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424 NATIONALØKONOMISK TIDSSKRIFT 2005. NR. 3 Identification of the correlation between the unobservable components is obtained through multiple occurrences of both marriage spells and premarital cohabitation status for the individuals, as suggested by identification results for duration models with multiple spells, cf. Honoré (1993). This identification approach has been used in a series of papers by Lillard and co-authors (see e.g., Panis and Lillard (1994), Lillard et al. (1995), and Upchurch et al. (2002)). Identification requires that I – for at least a subset of individuals – observe marriage spells both when the individual premaritally cohabited and when the individual did not. The intuition for identification is spelled out in Panis (2004). In terms of our application, his argument goes as follows: suppose I observe only one respondent over a long period of time during which she switches premarital cohabitation status. With a sample of one, there is no heterogeneity and no correlation across equations, such that the equations are independent. The effect of premarital cohabitation on exit rates from marriage is identified because of repeated observations on marriage spells and variations in premarital cohabitation status. More generally, conditional on heterogeniety, the equations are independent and identification rests on repeated outcomes with intraperson variation in premarital cohabitation status. In terms of intraperson variation in premarital cohabitation status 4% of the individuals in the sample are observed both as premarital cohabitators and not. Obviously, basing identification on 4% of the sample is not the most attractive nor powerful identification strategy. The author of this article were, however, not able to come up with an instrument that could explain premarital cohabitation and at the same time not influence divorce decisions. 5. Results In Table 5.1 I report the maximum likelihood estimates for the parameters of the estimated model. Since I only observe that a divorce has occurred sometime within a given year, I use explanatory variables or time t - 1 to explain the divorce hazard at time t in order to avoid that the value of a given characteristic is influenced by the divorce event. Compared to Svarer (2004) I pay more attention to the possible endogeneity of premarital cohabitation in the divorce hazard. This is, however, not the only potential endogenous variable. Several of the included explanatory variables face the same issue of endogeneity. Weiss and Willis (1997) provide evidence of this with respect to earnings, Johnson and Skinner (1986) with respect to female labour supply, Lillard and Waite (1993) with respect to children, and Lillard and Panis (1996) with respect to health. The endogeneity problem of other variables than cohabitation will not be explicitly addressed in the empirical model. However, I keep the endogeneity issues in mind when drawing inference.
TWO TESTS OF DIVORCE BEHAVIOUR ON DANISH MARRIAGE MARKET DATA 425 Table 3. Results from econometric model. a Cohabitation decision Hazard of divorce Coeff. Std dev. Coeff. Std dev. Cohabitation Couple has cohabited -0.6970b 0.1418 Duration of cohabitation -0.1284b Deviation between predicted and realised earnings 0.0181 Positive deviation, wife 0.6092b 0.1254 0.2677b 0.1032 Negative deviation, wife -0.1647b 0.0220 0.0611b 0.0144 Positive deviation, husband 0.0518 0.1202 -0.3267b 0.1070 Negative deviation, husband -0.2525b 0.0280 0.0386b Husband’s education 0.0168 Vocational 0.1255b 0.0889 -0.3562b 0.0723 Short 0.0233 0.1618 -0.1637 0.1361 Medium -0.1380 0.1540 -0.4874b 0.1522 Long 0.0158 0.1413 -0.7911b Children 0.1588 Own children younger than 2 0.5469b 0.1760 -0.4613b 0.0545 Own children between 3 and 6 1.8239b 0.1909 -0.0968b 0.0583 Own children between 7 and 9 1.4347b 0.1793 -0.1181b 0.0692 Own children between 10 and 17 1.4310b 0.1820 0.0243 0.0887 Step children -1.3673b 0.2042 0.5263b 0.0906 Premarital birth to the couple 6.5812 8.8726 0.2771b Age 0.0838 Wife between 15-20 -1.1765b 0.1737 0.1272 0.1470 Wife between 21-25 -0.9160b 0.1476 0.2637b 0.1073 Wife between 26-30 -1.1010b 0.1500 0.0634 0.0908 Husband between 15-20 0.8542b 0.1748 0.4790b 0.1775 Husband between 21-25 1.0460b 0.1453 0.2819b 0.1165 Husband between 26-30 0.7899b 0.1334 0.2180b 0.0911 Wife more than 4 years older -0.8507b 0.1481 0.1062 0.1363 Husband more than 4 years older -0.0959b 0.0798 0.2636b Sickness and unemployment 0.1073 Sickness, wife -0.0682 0.0930 0.2104b 0.0631 Sickness, husband -0.2924b 0.0951 0.2617b 0.0662 Unemployment degree, wife -0.3725b 0.1214 0.3900b 0.0944 Unemployment degree, husband -0.4902b 0.1578 0.9638b Other characteristics 0.1266 2nd or higher order marriage -1.0919b 0.1612 0.0344 0.1722 Province 0.3462b 0.0586 -0.3628b 0.0623 vd 2 -1.6469b v 0.3431 c 1 1.7575b v 0.2132 c 2 P1(v 0.3664 0.2461 d = 0, v c = vc 1 ) P2(v 0.4960 0.3431 d = vd 2 , vc = v c 2 ) 0.5040b Number of observations 0.1150 10882 Notes: (a) The reference categories are: no education above mandatory education and over 30 years old. ( b ) significant at .05. ( c ) significant at .1.
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Nationaløkonomisk Tidsskrift 143 (
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OM LÆREPLADSSPØRGSMÅLET 3 serier
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OM LÆREPLADSSPØRGSMÅLET 5 90000
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OM LÆREPLADSSPØRGSMÅLET 7 0,60 0
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MILJØMODELLER TIL ADAM 27 ling i D
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MILJØMODELLER TIL ADAM 35 Tabel 4.
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MILJØMODELLER TIL ADAM 37 8%). End
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MILJØMODELLER TIL ADAM 41 Konkurre
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THE EFFECT OF LABOUR MARKET CONDITI
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DEBAT OG KOMMENTARER 121 Appendiks:
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BOGANMELDELSER 123 J. A. Schumpeter
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126 NATIONALØKONOMISK TIDSSKRIFT 2
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132 Det fremgår, at minimering af
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136 3 2 1 0 -1 -2 -3 -4 1986 1988 1
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138 Ymax Fmax Flag NATIONALØKONOMI
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142 1,50 1,25 1,00 0,75 0,50 0,25 N
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146 3 2 1 0 -1 -2 -3 -4 Filtrerede
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150 Dahl, C., H. Hansen og J. Smidt
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152 Autoregressiv model. (Ymax = 4)
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154 25 20 15 10 5 Official discount
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160 25 20 15 10 5 0 -5 Figure 3. Re
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162 ry of monetary regimes - some l
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164 Table A.1. Danish interest rate
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166 continued ... NATIONALØKONOMIS
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172 Average UIB rate pr. year 100 9
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180 Per cent 40 35 30 25 20 15 10 5
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182 Table 2. Trend adjusted differe
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186 den, Finland, Austria, Germany,
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188 continued ... NATIONALØKONOMIS
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190 1.000 kr 150 100 50 0 -50 -100
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196 Forsørgerkvote 150 140 130 120
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202 Timer 2200 2000 1800 1600 1400
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204 Pct. af BNP 5 0 2001 2011 2021
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206 Pct. 18 16 14 12 10 8 6 4 2 0 2
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210 Procent af BNP 8 4 0 2001 2021
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212 Pct. 18 16 14 12 10 8 6 4 2 0 2
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236 Bundskatteprocent 5,5 Figur 1.
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242 1999. Scandinavian Economic His
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298 rapport, København. Velfærdsk
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318 tations. An understanding of th
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