## 1lvaea2024002

## Source details

**Canonical URL:** [1lvaea2024002](https://www.imf.org/-/media/files/publications/cr/2024/english/1lvaea2024002.pdf)

## Other formats

- [Markdown version](/-/media/files/publications/cr/2024/english/1lvaea2024002.pdf.md)
- [Structured JSON version](/-/media/files/publications/cr/2024/english/1lvaea2024002.pdf.json)

---

### Export market share and top destinations
- Latvia’s merchandise exports as a share of global exports "fell by 6 percent between 2021Q3 and 2023Q4."
- The export decline during 2021Q3-2023Q4 was mainly driven by metals, wood, and wood-related sectors.
- Immediate causes included adverse external shocks, notably Russia’s war in Ukraine, which led to supply-chain disruptions and increased input costs.
- The United Kingdom is the eighth largest export destination for Latvia as of 2023; its negative contribution to Latvia’s export share decline during 2021Q3-2023Q4 may be related to the UK’s exit from the European Union in 2020.
- Latvia: Export Destinations, 2023Q4 (Percent; share of total exports):
  - LTU, 16%
  - EST, 11%
  - RUS, 10%
  - DEU, 6%
  - SWE, 5%
  - GBR, 5%
  - POL, 4%
  - DNK, 4%
  - NLD, 3%
  - USA, 3%
  - Other EU, 15%
  - Other non-EU, 19%
- Country contribution to Latvia’s export share decline, 2021Q3-2023Q4: distribution shows negative contributions from some partners (e.g., United Kingdom, Germany, Russia, Lithuania, Estonia) and positive/other contributions aggregated; overall export share fell by 6 percent in the period.

### Real exchange rate, inflation, and labor costs
- High inflation differential and labor costs led to an appreciation of Latvia’s real effective exchange rate (REER).
- The energy shock—given a large share of energy in the consumer price index basket for the Baltics—resulted in a high inflation rate: "twice the euro area average and four times the rate in the lowest-inflation euro area members at one point."
- Large nominal wage growth caused unit labor costs (ULC) to increase, worsening relative costs in Latvia more than in the euro area but less than in the other Baltic countries.
- The combined effect of higher inflation and labor costs undermined the price competitiveness of Latvian exports.
- There was an appreciation of the REER in Latvia and the other Baltics of "around 10-15 percent."

### Constant Share Analysis (CSA) and export share decomposition
- CSA decomposition shows that in Latvia the decline in export share during 2021Q3-2023Q4 was driven by:
  - Weakening external demand (composition effect).
  - Effects of EU trade sanctions in response to Russia’s war in Ukraine (interaction effect).
- Competitiveness issues (intensive margin) played a much less prominent role overall in Latvia’s export share decline.
- Cross-country contrasts:
  - Lithuania’s fall in export share mainly reflected a large contribution from the extensive margin (shrinking foreign demand).
  - Estonia’s decline saw a key role for the competitiveness effect.

### Balassa‑Samuelson assessment and TFP-based REER gaps
- Johansen cointegration tests indicate a long-run relationship between TFP and REER for all three Baltic countries; for Latvia the cointegration result is described as "weak" though a cointegration relationship between TFP and trend REER was established.
- A TFP-based REER is constructed from the long-term TFP–REER relationship; the REER gap is defined as the deviation of actual REER from the TFP-based REER. A negative REER gap indicates price competitiveness advantages.
- Historical patterns:
  - Prior to the GFC, high TFP relative to REER explained consistently negative REER gaps for the Baltics.
  - In Estonia negative gaps were driven largely by high TFP; in Latvia a depreciating real exchange rate was the main factor; in Lithuania the gap was negative for a shorter period (between 2004-2007).
  - Post-GFC the competitiveness advantage faded around 2007-2015 for Latvia and 2007-2010 for Estonia.
  - Latvia maintained a competitiveness buffer (negative REER gap) during mid-2016 to mid-2022, which helped sustain Latvia’s export market share until 2021.
- Recent REER gap timing (gaps turned positive):
  - Estonia: "2021Q4"
  - Latvia: "2022Q3"
  - Lithuania: "2023Q1"
- The decoupling between actual and TFP-based REER in recent years shows widening positive gaps, particularly pronounced in Estonia.

### Productivity, income convergence, and TFP decomposition
- Income convergence: Latvia’s income convergence lags that of the other Baltic economies (GDP per capita in PPP series shown).
- Labor productivity growth, annual average (2009-2020):
  - Latvia: "nearly 3 percent"
  - Lithuania: "nearly 3 percent"
  - Estonia: "around 2 percent"
- Contribution of TFP to labor productivity growth (2009-2020):
  - Latvia: "over half"
  - Lithuania: "20 percent"
  - Estonia: "10 percent"
- Episode decomposition (2009–2020):
  - GFC (2009-2010): negative TFP growth in Latvia and other Baltics; positive labor productivity growth persisted due to significant capital deepening.
  - Post-GFC recovery (2011-2019): Latvia’s TFP growth surpassed that of other Baltics and became the primary driver of its labor productivity growth; labor productivity growth was similar across Baltics.
  - COVID-19 pandemic: TFP growth in Latvia slowed significantly, falling below that for Lithuania.
- Possible drivers of Latvia’s post-GFC TFP performance:
  - Structural reforms during the IMF fund-supported reform program 2009-10 likely contributed to a post-GFC TFP boost.
  - Differences in economic structure: Latvia had a lower share of capital-intensive industries "around 20 percent of total value added in 2019" compared to other Baltics "close to 30 percent"; less-capital-intensive sectors experienced stronger post-GFC labor productivity growth in Latvia.
  - Measurement limitations: TFP is a residual and subject to unobserved factor utilization and measurement error; the large post-GFC drop in gross fixed capital formation and capital stock in Latvia complicates accurate measurement of capital inputs.
  - Different developments in residential investment across the Baltics may explain some productivity differences.

### Empirical results on TFP determinants (selected coefficients and magnitudes)
- EU-28 baseline (dependent variable = TFP growth; Table 1):
  - TFP growth at frontier: 0.174*** (All); 0.178*** (Tradables); 0.133*** (Non-tradables).
  - Technological gap: -12.45*** (All); -13.68*** (Tradables); -10.43*** (Non-tradables).
  - ICT capital: 5.536*** (All); 3.072 (Tradables); 8.657*** (Non-tradables).
  - Non-ICT capital: -0.933 (All); -8.751 (Tradables); 2.533 (Non-tradables).
  - R&D spending: 7.035** (All); 6.197* (Tradables); 7.990 (Non-tradables).
  - Real GDP per capita: 3.794* (All).
  - Inflation: -0.111 (All).
  - Financial development: -0.006 (All).
  - Trade openness: 0.721 (All).
  - Bureaucratic quality: 1.425** (All).
  - Number of observations: 8,615 (All); 4,153 (Tradables); 3,644 (Non-tradables).
  - R2: 0.159 (All); 0.174 (Tradables); 0.144 (Non-tradables).
- EU-28 with country-level controls (Table 1, columns 4–6):
  - TFP growth at frontier: 0.158*** (All); 0.170*** (Tradables); 0.0926** (Non-tradables).
  - Technological gap: -14.34*** (All); -16.19*** (Tradables); -10.88*** (Non-tradables).
  - ICT capital: 5.887** (All); 5.209 (Tradables); 7.665** (Non-tradables).
  - R&D spending: 7.293** (All); 7.729* (Tradables); 5.497 (Non-tradables).
  - Number of observations: 7,505 (All); 3,584 (Tradables); 3,200 (Non-tradables).
  - R2: 0.162 (All); 0.186 (Tradables); 0.138 (Non-tradables).
- Latvia and Lithuania (Table 3; dependent variable = TFP growth):
  - TFP growth at frontier: 0.293*** (column 1); 0.224*** (column 2).
  - Technological gap: -27.77*** (column 1); -27.83*** (column 2).
  - ICT capital: 18.17* (column 1); -0.0142 (column 2).
  - Non-ICT capital: 3.120 (column 1); -8.486 (column 2).
  - R&D spending: -10.90 (column 1); -9.883 (column 2).
  - Real GDP per capita, log: 169.3*** (column 2).
  - Inflation: 0.824 (column 2).
  - Financial development: -0.148** (column 2).
  - Bureaucratic quality: 17.77* (column 2).
  - Population, log: 173.4** (column 2).
  - Number of observations: 315 (column 1); 291 (column 2).
  - R2: 0.367 (column 1); 0.353 (column 2).

### Competitiveness outlook, constraints, and risks
- Latvia’s REER appreciation in recent years has been greater than that implied by its productivity trend, narrowing the competitiveness buffer.
- The positive wedge between the actual and TFP-based REER reduced Latvia’s external price competitiveness.
- Binding constraints to productivity and competitiveness:
  - A decade-long weak investment record.
  - Large infrastructure gaps.
  - Aging and emigration.
  - Insufficient accumulation in skills.
- Risks: Without structural reforms and higher capital investment, Latvia’s TFP growth boost post-GFC is unlikely to be sustained and the country could be caught in a middle-income trap with low growth and slow convergence to euro area income level.
- Policy priority: significantly higher investment is required for sustained convergence; promoting productivity growth via structural reforms and capital investment is key to preserve competitiveness and build resilience against future shocks.

### Policy implications and recommendations (from analysis)
- Promote structural reforms in product, capital, and labor markets to safeguard competitiveness given REER appreciation.
- Raise overall investment—both ICT and non-ICT where binding—to address decade-long weak investment and infrastructure gaps.
- Enhance human capital accumulation and skills to offset aging and emigration impacts; evidence on high-skilled labor effects on TFP is mixed but may matter more close to the frontier and in non-tradables.
- Intensify R&D and ICT investment to facilitate technology adoption and diffusion; R&D and ICT spending are positively associated with higher TFP growth in many specifications.
- Improve institutional quality (bureaucratic quality), which is positively associated with TFP growth.
- Address risks of a middle-income trap by accelerating convergence through targeted investments and reforms to narrow the technological gap.

### Product and labor market regulation, allocative efficiency, and firm-level evidence
- OECD Employment Protection Legislation indicators show Latvia has relatively strict employment protection legislation:
  - Higher severance pay for low tenure employees.
  - Stricter definitions of unfair dismissal including the exclusion of non-performance-related reasons.
  - Generous availability for re-instatement after an employee’s dismissal.
- It is more costly to dismiss an individual worker under a regular contract in Latvia than other OECD economies.
- Latvia and the other Baltic economies rank favorably on product market regulation and financial market liberalization compared to other advanced and emerging market economies.
- Evidence of dispersion in the marginal revenue product of capital among Latvian firms indicates distortions in the capital market.
- Concerns about tight credit conditions and limited access to finance by small firms in Latvia are noted.
- Quantitative relationship from methodology: "For each unit decline in allocative efficiency, there will be a one-percentage point decline in TFP growth."

### Firm-level dataset and methodology (descriptive and technical)
- Firm-level dataset coverage, total observations across years 1997–2020:
  - Estonia: 351,129
  - Lithuania: 568,126
  - Latvia: 22,660
  - Total: 941,915
- 2020 cross-section counts by country (Micro, Small, Medium, Large):
  - Estonia: Micro (0-9) 21,417; total 63,069 (Estonia+Lithuania+Latvia totals presented).
  - Latvia: Micro (0-9) 17,226; Small (10-49) 2,768; Medium (50-249) 364; Large (250+) 1,059.
  - Lithuania: Micro (0-9) 26,539; Small (10-49) 10,255; Medium (50-249) 2,122; Large (250+) 394.
- Descriptive statistics include minimum, maximum, mean, median for variables such as Number of employees, Value added (real), Capital (real), Labor costs (real), Fixed assets (nominal), Sales (nominal), Firm age.
- Methodology: allocative efficiency derived using a Cobb-Douglas firm-level production function with country-sector-specific capital share; aggregation with constant elasticity of substitution (휎휎_c); distortions represented by wedges 휏휏_K, 휏휏_L, 휏휏_Y and composite distortion 휏휏_csit; firms maximize profits under monopolistic competition; allocative efficiency (AE) reduces sector-level TFP under distortions and TFP growth is decomposed into innovation and allocative efficiency components.

*Source: 1lvaea2024002 - 1. Export Market Share and Growth of Latvia’s Top Export Markets; 7. Our empirical results; 11. Latvia faces weakening competitiveness. Latvia’s real effective exchange rate (REER); 11. Latvia has relatively flexible product market regulation and stringent labor market regulation (REPUBLIC OF LATVIA, INTERNATIONAL MONETARY FUND).*

### 1. Export Market Share and Growth of Latvia’s Top Export Markets ___________________ 4

### 1. Export Market Share and Growth of Latvia’s Top Export Markets

### Introduction and recent developments
- Latvia’s merchandise exports as a share of global exports remained stagnant post-GFC and "fell by 6 percent between 2021Q3 and 2023Q4."
- The export decline during 2021Q3-2023Q4 was mainly driven by metals, wood, and wood-related sectors.
- The immediate causes of the recent export share decline included adverse external shocks, notably Russia’s war in Ukraine, which led to supply-chain disruptions and increased input costs.
- The United Kingdom is the eighth largest export destination for Latvia as of 2023; its negative contribution to Latvia’s export share decline during 2021Q3-2023Q4 may be related to the UK’s exit from the European Union in 2020.

### Export destinations and contributions to the 2021Q3–2023Q4 export share decline
- Latvia: Export Destinations, 2023Q4 (Percent; share of total exports):
  - LTU, 16%
  - EST, 11%
  - RUS, 10%
  - DEU, 6%
  - SWE, 5%
  - GBR, 5%
  - POL, 4%
  - DNK, 4%
  - NLD, 3%
  - USA, 3%
  - Other EU, 15%
  - Other non-EU, 19%
- Country contribution to Latvia’s export share decline, 2021Q3-2023Q4 (Percentage points): shown as a distribution with negative contributions from some partners (e.g., United Kingdom, Germany, Russia, Lithuania, Estonia) and positive/other contributions aggregated; overall export share fell by 6 percent in the period.

### Real exchange rate, inflation, and labor costs
- High inflation differential and labor costs led to an appreciation of Latvia’s real effective exchange rate (REER).
- The energy shock—given a large share of energy in the consumer price index basket for the Baltics—resulted in a high inflation rate: "twice the euro area average and four times the rate in the lowest-inflation euro area members at one point."
- Large nominal wage growth caused unit labor costs (ULC) to increase, worsening relative costs in Latvia more than in the euro area but less than in the other Baltic countries.
- The combined effect of higher inflation and labor costs undermined the price competitiveness of Latvian exports.
- There was an appreciation of the REER in Latvia and the other Baltics of "around 10-15 percent."

### Constant Share Analysis (CSA) decomposition: Baltic comparison
- CSA decomposition shows that in Latvia the decline in export share during 2021Q3-2023Q4 was driven by:
  - Weakening external demand (composition effect).
  - Effects of EU trade sanctions in response to Russia’s war in Ukraine (interaction effect).
- Competitiveness issues (intensive margin) played a much less prominent role overall in Latvia’s export share decline.
- Cross-country contrasts:
  - Lithuania’s fall in export share mainly reflected a large contribution from the extensive margin (shrinking foreign demand).
  - Estonia’s decline saw a key role for the competitiveness effect.

### Balassa‑Samuelson assessment and TFP-based REER
- Johansen cointegration tests indicate a long-run relationship between TFP and REER for all three Baltic countries, consistent with the Balassa-Samuelson hypothesis; for Latvia the cointegration result is described as "weak" though a cointegration relationship between TFP and trend REER was established.
- The authors construct a TFP-based REER implied by the long-term TFP–REER relationship and define the REER gap as the deviation of actual REER from the TFP-based REER. A negative REER gap indicates price competitiveness advantages.
- Historical patterns:
  - Prior to the GFC, high TFP relative to REER explained consistently negative REER gaps for the Baltics.
  - In Estonia negative gaps were driven largely by high TFP; in Latvia a depreciating real exchange rate was the main factor; in Lithuania the gap was negative for a shorter period (between 2004-2007).
  - Post-GFC the competitiveness advantage faded around 2007-2015 for Latvia and 2007-2010 for Estonia.
  - Latvia maintained a competitiveness buffer (negative REER gap) during mid-2016 to mid-2022, which helped sustain Latvia’s export market share until 2021.
- Recent developments in REER gaps:
  - All three Baltic economies had negative REER gaps prior to 2021Q4, but gaps disappeared at different times:
    - Estonia: REER gaps became positive in 2021Q4.
    - Latvia: REER gaps became positive in 2022Q3.
    - Lithuania: REER gaps became positive in 2023Q1.
  - The decoupling between actual and TFP-based REER in recent years shows widening positive gaps, particularly pronounced in Estonia.

### Latvia’s productivity and income convergence versus other Baltics
- Income convergence:
  - Latvia’s income convergence lags that of the other Baltic economies (GDP per capita in PPP series shown).
- Labor productivity growth:
  - Annual average labor productivity growth was "nearly 3 percent in both Latvia and Lithuania, and lower (around 2 percent) in Estonia" during 2009-2020.
- Decomposition of labor productivity growth, 2009–2020:
  - In Latvia, TFP growth accounted for "over half" of labor productivity growth, surpassing Lithuania and Estonia.
  - In Lithuania and Estonia, TFP growth accounted for only "20 and 10 percent of labor productivity growth, respectively."
- Episode decomposition of labor productivity and TFP:
  - GFC (2009-2010): negative TFP growth in Latvia and other Baltics; positive labor productivity growth persisted due to significant capital deepening.
  - Post-GFC recovery (2011-2019): Latvia’s TFP growth surpassed that of other Baltics and became the primary driver of its labor productivity growth; labor productivity growth was similar across Baltics.
  - COVID-19 pandemic: TFP growth in Latvia slowed significantly, falling below that for Lithuania.
- Possible drivers of Latvia’s post-GFC TFP performance:
  - Structural reforms implemented during the IMF fund-supported reform program 2009-10 likely contributed to a post-GFC TFP boost.
  - Differences in economic structure: Latvia had a lower share of capital-intensive industries (around 20 percent of total value added in 2019) compared to other Baltics (close to 30 percent), and less-capital-intensive sectors experienced stronger post-GFC labor productivity growth in Latvia.
  - Measurement limitations: TFP is a residual and subject to unobserved factor utilization and measurement error; the large post-GFC drop in gross fixed capital formation and capital stock in Latvia complicates accurate measurement of capital inputs.
  - Different developments in residential investment across the Baltics may explain some productivity differences.

### Key statistics and dates (preserved exactly)
- Export share fall: "fell by 6 percent between 2021Q3 and 2023Q4."
- REER appreciation: "around 10-15 percent."
- Baltics: REER gap positive timing:
  - Estonia: "2021Q4"
  - Latvia: "2022Q3"
  - Lithuania: "2023Q1"
- Labor productivity growth, annual average (2009-2020):
  - Latvia: "nearly 3 percent"
  - Lithuania: "nearly 3 percent"
  - Estonia: "around 2 percent"
- Contribution of TFP to labor productivity growth (2009-2020):
  - Latvia: "over half"
  - Lithuania: "20 percent"
  - Estonia: "10 percent"
- Latvia sectoral share: "around 20 percent of total value added in 2019" are capital-intensive industries; other Baltics "close to 30 percent."

*Source: 1lvaea2024002 - 1. Export Market Share and Growth of Latvia’s Top Export Markets (IMF, August 2, 2024).*

### 11.      Latvia faces weakening competitiveness. Latvia’s real effective exchange rate (REER)

### 11. Latvia faces weakening competitiveness. Latvia’s real effective exchange rate (REER)

### REER and competitiveness
- Latvia’s real effective exchange rate (REER) appreciation in recent years has been greater than that implied by its productivity trend, so the economy faces a narrowing competitiveness buffer.
- Estimates show that the positive wedge between the actual and TFP-based REER reduced Latvia’s external price competitiveness.
- Reforms in product, capital, and labor markets could help retain competitiveness.

### Productivity outlook and risks
- Latvia’s TFP growth boost post-GFC is unlikely to be sustained without structural reforms and efforts to increase capital investment.
- Binding constraints identified:
  - A decade-long weak investment record.
  - Large infrastructure gaps.
  - Aging and emigration.
  - Insufficient accumulation in skills.
- These constraints weigh on Latvia’s productivity growth and competitiveness and pose risks that Latvia could be caught in a middle-income trap with low growth and slow convergence to euro area income level.
- Policy priority: significantly higher investment is required for sustained convergence.
- To preserve competitiveness and build resilience against future shocks, it is key to promote productivity growth via structural reforms and capital investment.
- Boosting productivity is also needed to meet challenges presented by Russia’s war in Ukraine and the ongoing transitions to sustain income convergence.

### EU and Baltic TFP context (selected quantitative findings)
- Aggregate TFP growth in the EU declined from an average of 0.7 percent between 1996 and 2007 to 0.1 percent over the period 2009–2019 and -2 percent in 2020.
- Latvia had the highest TFP growth in the Baltics (around 1 percent on average) over 1996–2020.
- Industry-level TFP drivers emphasized:
  - TFP growth at the frontier is positive and statistically significant across specifications, indicating cross-border innovation and technology spillovers.
  - The technological gap (TFP distance to frontier) is a significant determinant of TFP growth; closing the gap would raise TFP growth and explains most cross-country differences in TFP growth.

### Empirical results: magnitudes and significance (selected coefficients from baseline regressions)
- EU-28 baseline (Table 1): dependent variable = TFP growth
  - TFP growth at frontier: 0.174*** (All); 0.178*** (Tradables); 0.133*** (Non-tradables).
  - Technological gap: -12.45*** (All); -13.68*** (Tradables); -10.43*** (Non-tradables).
  - ICT capital: 5.536*** (All); 3.072 (Tradables); 8.657*** (Non-tradables).
  - Non-ICT capital: -0.933 (All); -8.751 (Tradables); 2.533 (Non-tradables).
  - R&D spending: 7.035** (All); 6.197* (Tradables); 7.990 (Non-tradables).
  - Real GDP per capita: 3.794* (All).
  - Inflation: -0.111 (All).
  - Financial development: -0.006 (All).
  - Trade openness: 0.721 (All).
  - Bureaucratic quality: 1.425** (All).
  - Number of observations: 8,615 (All); 4,153 (Tradables); 3,644 (Non-tradables).
  - R2: 0.159 (All); 0.174 (Tradables); 0.144 (Non-tradables).
- EU-28 with country-level controls (Table 1, columns 4–6):
  - TFP growth at frontier: 0.158*** (All); 0.170*** (Tradables); 0.0926** (Non-tradables).
  - Technological gap: -14.34*** (All); -16.19*** (Tradables); -10.88*** (Non-tradables).
  - ICT capital: 5.887** (All); 5.209 (Tradables); 7.665** (Non-tradables).
  - R&D spending: 7.293** (All); 7.729* (Tradables); 5.497 (Non-tradables).
  - Number of observations: 7,505 (All); 3,584 (Tradables); 3,200 (Non-tradables).
  - R2: 0.162 (All); 0.186 (Tradables); 0.138 (Non-tradables).
- Latvia and Lithuania (Table 3): dependent variable = TFP growth
  - TFP growth at frontier: 0.293*** (column 1); 0.224*** (column 2).
  - Technological gap: -27.77*** (column 1); -27.83*** (column 2).
  - ICT capital: 18.17* (column 1); -0.0142 (column 2).
  - Non-ICT capital: 3.120 (column 1); -8.486 (column 2).
  - R&D spending: -10.90 (column 1); -9.883 (column 2).
  - Real GDP per capita, log: 169.3*** (column 2).
  - Inflation: 0.824 (column 2).
  - Financial development: -0.148** (column 2).
  - Bureaucratic quality: 17.77* (column 2).
  - Population, log: 173.4** (column 2).
  - Number of observations: 315 (column 1); 291 (column 2).
  - R2: 0.367 (column 1); 0.353 (column 2).

### Policy implications and recommendations (drawn from analysis)
- Promote structural reforms in product, capital, and labor markets to safeguard competitiveness given REER appreciation.
- Raise overall investment—both ICT and non-ICT where binding—to address decade-long weak investment and infrastructure gaps.
- Enhance human capital accumulation and skills to offset aging and emigration impacts; evidence on high-skilled labor effects on TFP is mixed but may matter more close to the frontier and in non-tradables.
- Intensify R&D and ICT investment to facilitate technology adoption and diffusion; R&D and ICT spending are positively associated with higher TFP growth in many specifications.
- Improve institutional quality (bureaucratic quality), which is positively associated with TFP growth.
- Address risks of a middle-income trap by accelerating convergence through targeted investments and reforms to narrow the technological gap.

*Source: 11. Latvia faces weakening competitiveness. Latvia’s real effective exchange rate (REER) (content unit 1lvaea2024002).*

### 7.      Our empirical results, in line with previous studies, highlight four main points. First, TFP

### 7. Our empirical results

### Key empirical findings on TFP growth
- First, "TFP growth is driven largely by the extent to which countries are involved in scientific and technological innovation as the leader country or benefiting from knowledge spillovers."
- Second, "the technological gap is a highly significant factor with a substantial economic magnitude in determining TFP growth as countries move towards the technological frontier by adopting new innovations and technologies."
- Third, "increased investment in ICT capital and R&D contributes significantly to higher TFP growth across all EU countries."
- Fourth, "human capital does not appear to have a statistically significant impact on TFP growth, but there is some evidence that this effect is stronger the closer a country is to the technological frontier and human capital matters more in non-tradables than tradable sectors of the economy."

### Policy implications and recommendations
- "Reversing the downward trend in productivity growth is key to raising living standards amid adverse demographic transitions and global economic realignments."
- Revamp tangible and intangible capital investment in new technologies to:
  - "generate higher productivity growth directly and indirectly by closing the technological gap vis-à-vis the frontier."
- Strengthen human capital to:
  - "remain critical for rapid progress in science and technology and thereby expanding economic growth potential."
- Policymaker actions recommended:
  - "create a conducive environment for higher business investment and better capital allocation by modernizing regulations,"
  - "lowering trade barriers,"
  - "increasing public investment in physical infrastructure,"
  - "strengthening human capital accumulation through education and healthcare,"
  - "providing incentives for capital investment and R&D."

*Source: Republic of Latvia — International Monetary Fund (excerpt).*

### 11.      Latvia has relatively flexible product

### 11.      Latvia has relatively flexible product market regulation and stringent labor market regulation, as compared to the rest of the Baltic economies and other advanced economies (Figure 8).

### Employment protection and labor market regulation
- OECD Employment Protection Legislation indicators show Latvia has relatively strict employment protection legislation:
  - Higher severance pay for low tenure employees.
  - Stricter definitions of unfair dismissal including the exclusion of non-performance-related reasons.
  - Generous availability for re-instatement after an employee’s dismissal.
- It is more costly to dismiss an individual worker under a regular contract in Latvia than other OECD economies.
- Labor market measures protecting jobs in economic downturns may come at the cost of labor market flexibility.
- Recent research cited: Meriküll and Paulus 2024 suggest government programs such as job retention schemes in response to the pandemic may have hampered efficient labor allocation and led to productivity losses.

### Product market regulation and financial liberalization
- Latvia and the other Baltic economies rank favorably on product market regulation and financial market liberalization compared to other advanced and emerging market economies (Figures 9 and 10).
- Indicators referenced: IMF World Economic Outlook, Chapter 3 (April 2024); IMF structural reforms dataset; OECD; Orbis; Statistics Lithuania; IMF staff estimations.

### Allocative efficiency, misallocation, and financing constraints
- Evidence of dispersion in the marginal revenue product of capital among Latvian firms indicates the impact of distortions in the capital market.
- Concerns noted about tight credit conditions and limited access to finance by small firms in Latvia (Benkovskis 2015).
- Calculated allocative efficiency values are standardized using the USA as the benchmark (figures and scatter relationships shown in Figures 9–11).

### Implications for growth and policy direction
- Structural reforms could improve allocative efficiency, support productivity growth, and preserve competitiveness for Latvia.
- Less regulation in product markets and more liberalization in financial and labor markets are generally associated with better allocative efficiency (IMF 2024).
- Labor market liberalization has room for improvement based on IMF structural reforms and OECD employment protection legislation datasets.
- Key quantitative relationship from methodology: "For each unit decline in allocative efficiency, there will be a one-percentage point decline in TFP growth."

### Firm-level dataset and descriptive statistics (2020)
- Firm-level dataset covers Estonia, Latvia, and Lithuania with total observations across years 1997–2020 summing to: 351,129 (Estonia), 568,126 (Lithuania), 22,660 (Latvia), total 941,915.
- 2020 cross-section counts by country (Micro, Small, Medium, Large):
  - Estonia: Micro (0-9) 21,417; total 63,069 (Estonia+Lithuania+Latvia totals presented).
  - Latvia: Micro (0-9) 17,226; Small (10-49) 2,768; Medium (50-249) 364; Large (250+) 1,059.
  - Lithuania: Micro (0-9) 26,539; Small (10-49) 10,255; Medium (50-249) 2,122; Large (250+) 394.
- Descriptive statistics include minimum, maximum, mean, median for variables such as Number of employees, Value added (real), Capital (real), Labor costs (real), Fixed assets (nominal), Sales (nominal), Firm age (detailed tabulations shown for each firm-size class and country).

### Methodology: how allocative efficiency is derived (Annex I)
- Framework assumptions:
  - Cobb-Douglas firm-level production function with country-sector-specific capital share.
  - Aggregation with constant elasticity of substitution (휎휎_c).
  - Distortions in output, capital, and labor markets represented by wedges 휏휏_K, 휏휏_L, and 휏휏_Y; composite distortion 휏휏_csit as a function of these.
  - Firms maximize profits under monopolistic competition; marginal revenue product of inputs equals marginal cost (Equations (4) and (5)); firm price is a fixed markup over marginal cost.
- In absence of distortions (휏휏 parameters equal 1), sector-level total factor productivity is an aggregation of firm-level technology A. With distortions, TFP is lower, and the wedge is represented by AE in Equation (10).
- Aggregation: allocative efficiency is aggregated to sector level and country-level TFP growth is decomposed into innovation and allocative efficiency components (Equation (11)).

*REPUBLIC OF LATVIA, INTERNATIONAL MONETARY FUND*

---


_Source: https://www.imf.org/-/media/files/publications/cr/2024/english/1lvaea2024002.pdf_