Applied health economics:
Saved in:
| Format: | Book |
|---|---|
| Language: | English |
| Published: |
London [u.a.]
Routledge
2007
|
| Edition: | 1. publ. |
| Series: | Routledge advanced texts in economics and finance
8 |
| Subjects: | |
| Online Access: | Table of contents only Inhaltsverzeichnis |
| Item Description: | Includes bibliographical references and index |
| Physical Description: | XV, 335 S. graph. Darst. |
| ISBN: | 0415397715 0415397723 9780415397711 9780415397728 |
Staff View
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| 245 | 1 | 0 | |a Applied health economics |c Andrew M. Jones ... [et al.] |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a London [u.a.] |b Routledge |c 2007 | |
| 300 | |a XV, 335 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
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| 490 | 1 | |a Routledge advanced texts in economics and finance |v 8 | |
| 500 | |a Includes bibliographical references and index | ||
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| 650 | 7 | |a Gezondheidszorg |2 gtt | |
| 650 | 4 | |a Gesundheitswesen | |
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| 830 | 0 | |a Routledge advanced texts in economics and finance |v 8 |w (DE-604)BV037241432 |9 8 | |
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Record in the Search Index
| _version_ | 1804136265074868224 |
|---|---|
| adam_text | Contents
List of illustrations viii
Preface xii
Acknowledgements xiv
Introduction 1
PART I
Data description 3
1 Data and survey design 5
/./ The Health and Lifestyle Survey (HALS) 5
1.2 The British Household Panel Survey (BHPS) 7
1.3 The European Community Household Panel t EC HP) 9
1.4 The Canadian National Population Health Survey
(NPHS) 10
1.5 The WHO Multi Country Survey Study ( WHO MCS) 12
1.6 Overview 12
2 Describing the dynamics of health 13
2.1 Introduction 13
2.2 Graphical analysis 15
2.3 Tabula tint; the data 22
3 Inequality in health utility and self assessed health 29
3.1 Introduction 29
3.2 Distributional analysis 30
3.3 Regression analysis of HL I: Ordinary Least Squares lOLS) 34
3.4 Regression analysis of SAH: orderedprobit model 3H
vi Contents
3.5 Combined analysis of HUI and SAH: interval regression 45
3.6 Overview 49
PART II
Categorical data 51
4 Bias in self reported data 53
4.1 Introduction 53
4.2 Vignettes 54
4.3 Standard ordered probit model 56
4.4 Using vignettes to control for heterogeneous reporting 58
5 Health and lifestyles 81
5.7 Introduction 81
5.2 HALS data and sample 82
5.3 Descriptive analysis 88
5.4 Estimation strategy and results 97
5.5 Overview 121
PART III
Survival data 123
6 Smoking and mortality 125
6.1 Introduction 125
6.2 Basic concepts of survival analysis 126
6.3 The HALS data 127
6.4 Survival data in HALS 129
6.5 Descriptive statistics 134
6.6 Duration models 136
7 Health and retirement 169
7.1 Introduction 169
7.2 Preparing and summarizing the data 169
7.3 The endogeneity of health 180
7.4 Empirical approach to duration modelling 183
7.5 Stock sampling and discrete time hazard analysis 189
7.6 Overview 199
Contents vii
PART IV
Panel data 201
8 Health and wages 203
8.1 Introduction 203
8.2 BHPS sample and variables 203
8.3 Empirical model and estimation 209
8.4 Overview 225
9 Modelling the dynamics of health 227
9.1 Introduction 227
9.2 Static models 233
9.3 Dynamic models 249
10 Non response and attrition bias 265
10.1 Introduction 265
10.2 Testing for non response bias 268
10.3 Estimation 272
11 Models for health care use 279
11.1 Introduction 279
11.2 The Poisson model 280
11.3 The Negative Binomial model 283
11.4 Zero inflated models 286
11.5 Hurdle models 291
11.6 Finite mixture I latent class models 293
11.7 Latent class hurdle model 299
Bibliography 321
Index 330
Illustrations
Figure
2.1 Bar chart for SAH, men 16
2.2 Bar chart for SAH by wave, men 16
2.3 Bar chart for SAH by age group, wave 1, men 18
2.4 Bar chart for SAH by quintile of meaninc, men 19
2.5 Empirical CDFs of meaninc, men 19
2.6 Bar chart for SAH by education, men 20
2.7 Bar chart for SAH by previous SAH, wave 2, men 21
3.1 Empirical distribution function (EDF) of HUI 30
3.2 Empirical CDFs of HUI, by income quintile 31
3.3 Lorenz curves for HUI, by income quintile 34
3.4 Kernel density estimates for OLS residuals 37
6.1 Non parametric functions for smoking initiation 139
6.2 Cox Snell residuals test smoking initiation 142
6.3 Log logistic functions for smoking initiation 145
6.4 Cox Snell residuals test starters smoking initiation 147
6.5 Log logistic functions for smoking initiation 149
6.6 Non parametric functions for smoking cessation 151
6.7 Cox Snell residuals test smoking cessation 154
6.8 Weibull estimated functions for smoking cessation 157
6.9 Normal probability plot for lifespan 158
6.10 Non parametric functions for lifespan 160
6.11 Cox Snell residuals test lifespan 163
6.12 Gompertz estimated functions for lifespan 168
7.1 Life table estimates of the proportion not retired by health
limitations 188
Table
3.1 OLS regression for HUI 35
3.2 Ordered probit regression for SAH 39
3.3 Generalized ordered probit for SAH 41
Illustrations ix
3.4 Interval regression for SAH 46
4.1 Ordered probit for self reported health (affect) 57
4.2 Ordered probit for vignettes ratings {affect) 62
4.3 Generalized ordered probit for vignette ratings {affect) 64
4.4 Interval regression for self reported health with parallel
cut point shift (affect) 70
4.5 Interval regression for self reported health with non parallel
cut point shift (affect) 72
4.6 HOPIT for self reported health with cut point shift (affect) 76
5.1 Probit model for mortality with exclusion restrictions 101
5.2 Probit model for mortality without exclusion restrictions 102
5.3 Multivariate probit 8 equations 104
5.4 Multivariate probit 5 equations 113
5.5 Average partial effects from alternative models for
mortality 121
6.1 Information criteria smoking initiation 142
6.2 Smoking initiation log logistic distribution (AFT)
coefficients 144
6.3 Information criteria starters smoking initiation 146
6.4 Smoking initiation for starters log logistic distribution
(AFT) coefficients 148
6.5 Information criteria smoking cessation 154
6.6 Smoking cessation Weibull distribution (AFT)
coefficients 155
6.7 Information criteria lifespan 164
6.8 Lifespan Gompertz model coefficients 165
6.9 Lifespan Gompertz model hazard ratios 166
7.1 Variable names and definitions 174
7.2 Labour market status by wave 178
7.3 Descriptive statistics 179
7.4 Ordered probits for self assessed health 182
7.5 Life table for retirement by health limitations 187
7.6 Discrete time hazard model no heterogeneity 192
7.7 Complementary log log model with frailty 194
7.8 Discrete time duration model with gamma distributed
frailty 196
7.9 Discrete time duration models with latent self assessed
health 198
8.1 Variable labels and definitions 207
8.2 Summary statistics for full sample of observations 208
8.3 OLS on full sample of observations 210
8.4 RE on full sample of observations 212
8.5 FE on full sample of observations 214
8.6 Hausman and Taylor IV estimator on full sample of
observations 219
x Illustrations
8.7 Men: Amemiya and MaCurdy IV estimator on full sample
of observations 222
8.8 Men comparison across estimators 224
9.1 Pooled probit model, unbalanced panel 234
9.2 Pooled probit model, balanced panel 235
9.3 Mundlak specification of pooled probit model, unbalanced
panel 237
9.4 Mundlak specification of pooled probit model, balanced
panel 238
9.5 Random effects probit model, unbalanced panel 240
9.6 Random effects probit model, balanced panel 243
9.7 Mundlak specification of random effects probit model,
unbalanced panel 245
9.8 Mundlak specification of random effects probit model,
balanced panel 246
9.9 Conditional logit model, unbalanced panel 248
9.10 Conditional logit model, balanced panel 249
9.11 Dynamic pooled probit model, unbalanced panel 252
9.12 Dynamic pooled probit model, balanced panel 253
9.13 Dynamic pooled probit model with initial conditions,
unbalanced panel 254
9.14 Dynamic pooled probit model with initial conditions,
balanced panel 255
9.15 Dynamic random effects probit model, unbalanced
panel 256
9.16 Dynamic pooled probit model, balanced panel 257
9.17 Dynamic pooled probit model with initial conditions,
unbalanced panel 258
9.18 Dynamic pooled probit model with initial conditions,
balanced panel 259
9.19 Heckman estimator of dynamic random effects probit 263
10.1 Dynamic pooled probit with IPW, unbalanced panel 276
10.2 Dynamic pooled probit with IPW, balanced panel 277
11.1 Poisson regression for number of specialist visits 281
11.2 Poisson regression for number of specialist visits with
robust standard errors 283
11.3 Negative Binomial model for number of specialist visits 284
11.4 Generalized Negative Binomial model for number of
specialist visits 286
11.5 Zero Inflated Poisson model for number of specialist
visits I 287
11.6 Zero Inflated Poisson model for number of specialist
visits II 289
11.7 Zero Inflated NB model for number of specialist visits I 289
11.8 Zero Inflated NB model for number of specialist visits II 290
Illustration xi
11.9 Logit model for the probability of having at least one
visit to a specialist 292
11.10 Truncated at zero NB2 for the number of specialist visits 293
11.11 LCNB2 model for the number of specialist visits (with two
latent classes) 297
11.12 Summary statistics of fitted values by latent class (LCNB2) 298
11.13 AIC and BIC of NB2 and LCNB2 (with two latent classes)
for the number of specialist visits 299
11.14 LCNB2 Pan for the number of specialist visits (with two
latent classes) 306
11.15 Summary statistics of fitted values by latent class
(LCNB2 Pan) 307
11.16 AIC and BIC of NB2, LCNB2 and LCNB2 Pan (with two
latent classes) for the number of specialist visits 308
11.17 LCH Pan for the number of specialist visits (with two
latent classes), with constant class membership 312
11.18 AIC and BIC of LCNB2 Pan and LCH Pan (with two
latent classes) for the number of specialist visits 313
11.19 LCH Pan for the number of specialist visits (with two
latent classes), with variable class membership 316
11.20 Summary statistics for individual n in LCH Pan, with
variable class membership 317
11.21 Summary statistics of fitted values by latent class in
LCH Pan, with variable class membership 318
11.22 AIC and BIC of LCNB2 Pan and LCH Pan (with two
latent classes) with constant and variable class memberships 320
|
| adam_txt |
Contents
List of illustrations viii
Preface xii
Acknowledgements xiv
Introduction 1
PART I
Data description 3
1 Data and survey design 5
/./ The Health and Lifestyle Survey (HALS) 5
1.2 The British Household Panel Survey (BHPS) 7
1.3 The European Community Household Panel t EC HP) 9
1.4 The Canadian National Population Health Survey
(NPHS) 10
1.5 The WHO Multi Country Survey Study ( WHO MCS) 12
1.6 Overview 12
2 Describing the dynamics of health 13
2.1 Introduction 13
2.2 Graphical analysis 15
2.3 Tabula tint; the data 22
3 Inequality in health utility and self assessed health 29
3.1 Introduction 29
3.2 Distributional analysis 30
3.3 Regression analysis of HL'I: Ordinary Least Squares lOLS) 34
3.4 Regression analysis of SAH: orderedprobit model 3H
vi Contents
3.5 Combined analysis of HUI and SAH: interval regression 45
3.6 Overview 49
PART II
Categorical data 51
4 Bias in self reported data 53
4.1 Introduction 53
4.2 Vignettes 54
4.3 Standard ordered probit model 56
4.4 Using vignettes to control for heterogeneous reporting 58
5 Health and lifestyles 81
5.7 Introduction 81
5.2 HALS data and sample 82
5.3 Descriptive analysis 88
5.4 Estimation strategy and results 97
5.5 Overview 121
PART III
Survival data 123
6 Smoking and mortality 125
6.1 Introduction 125
6.2 Basic concepts of survival analysis 126
6.3 The HALS data 127
6.4 Survival data in HALS 129
6.5 Descriptive statistics 134
6.6 Duration models 136
7 Health and retirement 169
7.1 Introduction 169
7.2 Preparing and summarizing the data 169
7.3 The endogeneity of health 180
7.4 Empirical approach to duration modelling 183
7.5 Stock sampling and discrete time hazard analysis 189
7.6 Overview 199
Contents vii
PART IV
Panel data 201
8 Health and wages 203
8.1 Introduction 203
8.2 BHPS sample and variables 203
8.3 Empirical model and estimation 209
8.4 Overview 225
9 Modelling the dynamics of health 227
9.1 Introduction 227
9.2 Static models 233
9.3 Dynamic models 249
10 Non response and attrition bias 265
10.1 Introduction 265
10.2 Testing for non response bias 268
10.3 Estimation 272
11 Models for health care use 279
11.1 Introduction 279
11.2 The Poisson model 280
11.3 The Negative Binomial model 283
11.4 Zero inflated models 286
11.5 Hurdle models 291
11.6 Finite mixture I latent class models 293
11.7 Latent class hurdle model 299
Bibliography 321
Index 330
Illustrations
Figure
2.1 Bar chart for SAH, men 16
2.2 Bar chart for SAH by wave, men 16
2.3 Bar chart for SAH by age group, wave 1, men 18
2.4 Bar chart for SAH by quintile of meaninc, men 19
2.5 Empirical CDFs of meaninc, men 19
2.6 Bar chart for SAH by education, men 20
2.7 Bar chart for SAH by previous SAH, wave 2, men 21
3.1 Empirical distribution function (EDF) of HUI 30
3.2 Empirical CDFs of HUI, by income quintile 31
3.3 Lorenz curves for HUI, by income quintile 34
3.4 Kernel density estimates for OLS residuals 37
6.1 Non parametric functions for smoking initiation 139
6.2 Cox Snell residuals test smoking initiation 142
6.3 Log logistic functions for smoking initiation 145
6.4 Cox Snell residuals test starters smoking initiation 147
6.5 Log logistic functions for smoking initiation 149
6.6 Non parametric functions for smoking cessation 151
6.7 Cox Snell residuals test smoking cessation 154
6.8 Weibull estimated functions for smoking cessation 157
6.9 Normal probability plot for lifespan 158
6.10 Non parametric functions for lifespan 160
6.11 Cox Snell residuals test lifespan 163
6.12 Gompertz estimated functions for lifespan 168
7.1 Life table estimates of the proportion not retired by health
limitations 188
Table
3.1 OLS regression for HUI 35
3.2 Ordered probit regression for SAH 39
3.3 Generalized ordered probit for SAH 41
Illustrations ix
3.4 Interval regression for SAH 46
4.1 Ordered probit for self reported health (affect) 57
4.2 Ordered probit for vignettes ratings {affect) 62
4.3 Generalized ordered probit for vignette ratings {affect) 64
4.4 Interval regression for self reported health with parallel
cut point shift (affect) 70
4.5 Interval regression for self reported health with non parallel
cut point shift (affect) 72
4.6 HOPIT for self reported health with cut point shift (affect) 76
5.1 Probit model for mortality with exclusion restrictions 101
5.2 Probit model for mortality without exclusion restrictions 102
5.3 Multivariate probit 8 equations 104
5.4 Multivariate probit 5 equations 113
5.5 Average partial effects from alternative models for
mortality 121
6.1 Information criteria smoking initiation 142
6.2 Smoking initiation log logistic distribution (AFT)
coefficients 144
6.3 Information criteria starters smoking initiation 146
6.4 Smoking initiation for starters log logistic distribution
(AFT) coefficients 148
6.5 Information criteria smoking cessation 154
6.6 Smoking cessation Weibull distribution (AFT)
coefficients 155
6.7 Information criteria lifespan 164
6.8 Lifespan Gompertz model coefficients 165
6.9 Lifespan Gompertz model hazard ratios 166
7.1 Variable names and definitions 174
7.2 Labour market status by wave 178
7.3 Descriptive statistics 179
7.4 Ordered probits for self assessed health 182
7.5 Life table for retirement by health limitations 187
7.6 Discrete time hazard model no heterogeneity 192
7.7 Complementary log log model with frailty 194
7.8 Discrete time duration model with gamma distributed
frailty 196
7.9 Discrete time duration models with latent self assessed
health 198
8.1 Variable labels and definitions 207
8.2 Summary statistics for full sample of observations 208
8.3 OLS on full sample of observations 210
8.4 RE on full sample of observations 212
8.5 FE on full sample of observations 214
8.6 Hausman and Taylor IV estimator on full sample of
observations 219
x Illustrations
8.7 Men: Amemiya and MaCurdy IV estimator on full sample
of observations 222
8.8 Men comparison across estimators 224
9.1 Pooled probit model, unbalanced panel 234
9.2 Pooled probit model, balanced panel 235
9.3 Mundlak specification of pooled probit model, unbalanced
panel 237
9.4 Mundlak specification of pooled probit model, balanced
panel 238
9.5 Random effects probit model, unbalanced panel 240
9.6 Random effects probit model, balanced panel 243
9.7 Mundlak specification of random effects probit model,
unbalanced panel 245
9.8 Mundlak specification of random effects probit model,
balanced panel 246
9.9 Conditional logit model, unbalanced panel 248
9.10 Conditional logit model, balanced panel 249
9.11 Dynamic pooled probit model, unbalanced panel 252
9.12 Dynamic pooled probit model, balanced panel 253
9.13 Dynamic pooled probit model with initial conditions,
unbalanced panel 254
9.14 Dynamic pooled probit model with initial conditions,
balanced panel 255
9.15 Dynamic random effects probit model, unbalanced
panel 256
9.16 Dynamic pooled probit model, balanced panel 257
9.17 Dynamic pooled probit model with initial conditions,
unbalanced panel 258
9.18 Dynamic pooled probit model with initial conditions,
balanced panel 259
9.19 Heckman estimator of dynamic random effects probit 263
10.1 Dynamic pooled probit with IPW, unbalanced panel 276
10.2 Dynamic pooled probit with IPW, balanced panel 277
11.1 Poisson regression for number of specialist visits 281
11.2 Poisson regression for number of specialist visits with
robust standard errors 283
11.3 Negative Binomial model for number of specialist visits 284
11.4 Generalized Negative Binomial model for number of
specialist visits 286
11.5 Zero Inflated Poisson model for number of specialist
visits I 287
11.6 Zero Inflated Poisson model for number of specialist
visits II 289
11.7 Zero Inflated NB model for number of specialist visits I 289
11.8 Zero Inflated NB model for number of specialist visits II 290
Illustration xi
11.9 Logit model for the probability of having at least one
visit to a specialist 292
11.10 Truncated at zero NB2 for the number of specialist visits 293
11.11 LCNB2 model for the number of specialist visits (with two
latent classes) 297
11.12 Summary statistics of fitted values by latent class (LCNB2) 298
11.13 AIC and BIC of NB2 and LCNB2 (with two latent classes)
for the number of specialist visits 299
11.14 LCNB2 Pan for the number of specialist visits (with two
latent classes) 306
11.15 Summary statistics of fitted values by latent class
(LCNB2 Pan) 307
11.16 AIC and BIC of NB2, LCNB2 and LCNB2 Pan (with two
latent classes) for the number of specialist visits 308
11.17 LCH Pan for the number of specialist visits (with two
latent classes), with constant class membership 312
11.18 AIC and BIC of LCNB2 Pan and LCH Pan (with two
latent classes) for the number of specialist visits 313
11.19 LCH Pan for the number of specialist visits (with two
latent classes), with variable class membership 316
11.20 Summary statistics for individual n in LCH Pan, with
variable class membership 317
11.21 Summary statistics of fitted values by latent class in
LCH Pan, with variable class membership 318
11.22 AIC and BIC of LCNB2 Pan and LCH Pan (with two
latent classes) with constant and variable class memberships 320 |
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| dewey-ones | 338 - Production |
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| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| edition | 1. publ. |
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| id | DE-604.BV022263892 |
| illustrated | Illustrated |
| index_date | 2024-07-02T16:43:42Z |
| indexdate | 2024-07-09T20:53:39Z |
| institution | BVB |
| isbn | 0415397715 0415397723 9780415397711 9780415397728 |
| language | English |
| lccn | 2006028492 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015474494 |
| oclc_num | 71223231 |
| open_access_boolean | |
| owner | DE-703 DE-12 DE-473 DE-BY-UBG DE-384 DE-19 DE-BY-UBM |
| owner_facet | DE-703 DE-12 DE-473 DE-BY-UBG DE-384 DE-19 DE-BY-UBM |
| physical | XV, 335 S. graph. Darst. |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | Routledge |
| record_format | marc |
| series | Routledge advanced texts in economics and finance |
| series2 | Routledge advanced texts in economics and finance |
| spelling | Applied health economics Andrew M. Jones ... [et al.] 1. publ. London [u.a.] Routledge 2007 XV, 335 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Routledge advanced texts in economics and finance 8 Includes bibliographical references and index Economische aspecten gtt Gezondheidszorg gtt Gesundheitswesen Wirtschaft Medical economics Gesundheitsökonomie (DE-588)4130935-2 gnd rswk-swf Gesundheitsökonomie (DE-588)4130935-2 s DE-604 Jones, Andrew M. 1960- Sonstige (DE-588)128792817 oth Routledge advanced texts in economics and finance 8 (DE-604)BV037241432 8 http://www.loc.gov/catdir/toc/ecip0620/2006028492.html Table of contents only HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015474494&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Applied health economics Routledge advanced texts in economics and finance Economische aspecten gtt Gezondheidszorg gtt Gesundheitswesen Wirtschaft Medical economics Gesundheitsökonomie (DE-588)4130935-2 gnd |
| subject_GND | (DE-588)4130935-2 |
| title | Applied health economics |
| title_auth | Applied health economics |
| title_exact_search | Applied health economics |
| title_exact_search_txtP | Applied health economics |
| title_full | Applied health economics Andrew M. Jones ... [et al.] |
| title_fullStr | Applied health economics Andrew M. Jones ... [et al.] |
| title_full_unstemmed | Applied health economics Andrew M. Jones ... [et al.] |
| title_short | Applied health economics |
| title_sort | applied health economics |
| topic | Economische aspecten gtt Gezondheidszorg gtt Gesundheitswesen Wirtschaft Medical economics Gesundheitsökonomie (DE-588)4130935-2 gnd |
| topic_facet | Economische aspecten Gezondheidszorg Gesundheitswesen Wirtschaft Medical economics Gesundheitsökonomie |
| url | http://www.loc.gov/catdir/toc/ecip0620/2006028492.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015474494&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV037241432 |
| work_keys_str_mv | AT jonesandrewm appliedhealtheconomics |