Temporal decomposition and semantic enrichment of mobility flows

Mobility data has increasingly grown in volume over the past decade as loc- alisation technologies for capturing mobility ows have become ubiquitous. Novel analytical approaches for understanding and structuring mobility data are now required to support the back end of a new generation of space-time GIS systems. This data has become increasingly important as GIS is now an essen- tial decision support platform in many domains that use mobility data, such as eet management, accessibility analysis and urban transportation planning. This thesis applies the machine learning method of probabilistic topic mod- elling to decompose and semantically enrich mobility ow data. This process annotates mobility ows with semantic meaning by fusing them with geograph- ically referenced social media data. This thesis also explores the relationship between causality and correlation, as well as the predictability of semantic decompositions obtained during a case study using a real mobility dataset

Quarterly Economic Commentary Winter 2019

No Abstract

Habitualisation: localisation without location data

This paper looks at identifying the locations of users from the Nokia MDC dataset throughout the day without taking into consideration location based data. By looking at a users habits and idiosyncrasies we determined the likelihood of a users location within known stay regions which we call habitats. The features used to determine location were extracted from a users interaction with the smart phone. None of the features contained a users locations or a users proximity to objects with known locations. Using a set of structured output support vector learning techniques we found that a users location with respect to the areas of typical activities is well predictable solely from daily routines and a smart phone usage habits

Rental equivalence, owner-occupied housing and inflation measurement: Micro-level evidence from Ireland. ESRI Working Paper 685 November 2020.

In this paper, we use unique supervisory property-level rental data to estimate a rental equivalence (RE) measure for owner-occupied housing (OOH) for the Irish housing market. Our data from the official, domestic rental regulator allow us to simultaneously address three significant issues which have arisen in the empirical application of rental equivalent measures. First, we are able to consider the differences in using data on both new and existing rent levels in the analysis, we can also control for other utility costs and finally we are able to estimate a RE measure in the absence of rent controls. To better approximate the OOH structure of the Irish residential market, we also avail of regional data to estimate 32 separate hedonic rent models and use the results to reweight the RE index. We find that our subsequent estimate of RE results in a reduction in the Irish headline rate of consumer price inflation by 0.4 percentage points. Furthermore, we show there are considerable differences in the inflation rate if new relative to existing rents are used in the rental equivalence measures with measures based purely on existing rents biasing downwards both the rental equivalence measure and the overall consumer price index. This suggests that considerable care is required for policymakers in using rental equivalence methods in the presence of data gaps

The RTB Rent Index, Quarter 4 2020. ESRI Indices Report March 2021.

The Rent Index is produced by the Residential Tenancies Board (RTB) and the Economic and Social Research Institute (ESRI). It provides rental indicators (such as the Rent Index) generated to track price developments in the Irish market. Rents grew nationally by 2.7% in Q4 2020 in comparison to 6.4% in Q4 2019. The national standardised average rent stood at €1,256 in Q4 2020, equal to its level in Q3 2020

The RTB Rent Index, Quarter 3 2020. ESRI Indices Report December 2020.

This report is produced by the Residential Tenancies Board (RTB) and the Economic and Social Research Institute (ESRI) and provides rental indicators (the Rent Index) generated to track price developments in the Irish market. The analysis in this report presents rental indices on a quarterly basis covering the period between Q3 2007 and Q3 2020. It must be noted that the period since the onset of the pandemic has seen the introduction and easing of restrictions around rental price growth in line with the public health measures. This is likely to have had an effect on the trend between the second and third quarters

The effect of the COVID-19 pandemic on consumption and indirect tax in Ireland. ESRI Budget Perspectives 202103 May 2020.

Using microdata from the Central Statistics Office (CSO) Household Budget Survey (HBS), we assess the effect of the COVID-19 pandemic on consumption and its implications for indirect tax receipts in 2020. We show that over one-third of household expenditure is on items that are currently restricted due to public health measures such as transport, selected retail expenditure and entertainment items. We parameterise three scenarios which attempt to take into account: 1) a return to a ‘new normal’ with ongoing physical and social distancing; 2) a ‘second wave’ lockdown; and 3) rapid vaccine development that allows a return to normal economic and social life by the end of 2020. Under these scenarios, household consumption this year is estimated to be between 12 and 20 per cent lower than what it would have been in the absence of the pandemic. Indirect tax paid by households is estimated to be between 19 and 32 per cent lower than it otherwise would have been

Quarterly Economic Commentary, Spring 2021. ESRI Forecasting Series March 2021.

In light of the current level-5 restrictions, we have revised down our 2021 forecasts from the 2020 Winter Commentary. We now assume that the lockdown measures that commenced on the 30 December 2020 will last until at least the 5 April 2021 and that there will be a gradual easing of restrictions thereafter. We also assume that the vaccination programme will facilitate the broad relaxation of public health restrictions in the second half of 2021 and that there will not be another full Level 5 lockdown towards the end of the year. Under these assumptions, we expect Irish GDP to increase by 4.4 per cent in the present year. We also outline our first set of forecasts for 2022 with output expected to increase by 5.2 per cent

Stratification structure of urban habitats

This paper explores the community structure of a network of significant locations in cities as observed from location-based social network data. We present the findings of this analysis at multiple spatial scales. While there is previously observed distinct spatial structure at inter-city level, in a form of catchment areas and functional regions, the exploration of in-city scales provides novel insights. We present the evidence that particular areas in cities stratify into distinct “habitats” of frequently visited locations, featuring both spatially overlapping and disjoint regions. We then quantify this stratification with normalized mutual information which shows different stratification levels for different cities. Our findings have important implications for advancing models of human mobility, studying social exclusion and segregation processes in cities, and are also of interest for geomarketing analysts developing fidelity schemes and promotional programmes

Quarterly Economic Commentary, Summer 2020. ESRI Forecasting Series May 2020.

Given the high degree of uncertainty about the spread of COVID-19, our Summer Quarterly Economic Commentary assesses the future prospects for the Irish economy under three different scenarios: Baseline (“New normal with ongoing physical distancing”, Severe (“Second wave requiring strict lockdown”) and Benign (“Successful disease suppression”)