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420 Table 1. Number of marriages. NATIONALØKONOMISK TIDSSKRIFT 2005. NR. 3 Number of marriages Number of persons Percentage 1 10409 95.7 2 459 4.2 3 12 0.1 4 2 0.0 The information used in the analysis is gathered in the following way: I observe the individuals in 1980 where I have information about various personal characteristics and marriage market status. For each subsequent year I observe a new stream of data for the individuals. If the individual enters a relationship I also observe the personal characteristics of the partner. Since I am interested in marriages, and especially the personal characteristics during the marriage, I disregard left censored marriages. The individuals were between 15 and 25 years of age in 1980, and since I disregard individuals already married, the first marriage of the unit of observation is observed for the majority of the individuals (some may, of course, already be divorced). The partners are not restricted by age, and it is therefore more likely that they have experienced more marriages at the time I observe them. In the sample there are 10822 marriages during the period. The number of marriages per person is distributed as presented in Table 1. Only around 4 percent experience more than one marriage during the sample period. 3.1. Explanatory variables Table 2 contains descriptive statistics of the variables used in the analysis. The mean and standard deviation of the explanatory variables are the calculated at start of the marriage. All variables are, however, allowed to vary during the marriage spell. The main variabels of interest are a dummy indicating whether the couple premaritally cohabited and four variables representing differences in expected and realised earnings. The latter variables are constructed in the following manner. First, an earnings equation is estimated by OLS. In this first step, earnings are regressed on education, age, geographical belonging, number of kids, level of unemployment and sickness. In the second step, the predicted earnings in a given year are compared to the actual earnings to define four variables: ∧ ∧ Positive deviation i =(Earnings i,t – Earnings i,t ) if Earnings i,t > Earnings i,t , ∧ ∧ Negative deviation i = (Earnings i,t – Earnings i,t ) if Earnings i,t Earnings i,t where i = husband, wife.
TWO TESTS OF DIVORCE BEHAVIOUR ON DANISH MARRIAGE MARKET DATA 421 Table 2. Descriptive statistics of variables in sample by type of marriage. Mean Std. dev. Education of Husband Vocational 0.27 Short 0.04 Medium 0.04 Long Differences if expected and realised earnings (in DKK 1980) 0.05 Positive deviation, wife 793 7711 Negative deviation, wife 399 6156 Positive deviation, husband 1374 22108 Negative deviation, husband Age at marriage 644 7187 Wife < 21 0.20 Wife between 21-25 0.23 Wife between 26-30 0.08 Husband < 21 0.10 Husband between 21-25 0.23 Husband between 26-30 0.12 Husband more than 4 years older 0.23 Wife more than 4 years older Unemployment and sickness 0.03 Wife’s yearly degree of unemployment 0.13 0.23 Husband's yearly degree of unemployment 0.07 0.18 Sickness, wife 0.18 Sickness, husband Children 0.12 Own child younger than 2 0.26 Own child between 3 and 6 0.15 Own child between 7 and 9 0.05 Own child between 10 and 17 0.04 Presence of step children 0.13 Premarital birth 0.26 Other characteristics Province 0.53 Duration of pre-marital cohabitation 2.82 2.78 Mean duration of marriage (in years) 6.97 3.90 Number of observations 10882 In addition, we have dummies for educational attainment. The reference category is no education beyond primary school. Since some individuals may still be studying, I observe the current education at the time of observation. The educational variables are therefore also allowed to be time-varying. Next, I have six variables on children; an indicator variable for the presence of a child born to the couple younger than 3 years of
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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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OM LÆREPLADSSPØRGSMÅLET 9 givet
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OM LÆREPLADSSPØRGSMÅLET 11 over
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OM LÆREPLADSSPØRGSMÅLET 13 angiv
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OM LÆREPLADSSPØRGSMÅLET 15 Dette
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OM LÆREPLADSSPØRGSMÅLET 17 Tabel
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OM LÆREPLADSSPØRGSMÅLET 19 hverv
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OM LÆREPLADSSPØRGSMÅLET 21 Ikke
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OM LÆREPLADSSPØRGSMÅLET 23 didat
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OM LÆREPLADSSPØRGSMÅLET 25 Litte
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MILJØMODELLER TIL ADAM 27 ling i D
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MILJØMODELLER TIL ADAM 29 Tekniske
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MILJØMODELLER TIL ADAM 31 LADA kan
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MILJØMODELLER TIL ADAM 33 NH 3 54%
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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 39 portsyst
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MILJØMODELLER TIL ADAM 41 Konkurre
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BØR VIRKSOMHEDER OPLYSES OM SANDSY
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THE CONSUMPTION OF ALCOHOL IN THE S
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THE EFFECT OF LABOUR MARKET CONDITI
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DEBAT OG KOMMENTARER 105 det astron
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DEBAT OG KOMMENTARER 107 gælder ik
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DEBAT OG KOMMENTARER 109 prisstivhe
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DEBAT OG KOMMENTARER 111 keynesiane
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DEBAT OG KOMMENTARER 113 outside in
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DEBAT OG KOMMENTARER 115 Begrebet '
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DEBAT OG KOMMENTARER 117 men ikke k
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DEBAT OG KOMMENTARER 119 som et ana
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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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278 Pct. 0,20 0,15 0,10 0,05 0,00 -
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298 rapport, København. Velfærdsk
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314 hold til individuelle handelspa
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316 ters, and a comprehensive cover
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318 tations. An understanding of th
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LABOR SUPPLY BEHAVIOR AND THE DESIG
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WHAT AFFECTS STUDENTS’ PERFORMANC
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