Republic of Estonia: Selected Issues

International Monetary Fund. European Dept.

doi:10.5089/9781513526911.002.A001

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International Monetary Fund. European Dept.

International Monetary Fund. European Dept.
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Publication Date:: 22 Jan 2020

eISBN:: 9781513526911

Language:: English

Keywords:: ISCR; CR; CFT; CFT supervision; wage distribution; income inequality; wage ratio; EFSA participation; Anti-money laundering and combating the financing of terrorism (AML/CFT); Income inequality; Gender inequality; Real effective exchange rates; Wages; Global; Baltics; Tariffs; IssuesRepublic of Estonia; Income distribution; Estonia's competitiveness; price differential; trade tension; exposure to shock; export sector performance; Competition; Exports; Export performance

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Selected Issues

Abstract

Selected Issues

Assessing Competitiveness And Exposure To Shocks Integrating Global Value Chains: An Application To Estonia¹

Standard real effective exchange rates (REER) indexes assume trade is only in final goods. But like most European economies, Estonia is highly integrated into global value chains (GVCs). This implies that assessments of competitiveness should take into account trade in value added. Based on a structural model, the paper assesses competitiveness and exposure to trade shocks accounting for the GVC participation in Estonia. The analysis using a REER index considering the GVC architecture suggests potential competitiveness problems in Estonia. The paper also estimates the impact of overvaluation (and appreciation) of the GVC related REER measure on value added export and real GDP growth and finds observable effects. Further, trade tension induced tariff hikes may have important costs for value added produced in Estonia.

A. Introduction

1. Competitiveness is an important component in a country’s macroeconomic performance. Policy makers are typically interested in how their country’s exports stack up against those of their competitors (Bayoumi, et a l, 2018). Finding a loss of competitiveness is helpful in assessing a build-up of imbalances and to guide policies for a smooth adjustment path. This is particularly important for countries like Estonia that belongs to a monetary union. The adoption of the Euro in 2011 has been beneficial overall but it has eliminated the availability of independent exchange rate policy and monetary policy as a tool of addressing macroeconomic imbalances.

2. Gauging competitiveness routinely relies on a package of different exercises. The real effective exchange rate (REER), which provides an aggregate measure of relative changes in international prices by weighting exchange rates based on trade patterns, are the standard metric for measuring such competitiveness. However, empirical analysis of exchange rates presents a range of conceptual and methodological limitations. Thus, in addition non-RER approaches are used and take into account export sector performance, level of production costs, and the quality of the business environment.

3. In the case of Estonia, conventional methodologies are providing different results. Exports of goods to foreign markets as measured by the relative market share have been stable (Figure 1). Price competitiveness as measured by the nominal effective exchange rate (NEER) has been stable since 2015 despite fluctuating within years (Eesti Pank). REER shows signs of appreciation after low inflation during and are above global financial crisis levels. The rise in REER based on unit labor costs has been higher compared to peers (Figure 1) reflecting partly a tightening labor market. The current account surplus has been volatile, but constantly in surplus. Synthetic survey-based indices² of quality of business climate indicate a slight deterioration in competitiveness ranking. However, in assessing competitiveness, these indicators assume that only final products cross borders and do not take into account the global value chains (GVCs) effects, that is the impact of the production processes have become internationally fragmented and trade in intermediate goods and services has substantially increased. Thus, in assessing Estonia’s competitiveness, global value chains (GVCs) should deserve more attention as it is more involved in GVCs compared to peers.

Figure 1.

Evolution of Competitiveness

Citation: IMF Staff Country Reports 2020, 013; 10.5089/9781513526911.002.A001

4. Estonia has participated extensively in GVCs. Its participation is about 75 percent compared to its Baltic peers Lithuania (64 percent) and Latvia (60 percent). Regionally, its participation exceeds that of the EU28 average. In terms of the sectoral dimension of production linkages, the increased participation has been mainly spurred, inter alia, by use of foreign intermediates in exports (backward participation)³ especially in electrical and machinery, textiles and apparel, petroleum and chemicals, transport, metal products, and wood and paper (Figure 2). Estonia incorporates foreign value-added intermediate imports mainly from Finland, Russia, Germany and Sweden. Forward participation, as measured by the amount of value added exported as inputs, is predominantly with Finland and Sweden and is focused mainly in the business and financial services, transport, petroleum and chemicals, woods and paper, and agricultural sectors. The nature of GVCs participation is different for services and manufacturing sectors with services exhibiting more forward linkages (Banh, Wingender and Gueye et al, 2019, forthcoming).

Figure 2.

Global Value Chains Participation

Citation: IMF Staff Country Reports 2020, 013; 10.5089/9781513526911.002.A001

5. This Selected Issue Paper (SIP) strengthens the analytical underpinnings of competitiveness assessments and exposure to shocks by incorporating GVCs. In particular, we use the structural model developed by Bems and Johnson (2017) to derive REER based on value added (VA-REER) that accounts for supply chain linkages by mapping underlying trade in inputs and final goods. The VA-REER thus derived from the structural model is also used to investigate the implications of its over-valuation for value added exports and growth. The paper concludes by discussing the polices needed to foster competitiveness and resilience to external shocks, in the context of GVC.

B. Assessment of Estonia’s Competitiveness Based on Value Added REER

6. Using a structural model that accounts for supply chain linkages and trade in value added we assess Estonia’s competitiveness. We employ a structural framework developed by Bems and Johnson (2017) with the objective to compute a REER index that replaces the weights of trading partners based on their gross trade flow shares with Estonia (conventional REER weights) with weights based on trade in value added.⁴ We use the 2016 vintage of the World Input-Output Database (WIOD, Timmer et al., 2015) to compute the value added REER of Estonia, taking into account bilateral trade in value added.⁵

7. The conventional REER is derived from a log-linearization of the standard Armington CES demand system as follows:⁶

\begin{matrix} C o n v R E E R_{i} = Σ_{j \neq i} [\frac{1}{S_{j}} Σ_{k} (\frac{p_{i} D_{i k}}{p_{i} D_{i}}) (\frac{p_{j} D_{j k}}{P_{k} E_{k}})] ({\hat{p}}_{i} - {\hat{p}}_{j}) (1), \\ w h e r e S_{i} = 1 - Σ_{k} (\frac{p_{i} D_{i k}}{p_{i} D_{i}}) (\frac{p_{j} D_{j k}}{P_{k} E_{k}}) \end{matrix}

In this expression, D_ik denotes country k’s demand for output from i, P_k is the price index for real expenditure by country k on output from all countries (E_k), and D_i is the total demand for country i’s output. This conventional REER thus features the so-called double export weights for bilateral relative price changes, with a weighting scheme accounting for head-to-head competition between i and j in all destinations k (through $\frac{p_{j} D_{j k}}{P_{k} E_{k}}$ ) and the share of each destination in country i’s total sales (through $\frac{p_{i} D_{i k}}{p_{i} D_{i}}$ ).

8. The value-added REER (VA-REER) is derived from a theoretical framework that explicitly distinguishes between gross output and value-added, by modeling production and trade in final goods and inputs. The general expression of the VA-REER is given by:

, \begin{matrix} V A R E E R_{i} = Σ_{j \neq i} [Σ_{k} (\frac{- T^{i j}}{T^{i i}})] ({\hat{p}}_{i}^{v} - {\hat{p}}_{j}^{v}) = Σ_{j \neq i} [\frac{1}{s_{i}} Σ_{k} (\frac{{\hat{p}}_{i}^{v} V_{i k}}{{\hat{p}}_{i}^{v} V_{i}}) (\frac{{\hat{p}}_{j}^{v} V_{j k}}{{\hat{p}}_{k}^{g} F_{k}})] ({\hat{p}}_{i}^{v} - {\hat{p}}_{j}^{v}) (2) \\ w h e r e S_{i} = 1 - Σ_{k} (\frac{{\hat{p}}_{i}^{v} V_{i k}}{{\hat{p}}_{i}^{v} V_{i}}) (\frac{{\hat{p}}_{j}^{v} V_{j k}}{{\hat{p}}_{k}^{g} F_{k}}) \end{matrix}

In this general formula, the REER index features weights $\frac{- T^{i j}}{T^{i i}}$ attached to bilateral relative value-added prices changes. The second part of the expression shows a version that assumes equal elasticities (elasticity of substitution across final goods, across inputs, and between inputs and value added in production). Here, V_ij denotes the value added produced by country i that is ultimately absorbed in country j, $p_{i}^{v} V_{i j}$ is the value-added exports from country i to country j. This second part of the expression is similar to the conventional REER index as it features a double-weighting scheme, but focusing on value added (V_ik denotes country k’s demand for value added from i) and final goods ( $p_{k}^{f} F_{k}$ refers to expenditure on final goods).

9. We use the VA-REER that accounts for the global input output linkages where weights are a complex function of trade flows and elasticities. In its version capturing the full global input-output linkages, it is assumed that the elasticity of substitution across inputs, and the elasticity of substitution between input and value added in production are zero (Leontief production function). This property captures the well-known view of inflexible or rigid production chains, which implies that it is difficult for producers to substitute across suppliers in the short run (see for instance Boehm, Flaaen, and Nayar, 2019; Bayoumi et al, 2019). This measure of VA-REER has also the property of putting more weight on final goods trade, and lower weights on country with strong bilateral input linkages as discussed further below.

Bilateral Conventional and Value-Added Weights (2013–15)

(In percent)

Citation: IMF Staff Country Reports 2020, 013; 10.5089/9781513526911.002.A001

Sources: IMF, Timmer et al (2015) , Bems and Johnson (2017) and IMF staff calculations

10. The difference between value-added weights and gross weights are non-negligible for most trading partners. Overall, bilateral value-added weights are lower than conventional for all countries, but the difference is more pronounced for Finland and Sweden with the absolute percentage of deviation ranging from 36 percent to 79 percent, respectively. This represents a key feature of the GVC-based model that suggests that bilateral trading partners with stronger input linkages tend to have lower cross-price elasticities and hence lower value-added than conventional weights, in line with regional supply chains (Bems and Johnson, 2017 and Bayoumi et al, 2018). However, in some cases the absolute percentage deviation is lower for China, USA and averaging 5 percent, especially for Russia, Germany and negligible for Poland. These data show again how it is important to take into account GVC in assessing Estonia’s competitiveness.

11. VA-REER shows larger changes in price competitiveness compared to conventional REER for Estonia. A comparison of the dynamics of the VA-REER with conventional REER post-adoption of the Euro shows a rising pattern of loss of competitiveness. Estonia’s VA-REER has appreciated more rapidly than the conventional REER (see chart below). Interestingly, the peaks and troughs of the VA-REER seems to track consistently the path of unit labor costs and the correlation between the two is high at 0.8, suggesting competitiveness in supplying domestic value added might be highly dependent on the pickup of labor costs. This implies that VA-REER could offer a complementary assessment that enriches the interpretation of more traditional measures based on gross trade.

Price Competitiveness Developments

(Index 2010=100)

Citation: IMF Staff Country Reports 2020, 013; 10.5089/9781513526911.002.A001

Sources: Bems and Johnson (2017) and IMF Staff Calculations

12. We examine factors that could explain the gap between the VA REER and the conventional REER to inform possible drivers of loss of competitiveness. The gap between the VA REER and the conventional REER contains a price and a weight component that can be modeled as follows:

\begin{matrix} V A R E E R i - & C o n v R E E R i \\ = \sum_{J \neq i} (ω_{i j}^{v} - w_{i j}^{A r \min g t o n}) ({\hat{p}}_{i}^{v} - {\hat{p}}_{j}^{v}) \\ + \sum_{j \neq i} w_{i j}^{A r \min g t o n} [({\hat{p}}_{i}^{v} - {\hat{C P I}}_{i}) - ({\hat{p}}_{j}^{v} - {\hat{E}}_{i / j} - {\hat{C P I}}_{j})] \end{matrix}

where, the first part captures the role of differences in weights between the value-added and the conventional REER. The second term rather captures the differences in prices used in constructing the two REER indexes. This price component has also two subcomponents which are the own-price component $({\hat{p}}_{i}^{v} - {\hat{C P I}}_{i})$ showing the difference between the GDP deflator and the CPI, and the partner price component $({\hat{p}}_{j}^{v} - {\hat{E}}_{i / j} - {\hat{C P I}}_{j}) . \hat{C P I} a n d {\hat{E}}_{i / j}$ are respectively the log changes in the CPI index and the nominal exchange rate respectively.

13. The growing gap between the conventional and value-added REER is largely explained by price differentials. The decomposition reveals that the bulk of the gap—about 74 percent—is predominantly accounted by price differentials while the remaining part is explained by the weight component. A further analysis of the gap shows that half of the price gap is explained by Estonia’s prices used in the VA REER (the GDP deflator) compared to the differential of partner prices. Further, value-added weights account for 29.7 percent of the gap, with a significant role for elasticities at 71.3 percent compared to the small role for weights.

14. Estonia’s price differential shows large discrepancies between the GDP deflator and the CPI. After stabilizing after crisis, the cumulative difference between the GDP deflator and the CPI has increased substantially since 2012. The GDP deflator has grown cumulatively by 16.8 percent since 2012, while the CPI has increased by 12.2 percent during the same period. A closer look at the rapid increase of the GDP deflator shows that a rise in prices of capital goods accounted mainly for the opening of the gap in the beginning of the period. However, prices of capital goods have largely decreased since 2012 (with a pickup in 2017). Decomposing the GDP deflator using the income definition of GDP reveals that unit labor costs have remained a steady driver of final output prices, increasing by about 5.3 percent annually since 2013. Furthermore, while some of Estonia’s euro area trading partners may have also experienced a more rapid increase in the GDP deflator in recent years, the gap between the GDP deflator and CPI appears to be particularly large in Estonia.⁷

Figure 4.

GDP Deflator Developments

Citation: IMF Staff Country Reports 2020, 013; 10.5089/9781513526911.002.A001

C Estonia’s Exposure to Shocks in a World of Global Value Chains

VA-REER Shocks, Value Added Export Performance, and Growth

15. The impact of VA-REER over-valuation shocks on value added export growth can be estimated empirically. A local projection approach à la Jordá (2005), could be used to estimate the dynamic effect of VA-REER misalignment (over-valuation) from shocks on real value-added export growth. This methodology has the advantage of being robust to misspecification as the impulse responses can be defined without knowing the data generating process, and even when its Wold decomposition does not exist (see for instance Koop et al., 1996; Potter, 2000; and Jordá, 2005).⁸,⁹

16. The model specification is as follows:¹⁰

Δ Y_{c, t + h} = δ_{j} Σ_{j = 0}^{h} Δ {[\ln (V A R E E R) - \bar{\ln (V A R E E R)}]}_{c, t - 1 + j} + θ_{h} X_{c t - 1} + α_{c} + τ_{t} + ϵ_{c, t + h} (3)

Where the dependent variable (ΔT_c,t+h) is the change in the logarithm of real value added exports at horizon h; $Δ [\ln (V A R E E R) - \bar{\ln (V A R E E R)}]$ is the change in the VAR misalignment with $\bar{\ln (V A R E E R)}$ representing the long-term value of the VA-REER (obtained through Hodrick-Prescott filter), δ_j are the coefficients of interest for each horizon h=0,1,2,3; α_c is a country fixed effect; τ_t is a time fixed effect; X is a set of control variables including (inflation, real GDP per capita, net foreign direct investment inflows and external demand).

17. Overvaluations in VA-REER are estimated to have a negative and persistent effect on value added exports growth. Our estimates use panel data of 27 European countries over the 2003–13 period and the VA-REER index constructed using the structural framework above. The regressions results suggest that a 10-percentage point over-valuation (positive deviation relative to the long-term value) leads to a statistically significant reduction in value-added export growth by 0.8 percentage point the first year which cumulates to 1.5 percentage point the third year (Figure 3).

Figure 3.

REER Gap Breakdown

Citation: IMF Staff Country Reports 2020, 013; 10.5089/9781513526911.002.A001

18. The impact of the VA-REER over-valuation depends on the degree of integration into GVCs. We estimate the same equation on the subsample of countries highly integrated into GVCs defined as having a GVC participation index higher than the sample median of 69.8 versus the subsample of countries with a low level of integration into GVCs with an index below this sample median. The results show that a 10 percentage point over-valuation in the VA-REER index leads to a reduction in VA export growth by 1 percentage point in the first year and cumulates up to 1.8 percentage point in the third year in countries highly integrated into GVCs. We do not find any statistically significant effect for countries that are weakly integrated in GVCs.

Figure 5.

The Effect of VA-REER Shocks on Real Value-added Export Growth

Citation: IMF Staff Country Reports 2020, 013; 10.5089/9781513526911.002.A001

Sources: IMF Staff estimatesNotes: These figures show the impulse response functions (for a 1 percentage point over-valuation). The dependent variable is the real value-added export growth. Regressions include the full list of control variables, as well as country fixed effects and year fixed effects. Year 0 is the year of the shock. We corrected the Local Projection method following Teulings and Zubanov (2014). 95 percent confidence interval level in dashed lines.

19. VA-REER over-valuation thus has an impact on real GDP growth through trade channels.¹¹ Using the Local projection specification, we estimate the impact of VA export growth on real GDP growth. The empirical results suggest that a 1 percentage point increase in real value-added export is associated with a 0.3 percentage point increase in real GDP growth cumulatively over the 4 years (Figure 6). These estimates are used to calculate the impact of a 10 percent over-valuation in VA-REER on growth as follows:

Figure 6.

The Impact of Value-added Export Growth on Real GDP Growth

Citation: IMF Staff Country Reports 2020, 013; 10.5089/9781513526911.002.A001

Sources: IMF Staff estimatesNotes: These figures show the impulse response functions (for a 1 percentage point increase). The dependent variable is the real GDP growth. Regressions include the full list of control variables, as well as country fixed effects and year fixed effects. Year 0 is the year of the shock. We corrected the Local Projection method following Teulings and Zubanov (2014). 95 percent confidence interval level in dashed lines.

\frac{Δ Re a l G D P g r o w t h}{Δ [\ln (V A R E E R) - \bar{\ln (V A R E E R)}]} = \frac{Δ Re a l G D P g r o w t h}{Δ V A \exp o r t g r o w t h} * \frac{Δ V A e x p o r t g r o w t h}{Δ [\ln (V A R E E R) - \bar{\ln (V A R E E R)}]} (2)

A 10 percent over-valuation in the VA-REER could reduce growth rate by 0.5 percentage point.¹² These findings suggest that VA-REER over-valuations could be associated with a significant loss in competitiveness and growth.

20. The implied estimates of the impact of VA-REER over-valuation for Estonia are expected to be large given its high integration into GVCs. Estonia is among countries that are highly integrated into GVCs, and our estimates imply a reduction in growth by 0.2 percentage point given the average over-valuation of 4 percent in the VA-REER over the period. Growth would have been higher by 0.2 percentage point on average over the period in Estonia if there were no over-valuation, and thus, if there was no such as rise in ULC, given the aforementioned strong pass-through.

Transmission of a Tariff Shock Through Global Value Chains

21. Tariff hikes would propagate through global value chains and thus affecting indirectly countries and sectors beyond those directly targeted. A tariff can affect the competitiveness of an entire value chain by amplifying trade costs as it penalizes not only the assembler of the product but also the supplier. (Yi, 2003 and Miroudot et al, 2013). Moreover, tariffs on goods can also spillover to the service sector as international trade in goods is increasingly integrated with services (OECD, 2013). Finally, escalating trade tensions could impact global economic growth directly through higher trade costs and indirectly via lower business confidence, weaker private sector investment, and tighter financial conditions (IMF, World Economic Outlook, October 2018).

22. Europe is vulnerable to escalated trade tensions given its trade openness and deep integration into GVCs. The exposure of European countries to US tariff shocks in value-added terms has been shown to be larger than in gross trade terms (See Huidrom et al, forthcoming).¹³ Trade tensions could lead to lower investment by fueling uncertainties, (See IMF,2018b and Ebeke and Siminitz, 2018) and thus could negatively affect competitiveness. In particular, countries using foreign value added in their exports such as Estonia may become less competitive as their cost increases due to a tariff hike in the US and China.

23. We use the structural model developed by Bems and Johnson (2017) to estimate the short-run impact of changes in relative international prices induced by tariffs on demand for gross trade and value-added produced in Estonia.¹⁴ Guided by the October 2018 World Economic Outlook, we provide estimates of the impact of trade tension on both gross trade and value-added. We thus analyze the effect of tariff imposed by the United States on its imports, with retaliation by all countries using the same tariff.¹⁵ Because the structural model features demand functions for value added that are obtained holding countries’ real expenditure levels constant, the impact of price changes on the reallocation of production across countries should be viewed as a short-run partial equilibrium effect. Further, it does not account for potential realignment of supply chains that is likely in the long-run.

24. Estonia’s exposure to trade shocks from China, US, and the UK are significant. The bilateral weights implied based on trade in value added are however higher than those based on gross trade flows for China, US and UK. This suggests that Estonia has a weaker input linkage with China, US and UK and, competition with these countries is mainly on final goods (rather than on inputs). Again, because the value added embodied in each production step between countries with strong input linkages is often much lower than the gross trade flow, the VA weights are lower for these countries. Higher VA weights imply therefore a weaker input linkage. Also, it follows that China, US and UK are more important to determine Estonia’s competitiveness once we account for supply chain linkages as compared to gross trade.¹⁶ Overall, accounting for trade in value-added, Estonia would be more exposed to external trade shock (related to tariff hikes) originating in these countries than currently captured by gross trade (Figure 7). Our estimates show that, a 5.9 percent tariff imposed by the US on its imports (Layer 1), with retaliation from all countries using the same tariff, would lead to a reduction of 0.3 percent in Estonia’s value added (three times larger than the reduction in gross turnover flows). A cumulated tariff shock (of all three layers equivalent to a 14.7 percent tariff) would reduce value added produced in Estonia by 0.6 percent.

Figure 7.

Implications of Trade Tensions

Citation: IMF Staff Country Reports 2020, 013; 10.5089/9781513526911.002.A001

Sources: IMF, Timmer et al [2015), Bems and Johnson (2017) and IMF staff calculationsNote:Layer 1: United States imposing a 10 percent tariff on all aluminum imports, a 25 percent tariff on all steel imports, a 25 percent tariff on $50 billion of imports from China, and a 10 percent tariff on an additional $200 billion of imports from China that subsequently increases to 25 percent.Layer 2: United States imposing a 25 percent tariff on a further $267 billion of imports from China and China responding by raising both the base that tariffs apply to and the tariff rates such that all goods imports from the United States also face a 25 percent tariff (roughly $130 billion in imports from the United States).Layer 3: United States following through on the proposal to impose a 25 percent tariff on all imported cars and car parts (worth about $350 billion).Cumulative: A cumulated tariff shock from the three layersGross turnover is the sum of all intermediate and final goods transactions that occurs across sector in Estonia.

25. Estonia’s exposure is relatively moderate compared to most European (EU28) countries. Our estimate of the impact of the US tariff hike (under the Layer 1) yield similar effects for most European countries (except for Luxembourg and Ireland). The largest exposure to trade tensions is found in Germany (owing to the vulnerability of the car industry supply chains) where the reduction in domestically produced value-added reaches 0.43 percent.

US Tariffs (Under Layer 1) and Change in Europe’s Demand by Country

(Percent charge in demand)

Citation: IMF Staff Country Reports 2020, 013; 10.5089/9781513526911.002.A001

Note; Gross turnover is the sum of all intermediate and final goods transactions that occur across sectors in an economy, including gross exports.Sources: Bems and Johnson 2017; Tirnmer and others 2015, IMF staff calculations.

D. Conclusions and Policy Implications

26. The value-added REER (VA-REER) index accounting for input-output linkages suggests that there could be more competitive problems for Estonia than would imply a standard REER index based on gross trade. The recent rise in unit labor cost may have been a drag on Estonia’s ability to supply its domestic value added on world markets reflecting the rising labor cost and wage growth. Preventing a long-term misalignment between wage growth and productivity would help preserve Estonia’s competitiveness.

27. There is significant scope to improve Estonia’s competitiveness in the context of GVCs.

Backward GVC Participation. Estonia’s involvement in GVCs has mainly been toward backward participation, that is the country incorporates significant foreign value added into its own exports. Estonia’s competitiveness could be enhanced by improving the degree of sophistication of its production, which would require greater use of imported intermediate goods with high-technological content. Indeed, using imported inputs allows countries to benefit from knowledge transfers, diversify their export and improve product quality (Amiti and Konings, 2017).
Forward GVC Participation. The participation in activities such as non-transport services have been found to generate substantial productivity gains in Estonia (Benkovskis et al., 2017). Improving allocation and incentives for innovation—through better access to credit and skilled labor with knowledge of foreign markets—could yield significant productivity gains particularly for firms operating in upstream GVCs.

28. Trade tensions induced tariff hikes may have important cost for Estonia especially in term of value added produced in the country. In this regard, policies aimed at enhancing product sophistication or quality and export market diversification could mitigate Estonia’s exposure to trade shocks in GVCs.

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Prepared by Rodgers Chawani and Kodjovi Eklou.

“The Global Competitiveness Report, 2018, “World Economic Forum and “Ease of Doing Business,” 2019 World Bank.

Forward participation refers to the extent to which partner countries use Estonia’s value-added exports as inputs in their own exports while backward participation refers to the extent which Estonia uses foreign intermediate value added to generate output for its own exports.

This value-added REER is obtained as an aggregation of bilateral value-added price changes into an index that measures the average multilateral price of domestic relative to foreign value added. In this index, the weight attached to bilateral price changes depends on the cross-price elasticity of demand, that is the elasticity of demand for value added from a given country with respect to another country’s value-added price. In addition, this cross-price elasticity depends on the interaction of the global input-output structure with relative elasticities in production versus consumption.

Given high persistency in the weights, we assume that they remain constant from 2014 through 2018.

See Bems and Johnson (2017) for details on the derivation. The terms $\hat{x}$ represent a first difference in logarithm of x.

ECB (2016) discusses the decoupling of the GDP deflator and HICP in the euro area after 2014, attributing it largely to the increase in profit margins owing to an improvement in terms of trade (euro depreciation and decline in energy prices).

To reduce potential bias, we implement the correction suggested by Teulings and Zubanov (2014) to control for innovations in the regressors between periods t and t+h when estimating the impulse response at horizon h.

See “Latvia’s Participation In Global Value Chains: Implications For Competitiveness and Exposure to Shocks,” Republic of Latvia, Selected Issues for a similar approach estimating the effect of VA-REER appreciations.

We also estimate the effect of conventional CPI-based REER misalignment on value added export growth and found no statistically significant effect. Further, we estimated the effect of appreciations in VA-REER and found similar results. Also, we tested for asymmetric effects and found that VA-REER under-valuation have a strong, positive and temporary effect on value added export growth while over-valuations have a persistent negative effect.

Using the formula, we calculate the impact by 0.3*(-1.5).

Huidrom et al (forthcoming) estimate the effect of a 5 percent tariff on all US’ imports for Europe and find that it would lead to a decrease in total value-added by 0.2 percent while in gross output term it would be only 0.1 percent. In addition, they also find that most European countries are less competitive in value added terms than in gross trade flow terms.

We use MATLAB code provided in the online Additional Materials of Bems and Johnson (2017) to calculate gross and value-added trade flows, partner weights, effective elasticities of substitution and demand spillovers https://www.aeaweb.org/articles?id=10.1257/mac.20150216). We use the 2016 vintage of the World Input-Output Database (http://www.wiod.org/database/wiots16) to estimate the effect of tariff for 43 countries, from 2000 to 2018. Bilateral exchange rates, CPI and GDP deflator are taken from the World Economic Outlook.

We use the equivalent of a tariff on all US imports implied by the tariffs in each layer. See chapter one of October 2018 WEO. Given the single output price assumption in the structural model, we proceed sequentially. First, we estimate the implied US demand of a tariff induced price change for all goods (except for the US). Second, we estimate the response of demand in other countries to the tariff induced change in the prices of US goods. Our estimations of the tariff impact in both steps are based on the elasticities built in the structural model.

Germany has the largest weight with both concepts, but the value-added weight is lower than the conventional one.

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