1. Poster design: Zia Wadud Bangladesh University of Engineering and Technology www.buet.ac.bd Authors (+ affiliation if multiple institution) Email address@ce.buet.ac.bd BACKGROUND & RESEARCH QUESTIONS Noise Depreciation Index (NDI) = % change in property prices/change in noise exposure NDI = ∂ln(Price)/∂Noise NDI used to determine the noise costs around airports NDI determined by Hedonic Price methods, by observing the tradeoff between property prices and noise exposure in a sample of households with differing characteristics Different NDI estimates available for different countries/airports Is there any consistency among the NDI estimates? Can we explain the differences among the NDI estimates? Can we transfer the NDI values to other countries, where NDI’s are not available? Does income/wealth has any effect on sensitivity to noise, i.e. NDI (previous summary evidence contradictory)? HEADER Functional Specification: Linear vs. Semilog: Same data, different specification: Number of covariates and omitted variable bias, e.g. airport access control Spatial autocorrelation: does not affect much Data type: individual household/census tract or block; sample size etc. Regional differences: Etc HEADER Functional Specification: Linear vs. Semilog: Same data, different specification: Number of covariates and omitted variable bias, e.g. airport access control Spatial autocorrelation: does not affect much Data type: individual household/census tract or block; sample size etc. Regional differences: TABLE 2 Caption of table ACKNOWLEDGEMENTS Dr. Andreas Schäfer, Dr. Tom G Reynolds, and University of Cambridge CONCLUSIONS Functional Specification: Linear vs. Semilog: Same data, different specification: Number of covariates and omitted variable bias, e.g. airport access control Spatial autocorrelation: does not affect much Data type: individual household/census tract or block; sample size etc. Regional differences: NDI = 0.367 + 1.49×10 -6 ×Property Price [+ 0.184 if in Canada] (0.119) (4.1×10 -7 ) (0.184) NDI = 0.428 + 0.0367×Relative Property Price [+ 0.088 if in Canada] (0.139) (0.0177) (0.202) TITLE OF THE PROJECT: GOES HERE Department of Civil Engineering FIGURE 1 Title of Figure Explanatory factors Expected sign Model No abcd Modelabcd At sample mean property price or relative property price Airport accessibility corrected At property price USD 300,000 with airport access TABLE 2 Caption of table HEADER Functional Specification: Linear vs. Semilog: Same data, different specification: Number of covariates and omitted variable bias, e.g. airport access control Spatial autocorrelation: does not affect much Data type: individual household/census tract or block; sample size etc. Regional differences REFERENCES Dr. Andreas Schäfer ……………… Dr. Tom G Reynolds …………………… University of Cambridge ……………….. FIGURE 2 Title of Figure HEADER Functional Specification: Linear vs. Semilog: Same data, different specification: Number of covariates and omitted variable bias, e.g. airport access control Spatial autocorrelation: does not affect much Data type: individual household/census tract or block; sample size etc. Regional differences:

2. Poster design: Zia Wadud Bangladesh University of Engineering and Technology www.buet.ac.bd Using the template DO change the pictures in the bottom banner for pictures relevant to your project!! DO use Edit>Paste Special> Unformatted text when pasting into text boxes, to avoid changing the font or font size. DO use the on-screen guides to help you align columns (view>grid and guides), particularly if you need to rearrange items. DO print an A4 test copy (using scale to page). If any figures, text etc are difficult to read, they will be difficult to read on the final poster. DO ask someone else to check the poster before you pay for full size colour printing.