The monetary policy dichotomy in emerging economies

The recovery in emerging economies since mid-2020 has been accompanied by a tightening of monetary policy in Latin America and Europe but not in Asia so far (except South Korea). The main reasons for this lie in the level and dynamics of inflation. Inflation is strong and accelerating in Latin America and Europe, more modest and still contained in Asia. A comparison between the most highly industrialised countries of Central Europe and of Asia shows that although the recent acceleration in inflation results in part from common economic factors (higher energy and food prices), the differences in underlying inflation, that were apparent before the pandemic and have persisted since, relate to more lasting/structural factors (pressure on wages and the labour market, exposure of economies to supply-side shocks). The dichotomy in monetary policy looks likely to last.

The acceleration in inflation has become the main concern of central banks. In emerging countries, this led to hikes in policy rates in Brazil, Russia and Turkey in 2020[1]. Since mid-2021 other central banks in Latin America (Chile, Colombia, Mexico, Peru) and Central Europe (Czech Republic, Hungary, Poland, Romania) have followed suit. The increases were particularly marked in Central Europe.

Conversely, Asian central banks, other than in South Korea, have kept their powder dry[2].

The main reasons for this lie in the level and dynamics of inflation. It is high and accelerating in Latin America and Europe, moderate and more gradual in Asia, particularly in China and the most industrialised economies (South Korea, Taiwan, Singapore). How can we explain this dichotomy, when the above mentioned Asian countries were amongst the first to return to their pre-pandemic levels of economic activity? Is it temporary, or does it result from lasting underlying factors wherebyAsian central banks can hold off tightening monetary policy, or at least limit its magnitude?

Underlying inflation: differences and divergence since 2018

To answer this question, this note sets out a comparative analysis of inflation and its main drivers between two groups of countries having relatively similar economic structures, with a strong industrial base: Central European countries (Hungary, Poland, Czech Republic; CECs hereafter) and industrialised Asian countries excluding Japan (South Korea, Taiwan, Singapore; NIAs hereafter).

The comparison covers a five-year period. It has been made easier by the fact that over this period the exchange rates of these countries have not moved significantly, in either direction, relative to their benchmark currency (the US dollar for the NIAs and the euro for CECs).

Three measures of inflation are used: headline inflation, official core inflation and inflation excluding food, energy and housing costs[3].

From 2017, headline inflation rates showed divergent trends up to the end of 2019: deceleration in the NIAs, acceleration in the CECs (Figure 1). Then, the curves went more hand in hand in 2020 (deflation in the NIAs, deceleration in the CECs), followed by an acceleration in 2021.

Core inflation rates followed significantly different paths: for the NIAs, stability to the end of 2018, deceleration in 2019 and 2020, and then a re-acceleration in 2021 that was, however, much less marked than headline inflation (Chart 2). Conversely, in the CECs, core inflation rose throughout the period, a trend interrupted temporarily by the recession in 2020. Lastly, inflation rates excluding food, energy and housing costs show and even emphasize the dichotomy between the two groups (Chart 3), even though for the NIAs, the trend was more uneven than for core inflation in the period from 2019 to 2021. The inflation gap excluding food, energy and housing costs is currently 3.5 points between the two groups. There was not such a gap between 2015 and 2018.

Wage trends and the labour market make more of a difference than recourse to credit

Difference in underlying inflation between the two zones can be explained first by trends in wages reflecting the situation in their labour markets and productivity. In the CECs, nominal wages accelerated rapidly between 2015 and 2019, which was not the case in the NIAs. Wages in manufacturing industry increased by 6.7% per year on average in the CECs, against an average of 2.7% per year in the NIAs.

The more subdued wage growth in the NIAs is not the result of a higher unemployment rate, which is structurally very low (at around 3.5% on average), and did not increase in any of the three countries over the period. However, for the CECs, the traditional relationship between wage growth and the unemployment rate worked as expected, with wages rising in lockstep with a sharp fall in unemployment (Figure 4). Regarding productivity, one might expect a still positive gap for the CECs, which are still catching-up. But the time period of the comparison is too short (prior to the pandemic) and too cyclical (over the recent period) for assessing how the productivity gap has changed between the two zones.

The increase in real wages and the fall in unemployment in the CECs seem, at first sight, to be key explanatory factors for the differences in the growth of household consumption between the two zones, at least until 2019 (Table 2).

Credit may also have been a supportive factor for consumption. However, the comparison of lending to households (total or only consumer credit) does not show differentiated trends between the two zones during the 2015-2019 period (Charts 5 and 6). Credit growth was very strong in South Korea (even though it began to decelerate from 2017), whilst it was negative in Hungary. However, consumer credit was consistently strong in Poland and the Czech Republic, contributing to fuelling consumption and underlying inflation.

CECs more exposed to supply-side shocks

In the recent period (2020-2021), as mentioned above, the gap in underlying inflation between the two zones has widened. However, the comparative trends in household consumption were not as divergent during this period as they were between 2015 and 2019 (Table 2). The same is true of wages, where trends have been highly divergent with some catch-up effects, notably in Asia. Moreover, trends in consumer credit were also more divergent than between 2015 and 2019: strong in Hungary, South Korea and Taiwan, and more recently Singapore, whilst the trend was flatter in Poland and the Czech Republic. In terms of contribution to private consumption momentum, credit may even have been a more significant driving force in the NIAs than in the CECs.

Actually, the widening gap in underlying inflation over the recent period can be explained by the particular nature of the post-Covid recovery (the abrupt fall in production and consumption due to lockdowns, followed by an equally sudden recovery once restrictions were lifted), which simultaneously caused a catching up in consumer spending and shortages or rationing of intermediate products in industry. In Asia, lockdown measures were introduced at a very early stage of the pandemic and were very restrictive, with the result that they were shorter-lived. As a consequence, one can argue that the recovery in consumption may have been less marked than elsewhere, but there is little evidence of this.

A supply-side effect seems to have played a major role, via the degree of integration of countries in global value chains. Indeed, the higher the integration, the more vulnerable industrial sectors to supply and demand shocks. The OECD calculates vulnerability indicators for the two types of shock[4]. The CECs stand out for their high level of exposure to demand shocks, due in particular to the importance of the automotive industry, where they play the role of sub-contractors (the forward integration index is 80% for Hungary and 75% for the Czech Republic, but it is also high for South Korea, at 60%, the same as for Poland). But to assess the impact of shortages or rationing in the price set up, the vulnerability to supply-side shocks is more relevant. Here, the OECD calculations show greater exposure for the CECs than for South Korea, the only NIA country for which data is available (the backward integration index is 60% for Hungary, slightly less than 50% for the Czech Republic, 40% for Poland and just 20% for South Korea). Thus, the pass-through between prices of intermediate products to final output price is larger and faster in the CECs than in South Korea.

This hypothesis is confirmed by Markit PMI surveys, for which data is available for all six countries. Between June 2020 and October 2021, the diffusion index[5] for prices of intermediate products increased by an average of 32 points (from just over 53 to 85), compared to an average of 20 points for South Korea and Taiwan (from 50 to 70) and just 3 points for Singapore.

The increase in output prices in relative terms (i.e relative to the price of intermediate products) has also been greater in the CECs than in the NIAs. The ratio between changes in the diffusion indices for output prices and input prices (below 1 for all countries, as companies have absorbed some of the increase in input prices by narrowing their margins) is 0.8 in the CECs and 0.6 in the NIAs.

In conclusion, the recent acceleration in inflation across both CECs and NIAs results from common factors (higher energy and food prices). However, the gap in underlying inflation, that was apparent before the pandemic and has persisted since, reflects more lasting and structural factors (pressure on wages and the labour market, exposure of economies to supply-side shocks). The dichotomy between the two regions therefore looks set to last.

[1] In Turkey the central bank has performed an about turn since September 2021, making three successive rate cuts, despite an acceleration in inflation to 21.3% year-on-year in November. However, at 15%, the main policy rate is 675 basis points higher than it was in September 2020 and 300 basis points up on the end of 2019.

[2] The South Korean central bank has made two 25 basis point increases since September, taking its policy rate to just 1%.

[3] The scope of official core inflation and inflation excluding food, energy and housing costs differs even though both indexes provide a measurement of the underlying trend in the general price level. Official core inflation is adjusted for volatile prices and the effects of taxation which, due to their temporary and supposedly reversible impact, can hide the underlying trend. Volatile prices for goods and services usually refer to food and energy prices. But official core inflation rates are not strictly comparable. Thus we have also calculated an index excluding food, energy and housing costs for all countries for the sake of harmonisation. This harmonisation has the advantage of taking account of widely controlled prices for water and rent thus providing a better proxy of the underlying inflation trend.

[4] Arriola et al., “Efficiency and risks in global value chains in the context of COVID-19” OECD working paper n° 1637 – December 2020. The vulnerability of a country to a supply shock is from a producer point of view. It is defined by the backward Global Value Chains linkages index, i.e. the foreign value added embodied in domestic production of the given country (in % of total foreign value added). The vulnerability of a country to a demand shock is from the supplier point of view. It is defined by the forward Global Value Chains Linkages index, i.e. the domestic value added embodied in exports of the country (in % of total domestic value added).

[5] Markit’s diffusion indices are on a range from 0 to 100, with 50 indicating no change from the previous month. For Hungary, survey data is from Halpim.