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Valuation-Driven Profit Transfer among Corporate Segments

Valuation-Driven Profit Transfer among Corporate Segments. Haifeng You Hong Kong University of Science and Technology Shanghai University of Finance and E conomics May 20 , 2011. Research Questions.

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Valuation-Driven Profit Transfer among Corporate Segments

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  1. Valuation-Driven Profit Transfer among Corporate Segments Haifeng You Hong Kong University of Science and Technology Shanghai University of Finance and Economics May 20, 2011

  2. Research Questions • Does equity valuation consideration induce conglomerates to transfer profits among corporate segments? Specifically, do they transfer profits from segments with relatively low valuations to those with high valuations? • If such incentives exist, do they vary with the dispersion of segment valuations? • What are the implications on equity valuation of conglomerate firms?

  3. Background: Analysts’ valuation of conglomerates

  4. Background • Valuation using multiples is still one of the most popular equity valuation techniques • Liu et al (2002), more sophisticated residual income model does not explain stock prices better than simple valuation multiples. • How to use valuation multiples to value multi-segment firms? • Estimate individual segment values using valuation multiples and reported accounting number for segments • Sum up segment value estimates to arrive at firm-level imputed values • Lang and Stulz (1994), Berger and Ofek (1995), among others • If the market adopts this valuation method mechanically, investors should have incentives to transfer profits from segments with low valuations to those with high valuations. • Can inter-segment profit transfers exist if investors are rational?

  5. Model • One firm with two segments • Unobservable economic earnings: and , independently distributed and both follow normal distributions with mean μ and precision s • Manager observe private signals of the economic earnings with noise: and , both noise term follow normal distributions with mean 0 and precision • Investors only observe the reported earnings, which may be subject to manipulation, denoted as: and Neither manager’s private signal nor b is observable to investors.

  6. Model , • Managers bear personal costs for profit transfer f(b). The cost function is a convex function with f(0)=0 and f’(0)=0. • Earnings multiples for the two segments, m and m+n, are exogenous. And n>0. • The task of the market is to determine the market value of the firm, given reported earnings and a conjecture of profit transfer: It is easy to show that:

  7. Model • The manager’s objective function: • His task is to maximize his objective function by choosing an optimal b, which implies that: • Solve for the first-order condition, we have the following proposition: Proposition 1: Given the convexity of f(b), there exists a unique equilibrium characterized by the following properties: • For any , the equilibrium amount of profit transfer . • The equilibrium amount profit transfer is an increasing function of . • On average, the equilibrium market value is lower than the imputed value estimated from valuation multiples approach, , i.e. . The expected discount is given by:

  8. Empirical Implications and Hypotheses • Property 1: For any , the equilibrium amount of profit transfer • Even if investors are rational and the market is not fooled, the manager still transfers a positive amount of profits from the segment with lower valuation to the other. • If profits are transferred to (from) segments with relatively higher (lower) valuations, those segments should report abnormally high (low) profitability. • Hypothesis 1: Ceteris paribus, the abnormal profitability of a segment is increasing with its relative valuation multiple.

  9. Empirical Implications and Hypotheses • Property 2: The equilibrium amount profit transfer is an increasing function of n. • An example with naïve investors: • Firm A: P/E=10 for segment A1 and 20 for A2. • Firm B: P/E=14 for segment B1 and 16 for B2. • Unmanaged earnings for the two segments are 50 for both firms. • Valuation under truthful reporting • Firm A=50*10+50*20=1,500 • Firm B=50*14+50*16=1,500 • Valuation if each firm transfers 10 units of profit • Market cap for A=40*10+60*20=1,600 • Market cap for B=40*14+60*16=1,520.

  10. Empirical Implications and Hypotheses • Under the rational framework, investors do not observe, but rationally anticipate the amount of profit transfer. • Given any market conjecture, the marginal benefit of profit transfer under the rational investor scenario is still larger for firms with more dispersed valuations. Other things being equal, these firms should have greater incentive to transfer profits. • Hypothesis 2: The positive association between abnormal profitability and relative industry valuation is stronger for conglomerate firms with more dispersed valuation multiples.

  11. Empirical Implications and Hypotheses • Property 3: On average, the equilibrium market value is lower than the imputed value estimated from valuation multiples approach, IV, i.e. The expected discount is given by: • The imputed value fails to adjust for the profit transfer among corporate segments. It therefore tends to overestimate firm value. • The measurement errors should be larger for these firms. • Firms with more dispersed segment valuations have greater incentives to manipulate segment earnings. • The impact of a unit of profit transfer is also higher for these firms. • Hypothesis 3: Ceteris paribus, the discounts of market values relative to the imputed values are greater for conglomerate firms with more dispersed segment valuation multiples.

  12. Data and Sample Selection • Financial data • Segment data: Compustat Segments Database • Other financial data: Compustat North America Fundamental • Stock returns and prices: CRSP • Sample selection • Sample period: 1998-2007 • Exclude financial and utilities industries • Exclude firm-years with total assets or sales revenue less than $20 million • Exclude multiple-segment firms with total sales from Compustat Segment database differing from sales revenue from the Annual Fundamental database for more than 1%

  13. Research Design • Abnormal profitability (ABROA) • ABROAs,t=(ROAs,t -IROAs,t )- Σs((ROAs,t -IROAs,t ) * ωs,t ). • ROAs,t is the ratio of operating income after depreciation and amortization to identifiable assets for segment s at year t • IROAs,t is the median ROA of all single-segment firms in the same SIC three-digit industry in fiscal year t. • ωs,t is the weight of segment sales as a fraction of the firm’s total sales, so ωt =Saless,t/(ΣsSaless,t). • Relative valuation multiple (RVALMUL) • RVALMULs,t=VALMULs,tΣs(VALMULs,t* ωs,t). • VALMULs,t is the median valuation multiples of all single-segment firms with that three-digit SIC code. • Examine three multiples: ratios of Sales, EBIT and EBITDA to enterprises

  14. Model to Test Hypothesis 1 • ABROAs,t=a0+a1RVALMULs,t+a2ABROAs,t-1+a3ABINVs,t-1 +a4RELSIZEs,t-1+a5MKTSHRs,t+a6HINDXs,t+a7SIZEt+a8BMt+εt Where • ABINVs,t is the firm- and industry-adjusted abnormal investment as calculated as (INVs,t -IINVs,t )- Σs((INVs,t -IINVs,t ) * ωs,t ). INVs,t is the ratio of segment capital expenditure to identifiable assets. IINVs,t is the median ratio of capital expenditure to total assets of all single-segment firms in the same SIC three-digit industry in fiscal year. • RELSIZEs,t is calculated as the ratio of segment assets to firm assets at year t. • MKTSHRs,t is market share, calculated as the sales of segment s as the fraction of the total sales of all firm/segments with the same three-digit SIC code. • HINDXs,t is the Herfindahl index for the industry that a segment belongs to, where industry is again defined with three-digit SIC code. • SIZEt is logarithm of market cap of equity; • BMt is the book-to-market ratio.

  15. Descriptive Statistics

  16. Correlation matrix

  17. Test of Hypothesis 1: Table 2

  18. Model to Test Hypothesis 2 • ABROAs,t=a0+a1RVALMULs,t+ a2VDISPt+ a3RVALMULs,t* VDISPt +a4ABROAs,t-1+a5ABINVs,t-1+a6RELSIZEs,t-1+a7MKTSHRs,t+a8HINDXs,t +a9SIZEt+a10BMt+εt • Where • VDISPt is the normalized dispersion of relative valuation multiples, calculated as: VDISPt=Σs(|RVALMULs,t|* ωs,t )/Σs(VALMULs,t*ωs,t), where ωs,t is the weight of segment sales as a fraction of a firm’s total sales, i.e. ωt =Saless,t/(ΣsSaless,t). All the other variables are as defined earlier. • Hypothesis 2 predicts that a3 should be positive and significant.

  19. Test of Hypothesis 2: Table 3

  20. Test of Hypothesis 3: The Model • EXVt=a0+a1VDISPt+a2SAMEINDt+a3OPMGt+a4SIZEt+a5CAPEXt +a6LEVt+a7R&Dt+a8ADVt+a9NSEGt +εt Where • EXV is the ratio of market value to estimated firm value calculated as the sum of imputed segment values using valuation multiples as described in Berger and Ofek (1995). • VDISPt is the normalized dispersion of relative valuation multiples, same as defined earlier. • SAMEINDtis a dummy variable set to 1 if all of a firm’s segments are from the same SIC two-digit industry. • OMPGtwhichis EBIT divided by net sales. • SIZEt the logarithm of the firm’s market cap in millions; • CAPEXtcapital expenditure in year t divided by net sales; • LEVtlong-term debt divided by the sum of long-term debt and the market value of equity; • R&Dt which is R&D expense divided by net sales; • ADVt advertising expense divided by net sales; and • NSEGt which is the logarithm of the number of segments that a firm has. • Hypothesis 3 suggests that a1should be negative.

  21. Descriptive statistics

  22. Correlation matrix

  23. Segment valuation dispersion of the diversification discounts: Table 5A

  24. Regression Test of Hypothesis 3: Table 5B • Regression of the diversification discount calculated using sales multiple against the dispersion of valuation multiples and other control variables

  25. Regression Test of Hypothesis 3: Table 5C • Regression of the diversification discount calculated using EBIT multiples against the dispersion of valuation multiples and other control variables

  26. Regression Test of Hypothesis 3: Table 5D • Regression of the diversification discount calculated using assets multiples against the dispersion of valuation multiples and other control variables

  27. Revenue Transfer or Cost Allocation? Table 6A • Regression of abnormal asset turnover against relative valuation multiples and other control variables

  28. Revenue Transfer or Cost Allocation? Table 6B • Regression of abnormal cost ratio against relative valuation multiples and other control variables

  29. Revenue Transfer or Cost Allocation? Table 7A • Regression of abnormal assets turnover against relative valuation multiples and their interaction with valuation dispersion and other control variables

  30. Revenue Transfer or Cost Allocation? Table 7B • Regression of abnormal cost ratio against relative valuation multiples and their interaction with valuation dispersion and other control variables

  31. Effect of Segment Valuation Dispersion on the Discounts - Change Specification (Table 8)

  32. Does the Market Fully Appreciate the Implication of Segment Valuation Dispersion on Profit Transfer? • This table presents the regression results of the following model: RETt+1=a0+a1VDISPt+a2SIZEt+a3BMt+εt

  33. Conclusions • Equity valuation incentives induce managers to transfer profits from segments with relatively low valuations to those with high valuations. • Such incentive exists even if investors are rational and perfectly anticipate and adjust for the amount of profit transfer. • Managers have greater incentives to transfer profits for firms with more divergent segment valuations. • Valuing conglomerates using multiples approach without adjusting for the inter-segment profit transfer leads to overestimated firm values. Such measurement errors increase with the dispersion of segment valuations. • The market appears to at least partially appreciate and adjust for such earnings manipulation incentives in setting the prices for conglomerate firms.

  34. Appendix: Table 1-firms operating at least in two industries

  35. Appendix: Table 1-firms operating at least in two industries

  36. Appendix: Table 2

  37. Appendix: Table 3

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