Corporate pension plans and investment choices: Bargaining or conforming?

Duygun, Meryem; Huang, Bihong; Qian, Xiaolin; Tam, Lewis H. K. Working Paper Corporate pension plans and investment choices: Bargaining or conforming? ADBI Working Paper, No. 682 Provided in Cooperation with: Asian Development Bank Institute (ADBI), Tokyo Suggested Citation: Duygun, Meryem; Huang, Bihong; Qian, Xiaolin; Tam, Lewis H. K. (2017) : Corporate pension plans and investment choices: Bargaining or conforming?, ADBI Working Paper, No. 682, Asian Development Bank Institute (ADBI), Tokyo This Version is available at: https://hdl.handle.net/10419/163187 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Tam No. 682 March 2017 Asian Development Bank Institute The Working Paper series is a continuation of the formerly named Discussion Paper series; the numbering of the papers continued without interruption or change. ADBI’s working papers reflect initial ideas on a topic and are posted online for discussion. ADBI encourages readers to post their comments on the main page for each working paper (given in the citation below). Some working papers may develop into other forms of publication. Suggested citation: Duygun, M., B. Huang, X. Qian, and L. H. K. Tam. 2017. Corporate Pension Plans and Investment Choices: Bargaining or Conforming?. ADBI Working Paper 682. Tokyo: Asian Development Bank Institute. Available: https://www.adb.org/publications/corporate-pensionplans-and-investment-choices Please contact the authors for information about this paper. Email: [email protected], [email protected], [email protected], [email protected] Meryem Duygun is a professor at Hull University Business School, United Kingdom. Bihong Huang is a research fellow at the Asian Development Bank Institute. Xiaolin Qian is an assistant manager at Standard Chartered PLC. Lewis H.K. Tam is an associate professor at the University of Macau. The views expressed in this paper are the views of the author and do not necessarily reflect the views or policies of ADBI, ADB, its Board of Directors, or the governments they represent. ADBI does not guarantee the accuracy of the data included in this paper and accepts no responsibility for any consequences of their use. Terminology used may not necessarily be consistent with ADB official terms. Working papers are subject to formal revision and correction before they are finalized and considered published. Asian Development Bank Institute Kasumigaseki Building, 8th Floor 3-2-5 Kasumigaseki, Chiyoda-ku Tokyo 100-6008, Japan Tel: +81-3-3593-5500 Fax: +81-3-3593-5571 URL: www.adbi.org E-mail: [email protected] © 2017 Asian Development Bank Institute ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Abstract This paper investigates the impacts of defined-benefit (DB) pension plans on the corporate investment choices between diversifying and non-diversifying investments. We find a firm’s DB plan coverage is negatively associated with its propensity of making a major investment. Subject to a major investment decision, however, the firm with higher DB plan coverage is more likely to diversify, i.e., acquire firms abroad or in other industries, rather than invest in fixed assets or make non-diversifying (i.e., domestic horizontal) acquisitions. Moreover, in diversifying acquisitions, they are more likely to invest in countries or industries with a strongly unionized workforce. Further analysis on post-investment performance shows that firms with higher DB plan coverage experience a greater improvement in operating profitability after a diversifying acquisition, and the improvement mainly comes from a higher asset turnover rather than cost reduction. On the other hand, DB plan sponsoring firms experience a decline in profitability after a large capital expenditure or a non-diversifying acquisition. We propose that both the bargaining motive and the conforming motive can explain these results. JEL Classification: G30; G31; G34 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Contents 1. INTRODUCTION ......................................................................................................... 1 2. INSTITUTIONAL BACKGROUND AND LITERATURE REVIEW ................................ 5 2.1 DB Plan and Employees’ Bargaining Power ................................................... 5 2.2 DB Plan and Financial Risk ............................................................................. 7 3. DATA SAMPLE, CONSTRUCTION OF VARIABLES, AND EMPIRICAL STRATEGY ................................................................................... 8 3.1 Data Sample ................................................................................................... 8 3.2 DB-plan Coverage ........................................................................................... 8 3.3 Major Investment Decision .............................................................................. 9 3.4 Empirical Strategy and Explanatory Variables ................................................ 9 3.5 Summary Statistics ........................................................................................ 10 4. EMPIRICAL RESULTS.............................................................................................. 12 5. FURTHER DISCUSSIONS AND ROBUSTNESS CHECKS ..................................... 23 5.1 Relation with Other Studies in Cross-border Acquisitions and Additional Controls for Investment Choice ............................................. 23 5.2 Endogeneity of DB Plan Coverage ................................................................ 27 6. CONCLUSION .......................................................................................................... 29 REFERENCES ..................................................................................................................... 31 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam 1. INTRODUCTION At present there is a growing amount of research on how the corporatesponsored defined-benefit (DB hereafter) pension plans affect corporate investment decisions. Among others, Rauh (2006) shows that the mandatory contribution to DB pension funds results in lower investment in fixed assets. Chang, Kang, and Zhang (2012) conclude that firms with more DB pension plan deficits are more likely to engage in value-enhancing mergers. Cocco and Volpin (2013) indicate that firms sponsoring DB pension plans are less likely to be a takeover target while the acquirer firms with DB pension plans are more likely to pay in cash than their counterparts without such plans. The above studies mainly focus on how a DB plan affects a particular type of investment. However, we still know little about its impacts on corporate investment decisions and the channels through which pension plans affect corporate investment choice. Our paper contributes to the literature by demonstrating that DB pension plans affect the firms’ decisions on capital expenditure and choice of investment industries and locations. We propose that both the bargaining motive, and the conforming motive implied by the stakeholder theory can explain firms’ investment choices. The bargaining motive predicts that firms invest strategically to reduce employees’ influence over corporate resource allocations. Previous studies and anecdotal evidences widely suggest that employees have strong incentives to fight for better compensation through threats of actions, especially in good states of firm performance. We argue that the existence of DB pension plans reflects employees’ bargaining power because unionized workers generally have a much higher participation rate in DB plans than non-unionized workers.1 When facing strong employees’ bargaining power, the firms would respond strategically by changing their investment decisions. Several theoretical models imply that firms can strengthen their bargaining position against the employees through under-investment (Baldwin 1983; Grout 1984), cross-industry diversification (Rose 1991), moving their investments towards overseas plants (Lommerud, Meland, and Sorgard 2003; and Eckel and Egger 2009), or carrying out international or vertical acquisitions (Lommerud, Staume, and Sorgard 2006).2 The conforming motive, on the other hand, predicts that firm managers would consider employees’ benefits and concerns while aiming at increasing shareholders’ value in investment decisions. Recent studies on the stakeholder theory of capital structure show that firms would take employees’ benefits into consideration when deciding their debt policies (Bae, Kang, and Wang 2013) and higher debt ratios do result in higher compensation to top managers and employees (Chemmanur, Cheng, and Zhang 1 Nowadays, although the powers of labor unions are declining and more and more firms are shifting their pension plans towards defined-contribution schemes, unionized workers still have a much higher participation rate in DB plans than non-unionized workers (Bureau of Labor Statistics 2013). At present when firms shift away from DB to DC plans, they mostly keep the pension benefits of existing employees unchanged while excluding new hires from DB pension plans. Therefore, the existence of DB plans and the extent thereof indicate the employees’ bargaining power in a firm. Besides changing their investment strategies, firms can strategically reduce the financial resources on the bargaining table by adopting a tightened financial policy to increase their bargaining power. See Perotti and Spier (1993), Klasa, Maxwell, Molina (2009), and Matsa excluding new hires from DB pension plans. Therefore, the existence of DB plans and the extent thereof indicate the employees’ bargaining power in a firm. 2 Besides changing their investment strategies, firms can strategically reduce the financial resources on the bargaining table by adopting a tightened financial policy to increase their bargaining power. See Perotti and Spier (1993), Klasa, Maxwell, Molina (2009), and Matsa (2010) for examples and detailed discussions. 1 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam 2013). Compared to definedcontribution (DC hereafter) pension plans, DB plans are not only more costly to maintain (Comprix and Muller 2011; Rauh, Stefanescu, and Zeldes 2013) but also expose sponsoring firms to additional funding risks arising from financial market fluctuations, uncertainties in participants’ longevity, employees’ mobility, among others (Rauh 2006; Shivdasani and Stefanescu 2010; Cocco and Volpin 2013). Subjecting to competitive disadvantages in their operating industries, a DB plan sponsoring firm has strong incentives of investing abroad or other industries to reduce its financial risk. Previous studies find that geographical or product-market diversification provides benefits by moderating stock return volatility (Fatemi 1984), lowering the cost of capital (Yan 2006; Hovakimian 2011; Hann, Ogneva, and Ozbas 2013), and increasing financial flexibility (Jang 2016). From the employees’ perspective, they are essentially the long-term creditors of DB plan sponsoring firms, and their propensity of receiving full pension benefits upon retirement depends on their employers’ financial viability. As a result, employees receiving DB-plan benefits also hope their employers to invest safely and reduce the cash-flow risk by diversification. In short, both bargaining motive and conforming motive indicate not only a lower propensity of investment but also an investment preference towards abroad or new industries over local or similar industries. However, the two theories predict differently on the post-investment performances, as well as choices of target countries and target industries in diversifying (cross-border or cross-industry) acquisitions. 3 Firstly, the bargaining motive implies that DB-plan sponsoring firms achieve better operating performance by gaining a stronger bargaining power against local employees. Consequently, the improvement in performance after a diversifying acquisition should mostly come from reduction of costs, especially labor-related expenses. The conforming motive, however, suggests that the DB plan sponsoring firms would improve their operating performance by other methods such as augmenting the operating efficiency rather than cutting labor-related expenses. Secondly, the bargaining motive predicts DB-plan sponsoring firms to invest in countries or industries with weak unionized workforce so as to prevent incumbent labor unions from joining force with unions in the countries or industries of new investments. The conforming motive, however, predicts DB-plan sponsoring firms would invest in countries or industries with strong unionized workforce. Although investing abroad or in other industries can reduce DB plan sponsoring firms’ cash flow risks, the decision could also be viewed as an unfriendly strategy of keeping new investments out of touch by existing employees.4 In order to gain the employees’ support for new investments, DB-plan sponsoring firms have to commit and cement their relations with unionized workforces by investing in countries or industries with strong union power but higher labor productivity.5 To the best of our knowledge, this is the first study that empirically tests the implications of both bargaining and conforming motives of corporate investment. Utilizing information gleaned from United States (US) Internal Revenue Service (IRS) Form 5500 filings that cover all US pension plans with at least 100 participants, we construct our proxy for DB plan coverage as the ratio of DB pension plan assets to 3 In the mergers and acquisitions (M&A) literature, diversifying acquisitions mostly refer to cross-industry acquisitions. However, as firms can diversify their risks by acquiring firms or assets abroad, we classify diversifying acquisitions as either crossborder or cross-industry acquisitions, and non-diversifying acquisitions as domestic horizontal acquisitions. 4 For example, a firm’s foreign subsidiary is not liable for the parent firm’s DB plan liabilities. As a result, the parent firm’s DB pension plans are protected by fewer assets. We thank the guest editor for providing this argument. 5 We thank the anonymous referee for providing this direction to disentangle the two hypotheses. 2 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam total pension assets. Examining a sample of 27,883 US manufacturing firm-years in 1990–2003, we find that DB plan coverage is negatively associated with the propensity of a major investment defined as a large capital expenditure or an acquisition of a firm. A one-standard-deviation increase in DB plan coverage is associated with a reduction of 0.062 in odds ratio for acquisition and 0.244 in odds ratio for large capital expenditure. Subject to a major investment decision, a firm with higher DB plan coverage is more likely to acquire rather than to invest in fixed assets. A one-standarddeviation of increase in DB-plan coverage is related to an increase of 0.217 in odds ratio of acquisition versus capital expenditure. Among various forms of acquisitions, a firm with higher DB plan coverage prefers diversifying acquisition over non-diversifying acquisition. A one-standard-deviation of increase in DB plan coverage is linked with an increase of 0.184 in odds ratio of diversifying acquisition versus non-diversifying acquisition. The above findings are consistent with both bargaining motive and conforming motive that higher DB-plan coverage results in less investment and the dominance of diversifying acquisitions over non-diversifying investments. To test the bargaining motive versus the conforming motive, we first examine the financial impacts of DB plan coverage by investigating changes in operating performance around major investment. Our empirical result indicates that firms with higher DB-plan coverage tend to have lower return on assets after a big capital expenditure or a non-diversifying acquisition. Further analysis shows that the result is related to a decline in operating profit margin and increase in pension expense, but unrelated to change in asset turnover. The finding is consistent with the bargaining motive that firms with higher DB plan coverage would avoid large local investments because such investments will further expose their assets to local union forces while workers in the same industry with common interests can join forces more easily. On the other hand, our empirical evidence shows that diversifying acquisitions bring in higher return on assets for firms with higher DB plan coverage, and the improvement in operating profitability is related to improvement in asset turnover rather than cost cutting effort. Therefore, the finding is inconsistent with the bargaining motive but consistent with the conforming motive, which indicates that cost-cutting is not the main motive of diversifying acquisitions. We then examine the impact of DB plan coverage on acquirers’ choice of target location and target industry in diversifying acquisitions. The bargaining motive predicts that firms with higher DB-plan coverage will invest in countries and industries with weaker union power, while the conforming motive predicts the opposite. Two measurements are employed to test these two predictions. For each cross-border acquisition, we gauge a target country’s labor power with the collective relations law index constructed by Botero et al. (2004). We then compute the average value of all countries in which a firm has carried out it cross-border deals to measure its preference of labor power in cross-border acquisitions. We measure firm’s preference of labor power in cross-industry acquisitions in a similar way by using the industry unionization rate provided by Barry Hirsch and David Macpherson available at www.unionstats.com. Our finding supports the conforming motive but not the bargaining motive. Together with the above finding for operating performances, we suggest that weakening labor bargaining power is not the main objective of diversifying acquisitions by DB plan sponsoring firms. Instead, those firms are willing to consider employees’ job-related concerns when they choose the location and industry of acquisition. 3 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam We perform additional tests to show the robustness of our main findings. First, previous studies find that other than employees’ bargaining power, cross-border acquisitions are driven by many factors such as cross-border trade activity, corporate tax rate, institutional ownership, and so on. Our main results for investment choice survive after controlling those factors. Second, we perform an additional test to address the potential endogeneity concern. Examining change in performance rather than the level of performance can eliminate omitted time-invariant firm characteristics that could cause a spurious relation between DB plan coverage and firm performance. However, some time-varying omitted firm or industry characteristics may still simultaneously affect DB plan coverage and firm performance. For example, technological development and trade liberalization may change a firm’s investment opportunities and labor policies. We address the endogeneity concern by using instrumental variable regressions with firm fixed effects. The main results are qualitatively unchanged, implying the robustness of our empirical evidences. This study contributes to the literature in two ways. Firstly, although the impact of employees’ bargaining power on corporate investment choice has been investigated theoretically, the empirical evidences are scant (Clougherty et al. 2014). We find that higher DB plan coverage induces more diversifying acquisitions rather than nondiversifying acquisitions or capital expenditures. Although the finding is consistent with the theoretical predictions proposed by Rose (1991), Lommerud, Straume, and Sorgard (2003, 2006), and Eckel and Egger (2009) that firms shift capital outside their core areas in response to increasing labor power, our evidence suggests that cutting costs is not the main objective of diversifying acquisitions by DB plan sponsoring firms. At the same time, DB plan sponsoring firms indeed avoid investing in existing industries because cost synergies are difficult to realize when labor power is strong. In sum, our findings support both bargaining and conforming motives of DB plan sponsoring firms in investment decisions. Secondly, our study sheds new light on the growing literature on cross-border mergers. Previous studies find that at the aggregate level, the volumes of cross-border merger are driven by country factors such as accounting standards, corporate governance, investor protection (Rossi and Volpin 2004; Martynova and Renneboog 2008), taxation (Scholes and Wolfson 1990; Huizinga and Voget 2009), culture (Ahern, Daminelli, and Fracassi 2015), as well as geographical distance, quality of accounting disclosure, and bilateral trade (Erel, Liao, and Weisbach 2014). At the firm level, cross-border mergers create value by binding targets from countries with lower standards of corporate governance and investor protection with the higher standards in bidders’ countries (Bris, Brisley, and Cabolis 2008; Bris and Cabolis 2008), governing targets by foreign institutional investors (Ferreira, Massa, and Matos 2010), and disciplining poorly performing CEOs in countries with weak investor protection (Lel and Miller 2015). Our results show that corporate pension plans induce firms to invest abroad but the motivations are more complicated than reducing labor influence through shifting assets abroad or to other industries. The remainder of this paper proceeds as follows. Section 2 provides institutional background and reviews prior research. Section 3 describes data and construction of key variables. Section 4 presents the main empirical results. Section 5 compares our research with other studies for cross-border M&As and provides robustness check. Finally, Section 6 concludes. 4 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Table 1: Distribution of Sample and Summary Statistics of Key Variables The sample consists of all manufacturing firms (SIC 2000–3999) that file IRS Form 5500 for their eligible pension plans with over 100 participants and are covered by CRSP/Compustat Merged Database from 1990 to 2013. Firms with missing variables for key regressions are also excluded. Panel A reports the sample distribution, and summary statistics for DBplan coverage (DB_Cover) and variables for major investment decisions. Mean values by year and overall are reported. DB_Cover is the ratio of DB-plan assets to total pensionplan assets based on information in IRS Form 5000 filings. Acquire equals one if a firm acquires at least one firm in the year. CrossBorder equals one if a firm acquires at least one firm outside the United States in the year, CrossIndustry equals one if a firm acquires at least one firm in other industry, i.e., belonging to a different 4-digit SIC code, and CBI equals one if CrossBorder equals one or CrossIndustry equals one. Panel B reports the summary statistics for explanatory variables. DB_Cover is defined above. CashFlow is the sum of net income and depreciation minus dividends, divided by lagged total assets. Q is the market-to-book ratio of assets. Size is the natural logarithm of total assets in 2005 constant value. Tang is net property, plant and equipment scaled by total assets. WC is net working capital less cash, divided by total assets. Div is cash dividend divided by lagged total assets. CumRet is the 12-month cumulative stock return in fiscal year. ΔR0At,t+2 is change in earnings before interest, taxes and depreciation, scaled by lagged total assets, from t to t+2; Δ0Mt,t+2 is change in earnings before interest, taxes and depreciation, scaled by net sales, ΔAT0t,t+2 is the change in net sales scaled by lagged total assets from t to t+2; and ΔPen_Empt,t+2 is the change in pension and postretirement expense per employees (in thousands dollars) from t to t+2. The variables are winsorized at 1st and 99th percentiles of respective distributions. Panel A Year (1) N (2) DB_Cover (3) Acquire (4) CrossBorder (5) CrossIndustry (6) CBI 1990 1,071 0.306 1991 1,092 0.307 0.047 0.008 0.036 0.038 1992 1,139 0.276 0.069 0.016 0.052 0.055 1993 1,222 0.255 0.084 0.021 0.061 0.070 1994 1,364 0.241 0.087 0.024 0.068 0.074 1995 1,441 0.225 0.122 0.037 0.090 0.102 1996 1,472 0.211 0.133 0.040 0.099 0.109 1997 1,466 0.197 0.135 0.041 0.101 0.111 1998 1,405 0.193 0.141 0.052 0.107 0.116 1999 1,062 0.197 0.143 0.038 0.107 0.116 2000 1,079 0.182 0.142 0.039 0.102 0.106 2001 1,263 0.160 0.115 0.026 0.082 0.090 2002 1,231 0.155 0.080 0.021 0.057 0.063 2003 1,234 0.162 0.079 0.018 0.057 0.060 2004 1,158 0.149 0.121 0.043 0.088 0.100 2005 1,161 0.164 0.113 0.036 0.076 0.090 2006 1,103 0.148 0.120 0.044 0.086 0.099 2007 1,079 0.145 0.135 0.046 0.091 0.101 2008 1,095 0.152 0.105 0.034 0.074 0.082 2009 1,011 0.146 0.073 0.022 0.045 0.051 2010 977 0.162 0.110 0.051 0.075 0.093 2011 946 0.169 0.113 0.046 0.089 0.098 2012 922 0.165 0.101 0.035 0.071 0.081 2013 890 0.161 0.098 0.041 0.067 0.081 2014 0.113 0.044 0.081 0.093 Total 27,883 0.194 0.109 0.034 0.079 0.088 continued on next page 11 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Table 1 continued Panel B (1) Mean (2) Median (3) Minimum (4) Maximum (5) Standard Deviation (6) N DB_Cover 0.194 0 0 1 0.297 27,883 CashFlow 0.059 0.091 –0.704 0.399 0.170 27,883 Q 1.898 1.466 0.584 8.292 1.339 27,883 Size 5.956 5.769 2.677 10.584 1.804 27,883 Tang 0.241 0.209 0.015 0.717 0.158 27,883 WC 0.145 0.141 –0.318 0.553 0.163 27,883 Div 0.011 0 0 0.107 0.019 27,883 CumRet 0.167 0.066 –0.809 3.179 0.634 27,883 ΔR0A t,t+2 –0.008 –0.004 –0.472 0.437 0.129 25,185 Δ0M t,t+2 0.006 0.002 –2.145 2.421 0.391 25,077 ΔAT0 t,t+2 –0.033 –0.010 –1.460 1.200 0.403 25,115 ΔPen_Emp t,t+2 0.186 0.047 –4.181 6.437 1.301 20,853 As the explanatory variables are lagged by one year relative to the investment decision variables, the summary statistics in Panel A for DB_Cover are for the period 1990–2013, and the summary statistics for Merger, CrossBorder, CrossIndustry, and CBI are for the period 1991–2014. Column 1 shows that the number of sample firms increases from 1990 to 1996, and then experiences abrupt drops in 1999 and 2000.12 The number of firms picks up again in 2001, but experiences a gradual decline after 2004. Consistent with the summary statistics documented in previous studies, columns 2 and 3 indicate that DB-plan coverage (DB_Cover) dropped from 30.6% in 1990 to 16.1% in 2012. Column 3 presents the intensity of overall merger activity. The number in each entry is the percentage of sample firms acquiring at least one firm in the year. On average, about 10.9% of the sample firms acquire at least one firm in a year. The overall merger activity is volatile over time, peaking at 13%–14% in 1996–2000 and plunging to 8% in 2002–2003 after the Internet bubble burst. Columns 4–6 report the intensity of merger activity by merger type. Cross-industry acquisitions are more than two times as popular as cross-border acquisitions on average, but the activities of the two types of mergers vary closely to that of the overall. This suggests we should control for time-fixed effects in models for investment choices. 4. EMPIRICAL RESULTS Table 2 reports the results of the logit regressions for major investment decisions. In column 1, the dependent variable is a merger indicator that equals one if a firm acquires at least one firm in year t+1. To address the potential simultaneity issue, all explanatory variables are lagged one year relative to the dependent variable, or they are measured at year t. The result shows that higher DB-plan coverage is associated with a lower propensity of acquisition at a statistical significance of 5%. In terms of the economic magnitude, a onestandard-deviation increase in DB_Cover is associated 12 We checked the source document by Buessing and Soto (2006) at the Center for Retirement Research at Boston College, which states that for 1999 and 2000, the information of a significant number of plans is not available. 12 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam with a 0.062 reduction in odds ratio for acquisition.13 The signs of other coefficients are consistent with previous studies on mergers and acquisitions. Firms with stronger cash flow, higher valuation and better past stock returns are more likely to acquire others. Large firms are also more likely to be an acquirer than small firms, which probably reflects the fact that large firms have a larger capacity to absorb financial risks and stronger capability to raise external funds for acquisitions than small firms. On the other hand, asset tangibility is negatively related to the propensity of acquisition. A possible explanation is that a high level of tangible assets is generally associated with low growth options. Therefore, firms with high asset tangibility tend to growth internally rather than via acquisitions. In column 2, the dependent variable is an indicator for large capital expenditure that equals one if a firm’s capital expenditure-to-assets ratio is above 90th percentile of the sample firms in year t+1. The result indicates that higher DB plan coverage is associated with a lower propensity of large capital expenditure and the result is statistically significant at 1% level. A one-standard-deviation increase in DB_Cover is associated with a 0.244 reduction in odds ratio for making large capital expenditure. Consistent with column 1, firms with stronger cash flow, higher valuation and better past stock returns are more likely to invest in fixed assets. However, as opposed to column 1, large firms are less likely to invest in fixed assets than small firms, and asset tangibility is positively associated with the propensity of large fixed-asset investment. As argued above, smaller firms have weaker ability to absorb risk and raise external financing, so they have to rely more on fixed-asset investments for growth. The positive correlation between asset tangibility and large capital expenditure is consistent with our above argument that high asset tangibility indicates low growth options. Table 2: DB Plans and Major Investment Decision 01 2 3 4 5 2013 39 1 6 7 8 , , ,, 1991 21 _ ( 1) 2 t tt t t t t t t yr i i t ind j j t ij DB Cover CashFlow Q Size Tang Prob InvDum WC Div CumRet Yrdum SIC αα α α α α ααα α α + = = + + ++ + +   = = Ψ ++ + +  ∑∑ The dependent variable is an indicator for major investment decision at t+1. In column 1, the indicator equals one if a firm completes at least one acquisition at t+1. In column 2, the indicator equals one if capital expenditure-to-assets ratio in year t+1 is above 90th percentile of sample firms in the year. The explanatory variables include DB_Cover, CashFlow, Q, Size, Tang, WC, Div, and CumRet. All explanatory variables are defined in Table 1 and are measured as of time t. Regressions are estimated with logit. Ψ is the logistic transformation of the linear combination of the explanatory variables. Therefore, the probability that firm k makes major investment in year t+1 is modelled as, 1 exp( ) ( 1) . 1 exp( ) kt kt kt kt w Prob InvDum w w β β + ′ = = ′ + where wkt is a set of explanatory variables for firm k at year t as defined above, and β is the set of estimated coefficients of the model. Year fixed effects and 2digit SIC industry fixed effects are added but not reported. The standard errors are reported in the parentheses. *,**,*** represent 10%, 5%, and 1% significant levels, respectively. continued on next page 13 In a logit model, the proportional impact of an increase of y for a variable Y on the odds of a positive outcome is estimated as exp(α×y) – 1, where α is the coefficient of Y in the model. As the coefficient of DB_Cover in model (1) is –0.214, the impact of a one-standard-deviation reduction in DB_Cover on the odds of Acquisition is exp(–0.214 × 0.297) – 1 = –0.062. 13 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Table 2 continued Indicator (1) Acquisition (2) Large Capital Expenditure DB_Cover –0.214** –0.942*** (0.095) (0.146) CashFlow 1.432*** 2.788*** (0.210) (0.288) Q 0.098*** 0.382*** (0.019) (0.023) Size 0.408*** –0.125*** (0.018) (0.027) Tang –1.709*** 6.802*** (0.215) (0.250) WC 0.051 –0.190 (0.183) (0.267) Div –1.426 –8.242*** (1.357) (1.871) CumRet 0.127*** 0.272*** (0.035) (0.035) Year fixed effects Yes Yes Industry fixed effects Yes Yes Pseudo R-sq 0.098 0.198 N 27,883 27,883 Table 3 reports the results from multinomial logit regressions for investment decision. In particular, it aims to identify the determinants for capital expenditure versus acquisition decisions. The dependent variable is an indicator that equals zero (0) if a firm makes neither large capital expenditure nor a merger at t+1, one (1) if a firm makes a large capital expenditure no mergers at t+1, and two (2) if a firm completes at least one merger at t+1. Column 1 reports the choices between no major investment (0) and large capital expenditure (1). The coefficients are close in magnitudes but in opposite signs to that of column 2 of Table 2. As large capital expenditure is the base case, the coefficients reported represent the effects of explanatory variables on the propensity of no major investment. Therefore, the result is consistent with that of column 2 of Table 2. Column 2 reports the decision between large capital expenditure (1) and acquisition (2). The result indicates that higher DB-plan coverage is significantly related with a higher propensity of acquisition rather than large capital expenditure. A one-standard-deviation increase in DB_Cover is associated with a 0.217 increase in odds ratio for acquisition versus large capital expenditure. Surprisingly, cash flow, firm valuation, and past stock return are all negatively linked with the propensity of acquisition versus large capital expenditure. Previous studies show that the merger wave is highly correlated with valuation wave because firms have strong tendency to issue stock to finance their mergers in high valuation for behavioral reasons (Shleifer and Vishny 2003; Rhodes–Kropf and Viswanathan 2004; Rhodes–Kropf, Robinson, and Viswanathan 2005). It turns out that the correlation between capital expenditure and valuation overshadows the correlation between acquisition and valuation. Consistent with Table 2, more tangible assets are related with more capital expenditure and fewer acquisitions. 14 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Table 3: DB Plans and the Choice between Capital Expenditure and Mergers The dependent variable is an indicator (InvType) that equals zero (0) if a firm neither makes large capital expenditure nor completes an acquisition at t+1, one (1) if a firm makes a large capital expenditure but does not complete an acquisition at t+1, and two (2) if a firm completes at least one acquisition at t+1. A capital expenditure is large if the capital expenditure-to-assets ratio is above 90th percentile of the sample firms in the year. All explanatory variables are measured as of time t. Regression models are estimated with multinomial logit, with case (1) as the base case. The probability that firm k choose j in year t+1 is modelled as, 1 0 exp( ) | ) ,where 0,1,2. exp( ) kt j kt kt N j kt j w Prob(InvType j w j w β β + = ′ = = = ′ Σ wkt is a set of explanatory variables for firm k at year t, which include DB_Cover, CashFlow, Q, Size, Tang, WC, Div, and CumRet, as defined in Table 1. β j is the set of estimated coefficients for choice j. As case (1) is the base case, the set of coefficients β 1 are set to zeros. Result for case (0) versus case (1) is reported in column 1, result for case (2) versus case (1) is reported in column 2. Year fixed effects and 2-digit SIC industry fixed effects are added but not reported. The standard errors are reported in the parentheses. *,**,*** represent 10%, 5%, and 1% significant levels, respectively. (1) No Major Investment (0) vs Large CAPX (1, Base) (2) Acquisition (2) vs Large CAPX (1, Base) DB_Cover 0.959*** 0.661*** (0.149) (0.168) CashFlow –2.775*** –1.071*** (0.293) (0.340) Q –0.389*** –0.232*** (0.024) (0.026) Size 0.122*** 0.518*** (0.028) (0.032) Tang –6.626*** –7.555*** (0.248) (0.302) WC 0.278 0.267 (0.273) (0.305) Div 7.053*** 4.332** (1.874) (2.151) CumRet –0.273*** –0.106** (0.036) (0.047) Year fixed effects Yes Yes Industry fixed effects Yes Yes Pseudo R-sq 0.143 N 27,883 Table 4, Panel A examines the impact of DB plan coverage on the choices of mergers. Column 1 reports the multinomial logit regression for the decision between cross-border acquisition and domestic acquisition. The dependent variable is an indicator that equals zero (0) if a firm does not complete any mergers at t+1, one (1) if a firm completes at least one domestic merger but no cross-border merger at t+1, and two (2) if a firm completes at least one cross-border merger at t+1. Result for case (2) versus case (1) is reported. It indicates that higher DB plan coverage is significantly 15 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam related with a higher propensity of cross-border versus domestic acquisition. A one-standard-deviation increase in DB_Cover is associated with a 0.135 increase in odds ratio for cross-border versus domestic acquisition. Column 2 reports the multinomial logit regression for the choice between crossindustry acquisition (2) and horizontal acquisition (1). The result indicates that higher DB plan coverage is associated with a higher propensity of cross-industry versus horizontal acquisition, and the result is statistically significant at 5% level. A onestandard-deviation increase in DB_Cover is associated with a 0.134 increase in odds ratio for cross-industry versus horizontal acquisition. Column 3 combines the cases in columns 1 and 2 and examines the decision between cross-border or cross-industry (i.e., diversifying) acquisition (2) and domestic horizontal (i.e., non-diversifying) acquisition (1). The results are qualitative the same as those reported in columns 1 and 2. DB-plan coverage is positively associated with the propensity of acquiring foreign firms or firms in other industries. The economic magnitude is that a one-standarddeviation increase in DB-plan coverage is associated with an increase of 0.184 in odds ratio of diversifying acquisition versus non-diversifying acquisition. Table 4, Panel B examines the impact of DB plan coverage on the type of investment. The dependent variable is an indicator that equals zero (0) if a firm does not make any large capital expenditure or acquisition at t+1, one (1) if a firm makes a large capital expenditure but does not complete an acquisition at t+1, two (2) if a firm completes at least one non-diversifying acquisition but no diversifying acquisition at t+1, and three (3) if a firm completes at least one diversifying acquisition at t+1. Column 1 reports the decision between non-diversifying acquisition (2) and large capital expenditure (1), and column 2 reports the decision between diversifying acquisition (2) and large capital expenditure (1). The result indicates that DB-plan coverage has a statistically insignificant impact on the decision between nondiversifying acquisition and large capital expenditure, while it is positively related to the propensity of diversifying acquisition versus large capital expenditure. A possible explanation for the difference is that both capital expenditure and non-diversifying acquisition are mainly for expanding local production facilities. As a result, the choice between the two should not result in a significant difference in labor bargaining power and financial risk. On the other hand, a diversifying acquisition allows the acquirer to stay further away from labor power in its core business or to diversify its financial risk. Therefore, firms with stronger DB-plan coverage are inclined to acquire foreign firms or firms in other industries. Although the results above could suggest that firms stay away from labor power by acquiring firms abroad or in other industries, it is also possible that firms maintain DB plans in order to gain support from existing employees and labor unions for their investment plans. For example, foreseeing weakening bargaining power as a result of diversifying acquisitions, existing employees and labor unions may strongly oppose the investments unless they get the employers’ guarantee of keeping employees’ benefits untouched. There are two potential ways to gain support from labor unions. First, firms can pre-commit not to reduce employees’ benefits after acquisition. Second, firms can invest in countries or industries with strong presence of unionized workforce as a signal to respect the collective bargaining rights. 16 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Table 4: DB Plans and Type of Acquisition Panel A reports the multinomial logit regressions for the choice between different types of acquisition. In column 1, the dependent variable is an indicator that equals zero (0) if a firm does not complete an acquisition at t+1, one (1) if a firm completes at least one domestic acquisition but no cross-border acquisition at t+1, and two (2) if a firm completes at least one cross-border acquisition at t+1. In column 2, the dependent variable is an indicator that equals zero (0) if a firm does not complete an acquisition at t+1, one (1) if a firm completes at least one horizontal acquisition but no cross-industry acquisition at t+1, and two (2) if a firm completes at least one cross-industry acquisition at t+1. In column 3, the dependent variable is an indicator that equals zero (0) if a firm does not complete an acquisition at t+1, one (1) if a firm completes at least one domestic horizontal (i.e., non-diversifying) acquisition but no cross-border or cross-industry (i.e., diversifying) acquisition at t+1, and two (2) if a firm completes at least one cross-border or cross-industry acquisition at t+1. Case (1) as the base case. Result for case (2) versus case (1) is reported. Panel B reports the multinomial logit regression for the choice between large capital expenditure and different types of acquisition. The dependent variable is an indicator that equals zero (0) if a firm neither makes large capital expenditure nor completes an acquisition at t+1, one (1) if a firm makes a large capital expenditure but does not complete an acquisition at t+1, two (2) if a firm completes at least one non-diversifying acquisition but no diversifying acquisition at t+1, and three (3) if a firm completes at least one diversifying acquisition at t+1. Case (1) as the base case. Result for case (2) versus case (1) is reported in column 1 and result for case (3) versus case (1) is reported in column 2. The explanatory variables include DB_Cover, CashFlow, Q, Size, Tang, WC, Div, and CumRet. All explanatory variables are defined in Table 1 and are measured as of time t. Year fixed effects and 2-digit SIC industry fixed effects are added but not reported. The standard errors are reported in the parentheses. *,**,*** represent 10%, 5% ,and 1% significant levels, respectively. Panel A (1) Cross-border (2) vs Domestic (1, base) (2) Cross-industry (2) vs Horizontal (1, Base) (3) Diversifying (2) vs Non-diversifying (1, Base) DB_Cover 0.425** 0.424** 0.568** (0.171) (0.192) (0.230) CashFlow –0.292 0.202 0.190 (0.405) (0.378) (0.416) Q 0.003 –0.008 –0.015 (0.035) (0.033) (0.034) Size 0.208*** 0.089*** 0.139*** (0.031) (0.032) (0.034) Tang 1.018** –1.082*** –1.002** (0.419) (0.412) (0.457) WC 1.201*** 0.963*** 1.167*** (0.348) (0.355) (0.379) Div –1.768 2.201 3.537 (2.564) (3.005) (3.109) CumRet 0.137** 0.010 0.046 (0.069) (0.072) (0.082) Year fixed effects Yes Yes Yes Industry fixed effects Yes Yes Yes Pseudo R-sq 0.093 0.089 0.094 N 27,883 27,883 27,883 continued on next page 17 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Table 4 continued Panel B (1) Non-diversifying (2) vs Large CAPX (1, Base) (2) Diversifying (3) vs Large CAPX (1, Base)` DB_Cover 0.179 0.762*** (0.251) (0.174) CashFlow –1.123** –0.986*** (0.460) (0.357) Q –0.218*** –0.239*** (0.035) (0.028) Size 0.407*** 0.548*** (0.042) (0.033) Tang –6.655*** –7.791*** (0.493) (0.312) WC –0.661 0.530* (0.429) (0.314) Div 1.333 5.102** (3.386) (2.215) CumRet –0.136* –0.097** (0.081) (0.049) Year fixed effects Yes Yes Industry fixed effects Yes Yes Pseudo R-sq 0.136 N 27,883 Tables 5 and 6 disentangle the bargaining motive from the conforming motive of DB plan sponsoring firms who engage in diversifying acquisitions. If firms intentionally reduce labor bargaining power by acquiring firms abroad or in other industries, we should observe greater benefits accrued to firms where the labor power proxied by DB-plan coverage is stronger. This prediction is supported by Rose (1991)’s finding that compared with focused firms, diversified firms can endure longer labor strikes and therefore reduce wage settlements. Besides, DB plan sponsoring firms would invest mainly in countries or industries with weak presence of labor unions, and they are more likely to reduce costs including labor costs after acquisition. In contrast, although the conforming view also predicts that DB plan sponsoring firms are more likely to invest abroad and other industries to reduce financial risks than non-sponsoring firms, it suggests that those firms are more likely invest in countries and industries with strong unionized workforce and less likely to reduce labor benefits after acquisition. Empirically, we regress changes of the performance variables on the indicators of major investments. The performance variables include: (1) ΔR0At,t+2, change in earnings before interest, taxes and depreciation, scaled by lagged total assets, from t to t+2; (2) Δ0Mt,t+2, change in earnings before interest, taxes and depreciation, scaled by net sales, from t to t+2; (3) ΔAT0t,t+2, where ATO is net sales scaled by lagged total assets; and (4) ΔPen_Empt,t+2 where Pen_Emp is the pension and retirement expense scaled by number of employees (in thousands of dollars). Indicators of major investments include: (1) an indicator that equals one if a firm makes a large capital expenditure or non-diversifying acquisition (Local); (2) CBI as defined above. We combine large capital expenditure and non-diversifying acquisitions into a group because Table 4 shows that DB_Cover does not affect the choice between the two. 18 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Besides, we interact the investment indicators with DB_Cover to examine if the benefit from a particular type of investment is greater for firms with higher DB plan coverage. We run the following ordinary least squares (OLS) model regression for the change in operating performance: ,2 0 1 1 1 1 2 3 1 3 1 4 4 ,2 2013 39 , , ,, 1991 21 __ _ 2 tt t a t t t t a t t t a tt yr i i t ind j j t t ij Performance Local CBI DB Cover DB Cover Local DB Cover CBI Firm Firm Yrdum SIC ββ β β β β ββ β βε + ++ + ++ = = ∆ =+ ++ + × ′′ + × + +∆ + ++ ∑∑ (1) The dependent variable, ΔPerformancet,t+2, is one of ΔR0At,t+2, Δ0Mt,t+2, ΔAT0t,t+2, and ΔPen_Empt,t+2, as defined above. Firm is a vector of firm characteristics including Q, Size, Tang, WC and Div as defined in Table 1, in year t. ΔFirm is the change in firm characteristics (Firm) from t to t+2. Note that CashFlow is not included because it is highly correlated with R0A. We include ΔFirm in the regressions to control for changes in firm policies that are unrelated to the investment decisions but affect change in firm performance. Nevertheless, we report results with and without ΔFirm in Panel A and Panel B of Table 5. Panel A shows that without a major investment, DB plan coverage has a positive and significant effect on firm performance. This suggests DB pension plans do not negatively affect firm performance. However, large capital expenditures or nondiversifying acquisitions negatively affect firms’ performance, especially for firms with high DB-plan coverage (column 1) as indicated by the negative coefficient of the interaction term. To further investigate change in return on assets (ΔR0At,t+2), we use change in operating profit margin (Δ0Mt,t+2), change in asset turnover (ΔAT0t,t+2), and change in fixed asset to employee ratio (ΔPen_Empt,t+2) as dependent variables in columns 2, 3 and 4 respectively.14 The regression results show that all operating profit margin declines, after such investments especially for firms with higher DB plan coverage. Besides, pension expense per employee for firms with high DB plan coverage increases. Therefore, large capital expenditures and non-diversifying acquisitions seem to destroy value for DB plan sponsoring firms by reducing both their operating efficiency and ability to cut costs. The finding is consistent with the bargaining motive of DB plan sponsoring firms. The new investments in local and existing businesses expose more firm assets to unionized workforce, making firms difficult to improve profitability by reducing costs. As a result, DB plan sponsoring firms tend to avoid investing in existing businesses locally. While diversifying acquisitions also result in worse operating profitability (column 1), the effect is less negative for firms with higher DB-plan coverage. The finding suggests that diversifying acquisitions create more value for DB plan sponsoring firms than non-sponsoring firms. Columns 2, 3 and 4 show that the relative outperformance of DB plan sponsoring firms is mainly due to an improvement in asset turnover. On the other hand, there is no indication that those firms reduce operating expense after investing abroad or other industries, as suggested by insignificant coefficients of the interaction term in regressions for Δ0Mt,t+2 and ΔPen_Empt,t+2. Therefore, cutting costs is unlikely to be a major motivation for DB plan sponsoring firms to invest abroad or in new industries, which is inconsistent with the bargaining motive but consistent with the conforming motive. 14 Notice that ROA = OM × ATO. 19 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Table 5: The Effects of Large Capital Expenditures and Domestic Horizontal Acquisitions on Operating Performance ,2 0 1 1 1 1 2 3 1 3 1 4 4 ,2 2013 39 , , ,, 1991 21 __ _ 2 tt t a t t t t a t t t a tt yr i i t ind j j t t ij Performance Local CBI DB Cover DB Cover Local DB Cover CBI Firm Firm Yrdum SIC ββ β β β β ββ β βε + ++ +++ = = ∆ =+ ++ + × ′′ + × + +∆ + ++ ∑∑ The dependent variable, ∆Performancet,t+2, is one of the following variables. ΔR0At,t+2 is change in earnings before interest, taxes and depreciation, scaled by lagged total assets, from t to t+2; Δ0Mt,t+2 is change in earnings before interest, taxes and depreciation, scaled by net sales, from t to t+2; ∆AT0t,t+2 is the change in net sales scaled by lagged total assets from t to t+2; and ∆Pen_Empt,t+2 is the change in pension and retirement expense scaled by number of employees (in thousands of dollars per employee). Regressions are estimated with ordinary least squares (OLS) method. Local is an indicator for large capital expenditure or non-diversifying acquisition, and CBI is an indicator for diversifying acquisition. Firm is a vector of firm characteristics including Q, Size, Tang, WC and Div as defined in Table 1, in year t. ΔFirm is the change in Firm from t to t+2. Year fixed effects and 2-digit SIC industry fixed effects are added but not reported. The standard errors are reported in the parentheses. *,**,*** represent 10%, 5%, and 1% significant levels, respectively Panel A (1) ∆R0A (2) ∆0M (3) ∆AT0 (4) ∆Pen_Emp Local –0.017*** 0.005 –0.108*** 0.028 (0.004) (0.009) (0.010) (0.027) CBI –0.013*** –0.005 –0.048*** –0.134*** (0.004) (0.009) (0.012) (0.033) DB Cover 0.010*** 0.012** 0.013 0.164*** (0.003) (0.005) (0.009) (0.042) Local×DB Cover –0.016** –0.034** –0.031 0.208* (0.008) (0.014) (0.028) (0.120) CBI×DB Cover 0.017** 0.013 0.070*** –0.175 (0.007) (0.015) (0.026) (0.120) Q –0.003*** 0.015*** –0.023*** 0.000 (0.001) (0.004) (0.003) (0.008) Size –0.003*** –0.006*** –0.021*** 0.041*** (0.001) (0.002) (0.002) (0.007) Tang 0.058*** 0.055** 0.204*** –0.071 (0.007) (0.024) (0.020) (0.081) WC –0.075*** –0.133*** –0.263*** 0.083 (0.007) (0.025) (0.020) (0.064) Div –0.071 –0.390*** –0.066 0.733 (0.049) (0.139) (0.148) (0.522) CumRet –0.011*** –0.034*** –0.080*** 0.023 (0.002) (0.006) (0.005) (0.015) Year fixed effects Yes Yes Yes Yes Industry fixed effects Yes Yes Yes Yes Adj. R–sq 0.05 0.01 0.10 0.05 N 25,185 25,077 25,115 20,853 continued on next page 20 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam 5.2 Endogeneity of DB Plan Coverage This subsection aims to account for endogeneity concerns. For example, technological development may affect a firm’s relationship with labor unions as well as its investment opportunity set. While a firm’s technological development can enlarge its investment opportunities by allowing it to expand its production capacity, it may also reduce its reliance on labor forces and its incentives to provide DB pension plans to retain workers. Similar effects exist when trade agreements are set up to reduce barriers to trade. Trade liberalization provides more economic motivations for cross-border investments but trade agreements also affect firms’ incentives to retain workers and reduce the power of labor unions. Without controlling those unobserved firm-specific or market-wide heterogeneous factors, the estimation results might be biased and inconsistent. To address the endogeneity concern for the relationship between DB plan coverage and change in operating performance after major investments, we re-run models for Table 5 Panel B using instrumental variable (IV) regressions. We further add firm fixed effects to the regressions to control for omitted time-invariant firm characteristics that could cause a spurious relation between DB plan coverage and firm performance. Adding firm fixed effects to the regressions can also control for firm-specific factors that affect the investment choices, as Table 4 shows that firms making one form of investment may be fundamentally different from firms making another form of investment. We perform the IV regressions with the following instruments: (1) the industry unionization rate; (2) the 5-year lagged value of the natural logarithm pension and postretirement expenses per employee, which is motivated by Bae, Kang, and Wang (2011) who use it as an instrument for employee treatment index; and (3) the 5-year lagged value of the natural logarithm of number of employees. We expect lagged values of labor related variables are good instruments for current DB plan coverage for the following reason. Although a firm’s investment decision could be affected by its existing labor policies, it is much less likely that it could be affected by its labor policies long time ago. Therefore, it is unlikely that a firm’s labor policies a long time ago affect its current investment decision beyond the correlation between past and current pension policies. The industry unionization rate is used as an instrument because labor unions are found to be associated with DB pension plans and many DB plans were collectively bargained when labor unions were strong. It is the most widely used proxy for labor bargaining power in previous studies (e.g., Klasa, Maxwell, and Ortiz–Molina 2009; Matsa 2010; Shivdasani and Stefanescu 2010; Chang, Kang, and Zhang 2012). Simple correlation analysis shows that the correlations between DB_cover and those instrumental variables are between 0.05 and 0.44 and significant at 1% level. Table 8 reports the IV regression results for change in performance with DB plan coverage and its interaction with indicator for cross-border or diversifying acquisitions instrumented. The instruments include those listed above and their interaction with Local and CBI. The J-statistics of all models except the last column are statistically insignificant, suggesting that our IV models are well-specified. The IV regression results are generally consistent with those of the OLS regressions, except that the coefficients of Local×DB_Cover are still negative but insignificant for the regressions of 27 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam ΔR0At,t+2 and Δ0Mt,t+2, while the coefficients of Local×DB_Cover and CBI×DB_Cover become statistically significant for the regression of ΔPen_Empt,t+2.17 Table 8: Robustness Check: Instrumental Variable Model for Change in Operating Performance A two-stage firm fixed-effects model is estimated for change in performance from year t to t+2. In first stage DB_Covert, DB_Covert × Localt+1, and DB_Covert × CBIt+1 are respectively regressed on (1) industry unionization rate, (2) the 5year lagged value of pension and postretirement expenses per employee, (3) the 5-year lagged value of the natural logarithm of number of employees, and their interaction terms with Local and CBI , together with other exogenous variables and year dummies. The predicted values of the three variables are then included in the second-stage regression as follows: ,2 0 1 1 1 1 2 3 13 14 2013 4 ,2 , , 1991 ._ . (_ ) .(_ ) tt t a t t t t a tt t a t t yr i i t t i Performance Local CBI Inst DB Cover Inst DB Cover Local Inst DB Cover CBI Firm Firm Yrdum Firm fixed effects ββ β β β ββ ββ ε + ++ ++ += ∆ =+ ++ + ′ × + ×+ + ′∆+ + + ∑ Firm is a vector of firm characteristics including Q, Size, Tang, WC and Div as defined in Table 1, in year t. ΔFirm is the change in Firm from t to t+2. Year-fixed effects and firm-fixed effects are added but not reported. The standard errors are reported in the parentheses. *,**,*** represent 10%, 5%, and 1% significant levels, respectively. (1) ∆R0A (2) ∆0M (3) ∆AT0 (4) ∆Pen_Emp Local –0.005 0.030* –0.083* –0.089 (0.011) (0.018) (0.044) (0.098) CBI –0.047*** –0.023 –0.134** 0.074 (0.014) (0.022) (0.052) (0.120) DB_Cover 1.395*** 1.133** 5.538*** –8.539*** (0.360) (0.565) (1.378) (3.181) Local × DB_Cover –0.030 –0.094 –0.025 0.743** (0.041) (0.064) (0.157) (0.344) CBI × DB_Cover 0.139*** 0.088 0.448** –0.961** (0.046) (0.072) (0.176) (0.398) ΔQ 0.035*** 0.029*** 0.106*** –0.071*** (0.003) (0.005) (0.011) (0.025) ΔSize 0.069*** 0.046*** 0.193*** –0.345*** (0.007) (0.012) (0.028) (0.063) ΔTang –0.053 –0.004 0.342** –1.571*** (0.040) (0.063) (0.153) (0.343) continued on next page 17 A potential concern for using industry unionization rate as an instrument is that industry unionization rate is found to be correlated with corporate financing decisions (Matsa 2010) and cash holding (Klasa, Maxwell, and Ortiz–Molina 2009) by previous studies. It is possible that industry unionization rate also affects change in operating performance directly rather than via DB plan coverage. In an unreported test, we re-run regressions for Table 5 Panel B with industry unionization rate and firm-fixed effects. We found that industry unionization rate is uncorrelated with ΔROAt,t+2, ΔOMt,t+2 and ΔATOt,t+2, but it is negatively correlated with ΔPen_Empt,t+2. In other words, industry unionization rate fulfills the exclusion restriction for regressions for ΔROAt,t+2, ΔOMt,t+2 and ΔATOt,t+2. 28 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Table 8 continued (1) ∆R0A (2) ∆0M (3) ∆AT0 (4) ∆Pen_Emp ΔWC 0.136*** 0.135*** 0.374*** –0.334** (0.019) (0.030) (0.074) (0.159) ΔDiv –0.007 –0.006 –0.113 0.039 (0.053) (0.092) (0.224) (0.443) Q 0.014*** 0.029*** 0.028* –0.073** (0.004) (0.007) (0.016) (0.037) Size 0.004 0.006 –0.019 –0.250*** (0.009) (0.015) (0.036) (0.085) Tang 0.190*** 0.221*** 0.898*** –1.895*** (0.050) (0.079) (0.192) (0.429) WC 0.035 0.008 0.125 –0.458 (0.037) (0.058) (0.142) (0.299) Div –0.561*** –0.414 –1.676*** –0.154 (0.166) (0.265) (0.645) (1.405) CumRet –0.014*** –0.032*** –0.070*** 0.022 (0.003) (0.005) (0.013) (0.029) Year fixed effects Yes Yes Yes Yes Firm fixed effects Yes Yes Yes Yes Wald chi-2 (p-value) 0.00 0.00 0.00 0.00 Over-identification J-stat (p-value) 0.18 0.97 0.11 0.00 N 16,920 16,868 16,875 16,209 6. CONCLUSION Using a sample of 27,883 firm-years, we examine the US manufacturing firms in 1990–2013 and find that DB-plan coverage is negatively associated with the propensity of making a major investment defined as a large capital expenditure or an acquisition of a firm. However, subject to a major investment decision, a firm with higher DB-plan coverage is more likely to acquire other firms than to invest in fixed assets. More interestingly, we find that among acquisitions, a firm with high DB-plan coverage prefers diversifying acquisitions (cross-border or cross-industry) to non-diversifying (domestic horizontal) acquisitions or capital expenditures. The findings are consistent with both the bargaining motive and conforming motive of investments for DB plan offering firms. However, further evidence shows that although firms with higher DB-plan coverage experience a greater improvement in operating profitability and asset turnover after diversifying acquisitions. Besides, in those investments, they tend to invest in countries or industries with stronger unionized workforce. Therefore, their investments are likely to be driven by the conforming motive rather than the bargaining motive. In contrast, firms with higher DB-plan coverage experience a greater reduction in operating profitability and profit margin after large capital expenditures or nondiversifying acquisitions and an increase in pension expense. The finding suggests that cost cutting is difficult after investing in existing businesses, especially when existing employees are strongly unionized. As a result, firms tend to under-invest in existing businesses to avoid more assets being exposed to labor bargaining. 29 ADBI Working Paper 682 Duygun, Huang, Qian, and Tam Our results suggest that DB plan sponsoring firms have multiple considerations in their investment decisions. On one hand, most of their employees are unionized and have strong ability and incentives to bargain. 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