Intercountry Input-Output Table
5 countries, in current prices
(industry-by-industry)
(millions
of US$) FRANCE - EXPORTER AND AUS,BEL,CAN,ITA,JPN –IMPORTER
COUNTRY
YEAR SECTOR
AUS BEL CAN ITA JPN
2000 Crop and animal production, hunting
and related service activities 587 183 317 271 87
2001 Crop and animal production, hunting
and related service activities 707 190 285 278 929
2002 Crop and animal production, hunting
and related service activities 453 20 246 394 138
2000 Manufacture of coke and refined
petroleum products 47 65 76 22 0
2001 Manufacture of coke and refined
petroleum products 56 39 79 44 0
2002 Manufacture of coke and refined
petroleum products 60 57 60 87 0
Legal and accounting activities;
2000 activities of head offices; management
consultancy activities 5,108 3,181 307 1,998 134
Legal and accounting activities;
2001 activities of head offices; management
consultancy activities 4,821 4,282 306 2,354 762
Legal and accounting activities;
2002 activities of head offices; management
consultancy activities 5,423 4,677 306 2,484 815
STATSTICAL ANALYSIS
Column1 Column2 Column3
Mean 1918 Mean 1410.444 Mean 220.2222
Standard Error 805.3009272 Standard Error 671.8901 Standard Error 37.80203
Median 587 Median 183 Median 285
Mode #N/A Mode #N/A Mode 306
Standard Standard Standard
Deviation 2415.902782 Deviation 2015.67 Deviation 113.4061
Sample Variance 5836586.25 Sample Variance 4062927 Sample Variance 12860.94
-
Kurtosis 1.649684507 Kurtosis -1.16265 Kurtosis -1.72101
Skewness 0.835312062 Skewness 0.985823 Skewness -0.75131
Range 5376 Range 4657 Range 257
Minimum 47 Minimum 20 Minimum 60
Maximum 5423 Maximum 4677 Maximum 317
Report: Analysis of Intercountry Input-Output Table
Introduction
The dataset provided contains intercountry input-output tables detailing trade values (in
millions of US dollars) between France and five other countries (Australia, Belgium,
Canada, Italy, and Japan) across various industries for the years 2000, 2001, and 2002.
From this dataset, statistical analyses have been conducted to understand the patterns and
trends in trade dynamics between these countries and sectors. Let's break down the
analysis and discuss the implications based on international trade theories and existing
literature.
Data Summary and Analysis-The provided dataset includes trade values across several
sectors for each country pair (France with Australia, Belgium, Canada, Italy, and Japan)
over three years. Statistical analysis has been performed on these trade values to uncover
insights into the trading patterns and sectoral dependencies between these countries.
Sector Analysis:-The dataset covers diverse sectors including agriculture, manufacturing,
and services. Sectors like "Legal and accounting activities; activities of head offices;
management consultancy activities" show substantial trade volumes.
Country-Specific Trends: Different countries exhibit varying levels of trade intensity with
France across sectors. For instance, Belgium consistently engages in high-value trade
across various sectors with France.
Yearly Fluctuations: Trade values show fluctuations across the three years, suggesting
changing economic conditions or trade policies.
Observations and Interpretations
Crop and Animal Production, Hunting, and Related Services
Australia (AUS):
Trend: Export to BEL and CAN decrease from 2000 to 2002 but increased to ITA and JPN.
Belgium (BEL):
Trend: Stable import from AUS; overall trends vary by sector.
Canada (CAN):
Trend: Import fluctuations across years, potentially influenced by domestic production and
global market dynamics.
Italy (ITA):
Trend: Increased imports from AUS.
Japan (JPN):
Trend: Varied but consistent imports.
Manufacture of Coke and Refined Petroleum Products
Australia (AUS):
Trend: Minimal exports, suggesting domestic demand.
Belgium (BEL):
Trend: Moderate imports; potential for local demand or supply chain needs.
Canada (CAN):
Trend: Significant imports, indicating reliance on foreign supply.
Italy (ITA):
Trend: Imports vary annually, influenced by market conditions.
Japan (JPN):
Trend: No imports, indicating self-sufficiency or alternative supply sources.
Legal and Accounting Activities; Head Offices; Management Consultancy
Australia (AUS):
Trend: Minimal imports, potentially meeting specific needs.
Belgium (BEL):
Trend: Varied imports; reliance on external expertise.
Canada (CAN):
Trend: Steady imports; seeking specialized services.
Italy (ITA):
Trend: Imports indicate demand for external expertise.
Japan (JPN):
Trend: Growing imports; reliance on foreign services.
Economic Implications
Sectoral Dynamics: Certain sectors like "Legal and Accounting Activities; Head Offices;
Management Consultancy" demonstrate higher trade volumes, suggesting specialized
services or expertise sought by importing countries.
Country-Specific Trends: Variations in trade patterns among importing countries highlight
unique economic relationships with France, influenced by factors such as geographical
proximity, market size, and sectoral specialization.
Statistical Interpretations
The statistical analysis provides insights into the distribution and variability of trade values:
Mean: Average trade value across sectors and countries. The mean export value from
France to the importing countries (AUS, BEL, CAN, ITA, and JPN) varies across sectors
and years. For instance, the mean export value to AUS is $1918 million; to BEL is $1410.44
million.
Standard Deviation: Indicates the dispersion of trade values around the mean. These
measures indicate the dispersion or spread of export values around the mean. Higher
standard deviation and variance suggest greater variability in export values across sectors
and years.
Median: Middle value in the dataset, providing insight into central tendencies. The median
values provide insights into the central tendency of the data. For example, the median
export value to AUS is 587 million USD.
Skewness and Kurtosis: Indicate the shape and distribution characteristics of the dataset
Skewness measures the asymmetry of the distribution of export values. Positive skewness
indicates that the distribution is skewed towards higher export values. Kurtosis measures
the peakedness of the distribution. A negative kurtosis indicates a flatter distribution.
Range: The range between the minimum and maximum export values for each sector and
country pair provides an understanding of the extent of variation in export values.
Trading Patterns and Interpretation:
Sectorial Analysis: Different sectors exhibit varying levels of export activity. For instance,
legal and accounting activities show significantly higher export values compared to crop and
animal production.
Yearly Trends: The export values fluctuate over the years, suggesting changing demand or
supply dynamics, economic conditions, or policy influences.
Importing Countries: Variations in export values across different importing countries (AUS,
BEL, CAN, ITA, and JPN) can reflect specific trade relationships, market conditions, or
economic partnerships.
Trade Theories and Interpretation:
The observed trading patterns align with several international business theories:
Comparative Advantage: Countries specialize in sectors where they have a comparative
advantage, reflected in trade patterns.
Gravity Model: Proximity, economic size, and cultural factors influence trade patterns
between countries.
Product Life Cycle Theory: Shifts in import/export trends may reflect changing product life
cycles and market demands.
New Trade Theory: Countries trade based on economies of scale and differentiated
products, explaining varied import/export volumes.
In conclusion, this detailed analysis of intercountry trade dynamics between France and its
trading partners (Australia, Belgium, Canada, Italy, and Japan) reveals important insights
into sectoral dependencies, trade patterns, and economic relationships. By combining
statistical interpretations with established international trade theories, we gain a deeper
understanding of the underlying factors shaping these trade flows. The findings highlight the
diversity of sectors involved in trade, ranging from agriculture and manufacturing to
services, with notable variations across countries and over time.
By contextualizing statistical analyses within theoretical frameworks, this study contributes
to a more nuanced understanding of international trade dynamics and informs strategic
decision-making in the realm of global commerce. It underscores the importance of data-
driven insights in shaping effective trade policies and business strategies in an
interconnected global economy.
