Agricultural Survey Methods

Agricultural Survey Methods......Page 5
Contents......Page 9
List of Contributors......Page 19
Introduction......Page 23
1.1 Introduction......Page 27
1.2.1 General......Page 30
1.2.2 Specific agricultural statistics in the UNECE region......Page 32
1.3.1 The governance of agricultural statistics......Page 41
1.3.2 Horizontal issues in the methodology of agricultural statistics......Page 42
1.4 Development in the demand for agricultural statistics......Page 46
1.5 Conclusions......Page 48
Acknowledgements......Page 49
Reference......Page 50
Part I Census, Frames, Registers and Administrative Data......Page 51
2.1 Introduction......Page 53
2.2 Registers, register systems and methodological issues......Page 54
2.3.1 One source......Page 55
2.3.3 Use in a system for agricultural statistics linked with the business register......Page 56
2.4 Creating a farm register: the population......Page 60
2.5 Creating a farm register: the statistical units......Page 64
2.6 Creating a farm register: the variables......Page 68
References......Page 70
3.1 Introduction......Page 71
3.4 Direct tabulation of administrative data......Page 72
3.4.1 Disadvantages of direct tabulation of administrative data......Page 73
3.5.1 Coverage of administrative registers......Page 74
3.6.1 Quality control of the IACS data......Page 75
3.6.2 An estimate of errors of commission and omission in the IACS data......Page 76
3.7.1 Matching different registers......Page 77
3.7.3 Taking advantage of administrative data for censuses......Page 78
3.8 Calibration and small-area estimators......Page 79
3.9 Combined use of different frames......Page 80
3.9.2 Accuracy of estimates......Page 81
3.9.3 Complex sample designs......Page 82
3.10.1 Combining a list and an area frame......Page 83
3.11 Conclusions......Page 84
Acknowledgements......Page 85
References......Page 86
4.1 Introduction......Page 89
4.2.2 Classification......Page 90
4.3 Sampling......Page 91
4.4.1 Response error......Page 92
4.4.2 Non-response......Page 93
4.6 Weighting......Page 94
4.8 Disclosure avoidance......Page 95
4.9 Dissemination......Page 96
References......Page 97
5.1 Introduction......Page 99
5.2 Statistics Canada’s agriculture statistics programme......Page 100
5.4 Strategy to add farms to the farm register......Page 101
5.4.3 Step 3: Search for the potential farms from E on M......Page 102
5.5.2 2001 Coverage Evaluation Study......Page 103
5.6 2006 Census......Page 104
5.6.1 2006 Missing Farms Follow-up......Page 105
5.6.2 2006 Coverage Evaluation Study......Page 106
5.8 Conclusions......Page 107
References......Page 109
Part II Sample Design, Weighting and Estimation......Page 111
6.1 Introduction......Page 113
6.2.1 Probability proportional to size selection of area units......Page 114
6.2.4 Integrated versus separate sectoral surveys......Page 116
6.3 Description of the basic design......Page 117
6.4.1 The effect of ‘random’ weights......Page 119
6.4.3 Meeting sample size requirements......Page 120
6.5.2 Data by StrCon and sector (aggregated over areas)......Page 121
6.6.1 Numerical illustrations......Page 123
6.6.2 More flexible models: an empirical approach......Page 126
6.7 Conclusions......Page 130
References......Page 131
7.1 Introduction......Page 133
7.2 Stratification......Page 135
7.3 Probability proportional to size sampling......Page 139
7.4 Balanced sampling......Page 142
7.5 Calibration weighting......Page 144
7.6 Combining ex ante and ex post auxiliary information: a simulated approach......Page 150
7.7 Conclusions......Page 154
References......Page 155
8.2.1 Network sampling......Page 159
8.2.2 Adaptive sampling......Page 161
References......Page 164
9.1 Introduction......Page 165
9.3 Synthetic and composite estimates......Page 166
9.3.2 Composite estimates......Page 167
9.4 Area-level models......Page 168
9.5 Unit-level models......Page 170
9.6 Conclusions......Page 172
References......Page 173
Part III GIS and Remote Sensing......Page 175
10.1 Introduction......Page 177
10.2 Integrating agricultural and environmental information with LUCAS......Page 180
10.3 LUCAS 2001–2003: Target region, sample design and results......Page 181
10.4 The transect survey in LUCAS 2001–2003......Page 182
10.5 LUCAS 2006: a two-phase sampling plan of unclustered points......Page 184
10.7 Ground work and check survey......Page 185
10.8 Variance estimation and some results in LUCAS 2006......Page 186
10.9 Relative efficiency of the LUCAS 2006 sampling plan......Page 187
10.10 Expected accuracy of area estimates with the LUCAS 2006 scheme......Page 189
10.11.2 Excluded areas......Page 190
10.12 Conclusions......Page 191
References......Page 192
11.1 Introduction......Page 195
11.1.1 Brief history......Page 196
11.1.3 Disadvantages of using an area frame......Page 197
11.1.4 How the NASS uses an area frame......Page 198
11.2 Pre-construction analysis......Page 199
11.3 Land-use stratification......Page 202
11.4 Sub-stratification......Page 204
11.5 Replicated sampling......Page 206
11.6 Sample allocation......Page 209
11.7 Selection probabilities......Page 211
11.7.1 Equal probability of selection......Page 212
11.7.2 Unequal probability of selection......Page 213
11.8.2 Unequal probability of selection......Page 214
11.9 Sample rotation......Page 215
11.10 Sample estimation......Page 216
11.11 Conclusions......Page 218
12.1 Introduction......Page 219
12.2 Satellites and sensors......Page 220
12.3 Accuracy, objectivity and cost-efficiency......Page 221
12.4 Main approaches to using EO for crop area estimation......Page 222
12.7 Calibration and regression estimators......Page 223
12.8.1 US Department of Agriculture......Page 225
12.9 The GEOSS best practices document on EO for crop area estimation......Page 226
12.11 Accuracy assessment of classified images and land cover maps......Page 227
12.13 Forecasting yields......Page 229
12.14 Satellite images and vegetation indices for yield monitoring......Page 230
12.15.1 USDA......Page 231
12.15.2 Global Information and Early Warning System......Page 232
References......Page 233
13.1 Introduction......Page 239
13.2.1 Sampling strategy......Page 240
13.2.2 Ground and remote sensing data for land cover estimation in a small area......Page 242
13.3.1 An overview of the missing data problem......Page 244
13.3.2 Multiple imputation......Page 245
13.3.3 Multiple imputation for missing data in satellite images......Page 247
13.4 Analysis of the 2006 AGRIT data......Page 248
13.5 Conclusions......Page 253
References......Page 255
Part IV Data Editing and Quality Assurance......Page 257
14.1 Introduction......Page 259
14.2.1 Data capture......Page 262
14.2.2 Edit......Page 263
14.2.3 Imputation......Page 264
14.3.2 Micro-analysis......Page 265
14.4 Development status......Page 266
14.5 Conclusions......Page 267
References......Page 268
15.1 Introduction......Page 269
15.2 Edit rules......Page 271
15.3 The role of automatic editing in the editing process......Page 272
15.4 Selective editing......Page 273
15.4.1 Score functions for totals......Page 274
15.4.2 Score functions for changes......Page 276
15.4.3 Combining local scores......Page 277
15.4.4 Determining a threshold value......Page 278
15.5 An overview of automatic editing......Page 279
15.6 Automatic editing of systematic errors......Page 281
15.7 The Fellegi–Holt paradigm......Page 282
15.8.1 The Fellegi–Holt method......Page 283
15.8.3 The vertex generation approach......Page 285
15.8.4 A branch-and-bound algorithm......Page 286
15.9 Conclusions......Page 289
References......Page 290
16.1 Introduction......Page 293
16.2.1 The American example......Page 294
16.2.2 The Swedish example......Page 297
16.3.1 Quality assurance as an agency undertaking......Page 300
16.3.2 Examples of quality assurance efforts......Page 301
References......Page 302
17.1 Introduction......Page 303
17.2 Evolution of agriculture industry structure and user needs......Page 304
17.3 Agriculture statistics: a centralized approach......Page 305
17.4 Quality Assurance Framework......Page 307
17.5.1 Managing relevance......Page 309
17.5.2 Managing accuracy......Page 312
17.5.3 Managing timeliness......Page 319
17.5.4 Managing accessibility......Page 320
17.5.5 Managing interpretability......Page 322
17.5.6 Managing coherence......Page 323
17.6 Quality management assessment......Page 325
References......Page 326
Part V Data Dissemination and Survey Data Analysis......Page 329
18.1 Introduction......Page 331
18.2 The data situation in the NASS......Page 332
18.4 How does it work?......Page 334
18.5 What we learned......Page 336
18.7 Conclusions......Page 338
19.1 Introduction......Page 339
19.2 Data access and dissemination......Page 340
19.3 General characteristics of SDA......Page 342
19.4 A sample session using SDA......Page 344
19.5 Conclusions......Page 346
References......Page 348
20.1 Introduction......Page 349
20.2 Requirements of sample surveys for economic analysis......Page 351
20.3 Typical contents of a farm economic survey......Page 352
20.4.1 Multipurpose sample weighting......Page 353
20.4.2 Use of sample weights in modelling......Page 354
20.5.1 Data and modelling issues......Page 356
20.5.2 Economic and econometric specification......Page 357
20.6.1 ABARE broadacre survey data......Page 358
20.6.2 Time series model of the growth in fodder use in the Australian cattle industry......Page 359
20.6.3 Cross-sectional model of land values in central New South Wales......Page 361
References......Page 364
21.1 Introduction......Page 367
21.2.1 Resilience......Page 369
21.2.3 Vulnerability versus resilience......Page 371
21.3.1 The resilience framework......Page 373
21.3.2 Methodological approaches......Page 374
21.4.1 The Palestinian data set......Page 376
21.4.2 The estimation procedure......Page 377
21.5.1 Model validation with CART......Page 385
21.5.2 The role of resilience in measuring vulnerability......Page 389
21.5.3 Forecasting resilience......Page 390
21.6 Conclusions......Page 391
References......Page 392
22.1 Introduction......Page 395
22.2 The proposed approach......Page 398
22.2.1 A simulated exercise......Page 400
22.3 Case study: the province of Foggia......Page 402
22.3.1 The AGRIT survey......Page 403
22.3.2 Durum wheat yield forecast......Page 404
22.4 Conclusions......Page 410
References......Page 411
Author Index......Page 415
Subject Index......Page 421