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  • 标题:Layoff and firm long-term performance.
  • 作者:Scott, Brad G. ; Ueng, Joe ; Ramaswamy, Vinita
  • 期刊名称:Academy of Strategic Management Journal
  • 印刷版ISSN:1544-1458
  • 出版年度:2011
  • 期号:July
  • 语种:English
  • 出版社:The DreamCatchers Group, LLC
  • 摘要:Downsizing is "the planned elimination of positions or jobs" (Cascio, 1993, p. 96). A key question in corporate restructuring is what role downsizing plays, and why firms' announcements are met with different stock price reactions. A downsizing action may signal organizational decline or may be part of an overall restructuring effort of management for future productivity and profitability improvements.
  • 关键词:Employee performance;Layoffs

Layoff and firm long-term performance.


Scott, Brad G. ; Ueng, Joe ; Ramaswamy, Vinita 等


INTRODUCTION

Downsizing is "the planned elimination of positions or jobs" (Cascio, 1993, p. 96). A key question in corporate restructuring is what role downsizing plays, and why firms' announcements are met with different stock price reactions. A downsizing action may signal organizational decline or may be part of an overall restructuring effort of management for future productivity and profitability improvements.

According to many financial publications, the announcements of downsizing actions are met with positive responses by investors (1) (Bleakley, 1995; Downs, 1995; Fefer, 1994; Lesly & Light, 1992; Seglin, 1996). Recently, however, casual observers are reporting that many companies which announced downsizings have not reached anticipated goals, and in fact, may be worse off than before the action as expected benefits do not come to fruition (Fefer, 1994; Lesley & Light, 1992; Margulis, 1994). Although there are success stories such as AT&T2 (Bowman & Singh, 1993), some downsized companies are met with deteriorating productivity from low morale survivors (Cascio, 1993; Lee, 1992; McCune, Beatty, and Montagno, 1988), or with insufficient workers to meet market demand (Markels & Murray, 1996; Wyatt, 1994). Even though downsizing actions are widely observed, academic literature is sparse on this form of business restructuring.

Workforce layoff has become commonplace in American businesses over the last 20 years. While these actions are typically undertaken to improve firm performance and competitiveness, empirical research to date has been equivocal in supporting the efficacy of these initiatives (Guthrie & Datta, 2008). The purpose of this paper is to investigate long-term stock price performance, of firms that announce downsizing actions. In this study, the wealth effects, if any, are to be examined by investigating the long term stock price performance of firms that downsize.

Past research indicates that the overall market reaction for downsizing/layoff announcements is slightly negative and the returns are statistically significant. Additionally, long-term stock price performance can be tested to verify whether buy-and-hold returns are consistent with short-term performance results. Goins and Gruca (2008) study the impact of layoff on key stakeholders and their results suggest that reputation effects of layoff announcements spillover beyond the announcing firm and extend to other firms in the industry.

The motivation of downsizing firms may be quite different among those firms. A downsizing announcement releases information to the capital markets about the future opportunities available to the firm. On one hand, a downsizing may signal a reorientation, for purposes of restoring or improving competitiveness. Alternatively, a downsizing may signal an effort by management to stymie, or lessen the depth of, organizational decline. Examination of short-term and long-term returns may provide information regarding how the market interprets the announcement of those firms.

Market reaction of firms which downsize could possibly be just an unbiased reaction. That is, half of the firms have positive reactions and half negative reactions, with an overall result being no reaction. Conversely, firms with positive reactions may have systematic differences with the negative reaction firms.

SAMPLE AND METHODOLOGY

Events from the years 1990 to 1992, inclusive, were used to develop a sample. This period is clearly past the enactment of the Worker Adjustment and Retraining Notification (WARN) Act of 1988, which was part of the time period studied by Iqbal and Shetty (1995). The WARN Act of 1988 requires companies to provide a 60-day advance notice of plant closings and layoffs. Worrell et al. (1991) looked at layoffs in the pre-WARN years 1979-1987. Iqbal and Shetty (1995) found that passage of the act had little effect on stockholder reactions. The sample is drawn from the firms which make up the S & P 500 index. Guide database. The S & P 500 accounted for 69% of the database's capitalization" (Standard & Poor's, 1995, p.6) . Firms on the S & P 500 make up roughly 70 percent of the capitalization of the U.S. equity stocks (Standard and Poor's, 1995), and therefore fairly represents the top deciles of the market as a whole, as well as the most actively traded stocks.

Only companies that are part of the S & P 500 in 1988 are included in the study. This restriction is necessary to avoid a survival bias that choosing later periods may introduce. A company that is part of the 1988 S & P 500 will be included, provided they have a downsizing action, regardless of their membership from 1990 to 1992. Firms that have experienced significant change, such as going from wide market ownership to narrow or otherwise become too small, are periodically removed from the S & P 500 index. These firms will be allowed to stay in the sample.

The regression for normal returns will be performed over the estimation period -210 to -60 days. Standard error of the estimate is calculated over the estimation period from -210 to -60 days. The standard error of the estimate is calculated: (Peterson, 1989)

[s.sub.ie] = [[[T.summation over (t=1)] [([R.sub.it] - [R.sup.*.sub.it]).sup.2] / T - 2].sup.0.5]

where:

[S.sub.ie] = Standard error of the estimate for firm i over T periods in the estimation period.

[R.sub.it] - [R.sup.*.sub.it] = Equation (1), or the return for firm i over period t minus the expected return for firm i over period t.

T = Number of periods used in the regression equation for parameter estimation.

An adjustment is made to the standard error of the estimate to derive the standard error of the forecast. Peterson (1989) writes that this adjustment reflects "the deviations of the independent variables in the estimation period from the values employed in the original regression." The standard error of the forecast is derived:

[s.sub.ift] = [s.sub.ie][{1 + (1/T) +[[([R.sub.mt] - [R.sub.m]).sup.2]/[T.summation over (t=1)][([R.sub.mj] - [R.sub.m]).sup.2]]}.sup.0.5]

where:

[s.sub.ift] = Standard error of the forecast for security i in period t in the event period.

Market return for period j within the estimation period.

[R.sub.mt] = Market return for day t within the event period.

[R.sub.m] = Mean return on the market over the estimation period.

The standard error of the forecast can then be used in the calculation of the standardized abnormal return. The standardized abnormal return is derived by dividing the abnormal return by the standard error of the forecast:

[SAR.sub.it] = [AR.sub.it] / [s.sub.ift]

where:

[SAR.sub.it] = Standardized abnormal return for security i in period t.

Standardized cumulative abnormal returns can then be aggregated using the individually standardized abnormal returns for each firm

[SCAR.sub.in] = (1/[square root of n])[n.summation over (i=1)][SAR.sub.it]

where:

[SCAR.sub.in] =Standardized cumulative abnormal returns for firm i over the n day event period.

Then, the standardized cumulative abnormal returns for the individual firms can be used to calculate the standardized cumulative abnormal returns for N securities over n periods:

[SCAR.sub.Nn] = (1/[square root of N])[N.summation over (t=1)][SCAR.sub.in]

where:

[SCAR.sub.Nn] =Standardized cumulative abnormal return for a group of N firms over the n day event period, and assumed to be distributed unit normal. (Peterson 1989)

Day t=0 will be designated as the day of downsizing announcement as indicated in The Wall Street Journal. Using an estimation period closer to the announcement than -60 days risks contaminating the estimation due to leakage of information prior to announcement. Additionally, cumulative abnormal returns can be calculated for each firm over specific time periods.

EMPIRICAL RESULTS

Initially, 294 events by 144 companies in the years from 1990 to 1992 were identified using The Wall Street Journal Index (WSJI). To be included as an event, the announcement must be a permanent downsizing, not just a temporary layoff, such as when auto manufacturers lay off for retooling reasons. The WSJI was used to investigate a six-year window-three years before and three years after--around the event. Additionally, articles were scrutinized when the facts regarding the proposed downsizing were unclear. In some instances the announcement was non-existent or temporary in nature. To be included in the sample, the companies must be part of the 1988 S & P 500 index, be included in the Center for Research in Security Prices (CRSP) returns tapes, and be included in the Compustat reporting disks. Due to these screens of the initial firms, 14 firms and 41 events were deleted from the sample.

After the screening criteria was met, 253 events by 130 companies were left in the sample. Of these companies, 64 events and 10 firms were restricted because of confounding events in the announcement period, or indications that the announcement was anticipated by the market and/or press. Data are provided for the whole group (see Table 1) as an unrestricted sample (Set U), as well as data after confounding and anticipated announcements are deleted, which is referred to as Set A. Set A contains 189 downsizing announcements made by 120 firms over the three-year period. Multiple events by the same firm are considered separate observations. Only the restricted sample data from Set A are included in further breakdowns by category and later regression analysis.

Events by year are presented in Table 1, Panel B for Sets A. For Set A events, 18% of the events are from 1990, 39% from 1991, and 43% from 1992. A cursory review of the data revealed no distinguishing difference in returns based on the year of the event.

In this table, Panel A presents the number of announcements made by the number of firms in the sample. Panel B presents the events per year of the study. Events are presented for both Sets A and B. Panel C shows the main industrial grouping for each event. The main standard industrial code (SIC) for each company is used to identify the industrial grouping.

Events for Set A are also segregated by the main standard industrial code (SIC) and presented in Table 2. Under the industry classifications, eight subgroups are identified.

Tests of Market's Response to Downsizing Announcements

As shown in Table 3, Panel A, daily abnormal returns (AR) are provided for a three-day window. The day the Wall Street Journal reports the event is day 0. Since it is not apparent whether the announcements are on the day reported or the previous day, it is customary to report the abnormal return surrounding the event. The abnormal returns are cumulated to obtain the cumulative abnormal return (CAR), and shown in Table 3.

To test the hypothesis of whether there is a market response to downsizing announcements, it is necessary to determine the statistical significance of the returns. The standardized cumulative abnormal return (SCAR) is calculated for each return. The SCAR is used as the t-statistic to test the hypothesis of abnormal returns.

Overall, the market's reaction to downsizing announcements is negative. This overall result is consistent with evidence from other downsizing studies. (Iqbal & Shetty, 1995; Palmon et al., 1997; Worrell et al., 1991) However, as indicated by the standardized cumulative abnormal return (SCAR), the abnormal returns do not statistically differ from zero. Therefore, a definitive conclusion regarding the markets interpretation of downsizing events for this sample is not prudent. The other area of interest was to examine the long-term returns. This is discussed in the following section.

Tests of Long-Term Returns of Downsizing Firms

One-, two-, and three-year average holding period abnormal returns (AHPAR) are presented in Table 3, Panel B, for the sample events. Long-term tests measure the sample's return against a benchmark, either a matched-firm sample or a portfolio. In this study the return for the S&P 500 is used as the portfolio. To calculate the long-term abnormal return, the S&P 500 return is subtracted from the firm's return over the same period, providing the long-term abnormal return. One-year AHPARs are positive, but not statistically different from zero. Therefore, the stock price performance over a one-year window of the firm's announcing downsizing actions is very similar in magnitude to the overall market performance of the stock market as measured by the S&P 500. In other words, an investor would not earn excess returns over a one-year window by investing in firms announcing downsizing actions.

However, both two- and three-year returns are positive and statistically significant. Investors holding securities representing a broad portfolio of downsizing firms over the test period would have earned substantially more than the market return over exactly the same periods. This may provide evidence that stock prices of firms that announce downsizing actions are depressed. These firms use the action as part of an overall restructuring plan/effort towards a turnaround of the firm. The turnaround effort may take a couple of years before the market rewards the results.

In these tables, abnormal returns are presented for downsizing events. Panel A presents daily and cumulative returns for downsizing events. Panel B presents one-, two-, and three-year average holding period returns for downsizing events. Data are shown for all firms, in Set U, prior to deleting anticipated and confounding announcements. Set A represents the announcements after deleting anticipated and confounding announcements. Set B is further restricted by allowing only one announcement per firm in a six month period. The test statistic (SCAR) and 2-group Z test statistic (2-Grp Z) is shown below each return figure for the short-term returns and long-term returns in Panel A and Panel B, respectively. Returns that are statistically significant are marked accordingly with asterisks.

CONCLUSION

This study answers several questions of importance to both researchers and investors. Most previous studies have only examined the short-term market response and interpret the efficacy of the downsizing action. This study expands the research and evaluates the long-term stock returns to firms announcing downsizing actions.

Overall, this study found negative returns to downsizing announcements, but the returns were not statistically different from zero. The negative returns are consistent with other research results. The sample group did not exhibit significant returns in any of the short-term periods examined.

For both the two- and three-year AHPAR, firms that announced downsizing actions, for the sample period investigated, experienced significantly higher returns than the market portfolio.

This study is subject to several limitations which could affect the conclusions. One limitation is that daily returns may not be a good indicator for the interpretation of the event. Alternative interpretations for market reactions are available. For example, a negative market announcement return may indicate that the market interprets the downsizing announcement as a bad move by management. Alternatively, if the market was expecting a downsizing announcement and the firm cuts either too little or too much, it may also elicit a negative reaction. In other words, management did the correct and expected action, but either went too shallow in cuts or way overboard. The market reaction may be a factor of whether the management made the right downsizing announcement given the market's general appraisal of the firm's situation at that given time.

Another limitation is that it is extremely difficult to measure the labor-capital tradeoff when firms downsize, as well as what firms are able to make effective labor-capital swaps. For example, when a phone company downsizes human operators for computer technology we would expect a different market reaction than when a contractor downsizes due to cuts in federal military budgets.

A final limitation is data availability. To address this limitation, the research design limited the sample firms to those which are widely known and followed by the financial press. Results found here may not be applicable to small companies.

Extensions and Suggestions for Further Research

The primary implication of this study is that returns to firms that downsize are affected by the characteristics of the firm announcing the action. Not all downsizing actions are good, or bad, and further research may indicate which factors are most important for a firm undergoing this form of restructuring.

Additionally, an out-of-date-sample with a similar model may effectively deal with some of the questions. Were the strong long-term returns of firms with weak financial conditions mainly related to the time-frame selected? The sample time-frame included a mild recession which may have affected returns of the cyclical industries.

The labor-capital tradeoff has long interested researchers and may provide some insight into this quagmire. This research was limited to investigation of the returns of firms that downsize. Further research may want to investigate the other costs and benefits, such as social and personal, to the communities of firms that downsize.

The fact that different industrial classifications result in differing returns suggests that downsizing is not a simple event which can be studied and described in isolation to other corporate events. Additional testing of results could include industry, book-to-market, and size matched paired sample analysis.

REFERENCES

Bleakley, Fred R(1995). New Write-offs Mostly Please Investors. The Wall Street Journal, C1, C2.

Bowman, Edward H. & Harbir Singh(1993) . Corporate Restructuring: Reconfiguring the Firm. Strategic Management Journal, 14, Special Issue, 5-14.

Cascio, Wayne F(1993). "Downsizing: What Do We Know? What Have We Learned?" Academy of Management Executive 7, No. 1, 95-104.

Downs, Alan(1995). "The Truth About Layoffs." Management Review 84, Iss. 10, 57-61.

Fefer, Mark D (1994). "How Layoffs Payoff." Fortune 129, Iss. 2, 12.

Guthrie, James P. & Datta Deepak K (2008). Dumb and Dumber: The Impact of Downsizing on Firm Performance as Moderated by Industry Conditions. Organization Science Vol. 19, No. 1, pp. 108-123

Iqbal, Zahid & Shekar Shetty (1995). Layoffs, Stock Prices, and Financial Condition of The Firm. Journal of Applied Business Research 11, No. 2, 67-72.

Lee, Chris (1992). After the Cuts. Training 29, Iss. 17, 17-23.

Lesly, Elizabeth & Larry Light (1992). When Layoffs Alone Don't Turn the Tide. Business Week, 100-01.

Margulis, Stephen T (1994). Bad News, Good News About Downsizing. Managing Office Technology 39 (4), 23-4.

Markels, Alex & Matt Murray (1996). Call It Dumbsizing: Why Some Companies Regret Cost-Cutting. The Wall Street Journal 77, No. 148, A1, A6.

McCune, Joseph T., Richard W. Beatty, & Raymond V. Montagno (1988). "Downsizing: Practices in Manufacturing Firms." Human Resource Management 27, No. 2, 145-61.

Seglin, Jeffrey L (1996). The Happiest Workers in the World. Inc. 18, No. 7, 62-74.

Standard & Poor's (1991). S & P 500 1995 Directory. New York: Standard & Poor's, 1995.

Worrell, Dan L., Wallace N. Davidson III, and Varinder M. Sharma. Layoff Announcements and Stockholder Wealth. Academy of Management Journal, 34, No. 3, 662-78.

Wyatt, Edward A (1994). "Purge and Merge: A New Corporate Diet Pushes Stocks Higher on Near-Record Volume. Barron's 74, Iss. 12, MW3-4.

Brad G. Scott, Webster University

Joe Ueng, University of St. Thomas

Vinita Ramaswamy, University of St. Thomas

Ching Liang Chang, Yuan Chee University
Table 1: Descriptive Statistics Of Sample Groups

Panel A: Number of Announcements By Number Of Firms

Group                Unrestricted   Restricted   Restricted

                        Set U         Set A        Set B

# of Events              253           189          164
# of Firms               130           120          120

Panel B: Announcement events by year

Year          1990       1991          1992        Total

Set A          34         73            82          189
%             18%        39%           43%          100%

Table 2: Announcement Events By Standard Industrial
Codes/Industry Classification

Industry                     # events         %

1. Primary-Agr., Mining          7           3.70%
2. Mfg-Non-Durables             35          18.50%
3. Mfg-Durable Goods            94          49.70%
4. Transportation                8           4.20%
5. Utilities/Commun.            18           9.50%
6. Wholesale                     4           2.10%
7. Finance & Insurance          18           9.50%
8. Services                      5           2.60%

         Total                 189         100.00%

Table 3: Short And Long Term Abnormal Returns By Sets

Panel A
                                      Days

Grouping       # events    Period      -1         0          1

All Firms        253         AR      -0.15%    -0.16%     -0.22%
Unrestricted                SCAR     -0.1265   -0.4959    -0.2254
Set U
Restricted       189         AR      -0.18%    -0.31%     -0.235%
Set A                       SCAR     -0.1299   -0.4917    -0.0770

Panel B

Grouping                  # events   Period    1 year     2 year
All Firms                   253       AHPAR     3.38%     15.36%
Unrestricted                         2-Grp Z    1.169    2.466 ***
Set U
Restricted                  189       AHPAR     2.25%     16.45%
Set A                                2-Grp Z    0.661    2.095 **

Panel A
               Cumulative

Grouping         -1 to 1

All Firms        -0.53%
Unrestricted     -0.4896
Set U
Restricted       -0.724%
Set A            -0.4033

Panel B

Grouping         3 year
All Firms        21.48%
Unrestricted    2.933 ***
Set U
Restricted       24.54%
Set A           2.707 ***

*: Significant at the .10 level

**: Significant at the .05 level

***: Significant at the .01 level
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