## wpiea2019068

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---

### I. Introduction and research scope
- Research question: Does financial development (banking and stock market) act as a shock-absorber or shock-amplifier for macroeconomic volatility, with a focus on terms of trade shocks and low-income countries (LICs)?
- Sample and period:
  - Primary sample: 38 LICs over the period 1978-2012.
  - Expanded sample used in some specifications: 121 developing countries.
  - Period split in seven subperiods of five years each.
- Key motivations:
  - Macroeconomic stability is prerequisite for durable, sustainable and inclusive growth.
  - On average, most of the explained growth volatility stems from external factors, mainly terms of trade volatility.

### II. Theoretical background and empirical literature (summary)
- Theoretical channels:
  - Shock-dampening channels: financial deepening enables risk diversification, insurance, and more effective counter-cyclical monetary policy (Stiglitz, 1974; Townsend, 1982; Bardhan et al., 2000).
  - Shock-amplifying channels: information asymmetries and the financial accelerator imply adverse shocks to borrowers’ net worth amplify macro fluctuations (Stiglitz and Weiss, 1981; Bernanke and Gertler, 1989; Kiyotaki and Moore, 1997).
  - Banks vs markets: banks may better alleviate information asymmetries and provide liquidity and counter-cyclical lending (Diamond, 1984; Boot and Thakor, 1997; Raddatz, 2006), while markets may underprovide informational incentives (Stiglitz, 1985; Bhide, 1993).
  - Institutional dependence and non-linearities: banks’ comparative advantage may fade as institutions strengthen; potential U-shaped or other non-linear relationships exist between banking development and volatility.
- Empirical literature:
  - Mixed evidence: some studies find banking development reduces volatility; others find weak or no robust relation.
  - Limited prior work on whether financial structure modifies the transmission of terms of trade shocks.

### III. Data, model and econometric approach
- Volatility measurement (exact formulation):
  - ln(y_{i,t}) = α_i + β_i ln(y_{i,t−1}) + γ_i t + ε_{i,t}
  - Cyclical component: ε̂_{i,t} = ln(y_{i,t}) − ln(y_{i,t})̂
  - For each 5-year sub-period, growth volatility Vgrowth = sqrt(Σ_{j=1}^5 (ε̂_{i,t} − ε̄̂_{i,t})^2 / 4)
- Core empirical specification:
  - Vgrowth_{i,t} = α_0 + β Vtot_{i,t} + φ Findev_{i,t} + δ Vtot_{i,t} * Findev_{i,t} + A X_{i,t} + u_i + ε_{i,t}
    - Vgrowth: real GDP growth volatility.
    - Vtot: volatility of terms of trade.
    - Findev: indicator of financial development (banking and stock market indicators).
    - X: controls — GDP per capita, trade openness, financial volatility, inflation volatility, political stability index, share of agricultural value added in GDP.
- Financial development indicators:
  - Banking sector: private credit ratio; liquidity ratio.
  - Stock market: market capitalization ratio; total value traded ratio.
- Estimators:
  - Fixed-effect estimator.
  - System GMM estimator (Blundell and Bond, 1998).
  - Local projection approach (annual data; horizons h=0,1,2,3,4,5; n=4 lags; Teulings and Zubanov (2014) adjustment; Driscoll-Kraay standard errors).

### IV. Key empirical results (selected, exact quantitative statements)
- Main qualitative findings:
  - Banking sector development acts as a shock-absorber in LICs and reduces the transmission of terms of trade shocks to growth volatility.
  - The shock-absorber role of banking development fades as economies grow richer.
  - Stock market development generally appears neither a shock-absorber nor a shock-amplifier for most cases.
- Quantified example:
  - Moving from the first decile of the distribution of private credit ratio (4.2 percent of GDP) to the first quartile (6 percent of GDP) reduces the elasticity of growth volatility to terms of trade shocks by about 40 percent (from 0.39 to 0.24).
- Dominance of terms of trade shocks:
  - Terms of trade shocks are the dominant source of growth volatility in LICs: the elasticity of growth volatility to terms of trade shocks is the largest and is three times the elasticity to credit growth volatility.
- Dynamic response (local projections):
  - Growth volatility reacts rapidly to terms of trade shocks with the peak pass-through reached within a year; the effect dies out thereafter and is statistically insignificant in outer years.
- Robustness across methods:
  - Findings hold across fixed-effect, one-step system GMM (Hansen and AR(2) diagnostics reported), and local projection approaches.

### V. Selected econometric coefficients and diagnostics (exact reported values, selected)
- System-GMM (LICs; examples from Table A4):
  - Terms of trade volatility (log): 0.714 [0.324]**; 0.700 [0.334]**; 1.009 [0.410]**; 0.753 [0.394]*
  - Private credit ratio (log) * Terms of trade volatility: -0.250 [0.117]**; -0.224 [0.121]*; -0.343 [0.176]*; -0.254 [0.165]
  - Credit growth volatility (log): 0.462 [0.171]***; 0.492 [0.177]***; 0.337 [0.119]***; 0.508 [0.166]***
  - Observations: 161; Number of countries: 37
  - Hansen test p-values: 0.92, 0.92, 0.80, 0.95
  - AR(2) test p-values: 0.44, 0.36, 0.51, 0.36
- Fixed-effect estimates (LICs; examples from Table A5):
  - GDP per capita (log): -0.492 [0.219]**; -0.388 [0.229]*; -0.410 [0.243]*; -0.586 [0.241]**
  - Terms of trade volatility (log): 0.678 [0.187]***; 0.646 [0.186]***; 0.569 [0.171]***; 0.706 [0.189]***
  - Private credit ratio (log): -0.730 [0.226]***; -0.736 [0.217]***; -0.699 [0.212]***; -0.747 [0.229]***
  - Private credit ratio (log) * Terms of trade volatility (log): -0.255 [0.083]***; -0.262 [0.080]***; -0.224 [0.075]***; -0.266 [0.082]***
  - Observations: 178; 175; 169; 173. Number of countries: 38; R-squared up to 0.26.
- Stock market measures (selected from Table A7):
  - Stock market capitalization ratio (log): -0.243 [0.105]**; -0.371 [0.264]; 0.482 [0.234]**
  - Stock market total value traded ratio (log): -0.100 [0.150]; -0.022 [0.352]; 0.595 [0.326]*
  - Stock market capitalization (log) * Terms of trade volatility (log): -0.058 [0.102]; interaction terms vary across columns including a reported 0.242 [0.087]***.
  - Observations: 161; Number of countries: 37; Hansen test p-values up to 0.93; AR(2) p-value example 0.37.
- Measuring volatility and correlations (Table A1 and correlation matrix exact values):
  - GDP growth volatility: Obs 320 Mean 0.04 Std. Dev. 0.04 Min 0.00 Max 0.43
  - GDP per capita (USD): Obs 344 Mean 343.6 Std. Dev. 233.8 Min 42.5 Max 1,426.7
  - Trade openness (percent of GDP): Obs 347 Mean 56.8 Std. Dev. 28.7 Min 0.3 Max 168.3
  - Private credit ratio (percent of GDP): Obs 243 Mean 12.0 Std. Dev. 10.0 Min 0.3 Max 99.5
  - Correlation of GDP growth volatility with GDP per capita: -0.18*; with Terms of trade volatility: 0.11*; with Private credit ratio: -0.19*; with Volatility of private credit ratio: 0.32*; with Political stability: -0.29*; with Agricultural value-added share: 0.24*.
  - Notes. * significant at 1, 5 or 10 percent.

### VI. Conclusions and policy implications (explicit recommendations)
- Main conclusions:
  - Banking sector development in LICs reduces growth volatility and dampens the transmission of terms of trade shocks to growth volatility.
  - The shock-absorber role of banking development is most pronounced at early stages of economic development and fades as countries become richer.
  - Stock market development does not show consistent shock-absorbing properties in the LIC context examined; stock market indicators are not statistically significant for 97.5 percent of observations.
- Policy recommendations:
  - Promote banking sector deepening in LICs to enhance macroeconomic resilience.
  - Expand banks and improve credit issuance channels (for example, establish credit bureaus) to alleviate information frictions and loosen credit constraints.
  - Strengthen institutions, banking regulation and supervision to build a stable and sound banking system.
  - Support responsible expansion of financial mobile services, provided associated risks are controlled.
  - For LICs integrating into the world economy, prioritize banking sector development to shelter economies from increased exposure to terms of trade shocks.
- Policy caveats:
  - The shock-absorber role of banking development declines with higher income levels; policy design should account for evolving institutional contexts and financial structure.

### VII. Limitations and avenues for future research
- Analysis is exploratory and does not address bank-level characteristics or heterogeneity (e.g., ownership structure, foreign banks).
- The interaction between domestic and international capital market integration and the effects of regulatory and supervisory frameworks and banking competition on shock absorption are left for future research.
- Outstanding question: what incentives and market structures ensure banks incur screening costs and retain borrowers rather than losing them to competitors or foreign institutions?

*Source: wpiea2019068*

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

### References

### Figures
- 1. Trade Openness and Terms of Trade Volatility by Income Groups, 1978-2012 .................................. 6
- 2. Trends in Private Credit Ratio to GDP by Income Groups, 1978-2012 .................................................... 6
- 3. Banking Sector Development and Growth Volatility in LICs, 1978-2012 ............................................. 13
- 4. Banking Sector Development and the Correlation between Growth Volatility and Terms of Trade Shocks in LICs, 1978-2012 ........................................................................................................................ 13
- 5. Stock Market Development, Growth Volatility and its Correlation with Terms of Trade Shocks in LICs, 1978-2012 ......................................................................................................................................................... 14
- 6. Terms of Trade Shocks and Growth Volatility in LICs: Unconditional IRF ............................................ 22
- 7. Terms of Trade Shocks and Growth Volatility in LICs: IRFs Conditional to Financial Depth ......... 23

### Tables
- 1. Financial Development, Terms of Trade Shocks and Growth Volatility: Fixed-Effect Estimates . 15
- 2. Financial Development, Terms of Trade Shocks and Growth Volatility: System-GMM Estimates ......................................................................................................................................................................................... 16
- 3. Using the Liquid Liability Ratio to Gauge Financial Development: System-GMM Estimates ....... 18
- 4. Accounting for Stock Market Development: System-GMM Estimates ................................................. 19

### Appendix
- Appendix Figure A1. Robutness of the Estimated Effect of Stock Market Development on Growth Volatility in Developing Countries ................................................................................................................................................... 31

*wpiea2019068 - References*

### Appendix Tables

### Appendix Tables — wpiea2019068

### I. Introduction and research scope
- Research question: Does financial development (banking and stock market) act as a shock-absorber or shock-amplifier for macroeconomic volatility, with a focus on terms of trade shocks and low-income countries (LICs)?
- Sample and period:
  - Primary sample: 38 LICs over the period 1978-2012.
  - Expanded sample used in some specifications: 121 developing countries.
  - Period is split in seven subperiods of five years each.
- Key motivations:
  - Macroeconomic stability is prerequisite for durable, sustainable and inclusive growth.
  - Between 1950 and 2011, most of the relatively faster growth of high-income countries resulted from shrinking less, and less often, compared to lower-income countries (World Bank, 2017).
  - On average, most of the explained growth volatility stems from external factors, mainly terms of trade volatility (World Bank, 2018).

### II. Theoretical background and empirical literature (summary)
- Theoretical channels:
  - Shock-dampening channels: financial deepening enables risk diversification, insurance, and more effective counter-cyclical monetary policy (Stiglitz, 1974; Townsend, 1982; Bardhan et al., 2000).
  - Shock-amplifying channels: information asymmetries and the financial accelerator imply adverse shocks to borrowers’ net worth amplify macro fluctuations (Stiglitz and Weiss, 1981; Bernanke and Gertler, 1989; Kiyotaki and Moore, 1997).
  - Banks vs markets: banks may better alleviate information asymmetries and provide liquidity and counter-cyclical lending (Diamond, 1984; Boot and Thakor, 1997; Raddatz, 2006), while markets may underprovide informational incentives (Stiglitz, 1985; Bhide, 1993).
  - Institutional dependence: the comparative advantage of banks may fade as institutions strengthen and economies grow richer (Levine, 2002; Gerschenkron, 1962; Rajan and Zingales, 1999).
  - Non-linear possibilities: empirical work suggests potential U-shaped or other non-linear relationships between banking development and volatility (Easterly et al., 2001; Dabla-Norris and Srivisal, 2013; Kunieda, 2015).
- Empirical findings in the literature:
  - Some studies find banking development reduces output, investment and consumption volatility (Denizer et al., 2002; Ferreira da Silva, 2002).
  - Other studies find weak or no robust relation (Tiryaki, 2003; Beck et al., 2006).
  - Industry- and firm-level studies tend to support a stabilization role for banks, particularly where liquidity needs are high (Larrain, 2006; Raddatz, 2006; Huang et al., 2012).
  - Limited literature examines whether financial structure (bank- vs market-based) modifies the transmission of terms of trade shocks.

### III. Data, model and econometric approach
- Volatility measurement:
  - Instead of the standard deviation of growth rates, the long-term component is modeled as an AR(1) process with a trend:
    - ln(y_{i,t}) = α_i + β_i ln(y_{i,t−1}) + γ_i t + ε_{i,t}  (equation (2))
    - Cyclical component: ε̂_{i,t} = ln(y_{i,t}) − ln(y_{i,t})̂  (equation (3))
    - For each 5-year sub-period, growth volatility Vgrowth is computed as the standard error of ε̂_{i,t} over the sub-period:
      - Vgrowth = sqrt(Σ_{j=1}^5 (ε̂_{i,t} − ε̄̂_{i,t})^2 / 4)  (equation (4))
  - Advantages: allows country-specific coefficients in equation (2) and controls for time trend; avoids assuming α_i = γ_i = 0 and β_i = 1.
- Core empirical specification (drawing on Kpodar and Imam (2016)):
  - Vgrowth_{i,t} = α_0 + β Vtot_{i,t} + φ Findev_{i,t} + δ Vtot_{i,t} * Findev_{i,t} + A X_{i,t} + u_i + ε_{i,t}  (equation (1))
    - Vgrowth: real GDP growth volatility.
    - Vtot: volatility of terms of trade.
    - Findev: indicator of financial development (banking and stock market indicators).
    - X: controls — GDP per capita, trade openness (exports + imports/GDP), financial volatility, inflation volatility, political stability index, share of agricultural value added in GDP.
    - u_i: country-specific effect; ε_{i,t}: error term.
- Financial development indicators:
  - Banking sector: private credit ratio; liquidity ratio.
  - Stock market: market capitalization ratio; total value traded ratio.
  - Financial volatility proxied by volatility in private credit ratio or liquidity ratio.
- Expected signs and interpretation:
  - Negative coefficient on the interaction (δ) ⇒ financial development acts as shock-absorber for terms of trade shocks.
  - Positive coefficient on interaction ⇒ financial depth amplifies external shocks.
  - Other expectations: Vtot positively correlated with Vgrowth (especially in LICs); GDP per capita negatively correlated with Vgrowth; trade openness ambiguous; share of agricultural value added, financial volatility, inflation volatility, lack of political stability expected to be positively associated with Vgrowth.
- Estimators used:
  - Fixed-effect estimator: controls for time-invariant country-specific factors.
  - System GMM estimator (Blundell and Bond, 1998): addresses endogeneity by instrumenting RHS variables with appropriate lags; uses both the difference panel and level specification.
  - Local projection approach: discussed separately and relies on annual data.

### IV. Key results (fixed-effect, system GMM, and local projections — summary from text)
- Main findings reported in the paper:
  - Evidence supports that banking sector development acts as a shock-absorber in LICs, including through dampening transmission of terms of trade shocks to growth volatility.
  - The shock-absorber role of banking development fades away as economies grow richer.
  - Stock market development generally appears neither a shock-absorber nor a shock-amplifier for most cases.
  - Financial deepening through expansion of banks is associated with better access to finance and greater resilience to external shocks, especially at early stages of economic development.
- Empirical diagnostics and data patterns:
  - Figure indications (described in text):
    - In the LIC sample, deeper banking systems tend to experience lower growth volatility regardless of measure of financial depth.
    - Correlation between terms of trade shocks and growth volatility is weaker in countries with a more developed banking sector.
    - Stock market indicators provide a less clear picture, likely reflecting limited stock market development in many LICs.
- Robustness and methodological notes:
  - Results are derived from multiple econometric methodologies: fixed effect, system GMM, and local projections.
  - The paper expands some specifications to 121 developing countries to assess generalizability beyond LICs.

### V. Policy implications (as concluded)
- Implication 1: Expanding banking sector development in LICs may provide not only improved access to finance but also greater resilience to external (terms of trade) shocks.
- Implication 2: The shock-absorber role of banking development is most pronounced at early stages of economic development and may decline as countries become richer.
- Implication 3: Stock market development, in contrast, does not show consistent shock-absorbing properties in the LIC context examined.
- Considerations for policy design:
  - Policy aimed at financial deepening in LICs should prioritize strengthening banking intermediation and institutions that support banks’ ability to absorb shocks.
  - Institutional development matters: as institutions strengthen, the comparative advantage of banks vs markets may change, suggesting a dynamic approach to financial structure policy.

*Source: Appendix Tables, wpiea2019068 (Appendix Tables; content extracted from provided PDF text).*

### conclusions.

### Conclusions

### Main findings on finance and growth volatility in LICs
- Sample and period: 38 LICs over the period 1978-2012; extended samples include 83 and 121 developing countries in robustness checks.
- Banking sector development acts as a shock absorber in LICs and reduces the transmission of terms of trade shocks to growth volatility.
- Quantified example: moving from the first decile of the distribution of private credit ratio (4.2 percent of GDP) to the first quartile (6 percent of GDP) reduces the elasticity of growth volatility to terms of trade shocks by about 40 percent (from 0.39 to 0.24).
- Terms of trade shocks are a dominant source of growth volatility in LICs: the elasticity of growth volatility to terms of trade shocks is the largest and is three times the elasticity to credit growth volatility.
- Stock market development: no robust evidence that stock markets in LICs are associated with lower growth volatility; stock market indicators are not statistically significant for 97.5 percent of observations and thus stock markets appear neither to be shock-absorbers nor shock-amplifiers for most LICs.
- Dynamic response (local projection approach): growth volatility reacts rapidly to terms of trade shocks with the peak pass-through reached within a year; the effect dies out thereafter and is statistically insignificant in outer years, implying a temporary effect rather than a permanent one.
- Robustness across methods: findings hold across three econometric approaches used:
  - fixed-effect estimator (controls for country fixed effects),
  - one-step system GMM estimator (addresses potential endogeneity; Hansen and AR(2) tests reported and instrument validity supported),
  - local projection approach (captures dynamic impulse responses, with Driscoll-Kraay standard errors to account for autocorrelation and cross-sectional dependence).

### Econometric and measurement notes
- Banking sector development proxied by private credit ratio (log) and alternatively by liquid liability ratio (log); both show negative main effects and negative interactions with terms of trade volatility (log) in System-GMM and fixed-effects estimates.
- When extending the sample to LMICs and all developing countries, the association between banking sector development and growth volatility fades (U-shape relationship across income levels).
- Liquid liability ratio remains significant even in developing-country samples, suggesting the savings-provision dimension matters beyond LICs.
- Stock market measures (capitalization ratio (log), total value traded ratio (log)) show weak and non-robust associations; positive significant coefficients in larger samples are driven by outliers representing 2.5 percent of observations.
- Local projections specification includes:
  - horizons h=0,1,2,3,4,5 to estimate multi-year responses,
  - n=4 lags of terms of trade volatility,
  - Teulings and Zubanov (2014) adjustment to control intra-horizon innovations,
  - financial depth represented by a dummy (1 if above LIC median private credit ratio; stock market dummy = 1 if capitalization strictly positive),
  - volatility measured annually as the absolute deviation from the 5-year moving average of residuals; Driscoll-Kraay fixed-effect estimator used to obtain robust standard errors.

### Policy implications and recommendations
- Promote banking sector deepening in LICs to enhance macroeconomic resilience:
  - Expand banks and improve credit issuance channels (for example, establish credit bureaus) to alleviate information frictions and loosen credit constraints.
  - Pursue a stable macroeconomic environment and appropriate banking regulations and supervision to build a stable and sound banking system.
- Support responsible expansion of financial mobile services, provided associated risks are controlled, as a promising tool for macroeconomic stability in developing countries.
- For LICs integrating into the world economy, prioritize banking sector development to shelter economies from increased exposure to terms of trade shocks associated with greater openness.

### Limitations and avenues for future research
- Analysis is exploratory and does not address bank-level characteristics or heterogeneity:
  - The role of ownership structure (including the presence and behavior of foreign banks) remains unexamined; foreign banks may differ in local networks and informational capacity relative to domestic banks.
  - The interaction between domestic and international capital market integration and its impact on growth volatility is not assessed.
  - The effects of regulatory and supervisory frameworks and the degree of banking competition on whether financial intermediaries absorb or propagate shocks are left for future research.
- Outstanding question: what incentives and market structures ensure banks incur screening costs and retain borrowers rather than losing them to competitors or foreign institutions?

*Source: wpiea2019068 - conclusions*

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### Appendix tables and figures (contents and key numeric findings as listed)

H3: Table A1 — Summary Statistics (LIC Sample)
- GDP growth volatility: Obs 320 Mean 0.04 Std. Dev. 0.04 Min 0.00 Max 0.43
- GDP per capita (USD): Obs 344 Mean 343.6 Std. Dev. 233.8 Min 42.5 Max 1,426.7
- Trade openness (percent of GDP): Obs 347 Mean 56.8 Std. Dev. 28.7 Min 0.3 Max 168.3
- Terms of trade volatility: Obs 239 Mean 0.09 Std. Dev. 0.07 Min 0.00 Max 0.43
- Private credit ratio (percent of GDP): Obs 243 Mean 12.0 Std. Dev. 10.0 Min 0.3 Max 99.5
- Liquid liability ratio (percent of GDP): Obs 246 Mean 23.1 Std. Dev. 12.2 Min 0.4 Max 104.2
- Stock market capitalization ratio (percent of GDP): Obs 440 Mean 1.6 Std. Dev. 10.6 Min 0.0 Max 193.1
- Stock market total value traded (percent of GDP): Obs 440 Mean 0.5 Std. Dev. 8.3 Min 0.0 Max 173.6
- Volatility of private credit ratio: Obs 292 Mean 0.19 Std. Dev. 0.12 Min 0.00 Max 0.77
- Inflation volatility: Obs 252 Mean 0.09 Std. Dev. 0.18 Min 0.00 Max 1.88
- Political stability: Obs 173 Mean -0.85 Std. Dev. 0.86 Min -3.14 Max 0.96
- Agricultural value-added share (percent of GDP): Obs 331 Mean 37.6 Std. Dev. 13.9 Min 8.9 Max 77.7

H3: Table A1 — Correlation Matrix (selected correlations, exact values)
- Correlation of GDP growth volatility with:
  - GDP per capita: -0.18*
  - Trade openness: -0.01
  - Terms of trade volatility: 0.11*
  - Private credit ratio: -0.19*
  - Volatility of private credit ratio: 0.32*
  - Political stability: -0.29*
  - Agricultural value-added share: 0.24*
- Correlation of GDP per capita with:
  - Trade openness: 0.37*
  - Private credit ratio: 0.41*
  - Liquid liability ratio: 0.46*
  - Agricultural value-added share: -0.54*
- Notes. * significant at 1, 5 or 10 percent.

H3: Table A2 — Variable Definitions and Sources (selected entries as listed)
- GDP growth volatility: The standard deviation of the residual of the log of real GDP regressed on its lags value and a time trend (assuming an AR(1) process with a trend), calculated over a 5-year period. Source: World Development Indicators and author’s calculations.
- GDP per capita (USD): The ratio of nominal GDP divided by the size of the population. Source: International Monetary Fund.
- Trade openness (percent of GDP): Sum of exports and imports of goods and services measured as a share of GDP. Source: World Development Indicators.
- Terms of trade volatility: The standard deviation of the residual of the log of terms of trade index regressed on its lags value and a time trend, calculated over a 5-year period. The terms of trade index is calculated as the percentage ratio of the export unit value indexes to the import unit value indexes, measured relative to the base year 2000. Source: World Development Indicators and author’s calculations.
- Private credit ratio (percent of GDP): The total amount of credit by deposit money banks to the private sector divided by GDP. Source: Financial Development and Structure Dataset.
- Liquid liability ratio (percent of GDP): Total currency plus demand and interest-bearing liabilities of banks and other financial intermediaries divided by GDP. Source: Financial Development and Structure Dataset.
- Stock market capitalization ratio (percent of GDP): Total value of listed shares divided by GDP. Source: Financial Development and Structure Dataset.
- Volatility of private credit ratio: The standard deviation of the residual of the log of private credit ratio regressed on its lags value and a time trend, calculated over a 5-year period. Source: Financial Development and Structure Dataset and authors’ calculations.
- Inflation volatility: The standard deviation of the residual of the log of Consumer Price Index regressed on its lags value and a time trend, calculated over a 5-year period. Source: World Development Indicators and author’s calculations.
- Political stability: Political Stability and Absence of Violence/Terrorism (Estimate). Source: World Bank Governance Database.
- Agricultural value-added share (percent of GDP): Ratio of agricultural value added over GDP. Source: World Development Indicators.

H3: Table A3 — Mean-Comparison Tests (selected exact differences)
- GDP growth volatility: LICs average 0.04; Non LICs average 0.04; Difference (1)-(2) 0.00
- GDP per capita (USD): LICs average 343.64; Non LICs average 2143.49; Difference (1)-(2) -1799.85 ***
- Trade openness (percent of GDP): LICs 56.82; Non LICs 78.40; Difference -21.58 ***
- Terms of trade volatility: LICs 0.09; Non LICs 0.08; Difference 0.01 **
- Private credit ratio (percent of GDP): LICs 12.00; Non LICs 27.46; Difference -15.46 ***
- Liquid liability ratio (percent of GDP): LICs 23.15; Non LICs 40.11; Difference -16.96 ***
- Stock market capitalization ratio (percent of GDP): LICs 1.58; Non LICs 6.86; Difference -5.27 ***
- Volatility of private credit ratio: LICs 0.19; Non LICs 0.15; Difference 0.04 ***
- Political stability: LICs -0.85; Non LICs -0.22; Difference -0.64 ***
- Agricultural value-added share (percent of GDP): LICs 37.62; Non LICs 17.37; Difference 20.25 ***
- Notes: *,**,***Denote significance at 10%, 5% and 1%, respectively

H3: Figure A1 — Notes (as listed)
- Source. Authors’ calculations.
- Notes. A data point on the red line represents the coefficient on the stock market development (or its interaction term with terms of trade volatility) estimated on a sample of countries with a GDP per capital level below the corresponding x-axis value. As GDP per capita increases, the coefficients converge toward the full sample estimates shown in table 4, column 5 and 6.

H3: Tables A4–A7 — Econometric Estimates (selected coefficient values and diagnostics reported exactly)

Table A4. Testing a Dynamic Specification: System-GMM Estimates (selected coefficients, LICs columns)
- Lagged growth volatility: 0.071 [0.309]; 0.199 [0.305]; 0.056 [0.353]; 0.209 [0.305] (columns reported)
- GDP per capita (log): -0.378 [0.310]; -0.352 [0.341]; -0.339 [0.291]; -0.291 [0.349]
- Trade openness: -0.006 [0.005]; -0.003 [0.004]; -0.007 [0.005]; -0.003 [0.004]
- Terms of trade volatility (log): 0.714 [0.324]**; 0.700 [0.334]**; 1.009 [0.410]**; 0.753 [0.394]*
- Private credit ratio (log) * Terms of trade volatility: -0.250 [0.117]**; -0.224 [0.121]*; -0.343 [0.176]*; -0.254 [0.165]
- Credit growth volatility (log): 0.462 [0.171]***; 0.492 [0.177]***; 0.337 [0.119]***; 0.508 [0.166]***
- Observations: 161; Number of countries: 37 (for LICs columns)
- Hansen test p-values: 0.92, 0.92, 0.80, 0.95 (columns)
- AR(2) test (p-values): 0.44, 0.36, 0.51, 0.36 (columns)
- Notes. Robust standard errors in brackets. *,**,***Denote significance at 10%, 5% and 1%, respectively. AR(2): Arellano and Bond test of second order autocorrelation.

Table A5. Measuring Volatility with the Standard Deviation: Fixed-Effect Estimates (selected LICs coefficients)
- GDP per capita (log): -0.492 [0.219]**; -0.388 [0.229]*; -0.410 [0.243]*; -0.586 [0.241]**
- Terms of trade volatility (log): 0.678 [0.187]***; 0.646 [0.186]***; 0.569 [0.171]***; 0.706 [0.189]***
- Private credit ratio (log): -0.730 [0.226]***; -0.736 [0.217]***; -0.699 [0.212]***; -0.747 [0.229]***
- Private credit ratio (log) * Terms of trade volatility (log): -0.255 [0.083]***; -0.262 [0.080]***; -0.224 [0.075]***; -0.266 [0.082]***
- Credit growth volatility (log) (where included): 0.292 [0.089]*** or 0.269 [0.166]
- Observations: 178; 175; 169; 173 (varies by column). Number of countries: 38; R-squared up to 0.26 in reported columns.
- Notes. Robust standard errors in brackets. *,**,***Denote significance at 10%, 5% and 1%, respectively.

Table A6. Measuring Volatility with the Standard Deviation: System-GMM Estimates (selected coefficients)
- GDP per capita (log): -0.581 [0.339]*; -0.655 [0.355]*; -0.655 [0.285]**; -0.810 [0.397]**
- Trade openness: -0.006 [0.005]; -0.006 [0.005]; -0.008 [0.005]; -0.009 [0.004]**
- Terms of trade volatility (log): 0.632 [0.459]; 0.728 [0.386]*; 0.960 [0.436]**; 0.641 [0.427]
- Private credit ratio (log) * Terms of trade volatility (log): -0.165 [0.161]; -0.202 [0.148]; -0.255 [0.149]*; -0.277 [0.115]**
- Observations range: 161 to 532; Number of countries range: 37 to 122.
- Hansen test p-values and AR(2) test (p-values) reported per column (examples: Hansen 0.39, 0.38, 0.48; AR(2) 0.32, 0.34, 0.27).

Table A7. Measuring Volatility with the Standard Deviation: Accounting for the Impact of Stock Market Development on Growth Volatility — System-GMM Estimates (selected coefficients)
- GDP per capita (log): -0.729 [0.395]*; -0.776 [0.393]**; -0.240 [0.394]; -0.660 [0.395]*
- Terms of trade volatility (log): 0.705 [0.271]***; 0.684 [0.274]**; 0.471 [0.430]; 0.582 [0.313]*
- Private credit ratio (log) * Terms of trade volatility (log): -0.265 [0.104]**; -0.224 [0.105]**; -0.191 [0.194]; -0.187 [0.148]
- Stock market capitalization ratio (log): -0.243 [0.105]**; -0.371 [0.264]; 0.482 [0.234]**
- Stock market total value traded ratio (log): -0.100 [0.150]; -0.022 [0.352]; 0.595 [0.326]*
- Stock market capitalization (log) * Terms of trade volatility (log): -0.058 [0.102]; -0.058 reported and 0.242 [0.087]*** (interaction terms reported across columns)
- Credit growth volatility (log): 0.447 [0.196]**; 0.490 [0.187]***; 0.358 [0.132]***; 0.526 [0.168]***
- Observations: 161; Number of countries: 37 in LIC columns; Hansen test p-values up to 0.93; AR(2) test (p-values) example 0.37.
- Notes. Robust standard errors in brackets. *,**,***Denote significance at 10%, 5% and 1%, respectively. AR(2): Arellano and Bond test of second order autocorrelation.

*Source: Content unit "wpiea2019068 - REFERENCES" (PDF chapter/section) as provided.*

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