hort dummy. To increase statistical precision, birth cohorts are grouped.
8
Individu- als born between 1955 and 1960 form the control group, and this cohort dummy is
omitted from the regression. These unrestricted estimates in Equation 2 present the cohort- specifi c impacts of the wartime destruction. Thus, each coeffi cient β
1c
can be interpreted as an estimate of the effects of wartime destruction on a given cohort. For
the validity of identifying the assumption above, the effects of wartime destruction should be zero or negligible for the cohorts that completed their education before the
outbreak of WWII cohorts born between 1907 and 1916 and for the cohorts starting their education after the reconstruction of school inputs was completed in the early
1960s cohorts born between 1951 and 1960.
IV. Data and Descriptive Statistics
The measure of WWII destruction intensity that I use for my main anal- ysis is from Kaestner 1949, who reports the results of a survey undertaken by the Ger-
man Association of Cities “Deutscher Staedtetag”. Kaestner provides municipality- level information on the aggregate residential rubble in m
3
per capita accumulated in former West Germany by the end of WWII.
9
In order to examine prewar regional conditions and assess the mechanisms through which WWII destruction might have affected children’s
long- run outcomes, I gathered novel data from various years of the German Municipali- ties Statistical Yearbooks. First, I assembled detailed regional information on the number
of schools, teachers, and students to gauge the change in school inputs available to the affected cohorts. Second, I utilized regional data on postwar education and health expen-
diture per capita to analyze postwar government spending from various years of German Municipalities Statistical Yearbooks. Additionally, I compiled data on prewar regional
characteristics including average income per capita, area, and population density.
The data on individual and household characteristics are from the German Socio- Economic Panel GSOEP. The GSOEP is a household panel survey that is representa-
tive of the entire German population residing in private households. It provides a wide range of information on individual and household characteristics as well as parental
background and childhood environment. The GSOEP also incorporates war- related questions including whether an individual’s father was involved in WWII and whether
hisher parents died during the war years. In addition, the GSOEP asks respondents whether they still live in the area where they grew up.
10
I restrict the main empirical
8. Appendix Table A1 suggests that individuals born between 1936 and 1939 were of primary school age during WWII. Similarly, the 1931-35 birth cohorts were of primary and lower secondary school age; indi-
viduals born between 1925 and 1930 were of lower secondary and upper secondary school age during the war years. Appendix Table A1 also shows that individuals born between 1922 and 1924 were of upper secondary
and college age and the 1917-21 cohorts were of college age during WWII. Following the categorization presented in Appendix Table A1, I group the affected birth cohorts accordingly in Table 4.
9. The data on rubble in m
3
per capita and population in 1939 are available for almost all towns with 10,000 or more inhabitants in 1939.
10. The GSOEP question based on which the movers are identifi ed in this paper is “Do you still live in the city or area where you grew up until age 15?” with three possible responses “yes, still,” “yes, again,” and “no.” I have
coded individuals who answered this question as “yes, still” and “yes, again” as nonmovers. The interpretation of city or area was left to the perception of the respondents; therefore, it is likely that individuals are coded as mov-
ers even though they relocated within the same ROR rendering their exposure to WWII destruction unchanged.
analysis to individuals born between 1922 and 1960. I dropped individuals born be- tween 1940 and 1950 from the analysis as they were at school- going age during the
reconstruction period that ended in the early 1960s; thus they were partly exposed to the adverse effects of WWII destruction.
11
I consider the effects of WWII at the smallest representative geographical units “ROR” or “region” provided in GSOEP.
12
I obtain the historical data set used in my analysis by compiling the municipality- level data on WWII destruction and other
regional macrovariables from the various years of German Municipalities Statistical Yearbooks. I then aggregate these variables according to the 1985 German regional
ROR boundaries. This aggregation is possible since every municipality reported in the yearbooks belongs to only one ROR. Finally, I merge this aggregated ROR- level
historical data with the 1985 wave of GSOEP by an individual’s ROR.
13
I choose the 1985 wave of GSOEP because this is the earliest date both households’ ROR informa-
tion and individual and parental characteristics are available. Furthermore, the 1985 wave of GSOEP is only available for former West Germany.
Table 1 presents the descriptive statistics for war destruction measures and variables measuring prewar regional conditions. Table 1 shows that the average West German
region experienced a great deal of destruction: 10.26 rubble in m
3
per capita and 33 percent of total housing units were destroyed. There was variation across regions in
destruction intensity; regions with above- average destruction had around four times the rubble per capita as regions with below- average destruction. Table 1 also points
that highly destroyed regions are larger in area and have higher population density and average income per capita before WWII. Therefore, if we rely only on cross- region
variation in destruction to estimate the long- term effects of wartime destruction on children’s outcomes, it is diffi cult to isolate the effects of destruction from other region-
specifi c characteristics. The difference- in- differences strategy I propose therefore uses within- region cross- cohort variation to identify the effects of destruction, and controls
for differences between birth cohorts common across Germany.
14
Table 2 shows the descriptive statistics of the outcomes and the main individual- level control variables I use in my estimation. One of the main outcomes of interest is years of
schooling completed. The GSOEP asks respondents about educational attainment, then in the data fi les maps these attainment categories into years of schooling. In addition,
I will analyze health and labor market outcomes. I use three measures of adult health
11. The results for the entire sample, where these 1940-50 cohorts are added to the control group are pre- sented in Column 2 of Appendix Table A3. Point estimate for this specifi cation is smaller in magnitude but
statistically similar to the main education results presented in Table 3. 12. These units are called Raumordnungsregionen RORs and are determined by the Federal Offi ce for
Building and Regional Planning Bundesamt fuer Bauwesen und Raumordnung, BBR. West Germany has 75 different Raumordnungsregionen. RORs are “spatial districts” based on economic interlinkages and commut-
ing fl ows of areas. RORs encompass the aggregation of Landkreise and kreisfreie Städte Jaeger et al. 2010. 13. The rubble per capita measure is not available for Saar region, which joined West Germany in 1957.
Schleswig, Ditmarschen, Emsland, Hochrhein-Bodensee, and Oberland are other RORs with missing wartime destruction data.
14. The observed differences in population density, area, and per capita income may suggest possible dif- ferences in trends in children’s outcomes. Below, I assess whether there are differential trends by doing a
falsifi cation testcontrol experiment using data on cohorts who would have completed their schooling before WWII. Moreover, I control for the interaction of prewar regional population density with birth year dummies
in my analysis.
including adult height, mortality, and self- reported health satisfaction, and the logarithm of hourly wage as a labor market outcome. These outcomes are measured four decades
after WWII and refl ect the outcomes of WWII survivors who lived to 1985 or later.
V. Estimation Results
