Corporate Diversification and Long-run Performance

of SEO Firms--Evidence from Taiwan--

Jeng-Ren ChiouMing-Yuan Li

Ting-Kai ChouChao-Ya Wan

Outline

1. Introduction1. Introduction

2. Hypothesis Development 2. Hypothesis Development

3. Data and Empirical Design 3. Data and Empirical Design

4. Empirical Results Analysis 4. Empirical Results Analysis

5. Conclusions 5. Conclusions

Introduction

A large and growing literature examines the consequences of corporate diversification.

diversified firms sell at a discount relative to focused firms.

stock prices tend to fall when firms announce focus-decreasing corporate actions.

The prior evidence suggests that the costs of corporate diversification exceed the benefits.

Introduction

Recent papers try to identify some of the costs of diversification by examining the investment patterns of diversified firms.

Scharfstein (1998) Rajan, Servaes and Zingales (2000)

Cross-subsidization phenomenon A conglomerate firm always invest more in

weak division than their stand-alone industry peers.

diversified firms would invest more in relatively poorer projects than focused firms

Introduction

There is little empirical work that directly identifies the benefits of diversification.

Lewellen (1971) - coinsurance effects increase a diversified firms’ debt capacity relative to the aggregate debt capacity of its individual divisions as stand-alone firms.

Williamson (1975) , Stein (1997), Lamont (1997) and Shin and Stulz (1998) - internal capital market and efficiently allocating cash across divisions.

Research Objective

We try to provide evidence on the potential benefits associated with corporate diversification

examine the effect of diversification on subsequent performance following the equity issues.

The direction of relationship between diversification and post-SEO performance is unclear.

Hypotheses Development

Internal capital market hypothesis In diversified firms, profitable product lines

can allocate much needed capital to negative cash flow businesses.

There may also be positive synergies between the lines of businesses of the issuing firms.

Under the assumptions of efficient internal capital markets and/or synergies, we would expect a positive relationship between diversification and post-SEO long run performance.

Hypotheses Development

Resource misallocation hypothesis Berger and Ofek (1995) provide an exposition

on how corporate diversification can decrease firm value.

There may be a higher propensity for the misallocation of capital across business segments through inefficient cross-subsidization in a diversified firm. Rajan, Servaes, and Zingales (2000) Scharfstein and Stein (2000).

We expect a negative relationship between diversification and post-SEO long run performance.

Data

Seasoned equity offerings on the Taiwan Securities Exchange over 1995-2002.

exclude financial companies and firms without complete data.

A total of 386 equity issues remain after our selection criteria.

Number of SEOs issued in the period 1995 to 2002 on the Taiwan Securities Exchange 507

Less: utilities and financial firms (54)

Less: missing data on stock returns within 3 years after the SEO (35)

Number of firms conducting SEO with complete returns in the sample period 418

Less: missing data on diversification calculation-related variables (12)

Less: missing data on regression control variables (20)

Sample 386

Sample Selection

Sample Distribution by Year

SEO year Sample size Gross proceeds/ Firm size (%)

Gross proceeds (million NT$)

Gross proceeds (million US$)

1995 53 2.268 118.630 4.357 1996 61 3.672 265.119 9.658 1997 117 9.153 588.257 18.089 1998 75 6.535 470.109 14.618 1999 36 3.979 239.752 7.633 2000 28 9.950 785.171 23.757 2001 5 0.793 227.400 6.516 2002 11 3.113 910.058 26.226 Total 386 39.463 3604.496 110.854

Most of the offerings occur in the 1996-1998 periods. Due to the economic recession in Taiwan capital

markets, only five offerings conducted in 2001.

Sample Distribution by Industry

Industry TEJ Sample

size Gross proceeds/ Firm size (%)

Gross proceeds (million NT$)

Gross proceeds (million US$)

Cement 11 3 1.278 310.300 9.687 Food 12 16 2.965 94.781 3.053 Plastics 13 11 1.703 420.670 13.295 Textiles 14 36 3.394 152.642 4.920 Electric, Machinery 15 20 3.626 121.198 3.815 Appliance, Cable 16 12 1.227 263.795 8.424 Chemical 17 15 6.833 145.329 4.503 Glass, Ceramics 18 4 5.819 206.946 6.653 Paper, Pulp 19 4 1.302 81.114 2.709 Steel, Iron 20 22 8.606 454.297 14.276 Automobile 21 1 1.558 94.500 3.470 Transportation 22 2 0.696 255.275 7.937 Elect.& Computer 23 143 7.706 563.594 17.617 Construction 25 51 8.434 767.447 24.024 Transportation 26 13 5.509 498.001 16.868 Tourism 27 2 1.805 108.197 3.342 Department Stores 29 8 6.385 439.214 13.646 Others 99 23 4.524 273.005 8.574

The SEO sample varies by industry from 143 offerings in the electronics classification to 1 offering from automobile industry.

Methodology

Buy-and-Hold Abnormal Returns (BHAR)

BHAR represents the monthly compounding return for issuing firm from a buy and hold strategy, adjusted by the holding period return on the benchmark during the corresponding period. size-matched portfolio B/M-matched portfolio size-and-B/M-matched portfolio

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1ttB,

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1tti,Ti, )R(1)R(1BHAR

Methodology

Measure of Diversification (1) Herfindahl index (HINDEX) - reflects the

degree to which the sales of a firm are concentrated within its divisions.

The variable HINDEX equals 1 for all single-segment firms and is less than 1 for multiple-segment firms.

Smaller levels of HINDEX correspond to less industry focus and greater diversification.

2

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it itN

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jjitjitit SALESALEHINDEX

Methodology

Measure of Diversification (2) Diversification Dummy (DIV) - identify

whether a firm has multiple segments or not. The DIV equals 1 if the firm has multiple

segments, and 0 otherwise.

Mean Std. Q1 Median Q3

Number of Segments 2.101 1.145 1 2 3

Rev.-based Herfindahl Index 0.781 0.237 0.557 0.880 1.000

Offering price (NT$) 37.594 30.591 20 28 42

Issue Size (million NT$) 436.029 1038.610 60.000 117.545 307.294

Total assets (billion NT$) 10.206 16.128 2.669 4.928 9.940

Market value (billion NT$) 17.414 38.834 3.786 6.746 14.542

Book-to-market ratio 0.417 0.237 0.244 0.367 0.547

Age 5.829 8.483 0 2 6

Hot market 0.655 0.476 0 1 1

R&D expense ratio (%) 1.407 2.182 0.000 0.470 2.100

Tobin Q 2.337 1.806 1.387 1.805 2.531

Subsequent SEO activity 0.684 0.466 0 1 1

Debt ratio 0.441 0.146 0.354 0.453 0.549

Return on assets (%) 8.431 6.998 4.230 7.170 10.780

Cash flow/total assets (%) 2.807 11.390 -1.946 3.671 8.764

We find that SEO issuers, on average, have two segments.

The mean Herfindahl index is 0.781.The mean gross proceeds are 436.03 million NT dollars or US$ 13.03 million. Compared with other developed capital market like the U.S., and Japan, gross proceed for Taiwan SEOs are much smaller.

Empirical Results-Summary Statistics of

SEOs-

Empirical Results-Post-SEO Long-run

Performance-

Taiwan SEO firms don’t exhibit long run under-performance The result is robust to various benchmarks

Single firms(N=136)

Multi-Segments firms (N=250)

Single-Segment firms vs.Multi-Segments firms

Mean Median Mean MedianDiff. in Mean

Diff. in Median

Number of segments 1.000 1.000 2.700 2.000 -26.80*** -1.000

Rev.-based Herfindahl Index

1.000 1.000 0.662 0.627 24.77*** 0.373

Offering price (NT$) 41.405 29.500 35.521 27.000 1.71* 2.500

Issue Size (million NT$) 484.368 128.000 409.733

105.250 0.67 22.750

Total assets (billion NT$) 8.130 4.196 11.336 5.215 -2.11** -1.019

Market value (billion NT$) 17.200 6.506 17.531 6.827 -0.08 -0.321

Book-to-market ratio 0.399 0.354 0.427 0.370 -1.07 -0.016

Age 3.941 1.000 6.856 3.000 -3.61*** -2.000

Hot market 0.581 1.000 0.696 1.000 -2.23** 0.000

R&D expense ratio (%) 1.840 0.450 1.173 0.475 2.49** -0.025

Tobin Q 2.648 1.920 2.168 1.765 2.20** 0.155

Subsequent SEO activity 0.728 1.000 0.660 1.000 1.37 0.000

Debt ratio 0.426 0.432 0.449 0.461 -1.49 -0.029

Tech industry 0.412 0.000 0.348 0.000 1.24 0.000

Empirical Results-Summary Stat. by Issuer-

Type-

Relative to focused issuers, the diversified issuers have lower offering price and R&D intensity, but have longer listing history and larger assets amounts.

Univariate Comparisons

Panel A-1: Post-issue long-run buy-and-hold stock returns for single-segment firms First year First 2 years First 3 years Abnormal

Return (%)

Wealth Relative

Abnormal Return (%)

Wealth Relative

Abnormal Return (%)

Wealth Relative

A. Based on size-matched portfolios Performance 2.69 1.03 -8.16* 0.91 -17.25*** 0.80 Significant test 0.73 -1.67 -3.00 B. Based on B/M-matched portfolios Performance 2.49 1.03 -6.62 0.93 -13.95*** 0.83 Significant test 0.71 -1.43 -2.58 C. Based on size-and-B/M-matched portfolios Performance 1.37 1.01 -6.49 0.93 -13.41*** 0.84 Significant test 0.40 -1.42 -2.52 Panel A-2: Post-issue long-run buy-and-hold stock returns for multi-segments firms A. Based on size-matched portfolios Performance 5.55** 1.06 7.67** 1.08 8.82* 1.11 Significant test 2.07 1.98 1.94 B. Based on B/M-matched portfolios Performance 6.46** 1.07 9.18** 1.10 13.72*** 1.17 Significant test 2.49 2.42 3.24 C. Based on size-and-B/M-matched portfolios Performance 4.38* 1.04 7.57** 1.08 10.27** 1.13 Significant test 1.67 1.98 2.40 Panel A-3: Test-statistics for difference in excess return (%) Benchmark portfolio t-stat. z-stat. t-stat. z-stat. t-stat. z-stat. size-matched -0.58 1.29 -2.60*** 0.75 -3.75*** 2.30** B/M-matched -0.84 1.04 -2.69*** 1.36 -4.17*** 4.13*** size-and-B/M-match -0.64 0.74 -2.40** 1.22 -3.60*** 2.07**

The 3-year period buy-and-hold abnormal returns for single-segment SEO firms show significant underperformance phenomenon.

The result is robust to various benchmarks including size-matched, B/M matched, and size-and-B/M matched portfolios.

However, the post-issue buy-and-hold abnormal returns for multiple-segment SEO firms show significant outperformance.

The result is also robust to various benchmarks.

A test that the mean post-issue performance for single- and multiple-segment issuers are equal is rejected at 1% level.

Regression Results

Model 1 Model 2 Variable Coefficient t-stat. VIF

Coefficient t-stat. VIF

Experimental variable HINDEX -0.486*** -3.29 1.101 - - - DIV - - - 0.265*** 3.66 1.088 Control variables AGE 0.012 0.32 1.375 0.016 0.44 1.343 RDRATIO 0.029* 1.65 1.325 0.032* 1.83 1.335 TOBIN_Q -0.038* -1.80 1.316 -0.038* -1.78 1.317 ISSUESIZE -0.025 -0.92 1.178 -0.027 -0.98 1.172 SSEO 0.192** 2.52 1.124 0.206** 2.72 1.126 TECH 0.482*** 5.46 1.636 0.487*** 5.55 1.625 DEBT -0.036 -0.14 1.209 -0.043 -0.17 1.209 HOT 0.096 1.25 1.193 0.098 1.29 1.190 Intercept 0.548 1.07 0.000 0.004 0.01 0.000 Adjusted R2 0.129 0.135 F-statistic 7.331 7.650 Prob.(F-stat.) 0.000 0.000

1. The coefficient on HINDEX is negative and highly significant. Since increases in HINDEX represent increases in focus, it appears that equity-issue conducted by more focused firms occur more negative long-run performance.

2. The result supports the internal capital market hypothesis.

Regression Results-Endogeneity

Consideration-

1. Campa and Kedia (2002) suggests that firms that choose to diversify are not a random sample of firms. If this case, the estimation results using OLS will be biased.

2. We attempt to use simultaneous equation for model 1 to control for the endogeneity, and use Heckman’s (1979) two stage procedure to control for the self-selection of firms that diversify.

3. The empirical results show that there still exists a significant positive relationship between diversification and post-issue performance.

Summary

This paper is the first to examine the effect of corporate diversification on the equity issue performance.

We find that equity issues by diversified firm results in better subsequent stock price performance than equity issues by comparable focused firms.

These findings are consistent with the hypothesis that diversification improve the efficiency of internal capital-allocation process.

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