## 1. Investment in Plant and Equipment

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---

### I. Introduction: context and objectives
- Japan needs capital accumulation and productivity gains to raise potential growth over the medium term.
- Population is shrinking at about 0.3 percent a year.
- Public debt-to-GDP ratio of about 250 percent implies the fiscal stance needs to remain restrictive over the medium to long term; the pace of consolidation should be measured to balance reducing fiscal risks and maintaining growth and inflation momentum.
- Despite very favorable financial conditions after the launch of Abenomics, the recovery of private investment has remained sluggish.
  - The Bank of Japan embarked on quantitative and qualitative easing in April 2013; Japanese government bond yields declined further and both bank lending rates and corporate bond yields fell to historic lows.
  - Profitability of Japanese firms has improved significantly partly thanks to the sharp yen depreciation.
  - Private investment has not picked up as anticipated.
- Kang (2014) finds that firms’ expectations of demand growth over the medium term is a key determinant for corporate investment, implying weak private investment is partly due to slow progress in structural reforms that has not yet substantially boosted confidence and improved the demand outlook.

### Research questions and methodology
- Research questions:
  - Have there been differences in investment behavior across different types of firms over the past economic cycles?
  - What are main determinants for investment across different types of firms?
  - What has been the impact of a trend increase in production offshoring by Japanese firms on their investment decisions?
- Methodology:
  - Trace investment behavior and financial conditions across different types of firms using corporate survey data.
  - Use firm-level data on listed companies to estimate the standard neoclassical investment model relating investment to expectations of future profitability, cash flow, leverage, and lagged investment.
  - Pay particular attention to potentially different investment behavior of large companies with increased overseas expansion.

### Main findings
- Recovery of private investment after the recent global financial crisis has been slow in both manufacturing and non-manufacturing sectors despite improvement in profitability and liquidity conditions.
- Expectations of future profitability, cash flow, and leverage are all important factors for overall investment behavior of Japanese firms.
- For large firms, particularly those who have expanded abroad for production offshoring, cash flow has been the most important factor behind their investment although they are less liquidity constrained than the others.
- Findings are consistent with recent sluggish recovery of domestic corporate investment despite notable improvement in profitability and large build up of cash holdings.

### Investment trend by different types of firms
- Corporate survey coverage and representativeness
  - Surveys more than 2.7 million firms.
  - Total investment in this survey accounts for about two-thirds of aggregate private non-residential investment in the national accounts.
- Sectoral and cyclical patterns
  - Manufacturing investment more sensitive to cycles than non-manufacturing.
  - After the early-1990s bubble burst, annual average decline of investment for 1990 to 2002 was about 4 percent a year, twice as large as that of non-manufacturing firms.
  - Manufacturing sector share of total investment declined to about 30 percent in the early 2000s from a peak of 45 percent in early 1980s.
  - Mid-2000s global boom: manufacturing investment surged by more than 10 percent a year, twice as much as non-manufacturing.
  - With the global financial crisis, both sectors cut investment by more than 10 percent per year.
- Post-crisis recovery and capacity
  - Real GDP growth remained about 1 percent per annum in the post-crisis period described.
  - Corporate investment broadly flat in both manufacturing and non-manufacturing after crisis.
  - Tankan survey indicates excess capacity in manufacturing sector.
- Profitability and investment co-movement
  - Return on assets (ROA) of overall industry was about 1.5 during booming periods in 1980s and mid-2000s.
  - Return on equity (ROE) was above 5 during those boom periods.
  - After the recent global financial crisis, ROA and ROE over the last 3–4 years are comparable to mid-2000s levels, yet investment remains subdued.
- Leverage, liquidity, and credit
  - Japanese firms paid back about 40 percentage points of GDP in debt over the last 25 years.
  - Leverage ratio (total debt to asset) declined by more than 10 percent in both manufacturing and non-manufacturing over this period.
  - Bank borrowing declined to levels comparable to other advanced economies.
  - Liquidity ratio (average of cash, deposits, and securities to total sales) improved recently after a trend decline.
- Firm size and investment
  - Profitability recovered to pre-crisis levels across all firm sizes.
  - Debt payment burden lower due to lower leverage and interest rates.
  - Investment recovery subdued across all sizes, notably flat for large firms in recent years.
  - Corporate survey firm-size definitions: large firms capital > 1 billion yen; medium firms capital 100 million–1 billion yen; small firms capital 10 million–100 million yen.
- Offshore production and overseas investment
  - Overseas investment grew at a rate of 7 percent in the mid-1990s and 12 percent before the global financial crisis.
  - Overseas investment accounts for about 25 percent of total manufacturing investment.
  - Domestic production capacity declined by about 4 percent since 2011.
  - Transportation sector accounts for more than 60 percent of overseas investment.
  - In 2014, exports by Japanese subsidiaries located overseas (to countries excluding Japan) exceeded exports from Japan by more than 40 percent.
  - Listed-firm sample: less than 5 percent of firms operate overseas (fixed assets abroad over last 5 years) but they account for about 25 percent of total investment in the sample.

### Panel regression with firm-level data — model and data
- Investment model specification
  - I_{i,t}/K_{i,t−1} = c_i + β1 I_{i,t−1}/K_{i,t−2} + β2 Q_{i,t} + β3 CF_{i,t}/K_{i,t−1} + β4 LEV_{i,t} + ε_{i,t}
  - I: capital expenditure.
  - K: capital stock (gross property, plant and equipment less accumulated reserves for depreciation, depletion and amortization).
  - CF: cash flow proxied by post-income tax earnings before depreciation.
  - LEV: leverage ratio calculated by dividing total debt by common equity.
  - Q: (market capitalization + total debt) / total assets.
- Data coverage and sample selection
  - Firm-level data from Worldscope covers more than 5,000 Japanese firms from FY1994 to FY2013.
  - This covers about 55-60 percent of aggregate business investment over this period.
  - Empirical sample horizon: FY1999 to FY2013.
  - Financial sector excluded; estimation includes manufacturing and non-manufacturing firms, reducing sample to about 4,000 firms.
  - For specific analyses, 486 mega firms selected with average capital over sample period exceeding 100 billion yen.
  - In the listed-firm sample, 12 percent of firms (by count) are large firms by the 100 billion yen threshold but account for 85–90 percent of total investment in the sample.
  - Capital expenditure in firm-level database includes domestic and overseas investment; correlation with aggregate domestic business investment is 0.8.

### Empirical results — key findings and coefficients
- Visual correlations (pooled data)
  - Investment-to-capital ratio (I/K) positively correlated with Q, CF/K, and its own lag; negatively correlated with LEV.
- System-GMM estimates — full sample (Table 1, column 1)
  - L.Investment_ratio: 0.192*** (z-statistics (12.878))
  - Q: 0.066*** (9.415)
  - CF: 0.049*** (7.236)
  - LEV: -0.006*** (-3.779)
  - Constant: 0.043*** (8.261)
  - Observations: 41,889
  - Number of ID: 3,933
  - R-squared: 0.2580
- Robustness for positive cash flow subsample (Table 1, column 4)
  - L.Investment_ratio: 0.177*** (10.796)
  - Q: 0.064*** (8.421)
  - CF: 0.048*** (7.418)
  - LEV: -0.004** (-2.473)
  - Observations: 37,832
  - Number of ID: 3,892
  - R-squared: 0.2890
- Manufacturing vs non-manufacturing
  - Manufacturing shows more persistence (higher lag coefficient) and is more constrained by leverage (larger negative LEV coefficient) than non-manufacturing.
- Overseas operation comparison (Table 2)
  - Firms with overseas operations (full sample, positive CF) show:
    - L.Investment_ratio: 0.424*** (5.534)
    - Q: 0.013 (0.556)
    - CF: 0.058*** (6.391)
    - LEV: -0.003 (-0.361)
    - Observations: 2,299
    - Number of ID: 176
    - R-squared: 0.456
  - Firms without overseas operations:
    - Q: 0.065*** (8.022)
  - Post-crisis period for overseas firms:
    - Q = -0.063 (-0.387) for Overseas(Y), Post crisis (full sample).
    - CF = 0.089** (2.324) for Overseas(Y), Post crisis (positive CF).
- Firm size and sectoral heterogeneity (Table 3)
  - Mega firms vs SMEs (full sample, positive CF)
    - Large (mega) firms:
      - Q: 0.030** (1.972)
      - CF: 0.094*** (2.859)
      - L.Investment_ratio: 0.153*** (4.076)
      - Observations: 5,971
      - Number of ID: 484
      - R-squared: 0.3280
    - SME firms:
      - Q: 0.070*** (8.128)
      - CF: 0.044*** (6.772)
      - L.Investment_ratio: 0.168*** (9.881)
      - Observations: 31,861
      - Number of ID: 3,408
      - R-squared: 0.2880
  - Post-crisis, mega firms show Q coefficients that become negative (Q = -0.042* (-1.751)) while CF importance increases (CF = 0.115*** (3.299)).
  - Transportation sector vs other sectors
    - Transportation firms rely more on CF and less on Q than other sectors.
    - Transportation (full sample, positive CF): Q = 0.055*** (3.005), CF = 0.102*** (2.694), Observations: 5,527, R-squared: 0.2710.
    - Transportation (post crisis, positive CF): Q = -0.053* (-1.792), CF = 0.132*** (2.873), Observations: 1,524, R-squared: 0.2580.

### Interpretation of empirical patterns
- Determinants of investment
  - Expectations of future profitability (Q), cash flow (CF), leverage (LEV), and lagged investment all important determinants of investment for overall sample.
- Overseas expansion and Q measurement
  - Firms expanding abroad respond less to Tobin’s Q measured from Japanese stock exchanges; Q may not capture expected profitability from overseas operations because:
    - Only a fraction of overseas profits repatriated to Japan; significant portion reinvested abroad.
    - No good proxy for overseas Q when firms are not listed on foreign exchanges.
  - For firms with overseas operations, cash flow is a stronger determinant of investment than domestic-Q movements.
- Cash flow effect: financing constraint vs internal finance needs
  - Larger CF sensitivity for firms expanding abroad does not necessarily imply tighter financing constraints.
  - Alternative interpretations:
    - Firms need more internal cash or savings to finance riskier overseas investment; external finance may be more costly for overseas projects.
    - Increased reliance on intangible capital raises precautionary demand for cash (intangible capital cannot be pledged as collateral).
  - Abel and Eberly (2011) noted cash flow effects can arise without financing constraints.
- Sectoral and size patterns consistent with offshoring hypothesis
  - Mega firms and transportation-sector firms (responsible for about two-thirds of overseas investment) display weaker Q sensitivity and stronger CF sensitivity, consistent with overseas expansion altering investment behavior.

### Policy implications and conclusions
- Despite improved financial conditions and profitability since Abenomics, corporate investment recovery remained subdued.
- Trend increase in production offshoring contributed importantly to muted domestic investment recovery:
  - Large firms expanding abroad are less responsive to Tobin’s Q measured on Japanese exchanges and more responsive to internal cash flow.
  - This reflects reliance on internal financing for overseas expansion and possible structural shifts (offshoring, intangible capital).
- Implications for policy
  - Structural impediments from production offshoring, along with population aging, could be larger-than-expected drags on domestic investment despite improved financial conditions and sharp yen depreciation.
  - Recommendation: more ambitious structural reforms would be needed to provide a robust long-term outlook and underpin near-term demand.

### Appendix — Lagged Investment: key findings and empirical results
- Purpose: To empirically confirm that lagged investment is a better predictor than Q, CF/K, and LEV for investment (I/K).
- Basic pooled OLS results (Panel A)
  - Regressing I/K on either Q, CF/K, or LEV individually (columns 2 to 4) generates an R-squared of less than 0.15.
  - When Q, CF/K, and LEV are included together (column 5), the goodness-of-fit rises to R-squared = 0.17.
  - Using lagged I/K as the sole explanatory variable (column 1) yields R-squared = 0.22.
  - When all four regressors are present, the coefficient on lagged I/K = 0.35 (large and very highly significant), while coefficients on Q, CF/K, and LEV are highly significant but smaller compared to individual regressions.
- Panel regressions with firm fixed effects (Panel B)
  - Explanatory power of lagged-investment effect is close to that of Q, CF/K, and LEV together: R-squared = 0.44 versus 0.46.
  - When all four variables are included, goodness-of-fit rises marginally to R-squared = 0.48.
  - Coefficients on all variables remain highly significant and close to those in individual regressions.
- System GMM regressions with firm fixed effects (Panel C)
  - The lagged-investment effect remains highly significant even when year dummies are included.
  - The lagged-investment effect is present in both subsamples: FY1999-FY2007 and FY2010-FY2013.
  - The coefficient on lagged I/K remains highly significant when Q, CF/K, and LEV are included.
- Estimation choice for main analysis:
  - Based on these findings, the authors include lagged-investment but no time dummies in regression analysis and report only system GMM estimation results.

*Source: _wp15183 - 1. Investment in Plant and Equipment; Section III and IV text from the provided PDF content unit.*

### 1. Investment in Plant and Equipment ...................................................................................

### 1. Investment in Plant and Equipment

### I. Introduction: context and objectives
- Japan needs capital accumulation and productivity gains to raise potential growth over the medium term.
- Population is shrinking at about 0.3 percent a year.
- Public debt-to-GDP ratio of about 250 percent implies the fiscal stance needs to remain restrictive over the medium to long term; the pace of consolidation should be measured to balance reducing fiscal risks and maintaining growth and inflation momentum.
- Despite very favorable financial conditions after the launch of Abenomics, the recovery of private investment has remained sluggish.
  - The Bank of Japan embarked on quantitative and qualitative easing in April 2013; Japanese government bond yields declined further and both bank lending rates and corporate bond yields fell to historic lows.
  - Profitability of Japanese firms has improved significantly partly thanks to the sharp yen depreciation.
  - Private investment has not picked up as anticipated.
- Kang (2014) finds that firms’ expectations of demand growth over the medium term is a key determinant for corporate investment, implying weak private investment is partly due to slow progress in structural reforms that has not yet substantially boosted confidence and improved the demand outlook.

### Research questions and methodology
- Research questions:
  - Have there been differences in investment behavior across different types of firms over the past economic cycles?
  - What are main determinants for investment across different types of firms?
  - What has been the impact of a trend increase in production offshoring by Japanese firms on their investment decisions?
- Methodology:
  - Trace investment behavior and financial conditions across different types of firms using corporate survey data.
  - Use firm-level data on listed companies to estimate the standard neoclassical investment model relating investment to expectations of future profitability, cash flow, leverage, and lagged investment.
  - Pay particular attention to potentially different investment behavior of large companies with increased overseas expansion.

### Main findings
- Recovery of private investment after the recent global financial crisis has been slow in both manufacturing and non-manufacturing sectors despite improvement in profitability and liquidity conditions.
- Expectations of future profitability, cash flow, and leverage are all important factors for overall investment behavior of Japanese firms.
- For large firms, particularly those who have expanded abroad for production offshoring, cash flow has been the most important factor behind their investment although they are less liquidity constrained than the others.
- Findings are consistent with recent sluggish recovery of domestic corporate investment despite notable improvement in profitability and large build up of cash holdings.

*Source: _wp15183 - 1. Investment in Plant and Equipment (excerpt provided).*

### Section III, we estimate the standard investment model for different types of firms to better

### _wp15183 - Section III, we estimate the standard investment model for different types of firms to better

### Investment trend by different types of firms
- Corporate survey coverage and representativeness
  - Surveys more than 2.7 million firms.
  - Total investment in this survey accounts for about two-thirds of aggregate private non-residential investment in the national accounts.
- Sectoral and cyclical patterns
  - Manufacturing investment more sensitive to cycles than non-manufacturing.
  - After the early-1990s bubble burst, annual average decline of investment for 1990 to 2002 was about 4 percent a year, twice as large as that of non-manufacturing firms.
  - Manufacturing sector share of total investment declined to about 30 percent in the early 2000s from a peak of 45 percent in early 1980s.
  - Mid-2000s global boom: manufacturing investment surged by more than 10 percent a year, twice as much as non-manufacturing.
  - With the global financial crisis, both sectors cut investment by more than 10 percent per year.
- Post-crisis recovery and capacity
  - Real GDP growth remained about 1 percent per annum in the post-crisis period described.
  - Corporate investment broadly flat in both manufacturing and non-manufacturing after crisis.
  - Tankan survey indicates excess capacity in manufacturing sector.
- Profitability and investment co-movement
  - Return on assets (ROA) of overall industry was about 1.5 during booming periods in 1980s and mid-2000s.
  - Return on equity (ROE) was above 5 during those boom periods.
  - After the recent global financial crisis, ROA and ROE over the last 3–4 years are comparable to mid-2000s levels, yet investment remains subdued.
- Leverage, liquidity, and credit
  - Japanese firms paid back about 40 percentage points of GDP in debt over the last 25 years.
  - Leverage ratio (total debt to asset) declined by more than 10 percent in both manufacturing and non-manufacturing over this period.
  - Bank borrowing declined to levels comparable to other advanced economies.
  - Liquidity ratio (average of cash, deposits, and securities to total sales) improved recently after a trend decline.
- Firm size and investment
  - Profitability recovered to pre-crisis levels across all firm sizes.
  - Debt payment burden lower due to lower leverage and interest rates.
  - Investment recovery subdued across all sizes, notably flat for large firms in recent years.
  - Corporate survey firm-size definitions: large firms capital > 1 billion yen; medium firms capital 100 million–1 billion yen; small firms capital 10 million–100 million yen.
- Offshore production and overseas investment
  - Overseas investment grew at a rate of 7 percent in the mid-1990s and 12 percent before the global financial crisis.
  - Overseas investment accounts for about 25 percent of total manufacturing investment.
  - Domestic production capacity declined by about 4 percent since 2011.
  - Transportation sector accounts for more than 60 percent of overseas investment.
  - In 2014, exports by Japanese subsidiaries located overseas (to countries excluding Japan) exceeded exports from Japan by more than 40 percent.
  - Listed-firm sample: less than 5 percent of firms operate overseas (fixed assets abroad over last 5 years) but they account for about 25 percent of total investment in the sample.

### Panel regression with firm-level data — model and data
- Investment model specification (variables preserved as in source)
  - I_{i,t}/K_{i,t−1} = c_i + β1 I_{i,t−1}/K_{i,t−2} + β2 Q_{i,t} + β3 CF_{i,t}/K_{i,t−1} + β4 LEV_{i,t} + ε_{i,t}
  - I: capital expenditure.
  - K: capital stock (gross property, plant and equipment less accumulated reserves for depreciation, depletion and amortization).
  - CF: cash flow proxied by post-income tax earnings before depreciation.
  - LEV: leverage ratio calculated by dividing total debt by common equity.
  - Q: (market capitalization + total debt) / total assets.
- Data coverage and sample selection
  - Firm-level data from Worldscope covers more than 5,000 Japanese firms from FY1994 to FY2013.
  - This covers about 55-60 percent of aggregate business investment over this period.
  - Empirical sample horizon: FY1999 to FY2013.
  - Financial sector excluded; estimation includes manufacturing and non-manufacturing firms, reducing sample to about 4,000 firms.
  - For specific analyses, 486 mega firms selected with average capital over sample period exceeding 100 billion yen.
  - In the listed-firm sample, 12 percent of firms (by count) are large firms by the 100 billion yen threshold but account for 85–90 percent of total investment in the sample.
  - Capital expenditure in firm-level database includes domestic and overseas investment; correlation with aggregate domestic business investment is 0.8.

### Empirical results — key findings and coefficients
- Visual correlations (pooled data)
  - Investment-to-capital ratio (I/K) positively correlated with Q, CF/K, and its own lag; negatively correlated with LEV.
- System-GMM estimates — full sample (Table 1, column 1)
  - L.Investment_ratio: 0.192*** (z-statistics (12.878))
  - Q: 0.066*** (9.415)
  - CF: 0.049*** (7.236)
  - LEV: -0.006*** (-3.779)
  - Constant: 0.043*** (8.261)
  - Observations: 41,889
  - Number of ID: 3,933
  - R-squared: 0.2580
- Robustness for positive cash flow subsample (Table 1, column 4)
  - L.Investment_ratio: 0.177*** (10.796)
  - Q: 0.064*** (8.421)
  - CF: 0.048*** (7.418)
  - LEV: -0.004** (-2.473)
  - Observations: 37,832
  - Number of ID: 3,892
  - R-squared: 0.2890
- Manufacturing vs non-manufacturing (Table 1, columns 2 and 3)
  - Manufacturing shows more persistence (higher lag coefficient) and is more constrained by leverage (larger negative LEV coefficient) than non-manufacturing.
- Overseas operation comparison (Table 2)
  - Firms with overseas operations (full sample, positive CF) show:
    - L.Investment_ratio: 0.424*** (5.534) [column 2]
    - Q: 0.013 (0.556) — small and not statistically significant.
    - CF: 0.058*** (6.391)
    - LEV: -0.003 (-0.361)
    - Observations: 2,299
    - Number of ID: 176
    - R-squared: 0.456
  - Firms without overseas operations:
    - Q: 0.065*** (8.022) — investment positively and significantly associated with Q.
  - Post-crisis period (Table 2, columns 5–6) for overseas firms:
    - Q turns negative though statistically insignificant: Q = -0.063 (-0.387) for Overseas(Y), Post crisis (full sample).
    - CF increases in importance: CF = 0.089** (2.324) for Overseas(Y), Post crisis (positive CF).
- Firm size and sectoral heterogeneity (Table 3)
  - Mega firms vs SMEs (full sample, positive CF)
    - Large (mega) firms:
      - Q: 0.030** (1.972)
      - CF: 0.094*** (2.859)
      - L.Investment_ratio: 0.153*** (4.076)
      - Observations: 5,971
      - Number of ID: 484
      - R-squared: 0.3280
    - SME firms:
      - Q: 0.070*** (8.128)
      - CF: 0.044*** (6.772)
      - L.Investment_ratio: 0.168*** (9.881)
      - Observations: 31,861
      - Number of ID: 3,408
      - R-squared: 0.2880
  - Post-crisis, mega firms show Q coefficients that become negative (Q = -0.042* (-1.751)) while CF importance increases (CF = 0.115*** (3.299)).
  - Transportation sector vs other sectors
    - Transportation firms rely more on CF and less on Q than other sectors (Columns 5–8).
    - Transportation (full sample, positive CF): Q = 0.055*** (3.005), CF = 0.102*** (2.694), Observations: 5,527, R-squared: 0.2710.
    - Transportation (post crisis, positive CF): Q = -0.053* (-1.792), CF = 0.132*** (2.873), Observations: 1,524, R-squared: 0.2580.

### Interpretation of empirical patterns
- Determinants of investment
  - Expectations of future profitability (Q), cash flow (CF), leverage (LEV), and lagged investment all important determinants of investment for overall sample.
- Overseas expansion and Q measurement
  - Firms expanding abroad respond less to Tobin’s Q measured from Japanese stock exchanges; Q may not capture expected profitability from overseas operations because:
    - Only a fraction of overseas profits repatriated to Japan; significant portion reinvested abroad.
    - No good proxy for overseas Q when firms are not listed on foreign exchanges.
  - For firms with overseas operations, cash flow is a stronger determinant of investment than domestic-Q movements.
- Cash flow effect: financing constraint vs internal finance needs
  - Larger CF sensitivity for firms expanding abroad does not necessarily imply tighter financing constraints.
  - Alternative interpretations:
    - Firms need more internal cash or savings to finance riskier overseas investment; external finance may be more costly for overseas projects.
    - Increased reliance on intangible capital raises precautionary demand for cash (intangible capital cannot be pledged as collateral).
  - Abel and Eberly (2011) noted cash flow effects can arise without financing constraints.
- Sectoral and size patterns consistent with offshoring hypothesis
  - Mega firms and transportation-sector firms (responsible for about two-thirds of overseas investment) display weaker Q sensitivity and stronger CF sensitivity, consistent with overseas expansion altering investment behavior.

### Policy implications and conclusions
- Despite improved financial conditions and profitability since Abenomics, corporate investment recovery remained subdued.
- Trend increase in production offshoring contributed importantly to muted domestic investment recovery:
  - Large firms expanding abroad are less responsive to Tobin’s Q measured on Japanese exchanges and more responsive to internal cash flow.
  - This reflects reliance on internal financing for overseas expansion and possible structural shifts (offshoring, intangible capital).
- Implications for policy
  - Structural impediments from production offshoring, along with population aging, could be larger-than-expected drags on domestic investment despite improved financial conditions and sharp yen depreciation.
  - Recommendation: more ambitious structural reforms would be needed to provide a robust long-term outlook and underpin near-term demand.

*Italic: Source — Section III and IV text from the provided PDF content unit.*

### REFERENCES

### _wp15183 - REFERENCES

### References
- Abel, A. B. and J. C. Eberly, 2011, “How Q and cash flow affect investment without frictions: an analytic explanation,” Review of Economic Studies 78 (4): 1179-1200.
- Allayannis, G., and A. Mozumdar, 2001, “The investment-cash flow sensitivity puzzle: can negative cash flow observations explain it?” Virginia Tech Working Paper 98-5.
- Aslam A., S. Beidas-Strom, D. Leigh, S. G. Park, and H. Tong, 2015 “Private investment: what’s the holdup?,” Chapter 3 in World Economic Outlook (April) (Washington: International Monetary Fund).
- Botman, D. and J. S. Kang, 2015, “Japan’s Role in the Global Economy and Spillover Effects of Abenomics,” Chapter 10 in Can Abenomics Succeed? Overcoming the Legacy of the Lost Decades, D. Botman, S. Danninger, and J Schiff and eds. (Washington: International Monetary Fund).
- Bloom, N., S. Bond, and J. Van Reenen, 2007, “Uncertainty and Investment Dynamics” Review of Economic Studies 74, 391–415.
- Christiano, L., Eichenbaum, M., Evans, C., 2005, “Nominal rigidities and the dynamic effects of a shock to monetary policy,” Journal of Political Economy 113: 1–45.
- Eberly J., S. Rebelo, and N. Vincent, 2012, “What explains the lagged-investment effect?” Journal of Monetary Economics 59: 370-380.
- Falato, A., D. Kadyrzhanova, and J. W. Sim, 2013, “Rising intangible capital, shrinking debt capacity, and the US corporate savings glut,” Federal Reserve Board Finance and Economics Discussion Series 2013-67.
- Fazzari, S., G. Hubbard, and B. Petersen, 1988, “Financing constraints and corporate investment,” Brookings Papers on Economic Activity 141–195.
- Hayashi, F., 1982, “Tobin’s marginal Q and average Q: a neoclassical interpretation,” Econometrica 50: 215–224.
- Hubbard, R.G., 1998, “Capital-market imperfections and investment,” Journal of Economic Literature 36:193–225.
- International Monetary Fund, 2011, “Japan: Spillover Report,” IMF Country Report No. 11/183.
- Guimarães-Filho R., S. Piao, and L. Zhang, 2014, “Corporate leverage in Asia: a fault line?” Chapter 2 in Regional Economic Outlook: Asia and Pacific (Washington: International Monetary Fund).
- Kang, J. S., 2014, “How to raise private non-residential investment in Japan?,” IMF WP 14/141 (Washington: International Monetary Fund).
- Kang, J. S., 2015a, “Stimulating Private Investment and Innovation,” Chapter 9 in Can Abenomics Succeed? Overcoming the Legacy of the Lost Decades, D. Botman, S. Danninger, and J Schiff and eds. (Washington: International Monetary Fund).
- Kang, J. S., 2015b, “What explains Japan’s export sluggishness?” Box 1 in “Japan: Staff Report for the 2015 Article IV Consultation, forthcoming IMF Country Report.
- Kang, W., K. Lee, and R. A. Ratti, 2014, “Economic policy uncertainty and firm-level investment,” Journal of Macroeconomics 39: 42-53.
- McGuire, P. M, 2003, “Bank ties and bond market access: evidence on investment-cash flow sensitivity in Japan,” BIS Working Papers No. 151 (Bank for International Settlements).
- Syed, M. and J. Lee, 2010, “Japan’s Quest for Growth: Exploring the Role of Capital and Innovation,” IMF Working Paper, WP/10/294 (Washington: International Monetary Fund).

### Appendix. Lagged Investment — key findings and empirical results
- Purpose: To empirically confirm that lagged investment is a better predictor than Q, CF/K, and LEV for investment (I/K).
- Basic pooled OLS results (Panel A):
  - Regressing I/K on either Q, CF/K, or LEV individually (columns 2 to 4) generates an R-squared of less than 0.15.
  - When Q, CF/K, and LEV are included together (column 5), the goodness-of-fit rises to R-squared = 0.17.
  - Using lagged I/K as the sole explanatory variable (column 1) yields R-squared = 0.22.
  - When all four regressors are present, the coefficient on lagged I/K = 0.35 (large and very highly significant), while coefficients on Q, CF/K, and LEV are highly significant but smaller compared to individual regressions.
- Panel regressions with firm fixed effects (Panel B):
  - Explanatory power of lagged-investment effect is close to that of Q, CF/K, and LEV together: R-squared = 0.44 versus 0.46.
  - When all four variables are included, goodness-of-fit rises marginally to R-squared = 0.48.
  - Coefficients on all variables remain highly significant and close to those in individual regressions.
- System GMM regressions with firm fixed effects (Panel C):
  - The lagged-investment effect remains highly significant even when year dummies are included (column 3).
  - The lagged-investment effect is present in both subsamples: FY1999-FY2007 and FY2010-FY2013 (columns 4 and 5).
  - The coefficient on lagged I/K remains highly significant when Q, CF/K, and LEV are included (column 2).
- Estimation choice for main analysis:
  - Based on these findings, the authors include lagged-investment but no time dummies in regression analysis and report only system GMM estimation results.

### Table A1 — selected coefficient estimates and statistics
- Panel A: pooled OLS (columns 1–6)
  - VARIABLES (column ordering corresponds to table)
  - L.Investment_ratio: 0.444*** (t = 41.862) in column (1); 0.344*** (t = 27.633) in column (2)
  - Q: 0.118*** (t = 29.856) in column (2); 0.082*** (t = 20.599) in column (3); 0.049*** (t = 15.534) in column (4)
  - CF: 0.055*** (t = 23.875) in column (2); 0.042*** (t = 16.443) in column (3); 0.032*** (t = 14.110) in column (4)
  - LEV: -0.010*** (t = -9.505) in column (2); -0.005*** (t = -6.025) in column (3); -0.003*** (t = -5.651) in column (4)
  - Constant values by column: 0.087*** (t = 45.329), 0.063*** (t = 22.090), 0.133*** (t = 74.508), 0.175*** (t = 68.173), 0.075*** (t = 26.565), 0.048*** (t = 20.658)
  - Observations by column: 45,176; 46,318; 46,121; 47,142; 43,913; 41,889
  - R-squared by column: 0.220; 0.098; 0.147; 0.005; 0.167; 0.290
- Panel B: panel regressions with firm fixed effects (columns 1–6)
  - L.Investment_ratio: 0.080*** (t = 6.881) in column (1); 0.087*** (t = 6.971) in column (2)
  - Q: 0.060*** (t = 13.845) in column (2); 0.047*** (t = 10.010) in column (3); 0.042*** (t = 9.664) in column (4)
  - CF: 0.041*** (t = 15.535) in column (2); 0.036*** (t = 11.460) in column (3); 0.037*** (t = 10.894) in column (4)
  - LEV: -0.009*** (t = -6.609) in column (2); -0.005*** (t = -3.811) in column (3); -0.004*** (t = -3.512) in column (4)
  - Constant values by column: 0.147*** (t = 76.436), 0.108*** (t = 31.392), 0.140*** (t = 111.865), 0.174*** (t = 144.777), 0.105*** (t = 28.594), 0.092*** (t = 22.813)
  - Observations by column: 45,176; 46,318; 46,121; 47,142; 43,913; 41,889
  - R-squared by column: 0.443; 0.434; 0.463; 0.439; 0.464; 0.477
  - Number of ID: 4,009; 3,997; 3,999; 4,021; 3,964; 3,933
- Panel C: system GMM regressions with firm fixed effects (columns 1–5)
  - L.Investment_ratio: 0.207*** (t = 12.505) in column (1); 0.192*** (t = 12.878) in column (2); 0.176*** (t = 12.323) in column (3); 0.196*** (t = 9.801) in column (4); 0.139*** (t = 5.854) in column (5)
  - Q: 0.066*** (t = 9.415) in column (1); 0.072*** (t = 7.548) in column (2); 0.053*** (t = 6.923) in column (3); 0.053*** (t = 3.314) in column (4)
  - CF: 0.049*** (t = 7.236) in column (1); 0.051*** (t = 7.638) in column (2); 0.067*** (t = 5.848) in column (3); 0.049*** (t = 5.398) in column (4)
  - LEV: -0.006*** (t = -3.779) in column (1); -0.006*** (t = -3.629) in column (2); -0.004*** (t = -2.931) in column (3); -0.031*** (t = -4.281) in column (4)
  - Constant values by column: 0.114*** (t = 37.096), 0.043*** (t = 8.261), 0.275 (t = 0.489), 0.053*** (t = 8.186), 0.071*** (t = 5.658)
  - Observations by column: 45,176; 41,889; 41,889; 24,309; 11,498
  - Number of ID: 4,009; 3,933; 3,933; 3,650; 3,261
  - Sample periods by column: FY1999-FY2013; FY1999-FY2013; FY1999-FY2013; FY1999-FY2007; FY2010-FY2013
  - Time dummies: No; No; Yes; No; No

- Statistical significance notation: *** p<0.01, ** p<0.05, * p<0.1
- Note: Robust t-statistics or z-statistics are reported in parentheses.

*Source: _wp15183 - REFERENCES*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2015/_wp15183.pdf_