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Romania: Selected Issues

Author(s):
International Monetary Fund. European Dept.
Published Date:
March 2015
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Export Performance and External Competitiveness1

Core Questions and Findings

  • How did Romania’s exports perform in recent years?

    Romania’s export growth performed well during the post global crisis period, as reflected in steady gains in market share and increases in export-to-GDP ratios. The market share in the imports of main trading partners rose by 37 percent during 2008–13, and the share for transport equipment more than doubled. Most industries have a fairly high domestic value-added content in their exports. Nevertheless, the quality of exports is lower compared to regional peers.

  • What were the key driving forces behind Romania’s strong export performance?

    Export decomposition analysis suggests that domestic push factors (competitiveness effect) were the main driving forces of the positive export growth during 2006–13. While external demand factors also contributed positively to export growth until the global crisis, they became unfavorable for Romania since then.

  • What are policy priorities for securing a vibrant and sustainable export sector?

    Regression analysis indicates that maintaining price competitiveness and alleviating structural impediments are the key ingredients for future sustainable export growth. In this context, it remains crucial to continue allowing for exchange rate flexibility, while at the same time upgrading infrastructure and improving vocational training to attract FDI and boost export growth. Moreover, raising further export quality, promoting export diversification and repositioning toward higher-skill export products would help to protect against shocks and create opportunities to benefit from export-led growth in the medium term. Promoting FDI and facilitating participation in global value chains are essential parts for such a strategy.

A. Introduction

1. Romania’s external account position has undergone a major transition since the global financial crisis. Prior to 2008, net export contribution to the overall economic growth was mostly negative and gradually trending down. While the contribution from real export of goods and services was broadly stable, import growth steadily increased on the back of a stellar economic performance. The crisis forced a swift adjustment in the external sector, with the net export contribution rising by about 16½ percentage points during 2008–09. Over the past few years, strong performance in exports outweighed a gradual recovery in imports, translating into a positive contribution of net exports to overall GDP growth.

Contribution to Real GDP Growth

(In percent)

Sources: Haver; and IMF staff calculations.

2. The improvement in the trade and service balances has led to a sharp correction of the current account balance. The current account deficit fell to 4.2 percent of GDP in 2009 from its peak of 13.4 percent in 2007. The trade balance—particularly a sharp decline in goods imports—has been the main driver of the adjustment, reflecting a substantial compression in domestic demand. Notwithstanding a weak external environment, exports of goods and services witnessed a remarkable growth since 2010, replacing import compression as the major contributor to the improvement in the current account.

Current Account by Components

(In percent of GDP)

Sources: Haver; and IMF staff calculations.

Export and Import Growth

(Percent change, year-over-year)

Sources: Haver; and IMF staff calculations.

3. Against this background, this paper investigates the main factors behind Romania’s recent export performance and assesses the country’s underlying external competitiveness. The recent strong growth in Romania’s exports prompts an important policy question: is the export performance due to cyclical factors, such as favorable external demand, or structural improvements from the domestic supply side? The analysis in this paper contributes to a response to this question. First, it conducts a comprehensive assessment of Romania’s export performance using a wide range of indicators. And second, it identifies the key factors that drive export growth. This will allow developing policy priorities with a view to promoting export-led growth and preserving macroeconomic stability. The analysis will focus on goods exports only, as the service balance historically contributed only a small share to the overall current account balance.2

B. Export Performance

4. Romania’s exports have gradually regained ground after bottoming during 2007–09. Exports of goods as a percent of GDP rose to 34 percent in 2013, surpassing the pre-crisis average of 28 percent of GDP during 2000–07. While exports to non-European Union (EU) countries expanded noticeably during the post-crisis period, intra-EU exports during 2011–13 were only marginally higher than their pre-crisis peak in 2004, reflecting the sluggish recovery in the EU economy. Nevertheless, the EU remains the main destination of Romania’s exports, receiving more than 70 percent of its goods exports during 2009–13.

Exports by Destination

(In percent of GDP)

Sources: Direction of Trade Statistics; and IMF staff calculations.

5. Romania’s exports exhibit revealed comparative advantages (RCA) in labor intensive goods and low and medium-skill manufactures, but disadvantage in high-skill manufactures.3 The RCA in labor intensive and low-skill manufactures has been declining in the past ten years, accompanied by a steady increase of the RCA in medium-skill manufactures. High-skill manufactures continued to show comparative disadvantage throughout the period, albeit a moderate improvement in 2010–11. During this structural transformation process, exports from the once strong textile industry (labor intensive goods) shrank significantly, whereas the non-electronics machinery and transport equipment industry (medium-skill manufactures) has transformed from being a revealed comparative disadvantage to an advantage.4 In particular, machinery and transportation equipments have become the primary export products, accounting for about 40 percent of total merchandise exports in 2007–13. Transport equipment is the major driver of the recent export growth, with its international sales more than doubled between 2007 and 2013. As the industry continues to develop even further, Romania is gradually establishing itself as an important automotive producer in Eastern Europe.

Revealed Comparative Advantage by Degree of Manufacturing

(In percent)

Note: The classification of degree of manufacturing in UNTCAD Stat follows the definition from Trade and Development Report (2002). An RCA index above 1 indicates that the country’s exports of the product account for a larger share in its total exports than the global export share of the same product.

Sources: UNTCAD Stat; and IMF staff calculations.

Composition of Exports (Average of 2007-2014)

(In percent of total exports)

Sources: Haver; and IMF staff calculations.

6. Strong export performance has led to a steady growth of Romania’s market shares in the imports of its main trading partners. Using market share measures in its largest export region, the EU 28 countries, Romania’s exports as a share of total EU imports rose from 0.3 percent in 2000 to 0.8 percent in 2013. Exports of transport equipment experienced a major boom during the post-crisis period, with its market share in the EU market more than doubling between 2008 and 2013. Despite this impressive growth, Romania still has a relative low market share compared to its regional peers.5 Many of the new EU member states expanded their market shares in the post-crisis period, creating more competition in the EU market.

Market Share in the EU

(In percent)

Sources: UNCTAD Stat; and IMF staff calculations.

Market Share in the EU Imports of Transport Equipment

(In percent)

Sources: UNCTAD Stat; and IMF staff calculations.

7. Romania’s exports have a fairly high domestic value-added content, close to the OECD average. According to the OECD-WTO Trade in Value Added (TiVA) 2009 indicators,6 Romania’s domestic value-added embodied in exports as a percent of total exports was almost 76 percent, the highest among regional peers. A higher domestic value-added ratio may indicate a good structure of domestic value chains, but it also suggests slow progress in integrating into global value chains (GVC).7 At the industry level, most of Romanian industries’ domestic value-added contents were above 70 percent in 2009 and higher than in 2000. Increases were particularly large in the transport equipment and textile industries, likely reflecting technology and skill upgrades. Only few industries, such as financial intermediation, increased the foreign content of their exports between 2000 and 2009.

Domestic Value-added Export Ratio by Country

(In percent)

Sources: OECD-WTO TiVA indicators.

Domestic Value-added Export Ratio by Industry, 2000 vs 2009

(In percent)

Sources: OECD-WTO TiVA indicators.

8. Promoting export diversification and upgrading export quality could provide additional outlets for long-term sustainable export growth. Using the diversification indicators developed by an IMF team, Romania’s export diversification improved considerably prior to the crisis but stagnated during 2008–10.8 Compared to regional peers, Romania scored well in export diversification across trading partners, whereas diversification across products still has room for improvement. In theory, greater diversification does not necessarily imply a higher export growth, but it could strengthen the resilience to external shocks and safeguard export stability.9 The sharp drop in the Euro zone’s import demand during the crisis demonstrated Romania’s vulnerability associated with its export specialization. Improving export quality presents another channel of promoting export growth. In this regard, most Romanian export products are in the lower range of the EU countries quality ladder, suggesting large potential for quality upgrading. On car exports, Romania has gradually improved its relative quality since 2003, moving from 83 percent to 88 percent of the world frontier. Comparing to regional peers, however, there is still much scope for further quality upgrading.

Export Diversification

(Index)

Note: Higher index values indicate less diversification.

Sources: IMF Export diversification database.

Export Diversification: Country Comparisosn

(Index)

Note: Higher index values indicate less diversification.

Sources: IMF Export diversification database.

EU Countries Quality Ladder, 2010

(Index)

Sources: IMF Export Quality Database; and IMF staff calculations.

Quality of Car Exports by Country

(Index)

Note: The index is a relative measure with 90th percentile set to 1 in the relevant product-year combination for the world sample. Higher values indicate higher quality levels.

Sources: IMF Export Quality Database; and IMF staff calculations.

C. Export Decomposition Analysis

9. This section examines the driving forces of Romania’s export growth using a constant market share analysis of export decomposition. The constant market share analysis (CMSA), also known as the shift-share analysis, is a statistical decomposition methodology widely used in the trade literature.10 The general idea behind the CMSA is to decompose export market share changes into “pull” and “push” factors. While the former capture the impacts from changes in external demand or sectoral shifts in global markets, the latter demonstrate how different structures of individual countries’ exports affect their relative performance. The “push” factors are hence often interpreted as a broad measure of an economy’s “competitiveness” (see Annex I for technical details).

10. The analysis is conducted using annual merchandise exports data from UNTCAD Stat in value terms over the period 2006–13. The data covers Romania’s trade flows with all trading partners. Sectors are grouped into industries according to the ISIC (International Standard Industrial Classification) 2 digits classification. The decomposition analysis focuses on variation in export market share along the intensive margin, that is, changes in each individual sector. However, given that trade flows may be created or destroyed during the reference period, the calculation of percent changes in market share could be problematic when there is an extensive margin change (emergence of new export products or discontinuing of existing export products). To cope with this issue, we deviate from the standard literature by using the “mid-point growth rate” to calculate the percent changes.11

11. The results of the CMSA suggest that the competitiveness effect was the main driving force of the positive export growth from 2006–13. During this period, Romania’s export market share in the global trade market increased from 0.26 percent in 2006 to 0.35 percent in 2011. Much of the change was explained by domestic “push factors,” with its contribution mostly positive during the sample period except for 2006 and 2012. Among the “pull” factors, sectoral specialization contributed negatively during the onset of the global financial crisis, possibly reflecting the impact of the collapse of international trade. Changes in external demand had a positive impact prior to 2009, but became unfavorable for Romania since the start of the Euro zone crisis in 2009–10 due to its export concentration in the EU market. Moreover, the geographical composition effect accounts for most of the decline in 2012 reflecting continued distress in the Euro area. Overall, the positive push effect demonstrates that the domestic supply-side competitiveness possibly played a crucial role in Romania’s recent export performance.

Results of the Constant Market Share Analysis(Percentage changes, year-over-year)
20062007200820092010201120122013
Export market share1.37.95.76.20.26.1−8.411.2
Competitiveness effect−0.32.15.610.83.37.8−0.810.7
Structure effect1.65.90.2−4.6−3.0−1.7−7.60.5
Sectoral effect−0.80.3−1.80.0−0.4−1.6−0.31.5
Georgraphical effect1.53.70.9−3.3−4.8−0.4−5.1−0.2
Mix structure effect0.92.01.1−1.32.20.3−2.2−0.8
Sources: UNTCAD Stat; and IMF staff calculations.

Export Performance Decomposition

(Percentage points)

Sources: UNTCAD Stat; and IMF staff calculations.

D. External Competitiveness

12. What have been the key driving factors behind developments in Romania’s external competitiveness and what are key policy priorities going forward? These are the key questions explored in this section. The analysis goes beyond the decomposition analysis, which presents a useful measure of competitiveness in general, but does not yield conclusions on how to improve a country’s competitiveness. Thus, this section investigates the relationship between the estimated competitiveness effects from the CMSA and a series of price and non-price competitive measures, with a view to identifying the underlying factors that determine Romania’s external competitiveness and policies how to influence them.

13. Measures of non-price competitiveness indicate that structural impediments could potentially weigh on Romania’s external competitiveness. The World Economic Forum’s Global Competitiveness Index (GCI), based on a comprehensive assessment of countries’ competitiveness, ranks Romania 76th out of 148 countries in 2013–14. While the macroeconomic environment and technological readiness improved over the past three years, structural conditions in many other areas deteriorated noticeably, including institutions, infrastructure, health and primary education, as well as labor market efficiency.12 Overall, the 2013–14 survey identifies Romania as having a comparative advantage in macroeconomic environment and market size, but a disadvantage in institutions and infrastructure.

Global Competitiveness Indicators

(Score, 1-7, a higher score is better)

Sources: World Economic Forum, Global Competitiveness Report, 2013-14.

14. Turning to price competitiveness indicators, the Romania leu appreciated noticeably in real effective terms vis-à-vis the currencies of trading partners since 2012. Despite a fair amount of depreciation in 2011 and early 2012, the CPI-based real effective exchange rate (REER) appreciated 7¾ percent between 2012Q3 and 2014Q4. This exchange rate development was in contrast to that of its regional peers, as many of the neighbor countries experienced either only a moderate appreciation or even depreciation. The ULC-based REER has been moving closely with the CPI-based REER since 2011, although historically this measure suggests a much larger real exchange rate movement during 2007–10.

Real Effective Exchange Rate, Country Comparison

(Index 2000=100, + = appreciation)

Sources: INS; and IMF staff calculations.

Real Effective Exchange Rate

(Index 2005=100, + = appreciation)

Sources: Eurostat; and IMF staff calculations.

Box 1.Methods and Data Used to Estimate the Factors for Competitiveness

Regression analysis is used to examine how the various measures of price and non-price competitiveness impact the determinants of supply-side export performance (i.e., the competitiveness effect derived in the previous CMSA of decomposition).

Data: The sample period was chosen based on the availability of the competitiveness measures. Given that the World Economic Forum’s GCI starts from 2006 and is available only on annual basis, we expanded our data sample to the industry level and conducted the analysis using a cross-industry panel regression (details are described in Annex II). Following the ISIC 2 digits classification, the data covers 64 industries across 8 years. Due to limitation of the annual series data, only 6 out of the 12 indicators from the GCI can be tested in the regression model.

Model: The supply-side export performance is modeled as a function of the ULC-based REERs and a set of selected indicators that measure the structural conditions of the economy.1 The dependent variable is the industry-level competitiveness effect identified in the previous export decomposition analysis. The explanatory variables are indicators that cover the overall assessment of Romania’s institutions, infrastructure, macroeconomic environment, higher education and training, goods market efficiency, and labor market efficiency.2 Two model specifications were considered: Model (1) estimates constant marginal effects of the structural conditions, and Model (2) estimates variable marginal effects.

1 The ULC-based measure of the real effective exchange rate seems to be an appropriate choice in this context, given that our analysis focuses on goods exports, whereas the CPI also includes services and a large share of nontradable goods. Nevertheless, we examined the effect of the CPI-based REERs, but the results are statistically insignificant.2 The higher education and training index covers a wide range of issues, including assessments on secondary education enrollment, the quality of education and the availability of specialized and on-the-job training services. We focus on training service in particular, as it most likely matters for the export industry.

15. The regression results suggest that alleviating structural impediments could help strengthen Romania’s export competitiveness. Among the structural indicators, infrastructure stands out as an important factor for export growth—better infrastructure is associated with increases in export competitiveness (text table). For illustration purpose, consider that the infrastructure index in Romania (GCI level of 3.33 in 2013–14) and would be upgraded to the level in Poland (GCI level of 3.96 in 2013–14). Though one has to take this with a grain of salt since these indices are developed using opinion surveys, such an upgrade could potentially expand Romania’s export market share by almost 15 percent.13 Favorable macroeconomic environment and better specialized training services could also enhance export performance.14 On the other hand, the effect of goods market efficiency is statistically robust in Model (2) only, which indicates that its impact is likely to be non-constant.

Export Competitiveness Effect EquationDependent variable = yoy change in export market share
Model (1)Model (2)
REER (yoy change)−0.02*−0.01*
(0.01)(0.01)
Global Competitiveness Index
Institutions0.620.10
(0.69)(1.89)
Infrastructure0.35**1.63**
(0.17)(0.71)
Macroeconomic environment2.85*13.48*
(1.50)(6.98)
Specialized and on-the-job training services2.61*12.05*
(1.42)(6.45)
Goods market efficiency1.137.98*
(0.76)(4.12)
Labor market efficiency2.5811.01
(1.63)(6.85)
Number of observations512512
R-squared0.360.36
Number of industries6464
Note: Robust standard errors in parentheses, *** p<0.01, ** p<0.05, * p<0.1. All models include an industry fixed effect. Model (1) uses the level of the global competitiveness index; Model (2) considers the natural log of the competitiveness index.

16. In line with expectations, price competitiveness is also an important factor driving the supply-side export performance. According to the results of the estimation, a real exchange rate appreciation has a significant and negative effect on the growth of export market share (text table). All else equal, a 10 percent of REER appreciation could potentially reduce Romania’s export market share by about 12 percent. To examine the appropriateness of Romania’s current exchange rate level, we now present the results of the equilibrium exchange rate assessment.

17. Standard CGER-type methodologies for assessing the equilibrium exchange rate suggest that Romania’s real exchange rate is broadly in line with medium-term fundamentals.15 The macroeconomic balance approach indicates that the projected underlying current account deficit is lower than the current account norm of 4.1 percent of GDP. Assuming that only exchange rate changes can deliver a current account adjustment, an appreciation of 3.1 percent would be needed to close the gap between the underlying current account and the norm. Similarly, the external sustainability approach points to a modest undervaluation of 3.2 percent, given that the current account norm required to maintain the International Investment Position (IIP) at the current level (60 percent of GDP) is higher than the projected underlying deficit. Finally, taking into account the adjustment in the baseline projection, the equilibrium real exchange rate approach suggests a marginal overvaluation of 2.1 percent. Overall, considering the margins of error in these estimations, the real exchange rate is assessed to be in line with fundamentals.

Exchange Rate Assessment(In percent of GDP, unless otherwise indicated)
ApproachOver- (+) or Under- (-) Valuation
Macroeconomic balance−3.1
Current account norm−4.1
Underlying current account−3.3
External sustainability−3.2
Current account norm−4.1
Underlying current account−3.3
Equilibrium real exchange rate2.1
Source: IMF staff calculations.

E. Conclusion and Policy Discussion

18. Romania’s export growth performed well during the post-crisis period, mostly supported by domestic push factors. Its market share in the imports of main trading partners has steadily increased, particularly in the machinery and transport equipment industry. Despite significant structural transformation in the last decade, Romania’s revealed comparative advantage remained concentrated in labor intensive goods and low and medium-skill manufactures. While export diversification—both across products and trading partners—improved somewhat prior to the crisis, the process has stagnated since 2008. Most industries have a fairly high domestic value-added content in their exports, suggesting that Romania is gradually moving up the value-added chain. Nevertheless, the quality of Romania’s exports is relatively low comparing to regional peers and most products are ranked in the lower range of the EU countries quality ladder.

19. Going forward, improving export quality, promoting diversification and repositioning toward high-skill export products are crucial for the development of vibrant export sectors. Preceding the global financial crisis, Romania’s export growth was largely facilitated by trading partners’ fast growing imports. In recent years, however, export expansions were mostly supported by the strengthening of domestic competitiveness. In light of continued weakness in trading partners’ economic growth, Romania should build on the recent gains in structural competitiveness and boost export diversification to strengthen resilience to external shocks. In addition, repositioning toward exports of high-skill manufacturing goods presents a good potential for sustainable export growth in the medium term. At the industry level, upgrading export quality could help further improve export performance and safeguard medium and long-term sustainable growth.

20. Promoting foreign direct investment and participating in global value chains are also essential. Romania received sizeable amounts of FDI prior to the crisis, but the trend was reversed in recent years amid weak growth in the Euro area. The activity of foreign investment companies in Romania is generally export orientated and their contribution to total exports amounted to more than 70 percent in 2013.16 Given the vital role of FDI in export sectors, reviving FDI inflows can serve as an engine for future export growth. In this regard, policy priorities should be geared toward promoting a favorable business environment, including promoting sound and predictable macroeconomic policy, maintaining economic flexibility, and strengthening governance institutions. Furthermore, greater integration in global value chains could provide additional opportunities for Romania’s exports. While participation in global value chains may temporarily erode a country’s domestic value-added embodied in exports, the overall effect tends to be positive as the spur in exports typically raises the value-added generated both abroad and domestically (Rahman and Zhao, 2013).

21. Last but not least, maintaining price competitiveness and alleviating structural impediments are key ingredients for medium-term sustainable export growth. Standard assessment models suggest that Romania’s real exchange rate is broadly in line with medium-term fundamentals. In this context, it remains essential to continue allowing for exchange rate flexibility and safeguard the competitiveness gains accumulated in recent years. On the structural front, upgrading infrastructure and improving vocational training are top priorities for attracting FDI and boosting export growth. In this regard, securing sufficient fiscal space for public investment and increasing the quality of capital spending is indispensable. More importantly, the focus should be given to enhance the quality and efficiency of project spending and boost the absorption of EU funds.

Annex I. Export Decomposition—Constant Market Share Analysis

1. The constant market share analysis (CMSA) used in this paper follows a similar formulation as that in ECB (2005), which decomposes changes in export market share between any two periods into two major components—domestic “push” factors and external “pull” factors. The main innovation is that we compute the percent changes in market share using a “mid-point growth rate” instead of the standard year-on-year growth rate. This technique allows us to accommodate both intensive and extensive margin changes in the export market.

2. More specifically, the decomposition of “push” and “pull” factors can be illustrated in the following equation:

where,

is the growth rate of Romanian (world) exports of product k to destination j in period t,

is the share of product k to destination j in total Romanian (world) exports in period t-1, and

represents the growth of Romanian (world) total exports in period t.

3. The first term in the square bracket in equation (1) is domestic “push” factors or the “competitiveness” effect, which represents the aggregated impact of changes in market share of each product over each destination. The competitiveness effect for a specific industry k is the sum over all destination j. This item will be used as the dependent variable in our regression analysis of explaining the drivers of external competitiveness.

4. The second term in the square bracket in equation (1) represents external “pull” factors. A positive number indicates that Romania’s exports are more concentrated on high-growth products or markets comparing to world exports. This effect can be further decomposed into three items:

(i) a sectoral effect =Σk(θkθk*)gk*,

(ii) a geographical effect =Σj(θjθj*)gj*, and

(iii) a mixed effect = residual =[ΣjΣk(θjkθjk*)gjk*]Σk(θkθk*)gk*Σj(θjθj*)gj*,

Where,

is the share of product k in total Romanian (world) exports in period t-1,

is the share of market j in total Romanian (world) exports in period t-1, and

is the growth of world exports of product k (market j) in period t.

5. The mixed effect is essentially a residual item, representing the interaction between the sectoral and geographical structures. This implies that the two structure effects are not independently distributed. Hence, item (i) and (ii) above provide a good proxy for the sectoral and geographical effect only when the mixed effect is small.

6. The CMSA formulation discussed above deviates from the traditional approach in several aspects, namely to address issues related to translating the continuous-time into a discrete-time decomposition formula and treating the sectoral and geographical effects in a symmetric fashion. See Cheptea (2014) for a more detailed discussion about the traditional CMSA formulation.

Annex II. Regression Analysis on External Competitiveness

A. Model Specifications

1. The econometric analysis examines the drivers of external competitiveness in an industry-level panel regression with industry effects. Two model specifications are considered to capture both constant and variable marginal effects of structural conditions. Model (1) is formulated as following:

where “Competitiveness^” is the series of industry level competitiveness effect (“push” factors) computed in the previous CMSA decomposition. The availability of such a series allows us to concentrate the analysis on the effects of domestic factors exclusively. The term αk represents the unknown intercept for each industry k, i.e., industry specific effects. “ΔREERt” is the year-on-year change in ULC-based REER and the rest of the repressors are measures of structural conditions.

2. Model (2) follows a similar formulation as in Model (1) except the structural conditions are presented in natural log terms:

3. The estimation results are broadly robust to the two model specifications.

B. Data Descriptions

4. The ULC-based REER data are extracted from Eurostat. Measures of structural conditions use the World Economic Forum’s Global Competitiveness Index (GCI) database covering the period from 2006–07 to 2013–14. The details for each indicator are listed below.

Institutions:

1.01 Property rights, 1–7 (best)

1.02 Intellectual property protection, 1–7 (best)

1.03 Diversion of public funds, 1–7 (best)

1.04 Public trust in politicians, 1–7 (best)

1.05 Irregular payments and bribes, 1–7 (best)

1.06 Judicial independence, 1–7 (best)

1.07 Favoritism in decisions of government officials, 1–7 (best)

1.08 Wastefulness of government spending, 1–7 (best)

1.09 Burden of government regulation, 1–7 (best)

1.10 Efficiency of legal framework in settling disputes, 1–7 (best)

1.11 Efficiency of legal framework in challenging regs., 1–7 (best)

1.12 Transparency of government policymaking, 1–7 (best)

1.13 Business costs of terrorism, 1–7 (best)

1.14 Business costs of crime and violence, 1–7 (best)

1.15 Organized crime, 1–7 (best)

1.16 Reliability of police services, 1–7 (best)

1.17 Ethical behavior of firms, 1–7 (best)

1.18 Strength of auditing and reporting standards, 1–7 (best)

1.19 Efficacy of corporate boards, 1–7 (best)

1.20 Protection of minority shareholders’ interests, 1–7 (best)

1.21 Strength of investor protection, 0–10 (best)*

Infrastructure:

2.01 Quality of overall infrastructure, 1–7 (best)

2.02 Quality of roads, 1–7 (best)

2.03 Quality of railroad infrastructure, 1–7 (best)

2.04 Quality of port infrastructure, 1–7 (best)

2.05 Quality of air transport infrastructure, 1–7 (best)

2.06 Available airline seat km/week, millions*

2.07 Quality of electricity supply, 1–7 (best)

2.08 Mobile telephone subscriptions/100 pop.*

2.09 Fixed telephone lines/100 pop.*

Macroeconomic environment:

3.01 Government budget balance, % GDP*

3.02 Gross national savings, % GDP*

3.03 Inflation, annual % change*

3.04 General government debt, % GDP*

3.05 Country credit rating, 0–100 (best)*

Training:

5.07 Availability of research and training services, 1–7 (best)

5.08 Extent of staff training, 1–7 (best)

Goods market efficiency:

6.01 Intensity of local competition, 1–7 (best)

6.02 Extent of market dominance, 1–7 (best)

6.03 Effectiveness of anti-monopoly policy, 1–7 (best)

6.04 Effect of taxation on incentives to invest, 1–7 (best)

6.05 Total tax rate, % profits*

6.06 No. procedures to start a business*

6.07 No. days to start a business*

6.08 Agricultural policy costs, 1–7 (best)

6.09 Prevalence of trade barriers, 1–7 (best)

6.10 Trade tariffs, % duty*

6.11 Prevalence of foreign ownership, 1–7 (best)

6.12 Business impact of rules on FDI, 1–7 (best)

6.13 Burden of customs procedures, 1–7 (best)

6.14 Imports as a percentage of GDP*

6.15 Degree of customer orientation, 1–7 (best)

6.16 Buyer sophistication, 1–7 (best)

Labor market efficiency:

7.01 Cooperation in labor-employer relations, 1–7 (best)

7.02 Flexibility of wage determination, 1–7 (best)

7.03 Hiring and firing practices, 1–7 (best)

7.04 Redundancy costs, weeks of salary*

7.05 Effect of taxation on incentives to work, 1–7 (best)

7.06 Pay and productivity, 1–7 (best)

7.07 Reliance on professional management, 1–7 (best)

7.08 Country capacity to retain talent, 1–7 (best)

7.09 Country capacity to attract talent, 1–7 (best)

7.10 Women in labor force, ratio to men*

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    TudoC., 2012, “Modeling the Evolution of the Romanian Textile Industry: Empirical Evidence of Lead-lag and Causal Relationships,” Fibres & Textiles in Eastern Europe, 20, 4(93), pp. 812.

Prepared by Lucy Qian Liu.

The balance of the service account improved noticeably in 2013, due primarily to the change in data collection. Domestically the service sector has been booming in 2014 as regards job creation. This, however, has not translated to a major upsurge in service exports, indicating an area for future growth opportunities.

A country is said to have revealed comparative advantage (disadvantage) in a product if the product’s RCA index is above (below) 1, which indicates that the country’s exports of this product account for a larger (smaller) share in its total exports than the global export share of the same product.

The literature identifies the rises of labor cost (due to increases in the minimum wage), shortage of labor supply, and the integration into GATT in 2005 as the main factors behind the fall in the textile industry (see Tudor, 2012). In addition, the fast growing of the Asian Supply Chain, particularly exports of China, also contributed to a significant erosion of market share in the global market.

This note uses the other relatively new EU member states as comparator group, including Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovak Republic, and Slovenia.

The OECD-WTO TiVA database only provides data for 2005, 2008 and 2009, while illustrative data going back to 1995 is also available.

Most countries experience an increase in the domestic value-added export ratio in 2009, largely explained by the synchronized collapse of international trade in 2008 and its adverse impacts on global supply chains.

The Export Diversification database includes data only up to 2010, but a longer series of diversification measures compiled by UNCTAD Stat—the Herfindahl index—suggests that the degree of diversification remained broadly unchanged during 2009–13.

Many studies found the relationship between export diversification and growth is nonlinear, with developing countries often benefiting from diversifying their exports whereas advanced economies performing better with export specialization.

For the application of the CMSA, see ECB (2005), Cheptea et al. (2005), and Finicelli et al. (2011).

The mid-point growth rate is defined as gt=xtxt10.5*(xt+xt1), where xt denotes export market share in year t.

Detailed measurements for each indicator are presented in Annex II.

The estimated coefficients are the average marginal effect at the industry level. Hence, for the effect on the economy’s aggregate export, one needs to multiply the result by 64 (number of industries).

The forthcoming background paper for the New Member States (NMS) Policy Forum: “Making the Most of the EU Single Market” also cites vocational training and higher education attainment as obstacles for Romania’s export growth.

For the details of the CGER methodologies, see IMF Occasional Paper No. 261, “Exchange Rate Assessment: CGER Methodologies.”

See “Foreign Direct Investment in Romania 2013” in http://www.bnro.ro/PublicationDocuments.aspx?icid=14364.

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