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This paper investigates the determinants of intraindustry trade (IIT), horizontal IIT (HIIT), and Vertical IIT (VIIT) in the automobile industry in Portugal. The trade in this sector between Portugal and the European Union (EU-27) was examined, between 1995 and 2008, using a dynamic panel data. We apply the GMM system to solve the problems of serial correlation and the endogeneity of some explanatory variables. The findings are consistent with the literature. The difference between per capita incomes and factor endowments present a positive sign. These results are according to Heckscher-Ohlin predictions. The economic dimension has a positive impact on trade. A negative effect of the distance on bilateral trade was expected and the results confirm this, underlining the importance of neighbour partnerships for all trade.

The intraindustry trade (IIT) or two-way trade is explained by product differentiation and the existence of products belonging to the same category. The big push in the literature emerged with the work of Grubel and Lloyd [

In this respect, the vertical intraindustry trade (VIIT) admits different types of quality, that is, different types of preferences. The consumers have different types of income per capita, which emphasize the theoretical models of Falvey and Kierzkowski [

In 1990s the intermediate goods led to interest in the academic community [

This paper presents two contributions. First we use the GMM system estimator because we intended to evaluate the long-term effects. Second, this study contributes to the discussion of the development of automobile industry and fragmentation theory.

The results presented in this paper for this specific industrial sector are generally consistent with the expectations of intraindustry trade studies. The remainder of the paper is organised as follows: Section

In recent years, emerged in the literature an explanation of international trade based on the transaction of intermediate goods. Fragmentation also called outsourcing of production has received attention from many scholars especially starting in the 1990s.

In fact, the conceptual model of Jones and Kierzkowski [

Globalisation promotes regional clusters in the international economics. As Eiteam et al. [

The research of Ando [

The study of Faustino and Leitão [

Leitão [

Grubel and Lloyd [

The index is equal to 1 if all trade is intraindustry. If

Grubel and Lloyd [

Aquino [

To determine the horizontal (HIIT_{it}) and vertical intraindustry trade (VIIT_{it}), Grubel and Lloyd [

Where HIIT_{it}:

and VIIT_{it} is

In Figure

Trade between Portugal and European Countries for the period 1995–2008.

The dependent variable used is the IIT Grubel and Lloyd [

This study uses a dynamic panel data (GMM system). In static panel data models, Pooled OLS, fixed effects (FEs), and random effects (REs) estimators have some problems like serial correlation, heteroskedasticity, and endogeneity of some explanatory variables.

The estimator GMM system (GMM-SYS) permits the researchers to solve the problems of serial correlation, heteroskedasticity and endogeneity for some explanatory variables. These econometric problems were solved by Arellano and Bond [

There is a negative (positive) correlation between differences in per capita income and IIT and HIIT (VIIT).

Regarding Hypothesis

IIT and HIIT occurs more frequently among countries that are similar in terms of factor endowments.

VIIT predominate among countries that are dissimilar in terms of factor endowments.

LogEP is a proxy for differences in physical endowments. It is the logarithm of the absolute difference in electric power consumption (Kwh per capita) between Portugal and its partners. Considering Hypothesis

The economic dimension influences the volume of trade positively.

Trade increases when partners are geographically close.

LogDIST is the logarithm of geographical distance between Portugal and the partner country. Following the most empirical studies, we use kilometres between the capital cities of the trading partners. According to the literature, we expect a negative sign (Badinger and Breuss [

We consider that

Following the empirical work of Hummels and Levinsohn [

The model can be rewritten in the following dynamic representation:

Table

Summary statistics.

Variables | ||||
---|---|---|---|---|

LogIIT | −0.56 | 0.56 | −2.56 | −0.01 |

LogHIIT | −2.22 | 1.42 | −6.14 | −0.07 |

LogVIIT | −0.92 | 0.63 | −2.87 | −0.05 |

LogDGDP | 4.13 | 0.38 | 2.18 | 4.93 |

LogEP | 3.37 | 0.46 | 1.60 | 4.12 |

LogDIM | 4.31 | 0.20 | 3.77 | 4.82 |

LogDIST | 3.33 | 0.18 | 2.70 | 3.59 |

Before estimating the panel regression model, we have conducted a test for unit root of the variable. Table

Panel unit root test results.

Intercept and trend | ||

ADF-Fischer Chi square | Statistic | Probability |

LogIIT | 131.19 | 0.0000 |

LogHIIT | 65.31 | 0.0319 |

LogVIIT | 97.67 | 0.0000 |

LogEP | 88.60 | 0.0006 |

LogDIM | 65.63 | 0.0682 |

The most important variables such as the intraindustry trade (LogIIT), horizontal intraindustry trade (LogHIIT), vertical intraindustry trade (LogVIIT), electric power consumption (LogEP), economic dimension (LogDIM) do not have unit roots, that is, are stationary with individual effects and individual specifications.

In Figure

Distribution of intraindustry trade (IIT).

Table _{t−1}, LogDGDP, LogEP, LogDIM, and LogDIST). Our model presents consistent estimates, with no serial correlation (m2 statistics). The specification Sargan test shows that there are no problems with the validity of instruments used. As expected for the Lagged dependent variable (LogIIT_{t−1}) the result presents a positive sign, showing the changes in IIT have a significant impact on long-term effects. The difference between per capita incomes, in logs (LogDGDP), presents a positive sign. We can infer that countries have dissimilar demand. Following Falvey and Kierzkowski [

Determinants of intraindustry trade.

Variables | GMM system | Significance | Expected sign | |
---|---|---|---|---|

LogIIT_{t−1} | 0.10 | (6.25) | *** | (+) |

LogDGDP | 0.29 | (3.55) | *** | (−) |

LogEP | 0.38 | (10.49) | *** | (−) |

LogDIM | 0.21 | (3.09) | *** | (+) |

LogDIST | −1.53 | (−3.09) | *** | (−) |

C | 2.59 | (1.69) | * | |

Ar(2) | −0.69 [0.49] | |||

Sargan Test | 20.96 [1.00] | |||

Observations | 289 |

The null hypothesis that each coefficient is equal to zero is tested using one-step robust standard error.

The coefficient economic dimension (LogDIM) has a significant and a positive effect on IIT. This result confirms the importance of scale economy and product differentiation. We can conclude that economic dimension influences the volume of intraindustry trade. The geographical distance (LogDIST) has been used as a typical gravity model variable. A negative effect of the distance on bilateral IIT was expected and the results confirm this, underlining the importance of neighbour partnerships for all trade.

The Table _{t−1}) the result presents a positive sign. So we can infer that the changes in horizontal intraindustry trade have a a significant impact on the long-term effects.

Determinants of Horizontal Intraindustry Trade.

Variables | GMM system | Significance | Expected sign | |
---|---|---|---|---|

LogHIIT_{t−1} | 0.33 | (21.1) | *** | (+) |

LogDGDP | 2.06 | (2.44) | * | (−) |

LogEP | 1.09 | (3.33) | *** | (−) |

LogDIM | 2.69 | (4.19) | *** | (+) |

LogDIST | −1.92 | (−1.79) | * | (−) |

C | 3.94 | (0.90) | ||

Ar(2) | 2.09 [0.36] | |||

Sargan Test | 18.54 [1.00] | |||

Observations | 138 |

The null hypothesis that each coefficient is equal to zero is tested using one-step robust standard error.

The absolute difference in electric power consumption (LogEP) is statistically significant, with positive sign. We can conclude that countries have dissimilar factor endowment. As expected, the variable LogDIM (average of per capita GDP) between Portugal and the partner consider) has a significant and positive effect on trade. Therefore, the intensity of HIIT is positively correlated with the similarity in per capita income between trading partners. The coefficient of LogDIST (geographical distance) is negative as expected. The studies of Balassa and Bauwens [

In Figure

Distribution of horizontal intraindustry trade (HIIT).

Vertical intraindustry trade estimates are report in Table

Determinants of vertical intraindustry trade.

Variables | GMM system | Significance | Expected sign | |
---|---|---|---|---|

LogVIIT_{t−1} | 0.32 | (15.63) | *** | (+) |

LogDGDP | 0.19 | (4.18) | *** | (+) |

LogEP | 0.01 | (1.78) | * | (+) |

LogDIM | 0.55 | (5.13) | *** | (+) |

LogDIST | −0.44 | (−4.25) | *** | (−) |

C | 0.24 | (0.69) | ||

Ar(2) | 0.39 [0.70] | |||

Sargan Test | 21.14 [1.00] | |||

Observations | 267 |

The null hypothesis that each coefficient is equal to zero is tested using one-step robust standard error. ^{***/*}statistically significant at the 1 percent, 5 percent, and 10 percent levels. Ar(2) is tests for second-order serial correlation in the first-differenced residuals, asymptotically distributed as

The hypothesis for economic differences between countries (DGDP) in logs presents a positive sign and is significant at 1% level. Falvey and Kierzkowski [

In Figure

Distribution of vertical intraindustry trade (VIIT).

The coefficients electric power consumption (EP) and the economic dimension (DIM) are consistent with the expected sign

The difference in electric power consumption per capita (LEP) reflects the difference in endowments between Portugal and its trade partners. Regarding the hypothesis for the geographical distance on VIIT, the empirical result support the idea that the gravity model is important to explain vertical intraindustry trade between partners.

The objective of this paper was to analyze the main determinants of intraindustry trade in automobile sector. The IIT between Portugal and the European Union countries is over 50% for the period 1995–2008. For all of the period in analysis, the VIIT is much higher than the HIIT. These values are in accordance with the fragmentation theory.

The Lagged dependent variables (

The Linder theory considers that a difference in per capita incomes explains intraindustry trade and their components (HIIT and VIIT). The variable (LogDGDP) used to evaluate the relative factor endowments presents a positive impact on IIT, HIIT and VIIT. In fact the decision of multinational corporations is associated with different factors as in localization, skilled labour and economies of scales.

In relationship to the variable differences in physical capital endowments (LogEP), our results validate the hypothesis: VIIT occurs more frequently among countries that are dissimilar in terms of factor endowments. Our research confirms that fragmentation of production in the automobile sector is explained by the Heckscher-Ohlin. The difference in factor endowment allows showing that fragmentation is associated with vertical differentiation of products. This reveals that the decision-making of multinational corporations are based in reducing production costs; showing the importance of globalization to explain the phenomenon of fragmentation or outsourcing.

For the variable size of the market (average of GDP), the study suggests that Portugal has size to attract this type of industry. In fact, the Euro Zone countries considered in the econometric analysis show that the removal of tariff and nontariff barriers promoted the increase of intraindustry trade with special focus on the VIIT. In future studies it will be interesting to extend our sample.

According to the literature we expected a negative sign to geographical distance. Usually the literature attributes a negative sign to geographical distance, that is, trade increases if the partners are geographically close. The findings support this hypothesis, that is, the gravity model are important to explain the composition of trade (IIT, HIIT and VIIT) within partners.

The author is indebted to the anonymous referees for greatly improving is paper from the previous version.