Transcript Slide 1

The Academy of Economic Studies
DOFIN – Doctoral School of Finance and Banking
Romania’s exports revealed.
A trade and factor analysis
MSc Student: VLAD Mihail Razvan
Supervisor: Prof. Ph.D. Moisa ALTAR
Bucharest, July 2010
1
Objectives

Identifying the goods for which Romania holds a revealed comparative
advantage (RCA) for 2006 to 2009
- by means of the Balassa index

Pinpoint Romania and the EU27 countries in a bi-dimensional space having the
axes capital intensity and labor skill intensity
- by following Neven’s industry classification

Grouping EU27 countries by means of a cluster analysis.
-by the level of they factor intensities

Determining the influences our EU partners have on Romania’s level of exports
- by means of a Gravity model framework
2
Model and methodology
.1 Revealed comparative advantage
.2 Factor analysis – Neven’s classification
.3 The Gravity Model
3
.1 Revealed comparative advantage
o 1965, Balassa in “Trade Liberalization and Revealed Comparative Advantage”
This index compares the share of a given product in a country’s exports
within another country or region, to the share of the same product in
that country or region’s total exports.
The Balassa’s index signification is:
an index value over 1 for a product k denotes a comparative
advantage in the export of goods k for country i on the market j
or over county j
4
.2 Factor analysis – Neven’s classification
1995, Neven classified the factors intensity of production in which the countries
have RCA in 5 groups characterized by different levels of capital and
labor-skill intensities using the following criteria:
•
•
•
•
the share of white-collar workers in total industry labor force
the average wage in the industry,
the ratio of labor costs to industry value added,
and the ratio of fixed investment to value added in the industry
Intensity
Human
Labor
Physical
capital
wages
capital
Example
Cat.
1
Very high
High
Intermediate
High Tech
2
High
High
Low
Electrical equipment
3
Low
High
Low
Textiles; Apparel industry
4
Low
Low
High
Car industry
5
High
Low
High
Paper industry; Food-processing
Table 1. Source: Widgrén (2005)
5
… Factor analysis – Neven’s classification
Category coordinates
(2,0) for category 1
(1,-1) for category 2
(-1,-1) for category 3
(-1,1) for category 4
(1,1) for category 5
If a country’s RCA is equally
distributed across all categories,
it is located at (0.4,0)
•
Countries’ that have RCA in relatively skill-intensive sectors have an x-coordinate
larger than 0.4 and those having RCA in capital-intensive industries have a ycoordinate greater than 0.
6
.3 The Gravity Model
• Main presumption:
Exports from one country to another are explained by their economic size
(measured by GNP or GDP) and the geographical distance between them
• The bottom principle of the model is the Newtonian law of gravity for two
objects
For the purpose of this paper, two equations
were taken into consideration:
7
…The Gravity Model
8
Results and Data description
9
Data description
• The level of exports was extracted for each of the 27 : AT, BG, CZ, DK,
DE, GR, IE,EE, ES, FR, IT, CY, LV, LT, LU, HU, MT, NL, PL, PT, RO, SL,
SK, FI, SE and GB, for all of SITC’s Rev.3 level 4 products, in the period
2006 – 2009 ,-> 2700 products
• The GDP, the level of imports and exports was also extracted from
Eurostat database. The GDP was extracted in constant prices with 2000
as reference year, whereas the level of imports and exports was
extracted in Eur.
• The data for distance and population is taken from Centre D'etudes
Prospectives Et D'informations Internationales. The weighted distance
measure uses city-level data to to calculate distance between two
countries based on bilateral distances between the largest cities of
those two countries
10
.1 Revealed comparative advantage – Results
Romania’s major trading good are those from category 3 which are mostly
given by textile industry, shoes, leather or furniture industry.
11
.2 Factor analysis – Neven’s classification
12
… Revealed comparative advantage – Results
13
… Revealed comparative advantage – Results
14
.3 The Gravity Model - Results
Romania’s aggregate exports:
•
•
•
•
•
•
gdppartner –the GDP of Romania’s trading partners
gdpro – Romania’s GDP,
lndistance –the natural logarithm of the distance separating
the countries,
population~r (populationpartner) – partner’s population,
population~a (populationromania) – Romania’s population,
commoneume-p (commoneumembership) – dummy
variable used to reflect the period past since Romania
joined the EU (2007).
•
As expected, in accordance with the economic theory, the influences of booth Romania’s GDP
and its trading partners GDP have a positive effect in the variances in aggregate level of exports.
•
Distance, not surprisingly, has a negative impact. This may be more due to the fact that
Romania’s past is more related to its not so distant neighbors than with its partners more to the
West.
•
The model’s explanatory power is similar to the ones obtained by other authors that conducted
similar studies
15
… The Gravity Model - Results
Romania’s trade intensity index for aggregate exports:
•
The variances in partner’s GDP this time has a negative influence on the Trade Intensity index.
The negative coefficient may be interpreted as a decrease in the share that Romania’s exports
hold in its partner’s imports and not a decrease in the total volume of exports.
•
Booth Romania’s population and the dummy variable are not significantly different from 0 and
they exert no effect
16
… The Gravity Model - Results
Romania’s exports for goods with RCA in Romania’s trade intensity index for
goods with RCA in Neven’s category 1
Neven’s category 1
• As in the previous cases, the dummy variable and Romania’s population have no influence.
• For this group of products, it seems that the variances across partner’s GDP has no influence on the total
volume of exports, but only Romania’s GDP variances
17
… The Gravity Model - Results
Romania’s exports for goods with RCA in Neven’s category 2
Romania’s trade intensity index for goods with RCA in
Neven’s category 2
Romania’s exports for goods with RCA in Neven’s category 3
Romania’s trade intensity index for goods with RCA in
Neven’s category 3
18
… The Gravity Model - Results
Romania’s exports for goods with RCA in Neven’s category 4
Romania’s trade intensity index for goods with RCA in
Neven’s category 4
Romania’s exports for goods with RCA in Neven’s category 5
Romania’s trade intensity index for goods with RCA in
Neven’s category 5
19
Conclusions
•
Neven’s framework reveals that Romania enjoys the advantages of having goods with RCA in
all of Neven’s five categories, but with higher level of specialization in groups 3 and 4, the
lowest being in group 1
•
The difference between Romania and the other EU27 countries were ameliorated since 2006.
In this 4 year period it can be seen that a shift in specialization has occurred. Romania’s
specialization shifted from an area of goods produced by industries with low levels of capital
and labor skill intensities to goods produced by industries with relative high capital intensity
but low labor skill intensities.
•
The Gravity model has identified that the level of variance in aggregate export is not explained
only by the variances between groups but also by the changes within groups. As such, for
example, Romania’s aggregate export to one of its trading partner is determined not only by
the level of that partner’s GDP but also by the increases/decreases from one period to
another in the partners GDP. This effect, but with weaker force, is also visible in the level of
exports of goods from Neven’s category 1 and 2 especially.
•
The variances in TI are explained in a great measure, by the variables employed, for
categories 1, 2,4 and 5
•
The explanatory power of the model estimation is similar with the ones reported by other
authors who conducted similar studies, i.e. a value of R2 ranging between 0.6 and 0.7.
•
The main coefficients accounting for the influences of Romania’s and its trading partner’s
GDP are significantly different from 0 in the analysis of the total trade, and the TI determined
for this level of trade, and in analyzing goods from category 1 and 2.
20
Thank you!
21
Reference
22