology.

When faced with high uncertainty, firms often have the option to wait and see to avoid making mistakes. This option is most attractive if the business environment is very unpredictable and the decision is expensive to reverse, for example if it is expensive to fire employees or resell machinery and equipment. But it is expensive in itself: waiting means delaying or canceling some potentially profitable projects. In theory, such delays can have significant economic consequences. If too many businesses operate at low levels of technology, they can lower a country’s productivity. This issue may be more pressing in emerging and developing economies, where insufficient business investment and technology adoption drag down productivity and economic growth.

Measuring uncertainty

In practiceHowever, economists struggle to understand how much uncertainty affects business and the macro economy. One reason is that standard measures of volatility, such as stock market volatility and forecast volatility, do not capture uncertainty at the level of individual businesses. That is, uncertainty business managers pay attention About their future sales and performance forecasts. Recently, researchers have made significant progress in measuring this directly Actual instability at the organizational level. The modern method uses surveys of business managers that show a series of scenarios about future auto-firm outcomes and the probability of each scenario. This combination of factors and conditions allows researchers to develop business metrics Predictions and business Uncertainty As perceived by each individual manager.

So far, most efforts to measure objective trade Predictions And Uncertainty While limited to a few high-income countries like the US and the UK, new data from the World Bank show that a simpler version of this system works well in developing and emerging economies. This is an important development because many researchers believed that it would be difficult to conduct such a survey in developing countries where businesses and their managers may be more sophisticated. New World Bank data refute those concerns and show systematic differences in the way business managers perceive uncertainty in countries with different income levels.

The data in question comes from the World Bank’s Business Pulse and Enterprise Survey, created to track the impact of the coronavirus pandemic on the private sector. Both surveys include a central, optimistic, and pessimistic scenario module for future corporate sales with each scenario. More than 23,000 businesses in 41 countries across Eastern Europe, Asia, Africa and Latin America participated between April 2020 and March 2022. The countries covered a wide range of income levels, from Madagascar at the low end to Poland at the high end.

Unfashionable facts

As can be seen, the business sales forecasts and uncertainties constructed from these World Bank data, the following stylized facts, contain the most information about business that managers know.

First, future sales forecasts predict actual future sales As reported in follow-up survey interviews (Figure 1). Second, managers who express greater uncertainty at the time of the forecast make larger forecast errors (Figure 2). This second fact is that the survey-based measure of business volatility captures the level of unpredictability or volatility of firms’ sales and shows similar results to efforts in advanced economies.

Figure 1. Sales forecasts predict actual sales

Notes: Dispersion of sales perceived in a follow-up interview against sales expectations (forecast) on the horizontal axis for the next six months. Both confirmed and expected sales are expressed relative to 2019 levels.

Figure 2. Firms reporting high uncertainty make larger forecast errorsNotes: Scatter plot of the absolute error between sales expectations (i.e., forecasts six months ago) and sales confirmed in the follow-up interview, versus uncertainty in sales six months ago. Both confirmed and expected sales are expressed relative to 2019 levels.

Second, there are systematic differences in business volatility across countries at different stages of development.– New Fashionable Reality. Businesses in poorer countries, ie those with lower GDP per capita, tend to have higher uncertainty on average (Figure 3). Previous research has shown that employment, sales and investment data are more inaccurate in low-income countries. But now it is clear that this is not due to low quality or noisy data. Instead, business managers Understand correctly Uncertainty Three to six times higher Higher levels of business uncertainty in those low- and middle-income countries compared to the US or the UK could distort investment and employment patterns in low-income countries. This finding brings researchers one step closer to the fact that some countries may fail to grow and develop because their unpredictable business environment encourages companies to wait and see rather than invest and improve productivity.

Third, the negative relationship between uncertainty and GDP per capita is not easily explained. It does not appear to stem from differences in the composition of the business sector within countries. Often higher in the developing and developing world is not systematically linked to the volatility of exchange rates or business cycles. Rather, there appears to be a strong relationship between economic development and the level of risk and unpredictability (ie, uncertainty) businesses perceive in their economic environment.

Figure 3. Employment-weighted business uncertainty subtracted from GDP per capita.

Notes: This figure plots volatility in each country on the horizontal axis of the country’s average 2019 GDP per capita from the World Bank’s Business Pulse and Enterprise Survey. We measure firms by employment in each country. UK and US prices are taken as April 2020 – December 2021 and April 2020 – March 2022 averages.

Policy implications

The findings from these World Bank studies have at least two policy implications. First, central banks and governments in low- and middle-income countries can collect forecast and uncertainty information such as regular business surveys and obtain up-to-date information on the business outlook. Such information can be useful to policymakers and researchers interested in macroeconomic fluctuations and firm dynamics in these countries. In addition, country-specific surveys can gather information on prices, employment or investment forecasts and uncertainties that are useful for the implementation of monetary, fiscal and business development policies.

Second, addressing and reducing uncertainty perceived by businesses through specific policy interventions can play an important role in supporting strong investment and growth in developing countries and creating positive effects on the macroeconomy. And the economic gains from making business instability a higher policy priority can lead to greater stability in the political and social spheres, which is essential to the business environment.