## _wp15239

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---

### Overview
- Scope: exploration of the first leg of the interest rate transmission mechanism — from short-term (policy/interbank) rates to long-term government bond rates — in a sample of 16 countries including advanced, emerging market, and low-income countries.
- Main conclusion previewed: generally "well-behaved" yield curves and a functioning monetary transmission mechanism across the sample; policy or short-term interbank interest rates are transmitted to market-determined longer-term bond rates with no arbitrage.
- Operational definition of "well-behaved": policy or short-term interbank interest rates are transmitted seamlessly to market-determined, longer-term bond rates in all countries, with no arbitrage; the nominal interest rate part of the transmission mechanism appears functional and largely identical across sample countries, including low-income ones.
- Emphasis: focus restricted to the interest-rate leg of transmission (short-term to long-term rates); the paper does not extend to nominal lending rates because relevant lending-rate series are available only for some industrial countries.

### Theoretical framing
- Keynesian interest rate channel (Hicks, 1937; Mishkin, 1995): a policy-induced increase in the short-term nominal interest rate leads to an increase in longer-term nominal interest rates as investors arbitrage differences in risk-adjusted expected returns across maturities.
- Under sticky prices: movements in nominal interest rates translate into movements in real interest rates, raising real borrowing costs across horizons after a short-term rate hike.
- Yield-curve representation: three latent factors — level, slope, curvature — commonly describe yield-curve dynamics. A well-behaved yield curve would be dominated by the level shift factor, producing vertical shifts of the yield curve when policy rates change, minimizing arbitrage opportunities.

### Methodological approach (summary)
- Two complementary empirical techniques used to identify latent yield-curve factors and provide robustness:
  - Principal component analysis (PCA), denoted LS (Litterman and Scheinkman, 1991).
  - Diebold and Li dynamic representation, denoted DL (2006), employing a Nelson and Siegel dynamic state-space model and the Kalman filter to estimate level, slope, curvature (β1, β2, β3).
- Rationale:
  - LS (PCA) identifies mutually uncorrelated principal components via the sample covariance matrix; PCA imposes zero correlation restriction across factors.
  - DL does not impose the PCA zero-correlation restriction and is not restricted to stationary data.
- Empirical checks:
  - Compute share of variability in yields explained by latent factors using both LS and DL.
  - Inspect correlations between policy-driven short-term rates and the estimated factors (particularly the level factor).
  - Expectation: positive correlation between policy rate and level factor; negative correlation between policy rate and slope factor (tighter policy flattens the yield curve).

### Data and sample
- Sample composition: 16 countries, divided into:
  - Emerging market countries (EMC; 7): Egypt (EGY), Georgia (GEO), Indonesia (IDN), Malaysia (MYS), Morocco (MAR), South Africa (ZAF), Turkey (TUR).
  - Low-income countries (LIC; 6): Ghana (GHA), Kenya (KEN), Nigeria (NGA), Rwanda (RWA), Tanzania (TZA), Uganda (UGA).
  - Advanced countries (AC; 3 control group): Czech Republic (CZE), Israel (ISR), Sweden (SWE).
- Monetary policy regimes include inflation targeting (IT), monetary aggregate targeting, and multiple objectives; five out of 13 EMC/LIC group countries are also IT (de facto classification).
- Macroeconomic diversity:
  - Average inflation ranged from 1.4 percent in Sweden to almost 15 percent in Ghana.
  - Average ex post short-term real interest rate mostly positive, with some negative outliers among African countries.
  - Per capita GDP (PPP) varies across sample; poorest country in sample is Uganda and richest is Sweden.
- Data sources and types:
  - Monthly yields on government securities obtained from Bloomberg and public databases.
  - Yield types include yields at issue (primary market), Bloomberg generic yields for long tenors, and yield-to-maturity where available.
  - Maturities span short (3M, 6M) to long (up to 15Y) depending on country.
- Data processing and challenges:
  - Short time series for EMCs and LICs, frequently starting in the 2000s (exceptions: Sweden and South Africa have longer histories).
  - Secondary markets often non-existent or illiquid; primary issue yields may be influenced by non-market factors.
  - Missing monthly observations in primary-market series; missing data intrapolated using the Hodrick-Prescott filter with λ=14,400.
  - Detrending: yields expressed as term premiums using the HP-based trend of the country’s monetary policy rate (Hodrick-Prescott filter with λ=14,400).
  - Even after detrending, nonstationarity cannot be rejected in one fifth of all yields (Egypt, Georgia, Israel, Morocco, Turkey, Tanzania, and South Africa).
- Policy-rate versus interbank-rate issues:
  - Central bank rates are used differently across countries; in LICs central banks sometimes provide liquidity at rates different from declared policy rates.
  - Spreads between central bank and interbank rates: ACs and some EMCs have average spreads of tens of basis points; LICs exhibit spreads in hundreds of basis points.
  - Monetary policy stance defined either as the central bank rate or the shortest-maturity interbank rate, depending on which has been used consistently as a policy instrument and exhibits close alignment between central bank and interbank rates.

### Key findings previewed
- Main empirical finding: evidence of well-behaved yield curves in the sample — latent factors explain most of yield variability across maturities and factors are correlated with policy interest rates.
- Robustness: results robust to the two methodologies (LS and DL); checks include explanatory power comparisons and correlations between monetary policy rates and the first two factors.
- Methodology invariance: all checks suggest methodology invariance of the main findings.

### The LS and DL estimates of the latent factors (robustness and interpretation)
- LS and DL estimates of the latent factors are highly correlated in most sample countries despite different identifying restrictions; DL-based factors have clear structural interpretation as level, slope, curvature, so LS-based estimates can be labeled similarly.
- Joint explanatory power:
  - Jointly the three factors explain more than 95 percent of the interest rate variability in all countries, with an exception of Nigeria.
  - The first two factors account for most of yield variability: the two factors explain on average 95 percent of the yield variance.
  - The first latent factor (the level) is the dominant indicator of transmission in most countries.
  - Noise and stochastic (unexplained) parts of yield curve variability are estimated to be fairly small.
- Cross-country and regime comparisons:
  - Yield curves are (i) well behaved in both developed and low income countries and (ii) ACs are difficult to differentiate from EMCs and LICs (regime invariant).
  - Two major differences between the advanced IT countries (ACs) and the rest:
    - The contribution of the level factor declines at the 5-year and 10-year maturity in all three advanced countries—long maturities in AC inflation targeters are anchored by a credible inflation target and do not need to react to policy shocks.
    - The contribution of the level factor is small at short tenors (3-month, 6-month, and 12-month) in monetary targeters and EMC/LIC inflation targeters—central banks in these countries do not have complete control over the short end of the yield curve.
  - Grouping by income level:
    - The first two factors explain on average 96 percent of yield variance in ACs and EMCs, declining to 92 percent in LICs.
  - Interpretation: Advanced IT countries are more likely to have well-behaved yield curves than less developed countries, but the summary differences are fairly small.
- Short-term rates, policy rates, and latent factors:
  - All correlations between monetary policy rates and the shortest available maturity yield are positive, and correlations are high among the IT countries (exception: low correlation in South Africa driven by the shortest maturity available being 2-year).
  - Monetary policy rates are positively correlated with the level factors identified using LS in most countries; for a few IT countries there are negative correlations using the DL methodology.
  - Expected negative correlations between policy rates and the slope are found in all countries, except in Nigeria.
  - The first and second latent factors are positively correlated and most of these correlations are statistically significant—monetary tightening/loosening pivot the yield curve in addition to producing a level shift.
  - No systematic differences are observed between the advanced and low income countries in these relationships.
- PCA loadings and factor structure:
  - Level loadings are essentially constant at about 0.4-0.6 across maturities in all sample countries (exceptions: Rwanda—loadings level off at the 1-year maturity; Malaysia—loading close to zero for short maturities up to 2 years).
  - The second principal component loadings slope up or down across maturities, proxying the slope; the third approximates convex/concave curvature.
  - The first factor is positively correlated with empirical short- and long-term yields in all 16 countries.
  - Correlations between the first and third, and between the second and third latent factors, are small and change signs.

### Policy implications
- Summary of main policy implications:
  - Strong co-movement between the policy rate and bond yields, suggesting well-behaved yield curves without arbitrage opportunities. Such a yield curve is a necessary, if not sufficient, condition for monetary transmission.
  - For countries that use their policy rate as a monetary policy instrument, there is a strong link between the policy rate and short-term interbank or treasury bill rates.
  - Credibility of the policy regime and level of development matter:
    - Only in advanced countries — all practicing inflation forecast targeting — are inflation expectations anchored and long rates thus react less to the first (level) factor than in other countries.
    - In the EMC/LIC sample the level shift matters equally for all maturities.
    - Monetary targeters and EMC/LIC inflation targeters have incomplete control over the short end of the yield curve; the level factor explains less of the variability of short tenors compared to AC inflation targeters.
  - Deep secondary markets do not appear to substantially increase transmission gains in advanced countries; deep secondary markets do not seem absolutely necessary for a well-behaved yield curve, likely because commercial banks are the main buyers and sellers across all maturities.
  - The link between short rates and lending rates in EMCs and LICs remains unresolved due to lack of series on meaningful loan rates for most sample countries; the “lending nexus” requires future research.
- Detailed empirical takeaways:
  - The three latent factors — the level, slope, and curvature — explain the bulk of interest rate moves, with the vertical (level) shift dominating.
  - The link from policy/interbank rates to bond yields is robust across estimation techniques (LS and DL) and largely unaffected by monetary policy regime or stage of economic development.
  - No evidence that well-developed secondary markets supercharge transmission; commercial banks do most trading of government paper in low-income countries.
  - Only weak evidence that the transmission mechanism operates more smoothly in more developed countries practicing inflation targeting than in less developed countries.
  - Overall implication: the presence of the first leg of monetary transmission is broadly independent of the level of financial sophistication; central bank actions matter even in low-income countries.
- Illustrative country-level observations (exact figures from sample):
  - Czech Republic: the one-day interbank rate has been on average higher by only 14 basis points than the policy rate (the two-week repo rate); at the height of the 2008 financial crisis the spread temporarily widened to 100 basis points.
  - Ghana: between mid-2005 and end-2007 liquidity was made available to commercial banks on average 270 basis points below the policy rate; during 2013 it was made available some 600 basis point above the policy rate.
  - Country-specific root mean square differences (policy vs. liquidity/interbank) reported in the sample include:
    - Czech Republic: 14 (basis points)
    - Egypt, Arab. Rep.: 33 (basis points)
    - Georgia: 13 (basis points)
    - Ghana: 266 (basis points)
    - Indonesia: 183 (basis points)
    - Israel: 20 (basis points)
    - Kenya: 401 (basis points)
    - Morocco: 472 (basis points)
    - Malaysia: 20 (basis points)
    - Nigeria: 323 (basis points)
    - Rwanda: 164 (basis points)
    - South Africa: 104 (basis points)
    - Sweden: 12 (basis points)
    - Turkey: 213 (basis points)
    - Tanzania: 385 (basis points)
    - Uganda: 161 (basis points)
- Policy recommendations and implications for central banks:
  - Central banks in emerging and low-income countries can expect that indirect instruments (policy rates) will affect bond yields — the first leg of monetary transmission works broadly irrespective of market depth.
  - Strengthening policy credibility (e.g., consistent inflation-targeting frameworks) can further anchor inflation expectations and reduce the sensitivity of long rates to level shocks.
  - Developing secondary markets may have limited incremental benefit for transmission if commercial banks remain the primary market makers; consider complementary policies that broaden the investor base and market-making capacity.
  - To fully map the transmission mechanism including the lending channel, prioritize collection and publication of representative loan-rate series in EMCs and LICs.

*Source: _wp15239 - 1. Introduction (excerpts) — IMF working paper PDF content provided.*

### 1.     Introduction     ................................................................................................

### 1. Introduction

### Overview
- Scope: exploration of the first leg of the interest rate transmission mechanism — from short-term (policy/interbank) rates to long-term government bond rates — in a sample of 16 countries including advanced, emerging market, and low-income countries.
- Main conclusion previewed: generally "well-behaved" yield curves and a functioning monetary transmission mechanism across the sample; policy or short-term interbank interest rates are transmitted to market-determined longer-term bond rates with no arbitrage.
- Operational definition of "well-behaved": policy or short-term interbank interest rates are transmitted seamlessly to market-determined, longer-term bond rates in all countries, with no arbitrage; the nominal interest rate part of the transmission mechanism appears functional and largely identical across sample countries, including low-income ones.
- Emphasis: focus restricted to the interest-rate leg of transmission (short-term to long-term rates); the paper does not extend to nominal lending rates because relevant lending-rate series are available only for some industrial countries.

### Theoretical framing
- Keynesian interest rate channel (Hicks, 1937; Mishkin, 1995): a policy-induced increase in the short-term nominal interest rate leads to an increase in longer-term nominal interest rates as investors arbitrage differences in risk-adjusted expected returns across maturities.
- Under sticky prices: movements in nominal interest rates translate into movements in real interest rates, raising real borrowing costs across horizons after a short-term rate hike.
- Yield-curve representation: three latent factors — level, slope, curvature — commonly describe yield-curve dynamics. A well-behaved yield curve would be dominated by the level shift factor, producing vertical shifts of the yield curve when policy rates change, minimizing arbitrage opportunities.

### Methodological approach (summary)
- Two complementary empirical techniques used to identify latent yield-curve factors and provide robustness:
  - Principal component analysis (PCA), denoted LS (Litterman and Scheinkman, 1991).
  - Diebold and Li dynamic representation, denoted DL (2006), employing a Nelson and Siegel dynamic state-space model and the Kalman filter to estimate level, slope, curvature (β1, β2, β3).
- Rationale:
  - LS (PCA) identifies mutually uncorrelated principal components via the sample covariance matrix; PCA imposes zero correlation restriction across factors.
  - DL does not impose the PCA zero-correlation restriction and is not restricted to stationary data.
- Empirical checks:
  - Compute share of variability in yields explained by latent factors using both LS and DL.
  - Inspect correlations between policy-driven short-term rates and the estimated factors (particularly the level factor).
  - Expectation: positive correlation between policy rate and level factor; negative correlation between policy rate and slope factor (tighter policy flattens the yield curve).

### Data and sample
- Sample composition: 16 countries, divided into:
  - Emerging market countries (EMC; 7): Egypt (EGY), Georgia (GEO), Indonesia (IDN), Malaysia (MYS), Morocco (MAR), South Africa (ZAF), Turkey (TUR).
  - Low-income countries (LIC; 6): Ghana (GHA), Kenya (KEN), Nigeria (NGA), Rwanda (RWA), Tanzania (TZA), Uganda (UGA).
  - Advanced countries (AC; 3 control group): Czech Republic (CZE), Israel (ISR), Sweden (SWE).
- Monetary policy regimes in sample include inflation targeting (IT), monetary aggregate targeting, and multiple objectives; note: according to IMF (2012) de facto classification, five out of 13 EMC/LIC group countries are also IT, though many fail one or more of the Six Principles of Inflation Targeting (Freeman and Laxton, 2009).
- Macroeconomic diversity in sample:
  - Average inflation ranged from 1.4 percent in Sweden to almost 15 percent in Ghana.
  - Average ex post short-term real interest rate mostly positive, with some negative outliers among African countries.
  - Per capita GDP (PPP) varies across sample; poorest country in sample is Uganda and richest is Sweden.
- Data sources and types:
  - Monthly yields on government securities obtained from Bloomberg and public databases (Table 2).
  - Yield types include yields at issue (primary market), Bloomberg generic yields for long tenors, and yield-to-maturity where available.
  - Maturities span short (3M, 6M) to long (up to 15Y) depending on country (see Table 2 for country-specific maturities and sample periods).
- Data challenges highlighted:
  - Short time series for EMCs and LICs, frequently starting in the 2000s (with exception of Sweden and South Africa which have longer histories).
  - Secondary markets often non-existent or illiquid; primary issue yields may be influenced by non-market factors (liquidity management, regulatory demand effects).
  - Missing monthly observations in primary-market series; missing data intrapolated using the Hodrick-Prescott filter with λ=14,400.
  - Secular inflation moves produce trends in nominal yields; detrending undertaken by expressing yields as term premiums using the HP-based trend of the country’s monetary policy rate (Hodrick-Prescott filter with λ=14,400).
  - Even after detrending, nonstationarity cannot be rejected in one fifth of all yields (Egypt, Georgia, Israel, Morocco, Turkey, Tanzania, and South Africa, Appendix B).
- Policy-rate versus interbank-rate issues:
  - Central bank rates are used differently across countries; in LICs central banks sometimes provide liquidity at rates different from declared policy rates.
  - Spreads between central bank and interbank rates: ACs and some EMCs have average spreads of tens of basis points; LICs exhibit spreads in hundreds of basis points (Figure 2; Table 8 in Appendix C).
  - Monetary policy stance defined either as the central bank rate or the shortest-maturity interbank rate, depending on which has been used consistently as a policy instrument and exhibits close alignment between central bank and interbank rates.

### Key findings previewed and policy implications
- Main empirical finding: evidence of well-behaved yield curves in the sample — latent factors explain most of yield variability across maturities and factors are correlated with policy interest rates.
- Methodological robustness:
  - Results are robust to the two methodologies (LS and DL); checks include explanatory power comparisons and correlations between monetary policy rates and the first two factors.
  - All checks suggest methodology invariance of the main findings.

Italic source attribution line:
*Source: _wp15239 - 1. Introduction (excerpts) — IMF working paper PDF content provided.*

### 4.1  The LS and DL Estimates of the Latent Factors

### 4.1  The LS and DL Estimates of the Latent Factors

### Robustness and interpretation of LS and DL estimates
- The LS and DL estimates of the latent factors are highly correlated in most of the sample countries despite different identifying restrictions; the authors therefore consider these estimates to be robust.
- By extension, because the DL-based factors have clear structural interpretation as the level, slope, and curvature, the LS-based estimates can be labeled as level, slope, and curvature as well.

### Variance explained by the three factors
- Jointly the three factors explain more than 95 percent of the interest rate variability in all countries, with an exception of Nigeria.
- The first two factors account for most of yield variability: assessing average explanatory power across maturities, the two factors explain on average 95 percent of the yield variance.
- The first latent factor (the level) is the dominant indicator of transmission in most countries.
- The contribution of noise and stochastic (unexplained) parts of yield curve variability is estimated to be fairly small.

### Cross-country and regime comparisons
- The authors find yield curves to be (i) well behaved in both developed and low income countries and (ii) difficult to differentiate the ACs from EMCs and LICs (regime invariant).
- Two major differences between the advanced IT countries (ACs) and the rest of the sample:
  - First, the contribution of the level factor declines at the 5-year and 10-year maturity in all three advanced countries, i.e., common innovations do not transmit to the longest maturities. This indicates that long maturities in AC inflation targeters are anchored by a credible inflation target and do not need to react to policy shocks.
  - Second, the contribution of the level factor is small at short tenors (3-month, 6-month, and 12-month) in the sample of monetary targeters and EMC/LIC inflation targeters—implying central banks in these countries do not have complete control over the short end of the yield curve.
- Grouping by income level:
  - The first two factors explain on average 96 percent of yield variance in ACs and EMCs, declining to 92 percent in LICs.
- Interpretation: Advanced IT countries are more likely to have well-behaved yield curves than less developed countries, but the summary differences are fairly small.

### Short-term rates, policy rates, and latent factors
- All correlations between monetary policy rates and the shortest available maturity yield are positive (Table 4, first column), and correlations are high among the IT countries (exception: low correlation in South Africa driven by the shortest maturity available being 2-year).
- Monetary policy rates are positively correlated with the level factors identified using LS in most countries; however, for a few IT countries there are negative correlations using the DL methodology (Table 4, second column).
- The expected negative correlation coefficients between policy rates and the slope are found in all countries, except in Nigeria.
- Policy-induced interest rate moves are correlated with the vertical shifts of the yield curve, and such moves may also affect the slope. The first and second latent factors are positively correlated and most of these correlations are statistically significant—monetary tightening/loosening pivot the yield curve in addition to producing a level shift.
- No systematic differences are observed between the advanced and low income countries in these relationships.

### PCA loadings and factor structure
- Level loadings are essentially constant at about 0.4-0.6 across maturities in all sample countries, suggesting all observed maturities enter the first factor with similar weights (exceptions: Rwanda—loadings level off at the 1-year maturity; Malaysia—loading close to zero for short maturities up to 2 years).
- The second principal component loadings slope up or down across maturities, proxying the slope of the yield curve; the third principal component loadings approximate convex/concave curvature.
- The first factor is positively correlated both with empirical short- and long-term yields in all 16 countries.
- Correlations between the first and third, and between the second and third latent factors, are small and change signs.

*Source: Authors’ calculations and analysis in "4.1  The LS and DL Estimates of the Latent Factors" from the supplied PDF content.*

### 4.3  Policy Implications

### 4.3  Policy Implications

### Summary of main policy implications
- Strong co-movement between the policy rate and bond yields, suggesting well-behaved yield curves without arbitrage opportunities. Such a yield curve is a necessary, if not sufficient, condition for monetary transmission.
- For countries that use their policy rate as a monetary policy instrument, there is a strong link between the policy rate and short-term interbank or treasury bill rates.
- Credibility of the policy regime and level of development matter:
  - Only in advanced countries – all practicing inflation forecast targeting – are inflation expectations anchored and long rates thus react less to the first (level) factor than in other countries.
  - In the EMC/LIC sample the level shift matters equally for all maturities.
  - Monetary targeters and EMC/LIC inflation targeters have incomplete control over the short end of the yield curve; the level factor explains less of the variability of short tenors compared to AC inflation targeters.
- Deep secondary markets do not appear to substantially increase transmission gains in advanced countries; deep secondary markets do not seem absolutely necessary for a well-behaved yield curve, likely because commercial banks are the main buyers and sellers across all maturities.
- The link between short rates and lending rates in EMCs and LICs remains unresolved due to lack of series on meaningful loan rates for most sample countries; the “lending nexus” requires future research.

### Detailed empirical takeaways
- The three latent factors — the level, slope, and curvature — explain the bulk of interest rate moves, with the vertical (level) shift dominating.
- The link from policy/interbank rates to bond yields is robust across estimation techniques (LS and DL) and largely unaffected by monetary policy regime or stage of economic development.
- No evidence that well-developed secondary markets supercharge transmission; commercial banks do most trading of government paper in low-income countries.
- Only weak evidence that the transmission mechanism operates more smoothly in more developed countries practicing inflation targeting than in less developed countries.
- Overall implication: the presence of the first leg of monetary transmission is broadly independent of the level of financial sophistication; central bank actions matter even in low-income countries.

### Illustrative country-level observations (exact figures from sample)
- Czech Republic: the one-day interbank rate has been on average higher by only 14 basis points than the policy rate (the two-week repo rate); at the height of the 2008 financial crisis the spread temporarily widened to 100 basis points.
- Ghana: between mid-2005 and end-2007 liquidity was made available to commercial banks on average 270 basis points below the policy rate; during 2013 it was made available some 600 basis point above the policy rate.
- Country-specific root mean square differences (policy vs. liquidity/interbank) reported in the sample include:
  - Czech Republic: 14 (basis points)
  - Egypt, Arab. Rep.: 33 (basis points)
  - Georgia: 13 (basis points)
  - Ghana: 266 (basis points)
  - Indonesia: 183 (basis points)
  - Israel: 20 (basis points)
  - Kenya: 401 (basis points)
  - Morocco: 472 (basis points)
  - Malaysia: 20 (basis points)
  - Nigeria: 323 (basis points)
  - Rwanda: 164 (basis points)
  - South Africa: 104 (basis points)
  - Sweden: 12 (basis points)
  - Turkey: 213 (basis points)
  - Tanzania: 385 (basis points)
  - Uganda: 161 (basis points)

### Policy recommendations and implications for central banks
- Central banks in emerging and low-income countries can expect that indirect instruments (policy rates) will affect bond yields — the first leg of monetary transmission works broadly irrespective of market depth.
- Strengthening policy credibility (e.g., consistent inflation-targeting frameworks) can further anchor inflation expectations and reduce the sensitivity of long rates to level shocks.
- Developing secondary markets may have limited incremental benefit for transmission if commercial banks remain the primary market makers; consider complementary policies that broaden the investor base and market-making capacity.
- To fully map the transmission mechanism including the lending channel, prioritize collection and publication of representative loan-rate series in EMCs and LICs.

*Source: IMF authors’ calculations and country examples as presented in the chapter "4.3  Policy Implications".*

### References

### _wp15239 - References

### Academic articles and methodological sources
- Abbritti, Mirko, Salvatore Dell’Erba, Antonio Moreno, and Sergio Sola, 2013, “Global Factors in the Term Structure of Interest Rates,” IMF WP/13/233 (International Monetary Fund: Washington, DC).
- Abdi, Herve, and Lynne J. Williams, 2010, Principal Component Analysis, Wiley Interdisciplinary Reviews: Computational Statistics, Vol. 2, pp. 433–459.
- Adrian, Tobias, Richard K. Crump, Emanuel Moench, 2013, “Pricing the Term Structure with Linear Regressions,” Journal of Financial Economics, Vol. 110(1), pp. 110-138.
- Aguiar-Conraria, Luís, Manuel M. F. Martins, and Maria Joana Soares, 2012, “The Yield Curve and the Macro-economy Across Time and Frequencies,” Journal of Economic Dynamics and Control, Vol. 36(12), pp. 1950-1970.
- Christiano, Lawrence J., Martin Eichenbaum, and Charles L. Evans, 1999, “Monetary Policy Shocks: What Have We Learned and to What End?” In Handbook of Macroeconomics, Vol. 1A. Eds. J. B. Taylor and M. Woodford. North Holland.
- Cortés Espada, Josué Fernando, Carlos Capistrán, Manuel Ramos-Francia, and Alberto Torres García, 2009, “An Empirical Analysis of the Mexican Term Structure of Interest Rates,” Economics Bulletin, Vol. 29(3), pp. 2310-2323.
- Diebold, Francis X., and C. Li, 2006, “Forecasting the Term Structure of Government Bond Yields.” Journal of Econometrics, Vol. 130(2), pages 337-364.
- Diebold, F. X., G. D. Rudebusch, and S. B. Aruoba, 2006, “The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach,” Journal of Econometrics, Vol. 131(1-2), pp. 309-338.
- Forzani, Liliana, and Carlos Tolmasky, 2003, “A Family of Models Explaining the Level-Slope-Curvature Effect,” International Journal of Theoretical and Applied Finance, Vol. 6(3). pp. 239-255.
- Hicks, J.R., 1937, “Mr. Keynes and the ’Classics’; A Suggested Interpretation.” Econometrica, Vol. 5, pp. 147-159.
- Ireland, Peter N., 2008, “The Monetary Transmission Mechanism.” In The New Palgrave Dictionary of Economics. Second Edition. Eds. Steven N. Durlauf and Lawrence E. Blume. Palgrave Macmillan.
- Kim, Don H., Athanasios Orphanides, 2007, “The Bond Market Term Premium: What Is It, and How Can We Measure It?” BIS Quarterly Review (June), pp. 27-40.
- Litterman, R., and J.A. Scheinkman. 1991. “Common Factors Affecting Bond Returns.” Journal of Fixed Income, Vol. 1.
- Lord, Roger, and Antoon Pelsser, 2007, ”Level-Slope-Curvature - Fact or Artefact?” Applied Mathematical Finance, Vol. 14, pp. 105-130.
- Romer, Christina D. and David H. Romer, 1994, “Monetary Policy Matters,” Journal of Monetary Economics, Vol. 34(1), pp. 75-88.
- Svensson, Lars E.O., 1997, “Inflation Forecast Targeting: Implementing and Monitoring Inflation Targets,” European Economic Review, Vol. 41, (June), pp. 1111-1146.
- Taylor, John B., 1993, “Discretion Versus Policy Rules in Practice,” Carnegie-Rochester Conference Series on Public Policy, Vol. 39, pp. 195-214.

### IMF working papers, reports, and policy-related references
- Berg, Andrew, Luisa Charry, Rafael A. Portillo, and Jan Vlček, 2013, “The Monetary Transmission Mechanism in the Tropics: A Narrative Approach,” IMF WP/13/197 (International Monetary Fund: Washington, DC).
- Berg, Andrew, Philip D. Karam, and Douglas Laxton, 2006, ”A Practical Model-Based Approach to Monetary Policy Analysis-Overview, IMF WP/06/80 (International Monetary Fund: Washington, DC).
- Davoodi, Hamid Reza, Shiv V. S. Dixit, and Gabor Pinter, 2013, “Monetary Transmission Mechanism in the East African Community,” IMF WP/13/39 (International Monetary Fund: Washington, DC).
- Freedman, Charles, and Douglas Laxton, 2009, “Why Inflation Targeting?” IMF WP/09/86 (International Monetary Fund: Washington, DC).
- IMF, 2012, Annual Report on Exchange Arrangements and Exchange Restrictions (International Monetary Fund: Washington, DC).
- IMF, 2014, Sub-Saharan Africa: Fostering Durable and Inclusive Growth, (International Monetary Fund: Washington, DC).
- IMF, 2015, Evolving Monetary Policy Frameworks in Low-Income and Other Developing Countries, (International Monetary Fund: Washington, DC).
- Mishra, Prachi, Peter Montiel, and Antonio Spilimbergo, 2012, “Monetary Transmission in Low-Income Countries: Effectiveness and Policy Implications,” IMF Economic Review, Vol. 60, pp. 270-302.
- Mishkin, Frederic S., 1995, “Symposium on the Monetary Transmission Mechanism,” The Journal of Economic Perspectives, Vol. 9(4), pp. 3-10.

### Statistical guidance and interpretation
- Doucouliagos, Hristos, 2011, “How Large is Large? Preliminary and Relative Guidelines for Interpreting Partial Correlations in Economics,” Deakin University Working Paper, SWP 2011/5.

*References list from _wp15239 - References*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp15239.pdf_