July 2011 Draft!

REAL-IO : Analytical toolbox of Inter-regional Input-Output Analysis

Norihiko Yamano **, Chun-Hua Wu*, and Geoffrey Hewings*

*Regional Economics Applications Laboratory, University of Illinois at Urbana-Champaign

** OECD

Abstract

This manual outlines the features of recently updated Input-Output software (originally designated as PyIO) developed at Regional Economics Applications Laboratory, University of Illinois at Urbana-Champaign. The software has functions for table operations, displaying basic indicators for regional/country comparisons and advanced analysis using various types of input-output databases i.e. non-competitive type table, inter-regional input-output model. The latest version of REAL-IO is capable of adding functions without recompiling the interface code of software.

Tables of contents

1. Introduction

2. Installation

3. Running software

4. Preloaded functions

Input-output table operations

Analysis of single-region (country) model

Analysis of inter-regional (country) model

5. Installation of additional input-output database

5.1 single-region (country) tables

5.2 inter-regional (country) tables

6. Installation of additional functions

Appendix

History

Preloaded Database

OECD Input-Output Database (February 2011)

OECD Inter-country Input-Output model (June 2011)

World Input-Output Database (Preliminary)

1. Introduction

REAL-IO is an input-output operation software is a generic toolbox of Input-Output analysis based on open-source architecture running on Windows XP/7. Following the previous versions, termed PyIO (Nazara et al.,2003; Wu, 2009), Python is retained as the interface building software. However, the main modules of matrix calculations have been currently migrated to the R language environment.[1] (SPlus equivalent freeware). This change allows the users to introduce their own database and additional functions in a much more convenient way than in previous versions.

2. Installation

The latest set of software is available at All files should be unzipped and stored in a designated folder (e.g. c:/REAL-IO/). The example data sources (e.g. OECD STAN Input-Output Database for 44 countries and Inter-country inter-industry . See Appendix for the details) and the updated function codes for analyses are also available at

Please place the parameter set files under the folder named ./para and data sources files under the folder named ./dataset.

for OECD STAN Input-output tables for 44 countries. See Appendix for the details.

for OECD Inter-country input-output system. See Appendix for the details.

For userswho wish to revise the fundamental structure of the software, download and install Python 2.4 ( and wxPython ( Otherwise, no additional components are needed for installation.

Figure 1. Opening screen

3. Running the Software

Having installed all the software and data sources at the desired working directory (for example, c:/REAL-IO), the software can be started by clicking real-io.exe. Following the opening screen (figure 1), the software start,under [View] menu, there are two displaying functions, [Table] and [GDP by industry]. After choosing the dataset, target country and year (figure 2), it takes a while for R to produce the display files for the first time, but you can quickly see the results subsequently since the result files are already produced and stored in the results storing folder in an excel format (./results/). Users are recommended to run all the functions at the beginning by clicking “do all analysis in one click” to reduce the waiting time.

Figure 2. Dataset, Country and Period selection menu

4. Preloaded functions

4.1 Input-output table operations

[View] [Table] [Total / Domestic / Import]

[View] [GDP by industry]

Figure 3. Displaying input-output database

4.2 Analysis of single-region (country) model

Various single country-based analysis are preloaded in Py-R-IO.

Figure 4. Menu of Single region analysis

Inverse matrix for backward and forward linkages

Frequently used basic indicators of input-output table are backward linkage and forward linkage indicators based on Leontief and Ghosh inverse matrices.

Figure 4. Leontief Inverse (Austria, 2005)

Figure 5. Backward Linkages (Austria, 2005)

Figure 6 Ghosian Inverse (Germany, 2005)

Figure 7. Forward Linkages (Germany, 2005)

Import content of exports (vertical specialization) indicates the backward effects of global supply chains of exports. The direct and indirect imported intermediate values that are included in a country’s exports are measured. The larger OECD countries and natural resource oriented countries depend less on imported intermediates. Also, the significant increases in major Asian economies e.g. China, Korea and Japan were particularly evident.


4.3 Analysis of inter-regional(country) model

Interregional input-output model is very useful tool to identify the interregional spillover effects and feedback effects. Recently, production processes have become more fragmented in different regions and countries, but the spillover effects are negligible particularly in small economies.

In general, since an interregional (inter-country) input-output table often has a large dimension, it is efficient to store only the inter-regional table in one datafile (.Rdata extension files). Hence, the preloaded database of interregional input-output model is separated into different datafiles.

Inter-regional spillover effects

The non-domestic part of induced output i.e. inter-country spillover effects, have increased particularly in European region. This spillover effects is measured by the ratio of inter-country part of Leontief inverse (B). For simplicity, three countries example can be expressed as follows.

The spillover effect (S1), the output induced in foreign countries due to the increase in final expenditure of country 1 is then defined as

S1= (B21+B31)/(B11+B21+B31).

The spillover magnitudes are widely different across Asian countries (Error! Reference source not found. for Asian/Pacific countries and Annex for all target countries). While the induced output remains within domestic economy in large countries (China, India and Japan), the spillover magnitudes are greater in smaller Asian countries. In particular, the domestic impacts of final expenditures are less in the higher income countries in Southeast Asia (Malaysia, Singapore and Thailand). Nonetheless, most of the ripple effects of these countries are still confined in the other Asian countries; more than 70% of total economic effects are induced within Asia/Pacific region.

Inter-country spillover effects (2005)

Source: OECD Inter-country inter-industry model (March 2011)

Average propagation link of multi-country framework, another advanced analysis usinginter-country input-output model, indicates the complexity of inter-industry transaction both domestic and inter-country production network.

• Input coefficient = A , output X = AX+F

•Leontief inverse: B = (I-A)-1 = (I+A+A2+A3…)

•Length multiplier (L)=(I+1A+2A2+3A3… )/B

•Average length by industry = L F/B F

•Average length by country = sum(L F) / sum(BF)

•Average length decomposed by domestic & fragmented

The results clearly indicate that the propagation production processes has increased particularly in foreign propagation. The magnitude of changes in this index basically follows the result of fragmentation chain index.

Average propagation link indicator in multi-country framework

Source: OECD Inter-country inter-industry model (March 2011)

5. Installation of additional functions

There are two text files which recode single regional and multiregional analysis R-codes respectively in the folder ./para. Users easily restructure the menu structure of software and include the additional functions by following steps.

1) Edit ./para/funclist1.txt found in ./para folder

The format of the setting file follows. The first row recodes the menu name, “Single Regional Analysis”. From 2 to 71 rows, they recode 70 sets of expansiblefunctions.

The first item, ”GDP”, is the name of the function that shows on the menu. The second item, “func00” is the filename of R-code need to be specify”. The third item,“1”, is the pop-menu type which allow user to use different kind type of pop-menu. If it is specified “0”, then there is no pop-menu.

Similarly, the multiregional analysis functions could be added in ./para/funclist2.txt found in ./para folder.

2) Edit corresponding codes for the functions

Using the codes of preloaded function as example, the codes of Input-Output analysis can be included.

The R code files are put in ./Rcode folder. The filenames of R code mush response to the specification in funclist1.txt and funclist2.txt in ./para folder

References

REAL, Python Module for Input-Output Analysis,

Wu, C., 2009. PyIO 2.0 Quick Start, July 2009,

Nazara, S., D Guo, G. Hewings, and C. Dridi, 2003. PyIO: Input-Output Analysis with Python, REAL Discussion Paper, 03-T-23

Appendix

A. History

Date / Description
July 2011 / REAL-IO 1.0
October 2009 / REAL-IO development started
June 2009 / PyIO 2.1. Last version of old platform
2002 / PyIO 1.0 First public version

B. OECD Input-Output Database (May 2011)

The latest set of OECD Input-Output tables includes3 recently added countries (Chile,Romania and Thailand). The matrices of inter-industrial flows of transactions ofgoods and services (domestically produced and imported) in current prices, for all OECD countries (but Iceland) and 11 non-member countries, covering the years 1995, 2000 and 2005 or nearest years.(see coverage at Through the use of a standard industry list based on ISIC Revision 3, comparisons can be made across countries. The industry classification used in the current version of the I-O database is based on ISIC Rev.3 (Table 2), meaning that it is compatible with the other OECD industry-based analytical data sets such as the Structural Analysis database (STAN), based on SNA by activity, and bilateral trade in goods by industry (derived from merchandise trade statistics via standard Harmonized System to ISIC conversion keys).

Further information for each country and the estimation methodology is available in the Yamano and Ahmad, OECD Input-Output Database edition 2006 - STI Working Paper 2006/8.

To access the full dataset, users are invited to go to the themes:

"Industry and Services",

"Structural Analysis (STAN) Databases",

"Input Output Database".

Format of OECD Input-Output Database

Table B1. Target countries

Table B2. Target sectors

C. OECD Inter-country Input-Output model

The inter-country input-output database is useful data to measure the economic dependencies across countries in order to interpret the various economic policies e.g. formation of custom union, free-trade agreement and regional market integration. This database is not only useful to measure the globalisation indicator, but also it can be used as a fundamental data of various economic empirical models such as international computable general equilibrium model, environmental pollution embodied in international trade and international diffusions of innovation activities (R-D expenditures).

At OECD, using the harmonised input-output tables and bilateral trade coefficients in goods and services, the inter-country input-output tables for the reference years of 1995, 2000 and 2005 are estimated applying the multi-regional input-output model techniques previously established for regional analyses (Chenery-Moses; Isard).

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