The relationship between unemployment and wellbeing: an updated meta-analysis of longitudinal evidence

Figures & data

Table 1. Meta-analyses for unemployment and wellbeing.

Meta-analysis		K	N	d	SDd	δ	SDδ	% var.	95% CI		80% CV
									Lower	Upper	Lower	Upper
M1	All wellbeing measures	27	471,938	−.280	.243	−.318	.291	.37	−.325	−.311	−.690	.054
M1a	Without Van Hoorn and Maseland (2013) and Luo (2020)	25	142,164	−.362	.331	−.382	.384	.60	−.393	−.370	−.873	.110
M1b	Without regression coefficients	20	122,255	−.308	.157	−.328	.193	2.14	−.341	−.316	−.575	−.081
M2	Life satisfaction	11	353,208	−.222	.238	−.254	.281	.22	−.262	−.246	−.614	.106
M2a	Without regression coefficients	8	189,251	−.228	.178	−.260	.212	.51	−.271	−.250	−.531	.011
M3	Mental Health	20	95,607	−.209	.095	−.219	.094	9.50	−.232	−.205	−.339	−.099
M3a	Without Schmitz (2011)	19	71,873	−.210	.110	−.223	.110	9.07	−.238	−.207	−.363	−.082
M3b	Without regression coefficients	16	80,088	−.206	.098	−.214	.095	8.70	−.228	−.199	−.336	−.092
M3c	Only GHQ12	7	40,222	−.179	.062	−.189	.060	18.13	−.210	−.168	−.265	−.113
M3d	Other measures of depression	13	55,385	−.231	.108	−.239	.107	8.16	−.256	−.222	−.376	−.102
M4	Changes in wellbeing	5	230,779	−.214	.159	−.246	.198	.31	−.256	−.236	−.500	.008
M5	Changes in life satisfaction	4	224,973	−.237	.157	−.281	.195	.28	−.291	−.271	−.531	−.031

Note. K = total number of samples; N = total sample size across studies; d = sample-size-weighted mean effect size; SD_d = standard deviation of d; δ = estimated population effect size; SD_δ = standard deviation of δ; % var. = percent of variance accounted for by sampling and measurement error; 80% CV = 80% credibility interval; 95% CI = 95% confidence interval. GHQ12 = General Health Questionnaire 12-items.

Table 2. Meta-analyses of categorical moderators.

Meta-analysis

K

N

d

SDd

δ

SDδ

% var.

95% CI

80% CV

Lower

Upper

Lower

Upper

Gender

M6

Women – All wellbeing measures

10

55,058

−.415

.272

−.477

.341

.92

−.498

−.457

−.913

−.042

M6b

Without regression coefficients

9

44,766

−.412

.205

−.479

.263

1.72

−.502

−.456

−.815

−.142

M7

Women – Life satisfaction

7

50,361

−.442

.270

−.521

.341

.74

−.542

−.499

−.957

−.084

M8

Men – All wellbeing measures

9

56,835

−.619

.487

−.718

.620

.27

−.739

−.697

−1.512

.075

M8a

Without regression coefficients

8

46,777

−.559

.259

−.654

.346

.92

−.677

−.631

−1.096

−.211

M9

Men – Life satisfaction

7

53,258

−.667

.475

−.802

.615

.25

−.825

−.780

−1.590

−.014

Country – GII

M10

Low: Sweden, Germany, Switzerland, Spain, Belgium, France

11

93,609

−.180

.419

−.199

.477

.27

−.213

−.184

−.810

.412

M10a

Without Luo (2020)

10

35,885

−.479

.610

−.485

.692

.29

−.508

−.462

−1.371

.400

M11

High: Canada, UK, Ireland, US

11

58,623

−.221

.104

−.232

.108

6.71

−.249

−.215

−.370

−.093

Country – NTW scores (Roex & Rözer, 2017)

M12

Low: Canada, Ireland, UK, US, Spain, France, Belgium

16

74,265

−.190

.105

−.197

.103

8.12

−.212

−.182

−.329

−.066

M13

High: Germany, Portugal, Sweden, Switzerland

7

72,213

−.192

.478

−.217

.559

0.17

−.234

−.200

−.933

.498

M13a

Without Luo (2020)

6

14,489

−1.075

.917

−1.253

1.273

0.22

−1.302

−1.206

−2.883

.377

Country – European/non-European

M14

Canada, US, Australia

11

47,517

−.238

.126

−.246

.130

5.70

−.265

−.228

−.413

−.080

M14a

Without regression coefficients

10

39,687

−.263

.157

−.270

.167

3.84

−.291

−.249

−.484

−.056

M15

Europe

15

274,959

−.358

.293

−.414

.363

.24

−.423

−.405

−.878

.051

M15a

Without regression coefficients

13

266,185

−.323

.206

−.372

.259

.42

−.382

−.363

−.704

−.041

Country – Employment protection indicator (OECD)

M16

Low: Canada, USA, Switzerland, Ireland, Australia

13

57,014

−.415

.491

−.416

.543

.364

−.434

−.398

−1.111

.279

M16a

Without Oesch and Lipps (2013)

11

48,240

−.232

.132

−.240

.135

5.2

−.259

−.222

−0.414

−.067

M17

High: Germany, Portugal, Sweden, France, Spain, Belgium, UK

11

101,235

−.082

.100

−.096

.105

4.635

−.110

−.083

−0.231

.039

M17a

Without Luo (2020)

10

43,511

−.190

.059

−.200

.055

25.41

−.220

−.180

−0.271

−.130

Duration of unemployment

M18

Long-term unemployment

14

100,135

−.627

.468

−0.755

0.595

0.27

−0.771

−0.739

−1.516

0.006

M18a

Without Breslin and Mustard (2003)

12

94,039

−.657

.474

−0.789

0.606

0.24

−0.806

−0.772

−1.565

−0.013

M18b

Without regression coefficients

12

67,537

−.451

.305

−0.529

0.393

0.72

−0.548

−0.510

−1.033

−0.026

M18c

Including Clark et al. (2001)

12

63,657

−.459

.316

−0.540

0.408

0.71

−0.560

−0.520

−1.063

−0.017

Note. K = total number of samples; N = total sample size across studies; d = sample-size-weighted mean effect size; SD_d = standard deviation of d; δ = estimated population effect size; SD_δ = standard deviation of δ; % var. = percent of variance accounted for by sampling and measurement error; 80% CV = 80% credibility interval; 95% CI = 95% confidence interval. The random effects meta-analytic procedure (Schmidt & Hunter, 2015) was employed. GII = Gender Inequality Index; NTW = Norm to Work.

Table 3. Meta-analyses of cross-lagged correlations between unemployment and wellbeing.

Meta-analysis		K	N	$\bar{r}$	SD $\bar{r}$	ρ	SDρ	% var.	95% CI		80% CV
									Lower	Upper	Lower	Upper
1	Unemployment T1 – Wellbeing T2	7	6843	−.106	.075	−.108	.067	18.441	−.194	−.022	−.131	−.084
2	Wellbeing T1 – Unemployment T2	5	5,003	−.121	.050	−.126	.050	32.01	−.155	−.097	−.187	−.064
3	Unemployment T1/T2 – Wellbeing T1/T2	27	471,938	−.139	.118	−.157	.140	.37	−.16	−.15	−.34	.02
4	Unemployment T1 – T2	2	4,179	.111	.021	-	-	10.48	.081	.141	-	-
5	Wellbeing T1 – T2	6	20,559	.320	.130	.344	.126	1.64	.331	.357	.183	.505

Note. K = total number of samples; N = total sample size across studies; $\bar{r}$ = sample-size-weighted mean of correlations; SD. $\bar{r}$ = standard deviation of $\stackrel{-}{r}$ ; ρ = estimated population correlation; SD_ρ = standard deviation of ρ; % var. = percent of variance accounted for by sampling and measurement error; 80% CV = 80% credibility interval; 95% CI = 95% confidence interval; T = measurement point. All the estimated population correlations are sample-size weighted and corrected for unreliability in wellbeing, using the artefact distribution, except for the unemployment T1 – T2 bare-bone meta-analysis.

Table 4. Fit indices and comparison for the different cross-lagged meta-analytic structural equation models.

	χ ^2 (df)	CFI	RMSEA	SRMR	AIC	BIC	Model comparison	Δ-2LL	Δdf
Mod0: Stability	160.58 (2)***	.90	.09	.04	105,126.56	105,183.75
Mod1: Direct causality	124.253 (1)***	.92	.09	.04	105,092.23	105,156.57
Mod2: Reversed causality	33.799 (1)***	.98	.06	.02	105,001.78	105,066.12
Mod3: Reciprocal^a	0 (0)***	1.00	.00	.00	104,969.98	105,041.47
							Mod0 vs Mod1	36.33***	1
							Mod0 vs Mod2	126.78***	1
							Mod0 vs Mod3	160.58***	2
							Mod1 vs Mod3	124.25***	1
							Mod2 vs Mod3	33.80***	1

Note. ***p < .001. df = degree of freedom; Δ-2LL = −2 log-likelihood difference; Δdf = degree of freedom difference between the models compared. ^a The traditional fit indices were not available for the reciprocal model (Mod₃) as it is just-identified.

Figure 1. The reciprocal model (Mod₃).

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