The Drivers of Long-Distance Commuting in Chile: The Role of the Spatial Distribution of Economic Activities

Abstract

Long-distance commuting has emerged as an alternative to migration to equilibrate spatial labour markets. Coupled to changes in the labour and housing markets, technological advances have promoted long-distance commuting by reshaping the links between the spatial distribution of population and regional economies. While previous research has examined these links in developed countries, less is known about how these changes have played out in developing economies. Using micro-census data and regression analysis, this chapter addresses how contextual factors have shaped long-distance commuting in Chile. Our results reveal that the nature and spatial distribution of mining and construction activities have been the primary drivers of long-distance commuting in Chile. This contrasts with developed countries where, along with these activities, factors associated with the new service economy also comprise predominant forces encouraging long-distance commuting, particularly for those in high-skilled occupations.

Appendix 1: Data and Variable Definitions

Number (No.), Percentages (%) and Median Commuting Distance (MCD) in km

Variable	Definition	No.	%	MCD
Labour market characteristics
Industry sector
Agriculture	1 if respondent works in the agriculture sector; 0 otherwise	493,375	11.3	12.8
Mining	1 if respondent works in the mining sector; 0 otherwise	67,167	7.6	44.0
Manufacturing	1 if respondent works in the manufacturing sector; 0 otherwise	580,388	10.4	11.2
Utilities	1 if respondent works in the utility sector; 0 otherwise	31,102	0.9	13.7
Construction	1 if respondent works in the construction sector; 0 otherwise	321,749	21.7	14.5
Trade	1 if respondent works in the trade sector; 0 otherwise	954,591	12.9	11.2
Transport/communication	1 if respondent works in the transport and communication sector; 0 otherwise	349,722	9.4	12.5
Finance	1 if respondent works in the finance sector; 0 otherwise	92,065	1.0	12.7
Business services	1 if respondent works in the business service sector; 0 otherwise	440,138	10.6	12.5
Public administration	1 if respondent works in the public administration sector; 0 otherwise	220,179	4.9	12.7
Community/personal services	1 if respondent works in the community and personal service sector; 0 otherwise	934,285	9.3	10.9
Occupation
Managers	1 if respondent has a management occupation; 0 otherwise	557,415	4.7	11.5
Professionals	1 if respondent has a professional occupation; 0 otherwise	262,022	10.1	10.4
Technicians	1 if respondent has a technical occupation; 0 otherwise	450,074	14.1	11.4
Clerks	1 if respondent has a clerical occupation; 0 otherwise	633,478	5.0	12.9
Trades people	1 if respondent has a trade occupation; 0 otherwise	392,990	6.9	12.7
Agriculture/fishery workers	1 if respondent has an agricultural or fishery occupation; 0 otherwise	219,508	4.6	12.7
Craft workers	1 if respondent has a craft occupation; 0 otherwise	531,189	21.1	12.8
Plant operators	1 if respondent has a plant operator occupation; 0 otherwise	388,383	13.8	12.7
Labourers	1 if respondent has an elementary occupation; 0 otherwise	923,435	17.5	11.4
Armed forces	1 if respondent has a military occupation; 0 otherwise	50,082	2.3	14.4
Employment class
Wage earner	1 if respondent is employed, received a salary and is not included in the categories below; 0 otherwise	3,293,832	82.2	12.7
Domestic worker	1 if respondent is employed as domestic worker; 0 otherwise	258,982	2.8	10.5
Self-employed/employers	1 if respondent is self-employed or is an employer; 0 otherwise	869,140	9.3	10.5
Unpaid family workers	1 if respondent is employed but does not received a salary in return; 0 otherwise	62,999	4.3	10.9
Demographic characteristics
Age	A continuous variable that represents a respondent’s age, between 15 and 64 years	4,484,953	100.0	12.4
Age squared	The square of the continuous variable: age	4,484,953	100.0	12.4
Gender
Male	1 if respondent is male; 0 otherwise	2,914,950	85.4	12.7
Female	1 if respondent is female; 0 otherwise	1,570,003	14.6	10.9
Education
Preschool/non-formal education	1 if respondent has only preschool education, or has no formal education; 0 otherwise	81,380	1.7	12.1
Primary education	1 if respondent has as primary educational qualification as the highest qualification; 0 otherwise	1,096,735	23.4	12.2
Secondary education	1 if respondent has as secondary educational qualification as the highest qualification; 0 otherwise	2,016,700	45.8	12.4
Higher education	1 if respondent has as tertiary educational qualification as the highest qualification; 0 otherwise	1,290,138	29.1	12.4
Household composition
One-earner household	1 if respondent lives in a one-earner household; 0 otherwise	2,501,963	50.4	12.5
Two-earner household, without children	1 if respondent lives in a two-earner household without children younger than 15 years of age; 0 otherwise	449,228	6.3	11.2
Two-earner household, with children	1 if respondent lives in a one-earner household with children younger than 15 years of age; 0 otherwise	833,031	11.0	11.9
Alternative household structure	1 if respondent lives in a household with people aged 15 or over, and shares a home for employment, medical, religious or military reasons but without kinship; 0 otherwise	700,731	32.4	12.7
Housing characteristics
Owner-occupier	1 if respondent lives an owned dwelling; 0 otherwise	3,137,453	68.2	12.4
Renter	1 if respondent lives a rented dwelling; 0 otherwise	833,522	23.0	11.2
Rent-free occupier	1 if respondent lives a rent-free dwelling; 0 otherwise	402,138	8.8	12.5
Migration status
Stayer	1 if respondent has lived in the same municipality for the past 5 years; 0 otherwise	3,571,823	72.4	12.2
Migrant	1 if respondent has changed in the municipality of residence for the past 5 years; 0 otherwise	913,130	27.6	12.6
Geographical context
Population density
Low-density areas	1 if respondent lives in a municipality with a ratio of population to area between 0 and 79; 0 otherwise. The ratios of population density for this variable and those below were defined by using three quantile categories	1,514,185	33.8	19.3
Moderate-density areas	1 if respondent lives in a municipality with a ratio of population to area between 80 and 2490; 0 otherwise	1,552,100	34.6	10.4
High-density areas	1 if respondent lives in a municipality with a ratio of population to area between 2490 and 15,770; 0 otherwise	1,418,668	31.6	8.6
Job accessibility
Low job accessibility	1 if respondent lives in a municipality with access to only 52,362 jobs within a radius of 20 km; 0 otherwise	1,519,902	33.9	13.6
Moderate job accessibility	1 if respondent lives in a municipality with access to 1,304,780 jobs within a radius of 20 km; 0 otherwise	1,540,314	34.3	13.4
High job accessibility	1 if respondent lives in a municipality with access to 1,840,500 jobs within a radius of 20 km; 0 otherwise	1,424,737	31.8	8.2
Mining specialisation	1 if respondent lives in a municipality with a location quotation for mining index over 1	625,549	16.2	34.5
Geographical centrality	1 if respondent lives in a municipality in central Chile, i.e., the region of Valparaíso, the Metropolitan Region or O’Higgins	2,644,197	143.6	9.0