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Register-based Statistics: Statistical Methods for Administrative Data 2nd edition [Kõva köide]

(Statistics Sweden, Sweden), (Statistics Sweden, Sweden)
  • Formaat: Hardback, 328 pages, kõrgus x laius x paksus: 252x175x22 mm, kaal: 653 g
  • Sari: Wiley Series in Survey Methodology
  • Ilmumisaeg: 16-May-2014
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1119942136
  • ISBN-13: 9781119942139
Teised raamatud teemal:
Register-based Statistics: Statistical Methods for Administrative Data 2nd editionSuurem pilt
  • Formaat: Hardback, 328 pages, kõrgus x laius x paksus: 252x175x22 mm, kaal: 653 g
  • Sari: Wiley Series in Survey Methodology
  • Ilmumisaeg: 16-May-2014
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1119942136
  • ISBN-13: 9781119942139
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781119942139.html
Märksõnad:
Statistical Methods for Administrative Data

Second Edition

Provides a comprehensive overview of this important area of statistics

There is a growing interest in developing register-based statistics based upon already available data from administrative registers. The huge amounts of information generated within administrative systems offer the opportunity to use these data for statistical analysis without any of the costs otherwise involved in data collection.

Register-based Statistics offers readers a detailed account of the principles and practices of this increasingly important area of statistics.

The second edition has been extensively revised and updated, and includes practical examples of recent methodological work from different countries.

Register-based Statistics provides a unique guide for all those working in statistical agencies. It will also prove invaluable for academic researchers and teachers in statistics, and statisticians working with administrative systems in government institutions and enterprises.

This book provides a comprehensive and up to date treatment of theory and practical implementation in Register-based statistics. It begins by defining the area, before explaining how to structure such systems, as well as detailing alternative approaches. It explains how to create statistical registers, how to implement quality assurance, and the use of IT systems for register-based statistics. Further to this, clear details are given about the practicalities of implementing such statistical methods, such as protection of privacy and the coordination and coherence of such an undertaking.

This edition offers a full understanding of both the principles and practices of this increasingly popular area of statistics, and can be considered a first step to a more systematic way of working with register-statistical issues. This book addresses the growing global interest in the topic and employs a much broader, more international approach than the 1st edition. New chapters explore different kinds of register-based surveys, such as preconditions for register-based statistics and comparing sample survey and administrative data. Furthermore, the authors present discussions on register-based census, national accounts and the transition towards a register-based system as well as presenting new chapters on quality assessment of administrative sources and production process quality.

Preface xi
Chapter 1 Register Surveys -- An Introduction
1(24)
1.1 The purpose of the book
1(2)
1.2 The need for a new theory and new methods
3(2)
1.3 Four ways of using administrative registers
5(1)
1.4 Preconditions for register-based statistics
6(4)
1.4.1 Reliable administrative systems
7(1)
1.4.2 Legal base and public approval
8(2)
1.5 Basic concepts and terms
10(10)
1.5.1 What is a statistical survey?
10(1)
1.5.2 What is a register?
11(2)
1.5.3 What is a register survey?
13(1)
1.5.4 The Income and Taxation Register
14(2)
1.5.5 The Quarterly and Annual Pay Registers
16(4)
1.6 Comparing sample surveys and register surveys
20(3)
1.7 Conclusions
23(2)
Chapter 2 The Nature of Administrative Data
25(12)
2.1 Different kinds of administrative data
25(1)
2.2 How are data recorded?
26(1)
2.3 Administrative and statistical information systems
27(2)
2.4 Measurement errors in statistical and administrative data
29(1)
2.5 Why use administrative data for statistics?
30(2)
2.6 Comparing sample survey and administrative data
32(4)
2.6.1 A questionnaire to persons compared with register data
32(2)
2.6.2 An enterprise questionnaire compared with register data
34(2)
2.7 Conclusions
36(1)
Chapter 3 Protection of Privacy and Confidentiality
37(10)
3.1 Internal security
38(3)
3.1.1 No text in output databases
38(1)
3.1.2 Existence of identity numbers
39(2)
3.2 Disclosure risks -- tables
41(4)
3.2.1 Rules for tables with counts, totals and mean values
41(2)
3.2.2 The threshold rule -- analyse complete tables
43(1)
3.2.3 Frequency tables are often misunderstood
44(1)
3.2.4 Combining tables can cause disclosure
45(1)
3.3 Disclosure risks -- microdata
45(1)
3.4 Conclusions
46(1)
Chapter 4 The Register System
47(30)
4.1 A register model based on object types and relations
47(7)
4.1.1 The register system and protection of privacy
53(1)
4.1.2 The register system and data warehousing
53(1)
4.2 Organising the work with the system
54(2)
4.3 The populations in the system
56(4)
4.3.1 How to produce consistent register-based statistics
57(1)
4.3.2 Registers and time
58(1)
4.3.3 Populations, variables and time
59(1)
4.4 The variables in the system
60(5)
4.4.1 Standardised variables in the register system
60(2)
4.4.2 Derived variables
62(1)
4.4.3 Variables with different origins
63(1)
4.4.4 Variables with different functions in the system
64(1)
4.5 Using the system for micro integration
65(5)
4.6 Three kinds of registers with different roles
70(2)
4.7 Register systems and register surveys within enterprises
72(2)
4.8 Conclusions
74(3)
Chapter 5 The Base Registers in the System
77(26)
5.1 Characteristics of a base register
77(1)
5.2 Requirements for base registers
78(5)
5.2.1 Defining and deriving statistical units
78(2)
5.2.2 Objects and identities -- requirements for a base register
80(1)
5.2.3 Coverage and spanning variables in base registers
81(2)
5.3 The Population Register
83(5)
5.4 The Business Register
88(5)
5.5 The Real Estate Register
93(1)
5.6 The Activity Register
94(4)
5.7 Everyone should support the base registers
98(3)
5.8 Conclusions
101(2)
Chapter 6 How to Create a Register -- Matching and Combining Sources
103(18)
6.1 Preconditions in different countries
103(2)
6.2 Matching methods and problems
105(9)
6.2.1 Deterministic record linkage
105(1)
6.2.2 Probabilistic record linkage
106(6)
6.2.3 Four causes of matching errors
112(2)
6.3 Matching sources with different object types
114(6)
6.4 Conclusions
120(1)
Chapter 7 How to Create a Register -- The Population
121(26)
7.1 How should register surveys be structured?
121(4)
7.2 Register survey design
125(6)
7.2.1 Determining the research objectives
125(3)
7.2.2 Making an inventory of different sources
128(1)
7.2.3 Analysing the usability of administrative sources
128(3)
7.3 Defining a register's object set
131(11)
7.3.1 Defining a population
131(3)
7.3.2 Can you alter data from the National Tax Agency?
134(1)
7.3.3 Defining a population -- primary registers
135(1)
7.3.4 Defining a population -- integrated registers
136(1)
7.3.5 Defining a calendar year population
137(1)
7.3.6 Defining a population -- frame or register population?
138(3)
7.3.7 Base registers should be used when defining populations
141(1)
7.4 Defining the statistical units
142(3)
7.4.1 Units and identities when creating primary registers
143(1)
7.4.2 Using administrative objects instead of statistical units
144(1)
7.5 Creating longitudinal registers -- the population
145(1)
7.6 Conclusions
146(1)
Chapter 8 How to Create a Register -- The Variables
147(24)
8.1 The variables in the register
147(4)
8.1.1 Variable definitions
148(1)
8.1.2 Variables in statistical science
149(1)
8.1.3 Variables in informatics
150(1)
8.1.4 Creating register variables -- checklist
151(1)
8.2 Forming derived variables using models
151(8)
8.2.1 Exact calculation of values using a rule
152(1)
8.2.2 Estimating values with a rule
153(1)
8.2.3 Estimating values with a causal model
154(3)
8.2.4 Derived variables and imputed variable values
157(1)
8.2.5 Creating variables by coding
158(1)
8.3 Activity data
159(6)
8.3.1 Activity statistics
160(1)
8.3.2 Activity data aggregated for enterprises and organisations
161(1)
8.3.3 Activity data aggregated for persons: multi-valued variables
161(4)
8.4 Creating longitudinal registers -- the variables
165(4)
8.5 Conclusions
169(2)
Chapter 9 How to Create a Register -- Editing
171(22)
9.1 Editing register data
171(10)
9.1.1 Editing one administrative register
173(2)
9.1.2 Consistency editing -- is the population correct?
175(3)
9.1.3 Consistency editing -- are the units correct?
178(2)
9.1.4 Consistency editing -- are the variables correct?
180(1)
9.2 Case studies -- editing register data
181(4)
9.2.1 Editing work within the Income and Taxation Register
181(2)
9.2.2 Editing work with the Income Statement Register
183(1)
9.2.3 What more can be learned from these examples?
184(1)
9.3 Editing, quality assurance and survey design
185(7)
9.3.1 Survey design in a register-based production system
185(1)
9.3.2 Quality assessment in a register-based production system
186(5)
9.3.3 Total survey error in a register-based production system
191(1)
9.4 Conclusions
192(1)
Chapter 10 Metadata
193(8)
10.1 Primary registers -- the need for metadata
193(2)
10.1.1 Documentation of administrative sources
194(1)
10.1.2 Documentation of sources within the system
194(1)
10.1.3 Documentation of a new register
195(1)
10.2 Changes over time -- the need for metadata
195(1)
10.3 Integrated registers -- the need for metadata
196(1)
10.4 Classification and definitions database
197(1)
10.5 The need for metadata for registers
198(2)
10.6 Conclusions
200(1)
Chapter 11 Estimation Methods -- Introduction
201(8)
11.1 Estimation in sample surveys and register surveys
202(1)
11.2 Estimation methods for register surveys that use weights
203(1)
11.3 Calibration of weights in register surveys
204(3)
11.4 Using weights for estimation
207(1)
11.5 Conclusions
208(1)
Chapter 12 Estimation Methods -- Missing Values
209(12)
12.1 Make no adjustments, publish `value unknown'
210(4)
12.2 Adjustment for missing values using weights
214(1)
12.3 Adjustment for missing values by imputation
215(3)
12.4 Missing values in a system of registers
218(2)
12.5 Conclusions
220(1)
Chapter 13 Estimation Methods -- Coverage Problems
221(8)
13.1 Reducing overcoverage and undercoverage
221(3)
13.1.1 Coverage problems in the Population Register
221(1)
13.1.2 Coverage problems in the Business Register
222(2)
13.2 Estimation methods to correct for overcoverage
224(2)
13.3 Undercoverage in the administrative system
226(2)
13.4 Conclusions
228(1)
Chapter 14 Estimation Methods -- Multi-valued Variables
229(30)
14.1 Multi-valued variables
229(3)
14.2 Estimation methods
232(19)
14.2.1 Occupation in the Activity and Occupation Registers
232(4)
14.2.2 Industrial classification in the Business Register
236(2)
14.2.3 Importing many multi-valued variables
238(4)
14.2.4 Consistency between estimates from different registers
242(3)
14.2.5 Multi-valued variables -- what is done in practice?
245(2)
14.2.6 Additional estimation methods
247(4)
14.3 Application of the method
251(3)
14.4 Linking of time series using combination objects
254(4)
14.4.1 Linking time series
254(2)
14.4.2 Changed industrial classification in the Business Register
256(2)
14.5 Conclusions
258(1)
Chapter 15 Theory and Quality of Register-based Statistics
259(38)
15.1 Is there a theory for register surveys?
259(8)
15.1.1 Statistical inference at a national statistical office
260(2)
15.1.2 Theory-based methods or ad hoc methods
262(1)
15.1.3 The survey approach and the systems approach
263(4)
15.2 Measuring quality -- why and how?
267(4)
15.3 Analysing administrative sources -- input data quality
271(7)
15.4 Output data quality
278(1)
15.5 The integration process -- integration errors
279(9)
15.5.1 Creating register populations -- coverage errors
280(2)
15.5.2 Creating statistical units -- errors in units
282(1)
15.5.3 Creating statistical variables -- errors in variables
283(5)
15.6 Random variation in register data
288(3)
15.7 The register system and data warehousing
291(4)
15.8 Conclusions
295(2)
Chapter 16 Conclusions
297(4)
References 301(6)
Index 307
Anders Wallgren and Britt Wallgren, Statistics Sweden.