R: Structural Change Publications

scPublications {strucchange} | R Documentation

## Structural Change Publications

### Description

Bibliographic information about papers related to structural change and changepoints published in 27 different econometrics and statistics journals.

### Usage

    data("scPublications")

### Format

A data frame containing information on 835 structural change papers in 9 variables.

author

  character. Author(s) of the paper.

title

  character. Title of the paper.

journal

  factor. In which journal was the paper published?

year

  numeric. Year of publication.

volume

  numeric. Journal volume.

issue

  character. Issue within the journal volume.

bpage

  numeric. Page on which the paper begins.

epage

  numeric. Page on which the paper ends.

type

  factor. Is the journal an econometrics or statistics journal?

### Details

The data set `scPublications` includes bibliographic information about publications related to structural change and obtained from the ‘ISI Web of Science’. The query was based on the ‘Science Citation Index Expanded’ and ‘Social Sciences Citation Index’ (for the full range of years available: 1900-2006 and 1956-2006, respectively). The ‘Source Title’ was restricted to the 27 journals in the data frame and the ‘Topic’ to be one of the following: structural change, structural break, structural stability, structural instability, parameter instability, parameter stability, parameter constancy, change point, changepoint, change-point, breakpoint, break-point, break point, CUSUM, MOSUM. Additionally, the famous CUSUM paper of Brown, Durbin and Evans (1975) was added manually to `scPublications` (because it did not match the query above).

### Source

ISI Web of Science at http://www.isiknowledge.com/. Queried by James Bullard.

### Examples

    ## construct time series:
    ## number of sc publications in econometrics/statistics
    data("scPublications")

    ## select years from 1987 and
    ## `most important' journals
    pub <- scPublications
    pub <- subset(pub, year > 1986)
    tab1 <- table(pub$journal)
    nam1 <- names(tab1)[as.vector(tab1) > 9] ## at least 10 papers
    tab2 <- sapply(levels(pub$journal), function(x) min(subset(pub, journal == x)$year))
    nam2 <- names(tab2)[as.vector(tab2) < 1991] ## started at least in 1990
    nam <- nam1[nam1 %in% nam2]
    pub <- subset(pub, as.character(journal) %in% nam)
    pub$journal <- factor(pub$journal)
    pub_data <- pub

    ## generate time series
    pub <- with(pub, tapply(type, year, table))
    pub <- zoo(t(sapply(pub, cbind)), 1987:2006)
    colnames(pub) <- levels(pub_data$type)

    ## visualize
    plot(pub, ylim = c(0, 35))

[Package strucchange version 1.5-2 Index]