## REFERENCES and ANNEX TABLES (wp18139)

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### References section overview
- Contains the "REFERENCES" section as indicated on page 27.
- Purpose: Provides the bibliographic foundation for the working paper's analysis to allow verification of cited studies, data sources, and methodological references.
- Note: Actual bibliographic entries for the full references section are provided in the supplied content (see "Citations" below).

### Annex Table 1 (page 30)
- Title: ANNEX TABLE 1.
- Likely content: Tabulated data or supplementary material referenced in the main text.
- Note: Annex Table 1 is referenced as "Jorgenson and Siebert Model (1998-2014): Regression Coefficients" with source "Author’s estimates." Actual table contents are not included in the supplied excerpt.

### Annex Table 2 (page 31) — summary and key findings
- Purpose: Describes variables used in the empirical analysis and provides definitions, sources, codes, providers, frequency, and transformations.
- Context from the working paper (main conclusions summarized in Annex Table 2 text):
  - Main finding: Post-crisis U.S. business investment "has not behaved unusually but been in line with what weak expected demand growth suggested," with the marked decline in global oil prices further weighing on oil and gas investment between 2014 and end-2016.
  - Paper structure: stylized facts (Section II); macroeconomic, financial, and political factors (Sections III–V); Bayesian model averaging and joint predictive assessment (Section VI).

- Stylized facts about U.S. business investment:
  - Private fixed investment (PFI) measures additions to and replacements of the U.S. capital stock of private fixed assets.
  - Total nonresidential private fixed investment (NPFI) now constitutes 13 percent of GDP.
  - Investment in structures fell from 65 percent of NPFI in the late 1960s to 21 percent by end 2016.
  - Since the 1980s, structures lost importance while equipment and IP took larger shares.
  - Equipment and structures are highly cyclical; IP is relatively immune to cyclical swings.
  - Between end-2007 and mid-2009, equipment investment dropped by 30 percent, then rebounded by more than 40 percent until end-2015.
  - In 2016, investment growth weakened, derailing the post-GFC investment recovery.
  - Structures investment appears to have taken a permanent hit and never fully recovered.
  - IP continued to grow in line with its pre-crisis trajectory.
  - Since fall 2010, the labor market experienced the longest consecutive job creation on record while business investment became considerably more volatile relative to employment growth.
  - Nonresidential investment in advanced countries dropped 10-25 percent during the GFC.

- Macroeconomic factors:
  - The Jorgenson and Siebert accelerator model finds aggregate demand growth explains 97 percent of the variation in NPFI.
  - The basic accelerator model suggested the GFC drop in investment was in line with weak aggregate demand, but during 2015-2016 actual investment surprised on the downside.
  - The investment gap (projected minus actual business investment) averaged 4.1 percent over the three-year period 2015-2018.
  - The lion's share of the investment gap was due to weak equipment investment; average equipment investment gap during 2015-2017 was around 8 percent.
  - For IP, the accelerator model identifies an investment gap of around 5 percent on average.
  - Structures investment is less well explained by the basic accelerator model (R2 of only 68 percent).
  - The relative price of investment goods has fallen steadily; adding it to the accelerator model explains more than 1 additional percent of the variation in NPFI.
  - Annual oil and gas investment dropped from its 2014 peak of almost USD 200 million to considerably below USD 100 million; companies lowered capital expenditures by about 40 percent.
  - Exploration-firm leverage rose from a little over 20 percent to as high as 60 percent during 2015-2016; leverage remained elevated in 2017.
  - Volatility of Oil and gas ETFs increased from 15 to almost 40 index points.
  - Replacing actual GDP growth with the consensus one-year ahead GDP forecast reduces by about half the 2015-2016 investment gap estimated from the Jorgenson and Siebert model.
  - Adding "manufacturing and trade sales" and "manufacturers' new orders" (demand proxies) essentially eliminates the investment gap and raises adjusted R2 by 2 percentage points relative to the basic model.
  - Including the exchange rate or oil price does not improve the basic model fit substantially.
  - The level of interest rates (federal funds rate) and the oil price level marginally improve explanatory power but do not explain recent NPFI behavior.

- Financial factors:
  - Post-GFC, net payouts have averaged 2.7 percent of total assets, an increase of 50 percent compared to the pre-GFC period.
  - Share repurchases grew substantially since the 1990s after regulatory easing (Securities Exchange Act, Rule 10b-18) and wider use of stock options.
  - Bank lending standards after the crisis have been very loose by historical standards; a net tightening of lending standards was reported only during 2015-2016.
  - U.S. corporates generally enjoyed favorable debt market conditions; yields for AAA-rated firms were low relative to High Yield.
  - High Yield corporate bonds experienced a sharp spike in yields during the oil and gas stress; by mid-2017 High Yield yields came down to around 10 percent.
  - Debt market funding problems were pronounced for some high yield companies, particularly in the U.S. oil and gas sector.
  - Adding a broad financial conditions index does not improve the accelerator model nor explain NPFI during 2015-2017.
  - Adding equity market valuations (Russell 1000 Total Return Index) improves the fit (R2 above 98 percent in augmented specifications) and can explain around a quarter of the recent investment gap.
  - The VIX does not improve the accelerator fit.
  - Corporate profits improve the model generally but do not explain NPFI behavior over the past three years.
  - Bank credit supply/demand measures and high yield spreads do not appear to have driven recent aggregate NPFI.

- Political economy factors:
  - High uncertainty theorized to induce firms to delay irreversible investment and hiring (Bernanke, 1983).
  - Measures of economic policy uncertainty, dispersion in SPF forecasts, and partisan conflict do not improve the explanatory power of the basic accelerator model for NPFI.
  - Consumer sentiment marginally improves model fit; positive consumer sentiment supports expansion of business investment.
  - Partisan conflict may lower investment for firms that rely on government spending or engage in political campaigns, but political conflict is not identified as a key determinant of aggregate business investment in combination with traditional macro and financial factors.

- Bayesian Model Averaging (BMA) findings:
  - Estimation window: models estimated over 1983Q4-2014Q4; out-of-sample forecasts from 2015Q1 to 2017Q4 (12 quarters).
  - Oil and gas investment excluded from aggregate NPFI to produce non-oil and gas NPFI.
  - Relative price of investment (Rel. Price) positively impacts business investment.
  - Oil price (Oil price) and exchange rate (FX rate) have posterior probabilities of 100 percent and negative coefficients.
  - Total real manufacturing and trade sales (Sales) and manufacturers' new orders (New orders) have significant and large impacts as demand proxies.
  - Changes in the federal funds rate (Δ Fed Funds Rate) have a negative impact, suggesting rate hikes indicate higher future debt financing cost that reduces available internal funding.
  - Rich equity valuations (Russell 1000 Total Return Index) and high firm profits (Profits) predict stronger future business investment.
  - Corporate bond spreads (BAA-10Y) do not have an economically significant influence.
  - Other financial candidates (equity market volatility, bank credit supply/demand, high yield spreads) are neither identified as relevant nor economically significant drivers.
  - Economic policy uncertainty indices and SPF dispersion are not relevant stand-alone factors for NPFI.
  - Political conflict index (Polit. Conflict Idx) is not identified as a key determinant in combination with other variables.
  - Consumer sentiment (Cons. sent.) has a positive effect consistent with demand expectations.
  - The BMA model essentially explains the entirety of non-oil NPFI behavior during 2015-2017, with an average investment gap of zero.
  - Conclusion: aggregate demand growth expectations, corporate profits, and equity valuations account for observed business investment behavior; special factors (policy uncertainty, political conflict, financial frictions) play limited or no roles in explaining the aggregate investment gap.

### Citations (selected references included in the supplied content)
- Arif, Salman and Charles M.C. Lee. 2014. "Aggregate Investment and Investor Sentiment." The Review of Financial Studies, Vol. 27 (11), p. 3241–3279.
- Azzimonti, Marina. 2018. "Partisan Conflict and Private Investment." Journal of Monetary Economics, Vol. 23, p. 114-131.
- Baker, Scott and Nicholas Bloom. 2013. "Does Uncertainty Reduce Growth? Using Disasters as Natural Experiments." NBER Working Papers, No. 19475, NBER, Inc.
- Baker, Scott, Nicholas Bloom, and Steven Davis. 2016. "Measuring Economic Policy Uncertainty." Quarterly Journal of Economics, Vol 131 (4), p. 1593-1636.
- Banerjee, Ryan, Jonathan Kearns and Marco Lombardi, 2015. "(Why) Is Investment Weak?" in: BIS Quarterly Review, March 2015, Bank for International Settlements (BIS).
- Bernanke, Ben. 1983. "Irreversibility, Uncertainty and Cyclical Investment." Quarterly Journal of Economics, Vol. 97 (1983), p. 85–106.
- Bloom, Nicholas. 2009. "The Impact of Uncertainty Shocks." Econometrica, Vol. 77, p. 623–685.
- Bureau of Economic Analysis (BEA). 2017. "Private Fixed Investment." In: NIPA Handbook, Chapter 6.
- Campello, Murillo, John Graham, and Campbell Harvey. 2010. "The Real Effects of Financial Constraints: Evidence from a Financial Crisis." Journal of Financial Economics, Vol. 97 (3), p. 470-487.
- Gilchrist, Simon and Egon Zakrajsek. 2012. "Credit Spreads and Business Cycle Fluctuations." American Economic Review, Vol. 102 (4), p. 1692-1720.
- IMF. 2015. "Private Investment: What's the Holdup?" In: IMF World Economic Outlook, April 2015.
- Jorgenson, Dale and Calvin Siebert. 1968. "A Comparison of Alternative Theories of Corporate Investment Behavior." American Economic Review, Vol. 58 (4). p. 681-712.
- Raftery, Adrian, Jennifer Hoeting, Chris Volinsky, Ian Painter, and Ka Yee Yeung. 2018. "Package BMA." Version 3.18.8, CRAN depository, March 22, 2018.
- S&P Capital. 2014. "Buying Outperformance: Do Share Repurchase Announcements Lead to Higher Returns?" Quantamental Research, January 2014. S&P Capital IQ.

### Annex Table 2 — variable list (selected entries)
- Aggregate demand; output; GDP
  - Variable name: Real Gross Domestic Product (Bil.Chn.2009$)
  - Source: BEA /1
  - Code: GDPHA@USECON
  - Provider: Haver
  - Frequency: quarterly
  - Transformation: log idx, log diff
- Bank lending standards
  - Variable name: Net Percentage of Domestic Banks Tightening Standards for Commercial and Industrial Loans for Large and Middle-Market Firms
  - Source: Fed Board /2
  - Code: DRTSCILM
  - Provider: FRED
  - Frequency: quarterly
  - Transformation: none
- Capital stock: Nonresidential private fixed assets (NPFA)
  - Variable name: Real Net Stock: Private Fixed Nonresidential Assets (Bil.Chn.2009$)
  - Source: BEA
  - Code: EPNH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Consensus one-year ahead GDP growth forecast
  - Variable name: Survey of Professional Forecasters (SPF) 4-quarters ahead PGDP forecast, mean
  - Source: SPF /3
  - Code: dpgdp4
  - Provider: SPF
  - Frequency: quarterly
  - Transformation: none
- Consumer sentiment
  - Variable name: University of Michigan: Consumer sentiment
  - Source: University of Michigan
  - Code: UMCSENT
  - Provider: FRED
  - Frequency: monthly
  - Transformation: log idx
- Depreciation: NPFA
  - Variable name: Depreciation: Private Nonresidential Fixed Assets (Bil.Chn.2009$)
  - Source: BEA
  - Code: KPNH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Equity valuations
  - Variable name: Russell 1000® Total Market Index, index
  - Source: FTSE Russell
  - Code: RU1000TR
  - Provider: FRED
  - Frequency: daily
  - Transformation: log idx
- FX rate
  - Variable name: Real Trade-Weighted Exch Value of US$ vs Major Currencies (Mar-73=100)
  - Source: Federal Reserve Board
  - Code: FXTWMC
  - Provider: Haver
  - Frequency: daily
  - Transformation: log idx
- High yield (corporate) spread
  - Variable name: ICE BofAML US High Yield Master II Option-Adjusted Spread
  - Source: ICE/BofAML
  - Code: BAMLH0A0HYM2
  - Provider: FRED
  - Frequency: daily
  - Transformation: none
- Net capital stock: Equipment, oil and gas extraction
  - Variable name: Net Stock: Private Equipment: Oil and Gas Extraction (Hist.Cost, Bil.$)
  - Source: BEA
  - Code: EPPB1ET@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- NPFI: Oil and gas extraction
  - Variable name: Investment: Pvt Fxd Assets: Oil and Gas Extraction (Hist.Cost, Bil.$)
  - Source: BEA
  - Code: ZPPB1T@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Oil price
  - Variable name: Global price of WTI Crude
  - Source: IMF
  - Code: POILWTIUSDQ
  - Provider: FRED
  - Frequency: quarterly
  - Transformation: log idx
- Relative price of investment
  - Variable name: Relative price of investment goods (investment to consumption deflator)
  - Source: Federal Reserve
  - Code: PIRIC
  - Provider: FRED
  - Frequency: quarterly
  - Transformation: none
- VIX
  - Variable name: CBOE Volatility Index: VIX
  - Source: CBOE
  - Code: VIXCLS
  - Provider: FRED
  - Frequency: daily
  - Transformation: log idx

*Source: wp18139 - REFERENCES ___________________________________________________________________________________ 27; ANNEX TABLE 1 __________________________________________________________________________________ 30; ANNEX TABLE 2 __________________________________________________________________________________ 31*

### REFERENCES ___________________________________________________________________________________ 27

### REFERENCES ___________________________________________________________________________________ 27

### References
- This content unit contains the "REFERENCES" section as indicated on page 27.
- The section lists bibliographic sources cited in the associated working paper (content of the references is not provided in the supplied input).

### Purpose and content notes
- Provides the bibliographic foundation for the working paper's analysis.
- Intended to allow verification of cited studies, data sources, and methodological references (actual entries not included in the supplied excerpt).

### ANNEX TABLE 1 __________________________________________________________________________________ 30

### Annex Table 1
- An annex labeled "ANNEX TABLE 1" is present on page 30.
- The annex likely contains tabulated data or supplementary material referenced in the main text (actual table contents are not provided in the supplied input).

*Source: wp18139 - REFERENCES ___________________________________________________________________________________ 27; ANNEX TABLE 1 __________________________________________________________________________________ 30*

### ANNEX TABLE 2 __________________________________________________________________________________ 31

### wp18139 - ANNEX TABLE 2 __________________________________________________________________________________ 31

### Introduction
- Main finding: post-crisis U.S. business investment "has not behaved unusually but been in line with what weak expected demand growth suggested," with the marked decline in global oil prices further weighing on oil and gas investment between 2014 and end-2016.
- Paper structure: stylized facts (Section II); macroeconomic, financial, and political factors (Sections III–V); Bayesian model averaging and joint predictive assessment (Section VI).

### Stylized facts about U.S. business investment
- Definition: Private fixed investment (PFI) measures additions to and replacements of the U.S. capital stock of private fixed assets.
- Composition and shares:
  - Total nonresidential private fixed investment (NPFI) now constitutes 13 percent of GDP.
  - Investment in structures fell from 65 percent of NPFI in the late 1960s to 21 percent by end 2016.
  - Since the 1980s, structures lost importance while equipment and IP took larger shares.
- Cyclicality:
  - Equipment and structures are highly cyclical; IP is relatively immune to cyclical swings.
- Crisis and recovery dynamics:
  - Between end-2007 and mid-2009, equipment investment dropped by 30 percent, then rebounded by more than 40 percent until end-2015.
  - In 2016, investment growth weakened, derailing the post-GFC investment recovery.
  - Structures investment appears to have taken a permanent hit and never fully recovered.
  - IP continued to grow in line with its pre-crisis trajectory.
- Labor market vs. investment:
  - Since fall 2010, the labor market experienced the longest consecutive job creation on record while business investment became considerably more volatile relative to employment growth.
- International context:
  - Nonresidential investment in advanced countries dropped 10-25 percent during the GFC.

### Macroeconomic factors
- Accelerator model fit:
  - The Jorgenson and Siebert accelerator model finds aggregate demand growth explains 97 percent of the variation in NPFI.
  - The basic accelerator model suggested the GFC drop in investment was in line with weak aggregate demand, but during 2015-2016 actual investment surprised on the downside.
  - The investment gap (projected minus actual business investment) averaged 4.1 percent over the three-year period 2015-2018.
- Component gaps:
  - The lion's share of the investment gap was due to weak equipment investment; average equipment investment gap during 2015-2017 was around 8 percent.
  - For IP, the accelerator model identifies an investment gap of around 5 percent on average.
  - Structures investment is less well explained by the basic accelerator model (R2 of only 68 percent).
- Relative price and depreciation:
  - The relative price of investment goods has fallen steadily, indicating technological progress reduced the price of investment goods.
  - The falling relative price of investment explains more than 1 additional percent of the variation in NPFI when added to the accelerator model.
- Oil and gas sector:
  - Annual oil and gas investment dropped from its 2014 peak of almost USD 200 million to considerably below USD 100 million; companies lowered capital expenditures by about 40 percent.
  - Exploration-firm leverage rose from a little over 20 percent to as high as 60 percent during 2015-2016; leverage remained elevated in 2017.
  - Volatility of Oil and gas ETFs increased from 15 to almost 40 index points.
- Forward-looking accelerator:
  - Replacing actual GDP growth with the consensus one-year ahead GDP forecast reduces by about half the 2015-2016 investment gap estimated from the Jorgenson and Siebert model.
  - The forward-looking model aligns investment better with expectations of future growth, though the richer 12-lag specification of the Jorgenson/Siebert model fits better over the full estimation window.
- Augmented accelerator with macro variables:
  - Adding "manufacturing and trade sales" and "manufacturers' new orders" (demand proxies) essentially eliminates the investment gap and raises adjusted R2 by 2 percentage points relative to the basic model.
  - Including the exchange rate or oil price does not improve the basic model fit substantially.
  - The level of interest rates (federal funds rate) and the oil price level marginally improve explanatory power but do not explain recent NPFI behavior.

### Financial factors
- Corporate payouts and buybacks:
  - Post-GFC, net payouts have averaged 2.7 percent of total assets, an increase of 50 percent compared to the pre-GFC period.
  - Share repurchases grew substantially since the 1990s after regulatory easing (Securities Exchange Act, Rule 10b-18) and wider use of stock options.
- Credit supply and cost:
  - Bank lending standards after the crisis have been very loose by historical standards; a net tightening of lending standards was reported only during 2015-2016.
  - U.S. corporates generally enjoyed favorable debt market conditions; yields for AAA-rated firms were low relative to High Yield.
  - High Yield corporate bonds experienced a sharp spike in yields during the oil and gas stress; by mid-2017 High Yield yields came down to around 10 percent.
- Sector-specific funding stress:
  - Debt market funding problems were pronounced for some high yield companies, particularly in the U.S. oil and gas sector.
- Augmented accelerator with financial variables:
  - Adding a broad financial conditions index does not improve the accelerator model nor explain NPFI during 2015-2017.
  - Adding equity market valuations (Russell 1000 Total Return Index) improves the fit (R2 above 98 percent in augmented specifications) and can explain around a quarter of the recent investment gap.
  - The VIX (implied equity market volatility) does not improve the accelerator fit.
  - Corporate profits improve the model generally but do not explain NPFI behavior over the past three years.
  - Bank credit supply/demand measures and high yield spreads do not appear to have driven recent aggregate NPFI.

### Political economy factors
- Uncertainty and investment:
  - Theoretical work (Bernanke, 1983) suggests high uncertainty induces firms to delay irreversible investment and hiring.
  - Measures of economic policy uncertainty (Bloom, 2009; Baker and others, 2016), dispersion in SPF forecasts, and partisan conflict do not improve the explanatory power of the basic accelerator model for NPFI.
  - Consumer sentiment marginally improves model fit; positive consumer sentiment supports expansion of business investment, likely reflecting expectations of accelerating aggregate demand.
- Political conflict and targeted effects:
  - Partisan conflict may lower investment for firms that rely on government spending or engage in political campaigns, but political conflict is not identified as a key determinant of aggregate business investment in combination with traditional macro and financial factors.

### Bayesian Model Averaging (BMA) findings
- Estimation setup:
  - Models estimated over 1983Q4-2014Q4; out-of-sample forecasts from 2015Q1 to 2017Q4 (12 quarters).
  - Oil and gas investment excluded from aggregate NPFI to produce non-oil and gas NPFI.
- Key BMA results:
  - Relative price of investment (Rel. Price) positively impacts business investment.
  - Oil price (Oil price) and exchange rate (FX rate) have posterior probabilities of 100 percent and negative coefficients.
  - Total real manufacturing and trade sales (Sales) and manufacturers' new orders (New orders) have significant and large impacts as demand proxies.
  - Changes in the federal funds rate (Δ Fed Funds Rate) have a negative impact, suggesting rate hikes indicate higher future debt financing cost that reduces available internal funding.
  - Rich equity valuations (Russell 1000 Total Return Index) and high firm profits (Profits) predict stronger future business investment.
  - Corporate bond spreads (BAA-10Y) do not have an economically significant influence.
  - Other financial candidates (equity market volatility, bank credit supply/demand, high yield spreads) are neither identified as relevant nor economically significant drivers.
  - Economic policy uncertainty indices and SPF dispersion are not relevant stand-alone factors for NPFI.
  - Political conflict index (Polit. Conflict Idx) is not identified as a key determinant in combination with other variables.
  - Consumer sentiment (Cons. sent.) has a positive effect consistent with demand expectations.
- BMA predictive performance:
  - The BMA model essentially explains the entirety of non-oil NPFI behavior during 2015-2017, with an average investment gap of zero.
  - Conclusion: aggregate demand growth expectations, corporate profits, and equity valuations account for observed business investment behavior; special factors (policy uncertainty, political conflict, financial frictions) play limited or no roles in explaining the aggregate investment gap.

*Source: wp18139 - ANNEX TABLE 2 (text supplied).*

### REFERENCES

### REFERENCES

### Citations
- Arif, Salman and Charles M.C. Lee. 2014. "Aggregate Investment and Investor Sentiment." The Review of Financial Studies, Vol. 27 (11), p. 3241–3279.
- Azzimonti, Marina. 2018. "Partisan Conflict and Private Investment." Journal of Monetary Economics, Vol. 23, p. 114-131.
- Baker, Scott and Nicholas Bloom. 2013. "Does Uncertainty Reduce Growth? Using Disasters as Natural Experiments." NBER Working Papers, No. 19475, NBER, Inc.
- Baker, Scott, Nicholas Bloom, and Steven Davis. 2016. "Measuring Economic Policy Uncertainty." Quarterly Journal of Economics, Vol 131 (4), p. 1593-1636.
- Banerjee, Ryan, Jonathan Kearns and Marco Lombardi, 2015. "(Why) Is Investment Weak?" in: BIS Quarterly Review, March 2015, Bank for International Settlements (BIS).
- Bernanke, Ben. 1983. "Irreversibility, Uncertainty and Cyclical Investment." Quarterly Journal of Economics, Vol. 97 (1983), p. 85–106.
- Bloom, Nicholas. 2009. "The Impact of Uncertainty Shocks." Econometrica, Vol. 77, p. 623–685.
- Bloom, Nicholas. 2014. "Fluctuations in Uncertainty." Journal of Economic Perspectives, Vol. 28 (2), p. 153-176.
- Bureau of Economic Analysis (BEA). 2017. "Private Fixed Investment." In: NIPA Handbook, Chapter 6.
- Campello, Murillo, John Graham, and Campbell Harvey. 2010. "The Real Effects of Financial Constraints: Evidence from a Financial Crisis." Journal of Financial Economics, Vol. 97 (3), p. 470-487.
- Cochrane, John. 1991. "Production‐Based Asset Pricing and the Link Between Stock Returns and Economic Fluctuations." Journal of Finance, Vol. 46 (1), p. 209-237.
- Fragoso, Tiago, Wesley Bertoli, and Francisco Louzada. 2017. "Bayesian Model Averaging: A Systematic Review and Conceptual Classification." International Statistical Review, Vol. 86 (1), April 2018, p. 1-28.
- Gilchrist, Simon and Egon Zakrajsek. 2012. "Credit Spreads and Business Cycle Fluctuations." American Economic Review, Vol. 102 (4), p. 1692-1720.
- Gilchrist, Simon, Jae W. Sim, and Egon Zakrajsek. 2014. "Uncertainty, Financial Frictions, and Investment Dynamics," NBER Working Paper No. 20038, 2014.
- Gruber, Joseph and Steven Kamin (2017). "Corporate Buybacks and Capital Investment: An International Perspective," IFDP Notes 2017-04-11. Board of Governors of the Federal Reserve System (U.S.)
- Gutierrez, German and Thomas Philippon. 2016. "Investment-Less Growth: An Empirical Investigation." NBER Working Paper 22897, December 2016.
- IMF. 2015. "Private Investment: What's the Holdup?" In: IMF World Economic Outlook, April 2015.
- Jorgenson, Dale. 1963. "Capital Theory and Investment Behavior." American Economic Review, 53 (2), p. 247-259.
- Jorgenson, Dale and Calvin Siebert. 1968. "A Comparison of Alternative Theories of Corporate Investment Behavior." American Economic Review, Vol. 58 (4). p. 681-712.
- Kothari, S.P, Jonathan Lewellen and Jerold Warner. 2017/2014. "The Behavior of Aggregate Corporate Investment." MIT Sloan Research Paper No. 5112-14, Sloan School of Management, MIT, 2014. Updated version as of 2017.
- Lazonik, William. 2014. "Profits Without Prosperity." In: Harvard Business Review, September 2014. URL: https://hbr.org/2014/09/profits-without-prosperity.
- Leamer, 1978. "Specification Searches." New York: Wiley.
- Madigan, David, and Adrian E. Raftery. 1994. "Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window." Journal of the American Statistical Association, Vol. 89, p. 1535-46.
- OECD. 2015. "Lifting Investment for Higher Sustainable Growth." In: OECD Economic Outlook, Vol. 2015/1, Chapter 3. OECD, Paris, 2015.
- Oliner, Stephen, Glenn Rudebusch, and Daniel Sichel. 1995. "New and Old Models of Business Investment: A Comparison of Forecasting Performance." Journal of Money, Credit and Banking, Vol. 27, No. 3.
- Pinto, Eugenio and Stacey Tevlin. 2014. "Perspectives on the Recent Weakness in Investment." Federal Reserve Board of Governors, FEDS Notes, May 21, 2014.
- Raftery, Adrian, Jennifer Hoeting, Chris Volinsky, Ian Painter, and Ka Yee Yeung. 2018. "Package BMA." Version 3.18.8, CRAN depository, March 22, 2018.
- Samuelson, Paul. 1939. "A Synthesis of the Principle of Acceleration and the Multiplier." Journal of Political Economy, Vol. 47 (6), p. 786-797.
- S&P Capital. 2014. "Buying Outperformance: Do Share Repurchase Announcements Lead to Higher Returns?" Quantamental Research, January 2014. S&P Capital IQ.

### Annex Table 1
- Annex Table 1: Jorgenson and Siebert Model (1998-2014): Regression Coefficients
  - Source: Author’s estimates.

### Annex Table 2: Description of Variables
- Aggregate demand; output; GDP
  - Variable name: Real Gross Domestic Product (Bil.Chn.2009$)
  - Source: BEA /1
  - Code: GDPHA@USECON
  - Provider: Haver
  - Frequency: quarterly
  - Transformation: log idx, log diff
- Bank lending standards
  - Variable name: Net Percentage of Domestic Banks Tightening Standards for Commercial and Industrial Loans to Large and Middle-Market Firms
  - Source: Fed Board /2
  - Code: DRTSCILM
  - Provider: FRED
  - Frequency: quarterly
  - Transformation: none
- Capital stock: Nonresidential private fixed assets (NPFA)
  - Variable name: Real Net Stock: Private Fixed Nonresidential Assets (Bil.Chn.2009$)
  - Source: BEA
  - Code: EPNH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Capital stock: NPFA: Equipment
  - Variable name: Real Net Stock: Private Fixed Nonresidential Equip (Bil.Chn.2009$)
  - Source: BEA
  - Code: EPNEH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Capital stock: NPFA: Intellectual property products
  - Variable name: Real Net Stock: Pvt Fxd Nonres Intellectual Property Products(Bil.Chn.2009$)
  - Source: BEA
  - Code: EPNPH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Capital stock: NPFA: Structures
  - Variable name: Real Net Stock: Private Fixed Nonresidential Structures (Bil.Chn.2009$)
  - Source: BEA
  - Code: EPNSH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Consensus one-year ahead GDP growth forecast
  - Variable name: Survey of Professional Forecasters (SPF) 4-quarters ahead PGDP forecast, mean
  - Source: SPF /3
  - Code: dpgdp4
  - Provider: SPF
  - Frequency: quarterly
  - Transformation: none
- Consumer price inflation
  - Variable name: Consumer Price Index for All Urban Consumers: All Items, Percent Change from Year Ago, Quarterly, Seasonally Adjusted
  - Source: BLS /4
  - Code: CPIAUCSL_PC1
  - Provider: FRED
  - Frequency: quarterly
  - Transformation: log idx
- Consumer sentiment
  - Variable name: University of Michigan: Consumer sentiment
  - Source: University of Michigan
  - Code: UMCSENT
  - Provider: FRED
  - Frequency: monthly
  - Transformation: log idx
- Depreciation: NPFA
  - Variable name: Depreciation: Private Nonresidential Fixed Assets (Bil.Chn.2009$)
  - Source: BEA
  - Code: KPNH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Depreciation: NPFA: Equipment
  - Variable name: Depreciation: Private Nonresidential Fixed Assets: Equip (Bil.Chn.2009$)
  - Source: BEA
  - Code: KPNEH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Depreciation: NPFA: Intellectual property products
  - Variable name: Depreciation: Pvt Nonres Fxd Assets: Intellectual Property Prods (Bil.Chn.2009$)
  - Source: BEA
  - Code: KPNPH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Depreciation: NPFA: Structures
  - Variable name: Depreciation: Private Nonresidential Fixed Assets: Structures (Bil.Chn.2009$)
  - Source: BEA
  - Code: KPNSH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Economic policy uncertainty
  - Variable name: Economic Policy Uncertainty Index for United States
  - Source: Baker et al (2012)
  - Code: USEPUINDXD
  - Provider: FRED
  - Frequency: daily
  - Transformation: none
- Equity returns
  - Variable name: Russell 1000® Total Market Index, index, q/q change
  - Source: FTSE Russell
  - Code: RU1000TR
  - Provider: FRED
  - Frequency: daily
  - Transformation: none
- Equity valuations
  - Variable name: Russell 1000® Total Market Index, index
  - Source: FTSE Russell
  - Code: RU1000TR
  - Provider: FRED
  - Frequency: daily
  - Transformation: log idx
- Exports
  - Variable name: Real Exports of Goods & Services (SAAR, Bil.Chn.2009$)
  - Source: BEA
  - Code: XH
  - Provider: Haver
  - Frequency: quarterly
  - Transformation: log idx, log diff
- Federal funds rate (proxy for interest rate level)
  - Variable name: Effective Federal Funds Rate
  - Source: Federal Reserve Board
  - Code: DFF
  - Provider: FRED
  - Frequency: daily
  - Transformation: none
- Financial conditions index
  - Variable name: Chicago Fed National Financial Conditions Index
  - Source: Federal Reserve
  - Code: NFCI
  - Provider: FRED
  - Frequency: weekly
  - Transformation: none
- FX rate
  - Variable name: Real Trade-Weighted Exch Value of US$ vs Major Currencies (Mar-73=100)
  - Source: Federal Reserve Board
  - Code: FXTWMC
  - Provider: Haver
  - Frequency: daily
  - Transformation: log idx
- High yield (corporate) spread
  - Variable name: ICE BofAML US High Yield Master II Option-Adjusted Spread
  - Source: ICE/BofAML
  - Code: BAMLH0A0HYM2
  - Provider: FRED
  - Frequency: daily
  - Transformation: none
- Industrial production
  - Variable name: Industrial Production Index (SA, 2012=100)
  - Source: Fed Board
  - Code: IP
  - Provider: Haver
  - Frequency: quarterly
  - Transformation: log idx, log diff
- Inflation expectation
  - Variable name: Median expected price change next 12 months, Surveys of Consumers
  - Source: University of Michigan
  - Code: MICH
  - Provider: FRED
  - Frequency: monthly
  - Transformation: none
- Inflation gap
  - Variable name: Actual consumer price inflation minus target (distance actual to target)
  - Source: Own /5
  - Code: CPI_gap
  - Provider: NA
  - Frequency: NA
  - Transformation: log idx
- Manufacturers' new orders
  - Variable name: Manufacturers' New Orders: Nondefense Capital Goods (SA, Mil.1982$)
  - Source: CENSUS
  - Code: NMONC
  - Provider: Haver
  - Frequency: quarterly
  - Transformation: log idx, log diff
- Manufacturing and trade sales
  - Variable name: Real Manufacturing & Trade Sales: All Industries (SA, Mil.Chn.2009$)
  - Source: BEA
  - Code: TSTH
  - Provider: Haver
  - Frequency: quarterly
  - Transformation: log idx, log diff
- Net capital stock: Equipment, oil and gas extraction
  - Variable name: Net Stock: Private Equipment: Oil and Gas Extraction (Hist.Cost, Bil.$)
  - Source: BEA
  - Code: EPPB1ET@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Net capital stock: Structures, oil and gas extraction
  - Variable name: Net Stock: Private Structures: Oil and Gas Extraction (Hist.Cost, Bil.$)
  - Source: BEA
  - Code: EPPB1ST@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Nonresidential private fixed investment (NPFI)
  - Variable name: Investment: Private Nonresidential Fixed Assets (Bil.Chn.2009$)
  - Source: BEA
  - Code: ZPNH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- NPFI: Equipment
  - Variable name: Investment: Private Nonresidential Fixed Assets: Equip (Bil.Chn.2009$)
  - Source: BEA
  - Code: ZPNEH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- NPFI: Intellectual property products
  - Variable name: Investment: Pvt Nonres Fxd Assets: Intellectual Property Prods(Bil.Chn.2009$)
  - Source: BEA
  - Code: ZPNPH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- NPFI: Intellectual property: Oil and gas extraction
  - Variable name: Investment: Intellectual Property: Oil and Gas Extraction (Hist.Cost, Bil.$)
  - Source: BEA
  - Code: ZPPB1PT@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- NPFI: Oil and gas extraction
  - Variable name: Investment: Pvt Fxd Assets: Oil and Gas Extraction (Hist.Cost, Bil.$)
  - Source: BEA
  - Code: ZPPB1T@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- NPFI: Structures
  - Variable name: Investment: Private Nonresidential Fixed Assets: Structures (Bil.Chn.2009$)
  - Source: BEA
  - Code: ZPNSH@CAPSTOCK
  - Provider: Haver
  - Frequency: annual
  - Transformation: log idx, log diff
- Oil price
  - Variable name: Global price of WTI Crude
  - Source: IMF
  - Code: POILWTIUSDQ
  - Provider: FRED
  - Frequency: quarterly
  - Transformation: log idx
- Personal consumption expenditures (PCE)
  - Variable name: Real Personal Consumption Expenditures (SAAR, Bil.Chn.2009$)
  - Source: BEA
  - Code: CH
  - Provider: Haver
  - Transformation: log diff
- Political conflict; partisan conflict
  - Variable name: Partisan Conflict Index
  - Source: Azzimonti (2018)
  - Code: NA
  - Provider: Federal Reserve
  - Frequency: monthly
  - Transformation: none
- Productivity
  - Variable name: Average Weekly Hours: Prod & Nonsupervisory: Manufacturing (SA, Hrs)
  - Source: BLS
  - Code: LRMANUA
  - Provider: Haver
  - Frequency: quarterly
  - Transformation: log idx
- Profits
  - Variable name: Real Corporate Profits After Tax (SAAR, Bil.Chn.2009$)
  - Source: BEA
  - Code: YCATH@USECON
  - Provider: Haver
  - Frequency: quarterly
  - Transformation: log idx, log diff
- Rate hikes (changes in federal funds rate)
  - Variable name: Effective Federal Funds Rate, q/q change
  - Source: Fed Board
  - Code: DFF_qoq
  - Provider: FRED
  - Frequency: daily
  - Transformation: none
- Residential private fixed investment (RPFI)
  - Variable name: Investment: Res Fixed Assets: Private (Bil.Chn.2009$)
  - Source: BEA
  - Code: ZPRT@CAPSTOCK
  - Provider: Haver
  - Frequency: quarterly
  - Transformation: log idx, log diff
- Relative price of investment
  - Variable name: Relative price of investment goods (investment to consumption deflator)
  - Source: Federal Reserve
  - Code: PIRIC
  - Provider: FRED
  - Frequency: quarterly
  - Transformation: none
- SPF dispersion
  - Variable name: Range of individual SPF one-year ahead growth forecasts (max minus min)
  - Source: Own
  - Code: NA
  - Provider: SPF
  - Frequency: quarterly
  - Transformation: log idx
- Term spread, 10-year minus 2-year Treasury yield
  - Variable name: 10-Year Treasury Constant Maturity Minus 2-Year Treasury Constant Maturity
  - Source: Federal Reserve
  - Code: T10Y2Y
  - Provider: FRED
  - Frequency: daily
  - Transformation: none
- Tightening of lending standards
  - Variable name: Net Percentage of Domestic Banks Reporting Stronger Demand for Commercial and Industrial Loans from Large and Middle-Market Firms
  - Source: Federal Reserve Board
  - Code: DRSDCILM
  - Provider: FRED
  - Frequency: quarterly
  - Transformation: none
- VIX
  - Variable name: CBOE Volatility Index: VIX
  - Source: CBOE
  - Code: VIXCLS
  - Provider: FRED
  - Frequency: daily
  - Transformation: log idx

Source: Author. Notes: /1 Bureau of Economic Analysis; /2 Board of Governors of the Federal Reserve; /3 Survey of Professional Forecasters; /4 Bureau of Labor Statistics; /5 variables defined by author.

*Source: wp18139 - REFERENCES (pdf).*

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_Source: https://www.imf.org/-/media/files/publications/wp/2018/wp18139.pdf_