Investment, Overhang, and Tax Policy

Investment, Overhang, and Tax Policy Mihir A Desai Harvard University and NBER Austan D Goolsbee University of Chicago, American Bar Foundation and NBER November 2004 We thank Mark Veblen and James Zeitler for their invaluable research assistance and Alan Auerbach, Bill Brainard, Kevin Hassett, John Leahy, George Perry, Joel Slemrod, and participants at the BPEA conference for their comments Dale Jorgenson was kind enough to provide cost of capital estimates Desai thanks the Division of Research at Harvard Business School for financial support Investment, Overhang and Tax Policy ABSTRACT The unusual behavior of investment in the 1990s and early 2000s—abnormally high investment in the 1990s and abnormally low investment in the 2000s, despite several major tax cuts intended to stimulate investment — prompts two questions that we tackle in this paper: Did “capital overhang” contribute to the dramatic investment collapse of the early 2000’s? and Why has fiscal policy been unable to revive investment? We use firm level evidence to show that capital overhang – the notion that the late 1990s stock market bubble led to excess investment and prevented a rebound – is not a meaningful factor in explaining the fall of investment Controlling for fundamentals, there is little evidence of capital overhang We then modify the tax-adjusted q model to allow for clearer identification of tax effects in the presence of mismeasured q This modification yields estimates that are larger and more precisely measured suggesting that the taxadjusted q model does a reasonable job in explaining investment patterns Using this q model we then investigate the effects of the tax cuts First, in keeping with the “new” view of dividend taxation, the evidence suggests that dividend taxes not influence marginal investment incentives This evidence indicates that the dividend tax cut, with forecast revenue cost of more than $400 billion from 2003-2008, would have had little if any impact on investment Second, the partial expensing of equipment provisions (revenue cost of approximately $130 billion from 2002-2004) did have an effect on investment but were too small to counteract the large aggregate investment declines stemming from market movements The results put the investment increases resulting from the tax policies of 2002-2004 at only one to two percent Mihir A Desai Harvard Business School Morgan 363 Soldiers Field Boston, MA 02163 mdesai@hbs.edu Austan D Goolsbee University of Chicago Business School goolsbee@gsb.uchicago.edu 1 Introduction The pattern of investment over the past decade has been unusual The boom of the 1990s generated unusually high investment rates, particularly in equipment, and the bust of the 2000s witnessed an unusually large decline in investment Drops in equipment investment normally account for about 10-20 percent of the decline in GDP during a recession but in 2001 accounted for 120 percent of this decline.1 In the public mind, the boom and bust in investment are directly linked due to “capital overhang.” Though not very precisely defined, generally this view holds that that excess investment in the 1990s, fueled by an asset price bubble, left corporations with excess capital stocks and, therefore, no demand for investment during the 2000s The popular view also holds that these conditions will continue until normal economic growth eliminates the overhang and, consequently, there is little policy makers can about it by subsidizing investment with tax policy, for example Variants on this view have been extensively espoused by private sector analysts and economists (e.g., Berner, 2001; Leach, 2002; Roach, 2002) and certainly has been on the minds of leading Federal Reserve officials (e.g., Greenspan, 2002; Ferguson, 2002; Bernanke, 2003) and researchers (e.g., French et al., 2002; Pelgrin et al., 2002; Kliesen, 2003; McCarthy , 2004) Regardless of whether overhang is the true explanation of the investment bust, it is clear that the drop in investment has motivated policy makers to try to stimulate investment through large fiscal policy changes.2 President Bush twice increased depreciation allowances (2002 and 2003) for equipment investment and, in 2003, significantly cut the tax rate on dividend income and modestly cut the tax rate on capital gains income These measures were mainly intended to reduce the cost of capital and stimulate investment The typical analysis of the investment collapse and policy response is summarized by the Republican chairman of the Joint Economic Committee: "Excessive and bad business investments made during the stock market bubble have taken years to liquidate In nine of the 10 quarters beginning McCarthy (2003) documents the equipment declines as a share of GDP declines for all of the cycles since 1953 and shows the 2001 recession to be an extreme outlier Unlike investment behavior, this phenomenon of the 2000s is completely consistent with earlier time periods Cummins et al (1994) have documented that a primary determinant of investment tax subsidies is a drop in investment the fourth quarter of 2000, real business investment has actually declined Fortunately, recent tax legislation signed into law in 2003 should promote business investment by increasing the after-tax returns from investing in capital assets and alleviating financing constraints among small and medium-size firms." (Saxton, 2003) Yet, after several years of tax cuts, investment has still not risen impressively compared to previous recoveries This contrast has reignited claims that tax policy is ineffective at stimulating investment, though some make the more specific charge that tax policy may only be impotent when it follows a period following excessive investment In this paper, we attempt to examine the evidence on the two related issues of overhang and taxes in some detail using micro data, usually at the firm level Specifically we address two questions: 1) did "over"-investment of the 1990s cause the low investment of the 2000s and 2) did it make investment in the 2000s less sensitive to prices and is this why tax policies, specifically the equipment expensing and the dividend tax cuts of 2002 and 2003, have seemed to have so little ability to restore investment to normal levels? We begin by looking at correlations of investment during the boom and the declines in investment during the bust across different assets and industries There are, of course, many potential definitions of overhang or excess investment and we want to make clear at the outset that we will not be trying to show there was no over-optimism in product or capital markets Clearly equity prices rose and then fell as did investment rates Instead we are trying to figure out whether the rise of the 1990s "stays with us" into the 2000s—whether firms behave differently now, given today's observables, because there is too much capital sitting around from the 1990s That is our notion of overhang We will start with some suggestive evidence on investment rates across industries, asset types, and firms Contrary to the popular view, in all three cases, there is little correlation between the investment boom of the 1990s and the investment bust of the 2000s We will then present some specific evidence using firm level data that investment behavior has remained just as responsive to fundamentals/prices (as measured by Tobin’s q) regardless of how much investment growth or equity price growth the firm had in the 1990s Essentially, we find that the explanatory power of the standard empirical model of investment has not deteriorated in the 2000s, despite the common perception that the current period is unusual We will then use that standard model to consider the impact of tax cuts To estimate the impact of the dividend tax reduction, we revisit an enduring debate in public finance between the “new” view of dividend taxation that says dividend tax cuts not reduce the cost of capital for marginal investments and the “traditional” view that says that such cuts reduce the cost of capital and, thus, stimulate investment The evidence from the firm level data strongly supports the new view and suggests that the dividend tax reductions enacted in 2003 had little or no effect on investment Finally, to estimate the impact of the changes in depreciation allowances, we estimate a tax-adjusted q model as in Summers (1981) but with greater emphasis on the importance of measurement error in measuring q as emphasized in Cummins et al (1994) The method introduced for handling these measurement error issues suggests that tax policy (and q) are likely to have much larger effects on investment than in the traditional literature where coefficients are very small and imply implausibly large costs of adjustment Even with the larger coefficients, however, we show that the depreciation allowance changes of 2002 and 2003 changed the cost of capital by a relatively small amount and imply that the overall impact in these two years (2002-2003) was an increase in investment of only 1- percent, far too small to significantly offset the double digit declines of the early 2000s Capital Overhang and Investment 2.1 Motivation During the 1990s, gross investment was considerably higher than normal Non- recession year investment from 1947:Q1 to 1995:Q2 averaged about 12.3 percent of GDP and the highest quarterly level was 15 percent in 1984:Q3 From 1996:Q1 to 2000:Q4 this ratio averaged more than 16 percent and reached as high as 18 percent at its peak The distinctiveness of these investment rates holds even relative to the business cycle Norming investment in the peak quarter to one, Figure shows that investment in the quarters leading up to the peak in 2001:Q1 was higher than investment in previous cycles Tevlin and Whalen (2003) argue that the higher gross investment of the 1990s can, at least partly, be explained by falling prices and high depreciation rates of computers Nonetheless, the view that low investment resulted from the excesses of the 1990s remains widespread With that in mind, Figure provides a counterpart to the previous figure by showing the path of investment in the time after the trough quarter for the recovery in the 2000s relative to previous recoveries Investment is normed to one in the trough quarter for each series The increase in investment in this recovery, at least through the beginning of 2004, is notably lower than in an average recovery The aggregate data make it seem plausible to many observers that post-trough investment was lower precisely because the previous investment was higher Of course, these aggregate patterns not suggest any underlying mechanism Investment rose unusually and then investment declined unusually To test for any relationship between the rise and decline, it is critical to disaggregate investment Most academic work looking at overhang has not disaggregated the data or has done so at a very broad level, emphasizing that this reversal is concentrated in information technology investment.3 At the outset, we want to narrow our analysis of overhang to something that corresponds to the popular view/conventional wisdom That view holds that some industries, such as telecommunications or internet-related industries, experienced bubblefueled investment binges in the 1990s and subsequently had massive amounts of investment with no use and no market for resale Other industries experienced little rise in their equity values and were unrelated to technology Since this is inherently an industry or firm level phenomenon, we think it is important to look at data at that level The overhang phenomenon, if it exists, should not be equal across all industries A different reason to look at the micro data is that typically, investment theory begins with the premise that there is a perfectly functioning secondary market for capital goods and a flat supply curve for capital In such a world, firms with an overhang of unused capital could simply sell the machines without any loss For the popular view to make sense, then, one needs to have either irreversibility of investment (which leads to a rather McCarthy (2001, 2004) are exceptions different model as in, for example, Abel and Eberly (2002)) or some other type of adjustment costs on disinvestment.4 The work of Shapiro and Ramey (2001) has documented that, in some industries, there can be a sizable wedge between the purchase and sale price of capital goods The evidence in Goolsbee and Gross (2000) is also consistent with that view These types of irreversibilities are likely to be firm or asset specific rather than applying to everyone in the same way Fortunately micro data on investment are available at the industry, asset type and firm level and the evidence in all three is generally the same 2.2 Evidence at the Industry Level Before using our most detailed industry level data, we start with the broad categories from the Bureau of Economic Analysis In order to so, we compare the changes in net stock of private fixed assets, measured at current cost, from 1998 to 2000 relative to the change from 2000 to 2002 Figure provides the change in log real net stock of private fixed assets (excluding real estate) from 1998 to 2000 (i.e., the rise in investment over the boom) on one axis and the change from 2000 to 2002 (i.e., the change in investment during the bust) on the other The data come from Table of the Bureau of Economic Analysis' Fixed Assets tables Each industry and each industry is identified with a bubble that corresponds to its share of private fixed assets in 2000 (again excluding real estate) with the industry name below the bubble Several notable aggregate facts are apparent from Figure First, the relative decline between the two periods is apparent from the alternative scaling of the axes The 45º here represents an investment rate in the latter period of one-half the rate in the earlier period Second, contrary to what one might expect if overhang is important, the industries where investment boomed most in the late 1990s actually had their investment grow faster during the 2000s than the others did This pattern is particularly true if one restricts attention to the industries that constitute at least 5% of private fixed assets (utilities, finance and insurance, information, durable goods manufacturing, nondurable The adjustment costs could be firm-level adjustment costs or might be external in the sense that the supply of capital goods in a particular industry is upward sloping as in Goolsbee (2000, 2001) goods manufacturing, transportation and warehousing, wholesale trade, retail trade, mining and healthcare and social assistance) Rather than rely on these fairly aggregated categories, however, we use the Annual Capital Expenditure Survey (ACES) of the United States Census to examine the nature of overhang at the industry level The ACES provides a greater level of industry disaggregation than is available elsewhere The survey samples approximately 60,000 companies in more than 100 industries organized by the 1997 North American Industry Classification System (NAICS) We narrow this down to 81 non-overlapping industries at approximately the three-digit NAICS level.5 The ACES only provides measures of gross investment and does not estimate the capital stock for these industries Consequently, we cannot scale investment by lagged capital as in traditional empirical work on investment Instead, we simply investigate investment in a period for equipment alone (Table 1) and equipment combined with structures (Table 2) Empirical models of investment have struggled with explanations for structures investment and it is not known whether this is due to mismeasurement in the cost of capital, unobservable factors in structures markets such as liquidity and financing issues relating to the supply side of the market, or to some other factor.6 Since we cannot readily isolate equipment from structures investment in the firm level data employed below, we have to assume that equipment and overall investment behave the same way Given that by the 2000s, equipment accounted for something like 80 percent of total investment, this may not be too problematic Our goal with these data is to look for general evidence supporting the view that overhang from the 1990s is a key factor determining investment in the 2000s To test this, we provide a cross-sectional regression of the change in log investment in an industry from 2000 to 2002 (the period widely viewed as the "collapse") on the change in log investment from 1994 to 1999 in that same industry, estimating the equation: Prior to 1997, SIC codes were employed and the matching of NAICS to SIC codes enables comparison over the entire period See, for example, the discussion in Auerbach and Hassett (1992) who discuss the problems with estimating structures investment Since structures are so long-lived, long-term expectations may be especially important here and our contemporaneous cost of capital measures may be particularly bad (1) ln( I i ,2002 )  ln( I i ,2000 )      ln( I i ,1999 )  ln( I i ,1994 )    i In short, the β coefficient measures the degree to which industries where investment increased the most, in percentage terms, during the 1990s had the largest declines in investment in the 2000s This test would not pick up reversion if all industries boomed and then busted together since that would simply go into the constant term But the view of the bubble was certainly not a purely aggregate phenomenon The top panel of Table presents the results of estimating equation (1) by OLS and the bottom panel provides results employing median regressions to ensure that the results in the top panel not purely reflect the role of large outliers Column presents the results from the basic overhang specification The OLS and median regressions provide almost identical coefficients that are negative but very small and not significantly different from zero To give a sense of the magnitude, increasing one standard deviation in the investment rate for the 1994-1999 period (0.53) (changing it from the median of 0.38 to about the 90th percentile) would imply investment only 2.7 percent lower over the 2000-2002 period This is less than 1/12th of a standard deviation This evidence of overhang is modest, at best Given the serious decline of manufacturing in this recession, and given that oldline manufacturing was not typically associated with the internet boom, we wanted to look in this sector separately To so, we restrict the sample to the 23 manufacturing industries for the regressions provided in column of the two panels For these industries, the evidence seems more pronounced In both the OLS and the median regression, there is a large and significant negative coefficient on investment in the 1990s In the median regression, a one standard deviation increase in the 1994 to 1999 investment rate among manufacturing industries (of 0.32) would correspond with almost 22 percent lower investment in the 2000-2002 period which corresponds roughly to the mean drop in investment (-0.26) and is equal to about 2/3 of the standard deviation of those changes Even if one believed this larger effect were evidence of overhang (as opposed to something cyclical), it should be noted that manufacturing industries constituted only about 22 percent of total equipment investment and 18 percent of total investment in 2002 according to the ACES.7 Consequently, evidence of mean reversion for manufacturing can only have a limited influence on the aggregate collapse of investment The common explanation for capital overhang is that funds raised from the capital market during the bubble encouraged the excess investment, particularly during the 19971999 period Indeed, the broadly disaggregated analysis in McCarthy (2003), which uses a cost of capital type analysis, suggests that there was no capital overhang at all until 1998, even in the high-tech investment goods sector (computers and communications equipment) In columns and 4, we separately consider period from 1994 to 1997 and from 1997 to 1999 in order to isolate the effects of the so-called bubble period Again, there is little evidence of reversion across industries and there are larger negative coefficients in manufacturing The later period, typically associated with the overhang explanation, has a smaller coefficient than the earlier period, though the standard errors are not small enough to reject that they are equal Rather than supporting the intuition of a bubble-induced capital overhang, this consideration of the two subperiods suggests some underlying, more secular, mechanism associated with the continuing decline in U.S manufacturing Table considers the behavior of both equipment and structures investment The results are qualitatively similar to those provided in Table with little evidence of reversion generally and manufacturing featuring the dynamics discussed earlier 2.3 Evidence at the Asset Level Next we consider the general evidence on investment by type of investment good rather than by industry As with Figure 3, it is useful to consider first the aggregate facts with respect to investment by type In order to so, Table provides the change in the log of investment from 1998 to 2000 in the first column (the growth of investment in the bubble) and the change in log investment from 2000 to 2002 in the second column (the change in investment during the bust) along with the share of total investment the asset accounted for in 2000 All data are drawn from Table 5.5.6 of the Bureau of Economic Analysis' NIPA tables and are disaggregated into some general categories This is also consistent with the evidence cited by Bernanke (2003) designed Their magnitude, however, is simply not big enough to counteract the aggregate trend 4.2.2 Were the cuts directed at the hardest hit industries? Given the interest in countering the perceived overhang of investment through tax policy, we next investigate who the recipients of the tax cuts were to determine whether the cuts were largest for industries that either had the biggest drops in investment the 2000-2001 period, or the biggest increases in the 1990s, or the largest equity price changes Some of the popular discussion of these cuts emphasized that they might help the hardest hit industries To investigate this, we present regressions in Table 12 where the change in the tax cost of capital for equipment in the industry (top panel is the left hand side variable and explanatory variables corresponding to these measures of increased investment in the 1990s, decreased investment in the early 2000s or those with the largest equity value reductions on the right hand side All of the coefficients in this table are multiplied by 100 for presentation The results are, at best, mixed In the equipment cost results, firms whose investment grew most in the 1990s and fell most from 2000 to 2001 had the biggest cuts in the cost of capital While significant, the magnitudes are extremely small Increasing investment in the 1990s by one standard deviation corresponds to a cost of equipment capital being lowered in 2003 by 0004 (compared to a mean change of 03) A similar magnitude holds for the drops in investment from 2000 to 2001 Changes in equity prices as measured by changes in q have no relationship with the change in capital In the overall cost of capital results, there are no significant effects and, in fact, the sign for the 2000-2001 period reverses Firms where investment fell most from 2000-2001 saw their cost of capital drop the least Taken together, the benefits of these tax cuts were not concentrated on the hardest hit industries The median regressions in the bottom panel confirm this analysis 4.2.4 How much did these incentives increase investment? To estimate the precise impact of the tax changes on investment, we return to the tax-adjusted q model To use that model to simulate the impact of the tax cuts in 2002 and 2003, we need to compute the saddle path for investment in the standard q model 30 (see Abel (1981) and Summers (1981) for discussion) Auerbach (1989) outlines a linearization that makes this particularly easy and we adopt his notation to derive the predicted effects If we assume a Cobb-Douglas production function with a capital share of 1-a, a real interest rate of r, the adjustment cost parameter assuming quadratic adjustment costs of φ (the reciprocal of the true coefficient on Q in our regressions), and the adjustment cost modified depreciation rate for capital in the firm of $ (whose specific formula is listed below), Auerbach shows that for an unanticipated permanent change in tax policy, the capital stock follows a simple partial adjustment model with K&t  1 ( K *  K t ) where K* is the desired capital stock The rate of adjustment, -λ1 follows the formula r  r2  (20) 1  4a (r  $)  To compute this adjustment rate empirically, we assume a real interest rate of percent We compute a, the complement of the capital share, as one minus the gross output share of value added for each industry as reported in the disaggregated NIPA data for the year 1998 We take the true coefficient on Q to be 1, following the results above We compute $ =δ(1-φ δ/2) using our value for φ and using the industry average depreciation rate on their equipment or their total investment as computed from the weighted average by asset in the Jorgenson data using the industry weights in the Capital Flow Table This gives us an adjustment rate per year for each firm The average annual adjustment rate for all firms is about 0.33 and the average value for each 3-digit industry is listed in the appendix table (one column includes structures, the other only equipment) We then use the Cobb-Douglas production function to derive the optimal capital stock.25 To compute the effect of these policies over the past two years, we assume the depreciation changes were unanticipated and thought to be permanent.26 We first derive 25 This implies a long-run elasticity of K with respect to the user cost of -1 Such a figure is consistent with the empirical findings surveyed in Hassett and Hubbard (2002) or Goolsbee (2000) but larger than the findings discussed in Chirinko (1993) or Chirinko et al (1999) 26 Unanticipated is probably fairly accurate An assumption of permanence seems reasonable as they were announced to be temporary but from the moment they were passed many have been arguing that they be 31 the optimal capital stock and amount of adjustment in the first year (2002) We then calculate the new optimal capital stock for 2003 (after the second tax cut) and the amount of adjustment based on the new gap between K* and actual K (where actual K is higher than it was in 2001 because of the investment done in 2002) Averaging things for each 3-digit industry and summing over the two years we estimate the impact of the tax cuts on investment listed in Table 13 The average increase in the period is only about 1.0 to 1.5 percent so it is immediately clear why these tax cuts have seemed to have little success in stemming the investment declines Their short-run stimulus effect is too small This is not a refutation of the view that taxes matter The changed incentives were effective They were just not large enough to counteract the double digit declines in investment rates observed in the 2000s Tax policy is effective but using changes to depreciation allowances simply cannot have much impact when the system is already so close to full expensing and when aggregate declines in market values (and therefore q) are so large The adjustment is asymptoting to the optimal capital stock so further years of the policy will have smaller effects than the first two years After 2004, the average total increase is still less than percent Conclusion This paper has addressed the two questions arising from the puzzling investment experience of the 2000s: how correlated was the equity bubble of the 1990s with the decline in investment in the 2000s? and why didn't the major tax cuts of 2002-2003 more to restore investment to normal levels? The micro data is quite clear that the popular intuition of how capital overhang affected the investment market in the 2000s just cannot withstand scrutiny The general evidence across assets, industries and firms shows that high growth in the 1990s is not correlated with drops in the 2000s Specific evidence goes further and documents that the firm level investment-q relationship has not changed noticeably in the recent period for firms that excessively invested Instead, the rise and fall of equity prices in the context of a conventional tax-adjusted q model that better accounts for measurement error in measuring marginal q is the best explanation made permanent (and indeed have already been extended to 2004) We assume permanence here in order to significantly simplify the computation of the saddle path 32 This conventional tax adjusted q model then serves as the basis for our analysis of the impact of the tax cuts and their seeming inefficacy Our results show that the dividend tax cut, while having a high revenue cost, had minimal, if any, impact on marginal investment incentives The results strongly favor the "new" view of dividend taxation in which such taxes are capitalized into share prices and not affect marginal incentives We also show that the partial expensing provisions passed in 2002 and 2003 were not large enough to provide much counterweight to the declines in aggregate investment The policies contributed to an increase of the capital stock of 1-2 percent Breaking out the results by industry, there is little evidence that the gains were concentrated among the industries that experienced the biggest declines during the investment bust It will be interesting to see whether future tax policies toward investment will have a larger effect 33 References Abel, Andrew B (1981) "A Dynamic Model of Investment and Capacity Utilization," Quarterly Journal of Economics, 96: 379-403 Abel, Andrew B and Janice C Eberly (2002) “Q for the Long Run,” working paper Auerbach, Alan (1979), “Wealth Maximization and the Cost of Capital,” Quarterly Journal of Economics, 93(3), August, 433-446 Auerbach, Alan J (1989) “Tax Reform and Adjustment Costs: The Impact on Investment and Market Value,” International Economic Review 30:4, 939-962 Alan Auerbach (2002), “Taxation and Corporate Financial Policy,“ in Handbook of  Public Economics, vol. 3, Alan Auerbach and Martin Feldstein, eds, North­Holland  (Amsterdam, The Netherlands), 1251­1292 Auerbach, Alan J and Kevin A Hassett (1992) “Tax Policy and Business Fixed Investment in the United States, Journal of Public Economics, 141-170 Auerbach, Alan J and Kevin A Hassett (2003) “On the Marginal Source of Investment Funds,” Journal of Public Economics, 87:205-232 Bernanke, Ben (2003), "Will Business Investment Bounce Back?" remarks before the Forecasters Club, New York, New York, April 24 Berner, Richard (2001), "Purging Excess—The Capacity Overhang," Global Economic Forum, November 9, 2001,, accessed August, 2004 Blouin, Jennifer, Jana Raedy and Douglas Shackelford (2004), "Did Dividends Increase Immediately After the 2003 Reduction in Tax Rates," NBER WP#10301 Bolster, Paul and Vahan Janjigan Bond, Stephen R and Jason G Cummings (2000) “The Stock Market and Investment in the New Economy: Some Tangible Facts and Intangible Fictions,” Brookings Papers on Economic Activity 2000:1, 61-124 Bradford, David (1981), “The Incidence and Allocation Effects of a Tax on Corporate Distributions,” Journal of Public Economics, 15(1), April, 1-22 Carroll, Robert Kevin Hasset, and James Mackie (2002) “The Effect of Dividend Tax Relief on Investment Incentives” National Tax Journal 56: 629-651 Chetty, Raj and Emmanuel Saez (2004), “"Do Dividend Payments Respond to Taxes? Preliminary Evidence from the 2003 Dividend Tax Cut" joint with Raj Chetty, NBER Working Paper No 10572, June 34 Chirinko, Robert, Steven M Fazzari and Andrew P Meyer “How Responsive Is Business Capital Formation To Its User Cost?: An Exploration With Micro Data", Journal of Public Economics 74 (October 1999), 53-80 Cohen, Darryl, Kevin Hassett and Hansen, Dorthe-Pernille (2002), “The Effects of Temporary Partial Expensing on Investment Incentives in the United States”, National Tax Journal, Vol LV, No 3, 457-466 Cummins, Jason G., Kevin A Hassett, R Glenn Hubbard (1994) “A Reconsideration of Investment Behavior Using Tax Reforms as Natural Experiments,” Brookings Papers on Economic Activity 1994:2, 1-74 Cummins, Jason, Kevin Hassett and Stephen Oliner (forthcoming), "Investment Behavior, Observable Expectations, and Internal Funds," American Economic Review Doms, Mark (2004), "The Boom and Bust in Information Technology Investment," Federal Reserve Bank of San Francisco Economic Review 2004, 19-34 Fergeson, Roger (2001), "Reflections on the Capital Good Overhang," remarks to the Charlotte Economics Club, Charlotte, North Carolina, July 18 French, Eric, Thomas Klier and David Oppedahl (2002), "Is There Still an Investment Overhang, and if So, Should We Worry About It?" Federal Reserve Bank of Chicago, Chicago Fed Letter, Special Issue #177a, May Gilchrist, Simon and Charles Himmelberg (1998), "Investment: Fundamentals and Finance," NBER Macroeconomics Annual 1998, 223-273, MIT Press (Cambridge, MA) Goolsbee, Austan (1998), "Investment Tax Incentives, Prices and the Supply of Capital Goods," Quarterly Journal of Economics, 113(1), February 1998, pp 121 - 148 Goolsbee, Austan (2001), "The Importance of Measurement Error in the Cost of Capital," National Tax Journal June, 2000 vol 53(2), pp 215-228 Goolsbee, Austan (2004), "Taxes and the Quality of Capital," Journal of Public Economics, 88(3-4), March 2004, 519-543 Goolsbee, Austan and David Gross (2001), "Estimating Adjustment Costs with Data on Heterogeneous Capital Goods," Mimeo, University of Chicago, GSB Greenspan, Alan (2002), "Economic Volatility," remarks at Federal Reserve Bank of Kansas City symposium, Jackson Hole, Wyoming, August 30, 2002 35 Hassett and Hubbard (2002) “Tax Policy and Investment” in Handbook of Public  Economics, vol. 3, Alan Auerbach and Martin Feldstein, eds, North­Holland  (Amsterdam, The Netherlands) Hederman, Rea (2004), "Tax Cuts Boost Investment," Heritage Foundation Web Memo, February 3, , accessed August, 2004 Joint Committee on Taxation (2002) “Estimated Revenue Effects of the 'Job Creation and Worker Assistance Act of 2002,”, March 6, 2002, JCX-13-02; U.S Government Printing Office, Washington D.C Joint Committee on Taxation (2003a) “Estimated Budgetary Effects of the Conference Agreement for H.R and the 'Jobs and Growth Tax Relief Reconciliation Act of 2003,” May 22, 2003, JCX-55-03; U.S Government Printing Office, Washington D.C Joint Committee on Taxation (2003b) “Estimates of Federal Tax Expenditures for Fiscal Years, 2004-2008,”, December 22, 2003, JCS-8-03; U.S Government Printing Office, Washington D.C Jorgenson, Dale and Kun-Young Yun (2001), Investment, Volume 3: Lifting the Burden: Tax Reform, the Cost of Capital, and U.S Economic Growth, MIT Press (Cambridge, MA) Julio, Brandon and David Ikenberry (2004), "Reappearing Dividends," University of Illinois College of Business Working Paper Kaplan, Steven N and Luigi Zingales (1997) “Do Investment-Cash Flow Sensitivities Provide Useful Measures of Financing Constraints?” The Quarterly Journal of Economics 112:1, 169-215 King, Mervyn (1977), Public Policy and the Corporation, (London: Chapman and Hall) Kliesen, Kevin (2003), "Was Y2K Behind the Business Investment Boom and Bust?," Federal Reserve Bank of St Louis Review, January/February, 85(1), 31-42 Kudlow, Larry (2004), "A Capital Idea from Microsoft," National Review Online, July 23, 2004 Leach, Graeme (2002), "The Worries of the World," GCIEye, Issue #1, accessed, August, 2004 McCarthy, Jonathan (2004), "What Investment Patterns Across Equipment and Industries Tell Us about the Recent Investment Boom and Bust," Federal Reserve Bank of New York Current Issues in Economics and Finance, , 10(6), May, 1-7 36 - (2003), "Capital Overhangs: Has Equipment Investment Spending Suffered from a Hangover?" Business Economics, October, 2003, 20-27 - (2001), "Equipment Expenditures since 1995: The Boom and the Bust," Federal Reserve Bank of New York Current Issues in Economics and Finance, , 7(9), October, 16 Pelgrin, Florian, Sebastian Schich and Alain de Serres (2002), "Increases in Business Investment Rates in OECD Countries in the 1990s: How Much Can be Explained by Fundamentals?" OECD Economics Department Working Paper # 327, April 15 Poterba, James (2004), "Taxes and Corporate Payout Policy," American Economic Review, May, 94(2), 171-175 Poterba, James M and Lawrence H Summers (1983) “Dividend Taxes, Corporate Investment, and ‘Q,’” Journal of Public Economics 22, 135-167 Poterba, James M., and Lawrence Summers (1985): “The Economic Effects of Dividend Taxation,” in Recent Advances in Corporate Finance, E I Altman, and M G Subrahmanyam, eds pp 227–284 Richard D Irwin, Homewood, Ill Roach, Stephen (2002), "The Cost of Bursting Bubbles," New York Times, September 22, editorial Saxton, Jim (2003), "Economic Reprercussions of the Stock Market Bubble: A Joint Economic Committee Study," July 2003, , accessed August, 2004 Shapiro and Ramey (2001), “"Displaced Capital: A Study of Aerospace Plant Closings,” Journal of Political Economy, 109 (5), 958-992 Summers, Lawrence H (1981) “Taxation and Corporate Investment: A q-Theory Approach,” Brookings Papers on Economic Activity 1981:1, 67-140 Tevlin, Stacey and Karl Whelan (2003), "Explaining the Investment Boom of the 1990s," Journal of Money Credit and Banking, 35(1), February, 1-22 37 Data Appendix Firm-level data financials Annual data for all companies in the Compustat data base, from 1950 on, are accessed through WRDS Capital stock: Market valuation Property, Plant, and Equipment – Total (Net) is used as a measure of capital equipment; Capital Expenditures (Statement of Cash Flows) is used as a measure of capital expenditures Each of these measures is converted from current terms to real terms by dividing by the current value of PPI-Capital Goods Three factors enter into the current valuation of capital stock First, changes in prices of capital goods held over from previous years We sidestep this component by first deflating our measure of PPE by the producer price index for capital equipment, to give us a real measure of capital on hand Second, additions to capital through investment expenditures Third, depletion of capital on hand through depreciation The firm’s current real capital stock can be thought of as the sum of the non-depreciated stocks of all prior years plus the current level of investment Following (Cummins, Hassett, and Hubbard, 1994), assuming a constant rate of depreciation, , the current capital stock is calculated as: K T K 1     K 1   T T   K T -1 1     I T **ISN'T THIS SUPPOSED TO BE It-1 not Kt-1, etc.? For example, the firm starts in time with capital stock K0, but has only the non-depreciated part of this stock (1-) K0 to carry on to the next year, time Some of this carried-over capital is used up in the production of period 2, leaving (1-)2 K0 to carry on to period 3, and so forth By period T, only (1-)T K0 is carried over from period Similar reasoning explains the coefficients of the levels of capital stock carried over to period T from all prior years I T represents investment expenditures in period T (Note that prior years’ investment spending is already incorporated the prior years’ ending capital stock.) Given the ending levels of capital stock for all years, including the final year, and the final year’s investment spending, all deflated by the PPI-Capital Goods, we can solve for the average rate of depreciation for each firm This average rate of depreciation is then applied sequentially, from the first observed year for each firm to the last, to derive an estimated capital stock for each firmyear observation Inventories: Book to market valuation Compustat data item (Inventories – Total) is used as a measure of the current value of inventory holdings As in Cummins, Hasset and Hubbard (1994), inventory levels are converted from book to LIFO market value by adjusting carried-over inventories, the lagged book value, for year-toyear changes in prices of finished goods The implementation of the adjustment mechanism depends on whether final levels of inventories increase or decrease from one year to the next 38 If inventories increase, those goods carried over from the previous year are revalued at current prices, as is the net addition to total inventories: Inv mt Inv mt  Pt P  Inv t  Inv t  Inv mt  t  Inv t Pt  Pt    Essentially, under LIFO valuation rules, the ending levels of inventories include all that are carried over from the previous year plus unsold current production All inventories carried into the current year remain at the end of the year and are revalued at current prices The net addition to inventories is already measured at current prices, so needs no further adjustment On the other hand, if inventories decrease during the current year, then all current production is sold, plus some part of carried-over inventories Everything remaining at the end of the year is valued at current prices  Inv mt  Inv mt   Inv t  Inv t   PP t t   Inv mt   Inv t  PP t t Operating income Operating income before depreciation and Operating income after depreciation were used as measures of net income Each was converted from nominal to real terms by dividing by PPIFinished goods Analysts’ estimates Consensus analysts’ estimates of future years’ earnings per share were taken from the I/B/E/S summary statistics data maintained on WRDS The variables in this file include number of estimates, and mean, median, and standard deviation of estimates for a number of fiscal periods (quarters or years) into the future I/B/E/S identifies firms in its files by ticker, but also indicates periods for which each ticker can be related to a particular firm CUSIP Compustat identifies firms in its files by GVKEY We matched the I/B/E/S ticker to the Compustat GVKEY via the CRSP/Compustat Merged data base linkage file I/B/E/S ticker is linked to CUSIP in CRSP, which is linked to PERMNO in CRSP, which is linked to GVKEY in Compustat Thus, Compustat firm-level financial data is merged with I/B/E/S firm-level analysts’ estimates We kept the summary estimate made during the latest month before the end of the firm’s fiscal year Price indices Price indices are used for two purposes: capital valuation and inventory valuation The producer price index for capital equipment (PPI-Capital Equipment) is used for the first, and the producer price index for all finished goods (PPI-Finished Goods) is used for the second Annual time series of both indices are downloaded directly from the Bureau of Labor Statistics Asset Level Tax Costs of Capital The asset level tax cost of capital comes from Dale Jorgenson and his methodology is described in Jorgenson and Yun (2001) These data provide for each asset type an estimate of the net present value of depreciation allowances, z, the rate investment tax credit, the depreciation rate, as well as the capital stock and the average corporate tax rate We compute Γ as ITC+tz and the full 39 tax cost of capital as (1-ITC-tz)/(1-t) The calculations are myopic in that they not include the impact of expected future tax changes and are assumed permanent We modify the net present values of depreciation allowances in 2002 and 2003 to account for the partial expensing rules by recomputing the z, as 70 percent the old z and 30 percent a z of in 2002 and doing the same but with 50-50 percentages in 2003 Industry Tax Costs of Capital To derive industry level values of the cost of capital for equipment and structures as well as to get the industry level depreciation rates, we use the 1997 capital flow tables of the BEA and compute the share of equipment and structures investment by asset type for each industry at approximately the 3-digit NAICS level We match these weights to the Jorgenson cost of capital figures by year for each asset type to compute a weighted average tax cost of capital in each year for each industry and we then merge that series to each firm-year based on its first listed NAICS code in Compustat Present Value of Depreciation Allowances on Past Investments To estimate the value of A, the net present value of depreciation allowances on past investments, we divide firms according to the weighted average depreciation rates on the types of equipment invested in their industry Using one over this depreciation rate as an estimate of the estimated lifetime of capital for the firm, we assume that all firms in the industry have a discount rate of 10 percent and use double declining balance depreciation until straight line depreciation exceeds it and then switch to straight line We then multiply the NPV of the relevant year times the investment to capital ratio lagged that many periods For example, if the actual depreciation allowances for a three year lived good were 333 each year (i.e., purely straight line depreciation), then we would say that depreciation allowances on investment from the previous investments  333  I  333  I         Note that the NPV of depreciation allowances  1.1  K t 1 1.1  K t 2  would be A  t  for current investment (time t) is not included in this measure It is, instead, our measure z That is why in an industry where investment lasts years, there are not terms in A We compute the NPV assuming an asset life of years for any firm with the inverse of their average depreciation rate between and 4, years for any firm with an inverse between and 5, and so on, but capped at nine years (there were a few firms with average equipment lives of a bit over ten years Note that our measure is an approximation because it assumes a constant tax law over the whole sample In other words, the net present value of depreciation allowances on current investment, z, that we get from Jorgenson varies over time but we not have the entire depreciation schedules that each z is based on so we cannot let the calculation vary for A We tried many different ways of computing the A, such as different assumptions on depreciation methods, different discount rates, and so on and found negligible impact on the regression results 40 Appendix A: Tax Adjusted q We begin by establishing the equilibrium condition that shareholders receive their required return, r, to hold equity which provides taxable dividends and capital gains so that: (A1) rVθ 1 t D  ct  E1 V   t V  t 1V  t  N t  The tax rate on dividends is θ and c is the accrual-equivalent tax rate on capital gains Dt N denotes dividends paid to shareholders in period t, V is equity value, and Vt denotes equity contributions in period t Given that dividends and capital gains are alternative forms of returns to shareholders, it is useful to summarize the relative tax penalty on dividends and capital gains with the dividend tax preference parameter, γ: (A2) γ 1 θ 1  c Given the realization based nature of capital gains taxes, γ is considered to be less than one.27 Solving (A1) forward and imposing the transversality condition that firm value cannot be infinite in a finite period provides a value equation for the firm that implies: (A3)  Vβ E  γDt  t 0 V t  N t  where β is the appropriate after-tax discount factor Equation (A3) corresponds to the straightforward intuition that firm value at time is the present discounted, tax-adjusted value of all future dividends taking into account equity contributions required to maintain a proportional shareholding in the firm Firm value maximization is subject to several constraints Dividends and equity issuance are constrained to be non-negative.28 The firm capital stock, K, evolves according to: 27 Even with similar rates on dividends and realized capital gains, γ