Register–based Statistics: Statistical Methods for Administrative Data, 2e

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.

Table of Contents:
Preface xi Chapter 1 Register Surveys -- An Introduction 1 1.1 The purpose of the book 1 1.2 The need for a new theory and new methods 3 1.3 Four ways of using administrative registers 5 1.4 Preconditions for register-based statistics 6 1.4.1 Reliable administrative systems 7 1.4.2 Legal base and public approval 8 1.5 Basic concepts and terms 10 1.5.1 What is a statistical survey? 10 1.5.2 What is a register? 11 1.5.3 What is a register survey? 13 1.5.4 The Income and Taxation Register 14 1.5.5 The Quarterly and Annual Pay Registers 16 1.6 Comparing sample surveys and register surveys 20 1.7 Conclusions 23 Chapter 2 The Nature of Administrative Data 25 2.1 Different kinds of administrative data 25 2.2 How are data recorded? 26 2.3 Administrative and statistical information systems 27 2.4 Measurement errors in statistical and administrative data 29 2.5 Why use administrative data for statistics? 30 2.6 Comparing sample survey and administrative data 32 2.6.1 A questionnaire to persons compared with register data 32 2.6.2 An enterprise questionnaire compared with register data 34 2.7 Conclusions 36 Chapter 3 Protection of Privacy and Confidentiality 37 3.1 Internal security 38 3.1.1 No text in output databases! 38 3.1.2 Existence of identity numbers 39 3.2 Disclosure risks -- tables 40 3.2.1 Rules for tables with counts, totals and mean values 41 3.2.2 The threshold rule -- analyse complete tables! 43 3.2.3 Frequency tables are often misunderstood 44 3.2.4 Combining tables can cause disclosure 45 3.3 Disclosure risks -- micro data 45 3.4 Conclusions 46 Chapter 4 The Register System 47 4.1 A register model based on object types and relations 47 4.1.1 The register system and protection of privacy 53 4.1.2 The register system and data warehousing 53 4.2 Organising the work with the system 54 4.3 The populations in the system 56 4.3.1 How to produce consistent register-based statistics 57 4.3.2 Registers and time 58 4.3.3 Populations, variables and time 59 4.4 The variables in the system 60 4.4.1 Standardised variables in the register system 60 4.4.2 Derived variables 62 4.4.3 Variables with different origins 63 4.4.4 Variables with different functions in the system 64 4.5 Using the system for micro integration 65 4.6 Three kinds of registers with different roles 70 4.7 Register systems and register surveys within enterprises 72 4.8 Conclusions 74 Chapter 5 The Base Registers in the System 77 5.1 Characteristics of a base register 77 5.2 Requirements for base registers 78 5.2.1 Defining and deriving statistical units 78 5.2.2 Objects and identities -- requirements for a base register 80 5.2.3 Coverage and spanning variables in base registers 81 5.3 The Population Register 83 5.4 The Business Register 88 5.5 The Real Estate Register 93 5.6 The Activity Register 94 5.7 Everyone should support the base registers! 98 5.8 Conclusions 101 Chapter 6 How to Create a Register -- Matching and Combining Sources 103 6.1 Preconditions in different countries 103 6.2 Matching methods and problems 105 6.2.1 Deterministic record linkage 105 6.2.2 Probabilistic record linkage 106 6.2.3 Four causes of matching errors 112 6.3 Matching sources with different object types 114 6.4 Conclusions 120 Chapter 7 How to Create a Register -- The Population 121 7.1 How should register surveys be structured? 121 7.2 Register survey design 125 7.2.1 Determining the research objectives 125 7.2.2 Making an inventory of different sources 128 7.2.3 Analysing the usability of administrative sources 128 7.3 Defining a register's object set 131 7.3.1 Defining a population 131 7.3.2 Can you alter data from the National Tax Agency? 134 7.3.3 Defining a population -- primary registers 135 7.3.4 Defining a population -- integrated registers 136 7.3.5 Defining a calendar year population 137 7.3.6 Defining a population -- frame or register population? 138 7.3.7 Base registers should be used when defining populations 141 7.4 Defining the statistical units 142 7.4.1 Units and identities when creating primary registers 143 7.4.2 Using administrative objects instead of statistical units 144 7.5 Creating longitudinal registers -- the population 145 7.6 Conclusions 146 Chapter 8 How to Create a Register -- The Variables 147 8.1 The variables in the register 147 8.1.1 Variable definitions 148 8.1.2 Variables in statistical science 149 8.1.3 Variables in informatics 150 8.1.4 Creating register variables -- check list 151 8.2 Forming derived variables using models 151 8.2.1 Exact calculation of values using a rule 152 8.2.2 Estimating values with a rule 153 8.2.3 Estimating values with a causal model 154 8.2.4 Derived variables and imputed variable values 157 8.2.5 Creating variables by coding 158 8.3 Activity data 159 8.3.1 Activity statistics 160 8.3.2 Activity data aggregated for enterprises and organisations 161 8.3.3 Activity data aggregated for persons -- multi-valued variables 161 8.4 Creating longitudinal registers -- the variables 165 8.5 Conclusions 169 Chapter 9 How to Create a Register -- Editing 171 9.1 Editing register data 171 9.1.1 Editing one administrative register 173 9.1.2 Consistency editing -- is the population correct? 175 9.1.3 Consistency editing -- are the units correct? 178 9.1.4 Consistency editing -- are the variables correct? 180 9.2 Case studies -- editing register data 181 9.2.1 Editing work within the Income and Taxation Register 181 9.2.2 Editing work with the Income Statement Register 183 9.2.3 What more can be learned from these examples? 184 9.3 Editing, quality assurance and survey design 185 9.3.1 Survey design in a register-based production system 185 9.3.2 Quality assessment in a register-based production system 186 9.3.3 Total survey error in a register-based production system 191 9.4 Conclusions 192 Chapter 10 Metadata 193 10.1 Primary registers -- the need for metadata 193 10.1.1 Documentation of administrative sources 194 10.1.2 Documentation of sources within the system 195 10.1.3 Documentation of a new register 195 10.2 Changes over time -- the need for metadata 195 10.3 Integrated registers -- the need for metadata 196 10.4 Classification and definitions database 197 10.5 The need for metadata for registers 198 10.6 Conclusions 200 Chapter 11 Estimation Methods -- Introduction 201 11.1 Estimation in sample surveys and register surveys 202 11.2 Estimation methods for register surveys that use weights 203 11.3 Calibration of weights in register surveys 204 11.4 Using weights for estimation 207 11.5 Conclusions 208 Chapter 12 Estimation Methods -- Missing Values 209 12.1 Make no adjustments, publish 'value unknown' 210 12.2 Adjustment for missing values using weights 214 12.3 Adjustment for missing values by imputation 215 12.4 Missing values in a system of registers 218 12.5 Conclusions 220 Chapter 13 Estimation Methods -- Coverage Problems 221 13.1 Reducing overcoverage and undercoverage 221 13.1.1 Coverage problems in the Population Register 221 13.1.2 Coverage problems in the Business Register 222 13.2 Estimation methods to correct for overcoverage 224 13.3 Undercoverage in the administrative system 226 13.4 Conclusions 228 Chapter 14 Estimation Methods -- Multi-valued Variables 229 14.1 Multi-valued variables 229 14.2 Estimation methods 232 14.2.1 Occupation in the Activity and Occupation Registers 232 14.2.2 Industrial classification in the Business Register 236 14.2.3 Importing many multi-valued variables 238 14.2.4 Consistency between estimates from different registers 242 14.2.5 Multi-valued variables -- what is done in practice? 245 14.2.6 Additional estimation methods 247 14.3 Application of the method 251 14.4 Linking of time series using combination objects 254 14.4.1 Linking time series 254 14.4.2 Changed industrial classification in the Business Register 256 14.5 Conclusions 258 Chapter 15 Theory and Quality of Register-based Statistics 259 15.1 Is there a theory for register surveys? 259 15.1.1 Statistical inference at a national statistical office 260 15.1.2 Theory-based methods or ad hoc methods 262 15.1.3 The survey approach and the systems approach 263 15.2 Measuring quality -- why and how? 267 15.3 Analysing administrative sources -- input data quality 271 15.4 Output data quality 278 15.5 The integration process -- integration errors 279 15.5.1 Creating register populations -- coverage errors 280 15.5.2 Creating statistical units --errors in units 282 15.5.3 Creating statistical variables -- errors in variables 283 15.6 Random variation in register data 288 15.7 The register system and data warehousing 291 15.8 Conclusions 295 Chapter 16 Conclusions 297 References 301 Index 305

About the Author :
Anders Wallgren and Britt Wallgren, Statistics Sweden.

Review :
"I believe that sufficient practical information is provided to make the book worth reading." ("Technometrics", November 2008)"I believe that sufficient practical information is provided to make the book worth reading." ("Technometrics, " Nov 2008)