Package decompr. August 17, 2016
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1 Version Title Global-Value-Chain Decomposition Package decompr August 17, 2016 Two global-value-chain decompositions are implemented. Firstly, the Wang-Wei-Zhu (Wang, Wei, and Zhu, 2013) algorithm splits bilateral gross exports into 16 value-added components. Secondly, the Leontief decomposition (default) derives the value added origin of exports by country and industry, which is also based on Wang, Wei, and Zhu (Wang, Z., S.-J. Wei, and K. Zhu ``Quantifying International Production Sharing at the Bilateral and Sector Levels.''). Maintainer Bastiaan Quast Depends R (>= 2.10) License GPL-3 URL BugReports Suggests gvc, testthat, knitr VignetteBuilder knitr RoxygenNote NeedsCompilation no Author Bastiaan Quast [aut, cre], Fei Wang [aut], Victor Kummritz [aut], Oliver Reiter [ctb] Repository CRAN Date/Publication :47:36 R topics documented: countries decomp decompr final
2 2 decomp industries inter leontief load_tables load_tables_vectors out wwz Index 10 countries Leather Example the names of the countries data decomp Interface function for decompositions Usage This function runs the decomposition. NOTE: the default method is now "leontief", please specify method="wwz" explicitly for Wang-Wei-Zhu. See for more information. decomp(x, y, k, i, o, v, method = c("leontief", "wwz"), verbose = FALSE,...) Arguments x y k i intermediate demand table, it has dimensions GN x GN (G = no. of country, N = no. of industries), excluding the first row and the first column which contains the country names, and the second row and second column which contain the industry names for each country. In addition, an extra row at the end should contain final demand. final demand table it has dimensions GN x MN, excluding the first row and the first column which contains the country names, the second column which contains the industry names for each country, and second row which contains the five decomposed final demands (M). k is a vector of country of region names vector or country or region names vector of sector or industry names
3 decomp 3 o v Details Value method verbose vector of final outputs vector of value added, optional. If this vector is not specified, value added will be calculated as gross output - intermediate consumption user specified the decomposition method logical, should timings of the calculation be displayed? Default is FALSE... arguments to pass on the respective decomposition method Version 2 introduces several important changes, the default method is now leontief, which means that wwz has to be specified explicitly. Furthermore, the input object have a different structure, see the information below for details. The output when using the WWZ algorithm is a matrix with dimensions GNG*19. Whereby 19 is the 16 objects the WWZ algorithm decomposes exports into, plus three checksums. GNG represents source country, using industry and using country. Bastiaan Quast References Timmer, Marcel P. (ed) (2012), "The World Input-Output Database (WIOD): Contents Sources and Methods", WIOD Working Paper Number 10, downloadable at Wang, Zhi, Shang-Jin Wei, and Kunfu Zhu. Quantifying international production sharing at the bilateral and sector levels. No. w National Bureau of Economic Research, Examples # load leather example data data(leather) # explore the data set ls() # explore each of the objects inter final countries industries out # use the direct approach # run the Leontief decomposition decomp(inter, final,
4 4 final countries, industries, out, method = "leontief") # run the WWZ decomposition decomp(inter, final, countries, industries, out, method = "wwz") decompr Export Decomposition using the Wang-Wei-Zhu and Leontief decompositions algorithms. Two global-value-chain decompositions are implemented. Firstly, the Wang-Wei-Zhu (Wang, Wei, and Zhu, 2013) algorithm splits bilateral gross exports into 16 value-added components. Secondly, the Leontief decomposition (default) derives the value added origin of exports by country and industry, which is also based on Wang, Wei, and Zhu (Wang, Z., S.-J. Wei, and K. Zhu "Quantifying International Production Sharing at the Bilateral and Sector Levels."). Bastiaan Quast <bquast@gmail.com> Fei Wang Victor Kummritz References Wang, Zhi, Shang-Jin Wei, and Kunfu Zhu. Quantifying international production sharing at the bilateral and sector levels. No. w National Bureau of Economic Research, See Also final Leather Example the final demand data
5 industries 5 industries Leather Example the names of the industries data inter Leather Example the intermediate demand data leontief Leontief Decomposition Usage Leontief Decomposition leontief(x, post = c("exports", "output", "final_demand", "none"), long = TRUE) Arguments x post long an object of class decompr post-multiply the Leontief inverse with something, the default is exports transform the output data into a long (tidy) data set or not, default it TRUE. Value a data frame containing the square matrix and labelled column and rows Bastiaan Quast References Wang, Zhi, Shang-Jin Wei, and Kunfu Zhu. Quantifying international production sharing at the bilateral and sector levels. No. w National Bureau of Economic Research, 2013.
6 6 load_tables Examples ## load example data data(leather) ## create intermediate object (class decompr) decompr_object <- load_tables_vectors(inter, final, countries, industries, out ) ## run the Leontief decomposition on the decompr object leontief(decompr_object ) load_tables Load the Input-Output and Final demand tables This function loads the demand tables and defines all variables for the decomposition Usage load_tables(x, y) Arguments x y the intermediate demand table, it has dimensions GN x GN (G = no. of country, N = no. of industries), excluding the first row and the first column which contains the country names, and the second row and second column which contain the industry names for each country. In addition, an extra row at the end should contain final demand. the final demand table it has dimensions GN x MN, excluding the first row and the first column which contains the country names, the second column which contains the industry names for each country, and second row which contains the five decomposed final demands (M). Details Adapted from code by Fei Wang. Value a decompr class object Bastiaan Quast
7 load_tables_vectors 7 load_tables_vectors Load the Input-Output and Final demand tables This function loads the demand tables and defines all variables for the decomposition Usage load_tables_vectors(x, y, k, i, o, v = NULL, null_inventory = FALSE) Arguments x y k i o v intermediate demand table, it has dimensions GN x GN (G = no. of country, N = no. of industries), excluding the first row and the first column which contains the country names, and the second row and second column which contain the industry names for each country. In addition, an extra row at the end should contain final demand. final demand table it has dimensions GN x MN, excluding the first row and the first column which contains the country names, the second column which contains the industry names for each country, and second row which contains the five decomposed final demands (M). k is a vector of country of region names vector or country or region names vector of sector or industry names vector of final outputs vector of value added null_inventory when the inventory (last FDC) should be set to zero Details Adapted from code by Fei Wang. Value a decompr class object Bastiaan Quast
8 8 wwz Examples # load example data data(leather) # create intermediate object (class decompr) decompr_object <- load_tables_vectors(inter, final, countries, industries, out) # examine output object str(decompr_object) out Leather Example final output wwz Runs the Wang-Wei-Zhu decomposition This function runs the Wang-Wei-Zhu decomposition. Usage wwz(x, verbose = FALSE) Arguments x verbose an object of the class decompr logical, should timings of the calculation be displayed? Default is FALSE Details Adapted from code by Fei Wang. Value the decomposed table
9 wwz 9 Bastiaan Quast References Wang, Zhi, Shang-Jin Wei, and Kunfu Zhu. Quantifying international production sharing at the bilateral and sector levels. No. w National Bureau of Economic Research, Examples # load example data data(leather) # create intermediate object (class decompr) decompr_object <- load_tables_vectors(inter, final, countries, industries, out ) # run the WWZ decomposition on the decompr object wwz(decompr_object)
10 Index countries, 2 decomp, 2 decompr, 4 decompr-package (decompr), 4 final, 4 industries, 5 inter, 5 leontief, 5 load_tables, 6 load_tables_vectors, 7 out, 8 wwz, 8 10
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Package RIGHT. March 30, 2015
Type Package Title R Interactive Graphics via HTML Version 0.2.0 Date 2015-03-30 Package RIGHT March 30, 2015 Author ChungHa Sung, TaeJoon Song, JongHyun Bae, SangGi Hong, Jae W. Lee, and Junghoon Lee
Package polynom. R topics documented: June 24, 2015. Version 1.3-8
Version 1.3-8 Package polynom June 24, 2015 Title A Collection of Functions to Implement a Class for Univariate Polynomial Manipulations A collection of functions to implement a class for univariate polynomial
Package MixGHD. June 26, 2015
Type Package Package MixGHD June 26, 2015 Title Model Based Clustering, Classification and Discriminant Analysis Using the Mixture of Generalized Hyperbolic Distributions Version 1.7 Date 2015-6-15 Author
Package CIFsmry. July 10, 2016. Index 6
Type Package Package CIFsmry July 10, 2016 Title Weighted summary of cumulative incidence functions Version 1.0.1.1 Date 2013-10-10 Author Jianing Li Maintainer Jianing Li Depends R(>= 3.0.1)
Package tikzdevice. February 20, 2015
Encoding UTF-8 Type Package Title R Graphics Output in LaTeX Format Version 0.8.1 Date 2015-01-07 URL https://github.com/yihui/tikzdevice Package tikzdevice February 20, 2015 BugReports https://github.com/yihui/tikzdevice/issues