## 1. Asset Prices and Global Liquidity

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### Introduction and research focus
- Motivation:
  - Interest in the concept of “global liquidity” and its impact on economic growth and inflation increased in recent years.
  - Debated role of global liquidity in exerting upward pressure on equity, commodity and house prices.
  - Observations noted:
    - In the G-7 countries, aggregate house prices more than doubled between 2000 and 2008.
    - Equity prices increased by more than 10 percent over the same period.
    - The oil price at one point exceeded $140 per barrel.
- Research questions:
  - Is global liquidity useful in predicting global asset prices: housing, equity and commodity/oil?
  - Was the impact of global liquidity stable across two subperiods associated with the “Great Moderation” (pre-1984 and post-1984)?
  - What are the spillovers from global liquidity to domestic liquidity in G-7 countries and the relative impact of global liquidity versus domestic factors on domestic house prices?

### Global liquidity measure and data construction
- Global liquidity indicator (M):
  - Constructed as the sum of the U.S. monetary base (total reserves with the Federal Reserve plus currency) and world international reserves.
  - Intended to capture the availability of a global medium of exchange.
- Data and aggregation:
  - Quarterly data, 1971Q1 to 2009Q3, for G7 countries: Canada, France, Germany, Italy, Japan, USA, and U.K.
  - Country-level variables: Real GDP (Yi), GDP deflator (Pi), 3-month nominal interest rate (ISi), narrow money (Mi), House price index (HPIi).
  - Global asset price indices: MSCI World index (MSCI), CRB Spot Index (commodity price index), CoPI (global commodity price index including oil).
  - All data from IMF and OECD databases and seasonally adjusted, except interest rates, using the X12-ARIMA procedure.
  - G-7 aggregates constructed following the three-step aggregation procedure of Beyer and others, (2001) (weights wi,t, aggregate growth rate gagg,t, indexagg,T with base year 1970 = 100).
  - In spillover analysis global variables are G-6 aggregates (exclude the country under investigation); the global liquidity indicator is corrected for country i’s contribution (denoted with a tilde).

### Methodology and model specification
- Time span and unit-root/cointegration properties:
  - Sample: 1971Q1 to 2009Q3.
  - Unit root tests suggest all series are integrated of order one; at least some are cointegrated. Estimating the model in levels gives asymptotically consistent estimators.
- VAR specification:
  - Baseline VAR with lag order two (AIC, SC, and LR tests support AR(2)).
  - Baseline specification: xt = ν + αt + (A1 L + A2 L2) xt + ut.
- Variable vectors:
  - Global model: xt = (yt, pt, hpit, IS t, mt, copi t, msci t).
  - Spillover (domestic) model: xti = (ỹt, ṗt, ˜IS t, ˜m t, yti, pti, IS t i, hpi t i, m t i).
  - All variables except interest rates enter in logs.
- Identification:
  - Residual covariance Σu decomposed by Cholesky: Σu = P′P; transformation yields orthogonal residuals εt with diagonal covariance Σε.
  - Cholesky ordering imposes that a shock to variable l cannot have an instantaneous effect on variables k < l; ordering within blocks follows literature conventions and relative sluggishness.
- Caveats:
  - Global analysis allows a shock to country i’s GDP to affect all other global variables in line with its share of global GDP; this channel is absent in the spillover analysis.
  - Changing composition of the G6 aggregate alters contemporaneous influences across country-specific spillover estimations (example: U.S. vs Japan).

### Main empirical findings
- Global roles by asset class:
  - Global liquidity plays a relatively important role for house price developments, but less so for equity prices.
  - Global liquidity had a minimal impact on oil prices but is a more useful predictor of a broad based commodity price index.
- Responses to shocks (impulse responses and FEVDs):
  - Interest rate shock:
    - An unanticipated increase in the nominal interest rate corresponds to a contractionary monetary shock: economic activity declines and asset prices shrink.
    - A price puzzle is observed: an initially positive reaction of the price level to the interest rate shock.
  - Liquidity shock (positive shock to global liquidity = monetary expansion):
    - Global liquidity shocks have a sluggish but persistent impact on house and commodity prices.
    - No significant response of equity prices to global liquidity shocks.
    - The overall price level only picks up with a substantial lag.
- Time variation across sub-samples:
  - Pre–Great Moderation (1971Q1 to 1983Q4):
    - Impulse responses to a global liquidity shock: house prices and equity (in the short run) are significant.
    - Global liquidity—and to an even larger extent the nominal interest rate—explains a substantial share of asset price volatility.
  - Great Moderation (1984Q1 to 2007Q4):
    - Impulse responses to a liquidity shock become largely insignificant.
    - Global liquidity loses most forecasting power for equity and house prices and retains some for commodity prices.
    - The impact of liquidity on asset prices appears to have weakened during the Great Moderation.
  - Inclusion of 2008–09 (extending the latter sub-sample to 1983Q1–2009Q3):
    - Liquidity loses almost all predictive power for asset prices when the global financial crisis period is included.
    - Explanation: during crises monetary policy expands liquidity while asset prices collapse, creating a negative relationship between liquidity and asset prices. The impact of liquidity on asset prices is likely asymmetric across boom and bust phases.

### Spillover analysis and country heterogeneity
- Aggregation conceals heterogeneity in house price dynamics across G7 countries (example: strong housing bubbles in the U.S. and the U.K.; opposite dynamics in Japan and Germany).
- Japan (1971Q1–2009Q3):
  - Global liquidity shock contributes positively to the overall price level in Japan, but house prices do not respond significantly to global or domestic shocks.
  - Consistent with Japan not experiencing a housing bubble.
- United States (1971Q1–2009Q3):
  - Domestic rather than global liquidity shocks drive and forecast U.S. house prices in this analysis.
  - Challenges the view that global savings glut or global liquidity were primary drivers of the U.S. housing bubble and suggests domestic monetary policy played the dominant role.
- Interpretive caveats:
  - The global liquidity measure may not capture liquidity expansion associated with the shadow banking system, particularly in the United States.
  - Counterpoint: a large proportion of global reserves (including those of surplus countries such as China) were invested in advanced-economy financial assets; purchases of treasury bills with international reserves indirectly reduced domestic government funding demand and permitted private credit expansion.
- Overall: spillover analysis indicates domestic factors were more important than global factors for house price developments in the cases examined.

### Conclusions, policy implications, and suggested research avenues
- Conclusions:
  - The alternative global liquidity measure (M) shows an asymmetric impact of global liquidity across asset classes: a much stronger effect on house prices compared to equity and commodity prices.
  - Important differences before and during the Great Moderation: impact was lower during the Great Moderation and nearly lost predictive power for asset prices when including 2008–09.
  - During crises liquidity and asset prices can move in opposite directions due to expansionary monetary policy, implying an asymmetric relationship between boom and bust phases.
  - Domestic factors played a much greater role than global factors in house price developments (notably in the U.S. and Japan), supporting the view that monetary policy tools might have been effective in confronting housing market risks.
- Suggested research avenues:
  1. Adequacy of the global liquidity indicator:
     - Investigate whether the medium-of-exchange measure used adequately captures the expansion in liquidity associated with the shadow banking system and other market liquidity developments since the late 1980s.
     - If the indicator fails to capture shadow-banking liquidity, develop an adequate indicator of “global” market liquidity.
  2. Asymmetric relationship and regime-switching:
     - Test the hypothesis that global liquidity has a more pronounced impact during boom phases (or bubble formation) than during bust phases.
     - Econometric challenge: design a model that endogenously identifies regime switches between bubble/no-bubble phases.
- Additional observation:
  - The stronger impact of the liquidity measure on a broad commodity index than on oil is interpreted as partial evidence favoring the asymmetric/bubble hypothesis because a broad index picks up a greater number of bubbles.

*Source: IMF working paper chapter “1. Asset Prices and Global Liquidity,” text from the supplied PDF content unit.*

### 1. Asset Prices and Global Liquidity ...................................................................................

### 1. Asset Prices and Global Liquidity

### Introduction: motivation and conceptual framing
- Interest in the concept of “global liquidity” and its impact on economic growth and inflation increased in recent years.
- Prior to the recent economic crisis, economists debated whether global liquidity had played a significant role in exerting upward pressure on equity, commodity and house prices.
- Observations noted:
  - In the G-7 countries, aggregate house prices more than doubled between 2000 and 2008.
  - Equity prices increased by more than 10 percent over the same period.
  - The oil price at one point exceeded $140 per barrel.
- If excess global liquidity drove asset price increases, this would imply a global dimension weakening the potency of domestic monetary policy and could argue for enhanced monetary policy coordination.
- The paper adopts a measure of global liquidity constructed by adding international reserves to U.S. base money. This differentiates the analysis from most approaches that use aggregated broad money for major economies (G7-countries).

### Research focus and questions
- Examine whether global liquidity is useful in predicting global asset prices: housing, equity and commodity/oil.
- Assess whether the impact of global liquidity on asset prices was stable across two subperiods commonly associated with the “Great Moderation” (pre-1984 and post-1984).
- Examine spillovers from global liquidity to domestic liquidity in G-7 countries and the relative impact of global liquidity versus domestic factors on domestic house prices.

### Key empirical novelties
- Use of a global liquidity measure based on international reserves plus U.S. base money (introduced in an empirical setting by Matsumoto and Schindler (2006)).
- Focus on time-varying impact across sub sample periods (1971–83 and 1984–2007).
- Analysis of spillovers to G-7 countries and relative contributions of global and domestic factors to house price developments.

### Main results (authors’ summary)
- Global liquidity plays a relatively important role for house price developments, but less so for equity prices.
- Global liquidity had a minimal impact on oil prices but is a more useful predictor of a broad based commodity price index.
- The impact of global liquidity varied across the two sub sample periods (1971–83 and 1984–2007):
  - Before 1984, global liquidity had a traceable impact on asset price volatility.
  - After 1984, global liquidity lost its explanatory power almost entirely for equity prices, and noticeably for housing and commodity prices.
- Spillover effects from global liquidity vary across the G-7 countries.
- Relative to global factors, domestic factors played a much more significant role in house price developments.
- Findings are broadly in line with previous studies using broad money measures, but the observed change in the relationship across sample periods is a novel result.

### Literature context
- Prior studies and findings cited:
  - Baks and Kramer (1999): global liquidity (broad/narrow money aggregates) negatively correlated with interest rates; positively correlated with stock returns; spillovers from U.S. excess money to Japan.
  - Sousa and Zaghini (2006): global liquidity shocks matter for price and output fluctuations in the euro area; significant proportion of euro area M3 driven by global liquidity.
  - Rüffer and Stracca (2006): expansionary global monetary shocks generate significant spillovers to the euro area and to some extent Japan; a composite real asset price index did not appear sensitive.
  - Belke and others (2010): inclusion of commodity prices helps identify a significant role for global liquidity in explaining aggregate demand and inflation.
  - D’Agostino and Surico (2009): information content of global liquidity superior to domestic factors in forecasting inflation.
  - Giese and Tuxen (2007): weak relationship between global liquidity shocks and share prices.
  - Belke and others (2008): VAR models suggest house prices are relatively sensitive to global liquidity shocks.
- The paper follows Belke and others (2008) but (i) introduces a different global liquidity measure emphasizing international reserves and (ii) focuses on time variation across the Great Moderation period.

### Data and methodology (overview)
- Quarterly data, 1971Q1 to 2009Q3, for G7 countries: Canada, France, Germany, Italy, Japan, USA, and U.K.
- Country-level variables collected:
  - Real GDP (Yi)
  - GDP deflator (Pi)
  - 3-month nominal interest rate (ISi)
  - Measure of narrow money (Mi)
  - House price index (HPIi)
- Global asset price indices included:
  - MSCI World index (MSCI)
  - CRB Spot Index (commodity price index)
  - CoPI: a global commodity price index consisting of a basket of internationally traded commodities including oil
- The global liquidity measure used: international reserves + U.S. base money.

### Implications and contributions
- Demonstrates that choice of global liquidity measure matters and that results using reserves-plus-U.S.-base-money are broadly consistent with, but extend, the literature that uses aggregated broad money.
- Establishes that the explanatory power of global liquidity for asset prices is time-varying and weakened after 1984 for several asset classes.
- Highlights that domestic factors remain crucial for explaining house price developments in G-7 countries despite global spillovers.

*Source: IMF working paper chapter “1. Asset Prices and Global Liquidity,” text from the supplied PDF content unit.*

### introduction of a different global liquidity indicator (M), which is constructed as the sum of

### _wp10196 - introduction of a different global liquidity indicator (M), which is constructed as the sum of

### Data, aggregation, and indicator construction
- Global liquidity indicator (M) is constructed as the sum of the U.S. monetary base (total reserves with the Federal Reserve plus currency) and world international reserves. This measure is intended to capture the availability of a global medium of exchange.
- All data are taken from IMF and OECD databases and seasonally adjusted, except for the interest rate, using the X12-ARIMA procedure.
- Global (G7) aggregates are constructed for real GDP, the GDP deflator, short-run interest rates, and the house price index following the three-step aggregation procedure of Beyer and others, (2001) and applied by Belke and others, (2008):
  - Convert all GDP series to a common currency (SDR).
  - Country i’s weight at time t: wi,t = ei,tSDR GDPi,t / Σi ei,tSDR GDPi,t (equation III-1).
  - Aggregate growth rate at time t: gagg,t = Σi wi,t gi,t (equation III-2).
  - Global variable in levels: indexagg,T = 100 Πt=1..T (1 + gagg,t) with base year 1970 = 100 (equation III-3).
- In spillover analysis global variables are G-6 aggregates (exclude the country under investigation); the global liquidity indicator is corrected for country i’s contribution. These corrected variables are denoted with a tilde.

### Methodology and model specification
- Unit root tests suggest all series are integrated of order one; at least some are cointegrated. Estimating the model in levels gives asymptotically consistent estimators.
- Baseline approach: VAR with lag order two (AIC, SC, and LR test statistics suggest an autoregressive structure of order two). Baseline specification (equation III-4):
  - xt = ν + αt + (A1 L + A2 L2) xt + ut
- Two-part analysis:
  - Global model variables: xt = (yt, pt, hpit, IS t, mt, copi t, msci t) (equation III-5).
  - Spillover (domestic) model variables: xti = (ỹt, ṗt, ˜IS t, ˜m t, yti, pti, IS t i, hpi t i, m t i) (equation III-6).
  - In both cases, all variables except interest rates enter in logs.
- Identification and orthogonalization:
  - Residual covariance Σu is decomposed by Cholesky: Σu = P′P. Let D be diagonal with main diagonal identical to P; then Σu = P D−1 [D′ D] P D−1′ ≡ W Σε′ W, yielding a lower-triangular W with unit main diagonal (equations III-7 to III-9).
  - Pre-multiplying by W−1 yields orthogonal residuals εt with diagonal covariance Σε.
  - The Cholesky transformation imposes ordering sensitivity: a shock to variable l cannot have an instantaneous effect on variables k < l. The vectors in (III-5) and (III-6) represent the chosen Cholesky ordering; within blocks the ordering follows literature conventions and reflects relative sluggishness of responses.
- Caveats on spillover identification:
  - Global analysis allows a shock to country i’s GDP to affect all other global variables in line with its share of global GDP; this channel is absent in the spillover analysis. This implies an inconsistency in identifying assumptions across models.
  - Changing composition of the G6 aggregate alters contemporaneous influences across country-specific spillover estimations (example: U.S. vs Japan).

### Global analysis — main findings
- Sample and figures:
  - Full sample: 1971Q1 to 2009Q3.
  - Impulse responses to an interest rate shock and a liquidity shock are presented (Figure 2).
- Interest rate shock:
  - An unanticipated increase in the nominal interest rate corresponds to a contractionary monetary shock: economic activity declines and asset prices shrink.
  - A price puzzle is observed: an initially positive reaction of the price level to the interest rate shock. This is commonly interpreted as indicating the lack of a variable capturing long-term inflation expectations.
- Liquidity shock (positive shock to global liquidity = monetary expansion):
  - Global liquidity shocks have a sluggish but persistent impact on house and commodity prices.
  - No significant response of equity prices to global liquidity shocks.
  - The overall price level only picks up with a substantial lag.
  - These results are confirmed by forecast error variance decompositions (Appendix, Figure 10).
- Sub-sample analysis:
  - Pre–Great Moderation (1971Q1 to 1983Q4):
    - Impulse responses to a global liquidity shock: house prices and equity (in the short run) are significant.
    - Global liquidity—and to an even larger extent the nominal interest rate—explains a substantial share of asset price volatility (see Figure 4).
  - Great Moderation (1984Q1 to 2007Q4):
    - Impulse responses to a liquidity shock become largely insignificant.
    - Global liquidity loses most forecasting power for equity and house prices and retains some for commodity prices.
    - The impact of liquidity on asset prices appears to have weakened during the Great Moderation.
  - Inclusion of 2008–09 (extending the latter sub-sample to 1983Q1–2009Q3 in Appendix Figure 11):
    - Liquidity loses almost all predictive power for asset prices when the global financial crisis period is included.
    - Explanation: during crises monetary policy expands liquidity while asset prices collapse, creating a negative relationship between liquidity and asset prices. The impact of liquidity on asset prices is likely asymmetric across boom and bust phases.

### Spillover analysis — country heterogeneity and house prices
- Aggregation conceals heterogeneity: house price indices show different behavior across G7 countries (Figure 7). Examples cited: strong housing bubbles in the U.S. and the U.K.; opposite dynamics in Japan and Germany.
- Japan (sample 1971Q1–2009Q3; Figure 8):
  - Global liquidity shock contributes positively to the overall price level in Japan, but house prices do not respond significantly to global or domestic shocks.
  - Consistent with Japan not experiencing a housing bubble.
- United States (sample 1971Q1–2009Q3; Figure 9):
  - Domestic rather than global liquidity shocks drive and forecast U.S. house prices in this analysis.
  - This result challenges the view that global savings glut or global liquidity were primary drivers of the U.S. housing bubble and suggests domestic monetary policy played the dominant role.
- Interpretation and caveats:
  - The global liquidity measure may not capture liquidity expansion associated with the shadow banking system, particularly in the United States.
  - Counterpoint: a large proportion of global reserves (including those of surplus countries such as China) were invested in advanced-economy financial assets, thus contributing to global liquidity; purchases of treasury bills with international reserves indirectly reduced domestic government funding demand and permitted private credit expansion.
  - Overall, the spillover analysis indicates domestic factors were more important than global factors for house price developments in the cases examined.

### Conclusion, implications, and suggested research avenues
- Summary conclusions:
  - The alternative global liquidity measure (M) vindicates an asymmetric impact of global liquidity across asset classes: a much stronger effect on house prices compared to equity and commodity prices.
  - There are important differences in the impact of global liquidity before and during the Great Moderation: impact was lower during the Great Moderation and nearly lost predictive power for asset prices when including 2008–09.
  - During crises liquidity and asset prices can move in opposite directions due to expansionary monetary policy, suggesting an asymmetric relationship between boom and bust phases.
  - Domestic factors played a much greater role than global factors in house price developments (notably in the U.S. and Japan), supporting the view that monetary policy tools might have been effective in confronting housing market risks.
- Two key areas for future research identified:
  1. Adequacy of the global liquidity indicator:
     - Investigate whether the medium-of-exchange measure used adequately captures the expansion in liquidity associated with the shadow banking system and other market liquidity developments since the late 1980s.
     - If the indicator fails to capture shadow-banking liquidity, develop an adequate indicator of “global” market liquidity.
  2. Asymmetric relationship and regime-switching:
     - Test the hypothesis that global liquidity has a more pronounced impact during boom phases (or bubble formation) than during bust phases.
     - The econometric challenge: design a model that endogenously identifies regime switches between bubble/no-bubble phases.
- Additional observation:
  - The stronger impact of the liquidity measure on a broad commodity index than on oil is interpreted as partial evidence favoring the asymmetric/bubble hypothesis because a broad index picks up a greater number of bubbles.

*Source: IMF working paper content (figures, equations, and quoted sample periods and model specifications as provided in the source text).*

### References

### _wp10196 - References

### Major thematic areas covered by the references
- Global liquidity measurement and implications for asset prices and commodity prices.
- Links between liquidity, monetary policy, and financial cycles.
- Historical and cross-country data construction and macroeconomic modelling (including inflation and output fluctuations).
- House price dynamics and fundamentals.
- Global monetary policy shocks and transmission across major economies.
- Discussions of macro-financial stability and monetary framework debates.

### Key references (author, year, title, outlet or series as given)
- Adrian, T., Shin, H.S., 2008, “Liquidity, Monetary Policy and Financial Cycles,” Current Issues in Economics and Finance 14, Federal Reserve Bank of New York.
- Baks, K., Kramer, C., 1999, “Global Liquidity and Asset Prices: Measurement, Implications and Spillovers,” IMF Working Paper No. 99/168 (Washington).
- Belke, A., Bordon, I., Hendricks, T., 2010, “Monetary Policy, Global Liquidity and Commodity Price Dynamics,” Discussion Papers No. 971 (DIW Berlin: German Institute for Economic Research).
- Belke, A., Orth, W., Setzer, R., 2008, “Sowing the Seeds of the Subprime Crisis—Does Global Liquidity Matter for Housing and Other Asset Prices,” International Economics and Economic Policy Vol. 5(4), pp. 403–24.
- Belke, A., Gros, D., 2007, “Instability of the Eurozone? On Monetary Policy, House Prices and Labor Market Reforms,” IZA Discussion Papers No. 2547, Institute for the Study of Labor (IZA).
- Bernanke, B., 2005, “The Global Saving Glut and the U.S. Current Account Deficit,” remarks presented at the Sandridge Lecture, Virginia Association of Economics (Richmond: Virginia).
- Beyer, A., Doornik, J., Hendry, D.F., 2001, “Constructing Historical Euro-zone Data,” Economic Journal Vol. 111, pp. 308–27.
- Blanchard, O., Galí, J., 2008, “The Macroeconomic Effects of Oil Price Shocks: Why are the 2000s so Different from the 1970s?” Working Paper (MIT: Department of Economics).
- D’Agostino, A., Surico, P., 2009, “Does Global Liquidity Help to Forecast U.S. Inflation?” Journal of Money, Credit, and Banking Vol. 41, pp. 479–89.
- Dreger, C., Wolters, J., 2009, “Liquidity and Asset Prices: How Strong are the Linkages?” Discussion Papers No. 860, DIW Berlin, German Institute for Economic Research.
- Giese, J.V., Tuxen, C.K., 2007, “Global Liquidity and Asset Prices in a Cointegrated VAR,” manuscript.
- Hendry, D.F., 2001, “Modelling U.K. Inflation, 1875–1991.” Journal of Applied Econometrics, Vol. 16, pp. 255–75.
- King, M., 2006, Speech delivered at a dinner for Kent Business Contacts (January 16).
- Matsumoto, A., Schindler, M., 2006, “Global Monetary Conditions and Liquidity: Measurement and Implications,” IMF Research Note (Washington).
- McConnell, M., Perez-Quiros, G., 2000, “Output Fluctuations in the United States; What Has Changed Since the Early 1980s?” American Economic Review, 90–5, December, pp. 1464–76.
- Morgan, Stanley, 2005, “Is Global Excess Liquidity Drying Up?” Global Economic Forum (November 8).
- OECD, 2005, “Recent House Price Developments: The Role of Fundamentals,” Economic Outlook No. 78, Chapter III, pp. 193–234 (Paris).
- Rüffer, R., Stracca, L., 2006, “What is Global Excess Liquidity, and Does it Matter?” ECB Working Paper No. 696 (European Central Bank: Frankfurt).
- Shiller, R., 2005, “Irrational Exuberance,” 2nd ed., Princeton University Press (Princeton: New Jersey).
- Sousa, J.M., Zaghini, A., 2006, “Global Monetary Policy Shocks in the G5: A SVAR Approach,” Working Paper Series 2006/30 (Center for Financial Studies: Frankfurt).
- Taylor, J., 2009, “The Need to Return to a Monetary Framework,” paper presented at the NABE Panel at the AEA Meetings.

### Methodologies and data approaches represented
- VAR and SVAR approaches (cointegrated VAR, SVAR).
- Historical data construction for Euro-zone and long-run inflation series.
- Empirical analysis of liquidity–asset price linkages and forecasting of inflation.
- Policy speeches and discussion pieces providing interpretive frameworks (Sandridge Lecture, NABE Panel).
- Working papers and research notes from central banks and international institutions.

### Implications for research and policy synthesis (as reflected in the cited literature)
- Considerable emphasis on measuring global liquidity and assessing its spillovers to asset prices, housing markets, and commodity prices.
- Use of structural macroeconometric models and time-series techniques to link monetary conditions to real activity and inflation.
- Policy debate on monetary frameworks and the transmission of global monetary shocks across major economies.
- Historical and comparative analyses to understand regime shifts in output fluctuations and inflation dynamics.

*Source: _wp10196 - References (extracted from the supplied PDF content).*

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