Putting the effect sizes in context - Employer downsizing and older workers’ health

A helpful way of evaluating how much employer downsizing affects health is to compare its effects to those of other controls included in the baseline model. Figure 3 presents those comparisons for four outcomes: self-reported bad health, showing symptoms of clinical depression, the risk of being diagnosed with stroke, and the risk of being diagnosed with psychiatricor emotional problems. We compare the coefficients of downsizing with the effects of being married, of having a high-school or college degree, and of being a blue-collar or a pink-collar worker. As shown in Figure 3, across the four outcomes the effects of downsizing are much larger than those associated with being a blue-collar or a pink-collar worker. They are about half the size of those associate with having a college degree (but with opposite sign) for showing symptoms of clinical depression and of being diagnosed with a stroke. Downsizing has effects about one-fifth the size (with opposite sign) of college education on reporting bad health. Finally, across the four outcomes, downsizing has an effect that is at least half as big (with opposite sign) of the effect associated with being married. In short, the effect of downsizing on workers’ health is comparable to that of other important demographics such as marital status, educational

attainment, and type of occupation.

7. Conclusions

We find that employer downsizing increases the probability that older workers would rate their health as fair or poor, that it increases the risk of showing symptoms of clinical depression, and that it increases the risk of being diagnosed with stroke, psychiatric or emotional problems, and arthritis. There is also weaker evidence that downsizing can increase the risk of showing high levels of C-reactive protein (CRP), a measure of general inflammation. Health effects of

employer downsizing also appear comparable to the effects of other worker characteristics, such as being married or a blue-collar worker.

We find that downsizings affect health through increased job insecurity and increased levels of stress. The effects of downsizing remain statistically significant but are smaller after controlling for these factors, suggesting that other mechanisms such as reductions in morale and motivation also affect the health of workers. Therefore, our findings suggest that employers should think consider how to offset the detrimental health effects of downsizing on the (older) workers they retain.

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Figure 1: Mean reported rate of employer downsizing by HRS wave

0 5 10 15 20 25 30 35 40 45

1996 1998 2000 2002 2004 2006 2008 2010

HRS Wave

Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Means for not self-employed individuals working for pay.

Analysis weighted by sampling probabilities.

Figure 2: Subjective probability of job loss and stress level

020406080100

Subjective probability of job loss (%)

Strongly Agree Agree Disagree Strongly Disagree

My job involves a lot of stress

Source: Health and Retirement Study (HRS), 1994-2010

Downsizing

Spletzer (2002) California Annual: March

1999-March 2000 25.4 13.0 30.1 15.0

Table 2: Self-reported health and mental health indicators, by employer downsizing status

Variables All sample

Non-Downsizing Downsizing Difference P-value

Employer downsizing (0=No; 1=Yes) 0.254 .

Self-reported bad health (0=No; 1=Yes) 0.139 0.134 0.153 0.019 0.000 Mental health indicators (0=No; 1=Yes)

Felt depressed 0.098 0.094 0.109 0.015 0.001

Symptoms of clinical depression 0.097 0.091 0.116 0.025 0.000

Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Means for not self-employed individuals working for pay. Analysis weighted using wave-specific sampling weight for each respondent. Self-reported bad health is based on a 5 point scale self-reported health question. Those who report fair or poor health are defined as being in bad health.

Table 3: Conditions ever diagnosed by a doctor, by employer downsizing status

Variables All sample

Non-Downsizing Downsizing Difference P-value Number of conditions ever diagnosed (#) 1.301 1.297 1.314 0.017 0.314 Probability of first diagnosis

Psychiatric or emotional problems 0.065 0.060 0.079 0.018 0.000

Arthritis 0.278 0.276 0.286 0.010 0.165

Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Means for not self-employed individuals working for pay. Analysis weighted using wave-specific sampling weight for each respondent. Individuals' observations are included up to the time of first diagnosis.

Table 4: Biomarkers of health, by employer downsizing status

Variables All sample

Non-Downsizing Downsizing Difference P-value Measurements above threshold? (0=No; 1=Yes)

High total cholesterol (>240 mg/L) 0.206 0.202 0.219 0.016 0.478 Low total cholesterol (<160 mg/L) 0.108 0.111 0.096 -0.015 0.339 Source: Health and Retirement Study (HRS), waves 2006-2008.

Notes: Means for not self-employed individuals working for pay. Analysis weighted using wave-specific sampling weight for each respondent.

Table 5: Worker characteristics, by employer downsizing status

Variables All sample

Non-Downsizing Downsizing Difference P-value

Age 58.883 59.275 57.731 -1.544 0.000

Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Means for not self-employed individuals working for pay. Analysis weighted using wave-specific sampling weight for each respondent.

Table 6: Job characteristics, by employer downsizing status

Variables All sample

Non-Downsizing Downsizing Difference P-value Industry

Business, repair and personal services 0.064 0.069 0.049 -0.019 0.000

Entertn/recreatn 0.014 0.015 0.012 -0.003 0.026

Prof/related svcs 0.262 0.278 0.214 -0.064 0.000

Public administration 0.051 0.050 0.054 0.004 0.227

Missing 0.211 0.205 0.229 0.024 0.000

Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Means for not self-employed individuals working for pay. Analysis weighted using wave-specific sampling weight for each respondent.

Table 7: Effect of downsizing, symptoms of clinical depression and number of conditions on employment transitions (marginal effects from Multinomial Logit Model)

At same employer At different employer Not working

Sample Mean 0.7237 0.0964 0.1799

Downsizing -0.041*** 0.016*** 0.025***

(0.008) (0.005) (0.006)

Symp. clinical depression

All employers -0.054*** 0.000 0.054***

(0.011) 0.007 (0.010)

Downsizing employers -0.071*** 0.016 0.053***

(0.021) (0.016) (0.011)

Non-downsizing

employers -0.048*** -0.005 0.053***

(0.012) (0.007) (0.011)

# Conditions

All employers -0.018*** -0.003* 0.021***

(0.003) (0.002) (0.002)

Downsizing employers -0.025*** -0.001 0.026***

(0.005) (0.004) (0.004)

Non-downsizing

employers -0.015*** -0.004** 0.019***

(0.003) (0.002) (0.002)

Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Controls include: gender, cubic function of age, education attainment (less than high school, high school, college or more), occupation type (white collar, pink collar or blue collar) employment status (full-time, part-time, partial retirement), employer's size, employer's industry, tenure at job, employer-provided health insurance, employer-sponsored pension plans, level of physical effort at work, level of heavy lifting required at work, state and wave dummies and lagged health conditions. Regressions were weighted using wave-specific sampling weight for each respondent. Standard errors are clustered at the individual level. *** denotes significance at the 1% level; ** denotes significance at the 5% level; * denotes significance at the 10% level.

Table 8: Baseline model

Outcomes Bivariate model

Intermediate model

Baseline model

Sample size

Coef. S.E. Coef. S.E. Coef. S.E.

Self-reported bad health 0.019*** 0.006 0.018*** 0.006 0.036*** 0.006 37,201

Mental health indicators (0=No; 1=Yes)

Felt depressed 0.015*** 0.005 0.016*** 0.005 0.028*** 0.005 35,168

Felt everything is an effort 0.022*** 0.006 0.022*** 0.006 0.034*** 0.006 35,160

Sleep was restless 0.027*** 0.008 0.029*** 0.008 0.041*** 0.008 35,166

Was happy -0.026*** 0.005 -0.026*** 0.005 -0.027*** 0.006 35,134

Felt Lonely 0.008 0.005 0.009 0.005 0.019*** 0.005 35,164

Felt sad 0.022*** 0.006 0.023*** 0.006 0.035*** 0.006 35,157

Could not get going 0.019*** 0.005 0.019*** 0.005 0.030*** 0.005 35,159

Enjoyed Life -0.017*** 0.004 -0.017*** 0.004 -0.017*** 0.004 35,161

Symp. clinical depression 0.025*** 0.005 0.025*** 0.005 0.035*** 0.005 35,069

Probability of first diagnosis

High blood pressure 0.011 0.008 0.008 0.008 0.006 0.008 30,211

Diabetes 0.012*** 0.004 0.011** 0.004 0.007 0.005 35,237

Cancer -0.002 0.003 -0.002 0.003 0.000 0.003 35,934

Lunge disease 0.002 0.003 0.001 0.003 0.003 0.003 36,466

Hearth problems -0.002 0.004 -0.003 0.004 0.001 0.004 35,194

Stroke 0.004* 0.002 0.004* 0.002 0.006*** 0.002 36,828

Psychiatric or emotional problems 0.018*** 0.005 0.017*** 0.005 0.017*** 0.005 35,769

Arthritis 0.010 0.008 0.008 0.008 0.027*** 0.008 30,058

Controls

Long-term average county employment

growth No Yes Yes

Worker and employer characteristics No No Yes

Outcomes Bivariate Model

Intermediate Model

Baseline Model

Sample Size

Coef. S.E. Coef. S.E. Coef. S.E.

Measurements above threshold? (0=No; 1=Yes)

High A1c -0.008 0.017 -0.008 0.017 -0.011 0.017 3,012

High C-reactive protein 0.031 0.026 0.031 0.026 0.047* 0.027 2,929

High Cystatin C 0.001 0.008 0.001 0.008 0.005 0.008 2,910

Low high-density lipoprotein (HDL) -0.000 0.023 -0.000 0.023 -0.002 0.023 2,506

High total cholesterol 0.016 0.023 0.016 0.023 0.014 0.023 2,902

Low total cholesterol -0.015 0.016 -0.015 0.016 -0.014 0.017 2,902

High diastolic blood pressure -0.006 0.023 -0.006 0.023 -0.010 0.023 2,965

Low diastolic blood pressure -0.004 0.006 -0.004 0.006 -0.001 0.006 2,965

High systolic blood pressure -0.015 0.023 -0.015 0.023 -0.009 0.023 2,965

High pulse -0.008 0.012 -0.008 0.012 -0.004 0.013 2,965

High body-mass index (BMI) -0.015 0.027 -0.015 0.027 -0.010 0.028 2,897

Low body-mass index (BMI) -0.010* 0.006 -0.010* 0.006 -0.009 0.006 2,897

Controls

Long-term average county employment

growth No Yes Yes

Worker and employer characteristics No No Yes

Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Self-reported bad health is based on a 5 point scale self-reported health question. Those who report fair or poor health are defined as being in bad health. Refer to Table 4 for the list of thresholds for each biomarker. Worker and employer characteristics include: gender, cubic function of age, education attainment (less than high school, high school, college or more), occupation type (white collar, pink collar or blue collar) employment status (full-time, part-time, partial retirement), employer's size, employer's industry, tenure at job, employer-provided health insurance, employer-sponsored pension plans, level of physical effort at work, level of heavy lifting required at work, and state and wave dummies. Regressions were weighted using wave-specific sampling weight for each respondent. Standard errors are clustered at the individual level. *** denotes significance at the 1% level; ** denotes significance at the 5% level; * denotes significance at the 10% level.

Table 9: Robustness check - Controlling for lagged health outcomes

Outcomes Baseline Model Controlling for

lagged health

Self-reported bad health 0.029*** 0.007 0.016*** 0.005 27,751

Mental health indicators (0=No; 1=Yes)

Felt depressed 0.027*** 0.006 0.019*** 0.006 27,293

Symp. clinical depression 0.033*** 0.006 0.023*** 0.005 27,226

Probability of first diagnosis

Psychiatric or emotional problems 0.009* 0.005 0.005* 0.003 26,442

Arthritis 0.024** 0.010 0.015*** 0.006 21,152

Controls

Long-term average county employment

growth Yes Yes

Worker and employer characteristics Yes Yes

Lagged health outcomes No Yes

Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Self-reported bad health is based on a 5 point scale self-reported health question. Those who report fair or poor health are defined as being in bad health. Worker and employer characteristics include: gender, cubic function of age, education attainment (less than high school, high school, college or more), occupation type (white collar, pink collar or blue collar) employment status (full-time, part-time, partial retirement), employer's size, employer's industry, tenure at job, employer-provided health insurance, employer-sponsored pension plans, level of physical effort at work, level of heavy lifting required at work, and state and wave dummies. Regressions were weighted using wave-specific sampling weight for each respondent. Standard errors are clustered at the individual level. *** denotes significance at the 1% level; ** denotes significance at the 5% level; * denotes significance at the 10% level.

Outcomes Baseline Model Controlling for

lagged health

Worker and employer characteristics Yes Yes

Lagged health outcomes No Yes

Source: Health and Retirement Study (HRS), waves 2006-2008.

Notes: Self-reported bad health is based on a 5 point scale self-reported health question. Those who report fair or poor health are defined as being in bad health. Worker and employer characteristics include: gender, cubic function of age, education attainment (less than high school, high school, college or more), occupation type (white collar, pink collar or blue collar) employment status (full-time, part-time, partial retirement), employer's size, employer's industry, tenure at job, employer-provided health insurance, employer-sponsored pension plans, level of physical effort at work, level of heavy lifting required at work, and state and wave dummies Regressions were weighted using wave-specific sampling weight for each respondent. Standard errors are clustered at the individual level. *** denotes significance at the 1% level; ** denotes significance at the 5% level; * denotes significance at the 10% level.

Table 10: Robustness check - Individual fixed effect model

Baseline Model

FE Model

Sample Size

Coef. S.E. Coef. S.E.

Self-reported bad health 0.029*** 0.005 0.013*** 0.005 37,201

Mental health indicators (0=No; 1=Yes)

Felt depressed 0.029*** 0.004 0.008 0.005 35,168

Felt everything is an effort 0.034*** 0.005 0.018*** 0.006 35,160

Sleep was restless 0.037*** 0.006 0.009 0.007 35,166

Was happy -0.025*** 0.005 -0.002 0.005 35,134

Felt Lonely 0.024*** 0.005 0.003 0.005 35,164

Felt sad 0.033*** 0.005 0.010* 0.006 35,157

Could not get going 0.027*** 0.005 0.015*** 0.006 35,159

Enjoyed Life -0.017*** 0.003 -0.004 0.004 35,161

Symp. clinical depression 0.034*** 0.004 0.012** 0.005 35,069

Controls

Long-term average county employment

growth Yes Yes

Worker and employer characteristics Yes Yes

Lagged health outcomes No No

Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Self-reported bad health is based on a 5 point scale self-reported health question. Those who report fair or poor health are defined as being in bad health. Worker and employer characteristics include: gender, cubic function of age, education attainment (less than high school, high school, college or more), occupation type (white collar, pink collar or blue collar) employment status (full-time, part-time, partial retirement), employer's size, employer's industry, tenure at job, employer-provided health insurance, employer-sponsored pension plans, level of physical effort at work, level of heavy lifting required at work, and state and wave dummies. Standard errors are clustered at the individual level. *** denotes significance at the 1% level; ** denotes significance at the 5%

level; * denotes significance at the 10% level.

Table 11: Robustness check - Instrumental variables approach

Outcomes

First stage Main regression

Sample Size Coef. F-statistic Coef. S.E.

Self-reported bad health -0.361*** 9.425 0.078 0.255 37,201

Mental health indicators (0=No; 1=Yes)

Felt depressed -0.419*** 11.357 0.102 0.214 35,168

Felt everything is an effort -0.417*** 11.290 -0.093 0.251 35,160

Sleep was restless -0.416*** 11.223 0.145 0.306 35,166

Was happy -0.432*** 12.180 0.126 0.217 35,134

Felt Lonely -0.416*** 11.223 -0.033 0.223 35,164

Felt sad -0.419*** 11.357 0.082 0.257 35,157

Could not get going -0.417*** 11.290 0.148 0.221 35,159

Enjoyed Life -0.418*** 11.357 -0.154 0.170 35,161

Symp. clinical depression -0.431*** 12.041 0.109 0.207 35,069

Probability of first diagnosis

High blood pressure -0.304** 5.198 0.813 0.526 30,211

Diabetes -0.381*** 9.860 -0.275 0.200 35,237

Cancer -0.366*** 9.181 0.088 0.132 35,934

Lunge disease -0.313*** 7.129 -0.324* 0.185 36,466

Hearth problems -0.340*** 7.618 -0.059 0.215 35,194

Stroke -0.353*** 9.060 0.020 0.071 36,828

Psychiatric or emotional

problems -0.375*** 9.734 0.082 0.188 35,769

Arthritis -0.309** 5.712 0.247 0.410 30,058

Outcomes

First stage Main Regression

Sample Size Coef. F-statistic Coef. S.E.

Measured Biomarkers

High A1c -0.254 0.1936 0.966 2.791 3,012

High CRP -0.156 0.0729 4.593 16.67 2,929

High Cysc -0.163 0.0784 1.501 5.401 2,910

Low HDL -0.002 0.000 25.654 10,08 2,506

High Total Cholesterol -0.152 0.0676 4.846 18.50 2,902

Low Total Cholesterol -0.152 0.0676 -0.879 4.495 2,902

High Diastolic BP -0.241 0.1681 0.713 2.809 2,965

Low Diastolic BP -0.241 0.1681 0.468 1.293 2,965

High Systolic BP -0.241 0.1681 -0.014 2.030 2,965

High Pulse -0.241 0.1681 -0.799 2.379 2,965

High BMI -0.222 0.1444 0.955 3.506 2,897

Low BMI -0.222 0.1444 -0.174 0.786 2,897

Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Self-reported bad health is based on a 5 point scale self-reported health question. Those who report fair or poor health are defined as being in bad health. Controls include: gender, cubic function of age, education attainment (less than high school, high school, college or more), occupation type (white collar, pink collar or blue collar) employment status (full-time, part-time, partial retirement), employer's size, employer's industry, tenure at job, employer-provided health insurance, employer-sponsored pension plans, level of physical effort at work, level of heavy lifting required at work, state and wave dummies and lagged health conditions. Regressions were weighted using wave-specific sampling weight for each respondent.

Standard errors are clustered at the individual level. *** denotes significance at the 1% level; ** denotes significance at the 5% level; * denotes significance at the 10% level.

Table 12: Effect of employer downsizing on job loss expectation and job stress level A. Job loss expectations (denoted by p) -

OLS model B. Current job involves lots of stress –

OLS model Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Controls include: gender, cubic function of age, education attainment (less than high school, high school, college or more), occupation type (white collar, pink collar or blue collar) employment status (full-time, part-time, partial retirement), employer's size, employer's industry, tenure at job, employer-provided health insurance, employer-sponsored pension plans, level of physical effort at work, level of heavy lifting required at work, state and wave dummies and lagged health conditions.

Regressions were weighted using wave-specific sampling weight for each respondent. Standard errors are clustered at the individual level. *** denotes significance at the 1% level; ** denotes significance at the 5% level; * denotes significance at the 10% level.

Table 13: Health effects of Employer downsizing after controlling for job loss expectations and stress levels

Self-reported bad health 0.033*** 0.006 0.024*** 0.006 30,785

Mental health indicators (0=No; 1=Yes)

Felt depressed 0.027*** 0.005 0.015*** 0.005 30,774

Symp. clinical depression 0.031*** 0.005 0.018*** 0.005 30,692

Probability of first diagnosis

Psychiatric or emotional problems 0.019*** 0.005 0.015*** 0.005 29,654

Arthritis 0.031*** 0.009 0.025*** 0.009 25,013

Controls

Long-term average county employment

growth Yes Yes

Worker and employer characteristics Yes Yes

Lagged health outcomes No No

Source: Health and Retirement Study (HRS), waves 1994-2010.

Notes: Self-reported bad health is based on a 5 point scale self-reported health question. Those who report fair or poor health are defined as being in bad health. Worker and employer characteristics include: gender, cubic function of age, education attainment (less than high school, high school, college or more), occupation type (white collar, pink collar or blue collar) employment status (full-time, part-time, partial retirement), employer's size, employer's industry, tenure at job, employer-provided health insurance, employer-sponsored pension plans, level of physical effort at work, level of heavy lifting required at work, and state and wave dummies. Regressions were weighted using wave-specific sampling weight for each respondent. Standard errors are clustered at the individual level. *** denotes significance at the 1%

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