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In: The Economic Journal, Band 101, Heft 407, S. 1020
In: Advances in econometrics 26
The economics and statistics literature using computer simulation based methods has grown enormously over the past decades. Maximum Simulated Likelihood is a statistical tool useful for incorporating individual differences (called heterogeneity in the econometrics literature) and variations into a statistical analysis. Contributors to the volume discuss alternative simulation methods that permit faster and more accurate inference, as well as applications of established methods
In: The Economic Journal, Band 106, Heft 438, S. 1458
In: Social science quarterly, Band 66, Heft 4, S. 854
ISSN: 0038-4941
In: Social science quarterly, Band 66, S. 854-866
ISSN: 0038-4941
Racial pay differentials, 1967 and 1976 compared.
In: Social science quarterly, Band 63, Heft 1, S. 16-27
ISSN: 0038-4941
Differential risk & changes in risk affect human capital accumulation, labor market supply patterns, fertility, & many other types of human behavior. One specific type of risk is examined -- that of marital dissolution. It is hypothesized that wives subject to high probabilities of marital dissolution are more likely to be working in the labor market; it is further hypothesized that these wives will have accumulated larger amounts of labor market experience than other wives. These hypotheses are tested with 1967 US Census Bureau data on 2,000 white & 2,000 black couples. A significant impact of marital dissolution risk on wives' labor supply behavior is apparent; however, labor market behavior of white wives seems more sensitive than that of black wives to changes in the risk of divorce. 1 Table, 2 Figures. Modified HA.
In: Journal of political economy, Band 84, Heft 4, Part 1, S. 655-676
ISSN: 1537-534X
In: Eastern economic journal: EEJ, Band 43, Heft 4, S. 563-579
ISSN: 1939-4632
Cover; Half-title; Title; Copyright; Contents; Figures; Tables; Preface; 1 In the beginning; 2 Basic notions of statistics; 3 Choosing; 4 Paradigms of choice data; 5 Processes in setting up stated choice experiments; 6 Choices in data collection; 7 NLOGIT for applied choice analysis: a primer; 8 Handling choice data; 9 Case study: mode-choice data; 10 Getting started modeling: the basic MNL model; 11 Getting more from your model; 12 Practical issues in the application of choice models; 13 Allowing for similarity of alternatives; 14 Nested logit estimation; 15 The mixed logit model.
In: The quarterly review of economics and finance, Band 65, S. 36-49
ISSN: 1062-9769