418:
65:
Estimation of truncated regression models is usually done via parametric maximum likelihood method. More recently, various semi-parametric and non-parametric generalisation were proposed in the literature, e.g., based on the local least squares approach or the local maximum likelihood approach, which
35:. That means observations with values in the dependent variable below or above certain thresholds are systematically excluded from the sample. Therefore, whole observations are missing, so that neither the dependent nor the independent variable is known. This is in contrast to
493:
169:
Heckman, James J. (1976). "The Common
Structure of Statistical Models of Truncation, Sample Selection, and Limited Dependent Variables and a Simple Estimator for Such Models".
483:
459:
40:
32:
268:
399:
369:
343:
324:
116:
39:
where only the value of the dependent variable is clustered at a lower threshold, an upper threshold, or both, while the value for
452:
353:
498:
226:
488:
478:
445:
75:
36:
276:
28:
85:
269:"Local Likelihood Estimation of Truncated Regression and its Partial Derivatives: Theory and Application"
58:
noted the similarity between truncated and otherwise non-randomly selected samples, and developed the
24:
20:
50:, and consequently the development of suitable estimation techniques has long been of interest in
293:
249:
207:
151:
59:
47:
395:
391:
365:
357:
339:
320:
112:
429:
383:
285:
241:
199:
143:
106:
132:
Amemiya, T. (1973). "Regression
Analysis When the Dependent Variable is Truncated Normal".
472:
384:
379:
315:
Breen, Richard (1996). "Sample-Selection Models and the
Truncated Regression Model".
253:
80:
55:
297:
425:
190:
134:
51:
362:
Unifying
Political Methodology : the Likehood Theory of Statistical Inference
289:
46:
Sample truncation is a pervasive issue in quantitative social sciences when using
245:
188:
Heckman, James J. (1979). "Sample
Selection Bias as a Specification Error".
417:
211:
155:
317:
Regression Models : Censored, Samples
Selected, or Truncated Data
108:
Regression Models : Censored, Samples
Selected, or Truncated Data
203:
147:
386:
Limited-Dependent and
Qualitative Variables in Econometrics
433:
382:(1983). "Censored and Truncated Regression Models".
494:Mathematical and quantitative methods (economics)
390:. New York: Cambridge University Press. pp.
227:"Nonparametric Censored and Truncated Regression"
364:. Cambridge University Press. pp. 208–230.
336:Semiparametric Estimation of Selectivity Models
453:
267:Park, B. U.; Simar, L.; Zelenyuk, V. (2008).
8:
460:
446:
171:Annals of Economic and Social Measurement
319:. Thousand Oaks: Sage. pp. 33–47.
97:
54:and related disciplines. In the 1970s,
484:Single-equation methods (econometrics)
111:. Thousand Oaks: Sage. pp. 2–4.
7:
414:
412:
432:. You can help Knowledge (XXG) by
14:
358:"Models with Nonrandom Selection"
416:
225:Lewbel, A.; Linton, O. (2002).
1:
290:10.1016/j.jeconom.2008.08.007
17:Truncated regression models
515:
411:
338:. New York: Nova Science.
66:are kernel based methods.
37:censored regression models
31:for certain ranges of the
76:Censored regression model
334:Frölich, Markus (2002).
277:Journal of Econometrics
246:10.1111/1468-0262.00304
105:Breen, Richard (1996).
428:-related article is a
86:Truncated distribution
41:independent variables
499:Econometrics stubs
60:Heckman correction
48:observational data
33:dependent variable
489:Regression models
479:Actuarial science
441:
440:
506:
462:
455:
448:
420:
413:
405:
389:
375:
349:
330:
302:
301:
273:
264:
258:
257:
231:
222:
216:
215:
185:
179:
178:
166:
160:
159:
129:
123:
122:
102:
514:
513:
509:
508:
507:
505:
504:
503:
469:
468:
467:
466:
409:
402:
378:
372:
352:
346:
333:
327:
314:
311:
309:Further reading
306:
305:
271:
266:
265:
261:
229:
224:
223:
219:
204:10.2307/1912352
187:
186:
182:
168:
167:
163:
148:10.2307/1914031
142:(6): 997–1016.
131:
130:
126:
119:
104:
103:
99:
94:
72:
19:are a class of
12:
11:
5:
512:
510:
502:
501:
496:
491:
486:
481:
471:
470:
465:
464:
457:
450:
442:
439:
438:
421:
407:
406:
400:
380:Maddala, G. S.
376:
370:
350:
344:
331:
325:
310:
307:
304:
303:
284:(1): 185–198.
259:
240:(2): 765–779.
217:
198:(1): 153–161.
180:
161:
124:
117:
96:
95:
93:
90:
89:
88:
83:
78:
71:
68:
43:is available.
13:
10:
9:
6:
4:
3:
2:
511:
500:
497:
495:
492:
490:
487:
485:
482:
480:
477:
476:
474:
463:
458:
456:
451:
449:
444:
443:
437:
435:
431:
427:
422:
419:
415:
410:
403:
401:0-521-24143-X
397:
393:
388:
387:
381:
377:
373:
371:0-521-36697-6
367:
363:
359:
355:
351:
347:
345:1-59033-277-6
341:
337:
332:
328:
326:0-8039-5710-6
322:
318:
313:
312:
308:
299:
295:
291:
287:
283:
279:
278:
270:
263:
260:
255:
251:
247:
243:
239:
235:
228:
221:
218:
213:
209:
205:
201:
197:
193:
192:
184:
181:
176:
172:
165:
162:
157:
153:
149:
145:
141:
137:
136:
128:
125:
120:
118:0-8039-5710-6
114:
110:
109:
101:
98:
91:
87:
84:
82:
81:Sampling bias
79:
77:
74:
73:
69:
67:
63:
61:
57:
56:James Heckman
53:
49:
44:
42:
38:
34:
30:
26:
23:in which the
22:
18:
434:expanding it
426:Econometrics
423:
408:
385:
361:
335:
316:
281:
275:
262:
237:
234:Econometrica
233:
220:
195:
191:Econometrica
189:
183:
174:
170:
164:
139:
135:Econometrica
133:
127:
107:
100:
64:
52:econometrics
45:
16:
15:
473:Categories
354:King, Gary
177:: 475–492.
92:References
254:120113700
29:truncated
27:has been
356:(1989).
298:55496460
70:See also
212:1912352
156:1914031
398:
394:–196.
368:
342:
323:
296:
252:
210:
154:
115:
25:sample
21:models
424:This
294:S2CID
272:(PDF)
250:S2CID
230:(PDF)
208:JSTOR
152:JSTOR
430:stub
396:ISBN
366:ISBN
340:ISBN
321:ISBN
113:ISBN
392:149
286:doi
282:146
242:doi
200:doi
144:doi
475::
360:.
292:.
280:.
274:.
248:.
238:70
236:.
232:.
206:.
196:47
194:.
175:15
173:.
150:.
140:41
138:.
62:.
461:e
454:t
447:v
436:.
404:.
374:.
348:.
329:.
300:.
288::
256:.
244::
214:.
202::
158:.
146::
121:.
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.