Behavior of major statistical estimators in sampling accounting populations : an empirical study; Auditing research monograph, 2

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A stochastic model of the internal control system / BEBR No. 106

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Assessing the Impact of Road Traffic Externalities on Residential Price Values: a Case Study in Madrid, Spain

[EN] This paper describes a study of the relationship between undesired road traffic externalities and residential price values in the Spanish city of Madrid. A large database was gathered, including the price and characteristics of 21,634 flats and road traffic intensity at 3904 different points across the city. The results obtained by a hedonic model suggest that both distance from the traffic measurement point and average daily traffic are significantly related to the price of residential properties, even after controlling for structural and neighbourhood variables. Distance to traffic areas has a positive impact on dwelling prices, whilst these are negatively related to traffic intensity.Guijarro, F. (2019). Assessing the Impact of Road Traffic Externalities on Residential Price Values: a Case Study in Madrid, Spain. International Journal of Environmental research and Public Health. 16(24):1-13. https://doi.org/10.3390/ijerph16245149S1131624Kim, M., Chang, S. I., Seong, J. C., Holt, J. B., Park, T. H., Ko, J. H., & Croft, J. B. (2012). Road Traffic Noise. American Journal of Preventive Medicine, 43(4), 353-360. doi:10.1016/j.amepre.2012.06.014Sorensen, M., Hvidberg, M., Andersen, Z. J., Nordsborg, R. B., Lillelund, K. G., Jakobsen, J., … Raaschou-Nielsen, O. (2011). Road traffic noise and stroke: a prospective cohort study. European Heart Journal, 32(6), 737-744. doi:10.1093/eurheartj/ehq466Munzel, T., Gori, T., Babisch, W., & Basner, M. (2014). Cardiovascular effects of environmental noise exposure. European Heart Journal, 35(13), 829-836. doi:10.1093/eurheartj/ehu030Bodin, T., Albin, M., Ardö, J., Stroh, E., Östergren, P.-O., & Björk, J. (2009). Road traffic noise and hypertension: results from a cross-sectional public health survey in southern Sweden. Environmental Health, 8(1). doi:10.1186/1476-069x-8-38Lercher, P., Widmann, U., & Thudium, J. (2014). Hypotension and Environmental Noise: A Replication Study. International Journal of Environmental Research and Public Health, 11(9), 8661-8688. doi:10.3390/ijerph110908661Dzhambov, A. M., & Lercher, P. (2019). Road Traffic Noise Exposure and Depression/Anxiety: An Updated Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health, 16(21), 4134. doi:10.3390/ijerph16214134De Kluizenaar, Y., Janssen, S., Vos, H., Salomons, E., Zhou, H., & van den Berg, F. (2013). Road Traffic Noise and Annoyance: A Quantification of the Effect of Quiet Side Exposure at Dwellings. International Journal of Environmental Research and Public Health, 10(6), 2258-2270. doi:10.3390/ijerph10062258Urban, J., & Máca, V. (2013). Linking Traffic Noise, Noise Annoyance and Life Satisfaction: A Case Study. International Journal of Environmental Research and Public Health, 10(5), 1895-1915. doi:10.3390/ijerph10051895Shepherd, D., Welch, D., Dirks, K., & McBride, D. (2013). Do Quiet Areas Afford Greater Health-Related Quality of Life than Noisy Areas? International Journal of Environmental Research and Public Health, 10(4), 1284-1303. doi:10.3390/ijerph10041284Del Giudice, V., De Paola, P., Manganelli, B., & Forte, F. (2017). The Monetary Valuation of Environmental Externalities through the Analysis of Real Estate Prices. Sustainability, 9(2), 229. doi:10.3390/su9020229Wilhelmsson, M. (2000). The Impact of Traffic Noise on the Values of Single-family Houses. Journal of Environmental Planning and Management, 43(6), 799-815. doi:10.1080/09640560020001692Baranzini, A., & Ramirez, J. V. (2005). Paying for Quietness: The Impact of Noise on Geneva Rents. Urban Studies, 42(4), 633-646. doi:10.1080/00420980500060186Kim, K. S., Park, S. J., & Kweon, Y.-J. (2007). Highway traffic noise effects on land price in an urban area. Transportation Research Part D: Transport and Environment, 12(4), 275-280. doi:10.1016/j.trd.2007.03.002Blanco, J. C., & Flindell, I. (2011). Property prices in urban areas affected by road traffic noise. Applied Acoustics, 72(4), 133-141. doi:10.1016/j.apacoust.2010.11.004Łowicki, D., & Piotrowska, S. (2015). Monetary valuation of road noise. Residential property prices as an indicator of the acoustic climate quality. Ecological Indicators, 52, 472-479. doi:10.1016/j.ecolind.2015.01.002Szczepańska, A., Senetra, A., & Wasilewicz-Pszczółkowska, M. (2015). The effect of road traffic noise on the prices of residential property – A case study of the polish city of Olsztyn. Transportation Research Part D: Transport and Environment, 36, 167-177. doi:10.1016/j.trd.2015.02.011Levkovich, O., Rouwendal, J., & van Marwijk, R. (2015). The effects of highway development on housing prices. Transportation, 43(2), 379-405. doi:10.1007/s11116-015-9580-7Li, W., & Saphores, J.-D. (2012). Assessing Impacts of Freeway Truck Traffic on Residential Property Values. 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Biomass conversion and expansion factors are afected by thinning

Aim of the study: The objective of this paper is to investigate the use of Biomass Conversion and Expansion Factors (BCEFs) in maritime pine (Pinus pinaster Ait.) stands subjected to thinning. Area of the study: The study area refers to different ecosystems of maritime pine stands in Northern Portugal. Material and methods: The study is supported by time data series and cross sectional data collected in permanent plots established in the North of Portugal. An assessment of BCEF values for the aboveground compartments and for total was completed for each studied stand. Identification of key variables affecting the value of the BCEFs in time and with thinning was conducted using correlation analysis. Predictive models for estimation of the BCEFs values in time and after thinning were developed using nonlinear regression analysis. Research highlights: For periods of undisturbed growth, the results show an allometric relationship between the BCEFs, the dominant height and the mean diameter. Management practices such as thinning also influence the factors. Estimates of the ratio change before and after thinning depend on thinning severity and thinning type. The developed models allow estimating the biomass of the stands, for the aboveground compartments and for total, based on information of stand characteristics and of thinning descriptors. These estimates can be used to assess the forest dry wood stocks to be used for pulp, bioenergy or other purposes, as well as the biomass quantification to support the evaluation of the net primary productivityinfo:eu-repo/semantics/publishedVersio