16 It should be noted that there is only variation in this variable for the periods starting in 1939. There are many more refugees now, perhaps more than twenty-five million worldwide. This contrasts with other historical episodes of refugee inflows. The validity of cluster-robust inference requires that the number of clusters is large (Cameron et al., 2008). There is a negative and significant interaction effect which is almost equal in size of the main effect. The data stem from the occupation censuses in 1925 and 1939. This pattern suggests that there was no new spatial equilibrium and that location fundamentals are more important than agglomeration economies. Comparing growth in expellee population with that of non-expellees reveals that the effect is seven times stronger for the former group when not considering endogenous controls (Models III and VI). Including planning region-fixed effects circumvents the issue that the standard assumptions underlying the estimates for confidence intervals in DiD analyses are not appropriate if there are only one treatment and one control region (for further details, see Conley and Taber, 2011). Expellee characteristics comprise the share of expellees from the former eastern German territories, the share of expellees from Czechoslovakia, the share of Protestants among expellees, the share of expellees in non-agricultural private sector self-employment and the share of expellees that are active in agriculture in 1950. This pattern cannot be addressed by the small sample of Schumann (2014) who exploits mainly municipalities in a specific spatial context nor by Braun et al. One can speculate that expellees were negatively selected into public relocation programs, namely that only people that were not yet economically and socially integrated in the regions where they initially arrived, participated in the scheme. The United States is no longer the economic giant it was in 1945. This notwithstanding, the analysis demonstrates that temporary place-based migration barriers in the wake of a refugee crisis can have long-run negative implications for regional development. The results are robust to controlling for an array of other factors that determined expellee resettlement and long-run development. Expellees are defined as Germans from the former Eastern territories which are nowadays part of Poland and Russia, Sudeten Germans who resided in Czechoslovakia before WWII and so-called Volksdeutsche who were spread all over Central and Eastern European territories before 1945. Further analyses show that population growth in the former French occupation zone is to a lower degree related to growth in income levels as compared to other regions which suggest that the population inflow in these areas did contribute less to economic development. There are further methodologically appealing features of the empirical setting that circumvents typical issues in migration research like self-selection which is typically also present in the assessment of economic impacts of refugee crises (Engel and Ibanez, 2007; Ruiz and Vargas-Silva, 2013; Haan et al., 2017). 9 Brakman et al. The models of Table 2 show that war-time destruction in 1945 is negatively related to long-term growth.16 Distance to GDR and Czechoslovakia play no meaningful role. 4 There are also micro studies on the economic integration of expellees (Falck et al., 2013; Bauer et al., 2013). In the early 1960s, the public resettlement policies were fading out which suggests that there was no adjustment of population levels beyond the direct effects of this scheme. They mention that return migration is no issue since German expellees could not move back to their former home regions in Central and Eastern Europe. 
The share of men in conscription-prone age groups has a positive effect on growth in models that span the period 19251970. In Section 4.4, it was speculated that the in-migration into the French occupation zone after 1950 came along with a negative selection of expellees into the relocation program that implied that regions developed less successful as compared to places where particularly those expellees remained that were already economically integrated. The interaction between the post-1950 dummy and war-time destruction is insignificant. The other models suggest that the coefficient is not getting smaller for time periods including years beyond 1961.15 Rather there is even a slight increase in the gap. Behrens et al., 2014). option. 21 The correlation between the population share of expellees and the share of expellees living in emergency accommodations (Notunterkuenfte) was r = 0.78, while it is also highly correlated with local unemployment rates (r = 0.56). Falck et al., 2013). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, Southsouth migration and female labor supply in the Dominican Republic, Making markets decisive: a firm-level evaluation of state-led development in the ChinaMyanmar border region, How to enter high-opportunity places? All areas of sociology are welcome. In a first robustness check, endogenous controls, as discussed in Section 3.3, are introduced (Table 3). These patterns suggest that particularly war-time destruction is informative about migration behavior after 1950 and deserves a closer inspection. These studies have a limited time frame as well. Including the other year-interactions implies only a slight decrease in the coefficient which turns into insignificance (Model II). This procedure works well if economic activity is homogeneously distributed in an area but would be problematic if economic activity in counties is highly concentrated. 11 Due to data constraint, for the year 1925 the population share aged above 15 years is used to capture the workforce. They come from a greater variety of countries. 3 For a discussion of selectivity of refugee migration, see Engel and Ibanez (2007). 8 million expellees arrived in the late 1940s.
The border did not follow any historical state borders within Germany. In Model I of Table 5, the controls for war-related and natural conditions are interacted with year dummies for 1939 and 1950 to account for differential impacts of these factors during the first post-war years and the post-1950 period as compared to the pre-war years. They were too differentin the 1940s and early 1950s that meant some were Jewish. 7 An alternative would be to use the Federal States as clustering variable. This section devotes attention to population growth after removing the migration barrier. Information on war-time destruction comes from the housing census as of 1950 (Gebaeude- und Wohnungszaehlung) (Statistisches Bundesamt, 1956) which was conducted on the same day as the population and occupation census that are utilized in the analysis. Areas close to the new eastern border are expected to have higher shares of expellees (Braun and Kvasnicka, 2014). Population shocks and their impact on the spatial distribution of population over time gained attention recently. Introducing the year-war destruction interactions reduces the 1950 DiD coefficient substantially (Table 5, Model I). All Rights Reserved. Michael Wyrwich, Migration restrictions and long-term regional development: evidence from large-scale expulsions of Germans after World War II, Journal of Economic Geography, Volume 20, Issue 2, March 2020, Pages 481507, https://doi.org/10.1093/jeg/lbz024. We need to start now so that seventy-five years from now we can look back on a history of refugees resettled and societies enriched. This was a political decision by French authorities responsible for administering a part of Germany after WWII. But mostly they measured their success as most Americans do: in jobs that contributed to society and provided economic security, in families raised, and in opportunities to set and achieve personal goals. The empirical regularities found in this article also suggest that there is a negative treatment effect for regions where we should expect the prevalence of agglomeration forces while location fundamentals seem to matter in other areas. Thus, also policies to deal with asymmetric population shocks depend on this capacity. In Model III, the population share of expellees in 1950 is introduced.