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Micro-Simulation Modelling of Domestic Tourism in Sweden. KIRUNA. Anders Lundgren Dep. Geography, Umeå University. SVERIGE. S ystem for V isualizing E conomic and R egional I nfluences G overning the E nvironment
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Micro-Simulation Modelling of Domestic Tourism in Sweden KIRUNA Anders Lundgren Dep. Geography, Umeå University
SVERIGE System for Visualizing Economic and Regional Influences Governing the Environment SVERIGE is a Microsimulation model based on microdata on the Swedish population Socioeconomic data for ALL individuals
Current Modules Migration
What is microsimulation? Micro = individual level Microsimulation model - Simulation model that describes the behaviour of individual micro units and permits analysis of the impacts of the environment Laboratory ”world” for testing policies SVERIGE is dynamic and spatial - What happens if we increase immigration?
Experiment 80 000 immigrants Base case – 60 000 immigrants
”National” Tourism module How many trips are done? What do they do? Where do people go? Exchange of tourists between LA- regions
Swedish Tourist Database Managed by Åre marknadsfakta 14 years 24 000 interviews every year Using 10 years
Number of cases Randomly collected Densely populated areas are well represented
Different categories of tourism Domestic travel with at least one night away from home done at leisure time
Limitations in data To few observations to perform regressions analyses IF you look at municipalities and each activity in TDB
Natural environment (Experience) • Fishing (Participate/be active in) • Other activity (Participate/be active in) • Private matters/look for job (Experience) • See the country (Experience) • Buy things • Attraction (Visit, watch, listen to) • Stimulation (Experience) • Education/studies (Participate/be active in) • Urban environment (Experience) • Parks (Visit, watch, listen to) • Hunting (Participate/be active in) • Golf (Participate/be active in) • Adventure and excitement (Experience) • School trip (Experience) Activity/purpose in TDB Meeting friends and relatives Visit second home Piece and quiet/relaxation (Experience) Pleasure and entertainment (Experience) Community with others (Experience) Skiing (Participate/be active in) Sun&swimming (Participate/be active in) Events (away 00-01) Outdoor life (Participate/be active in) Sports (Participate/be active in) Course & meeting as leisure assignment Cultural activity (Participate/be active in) Cultural environment (Experience) Rush and speed (Experience) Seclusion (Experience) Prophylaxis, health care (Participate/be active in)
A model for number of trips The two key factors that make tourism possible is access to money and leisure time
A model for choice of activities Age, gender, income and lifecycle are key factors that affect activity choice
Regression analysis Poisson regression for the number of trips – most people make 1 trip per month - 98% within 5 trips. Multinomial logit regression for the choice between 10 activities
Choice of destination Interaction model used for destination choice Compare calculated and observed number of trips from TDB Interaction model estimated by using iteration and minimising misplaced flows
Results X 1000 Distance is important for the activities VSH and sun/bath – people prefer to do that close to home. Skiers and people who visits friends and relatives are less concerned about distance.
Tourism Flows Misplaced flows
Problems Multinomial logit regression for destination choice failed ”Empty” LA-regions – no observations ”Holes” in the data – system missing
Data needs More observations for individuals in sparsely populated areas Purpose NOT mixed with activity ”Clean” the array of variables with respect to desired information What about immigrants? Improve ”visit second home” and ”social bond” activities by using SCB-data
Future experiments Change in demand by running ”SVERIGE” 50 years forward divorce, labour market, migration Change supply – move central point of attraction
Summary We model the flow of tourists between LA-regions TDB explain choice of activities An interaction model calculates the choice of place