Spatial Estimation of the Impact of Airport Noise on Residential Housing Prices

The paper applies spatial econometric techniques to measure the impact of airport noise on the price of single-family homes in the Zurich Airport area. We exploit a large database of geo-referenced noise measurements to investigate the reaction of prices to different noise metrics. The particular institutional setting of Zurich Airport, with changing patterns of runways configurations allows to distinguish the impact of noise at different times of the day. The use of neighborhood fixedeffects is compared to the results given by a costlier modelling strategy involving a rich set of location descriptors. The paper documents the impact of airport noise on housing prices. In the base model specification the Noise Discount Index is 0.97% with typical discounts in the range of -2% to -8%. Accounting for the spatiality of the data has little effect on the results

Ist eine höhere bauliche Dichte wünschenswert? Evidenz aus den Preisen von Einfamilienhäusern im Kanton Zürich

hedonic regression, housing prices

Bloom Filters and Compact Hash Codes for Efficient and Distributed Image Retrieval

This paper presents a novel method for efficient image retrieval, based on a simple and effective hashing of CNN features and the use of an indexing structure based on Bloom filters. These filters are used as gatekeepers for the database of image features, allowing to avoid to perform a query if the query features are not stored in the database and speeding up the query process, without affecting retrieval performance. Thanks to the limited memory requirements the system is suitable for mobile applications and distributed databases, associating each filter to a distributed portion of the database. Experimental validation has been performed on three standard image retrieval datasets, outperforming state-of-the-art hashing methods in terms of precision, while the proposed indexing method obtains a $2\times$ speedup

Engagement in Nachhaltigkeit macht sich bezahlt: Minergie als Investition in die Zukunft

Der Energieeffizienz wird am Schweizer Immobilienmarkt bis anhin zu wenig Beachtung geschenkt. Dabei ist der Markt bereit, einen Aufpreis für Minergie zu bezahlen. Erforderlich sind aber Bewertungs-Instrumente, die Nachhaltigkeits- Aspekte umfassend einbeziehen

Property Derivatives and Index-Linked Mortgages

Economists have forcefully argued for the introduction and use of property derivatives as a hedge against house price risk (e.g. Shiller and Weiss, 1999). The rationale for these financial instruments seems clear, as many households are heavily invested in housing and standard financial instruments offer a poor hedge. In practice, however, most of the property derivatives available have been targeted to meet the needs of institutional investors, not those of owner-occupiers. Building on the recent launch of the first Swiss property derivative, we here propose index-linked mortgages tailored to retail consumers. The payments of these mortgages depend on the corresponding housing market performance. We further price the instruments, discuss the stabilization of the homeowner's net wealth, and quantify the expected decrease in the mortgage default risk achieved by this immunization effect

Tone-in-noise detection deficits in elderly patients with clinically normal hearing

One of the most common complaints among the elderly is the inability to understand speech in noisy environments. In many cases, these deficits are due to age-related hearing loss; however, some of the elderly that have difficulty hearing in noise have clinically normal pure-tone thresholds. While speech in noise testing is informative, it fails to identify specific frequencies responsible for the speech processing deficit. Auditory neuropathy patients and animal models of hidden hearing loss suggest that tone-in-noise thresholds may provide frequency specific information for those patients who express difficulty, but have normal thresholds in quiet. Therefore, we aimed to determine if tone-in-noise thresholds could be a useful measure in detecting age-related hearing deficits, despite having normal audiometric thresholds

Assessing airport noise, demand for quietness and land-structure substitution:three applications of the hedonic model in Switzerland

This dissertation collects three essays on the hedonic modelling of housing prices, location attributes and environmental amenities – or lack thereof. The first essay applies spatial econometric techniques to measure the impact of airport noise on the price of single-family homes in the Zurich Airport area. We exploit a large database of geo-referenced noise measurements to investigate the reaction of house prices to different noise metrics. The particular institutional setting of Zurich Airport, with a changing pattern of runway configurations allows to distinguish the impact of noise at different times of the day. The use of neighborhood fixed-effects is compared to the results given by a costlier modelling strategy involving a rich set of location descriptors. We document the impact of airport noise on housing prices. In the base model specification, the Noise Discount Index, i.e. the percentage depreciation per dB of aircraft noise, is 0:97%. Typical discounts are in the range of –2% to –8%. The results are similar to comparable Swiss and international studies on the impact of aircraft noise on residential property prices. From a methodological point of view, we show that accounting for the spatiality of the data has little effect on the results. In the second essay we estimate the willingness to pay for housing attributes of single-family home owners located in the greater Zurich area. A revealed-preferences approach is used, in which a structural hedonic model is identified and estimated. Our approach explicitly accounts for the heterogeneity of preferences of the owner-occupiers. Again, we use the GIS to match the data describing the housing characteristics and the attributes of the location to the socioeconomic traits of the owners. We perform a nonparametric estimation of the hedonic model that allows us to recover the preference parameters. We measure the impact of income differences on the willingness to pay for five major characteristics, i.e. travel time to the city center, size and age of the housing unit, lot size and proximity to a major environmental amenity, the Lake of Zurich. We show that the willingness to pay for the environmental amenity and for centrality is highly income elastic, while the demand for the lot size and for the house surface is not. We put the model in the context of the new urban economic literature which studies the importance of amenities for the location decision of households in cities. In the last part of the dissertation, we touch on another typical urban economics topic – the elasticity of substitution between capital and land. This concept is key in understanding some important phenomena like urban sprawl or urban density. Combining two new rich data sets on disaggregated land and house transactions, we propose one of the first estimates of this elasticity for a non-U.S. metropolitan region. For the region of Zurich we find an elasticity of substitution of 0:6 and an own-price elasticity of the demand for land of –0.5. These relatively low estimates imply that a policy aiming at restricting the supply of open spaces and limiting the availability of unimproved land may have a large impact on house prices. JEL-Classification: Q53, Q51, R31, L93, C2

Analisi della vulnerabilità di un aggregato edilizio nel centro storico di Torricella Sicura (TE) e confronto con il suo danneggiamento post sisma 2016.

La presente tesi prende in esame un aggregato edilizio storico colpito dal sisma del 2016, sito in Torricella Sicura (Te) . Innanzitutto è stata realizzata un’analisi della vulnerabilità sismica dell'aggregato, tramite un metodo che utilizza indici matematici, in grado di rappresentare le caratteristiche degli elementi strutturali degli edifici e di sintetizzare il livello di vulnerabilità dell'aggregato con un unico coefficiente numerico. Questo approccio necessita di una validazione attraverso l'applicazione a un caso di studio realmente danneggiato da un sisma, in modo da verificare se esista o meno una corrispondenza tra la propensione al danno misurata attraverso la vulnerabilità e il danno effettivamente registrato. Per questo motivo, si è proceduto anche alla quantificazione del danno subito dall’aggregato tramite un effettivo valore numerico e, successivamente, è stato operato un confronto tra i valori emersi dalle precedenti analisi. Il confronto è servito ad accertare l’attendibilità del modello di calcolo utilizzato, al fine di verificare l’esistenza o meno di uno scostamento tra quanto determinato con l’analisi della vulnerabilità e l’entità dei danni affettivamente riscontrati. Da ultimo, dopo aver preso in esame i dati emersi, è stata formulata una nuova proposta metodologica di calcolo, che rimodulando alcuni parametri, ha cercato di integrare e migliorare questo tipo di analisi, permettendo di raggiungere una più efficace corrispondenza tra la stima della vulnerabilità e la stima del danno

S-HR-VQVAE: Sequential Hierarchical Residual Learning Vector Quantized Variational Autoencoder for Video Prediction

We address the video prediction task by putting forth a novel model that combines (i) our recently proposed hierarchical residual vector quantized variational autoencoder (HR-VQVAE), and (ii) a novel spatiotemporal PixelCNN (ST-PixelCNN). We refer to this approach as a sequential hierarchical residual learning vector quantized variational autoencoder (S-HR-VQVAE). By leveraging the intrinsic capabilities of HR-VQVAE at modeling still images with a parsimonious representation, combined with the ST-PixelCNN's ability at handling spatiotemporal information, S-HR-VQVAE can better deal with chief challenges in video prediction. These include learning spatiotemporal information, handling high dimensional data, combating blurry prediction, and implicit modeling of physical characteristics. Extensive experimental results on the KTH Human Action and Moving-MNIST tasks demonstrate that our model compares favorably against top video prediction techniques both in quantitative and qualitative evaluations despite a much smaller model size. Finally, we boost S-HR-VQVAE by proposing a novel training method to jointly estimate the HR-VQVAE and ST-PixelCNN parameters.Comment: 14 pages, 7 figures, 3 tables. Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence on 2023-07-1