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1. 2 Review of related capitalization research A vast literature has inferred the value of non-marketed goods such as clean air (Chay and Greenstone, 2005), health risk (Currie et al., 2015; Davis, 2004), proximity to hazardous waste sites (Greenstone and Gallagher, 2008), crime risk (Linden and Rockoff, 2008), public school quality (Cellini et al., 2010; Gibbons et al., 2013), high-speed broadband (Ahlfeldt, Koutroumpis, et al., ♣ London School of Economics and Political Sciences (LSE) & Centre for Economic Policy Research (CEPR). g.ahlfeldt@lse.ac.uk, www.ahlfeldt.com ⊗ Darmstadt University of Technology. nitsch@vwl.tu-darmstadt.de ♦
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2. 5.2 Baseline results The tunnel entrance between the stations Nollendorfplatz and Wittenbergplatz, where Line A turns from an elevated line into an underground line, provides a source of sharp variation in rail disamenities. In the figure below, we illustrate the distributions of rail noise emitted by Line A around the tunnel entrance, as well as the distributions of land prices in levels and changes (19001904, the line opened in 1902). We restrict the sample to plots within close proximity to the track (50 meters), because this is where the noise disamenity of an elevated line is concentrated in this densely developed urban setting. We group parcels into 100-m-bins for which we then illustrate the mean value of an outcome as circles. The error bars allow for a quick evaluation of whether or not a within-bin mean is statistically different (at the 90% level) from the mean across all observations on the other side of the tunnel entrance.
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3. A collateral finding from column (1) is that per-kilometer metro rail construction costs in Berlin increased by about 4% per year from 1900 to 1930.
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4. × 𝐼𝑡 × 𝜂𝑡 Taking log-differences and rearranging the equation we obtain the longitudinal income elasticity of the marginal cost of noise: ∆ ln 𝑊𝑊𝑃𝑁 ∆ ln 𝐼 = 1 + ∆ ln(−𝛼𝑁) ∆ ln 𝐼 + ∆ ln(1 − 𝛿) ∆ ln 𝐼 + ∆ ln 𝜂 ∆ ln 𝐼 We use our baseline estimates from sections 3.2 (Table 1, column 3) and 4.2 (Table 3, column 6) in the main paper transformed into percentage terms to compute ln(−𝛼2000 𝑁 ) − ln(−𝛼1900 𝑁 ). For the change in real income ln 𝐼2000 − ln 𝐼1900 we use the German index of real GDP per capita from the Maddison Project (Bolt and van Zanden, 2014). As discussed in section 3.1 of this appendix, Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 42 real GDP per capita in Germany since 1900 grew at rates of about 2% per year, in line with the general trend in the world. This corresponds to an aggregated increase by about 650%.
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5. Abadie, A. & Gardeazabal, J., 2003. The Economic Costs of Conflict: A Case Study of the Basque Country. American Economic Review, 93(1), pp.113–132. Available at: http://www.aeaweb.org/articles?id=10.1257/000282803321455188.

6. Ahlfeldt, G.M. & Maennig, W., 2015. Homevoters vs. leasevoters: A spatial analysis of airport effects. Journal of Urban Economics, 87.
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7. Ahlfeldt, G.M. & McMillen, D.P., 2018. Tall buildings and land values: Height and construction cost elasticities in Chicago, 1870-2010. Review of Economics and Statistics, 100 (5). pp. 861-875.

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9. Ahlfeldt, G.M., Moeller, K. & Wendland, N., 2015. Chicken or egg? The PVAR econometrics of transportation. Journal of Economic Geography, 15(6).

10. Ahlfeldt, G.M., Redding, S.J., Sturm, D.M. & Wolf, N., 2015. The Economics of Density : Evidence from the Berlin Wall. Econometrica, 83(4).

11. Ahlfeldt, Gabriel M. (2018). Weights to Address Non-parallel Trends in Panel Difference-indifferences Models. CESifo Economic Studies, 64(2), 216-240.
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12. Ahlfeldt, Gabriel M., & Holman, Nancy. (2018). Distinctively Different: A New Approach to Valuing Architectural Amenities. The Economic Journal128, 1-33.

13. Ahlfeldt, Gabriel M., & Maennig, Wolfgang. (2015). Homevoters vs. leasevoters: A spatial analysis of airport effects. Journal of Urban Economics, 87, 85-99.

14. Ahlfeldt, Gabriel M., Maennig, Wolfgang, & Richter, Felix J. (2016). Urban renewal after the Berlin Wall: a place-based policy evaluation. Journal of Economic Geography, 17(1), 129-156.

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16. Ahlfeldt, Gabriel M., Redding, Stephan J., Sturm, Daniel M., & Wolf, Nikolaus. (2015). The Economics of Density: Evidence from the Berlin Wall. Econometrica, 83(6), 2127-2189.

17. Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 10 Tab A3. Descriptive statistics in weighted vs. non-weighted sample Non-weighted Weighted Mean Median S.D. Mean Median S.D. Ln land price 1881 4.213 4.094 0.605 4.388 4.094 0.615 Ln land price 1914 5.854 5.768 0.521 6.058 5.991 0.591 Station distance (km) 0.502 0.491 0.237 0.467 0.486 0.226 Noise (10 db) 0.229 0.010 0.553 0.321 0.013 0.665 Distance from CBD 2.018 2.061 0.797 1.764 1.733 1.033 Distance from sub-centre 4.212 4.258 1.725 3.999 3.703 1.712 Distance from Line A track 0.543 0.517 0.265 0.559 0.503 0.310 Notes: Source: Ahlfeldt (2018). Weights are constructed using the algorithm described in section 3.2 in the main paper and a Gaussian transformation of the mean 1881 to 1890 land price growth, the distance from the CBD and the distance from the most important sub-centre. 4.3 Time-varying OLS estimates In section 3.2 of the main paper, we focus on our preferred weighted-parallel-trend (WPT) models.
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18. Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 11 Fig A4. Difference-in-differences: Time-varying treatment effects (OLS models) Note: Time-varying treatment effects (𝛼𝑧 𝑆 and 𝛼𝑧 𝑁) based on baseline DD equation (1) and treatment function (2)in the main paper. Access parameters (effects of distance from station) multiplied by-1 so that positive shifts indicate positive economic effects. Vertical error bars indicate the 95% confidence interval based on standard errors that are clustered on parcels. Solid vertical lines denote the year of opening of the metro line (1902).
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19. Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 4 since 1900. For the world as an aggregate unit of observation, we find an average annual growth rate of about 2%. The average annual growth rate across all available countries is only marginally smaller. This is about the rate at which the US, Western Europe, and Germany grew. Other world regions such as Latin America, Africa and Asia had slightly lower growth rates of about 1%-1.5% per year.
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20. Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 48 (Reinhardt, 2015). Overall, it seems fair to conclude that metro rail users during the historical period were, on average and in relative terms, likely richer than metro rail users today.
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21. Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 58 Bajic, V. (1983). The Effects of a New Subway Line on Housing Prices in Metropolitan Toronto. Urban Studies, 20(2), 147-158.
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22. Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 59 Gibbons, Stephen. (2015). Gone with the wind: Valuing the visual impacts of wind turbines through house prices. Journal of Environmental Economics and Management, 72, 177-196.

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24. Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 61 Xu, Yangfei, Zhang, Qinghua, & Zheng, Siqi. (2015). The rising demand for subway after private driving restriction: Evidence from Beijing's housing market. Regional Science and Urban Economics, 54, 28-37.
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25. Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 7 Fig A1. 1902 Transport geography Notes: Own data collection. Own illustration based on Senatsverwaltung für Stadtentwicklung Berlin (2006).
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26. Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 8 Fig A2. 2006 Transport geography Notes: Own illustration. Data from Ahlfeldt, Redding, et al. (2015) and Senatsverwaltung für Stadtentwicklung Berlin (2006). 4 Historical difference-in-differences models 4.1 Weighted-parallel-trends difference-in-differences It is well known that causal inference using difference-in-differences models relies on the untestable assumption of parallel counterfactual trends. The idea of the weighted estimator discussed in Section 3.2 of the main paper is to reweight observations in a way that one or multiple treatment measures become orthogonal to observable trends in an outcome over the pre-treatment period.
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27. Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 9 4.2 Distribution of DD weights The algorithm described in Section 3.2 of the main paper finds a vector of parcel weights, which ensures that the partial correlations between our two treatment measures, noise and station distance, with the 1881 to 1890 property price trend are minimized. The resulting weights are plotted in Figure A3. Overall, parcels with relatively high weights are distributed relatively evenly across the study area. The most notable finding are areas with relatively low parcel weights in the central southern section and the north-eastern section of the study area.
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30. All contemporary speed parameters as well as the model parameters 𝜏, 𝜁1 and 𝜁2 are borrowed from Ahlfeldt, Redding, et al. (2015). All historical transport cost parameters are average velocities derived from the study of historical timetables. The effective accessibility premium a station s offers in a period t is then simply defined as: 𝐴𝑠𝑠 = 𝐴𝑠,𝑡,𝑧=𝑎𝑎𝑎𝑎𝑎𝑎 − 𝐴𝑠,𝑡,𝑧=𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐, where in the counterfactual we exclude the respective line segments (Line A in the historical period, the entire rail network in the contemporary period) when computing 𝑐𝑠𝑠𝑠𝑠.
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76. 𝑇𝑇𝑖 𝜆𝑇 � 2 �, where 𝜆𝑇 is a bandwidth that determines the degree of smoothing. We set the optimal bandwidth of 𝜆𝑇 = 133 meters in column (3) per the Silverman (1986) rule.3 In column (4), we use half the optimal bandwidth, which improves the local fit at the expense of a greater variance. In columns (5-6), we employ an alternative approach to estimating the discontinuity at the boundary using the following model: ln(∆𝑃𝑖𝑖) = 𝛽(𝐷𝑖 > 0)𝑖 + ∑ 𝜗𝑜 𝐷𝑖 𝑜
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83. Fig A11. Distribution by of trips by income category and transport mode Notes: Income class refers to the net monthly household income. Metro rail includes trips where part of the journey is taken by U-Bahn (subway) or S-Bahn (suburban railway). Car includes trip where part of the journey is taken by car. Raw data are micro survey data from Ahrens et al. (2009).
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84. Fig A12. Ranks in the distributions of land prices in the historical vs. the contemporary period Note: Unit of analysis is housing blocks. Data from Ahlfeldt, Redding, et al. (2015). Rank one corresponds to the highest land price within a period. Sample restricted to a balanced panel.
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85. Fig A3. Spatial distribution of pre-trend weights Notes: Classes defined based on quintiles. Own illustration using the Urban Environmental Information System of the Berlin Senate Department (Senatsverwaltung für Stadtentwicklung Berlin, 2006). Table A3 compares descriptive statistics of the weighted sample to the unweighted parcel population. The distributions are fairly similar. In line with Figure A3, the mean parcel in the weighted sample is somewhat closer to the CBD (Stadtmitte, in the north) and the sub-centre (Kurfürstendamm in the west). But, overall, the weights inspection suggests that the results in the weighted DD will not be driven by a small number of non-representative parcels, so the estimates are hopefully not too far from average effects. Most likely, the DD will have greater internal validity than the historical spatial differences estimate, which is identified from a small number of parcels around the tunnel entrance.
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86. Fig A6. Historical PTW-DD models: Distance from station gradient vs. distance bin effects Notes: Figure compares the linear distance effect from the baseline model (Table A8, column 1) to the distance bin effects estimated in Table A8, column 5. Distance bins are dummy variables indicating mutually exclusive 50-meter rings defined for 0-50, …, 700-750 meters. The residual category is 750-1000 meters. Error bars indicate the 95% confidence interval.
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87. Fig A7. Micro geography at tunnel entrance Notes: Dotted line is the orthogonal intersecting with the track at the tunnel entrance. Own illustration using the Urban Environmental Information System of the Berlin Senate Department (Senatsverwaltung für Stadtentwicklung Berlin 2006).
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90. For comparison, we present the OLS-equivalent to Figure 1 below. The OLS results turn out to be somewhat difficult to interpret. According to our estimates, parcels located closer to to-beopened stations experienced significantly lower land price growth, which points to a violation of the common trend assumption. As shown, the trend is flat from 1890 to 1896 and positive afterwards.
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91. For instance, in the final column, we add lagged land prices (1890 and 1896) to control for the effect of unobserved characteristics on land prices in levels and trends. These extensions moderately increase the magnitude of the estimated noise effect.
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114. � , 𝛼𝐴 𝑁𝑁 � )� − 1, where 𝛼𝑁 � is the estimated noise treatment level effect (as defined in equation (3) and 𝛼𝑁𝑁 � is estimated trend effect [Noise × (year – 1902) × (𝑡 > 1902)].
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115. �𝑖 + 𝜀𝑟𝑟, where ∆ln(𝑃𝑖,1890) is the change in log land price from 1881 to 1890 and tilde denotes normalization by standard deviation. In each regression, observations are weighted by Wi, which depends on the vector 𝑄(𝑞1, … , 𝑞𝑚). In the baseline approach, we select the combination of parameters that minimizes the additive objective function ∑ �𝑐𝑟 𝑉 �� 2 𝑉=(𝑆,𝑁) . As alternatives, we consider a function max�|𝑐𝑠 1| � , |𝑐𝑠 2| � �, to which we refer as min-max objective function, and a multiplicative function ∏ �𝑐𝑚 𝑞 �� 2 =(𝑆,𝑁) . In Table A5, we evaluate how the weighted DD estimates change as we alter the objective function in the algorithm. Evidently, the results are not particularly sensitive to the choice of the selection criterion.
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116. In column (6), we add interaction terms between our treatment measures and time trends (year – 1902) and the same interacted with an after-period dummy (𝑡 > 1902). With this specification, we test for an effect of the treatments on levels and trends in land prices. The near to zero and insignificant pre-trend effects [Distance × (year – 1902) and Noise × (year – 1902)], once again, confirm that the weights achieve their purpose of eliminating the conditional correlations between pre-intervention price trends on the one hand and rail noise and station access on the other.
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117. In Figure A14, we compare the estimated land price growth rates to interest rates (central bank discount and base rates). We find that the weighted (by year) average growth rates and interest rates over the period from 1881 to 2006 are roughly within the same range (about 4-5%). The correlation between the two variables is positive, with half of the observations being located above the 45-degree line and the other half below. It seems fair to conclude that over the course of about 130 years, nominal land prices in Berlin appreciated roughly at a rate that reflects the opportunity cost of capital.
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118. In the next columns, we estimate the change in ln land price as one moves from the underground to the elevated section of the rail corridor, restricting the identification to observations that are closer to the tunnel entrance using a similar approach as in e.g. Ahlfeldt, Maennig, et al. (2016) and Ahlfeldt and Holman (2017). In columns (3-4), we assign weights TW to observations that decline in distance from the tunnel entrance TD as determined by a Gaussian kernel function: 𝑇𝑊𝑖 = 1 𝜆𝑇√2𝜋 exp �− 1 2 �
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156. Noise spillover effect is a dummy variable taking the value of one for parcels within the corridor and within the first 250 m from the entrance along the underground section. Controls include distance from the CBD, distance from Kurfürstendamm (sub-centre), distance from canal, river or lake, distance from main street, distance from 1904 station, 1900 tram density, and change in tram density from 1900 to 1904. IV models estimated using 2SLS. Robust standard errors in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01.
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158. One interpretation is that this area close to Line A came out as a loser from the long-run cycle of sub-urbanization and gentrification that has been typical for many cities during the 20th century (McMillen, 1996). An alternative explanation is that the area has not yet recovered from the potentially detrimental effects of being close to the former Berlin Wall during the division period. In any case, it seems likely that such a remarkable decrease in the relative price of land is associated with a decrease in the relative income of the local population.
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176. Tab A11. Noise effects: Historical boundary discontinuity models (1) (2) (3) (4) (5) (6) Ln land price 1904 - ln land price 1900 Noise (10 decibel) -0.012*** (0.003) -0.052*** (0.014) -0.041*** (0.012) -0.062*** (0.015) -0.052*** (0.013) -0.049*** (0.013) Noise spillover effect - - Yes - Yes Yes Corridor effect - Yes Yes Yes Yes Yes Controls - - - Yes Yes Yes Lagged ln land prices - - - - - Yes Noise IV - Yes Yes Yes Yes Yes N 7,869 7,869 7,869 7,869 7,869 7,869 r2 .0019 - - - - -Notes: Corridor effect is a dummy variable taking the value of one for parcels within a tunnel distance of 500 m (either side of the entrance) and track distance of <= 50 m, and zero otherwise. Noise instrument is a dummy variable taking a value of one for parcels along the elevated section of the corridor and zero otherwise.
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177. Tab A24. Mode choice analysis (1) (2) (3) (4) (5) (6) Metro rail for part of the trip (0,1) Metro rail for part of the trip (0,1) Car for part of the trip (0,1) Car for part of the trip (0,1) Other modes (no car and no metro rail) (0,1) Other modes (no car and no metro rail) (0,1) Net income (€/month) -0.093*** (0.017) -0.129*** (0.019) 0.168*** (0.015) 0.170*** (0.016) -0.080*** (0.015) -0.071*** (0.017) Distance travelled (km) 0.118*** (0.004) 0.029*** (0.003) -0.178*** (0.006) Mode elasticity -.199 -.276 .31 .312 -.151 -.133 Origin effects - Yes - Yes - Yes Destination effects - Yes - Yes - Yes N 8,043 8,043 8,043 8,043 8,043 8,043 Notes: Unit of analysis is individual response in survey. Data from a 2008 representative travel survey Ahrens et al.
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178. Tanaka, S. & Zabel, J., 2018. Valuing nuclear energy risk: Evidence from the impact of the Fukushima crisis on U.S. house prices. Journal of Environmental Economics and Management, 88, pp.411–426. Available at: https://www.sciencedirect.com/science/article/abs/pii/S0095069617301626 [Accessed December 30, 2018].

179. The estimated OLS rail noise effects are even less conclusive. Not controlling for station distance effects, parcels which later become exposed to rail noise experience a relative decline in prices up until 1896, when, shortly after the concession was granted, the trend reverses. Controlling for station distance effects, the land price trends do not seem to depend on the degree to which parcels become exposed to rail noise. This pattern is not in line with rail noise being a disamenity. If anything, the unconditional OLS estimates suggest that rail noise is an amenity.
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180. The estimated station distance effect on land price levels (𝑆𝑖 × (𝑡 > 1902)𝑡) about halves in magnitude compared to the benchmark specification (column 6 of Table 1), but remains significant.
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181. The implicit assumption underlying the estimator is that if the weighting removes non-parallel trends successfully during the pre-treatment period (which can be tested), it will likely mitigate a potential non-parallel trends problem during the post-treatment periods (which cannot be tested) . For a more formal introduction and evaluation of the estimator in the context of a Monte Carlo study, we refer to a companion paper (Ahlfeldt, 2018). For better accessibility, there is some overlap between the material presented in this appendix and in the companion paper.
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182. The networks and modes illustrated are those which underlie the construction of the transport accessibility measures discussed in section 7.2 of this appendix. The figures show how the commuter rail network, despite significant technological upgrades (e.g. electrification from 1924 onwards) has remained roughly constant in terms of its coverage. In contrast, the subway network has since the opening of Line A developed into one of the densest networks in Europe. In line with the general settlement pattern, there was a dense network of complementary transport modes such as various tram systems and omnibuses within the central city around 1900, but the coverage was less complete in the suburbs. In contrast, the contemporary bus and tram (almost exclusively in the area of former East Berlin) networks cover a much broader area, reflecting the typical 20th century process of urban decentralization.
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183. The noise effect per grid cell g is 𝑃𝑔,1900�1 − exp�𝛼𝑁 � × 𝑁𝑔1904��, where Pg and Ng indicates the average land price and rail noise within a grid cell. The background map shows the situation in 2006, which corresponds to the situation in 1900 in most, but not all areas. Own illustration using the Urban Environmental Information System of the Berlin Senate Department (Senatsverwaltung für Stadtentwicklung Berlin, 2006). Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 53 10 Land price appreciation vs. interest rates In this section, we compare long-run land price growth rates and central bank interest rates to support the back-of-the-envelope calculations presented in Section 5.2 of the main paper. To our knowledge, no price index tracking real estate prices over the 19th and 20th century exists for Berlin.
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184. The real property tax rate that we estimate for Berlin is low by international standards. According to a Property Tax Comparison Study by the Minnesota Center for Fiscal Excellence (2014), the average property tax in US urban areas was 1.5%. Across urban areas, tax rates vary from 0.61% (Columnia, SC) to 4.1% (Bridgeport, CT).
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185. The results in Table A24 also confirm the strong intuition that the negative correlation between income and the use of public transport is driven by the availability of an attractive, but somewhat pricy alternative, the automobile. Before World War II, cars played a subordinate role as a means of transportation in Berlin. In relative terms, metro rail, therefore, was more attractive to higherincome groups as it was by far the fastest available mode of urban transportation (Leyden, 1933).
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186. Therefore, following Abadie, Athey, Imbens, and Wooldridge (2017), we keep the parcelclustered model as our baseline.
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187. Therefore, we combine our data with a data set on block-level land values in Berlin compiled by Ahlfeldt, Redding, et al. (2015). Consistently using the one-kilometer buffer around Line A as a study area, we regress the log of nominal land prices against block fixed effects and a year trend to obtain an estimate of the average yearly price appreciation during several historical periods. We note that in the results reported in Table A27 we exclude the 1914-1928 period because of the hyperinflation in the aftermath of WWI which complicates the comparison of nominal prices. For the later currency reforms (reichsmark to Deutsche Mark, 1948 and Deutsche Mark to euro, 1998) we apply the official conversion factors (10:1 and 1.95583:1).
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188. To approximate the real property tax rate in Table A28, we first compute the ratio of the Einheitswert over the market value as the inverse of a factor that captures the price inflation over fifty years since 1961. We get to this factor using the weighted (by year) average of the yearly land price growth rates from 1966 to 1986 and 1986 to 2006 reported in the Table A27 (columns 5 and 6). This appreciation rate implies that the Einheitswert after 50 years, on average, corresponds to 10.55% of the market value. For the tax rate, we consider values of 0.27%, which applies to single-family houses, and a rate of 0.35% which applies to larger structures. For the tax factor, we consider values of 333% (Hesse, the lowest in Germany), 410% (the German average) and 810% (Berlin, the highest in Germany), reported by the Federal Statistical office (Statistisches Bundesamt Fachserie 14 Reihe 10.1 – 2010).
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189. To assess the loss of effective accessibility in either counterfactual, we compute a measure of accessibility for each station s, in every period t, and scenario z (actual vs. counterfactual). Following Ahlfeldt, Redding, et al. (2015), we aggregate the population (POP) at all potential destinations j that can be accessed from a station weighted by the bilateral transport cost csjz to create a measure of effective accessibility: 𝐴𝑠𝑠𝑠 = � 𝑃𝑃𝑃𝑗𝑗𝑒−𝜏𝑐𝑠𝑠𝑠𝑠 𝑗 ,
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190. To infer the effect of the rail line, a judgement has to be made on a baseline period that provides a counterfactual trend. Because the relative trends are flat, it may be tempting to choose the 1890 to 1896 trend as a baseline, implying a price effect of a one-kilometer change in station distance of about 0.2 log points over the subsequent 20 years. However, given that the concession for the line was granted in 1895, it is possible that the change in trend between 1881-1890 and 1890-1896 is attributable to the rail line, in which case the rail effect would be considerably larger. Another, not particularly conclusive feature of the estimated OLS station effects is the insensitivity of the point estimates to controlling for rail noise effects.
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191. To obtain such an estimate, we make use of data compiled by Bousset (1935), who reports per kilometer construction costs for 31 segments of the Berlin underground network opened until 1930. In the table below, we present results of regressions of the natural log of per-kilometer construction costs against a dummy indicating underground sections. In column (1), we control for the opening year using a linear trend. In column (2), we replace this trend by five-year period effects. In column (3), we additionally control for the track width. The results are reasonably consistent across specifications. According to our preferred estimate in column (3), an underground section in the early 20th century in Berlin was about three times as expensive as an elevated section.
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192. To tailor to the needs of wealthier income groups, the historical trains operated on Line A featured special coaches that offered higher comfort at higher rates (Schmiedeke, 1997). More generally, some trains operated on several lines of the emerging metro rail network were casually referred to as banker trains (“Bankierzüge”) due to their popularity among wealthy commuters 5 See for details, http://daten.clearingstelle-verkehr.de/224/1/Staedtepegel_SrV2008.pdf.
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193. Touro College Berlin. wendland@urbancontext.org Ahlfeldt/Nitsch/Wendland: Appendix to Ease vs. noise 2 2016) or building externalities related to design and maintenance (Ahlfeldt and Holman, 2017; Rossi-Hansberg et al., 2010) from spatial variation in property prices. This approach is derived from the spatial equilibrium assumption in bid-rent theory, one of the workhorse tools in urban economics (Alonso, 1964; Mills, 1967; Muth, 1969). Essentially, it is argued that the value of (urban) land must offset all utility and productivity enhancing or depreciating factors, including noise and accessibility, if households are mobile and markets are competitive. The revealed preference approach is a popular tool in social cost-benefit analyses, which are, in many settings, the preferred method to evaluate welfare effects of public policies (Osborne and Turner, 2010).
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194. Tyrväinen, Liisa, & Miettinen, Antti. (2000). Property Prices and Urban Forest Amenities. Journal of Environmental Economics and Management, 39(2), 205-223.

195. U.S. Department of Labor. (2006). 100 Years of U.S. Consumer Spending. Washington, D.C.: U.S. Department of Labor,.
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196. Under the assumptions made, it is then straightforward to approximate a real property tax rate for the different scenarios by multiplying the ratio of the Einheitswert over market value by the tax rate and the tax factor. The typical tax rate in central Berlin is 0.35% (non-single-family houses) and the tax factor is 810%, thus the real property tax is 0.3%. In other parts of Germany, the real property tax rate is likely to be lower because the tax factors are much lower. Moreover, property price appreciation was, on average, higher at 7%, implying a ratio of Einheitswert over market value of just about 5% (Bundesministerium der Finanzen, 2011).
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197. Voith, Richard. (1993). Changing Capitalization of CBD-Oriented Transportation Systems: Evidence from Philadelphia, 1970-1988. Journal of Urban Economics, 33(3), 361.

198. Walls, M., Gerarden, T., Palmer, K. & Bak, X.F., 2017. Is energy efficiency capitalized into home prices? Evidence from three U.S. cities. Journal of Environmental Economics and Management, 82, pp.104–124. Available at: https://www.sciencedirect.com/science/article/abs/pii/S0095069616304508 [Accessed December 30, 2018].

199. Wardman, M., Bristow, A. & Arsenio, E., 2005. Applying Stated Preference Methods to the Valuation of Noise: Some Lessons to Date. Conference paper: The 2005 Congress and Exposition on Noise Control Engineering.
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200. We similarly evaluate the sensitivity of the weighted DD estimates to using alternative objective functions in the weight-generating algorithm. As described in the main paper, we search over a parameter space defined by 𝑞1 = 0, 0.01, 0.02, … ,1, 𝑞2 = 0, 0.01, 0.02, … ,1, 𝑞3 = 0, 0.01, 0.02, … ,1 to identiy the parameter vector 𝑄(𝑞1, … , 𝑞𝑚) in equation (4) in the main paper. To this end, we run r regressions of the form ∆ln(𝑃𝑖,1890) = 𝑐𝑟 0 + 𝑐𝑟 𝑆 𝑆 ̃𝑖 + 𝑐𝑟 𝑁 𝑁
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201. Wrigley, M., & Wyatt, P. (2001). Transport Policy and Property Values. Paper presented at the Royal Institution of Chartered Surveyors (RICS) ‘Cutting Edge’ Conference, University of the West of England.

202. Yeates, M.H., 1965. Some Factors Affecting the Spatial Distribution of Chicago Land Values, 19101960. Economic Geography, 41(1), pp.57–70. Available at: http://www.jstor.org/stable/141856.
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1. Interdependence and multilateral economic sanctions. (2024). Meng, Xue ; Jin, Yuying.
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2. Does foreign direct investment benefit local firms? Evidence from a natural experiment study. (2024). Tran, Tuyen ; Nguyen, Cuong ; van Vu, Huong.
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3. Does the Extractive Industries Transparency Initiative (EITI) help reduce corruption in Latin America? Evidence from Colombia, Guatemala, Honduras, Peru, and Trinidad and Tobago. (2020). Lopez, I M.
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4. Hybrid threats as an exogenous economic shock. (2019). Nozharov, Shteryo.
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5. Can Reform Waves Turn the Tide? Some Case Studies Using the Synthetic Control Method. (2016). Loungani, Prakash ; Duval, Romain ; Adhikari, Bibek ; Hu, Bingjie.
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6. Terrorism and Employment: Evidence from Successful and Failed Terror Attacks. (2015). Brodeur, Abel.
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7. Financial incentives for kidney donation: A comparative case study using synthetic controls. (2015). Bilgel, Firat ; Galle, Brian.
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8. Natural disasters, growth and institutions: a tale of two earthquakes. (2014). Mocetti, Sauro ; Barone, Guglielmo.
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9. What Lessons Can Asia Draw from Capital Controls in Brazil during 2008–2012?. (2013). Zheng, Huanhuan ; Noy, Ilan ; Jinjarak, Yothin.
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10. The effect of organized crime on public funds. (2013). Narciso, Gaia ; Barone, Guglielmo.
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11. Counterfactual Analysis in Macroeconometrics: An Empirical Investigation into the Effects of Quantitative Easing. (2012). Smith, Ronald ; Pesaran, Mohammad.
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12. Counterfactual Analysis in Macroeconometrics: An Empirical Investigation into the Effects of Quantitative Easing. (2012). Smith, Ronald ; Pesaran, Mohammad.
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13. On the Heterogeneity of Terror. (2012). Schulze, Günther ; Liebert, Helge ; Kis-Katos, Krisztina.
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14. On the Heterogeneity of Terror. (2012). Schulze, Günther ; Liebert, Helge ; Kis-Katos, Krisztina.
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15. Counterfactual Analysis in Macroeconometrics: An Empirical Investigation into the Effects of Quantitative Easing. (2012). Smith, Ronald ; Pesaran, Mohammad.
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16. The Legacy of Historical Conflict Evidence from Africa. (2012). Besley, Timothy ; Reynal-Querol, Marta.
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17. The economic costs of organized crime: evidence from southern Italy. (2012). pinotti, paolo.
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18. Impact of terrorism on investment decisions of farmers: evidence from the Punjab insurgency. (2011). Singh, Prakarsh.
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19. Terrorism Shocks and Stock Market Reaction Patterns. (2011). Kallandranis, Christos ; Drakos, Konstantinos.
    In: EUSECON Policy Briefing.
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20. Household Economic Decisions under the Shadow of Terrorism. (2009). Georgarakos, Dimitris ; Christelis, Dimitris.
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21. The risk of catastrophic terrorism: an extreme value approach. (2009). Murshid, Antu ; Mohtadi, Hamid.
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22. Terrorist Incidents in India, 1998–2004: A Quantitative Analysis of Fatality Rates. (2009). Borooah, Vani ; Borooah, Vani / K, .
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23. The Costs of Organized Violence: A Review of the Evidence. (2009). Skaperdas, Stergios.
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24. Deterrence, Preemption and Panic: A Common-Enemy Problem of Terrorism. (2008). Roy Chowdhury, Prabal ; Das, Satya.
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25. Inter-Group Conflict and Intra-Group Punishment in an Experimental Contest Game. (2008). Orzen, Henrik ; Brandts, Jordi ; Abbink, Klaus ; Herrmann, Benedikt.
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26. Political Autonomy and Independence: Theory and Experimental Evidence. (2007). Brandts, Jordi ; Abbink, Klaus.
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27. The aftermath of Civil War. (2007). Loayza, Norman ; Chen, Siyan ; Reynal-Querol, Marta.
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28. Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of Californias Tobacco Control Program. (2007). Hainmueller, Jens ; Abadie, Alberto ; Diamond, Alexis.
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29. Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of Californias Tobacco Control Program. (2007). Hainmueller, Jens ; Abadie, Alberto ; Diamond, Alexis.
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30. Islamistic Terror, the War on Iraq and the Job Prospects of Arab Men in Britain: Does a Country’s Direct Involvement Matter? This paper examines whether the labor market prospects of Arab men in Eng. (2007). Braakmann, Nils ; Groth, Markus.
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31. Agricultural Outputs and Conflict Displacement: Evidence from a Policy Intervention in Rwanda. (2007). Kondylis, Florence.
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32. International Trade, Security and Transnational Terrorism: Theory and Empirics. (2007). Verdier, Thierry ; Mirza, Daniel.
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33. Political Autonomy and Independence: Theory and Experimental Evidence. (2007). Brandts, Jordi ; Abbink, Klaus.
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34. International trade, security, and transnational terrorism : theory and empirics. (2006). Verdier, Thierry ; Mirza, Daniel.
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35. Is Terrorism Eroding Agglomeration Economies in Central Business Districts? Lessons from the Office Real Estate Market in Downtown Chicago. (2006). Dermisi, Sofia ; Abadie, Alberto.
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36. The Long Run Impact of Bombing Vietnam. (2006). Roland, Gérard ; Miguel, Edward.
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37. International Terrorism, International Trade, and Borders. (2006). Kang, Heejoon ; Fratianni, Michele.
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38. Mad Cows, Terrorism and Junk Food: Should Public Policy Reflect Subjective or Objective Risks?. (2006). Johansson-Stenman, Olof.
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39. Captive markets: the impact of kidnappings on corporate investment in Colombia. (2006). Suarez, Gustavo ; Pshisva, Rony .
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40. Poverty, Political Freedom, and the Roots of Terrorism. (2006). Abadie, Alberto.
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41. Terrorism and the World Economy. (2005). .
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42. The Impact of Terrorism Across Industries: An Empirical Study. (2005). Klor, Esteban ; Berrebi, Claude.
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43. The Cycle of Violence? An Empirical Analysis of Fatalities in the Palestinian-Israeli Conflict. (2005). Paserman, M. Daniele ; Jaeger, David.
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44. How Do Patent Laws Influence Innovation? Evidence from Nineteenth-Century Worlds Fairs. (2005). Moser, Petra.
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45. Convergence across Spanish Provinces:Cross-section and Pairwise Evidence. (2004). Webber, Don ; Minondo, Asier ; White, Paul ; Allen, David O.
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46. Poverty, Political Freedom, and the Roots of Terrorism. (2004). Abadie, Alberto.
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47. Poverty, Political Freedom, and the Roots of Terrorism. (2004). Abadie, Alberto.
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48. Valuing Public Goods: The Life Satisfaction Approach. (2004). Stutzer, Alois ; Luechinger, Simon ; Frey, Bruno.
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49. Valuing Public Goods: The Life Satisfaction Approach. (). Stutzer, Alois ; Luechinger, Simon ; Frey, Bruno.
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50. Measuring Terrorism. (). Luechinger, Simon ; Frey, Bruno.
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