Increasing business cycle synchronisation: The role of global value chains, market power and extensive margin adjustments

Francois de Soyres, Alexandre Gaillard 21 September 2019

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Over the past 30 years, worldwide business cycle co-movement has increased. In the 1980s, national economic cycles were largely independent, especially for middle- and low-income countries. But economic activity has since become much more correlated, especially for high-income countries (Figure 1).

This is important – synchronisation of economic activity across countries is a key indicator for many macroeconomic policies. For example, the extent to which the euro area can be considered an optimal currency area largely depends on the synchronicity of business cycles among member countries. If economic activity among countries is correlated, this signals interdependence, and calls for greater coordination of their public policies.

Figure 1 Global economic activity is increasingly synchronised

Source: authors’ calculations based on 150 countries in the World Bank World Development Indicators. 
Notes: H: High Income, MH: Medium High Income, MH: Medium Low Income, L: Low Income. GDP is HP filtered. Each bar represents the average of all country-pair GDP correlations, taken over all country-pairs containing one country in each income group specified in the title.

Have shocks become more correlated over time (Imbs 2004), is synchronisation linked to non-technology shocks (Huo et al. 2019), or are shocks increasingly propagated across countries (Frankel and Rose 1998)? If shocks are more widely propagated, are trade or financial linkages associated with their transmission?

Using within country-pair variations over time and controlling for many observable and non-observable factors, we can show that trade in intermediate inputs, linked to the development of global value chains, are strongly associated with the recent increase in business cycle synchronisation (de Soyres and Gaillard 2019a, 2019b). Trade in final goods, or financial linkages measured by foreign direct investments or cross-country claims, do not seem to have a large impact.

The trade co-movement puzzle

There is a puzzle in international macro – the 'trade co-movement puzzle' uncovered by Kose and Yi (2001, 2006). Simply put, standard international business cycle (IBC) models cannot quantitatively account for the positive empirical relationship between international trade and GDP co-movement. This is related to Kehoe and Ruhl (2008)’s curse which states that, in perfectly competitive models, foreign shocks do not have any impact on domestic productivity. In other words, if domestic GDP responds to a foreign shock, it is only through a change in factor supply and not through a change in productivity.

If we are to solve this puzzle, GDP movements should not be decomposed only into changes of technology and factor supply. We need to account for (at least) two other important elements: changes in aggregate profits, and fluctuations along the extensive margin. 

With these elements, we propose the first quantitative solution to the trade co-movement puzzle.

The role of profits in GDP movements

An old insight: markups play an important role in the propagation of shocks. With markups – that is, profits – GDP movements would not only be tied to changes in technology and the associated reaction in factor supply.

As noted previously by Hall (1988) and discussed in Basu and Fernald (2002) and Gopinath and Neiman (2014), price distortions introduce a wedge between marginal cost and the marginal product of inputs, implying that changes in intermediate input usage have a first-order impact on GDP, beyond changes in technology and factor supply. 

The intuition is that with markups, value-added – as computed by statistical agencies – is not simply equal to factor payment. It also includes profits. So even a country with a perfectly inelastic supply of domestic factors and a constant technology would experience GDP movements if profits changed.

Interpreting GDP fluctuations using a structural model with perfect competition, these profit fluctuations could easily be mistaken for a 'non-technology shock' — in the sense that they 'explain' GDP movements that are not changes due to technology shocks and the associated reaction in factor supply. We find that countries characterised by large markups are more sensitive to terms-of-trade variations (Figure 2).

Figure 2 Higher markups are associated with a lower correlation between terms of trade and GDP fluctuations

Note: The left panel uses the 'Price Cost Margin', computed using the OECD STAN database as a proxy for markups. The right panel uses markup estimates from De Loecker and Eeckhout (2018). A more negative correlation means that an increase in import prices is more systematically related to a decrease in real GDP.

Controlling for unobserved factors, our empirical findings emphasise the role of competition distortions to understand an economy’s sensitivity to foreign shocks. In our simulations, reducing markups to zero reduces GDP co-movement (Table 1). This is increasingly relevant, considering the rise of market power around the world (De Loecker and Eeckhout 2018, Díez et al. 2019). 

Table 1 Comparison between data and model simulation, with sensitivity analysis on the role of markups

Note: Trade proximity is defined for each country pair as the sum of bilateral trade divided by the sum of both countries' GDP.

Extensive margin adjustments

Fluctuations along the extensive margin also have the potential to create an additional amplification mechanism between domestic productivity and foreign shocks. As noted by Gopinath and Neiman (2014), love of variety is a form of increasing returns to scale. A firm with more suppliers is more efficient at transforming inputs into output, which leads to an increase of value-added above domestic factor supply variations.

Solow residuals and aggregate technology

Together, market power and extensive margin adjustments create a link between foreign shocks and domestic productivity as measured by the Solow residual (SR), and create a misalignment between the SR and aggregate technology.

Both in data and our simulations, countries with high markups are characterised by a strong relationship between shocks to their trade partners and domestic SR fluctuations. Our benchmark model reproduces a realistic trade-SR slope. This association is absent in a version without markups and extensive margin adjustments.

The SR measures the change in GDP that is not explained by movements of capital or labour fluctuations, and so it captures changes in technology and also fluctuations of profits and adjustments along the extensive margin. While international correlation of the SR is close to 25%, we estimate technology co-movement to be less than 19%. The difference simply reflects the endogenous synchronisation of the SR through trade, due to profits and extensive margin movements. The SR is also much more volatile and less auto-correlated than technology, which means it is a poor proxy for calibrating technology shocks.

Authors’ note: The views expressed in this column are those of the authors and they do not necessarily represent the views of the institutions there are or have been affiliated with.

References

Basu, S, and J G Fernald (2002), "Aggregate productivity and aggregate technology", European Economic Review 46(6): 963–991.

De Loecker, J and J Eeckhout (2018), "Global Market Power", NBER working paper 24768.

De Soyres, F and A Gaillard (2019a), "Value Added and Productivity Linkages Across Countries", working paper.

De Soyres, F and A Gaillard (2019b), "Trade, Global Value Chains and GDP Comovemement: An Empirical Investigation", working paper.

Díez, F, J Fan, and C Villegas-Sanchez (2019), "Global Declining Competition", CEPR discussion paper 13696.

Frankel, J and A Rose (1998), "The Endogeneity of the Optimum Currency Area Criteria", Economic Journal 108(449): 1009–25.

Gopinath, G and B Neiman (2014), "Trade Adjustment and Productivity in Large Crises", American Economic Review 104(3): 793–831.

Hall, R E (1988), "The Relation between Price and Marginal Cost in US Industry", Journal of Political Economy 96(5): 921–47.

Huo, Z, A A Levchenko, and N Pandalai-Nayar (2019), "The Global Business Cycle: Measurement and Transmission", CEPR discussion paper 13796.

Imbs, J (2004), "Trade, Finance, Specialization, and Synchronization", Review of Economics and Statistics 86(3): 723–34.

Kehoe, T and K Ruhl (2008), "Are shocks to the terms of trade shocks to productivity?", Review of Economic Dynamics 11(4): 804 – 819.

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Topics:  Global economy International trade

Tags:  business cycle, markups, profits, trade co-movement

Economist, Federal Reserve Board

PhD candidate in Economics, Toulouse School of Economics

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