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### Major findings on inflation shocks and firm performance
- Sample:
  - Unbalanced panel of 107,282 firms with a total of 629,089 firm-year observations from Estonia, Latvia and Lithuania during the period 1997–2021.
- Main variables:
  - Dependent variables: TFP growth (Levinsohn-Petrin (2003) estimate), gross profitability (profit before taxes / total assets in the preceding period), net fixed investment (Δ tangible assets scaled by total assets at end of previous year).
  - Independent variable: inflation shocks measured by the standard deviation of the annual rate of headline CPI inflation (series drawn from Eurostat).
- Estimation methods:
  - Panel fixed effects with firm, sector-year, and country-sector fixed effects; robust standard errors clustered at the country-industry-level.
  - Semi-parametric local projection (LP) method (Jordà (2005)) in panel setting with Spatial Correlation Consistent (SCC) standard errors (Driscoll and Kraay (1998)) and a state-dependent smooth transition specification for expansions vs. recessions.

### Key quantitative results (panel regressions)
- Effect of inflation level (Table 2):
  - A 1 percentage point increase in inflation is associated with:
    - a 0.004 percentage point decrease in TFP growth (lagged inflation effect).
    - an increase of 0.6 percentage points in profitability (contemporaneous effect reported as 0.604***).
    - an increase of 0.4 percentage points in net fixed investment (contemporaneous effect reported as 0.357***).
- Effect of inflation volatility (Table 3):
  - Contemporaneous inflation volatility: increases TFP by 0.007***, increases profitability by 1.192***, and has negligible effect on net fixed investment (-0.003).
  - Lagged inflation volatility: increases TFP by 0.004***, increases profitability by 0.850**, and increases net fixed investment by 0.233**.
- Selected control variable coefficients (Tables 2 and 3):
  - Total Assets: 0.096*** / 0.100*** for TFP; 54.61*** / 52.92*** for profitability; 24.80*** / 25.78*** for net fixed investment.
  - Leverage: positive and significant across outcomes (e.g., 0.000*** for TFP).
  - Sales Growth: positive and significant for TFP and profitability.

### Dynamic impulse response results (LP method)
- Baseline IRFs to a one standard deviation shock in headline inflation (with 90 percent confidence bands):
  - First-year effect: a one standard deviation shock is associated with an increase of 0.003 percentage points in TFP growth and negligible first-year impacts on profitability and net fixed investment.
  - Peak (second year after shock): increases of 0.008 percentage points in TFP growth, 1.5 percentage points in profitability, and 0.75 percentage points in net fixed investment.
  - Five-year cumulative effects: cumulative increase of 0.03 percentage points in productivity and 1.7 percentage points in net fixed investment over five years.
- Interpretation:
  - Firms appear agile in adjusting to moderate inflation shocks by transferring costs to consumers and/or substituting inputs.
  - Higher profitability tends to induce higher fixed investment, contributing to a persistent improvement in efficiency (TFP).

### Heterogeneity: firm size, sector, and state-dependence
- Firm size:
  - Smaller firms react more than larger firms in profitability and net fixed investment.
  - TFP response: close to zero for small firms; positive and statistically significant for larger firms within the first four years after the shock.
  - Net fixed investment: both small and large firms fluctuate around zero in the first four years; small firms’ net fixed investment picks up by the end of the projection period.
  - Small vs. large firm definitions: total assets below 25th percentile (small) and above 75th percentile (large).
- Sectoral differences (tradable vs. non-tradable):
  - Tradable sector: positive responses across TFP growth, profitability, and net fixed investment following inflation shocks.
  - Non-tradable sector: only marginal impacts on TFP growth and profitability in the second year, and miniscule medium-term increases.
  - Interpretation: tradable firms are less labor intensive, more able to substitute inputs, and may invest more when competitiveness is threatened by inflation.
- State-dependent responses (good vs. bad states):
  - Bad times (recession): no immediate firm response in year 1; profitability declines initially then returns positive by year 3, driven by positive TFP growth in year 3—consistent with a “purging effect” where unproductive firms exit and surviving firms gain market share and invest.
  - Good times (expansion): immediate positive responses in profitability and TFP growth followed by net fixed investment; however, by year 3 the initial positive effects dissipate or become negative—attributed to rising input costs, entry of new firms attracted by high profits, and declining firm market power over time.

### Contextual caveats and interpretation
- Sample period characteristics:
  - 1997–2021 characterized by disinflation after transition, low and stable inflation after EU accession (except pre-GFC imbalance), implying the analysis focuses on moderate inflation shocks rather than extreme episodes.
- External validity caution:
  - Results “do not necessarily extend to the recent bout of inflation.” The recent episode involved record-high inflation linked to large supply shocks (pandemic, energy crisis following Russia’s war in Ukraine) and large demand shifts; the authors note inflation reached “as high as 25 percent in 2022 across the Baltics,” and the benign firm-level effects may not hold if high inflation becomes persistent and undermines macro-financial stability.

### Overall conclusions
- On average, inflation shocks in the Baltics (1997–2021) had a marginally positive impact on TFP growth, profitability, and net fixed investment in the first year and over the medium term, though effects dissipate over time.
- Effects vary by firm size, sector (tradable vs. non-tradable), and cyclical state (expansion vs. recession).
- Mechanisms: cost pass-through, input substitution, reallocation of resources, and increased investment by more profitable firms contribute to observed dynamics.
- Policy implication (implicit): caution in extrapolating these results to episodes of very high and persistent inflation that differ in magnitude and origin from the sample shocks.

### References (by thematic grouping)
- Inflation and economic growth: Andres and Hernando (1997); Banerjee, Cockerell, and Russell (2001); Barro (1995); Batini, Jackson, and Nickell (2000); Benabou (1988); Bruno and Easterly (1998); Bullard and Keating (1995); De Gregorio (1993); Faria and Carneiro (2001); Kremer, Bick, and Nautz (2013); Lopez-Villavicencio and Mignon (2011); Mallick and Mohsin (2010); Mishkin (2007); Smyth (1992); Wu and Zhang (2001).
- Public investment and fiscal policy: Abiad, Furceri, and Topalova (2016); Auerbach and Gorodnichenko (2012); Ramey and Zubairy (2018); Romer and Romer (2019).
- Capital structure, leverage, and corporate finance: Baker and Wurgler (2002); Booth et al. (2001); Borio (1990); Frank and Goyal (2009); Graham, Leary, and Roberts (2015); Gungoraydinoglu and Öztekin (2011); Harris and Raviv (1991); Myers (1984); Öztekin (2015); Rajan and Zingales (1995); Titman and Wessels (1998); Kayo and Kimura (2011).
- Firm-level investment, productivity, and survival: Banerjee, Cockerell, and Russell (2001); Bhattacharjee et al. (2008); Bridges and Guariglia (2008); Cevik and Miryugin (2018, 2022); Foda, Shi, and Vaziri (2002); Gal (2013); Kalemli-Özcan et al. (2015, 2019); Levinsohn and Petrin (2003); Wu and Zhang (2001).
- Global factors, supply bottlenecks, and competition: Diez, Fan, and Villegas-Sanchez (2021); Celasun et al. (2022); Binici et al. (2022).
- Methodology, econometrics, and empirical techniques: Driscoll and Kraay (1998); Granger and Teräsvirta (1993); Im, Pesaran, and Shin (2003); Jordà (2005); Jordà and Taylor (2016); Teulings and Zubanov (2014); Levinsohn and Petrin (2003); Driscoll and Kraay (1998).

*Source: wpiea2024043-print-pdf - References*

### References .............................................................................................................

### References

### Major findings on inflation shocks and firm performance
- Sample: unbalanced panel of 107,282 firms with a total of 629,089 firm-year observations from Estonia, Latvia and Lithuania during the period 1997–2021.
- Main dependent variables: TFP growth (Levinsohn-Petrin (2003) estimate), gross profitability (profit before taxes / total assets in the preceding period), net fixed investment (Δ tangible assets scaled by total assets at end of previous year).
- Main independent variable: inflation shocks measured by the standard deviation of the annual rate of headline CPI inflation (series drawn from Eurostat).
- Estimation methods:
  - Panel fixed effects estimations with firm, sector-year, and country-sector fixed effects; robust standard errors clustered at the country-industry-level.
  - Semi-parametric local projection (LP) method (Jordà (2005)) in panel setting with Spatial Correlation Consistent (SCC) standard errors (Driscoll and Kraay (1998)) and a state-dependent smooth transition specification for expansions vs. recessions.

### Key quantitative results (panel regressions)
- Effect of inflation level (Table 2):
  - A 1 percentage point increase in inflation is associated with:
    - a 0.004 percentage point decrease in TFP growth (lagged inflation effect).
    - an increase of 0.6 percentage points in profitability (contemporaneous effect reported as 0.604***).
    - an increase of 0.4 percentage points in net fixed investment (contemporaneous effect reported as 0.357***).
- Effect of inflation volatility (Table 3):
  - Contemporaneous inflation volatility: increases TFP by 0.007***, increases profitability by 1.192***, and has negligible effect on net fixed investment (-0.003).
  - Lagged inflation volatility: increases TFP by 0.004***, increases profitability by 0.850**, and increases net fixed investment by 0.233**.
- Selected control variable coefficients (Tables 2 and 3):
  - Total Assets: positive and significant for TFP (0.096*** / 0.100***), profitability (54.61*** / 52.92***), and net fixed investment (24.80*** / 25.78***).
  - Leverage: positive and significant across outcomes (e.g., 0.000*** for TFP).
  - Sales Growth: positive and significant for TFP and profitability.

### Dynamic impulse response results (LP method)
- Baseline IRFs to a one standard deviation shock in headline inflation (with 90 percent confidence bands):
  - First-year effect: a one standard deviation shock is associated with an increase of 0.003 percentage points in TFP growth and negligible first-year impacts on profitability and net fixed investment.
  - Peak (second year after shock): increases of 0.008 percentage points in TFP growth, 1.5 percentage points in profitability, and 0.75 percentage points in net fixed investment.
  - Five-year cumulative effects: cumulative increase of 0.03 percentage points in productivity and 1.7 percentage points in net fixed investment over five years.
- Interpretation:
  - Firms appear agile in adjusting to moderate inflation shocks by transferring costs to consumers and/or substituting inputs.
  - Higher profitability tends to induce higher fixed investment, contributing to a persistent improvement in efficiency (TFP).

### Heterogeneity: firm size, sector, and state-dependence
- Firm size (Figure 2 / subsample analysis):
  - Smaller firms react more than larger firms in profitability and net fixed investment.
  - TFP response: close to zero for small firms; positive and statistically significant for larger firms within the first four years after the shock.
  - Net fixed investment: both small and large firms fluctuate around zero in the first four years; small firms’ net fixed investment picks up by the end of the projection period.
  - Small vs. large firm definitions: total assets below 25th percentile (small) and above 75th percentile (large).
- Sectoral differences (tradable vs. non-tradable; Figure 3):
  - Tradable sector: positive responses across TFP growth, profitability, and net fixed investment following inflation shocks.
  - Non-tradable sector: only marginal impacts on TFP growth and profitability in the second year, and miniscule medium-term increases.
  - Interpretation: tradable firms are less labor intensive, more able to substitute inputs, and may invest more when competitiveness is threatened by inflation.
- State-dependent responses (good vs. bad states; Figure 4):
  - Bad times (recession): no immediate firm response in year 1; profitability declines initially then returns positive by year 3, driven by positive TFP growth in year 3—consistent with a “purging effect” where unproductive firms exit and surviving firms gain market share and invest.
  - Good times (expansion): immediate positive responses in profitability and TFP growth followed by net fixed investment; however, by year 3 the initial positive effects dissipate or become negative—attributed to rising input costs, entry of new firms attracted by high profits, and declining firm market power over time.

### Contextual caveats and interpretation
- Sample period characteristics: 1997–2021 characterized by disinflation after transition, low and stable inflation after EU accession (except pre-GFC imbalance), implying the analysis focuses on moderate inflation shocks rather than extreme episodes.
- External validity caution: results “do not necessarily extend to the recent bout of inflation.” The recent episode involved record-high inflation linked to large supply shocks (pandemic, energy crisis following Russia’s war in Ukraine) and large demand shifts; the authors note inflation reached “as high as 25 percent in 2022 across the Baltics,” and the benign firm-level effects may not hold if high inflation becomes persistent and undermines macro-financial stability.

### Overall conclusions
- On average, inflation shocks in the Baltics (1997–2021) had a marginally positive impact on TFP growth, profitability, and net fixed investment in the first year and over the medium term, though effects dissipate over time.
- Effects vary by firm size, sector (tradable vs. non-tradable), and cyclical state (expansion vs. recession).
- Mechanisms: cost pass-through, input substitution, reallocation of resources, and increased investment by more profitable firms contribute to observed dynamics.
- Policy implication (implicit): caution in extrapolating these results to episodes of very high and persistent inflation that differ in magnitude and origin from the sample shocks.

*Source: IMF Working Paper (section: References and accompanying tables/figures, content from wpiea2024043-print-pdf).*

### References

### References

### Inflation and economic growth
- Andres, J., and I. Hernando (1997). “Does Inflation Harm Economic Growth? Evidence for the OECD,” NBER Working Papers No. 6062 (Cambridge, MA: National Bureau of Economic Research).
- Banerjee, A., L. Cockerell, and B. Russell (2001). “An I(2) Analysis of Inflation and the Markup,” Journal of Applied Econometrics, Vol. 16, pp. 221–240.
- Barro (1995). “Inflation and Economic Growth,” Bank of England Quarterly Bulletin, Vol. 35, pp. 166–176.
- Batini, N., B. Jackson, and S. Nickell (2000). “Inflation Dynamics and the Labor Share in the UK,” Discussion Paper No. 2 (London: Bank of England).
- Benabou, R. (1988). “Search, Price Setting and Inflation,” Review of Economic Studies, Vol. 55, pp. 353–373.
- Bruno, M., and W. Easterly (1998). “Inflation Crises and Long-Run Growth,” Journal of Monetary Economics, Vol. 41, pp. 3–26.
- Bullard, J., and J. Keating (1995). “The Long-Run Relationship Between Inflation and Output in Post-War Economies,” Journal of Monetary Economics, Vol. 36, pp. 477–496.
- De Gregorio, J. (1993). “Inflation, Taxation, and Long-Run Growth,” Journal of Monetary Economics, Vol. 31, pp. 271–298.
- Faria, J., and F. Carneiro (2001). “Does High Inflation Affect Growth in the Long and Short Run?” Journal of Applied Economics, Vol. 1, pp. 89–105.
- Kremer, S., A. Bick, and D. Nautz (2013). “Inflation and Growth: New Evidence from a Dynamic Panel Threshold Analysis,” Empirical Economics, Vol. 44, pp. 861–878.
- Lopez-Villavicencio, A., and V. Mignon (2011). “On the Impact of Inflation on Output Growth: Does the Level of Inflation Matter?” Journal of Macroeconomics, Vol. 33, pp. 455–464.
- Mallick, S., and M. Mohsin (2010). “On the Real Effects of Inflation in Open Economies: Theory and Empirics,” Empirical Economics, Vol. 39, pp. 643–673.
- Mishkin, F. (2007). “Inflation Dynamics,” International Finance, Vol. 10, pp. 317–334.
- Smyth, D. (1992). “Inflation and the Growth Rate in the United States’ Natural Output,” Applied Economics, Vol. 24, pp. 567–570.
- Wu, Y., and J. Zhang (2001). “The Effects of Inflation on the Number of Firms and Firm Size,” Journal of Money, Credit and Banking, Vol. 33, pp. 251–271.

### Public investment and fiscal policy
- Abiad, A., D. Furceri, and P. Topalova (2016). ”The Macroeconomic Effects of Public Investment: Evidence from Advanced Economies,” Journal of Macroeconomics, Vol. 50, pp. 224–240.
- Auerbach, A., and Y. Gorodnichenko (2012). “Measuring the Output Responses to Fiscal Policy,” American Economic Journal–Economic Policy, Vol. 4, pp. 1–27.
- Ramey, V., and S. Zubairy (2018). “Government Spending Multipliers in Good Times and in Bad: Evidence from US Historical Data,” Journal of Political Economy, Vol. 126, pp. 850–901.
- Romer, C., and D. Romer (2019). “Fiscal Space and the Aftermath of Financial Crises: How It Matters and Why,” NBER Working Paper No. 25768 (Cambridge, MA: National Bureau of Economic Research).

### Capital structure, leverage, and corporate finance
- Baker, M., and J. Wurgler (2002). “Market Timing and Capital Structure,” Journal of Finance, Vol. 57, pp. 1–32.
- Booth, L., V. Aivazian, A. Demirgüç-Kunt, and A. Maksimovic (2001). “Capital Structures in Developing Countries,” Journal of Finance, Vol. 56, pp. 87–130.
- Borio, C. (1990). “Leverage and Financing of Nonfinancial Companies: An International Perspective,” BIS Economic Papers No. 27 (Basel: Bank for International Settlements).
- Frank, M., and V. Goyal (2009). “Capital Structure Decisions: Which Factors Are Reliably Important?” Financial Management, Vol. 38, pp. 1–37.
- Graham, J., M. Leary, and M. Roberts (2015). “A Century of Capital Structure: The Leveraging of Corporate America,” Journal of Financial Economics, Vol. 118, pp. 532–551.
- Gungoraydinoglu, A., and Ö. Öztekin (2011). “Firm- and Country-Level Determinants of Corporate Leverage,” Journal of Corporate Finance, Vol. 17, pp. 1457–1474.
- Harris, M., and A. Raviv (1991). “The Theory of Capital Structure,” Journal of Finance, Vol. 46, pp. 297–355.
- Myers, S. (1984). “The Capital Structure Puzzle,” Journal of Finance, Vol. 39, pp. 575–592.
- Öztekin, Ö. (2015). “Capital Structure Decisions Around the World: Which Factors Are Reliably Important?” Journal of Financial and Quantitative Analysis, Vol. 50, pp. 301–323.
- Rajan, R., and L. Zingales (1995). “What Do We Know About Capital Structure? Some Evidence from International Data,” Journal of Finance, Vol. 50, pp. 1421–1460.
- Titman, S., and R. Wessels (1998). “The Determinants of Capital Structure Choice,” Journal of Finance, Vol. 43, pp. 1–19.
- Kayo, E., and H. Kimura (2011). “Hierarchical Determinants of Capital Structure,” Journal of Banking and Finance, Vol. 35, pp. 358–371.
- Booth, L., V. Aivazian, A. Demirgüç-Kunt, and A. Maksimovic (2001). “Capital Structures in Developing Countries,” Journal of Finance, Vol. 56, pp. 87–130.

### Firm-level investment, productivity, and survival
- Banerjee, A., L. Cockerell, and B. Russell (2001). “An I(2) Analysis of Inflation and the Markup,” Journal of Applied Econometrics, Vol. 16, pp. 221–240.
- Bhattacharjee, A., C. Higson, S. Holly, and P. Kattuman (2008). “Macroeconomic Instability and Business Exit: Determinants of Failures and Acquisitions of UK Firms,” Economica, Vol. 76, pp. 108–131.
- Bridges, S., and A. Guariglia (2008). “Financial Constraints, Global Engagement, and Firm Survival in the U.K.: Evidence from Micro Data,” Scottish Journal of Political Economy, Vol. 55, pp. 444–464.
- Cevik, S. and F. Miryugin (2018). “Does Taxation Stifle Corporate Investment? Firm‐Level Evidence from ASEAN Countries,” Australian Economic Review, Vol. 51, pp. 351–367.
- Cevik, S. and F. Miryugin (2022). “Leverage Shocks: Firm-Level Evidence on Debt Overhang and Investment,” Review of Economics, Vol. 73, pp. 79-101.
- Foda, K., Y. Shi, and M. Vaziri (2002). “Financial Constraints, Productivity, and Investment: Evidence from Lithuania,” IMF Working Paper No. 22/249 (Washington, DC: International Monetary Fund).
- Gal, P. (2013). “Measuring Total Factor Productivity at the Firm Level Using OECD-ORBIS,” OECD Economics Department Working Paper No. 1049 (Paris: Organization for Economic Co-operation and Development).
- Kalemli-Özcan, Ş., Sorensen, B., Villegas-Sanchez, C., Volosovych, V., and S. Yeşiltaş (2015). “How to Construct Nationally Representative Firm-Level Data from the ORBIS Global Database,” NBER Working Papers No. 21558 (Cambridge, MA: National Bureau of Economic Research).
- Kalemli-Özcan, Ş., L. Laeven, and D. Moreno (2019). “Debt Overhang, Rollover Risk, and Corporate Investment: Evidence from the European Crisis,” ECB Working Paper No. 2241 (Frankfurt: European Central Bank).
- Levinsohn, J., and A. Petrin (2003) “Estimating Production Functions Using Inputs to Control for Unobservables,” Review of Economic Studies, Vol. 70, pp. 317-341.
- Wu, Y., and J. Zhang (2001). “The Effects of Inflation on the Number of Firms and Firm Size,” Journal of Money, Credit and Banking, Vol. 33, pp. 251–271.
- Bhattacharjee, A., C. Higson, S. Holly, and P. Kattuman (2008). “Macroeconomic Instability and Business Exit: Determinants of Failures and Acquisitions of UK Firms,” Economica, Vol. 76, pp. 108–131.

### Global factors, supply bottlenecks, and competition
- Diez, F., J. Fan, and C. Villegas-Sanchez (2021). “Global Declining Competition?” Journal of International Economics, Vol. 132, 103492.
- Celasun, O., N. Hansen, A. Mineshima, M. Spector, and J. Zhou (2022). “Supply Bottlenecks: Where, Why, How Much, and What Next?,” IMF Working Paper No. 22/31 (Washington, DC: International Monetary Fund).
- Binici, M., S. Centorrino, S. Cevik, and G. Gwon, 2022, “Here Comes the Change: The Role of Global and Domestic Factors in Post-Pandemic Inflation in Europe,” IMF Working Paper No. 22/241 (Washington, DC: International Monetary Fund).

### Methodology, econometrics, and empirical techniques
- Driscoll, J., and A. Kraay (1998). “Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data,” Review of Economics and Statistics, Vol. 80, pp. 549–560.
- Granger, C., and T. Teräsvirta (1993). Modelling Nonlinear Relationships (New York: Oxford University Press).
- Im, K., M. Pesaran, and Y. Shin (2003). “Testing for Unit Roots in Heterogeneous Panels,” Journal of Econometrics, Vol. 115, pp. 53–74.
- Jordà, O. (2005). “Estimation and Inference of Impulse Responses by Local Projections,” American Economic Review, Vol. 95, pp. 161–182.
- Jordà, O., and A. Taylor (2016). “Estimation and Inference of Impulse Responses by Local Projections,” Economic Journal, Vol. 126, pp. 219–255.
- Teulings, C., and N. Zubanov (2014). “Is Economic Recovery a Myth? Robust Estimation of Impulse Responses,” Journal of Applied Econometrics, Vol 29, pp. 497–514.
- Levinsohn, J., and A. Petrin (2003) “Estimating Production Functions Using Inputs to Control for Unobservables,” Review of Economic Studies, Vol. 70, pp. 317-341.
- Driscoll, J., and A. Kraay (1998). “Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data,” Review of Economics and Statistics, Vol. 80, pp. 549–560.

*Source: wpiea2024043-print-pdf - References*

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_Source: https://www.imf.org/-/media/files/publications/wp/2024/english/wpiea2024043-print-pdf.pdf_