Help for package CIM

Date:

2018-12-21

Title:

Compositional Impact of Migration

Version:

1.0.0

Description:

Produces statistical indicators of the impact of migration on the socio-demographic composition of an area. Three measures can be used: ratios, percentages and the Duncan index of dissimilarity. The input data files are assumed to be in an origin-destination matrix format, with each cell representing a flow count between an origin and a destination area. Columns are expected to represent origins, and rows are expected to represent destinations. The first row and column are assumed to contain labels for each area. See Rodriguez-Vignoli and Rowe (2018) <doi:10.1080/00324728.2017.1416155> for technical details.

Depends:

R (≥ 3.4.0)

License:

GPL-2

Encoding:

UTF-8

Packaged:

2019-01-02 11:20:07 UTC; User

LazyData:

true

RoxygenNote:

6.1.1

Date/Publication:

2019-01-02 13:10:19 UTC

NeedsCompilation:

Author:

Francisco Rowe [aut], Nikos Patias [aut, cre], Jorge Rodríguez-Vignoli [aut]

Maintainer:

Nikos Patias <n.patias@liverpool.ac.uk>

Repository:

CRAN

Compositional Impact of Migration

Description

produce statistical indicators of the impact of migration on the socio-demographic composition of an area. Three measures can be used: ratios, percentages and the Duncan index of dissimilarity. The input data files are assumed to be in an origin-destination matrix format, with each cell representing a flow count between an origin and a destination area. Columns are expected to represent origins, and rows are expected to represent destinations. The first row and column are assumed to contain labels for each area. See Rodríguez-Vignoli and Rowe (2018) for technical details.

Usage

CIM(..., calculation, numerator, denominator, DuncanAll = TRUE,
  rest = TRUE)

Arguments

...

2 or more data frames, each containing an origin-destination migration matrix by population attribute (i.e. age, sex, education, ethnicity, etc.). Columns are expected to represent origins, and rows are expected to represent destionations. The first row and column are assumed to contain labels for each area.

calculation

a character, indicating the migration impact indicator selected to measure the socio-demographic composition of an area. Users can type one of three options: "ratio", "percentage" or "duncan".

numerator

a number, indicating the index number of the data frame to be used as the numerator for the calculation. Type 1 to use the first data frame included in the function. Type 2 to use the second data frame included in the function, and so on.

denominator

a number, indicating the index number of the data frame to be used as the denominator for the calculation. Type 1 to use the first data frame included in the function. Type 2 to use the second data frame included in the function, and so on. Note the numerator data frame must differ from the denominator data frame.

DuncanAll

a logical argument. If calculation = "Duncan", this logical argument must be specified. The Duncan index measures the dissimilarity in the spatial distribution of a chosen group (first data frame in the function) against a reference category as specified by the "DuncanAll" argument. If TRUE, the reference category is the sum of all data frames, except for the first data frame included in the function (i.e. chosen group). If FALSE, a specific data frame must be specified to be the reference group. See Duncan and Duncan (1955) for details on the Duncan index, and Rodríguez-Vignoli and Rowe (2017a, b) for an empirical application of the CIM using the Duncan index.

rest

a logical argument. If calculation = "Duncan", this argument must be specified. It enables a special calculation of the CIM, for a particular area (e.g. the Greater London Metropolitan Area), and the rest of spatial units comprising a country. To correctly compute the CMI, these spatial units need to be amalgamated and included as a single column/row in the matrix - labelled "Rest of the country" (e.g. Rest of the UK). If TRUE, the column/row of the "Rest of the country" is considered for the calculation and is excluded from the denominator of the duncan index. If FALSE, the "Rest of the country" column/row is included in the denominator, producing the wrong results.

Value

an object containing:

for the "ratio" and "percentage" calculation options:

num_results: a data frame containing nine area-level indicators: the Factual Value (FV), Counterfactual Value (CFV), Compositional Impact of Migration (CIM), Compositional Impact of Migration Percentage Change (CIM_PC), Diagonal Cell Indicator (DIAG), Compositional Impact of Migration for Inflows (CIM_I), Compositional Impact of Migration for Outflows (CIM_O), CIM_I as a percentage of CMI (CIM_I_PC), and CIM_O as a percentage of CMI (CIM_O_PC)

for the "duncan" calculation option:

duncan_results: a data frame, containing the Factual Value of the Area-Specific Share (ASFVShare_cg), and the Counterfactual Value of the Area-Specific Share (ASCFVShare_cg) for the chosen group; the Factual Value of the Area-Specific Share (ASFVShare_ref) and the Counterfactual Value of the Area-Specific Share (ASCFVShare_ref) for the reference group; the Area-Specific Share Factual Value Difference between the ASFVShare_cg and ASFVShare_ref (ASShareFV_diff); and the Area-Specific Share Counterfactual Value Difference between the ASCFVShare_cg and ASCFVShare_ref (ASShareCFV_diff). The chosen group corresponds to the first data frame in the function. See above the argument "DuncanAll" to specify the reference category.

duncan_index: a numeric value, indicating the Duncan Index of dissimilarity for the chosen group.

References

Duncan, O.D. and Duncan, B., 1955. A methodological analysis of segregation indexes. American sociological review, 20(2), pp.210-217.

Rodríguez-Vignoli, J.R. and Rowe, F., 2017a. ¿Contribuye la migración interna a reducir la segregación residencial?: el caso de Santiago de Chile 1977-2002. Revista Latinoamericana de Población, (21), pp.7-46.

Rodríguez-Vignoli, J.R. and Rowe, F., 2017b. The Changing Impacts of Internal Migration on Residential Socio-Economic Segregation in the Greater Santiago. 28th International Population Conference of the International Union for the Scientific Study of Population (IUSSP), Cape Town, South Africa.

Rodríguez-Vignoli, J. and Rowe, F., 2018. How is internal migration reshaping metropolitan populations in Latin America? A new method and new evidence. Population studies, 72(2), pp.253-273. doi.org/10.1080/00324728.2017.1416155

Examples

## Read in the two data.frames included in the package
m <- male
f <- female

## Run the function using "ratio" calculation
CIM.ratio <- CIM(m, f, calculation = "ratio", numerator = 1, denominator = 2)
## Print the resulted data.frame
CIM.ratio

## Run the function using "percentage" calculation
CIM.percentage <- CIM(m, f, calculation = "percentage", numerator = 1, denominator = 2)
## See the resulted data.frame
CIM.percentage

## For the Duncan index, we compute impact of internal migration on the spatial pattern of
## residential age segregation of people age 65 and over in the
## local authority districts of Greater London using 2011 census data.
## Chosen group: people aged 65 and over.
## Reference category: the rest of age groups.
## For this example, this group is people aged pop1-14, 15-29, 30-14 and 45-64).
CIM.duncan <- CIM(pop65over, pop1_14, pop15_29, pop30_44, pop45_64,
calculation = "duncan", numerator = 1, DuncanAll= TRUE)
CIM.duncan$duncan_results
CIM.duncan$duncan_index

OD matrix, female, 2008-2013.

Description

4x4 origin-destination migration data matrix, female, 2008-2013, Chile.

Usage

female

Format

A data frame of 4 rows by 4 columns containing a 3x3 origin-destination migration data matrix for females, including counts for the non-migrant population in the diagonal. The first row and column correspond to the area names. Rows correspond to destinations and columns represent origins.

Greater.Santiago: Population, female
Rest.of.the.Metropolitan.region: Population, female
Rest.of.the.country: Population, female

Source

https://www.tandfonline.com/doi/suppl/10.1080/00324728.2017.1416155?scroll=top

OD matrix, male, 2008-2013.

Description

4x4 origin-destination migration data matrix, male, 2008-2013, Chile.

Usage

male

Format

A data frame of 4 rows by 4 columns containing a 3x3 origin-destination migration data matrix for males, including counts for the non-migrant population in the diagonal. The first row and column correspond to the area names. Rows correspond to destinations and columns represent origins.

Greater.Santiago: Population, male
Rest.of.the.Metropolitan.region: Population, male
Rest.of.the.country: Population, male

Source

https://www.tandfonline.com/doi/suppl/10.1080/00324728.2017.1416155?scroll=top

OD matrix, people aged 15-29, 2010-2011.

Description

34x34 origin-destination migration data matrix, population aged 15-29, 2010-2011, UK.

Usage

pop15_29

Format

A data frame of 34 rows by 34 columns containing a 33x33 origin-destination migration data matrix for people aged 15-29, including counts for the non-migrant population in the diagonal. The first row and column correspond to the area names. Rows correspond to destinations and columns represent origins.

Barking and Dagenham: Population, aged 15 to 29
Barnet: Population, aged 15 to 29
Bexley: Population, aged 15 to 29
Brent: Population, aged 15 to 29
Bromley: Population, aged 15 to 29
Camden: Population, aged 15 to 29
Croydon: Population, aged 15 to 29
Ealing: Population, aged 15 to 29
Enfield: Population, aged 15 to 29
Greenwich: Population, aged 15 to 29
Hackney: Population, aged 15 to 29
Hammersmith and Fulham: Population, aged 15 to 29
Haringey: Population, aged 15 to 29
Harrow: Population, aged 15 to 29
Havering: Population, aged 15 to 29
Hillingdon: Population, aged 15 to 29
Hounslow: Population, aged 15 to 29
Islington: Population, aged 15 to 29
Kensington and Chelsea: Population, aged 15 to 29
Kingston upon Thames: Population, aged 15 to 29
Lambeth: Population, aged 15 to 29
Lewisham: Population, aged 15 to 29
Merton: Population, aged 15 to 29
Newham: Population, aged 15 to 29
Redbridge: Population, aged 15 to 29
Richmond upon Thames: Population, aged 15 to 29
Southwark: Population, aged 15 to 29
Sutton: Population, aged 15 to 29
Tower Hamlets: Population, aged 15 to 29
Waltham Forest: Population, aged 15 to 29
Wandsworth: Population, aged 15 to 29
City of London-Westminster: Population, aged 15 to 29
Rest of the UK: Population, aged 15 to 29

Source

2011 Census for England and Wales

OD matrix, people aged 1-14, 2010-2011.

Description

34x34 origin-destination migration data matrix, population aged 1-14, 2010-2011, UK.

Usage

pop1_14

Format

A data frame of 34 rows by 34 columns containing a 33x33 origin-destination migration data matrix for people aged 1-14, including counts for the non-migrant population in the diagonal. The first row and column correspond to the area names. Rows correspond to destinations and columns represent origins.

Barking and Dagenham: Population, aged 1 to 14
Barnet: Population, aged 1 to 14
Bexley: Population, aged 1 to 14
Brent: Population, aged 1 to 14
Bromley: Population, aged 1 to 14
Camden: Population, aged 1 to 14
Croydon: Population, aged 1 to 14
Ealing: Population, aged 1 to 14
Enfield: Population, aged 1 to 14
Greenwich: Population, aged 1 to 14
Hackney: Population, aged 1 to 14
Hammersmith and Fulham: Population, aged 1 to 14
Haringey: Population, aged 1 to 14
Harrow: Population, aged 1 to 14
Havering: Population, aged 1 to 14
Hillingdon: Population, aged 1 to 14
Hounslow: Population, aged 1 to 14
Islington: Population, aged 1 to 14
Kensington and Chelsea: Population, aged 1 to 14
Kingston upon Thames: Population, aged 1 to 14
Lambeth: Population, aged 1 to 14
Lewisham: Population, aged 1 to 14
Merton: Population, aged 1 to 14
Newham: Population, aged 1 to 14
Redbridge: Population, aged 1 to 14
Richmond upon Thames: Population, aged 1 to 14
Southwark: Population, aged 1 to 14
Sutton: Population, aged 1 to 14
Tower Hamlets: Population, aged 1 to 14
Waltham Forest: Population, aged 1 to 14
Wandsworth: Population, aged 1 to 14
City of London-Westminster: Population, aged 1 to 14
Rest of the UK: Population, aged 1 to 14

Source

2011 Census for England and Wales

OD matrix, people aged 30-34, 2010-2011.

Description

34x34 origin-destination migration data matrix, population aged 30-34, 2010-2011, UK.

Usage

pop30_44

Format

A data frame of 34 rows by 34 columns containing a 33x33 origin-destination migration data matrix for people aged 30-34, including counts for the non-migrant population in the diagonal. The first row and column correspond to the area names. Rows correspond to destinations and columns represent origins.

Barking and Dagenham: Population, aged 30 to 44
Barnet: Population, aged 30 to 44
Bexley: Population, aged 30 to 44
Brent: Population, aged 30 to 44
Bromley: Population, aged 30 to 44
Camden: Population, aged 30 to 44
Croydon: Population, aged 30 to 44
Ealing: Population, aged 30 to 44
Enfield: Population, aged 30 to 44
Greenwich: Population, aged 30 to 44
Hackney: Population, aged 30 to 44
Hammersmith and Fulham: Population, aged 30 to 44
Haringey: Population, aged 30 to 44
Harrow: Population, aged 30 to 44
Havering: Population, aged 30 to 44
Hillingdon: Population, aged 30 to 44
Hounslow: Population, aged 30 to 44
Islington: Population, aged 30 to 44
Kensington and Chelsea: Population, aged 30 to 44
Kingston upon Thames: Population, aged 30 to 44
Lambeth: Population, aged 30 to 44
Lewisham: Population, aged 30 to 44
Merton: Population, aged 30 to 44
Newham: Population, aged 30 to 44
Redbridge: Population, aged 30 to 44
Richmond upon Thames: Population, aged 30 to 44
Southwark: Population, aged 30 to 44
Sutton: Population, aged 30 to 44
Tower Hamlets: Population, aged 30 to 44
Waltham Forest: Population, aged 30 to 44
Wandsworth: Population, aged 30 to 44
City of London-Westminster: Population, aged 30 to 44
Rest of the UK: Population, aged 30 to 44

Source

2011 Census for England and Wales

OD matrix, people aged 45-64, 2010-2011.

Description

34x34 origin-destination migration data matrix, population aged 45-64, 2010-2011, UK.

Usage

pop45_64

Format

A data frame of 34 rows by 34 columns containing a 33x33 origin-destination migration data matrix for people aged 45-64, including counts for the non-migrant population in the diagonal. The first row and column correspond to the area names. Rows correspond to destinations and columns represent origins.

Barking and Dagenham: Population, aged 45 to 64
Barnet: Population, aged 45 to 64
Bexley: Population, aged 45 to 64
Brent: Population, aged 45 to 64
Bromley: Population, aged 45 to 64
Camden: Population, aged 45 to 64
Croydon: Population, aged 45 to 64
Ealing: Population, aged 45 to 64
Enfield: Population, aged 45 to 64
Greenwich: Population, aged 45 to 64
Hackney: Population, aged 45 to 64
Hammersmith and Fulham: Population, aged 45 to 64
Haringey: Population, aged 45 to 64
Harrow: Population, aged 45 to 64
Havering: Population, aged 45 to 64
Hillingdon: Population, aged 45 to 64
Hounslow: Population, aged 45 to 64
Islington: Population, aged 45 to 64
Kensington and Chelsea: Population, aged 45 to 64
Kingston upon Thames: Population, aged 45 to 64
Lambeth: Population, aged 45 to 64
Lewisham: Population, aged 45 to 64
Merton: Population, aged 45 to 64
Newham: Population, aged 45 to 64
Redbridge: Population, aged 45 to 64
Richmond upon Thames: Population, aged 45 to 64
Southwark: Population, aged 45 to 64
Sutton: Population, aged 45 to 64
Tower Hamlets: Population, aged 45 to 64
Waltham Forest: Population, aged 45 to 64
Wandsworth: Population, aged 45 to 64
City of London-Westminster: Population, aged 45 to 64
Rest of the UK: Population, aged 45 to 64

Source

2011 Census for England and Wales

OD matrix, people aged 65+, 2010-2011.

Description

34x34 origin-destination migration data matrix, population aged 65+, 2010-2011, UK..

Usage

pop65over

Format

A data frame of 34 rows by 34 columns containing a 33x33 origin-destination migration data matrix for people aged 65+, including counts for the non-migrant population in the diagonal. The first row and column correspond to the area names. Rows correspond to destinations and columns represent origins.

Barking and Dagenham: Population, aged 65 plus
Barnet: Population, aged 65 plus
Bexley: Population, aged 65 plus
Brent: Population, aged 65 plus
Bromley: Population, aged 65 plus
Camden: Population, aged 65 plus
Croydon: Population, aged 65 plus
Ealing: Population, aged 65 plus
Enfield: Population, aged 65 plus
Greenwich: Population, aged 65 plus
Hackney: Population, aged 65 plus
Hammersmith and Fulham: Population, aged 65 plus
Haringey: Population, aged 65 plus
Harrow: Population, aged 65 plus
Havering: Population, aged 65 plus
Hillingdon: Population, aged 65 plus
Hounslow: Population, aged 65 plus
Islington: Population, aged 65 plus
Kensington and Chelsea: Population, aged 65 plus
Kingston upon Thames: Population, aged 65 plus
Lambeth: Population, aged 65 plus
Lewisham: Population, aged 65 plus
Merton: Population, aged 65 plus
Newham: Population, aged 65 plus
Redbridge: Population, aged 65 plus
Richmond upon Thames: Population, aged 65 plus
Southwark: Population, aged 65 plus
Sutton: Population, aged 65 plus
Tower Hamlets: Population, aged 65 plus
Waltham Forest: Population, aged 65 plus
Wandsworth: Population, aged 65 plus
City of London-Westminster: Population, aged 65 plus
Rest of the UK: Population, aged 65 plus

Source

2011 Census, England and Wales