## _wp14238

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---

### Small-scale model
- Model type: prototypical monetary VAR model augmented by spread and equity variables.
- Variables (six):
  - GDP
  - GDP Price Index
  - Federal Funds Rate
  - AAA yield
  - BAA yield
  - net worth
- Small-VAR empirical findings:
  - Contractionary monetary shock: output falls; yields rise.
  - Credit spread (BAA-FFR), default risk spread (BAA-AAA), and maturity mismatch spread (AAA-FFR) drop below zero on impact and then gradually rise.
  - Net worth/equity drops on impact.
- Noted problem: "spread puzzle" — credit spread falling on contractionary monetary shocks in small VARs (contrary to financial accelerator predictions).

### Medium-scale model (JPTBGG data set)
- System: nine variables used to estimate DSGE models.
- Variables included:
  - Seven macroeconomic: output, consumption, investment, hours, wage, inflation, interest rate.
  - Two financial: spread and net worth.
- Data: per capita (used for DSGE estimation).
- Main purpose: cross-check monetary policy propagation in VAR and DSGE models.
- Reference: Furlanetto, Gelain, and Taheri Sanjani (2013).

### Large-scale model: specification and identification
- Model form: y_t = c + A1 y_{t−1} + A2 y_{t−2} + ··· + A_p y_{t−p} + e_t, with e_t ∼ N(0_n, Σ).
- Number of lags: p = 13.
- System size: 34 variables.
- Estimation: Bayesian shrinkage (Minnesota-type priors); degree of prior informativeness selected hierarchically to maximize the marginal likelihood (following Giannone, Lenza, and Primiceri (2012)).
- Spread measures and decomposition:
  - External finance premium proxy: BAA-FFR.
  - Maturity mismatch channel proxied by AAA-FFR.
  - Default risk channel proxied by BAA-AAA.
  - BAA and AAA: long-maturity Moody’s yields (Moody’s tries to include bonds with remaining maturities as close to 30 years as possible).
- Net worth block: six definitions NW1 to NW6; correlations with the Wilshire 5000 reported for 1971Q1 to 2012Q4 and described as high.
- Monetary policy shock identification:
  - Defined as a one percent exogenous deviation in the Federal Funds Rate.
  - Recursive (Cholesky) ordering: prices and real activity ordered before the policy rate (Christiano, Eichenbaum, and Evans (1999)).
- Generalized IRF (GIRF):
  - IRF to a shock on real GDP ordered first — interpreted as a business cycle shock (linear combination of historical shocks moving GDP).
- Spread shock identification:
  - Assume real activity, prices, and short- and long-rates (blocks 1, 2, 3) do not react contemporaneously; financial variables and net worth (blocks 5, 6) can react on impact.
  - Alternative: estimate on level bond yields and use an H-transformation to obtain IRFs for spreads (e.g., BAA-FFR = BAA − FFR), permitting intuitive priors and Cholesky identification of spread shocks.
- Robustness: reversing ordering of BAA and AAA in the VAR does not materially change spread-shock results.

### Impulse response analysis and model validation
- Comparison of DSGE variants:
  - JPTBGG (JPT with Bernanke, Gertler, Gilchrist (1999) financial accelerator) generates amplified responses relative to JPT; magnitudes closer to VAR evidence.
- Large-VAR responses to a contractionary monetary shock:
  - GDP, consumption, investment, employment contract substantially.
  - Prices decrease with a lag (price puzzle not present).
  - Monetary aggregates M1 and M2 decrease.
  - Stock prices fall and remain low; long rates jump up less than the short-term rate.
  - Credit spread (BAA-FFR) and maturity mismatch spread (AAA-FFR) fall to negative values on impact; default risk spread (BAA-AAA) jumps from a small positive value and reaches a maximum about eight quarters after impact.
  - Interpretation for spreads:
    - Maturity mismatch spread falls because AAA (long-maturity) yields are stickier to short-rate rises (elasticity of corporate yields to short-term rate decreases with bond maturity).
    - Default risk spread rises consistent with the financial accelerator: higher policy rates impede activity and raise firms’ default risk.
  - Policy-relevant observation: firms may issue longer maturity debt to protect against monetary contractions.

### Generalized IRF, cyclicality, and Great Recession evidence
- GIRF to a positive GDP shock (large VAR):
  - Real activity, short and long rates, and net worth are procyclical.
  - Bond yields go up slightly.
  - Monetary aggregates: M1 appears countercyclical; M2 appears procyclical (M2 contains broader household-held financial assets at longer maturities — e.g., savings deposits, small time deposits, retail money market mutual funds).
- Cyclicality of spreads:
  - Credit spread (BAA-FFR), default risk spread (BAA-AAA), and maturity mismatch spread (AAA-FFR) are countercyclical.
- Great Recession (Dec 2007 to June 2009) spread movements:
  - Credit spread rose four-fold.
  - Default risk spread rose three-fold.
  - Liquidity risk spread rose five-fold.
- Spread levels as of first quarter of 2013:
  - Default risk spread = 0.93.
  - Liquidity risk spread = 3.74.
- Monetary policy effects on spreads:
  - Expansionary policy lowers default risk spread but increases maturity mismatch spread.

### Spread shocks — transmission and comparative impact
- Spread shocks analyzed (one-standard-deviation terminology used interchangeably with one-percent):
  - Maturity mismatch spread shock (AAA-FFR).
  - Default risk spread shock (BAA-AAA).
- Common macro responses to a widening spread:
  - Investment and output respond in a hump-shaped manner with peak contraction at five quarters after impact.
  - Consumer expectations index rises, peaking at 10 quarters after impact.
  - Short and long rates decline.
  - Monetary aggregates increase; stock prices decline; exchange rate jumps initially then declines; equity variables fall.
- Comparative severity:
  - Maturity mismatch (liquidity) shock produces larger macroeconomic effects than the default risk shock.
  - Stock price declines are much larger when the shock originates from balance-sheet/liquidity problems than from default risk.
  - Net worth variables: after a default risk shock, net worth does not fully revert to pre-shock levels, unlike following a maturity mismatch shock.
- Policy implication: more measures may be needed to prevent or mitigate liquidity shortages.

### Key quantitative facts and statistics (preserved exactly from the analysis)
- System size: 34 variables.
- Lags in VAR: p = 13.
- Monetary policy shock magnitude used for identification: one percent exogenous deviation in the Federal Funds Rate.
- Contemporaneous correlations between spreads and log-GDP growth (Table 1):
  - BAA-FFR: −0.0238
  - AAA-FFR: 0.0557
  - BAA-AAA: −0.3416
- Sample range referenced for Wilshire correlation with net worth series: 1971Q1 to 2012Q4.
- Great Recession spread movements (Dec 2007 to June 2009):
  - Credit spread rose four-fold.
  - Default risk spread rose three-fold.
  - Liquidity risk spread rose five-fold.
- Spread levels as of first quarter of 2013:
  - Default risk spread = 0.93.
  - Liquidity risk spread = 3.74.
- Timing of peak responses to spread shocks:
  - Investment and output peak contraction at five quarters after impact.
  - Consumer expectations index peaks at 10 quarters after impact.
- Default risk spread reaches its maximum about eight quarters after a contractionary monetary policy shock in the large VAR.

### Main conclusions and policy-relevant implications
- Inclusion of broad information sets (large-scale VAR) changes key empirical responses relative to small-scale VARs and addresses the price puzzle.
- The "spread puzzle" in small VARs is resolved when decomposing spreads and using large information sets:
  - Maturity mismatch spread falls on monetary tightening due to long-yield stickiness, while default risk spread rises consistent with the financial accelerator.
- Both default risk and maturity mismatch components of credit spread are countercyclical, but they respond differently to monetary policy shocks.
- An adverse maturity mismatch (liquidity) shock has more severe macroeconomic consequences than an adverse default risk shock.
- Policy implications highlighted:
  - Firms may mitigate monetary contraction risk by issuing longer-maturity debt.
  - Additional measures are warranted to prevent liquidity shortages, given the larger macro impact of maturity mismatch shocks.

*Source: _wp14238 (canonical URL: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2014/_wp14238.pdf)*

### 1.   A  small-scale  modelthe  prototypical  monetary  VAR  model  augmented  by  spread  and

### _wp14238 - 1.   A  small-scale  modelthe  prototypical  monetary  VAR  model  augmented  by  spread  and

### Small-scale model
- The prototypical monetary VAR model augmented by spread and equity variables with six variables:
  - GDP
  - GDP Price Index
  - Federal Funds Rate
  - AAA yield
  - BAA yield
  - net worth

### Medium-scale model (JPTBGG data set)
- Contains nine variables and is used to estimate the author's DSGE models.
- Variables included:
  - Seven macroeconomic variables: output, consumption, investment, hours, wage, inflation, and interest rate
  - Two financial variables: spread and net worth
- The data set is per capita, as it is used to estimate the DSGE models.
- Reference for full description: Furlanetto, Gelain, and Taheri Sanjani (2013).
- Main purpose: cross-check the monetary policy propagation in VAR and DSGE models.

*Source: _wp14238 - 1.   A  small-scale  modelthe  prototypical  monetary  VAR  model  augmented  by  spread  and (canonical URL: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2014/_wp14238.pdf)*

### 3.  A large-scale model, with 34 variables, using a data set that nests the first specification

### 3.  A large-scale model, with 34 variables, using a data set that nests the first specification

### Model specification and data
- Endogenous vector y_t follows: y_t = c + A1 y_{t−1} + A2 y_{t−2} + ··· + A_p y_{t−p} + e_t, with e_t ∼ N(0_n, Σ).
- Number of lags: p = 13.
- System size: 34 variables.
- Shrinkage/estimation approach:
  - Bayesian shrinkage (Minnesota-type priors) to mitigate over-fitting for the richly parameterized system.
  - Degree of prior informativeness selected hierarchically to maximize the marginal likelihood (following Giannone, Lenza, and Primiceri (2012)).
- Variable definitions and transformations are in Table 2, Appendix 7 (not reproduced here).
- Spread measures:
  - External finance premium proxy: BAA-FFR.
  - Decomposition: maturity mismatch channel proxied by AAA-FFR; default risk channel proxied by BAA-AAA.
  - Note: BAA and AAA series are long-maturity Moody’s yields (Moody’s tries to include bonds with remaining maturities as close to 30 years as possible).
- Net worth block: six different definitions NW1 to NW6; correlations with the Wilshire 5000 are reported for 1971Q1 to 2012Q4 and are described as high (Table 3, Appendix).

### Identification strategy
- Monetary policy shock:
  - Defined as a one percent exogenous deviation in the Federal Funds Rate.
  - Recursive (Cholesky) identification ordering: prices and real activity ordered before the policy rate (Christiano, Eichenbaum, and Evans (1999)).
- Generalized IRF (GIRF):
  - IRF to a shock on real GDP ordered first — a linear combination of shocks historically moving GDP (interpreted as a business cycle shock).
- Spread shocks:
  - Identified by assuming real activity, prices, and short- and long-rates (blocks 1, 2, 3) do not react contemporaneously; financial variables and net worth (blocks 5, 6) can react on impact.
  - Alternative representation: estimate on level bond yields (e.g., BAA, AAA) and use an H-transformation to obtain IRFs for spreads (e.g., BAA-FFR = BAA − FFR). This permits intuitive priors (e.g., random walk on bond yields) and Cholesky identification of spread shocks.
- Robustness:
  - Ordering of BAA and AAA in the VAR reversed as a robustness check; results on spread shocks remain robust to ordering.

### Impulse response analysis — model validation
- Comparison of DSGE variants:
  - Models compared: JPT (Justiniano, Primiceri, Tambalotti (2013)) vs. JPTBGG (JPT augmented with Bernanke, Gertler, Gilchrist (1999) financial accelerator).
  - Finding: DSGE with financial frictions (JPTBGG) generates amplified responses relative to JPT; magnitudes closer to VAR evidence.
- VAR evidence and the "spread puzzle":
  - In small-scale VARs, credit spread (BAA-FFR) drops to negative values on impact of a contractionary monetary policy shock, contrary to financial accelerator prediction — termed the "spread puzzle".
  - Large-scale VARs ameliorate the price puzzle and change spread responses (see next subsection).

### Monetary policy transmission — small vs large VARs
- Small-scale VAR (six variables: GDP, GDP price index, Federal Funds Rate, AAA yield, BAA yield, net worth):
  - Contractionary monetary shock: output falls; yields rise; credit spread (BAA-FFR), default risk spread (BAA-AAA), and maturity mismatch spread (AAA-FFR) drop below zero on impact and then gradually rise.
  - Net worth/equity drops on impact.
- Large-scale VAR (34 variables):
  - Contractionary monetary shock: GDP, consumption, investment, employment contract substantially; prices decrease with a lag (price puzzle not present).
  - Monetary aggregates M1 and M2 decrease.
  - Stock prices fall and remain low; long rates jump up less than the short-term rate.
  - Credit spread (BAA-FFR) and maturity mismatch spread (AAA-FFR) fall to negative values on impact; default risk spread (BAA-AAA) jumps from a small positive value and reaches a maximum about eight quarters after impact.
  - Interpretation:
    - Maturity mismatch spread falls because AAA (long-maturity) yields are stickier to short-rate rises (elasticity of corporate yields to short-term rate decreases with bond maturity).
    - Default risk spread rises consistent with financial accelerator: higher policy rates impede activity and raise firms’ default risk.
  - Policy implication highlighted: firms may issue longer maturity debt to protect against monetary contractions.

### Generalized IRF and cyclicality
- GIRF to a positive GDP shock (large VAR):
  - Real activity, short and long rates, and net worth are procyclical.
  - Bond yields go up slightly.
  - Monetary aggregates: M1 appears countercyclical; M2 appears procyclical (M2 contains broader household-held financial assets at longer maturities — e.g., savings deposits, small time deposits, retail money market mutual funds).
- Cyclicality of spreads:
  - Generalized IRF analysis shows credit spread (BAA-FFR), default risk spread (BAA-AAA), and maturity mismatch spread (AAA-FFR) are countercyclical.
  - Evidence from the Great Recession:
    - Credit spread rose four-fold from Dec 2007 to June 2009.
    - Default risk spread rose three-fold in the same period.
    - Liquidity (maturity mismatch) risk spread rose five-fold in the same period.
    - By first quarter of 2013: default risk spread = 0.93; liquidity risk spread = 3.74.
  - Monetary policy effects: expansionary policy lowers default risk spread but increases maturity mismatch spread (consistent with earlier findings).

### Spread shocks — transmission and comparative impact
- Spread shock identification: macro blocks do not react contemporaneously; financial variables and net worth do.
- Two spread shocks analyzed via one-standard-deviation (one-percent or one-standard-deviation terminology used interchangeably in the exposition):
  - Maturity mismatch spread shock (AAA-FFR).
  - Default risk spread shock (BAA-AAA).
- Common responses to a widening spread:
  - Investment and output respond in a hump-shaped manner with peak contraction at five quarters after impact.
  - Consumer expectations index rises, peaking at 10 quarters after impact.
  - Short and long rates decline (consistent with accelerator mechanism).
  - Monetary aggregates increase; stock prices decline; exchange rate jumps initially then declines; equity variables fall.
- Comparative severity:
  - The maturity mismatch (liquidity) shock produces larger macroeconomic effects than the default risk shock.
  - Stock price declines are much larger when the shock originates from balance-sheet/liquidity problems than from default risk.
  - Net worth variables: after a default risk shock, net worth does not fully revert to pre-shock levels, unlike following a maturity mismatch shock.
  - Policy implication: more measures may be needed to prevent or mitigate liquidity shortages.

### Key quantitative facts and values preserved from the analysis
- System size: 34 variables.
- Lags in VAR: p = 13.
- Monetary policy shock magnitude used for identification: one percent exogenous deviation in the Federal Funds Rate.
- Contemporaneous correlations between spreads and log-GDP growth (Table 1):
  - BAA-FFR: −0.0238
  - AAA-FFR: 0.0557
  - BAA-AAA: −0.3416
- Sample range referenced for Wilshire correlation with net worth series: 1971Q1 to 2012Q4.
- Great Recession spread movements (Dec 2007 to June 2009):
  - Credit spread rose four-fold.
  - Default risk spread rose three-fold.
  - Liquidity risk spread rose five-fold.
- Spread levels as of first quarter of 2013:
  - Default risk spread = 0.93.
  - Liquidity risk spread = 3.74.
- Timing of peak responses to spread shocks:
  - Investment and output peak contraction at five quarters after impact.
  - Consumer expectations index peaks at 10 quarters after impact.
- Default risk spread reaches its maximum about eight quarters after a contractionary monetary policy shock in the large VAR.

### Main conclusions and policy-relevant implications
- Inclusion of broad information sets (large-scale VAR) changes key empirical responses relative to small-scale VARs and addresses the price puzzle.
- The "spread puzzle" (credit spread falling on contractionary monetary shocks in small VARs) is resolved when decomposing spreads and using large information sets:
  - Maturity mismatch spread falls on monetary tightening due to long-yield stickiness, while default risk spread rises consistent with the financial accelerator.
- Both default risk and maturity mismatch components of credit spread are countercyclical, but they respond differently to monetary policy shocks.
- An adverse maturity mismatch (liquidity) shock has more severe macroeconomic consequences than an adverse default risk shock.
- Policy implications:
  - Firms may mitigate monetary contraction risk by issuing longer-maturity debt.
  - Additional measures are warranted to prevent liquidity shortages, given the larger macro impact of maturity mismatch shocks.

*Source: _wp14238 - 3.  A large-scale model, with 34 variables, using a data set that nests the first specification*

### References

### References

### Bibliographic citations
- [1] Bernanke, B. & Gertler, M., 1989, ”Agency Costs, Net Worth and Business Fluctuations,” American Economic Review: 14-31.
- [2] Ben Bernanke, Gertler, M., & Simon Gilchrist, 1999, ”The Financial Accelerator in a Quantitative Business Cycle Framework,” Handbook of Macroeconomics.
- [3] Martha Banbura &Domenico Giannone & Lucrezia Reichlin, 2008. ”Large Bayesian VARs,” Working Papers ECARES 2008 033, ULB−−UniversiteLibredeBruxelles.
- [4] Jean Boivin & Marc P. Giannoni & Dalibor Stevanovic, 2013. ”Dynamic effects of credit shocks in a data-rich environment,” Staff Reports 615, Federal Reserve Bank of New York.
- [5] Christensen, I., Dib, A., 2008. Monetary policy in an estimated DSGE model with a financial accelerator. Review of Economic Dynamics 11, 155178.
- [6] Lawrence Christiano & Roberto Motto & Massimo Rostagno, 2013. ”Risk Shocks,” NBER Working Papers 18682, National Bureau of Economic Research, Inc.
- [7] Christiano, L. & Martin Eichenbaum & Charles L. Evans, 1994. ”Identification and the effects of monetary policy shocks,” Working Paper Series, Macroeconomic Issues 94-7, Federal Reserve Bank of Chicago.
- [8] Christiano, L. & Martin Eichenbaum & Charles L. Evans, 1998. ”Monetary Policy Shocks: What Have We Learned and to What End?,” in Handbook of Macroeconomics, chap. 2, pp. 65148. Elsevier.
- [9] Curdia, Vasco & Michael Woodford (2009), ”Credit Frictions and Optimal Monetary Policy”, working paper Federal Reserve Bank of New York.
- [10] De Mol, C., D. Giannone, & L. Reichlin (2008): ”Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?,” Journal of Econometrics, 146(2), 318328.
- [11] den Haan, W. J., S. W. Sumner, & G. M. Yamashiro (2007): ”Bank loan portfolios and the monetary transmission mechanism,” Journal of Monetary Economics, 54(3), 904924.
- [12] Doan, T., R. Litterman, & C. A. Sims (1984): ”Forecasting and Conditional Projection Using Realistic Prior Distributions,” Econometric Reviews, 3, 1100.
- [13] De Graeve, Ferre, 2008. ”The external finance premium and the macroeconomy: US post-WWII evidence,” Journal of Economic Dynamics and Control, Elsevier, vol. 32(11), pages 3415-3440, November.
- [14] Faia, E., Monacelli, T., 2007. Optimal interest rate rules, asset prices and credit frictions. Journal of Economic Dynamics and Control 31, 32283254.
- [15] Gertler, M., & S. Gilchrist (1995): ”The role of credit market imperfections in the monetary transmission mechanism: arguments and evidence,” Scandinavian Journal of Economics, (1), 4364.
- [16] Gilchrist, Simon, Vladimir Yankov & Egon Zakrajsek, 2009, ”Credit Market Shocks and Economic Fluctuations: Evidence from Corporate Bond and Stock Markets,” forthcoming in the Journal of Monetary Economics.
- [17] Giannone, D., M. Lenza, & G. Primiceri (2012): ”Priors for Vector Autoregressions,” Cepr discussion paper 8755.
- [18] Giannone, D., M. Lenza, & L. Reichlin (2012): ”Money, Credit, Monetary Policy and the Business Cycle in the Euro Area,” Working Papers ECARES 2012-008, ULB - Universite Libre de Bruxelles.
- [19] Giannone, D., M. Lenza, & L. Reichlin (2010): ”Business Cycles in the Euro Area,” National Bureau of Economic Research, Inc.
- [20] D. Giannone & L. Reichlin, 2006. ”Does information help recovering structural shocks from past observations?,” Journal of the European Economic Association, MIT Press, vol. 4(2-3), pages 455-465, 04-05.
- [21] Giannone, D., L. Reichlin, & L. Sala (2005): ”Monetary Policy in Real Time,” in NBER Macroeconomics Annual 2004, Volume 19, NBER Chapters, pp. 161224. National Bureau of Economic Research, Inc.
- [22] Goodfriend, Marvin, 1998, Using the Term Structure of Interest Rates for Monetary Policy, Federal Reserve Bank of Richmond Quarterly Review, volume 84/3 Summer.
- [23] Litterman, R. B. (1980): ”A Bayesian Procedure for Forecasting with Vector Autoregres- sion.,” Working paper, Massachusetts Institute of Technology, Department of Economics.
- [24] Justiniano, A. & Primiceri, G. E. & Tambalotti, A. (2010), ”Investment Shocks and Business Cycles,” Journal of Monetary Economics, 57(2), March 2010, pp. 132-145.
- [25] Kiyotaki, Nobuhiro & John Moore, 1997, ”Credit Cycles,” Journal of Political Economy.
- [26] Meeks, R., 2007. Shocks and cycles in the credit market. Mimeo, University of Oxford.
- [27] Peersman, G., 2011: ”Macroeconomic Effects of Unconventional Monetary Policy in the Euro Area,” CEPR Discussion Papers 8348, C.E.P.R. Discussion Papers.
- [28] Peersman, Gert Smets, Frank, 2001. ”The monetary transmission mechanism in the euro area: more evidence from VAR analysis,” Working Paper Series, European Central Bank 0091.
- [29] Smets, Frank & Raf Wouters, 2007, ”Shocks and Frictions in U.S. Business Cycles: A Bayesian DSGE Approach,” American Economic Review.

### Appendix - Data (variable list)
- 1. REAL GROSS DOMESTIC PRODUCT, Quantity Index (2000=100), SAAR.
- 2. GROSS DOMESTIC PRODUCT PRICE INDEX.
- 3. CPI All Items (SA).
- 4. Real SPOT MARKET PRICE INDEX: BLS CRB: ALL COMMODITIES (1967=100) (PSC-COM/PCEPILFE).
- 5. INDUSTRIAL PRODUCTION INDEX - TOTAL INDEX.
- 6. EMPLOYEES, NONFARM - TOTAL PRIVATE.
- 7. EMPLOYEES, NONFARM - SERVICE-PROVIDING.
- 8. REAL PERSONAL CONSUMPTION EXPENDITURES, Quantity Index (2000=100), SAAR.
- 9. REAL GROSS PRIVATE DOMESTIC INVESTMENT - Residential, Quantity Index (2000=100).
- 10. REAL GROSS PRIVATE DOMESTIC INVESTMENT - Nonresidential, Quantity Index.
- 11. PERSONAL CONSUMPTION EXPENDITURES PRICE INDEX.
- 12. GROSS PRIVATE DOMESTIC PRICE INDEX.
- 13. CAPACITY UTILIZATION - MANUFACTURING (SIC).
- 14. U. OF MICH. INDEX OF CONSUMER EXPECTATIONS (BCD-83).
- 15. HOURS OF ALL PERSONS: NONFARM BUSINESS SEC (1982=100, SA).
- 16. REAL COMPENSATION PER HOUR, EMPLOYEES: NONFARM BUSINESS (82=100, SA).
- 17. FEDERAL FUNDS (EFFECTIVE) (% PER ANNUM, NSA).
- 18. U.S. TREASURY CONST MATURITIES, 3 months.(% PER ANN, NSA).
- 19. U.S. TREASURY CONST MATURITIES, 6 months.(% PER ANN, NSA).
- 20. U.S. TREASURY CONST MATURITIES, 1-YR.(% PER ANN, NSA).
- 21. U.S. TREASURY CONST MATURITIES, 5-YR.(% PER ANN, NSA).
- 22. U.S. TREASURY CONST MATURITIES, 10-YR.(% PER ANN, NSA).
- 23. BOND YIELD: MOODY’S AAA CORPORATE (% PER ANNUM).
- 24. BOND YIELD: MOODY’S BAA CORPORATE (% PER ANNUM).
- 25. MONEY STOCK: M1(CURR, TRAV.CKS, DEM DEP, OTHER CK’ABLE DEP) (BIL$, SA)’.
- 26. MONEY STOCK: M2 (M1+O’NITE RPS, EURO $, G/P, B/D MMMFS, SAV, SM TIME DEP(BIL$).
- 27. S&P’S COMMON STOCK PRICE INDEX: COMPOSITE (1941-43=10).
- 28. USA EFFECTIVE EXCHANGE RATE (MERM)(INDEX NO.).
- 29. NW1: MVEONWMVBSNNCB MARKET VALUE OF EQUITIES OUTSTANDING - NET WORTH (MARKET VALUE) - BALANCE SHEET OF NONFARM NONFINANCIAL CORPORATE BUSINESS (MVEONWMVBSNNCB), BILLIONS OF DOLLARS, QUARTERLY, NOT SEASONALLY ADJUSTED.
- 30. NW2: OEHRENWBSHNO OWNERS’ EQUITY IN HOUSEHOLD REAL ESTATE - NET WORTH - BALANCE SHEET OF HOUSEHOLDS AND NONPROFIT ORGANIZATIONS (OEHRENWBSHNO), BILLIONS OF DOLLARS, QUARTERLY, NOT SEASONALLY ADJUSTED.
- 31. NW3: TNWMVBSNNCB TOTAL NET WORTH (MARKET VALUE) - BALANCE SHEET OF NONFARM NONFINANCIAL CORPORATE BUSINESS (TNWMVBSNNCB), BILLIONS OF DOLLARS, QUARTERLY, NOT SEASONALLY ADJUSTED.
- 32. NW4: RCSNNWMVBSNNCB REPLACEMENT-COST VALUE OF STRUCTURES: NON-RESIDENTIAL - NET WORTH (MARKET VALUE) - BALANCE SHEET OF NONFARM NONFINANCIAL CORPORATE BUSINESS (RCSNNWMVBSNNCB), BILLIONS OF DOLLARS, QUARTERLY, NOT SEASONALLY ADJUSTED.
- 33. NW5: TNWHCBSNNCB TOTAL NET WORTH (HISTORICAL COST) - BALANCE SHEET OF NONFARM NONFINANCIAL CORPORATE BUSINESS (TNWHCBSNNCB), BILLIONS OF DOLLARS, QUARTERLY, NOT SEASONALLY ADJUSTED.
- 34. NW6: TNWBSNNB TOTAL NET WORTH - BALANCE SHEET OF NONFARM NONCORPORATE BUSINESS (TNWBSNNB), BILLIONS OF DOLLARS, QUARTERLY, NOT SEASONALLY ADJUSTED.

### Table 2: Data Description and Transformation (variable mappings)
- Block #1
  - Position 1: RGDP — Real GDP — log level — Small: X — Large: X
  - Position 2: PGDP — GDP Price Index — log level — Small: X — Large: X
  - Position 3: CPI-ALL — CPI All Items — log level — Small: X
  - Position 4: Com: spot price (real) — Commodity Price — log level — Small: X
  - Position 5: IP: total — Industrial Production — log level — Small: X
  - Position 6: Emp: total — Total Employment — log level — Small: X
  - Position 7: Emp: services — Service Employment — Level — Small: X
- Block 1 (continued)
  - Position 8: Cons — Real Personal Consumption — log level — Small: X
  - Position 9: Res.Inv — Residential Investment — log level — Small: X
  - Position 10: NonResInv — NonResidential Investment — log level — Small: X
  - Position 11: PCED — Consumption expenditures Price Index — log level — Small: X
  - Position 12: PGPDI — Investment Price Index — log level — Small: X
  - Position 13: Capacity Util — Capcity Utilization: Manufacturing — Level — Small: X
  - Position 14: Consumer expect — Consumer expectation — Level — Small: X
  - Position 15: Emp. Hours — Hours worked — log level — Small: X
  - Position 16: Real Comp/Hour — real compensation per hours — log level — Small: X
- Block 2
  - Position 17: FedFunds — Effective Federal Fund Rate — Level — Small: X — Large: X
  - Position 18: 3mTB — Treasury Bill Rate 3 months — Level — Small: X
  - Position 19: 6mTB — Treasury Bill Rate 6 months — Level — Small: X
- Block 3
  - Position 20: 1yTB — Treasury Bill Rate 1 year — Level — Small: X
  - Position 21: 5yTb — Treasury Bill Rate 5 year — Level — Small: X
  - Position 22: 10yTB — Treasury Bill Rate 10 year — Level — Small: X
- Block 4
  - Position 23: AAA yield — AAA Corporate Bond Yield — Level — Small: X — Large: X
  - Position 24: BAA yield — BAA Corporate Bond Yield — Level — Small: X — Large: X
  - Position 25: M1 — M1 — log level — Small: X
- Block 5
  - Position 26: M2 — M2 — log level — Small: X
  - Position 27: S&P 500 — SP500 — log level — Small: X
  - Position 28: Ex rate: avg — Effective Exchange Rate — log level — Small: X
  - Position 29: NW1 — MVEONWMVBSNNCB — log level — Small: X — Large: X
  - Position 30: NW2 — OEHRENWBSHNO — log level — Small: X
- Block 6
  - Position 31: NW3 — TNWMVBSNNCB — log level — Small: X
  - Position 32: NW4 — RCSNNWMVBSNNCB — log level — Small: X
  - Position 33: NW5 — TNWHCBSNNCB — log level — Small: X
  - Position 34: NW6 — TNWBSNNB — log level — Small: X

### Appendix - Net worth (summary statistics)
- Figure 16: Net Worth time series.
- Table 3: Correlation Between Net worths and Whilshire 5000
  - Corr with Whilshire: NW1 0.996, NW2 0.916, NW3 0.944, NW4 0.939, NW5 0.971, NW6 0.934
- Table 4: Series Definitions
  - NW1: MVEONWMVBSNNCB Market Value of Equities Outstanding-Corporate
  - NW2: OEHRENWBSHNO Owners’ Equity in Household Real Estate
  - NW3: TNWMVBSNNCB Total Net Worth (Market Value)-Corporate
  - NW4: RCSNNWMVBSNNCB Replacement-Cost Value of Structures-Corporate
  - NW5: TNWHCBSNNCB Total Net Worth (Historical Cost)-Corporate
  - NW6: TNWBSNNB Nonfarm Noncorporate Business (Financial)

*Content unit: _wp14238 - References (PDF chapter/section)*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2014/_wp14238.pdf_